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class="suggested-user-card__avatar social-profile-avatar-container"><a href="https://utoledo.academia.edu/CStepien"><img class="profile-avatar u-positionAbsolute" alt="Carol Stepien" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/3286365/5207919/5960280/s200_carol.stepien.jpg" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://utoledo.academia.edu/CStepien">Carol Stepien</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">The University of Toledo</p></div></div></ul></div><div class="ri-section"><div class="ri-section-header"><span>Interests</span></div><div class="ri-tags-container"><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="104999990" 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class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Roald Forsberg</h3></div><div class="js-work-strip profile--work_container" data-work-id="79570875"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570875/Introduction_of_Viral_Hemorrhagic_Septicemia_Virus_into_Freshwater_Cultured_Rainbow_Trout_Is_Followed_by_Bursts_of_Adaptive_Evolution"><img alt="Research paper thumbnail of Introduction of Viral Hemorrhagic Septicemia Virus into Freshwater Cultured Rainbow Trout Is Followed by Bursts of Adaptive Evolution" class="work-thumbnail" src="https://attachments.academia-assets.com/86240595/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570875/Introduction_of_Viral_Hemorrhagic_Septicemia_Virus_into_Freshwater_Cultured_Rainbow_Trout_Is_Followed_by_Bursts_of_Adaptive_Evolution">Introduction of Viral Hemorrhagic Septicemia Virus into Freshwater Cultured Rainbow Trout Is Followed by Bursts of Adaptive Evolution</a></div><div class="wp-workCard_item"><span>Journal of Virology</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Viral hemorrhagic septicemia virus (VHSV), a rhabdovirus infecting teleost fish, has repeatedly c...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Viral hemorrhagic septicemia virus (VHSV), a rhabdovirus infecting teleost fish, has repeatedly crossed the boundary from marine fish species to freshwater cultured rainbow trout. These naturally replicated cross-species transmission events permit the study of general and repeatable evolutionary events occurring in connection with viral emergence in a novel host species. The purpose of the present study was to investigate the adaptive molecular evolution of the VHSV glycoprotein, one of the key virus proteins involved in viral emergence, following emergence from marine species into freshwater cultured rainbow trout. A comprehensive phylogenetic reconstruction of the complete coding region of the VHSV glycoprotein was conducted, and adaptive molecular evolution was investigated using a maximum likelihood approach to compare different codon substitution models allowing for heterogeneous substitution rate ratios among amino acid sites. Evidence of positive selection was detected at six...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="890ab83e1033d64e98f201813ef2a0b8" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240595,"asset_id":79570875,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240595/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570875"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570875"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570875; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570874"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570874/Molecular_Epidemiology_of_PRRSV"><img alt="Research paper thumbnail of Molecular Epidemiology of PRRSV" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570874/Molecular_Epidemiology_of_PRRSV">Molecular Epidemiology of PRRSV</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570874"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570874"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570874; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570874]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570874,"title":"Molecular Epidemiology of PRRSV","internal_url":"https://www.academia.edu/79570874/Molecular_Epidemiology_of_PRRSV","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570873"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570873/Reversion_of_a_live_porcine_reproductive_and_respiratory_syndrome_virus_vaccine_investigated_by_parallel_mutations"><img alt="Research paper thumbnail of Reversion of a live porcine reproductive and respiratory syndrome virus vaccine investigated by parallel mutations" class="work-thumbnail" src="https://attachments.academia-assets.com/86240606/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570873/Reversion_of_a_live_porcine_reproductive_and_respiratory_syndrome_virus_vaccine_investigated_by_parallel_mutations">Reversion of a live porcine reproductive and respiratory syndrome virus vaccine investigated by parallel mutations</a></div><div class="wp-workCard_item"><span>Journal of General Virology</span><span>, 2001</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A live attenuated porcine reproductive and respiratory syndrome (PRRS) vaccine virus has been sho...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">A live attenuated porcine reproductive and respiratory syndrome (PRRS) vaccine virus has been shown to revert to virulence under field conditions. In order to identify genetic virulence determinants, ORF1 from the attenuated vaccine virus and three Danish vaccine-derived field isolates was sequenced and compared with the parental strain of the vaccine virus (VR2332). This revealed five mutations that had occurred independently in all three vaccine-derived field isolates, indicating strong parallel selective pressure on these positions in the vaccine virus when used in swine herds. Two of these parallel mutations were direct reversions to the parental VR2332 sequence and were situated in a papain-like cysteine protease domain and in the helicase domain. The remaining parallel mutations might be seen as second-site compensatory mutations for one or more of the mutations that accumulated in the vaccine virus sequence during cell-culture adaptation. Evaluation of the remaining mutations...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="be63b1f09a9524383386254bd83da8eb" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240606,"asset_id":79570873,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240606/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570873"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570873"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570873; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570873]").text(description); $(".js-view-count[data-work-id=79570873]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570873; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570873']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570872"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570872/The_Genetic_Diversity_of_European_Type_PRRSV_Is_Similar_to_That_of_the_North_American_Type_but_Is_Geographically_Skewed_within_Europe"><img alt="Research paper thumbnail of The Genetic Diversity of European Type PRRSV Is Similar to That of the North American Type but Is Geographically Skewed within Europe" class="work-thumbnail" src="https://attachments.academia-assets.com/86240601/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570872/The_Genetic_Diversity_of_European_Type_PRRSV_Is_Similar_to_That_of_the_North_American_Type_but_Is_Geographically_Skewed_within_Europe">The Genetic Diversity of European Type PRRSV Is Similar to That of the North American Type but Is Geographically Skewed within Europe</a></div><div class="wp-workCard_item"><span>Virology</span><span>, 2002</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Porcine reproductive and respiratory syndrome virus (PRRSV) is a recently emerged pathogen. Two P...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Porcine reproductive and respiratory syndrome virus (PRRSV) is a recently emerged pathogen. Two PRRSV genotypes exist, North American and European, which are only 55-70% identical at the nucleotide level. Previous studies have shown high nucleotide diversity in the North American genotype and low nucleotide diversity in the European genotype. Here, we analyzed the ORF5 and ORF7 genes for a large number of new European type PRRSV isolates in conjunction with existing database sequences. This new analysis showed that contrary to previous assumptions, genetic diversity is at least as high in the European genotype as in the North American genotype. Furthermore, we showed that genetic diversity of European type PRRSV has a marked geographical pattern, with exceptionally high genetic diversity among Italian sequences. The geographical pattern of diversity in relation to the epidemiology of PRRSV in Europe is discussed. Discrepancies between ORF5-and ORF7-based genealogies were observed, and further analysis of the data set confirmed the presence of recombination. We were therefore able to report the first observation of recombination in wild-type isolates of European genotype PRRSV.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ae5c1b3e22ee7e79e0c46b02fde6bd7c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240601,"asset_id":79570872,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240601/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570872"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570872"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570872; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570872]").text(description); $(".js-view-count[data-work-id=79570872]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570872; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570872']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ae5c1b3e22ee7e79e0c46b02fde6bd7c" } } $('.js-work-strip[data-work-id=79570872]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570872,"title":"The Genetic Diversity of European Type PRRSV Is Similar to That of the North American Type but Is Geographically Skewed within Europe","internal_url":"https://www.academia.edu/79570872/The_Genetic_Diversity_of_European_Type_PRRSV_Is_Similar_to_That_of_the_North_American_Type_but_Is_Geographically_Skewed_within_Europe","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[{"id":86240601,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/86240601/thumbnails/1.jpg","file_name":"aHR0cDovL2FwaS5lbHNldmllci5jb20vY29udGVudC9hcnRpY2xlL3BpaS9zMDA0MjY4MjIwMjkxNDUwOQ__.pdf","download_url":"https://www.academia.edu/attachments/86240601/download_file","bulk_download_file_name":"The_Genetic_Diversity_of_European_Type_P.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/86240601/aHR0cDovL2FwaS5lbHNldmllci5jb20vY29udGVudC9hcnRpY2xlL3BpaS9zMDA0MjY4MjIwMjkxNDUwOQ__-libre.pdf?1653125984=\u0026response-content-disposition=attachment%3B+filename%3DThe_Genetic_Diversity_of_European_Type_P.pdf\u0026Expires=1741326391\u0026Signature=ZTnbLclPwVqyRdgvoNZnuO0NWXh7CnuLCCDGhaP5u~9vIYboBI-FUD~uU-DQD-GCdg1lYmvtAn34eXmguvxYyjZHAzw-TaAHnoXEc6SPNC3RxjJCzuuUhRqbLXMBw8Usl7KFfXiXJd9hYj1CR5zEUIKpEO-0hxqcevc5TdXjppfpKQVcfJrnE25IWtQefhJCInmokVB4slej6~fFLHIgrS5BreK0bVB2FicjVxFKDeukQMoHYmuQXhy7oWRLPgV1gpQhlPkkKPA1IQ93C-Iiw9N8nK9NuQaCBSvHgmkoEyD82fBmAVVt-crjnGVGJpML6sWfIjPQa64YujPbj4ALEg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570871"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570871/Abstract_5332_Comparison_of_variant_calling_from_whole_exome_and_transcriptome_sequencing_using_CLC_Cancer_Research_Workbench"><img alt="Research paper thumbnail of Abstract 5332: Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570871/Abstract_5332_Comparison_of_variant_calling_from_whole_exome_and_transcriptome_sequencing_using_CLC_Cancer_Research_Workbench">Abstract 5332: Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The now commonplace application of whole exome and genome sequencing in cancer research and diagn...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The now commonplace application of whole exome and genome sequencing in cancer research and diagnostics has allowed for rapid identification of SNPs and InDels in protein coding regions, but neither method is able to reveal situations of incomplete penetrance. That is, while possible cancer causing allele variants can be detected with these methods, this does not mean these alleles are actually expressed. Reasons for this are various and include epigenetic effects and changes, transcription regulation mechanisms, mRNA degradation and epistasis. By contrast, transcriptome sequencing (RNA-seq) can be used to identify the alleles being expressed. This method has the additional benefits of providing insight into the transcript expression levels, expressed allele isoforms and offers the possibility of identifying instances of fusion transcripts. Such knowledge about variants expressed in tumor cells is crucial for the identification of effective drug targets. Here, we illustrate the benefits of combining whole exome sequencing with RNA-seq by analyzing whole exome and RNA-seq datasets from uveal melanoma samples with our newly developed CLC Cancer Research Workbench. This software suite enables the complete analysis of both approaches, including variant calling, followed by the comparison of the called variants. The analysis will be carried out using user-friendly, automated workflows distributed with the CLC Cancer Research Workbench. In this work, we discuss and compare variants identified in the exome and RNA-seq datasets using our algorithms, and focus particularly on variants identified in the exome data that appear not to be expressed in the tumor samples. Citation Format: Anne Arens, Anne-Mette K. Hein, Uwe Appelt, Anika Joecker, Soren Monsted, Bjarne Knudsen, Naomi Thomson, Richard Lussier, Cecilie Boysen, Roald Forsberg. Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5332. doi:10.1158/1538-7445.AM2014-5332</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570871"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570871"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570871; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570871]").text(description); $(".js-view-count[data-work-id=79570871]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570871; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570871']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570871]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570871,"title":"Abstract 5332: Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench","internal_url":"https://www.academia.edu/79570871/Abstract_5332_Comparison_of_variant_calling_from_whole_exome_and_transcriptome_sequencing_using_CLC_Cancer_Research_Workbench","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570870"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570870/Abstract_4181_Accurate_and_fast_detection_and_comparison_of_larger_clinically_relevant_insertions_and_deletions"><img alt="Research paper thumbnail of Abstract 4181: Accurate and fast detection and comparison of larger clinically relevant insertions and deletions" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570870/Abstract_4181_Accurate_and_fast_detection_and_comparison_of_larger_clinically_relevant_insertions_and_deletions">Abstract 4181: Accurate and fast detection and comparison of larger clinically relevant insertions and deletions</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Larger somatic insertions and deletions in tumor samples are often of significant clinical impact...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Larger somatic insertions and deletions in tumor samples are often of significant clinical impact. Many of them are cancer driver mutations and play an important role in drug treatment1. Detecting the accurate breakpoints of larger insertions and deletions is often problematic and inaccurate. Furthermore, due to ambiguous positioning of them in the human genome, they are hard to compare with known deletions and insertions in publicly available databases. Here we present a complete analysis workflow to accurate identify, filter and annotate larger insertions and deletions with information from publicly available databases such as COSMIC. We apply our pipeline on publicly available tumor/normal matched pair data from a patient with Massive Acinic Cell Carcinoma (A. Nichols et al. (2013) Case Reports in Oncological Medicine, Article ID 270362), which has not been investigated for larger insertions and deletions before. We show that we can identify insertions and deletions, which should be reported as part of the list of somatic variants, the authors have presented. Moreover, we will point out potential challenges and how to solve them while comparing own results to data in databases. Citation Format: Anne-Mette K. Hein, Patrick Dekker, Anika Joecker, Cecilie Boysen, Naomi Thomson, Bodil Oester, Anne Arens, Bjarne Knudsen, Thomas Knudsen, Roald Forsberg. Accurate and fast detection and comparison of larger clinically relevant insertions and deletions. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4181. doi:10.1158/1538-7445.AM2014-4181</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570870"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570870"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570870; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570870]").text(description); $(".js-view-count[data-work-id=79570870]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570870; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570870']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570870]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570870,"title":"Abstract 4181: Accurate and fast detection and comparison of larger clinically relevant insertions and deletions","internal_url":"https://www.academia.edu/79570870/Abstract_4181_Accurate_and_fast_detection_and_comparison_of_larger_clinically_relevant_insertions_and_deletions","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570869"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570869/Abstract_2334_Identification_of_differentially_expressed_genes_and_somatic_mutations_in_esophageal_adenocarinoma_cancer_patients"><img alt="Research paper thumbnail of Abstract 2334: Identification of differentially expressed genes and somatic mutations in esophageal adenocarinoma cancer patients" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570869/Abstract_2334_Identification_of_differentially_expressed_genes_and_somatic_mutations_in_esophageal_adenocarinoma_cancer_patients">Abstract 2334: Identification of differentially expressed genes and somatic mutations in esophageal adenocarinoma cancer patients</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">High throughput sequencing technologies are currently revolutionizing the cancer research area wi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">High throughput sequencing technologies are currently revolutionizing the cancer research area with rapid improvements in sequencing capacity and time consumption. As a result the most time consuming step has moved from being the sequencing process itself to being the bioinformatic data analysis. RNA sequencing (RNA-Seq) is used in an increasing number of transcriptomic studies. The great advantage of using RNA-Seq is its ability to precisely quantify transcript levels and identify novel transcripts, isoforms, and splice junctions, while further providing information of the mutational landscape down to single base resolution. To ease the hurdles associated with RNA-Seq data analysis there is an increasing demand for tools that are specifically tailored to RNA-Seq data. Here we describe how the newly developed CLC Cancer Research Workbench can be used to analyze and visualize RNA-Seq data with ready-to-use workflows that automatically map, quantify, and annotate transcriptomes. We identify differentially expressed genes and transcripts in Illumina HiSeq transcriptomic data from matched tumor and normal samples from four esophageal adenocarinoma cancer patients, and compare the mutational patterns in the samples with the expression values of the corresponding genes. Results are visualized in a track based genome browser view, which provides the means for quick and easy navigation as well as allowing the user to simultaneously view and annotate multiple samples and different data types (e.g. genes, transcript expression levels, and detected variants). Citation Format: Bodil Oster, Anika Joecker, Anne-Mette K. Hein, Patrick Dekker, Robert O9Neill, Adam Krejci, Anne Arens, Naomi Thomson, Cecilie Boysen, Soren Monsted, Roald Forsberg, Bjarne Knudsen, Thomas Knudsen, Richard Lussier, Ted R. Hupp. Identification of differentially expressed genes and somatic mutations in esophageal adenocarinoma cancer patients. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2334. doi:10.1158/1538-7445.AM2014-2334</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570869"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570869"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570869; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570869]").text(description); $(".js-view-count[data-work-id=79570869]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570869; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570869']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570869]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570869,"title":"Abstract 2334: Identification of differentially expressed genes and somatic mutations in esophageal adenocarinoma cancer patients","internal_url":"https://www.academia.edu/79570869/Abstract_2334_Identification_of_differentially_expressed_genes_and_somatic_mutations_in_esophageal_adenocarinoma_cancer_patients","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570868"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570868/Abstract_2227_An_automatic_pipeline_to_find_and_annotate_rare_subclonal_somatic_variants_in_a_paired_tumor_normal_sample"><img alt="Research paper thumbnail of Abstract 2227: An automatic pipeline to find and annotate rare subclonal somatic variants in a paired tumor/normal sample" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570868/Abstract_2227_An_automatic_pipeline_to_find_and_annotate_rare_subclonal_somatic_variants_in_a_paired_tumor_normal_sample">Abstract 2227: An automatic pipeline to find and annotate rare subclonal somatic variants in a paired tumor/normal sample</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Identifying and characterizing somatic variants in deep genome sequence data from tumor samples r...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Identifying and characterizing somatic variants in deep genome sequence data from tumor samples remains challenging and time-consuming. Of special interest in cancer research and diagnostics is the detection and annotation of rare subclonal somatic variants found only in a small proportion of primary tumor cells. Such variants can drive tumor spread and recurrence, but are often neglected in choosing treatments. Currently, few tools reliably distinguish such rare subclonal variants from sequencing errors. And even among real somatic variants, drivers (of tumor growth, spread, or resistance) are hard to distinguish from passengers. Doing so entails integrating diverse information on variants, genes, pathways, cancer-relevant phenotypes, and treatments (including insights on population allele frequencies and broader evolutionary conservation; known/likely effects on gene product structure, function, expression, and interaction; and relations among gene products, phenotypes, and drugs). Software for effectively integrating such data in light of genomic variation in samples, to highlight relevant findings through clear visualization, has been a pressing need. Here we present an end-to-end analysis workflow for finding and functionally characterizing rare subclonal variants, using the newly developed CLC Cancer Research Workbench to feed the interpretive platform of Ingenuity Variant Analysis, to identify cancer driver mutations in paired tumor/normal samples. We will show new interesting results from this analysis, which were not shown beforehand on this publicly available cancer dataset (Case Reports in Oncological Medicine, Volume 2013 (2013), Article ID 270362) from a patient with massive acinic cell carcinoma. Citation Format: Anika Joecker, Nathan Pearson, Cecilie Boysen, Naomi Thomson, Anne-Mette Hein, Bodil Oster, Anne Arens, Bjarne Knudsen, Thomas Knudsen, Dan Richards, Roald Forsberg. An automatic pipeline to find and annotate rare subclonal somatic variants in a paired tumor/normal sample. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2227. doi:10.1158/1538-7445.AM2014-2227</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570868"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570868"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570868; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570868]").text(description); $(".js-view-count[data-work-id=79570868]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570868; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570868']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570868]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570868,"title":"Abstract 2227: An automatic pipeline to find and annotate rare subclonal somatic variants in a paired tumor/normal sample","internal_url":"https://www.academia.edu/79570868/Abstract_2227_An_automatic_pipeline_to_find_and_annotate_rare_subclonal_somatic_variants_in_a_paired_tumor_normal_sample","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570867"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570867/CLC_Bio_Integrated_Platform_for_Handling_and_Analysis_of_Tag_Sequencing_Data"><img alt="Research paper thumbnail of CLC Bio Integrated Platform for Handling and Analysis of Tag Sequencing Data" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570867/CLC_Bio_Integrated_Platform_for_Handling_and_Analysis_of_Tag_Sequencing_Data">CLC Bio Integrated Platform for Handling and Analysis of Tag Sequencing Data</a></div><div class="wp-workCard_item"><span>KAHL:TAG BASED SEQUENCING O-BK</span><span>, 2012</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570867"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570867"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570867; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570867]").text(description); $(".js-view-count[data-work-id=79570867]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570867; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570867']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570867]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570867,"title":"CLC Bio Integrated Platform for Handling and Analysis of Tag Sequencing Data","internal_url":"https://www.academia.edu/79570867/CLC_Bio_Integrated_Platform_for_Handling_and_Analysis_of_Tag_Sequencing_Data","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570866"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570866/A_computer_simulator_for_assessing_different_challenges_and_strategies_of_de_novo_sequence_assembly"><img alt="Research paper thumbnail of A computer simulator for assessing different challenges and strategies of de novo sequence assembly" class="work-thumbnail" src="https://attachments.academia-assets.com/86240593/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570866/A_computer_simulator_for_assessing_different_challenges_and_strategies_of_de_novo_sequence_assembly">A computer simulator for assessing different challenges and strategies of de novo sequence assembly</a></div><div class="wp-workCard_item"><span>Genes</span><span>, 2010</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This study presents a new computer program for assessing the effects of different factors and seq...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This study presents a new computer program for assessing the effects of different factors and sequencing strategies on de novo sequence assembly. The program uses reads from actual sequencing studies or from simulations with a reference genome that may also be real or simulated. The simulated reads can be created with our read simulator. They can be of differing length and coverage, consist of paired reads with varying distance, and include sequencing errors such as color space miscalls to imitate SOLiD data. The simulated or real reads are mapped to their reference genome and our assembly simulator is then used to obtain optimal assemblies that are limited only by the distribution of repeats. By way of this mapping, the assembly simulator determines which contigs are theoretically possible, or conversely (and perhaps more importantly), which are not. We illustrate the application and utility of our new simulation tools with several experiments that test the effects of genome comple...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5085d8515f7d7cbedd8744b3c3dc855b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240593,"asset_id":79570866,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240593/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570866"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570866"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570866; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570865"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570865/Using_NGS_Data_to_Facilitate_Plant_Breeding"><img alt="Research paper thumbnail of Using NGS Data to Facilitate Plant Breeding" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570865/Using_NGS_Data_to_Facilitate_Plant_Breeding">Using NGS Data to Facilitate Plant Breeding</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We are developing a platform withing the CLC suite to optimise bulk segregant analysis on the pop...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We are developing a platform withing the CLC suite to optimise bulk segregant analysis on the population of plants derived from all possible pairwise crosses of a small number of elite parental lines. Parental DNA, as well as pooled progeny DNA from the individuals having extreme values of a trait of interest, has been sequenced. Implemented outcomes would be facilitation of genome-wide selection, assignment of &#39;breeding values&#39; to elite parents, and identification of individual markers/genes affecting the trait.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570865"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570865"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570865; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570865]").text(description); $(".js-view-count[data-work-id=79570865]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570865; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570865']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570865]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570865,"title":"Using NGS Data to Facilitate Plant Breeding","internal_url":"https://www.academia.edu/79570865/Using_NGS_Data_to_Facilitate_Plant_Breeding","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570864"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570864/A_Molecular_Clock_Dates_the_Common_Ancestor_of_European_type_Porcine_Reproductive_and_Respiratory_Syndrome_Virus_at_More_Than_10_Years_before_the_Emergence_of_Disease"><img alt="Research paper thumbnail of A Molecular Clock Dates the Common Ancestor of European-type Porcine Reproductive and Respiratory Syndrome Virus at More Than 10 Years before the Emergence of Disease" class="work-thumbnail" src="https://attachments.academia-assets.com/86240598/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570864/A_Molecular_Clock_Dates_the_Common_Ancestor_of_European_type_Porcine_Reproductive_and_Respiratory_Syndrome_Virus_at_More_Than_10_Years_before_the_Emergence_of_Disease">A Molecular Clock Dates the Common Ancestor of European-type Porcine Reproductive and Respiratory Syndrome Virus at More Than 10 Years before the Emergence of Disease</a></div><div class="wp-workCard_item"><span>Virology</span><span>, 2001</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The disease caused by porcine reproductive and respiratory syndrome virus (PRRSV) emerged indepen...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The disease caused by porcine reproductive and respiratory syndrome virus (PRRSV) emerged independently and almost simultaneously in Europe (1990) and North America (1987). The original reservoir of the virus and the date it entered the pig populations is not known. In this study, we demonstrate an accurate molecular clock for the European PRRSV ORF 3 gene, place the root in the genealogy, estimate the rate of nucleotide substitution, and date the most recent common viral ancestor of the data set to 1979; more than 10 years before the onset of the European epidemic. Based on these findings, we conclude that PRRSV virus most likely entered the pig population some time before the epidemic emergence of the virus, and hence, that emergence of European-type PRRSV is not the result of a recent species transmission event. Together, our results show that ORF3 sequencing is a valuable epidemiologic tool for examining the emergence and spread of PRRSV in Europe. As such, the panel of well-characterized and highly divergent ORF3 sequences described in this study provides a reference point for future molecular epidemiologic studies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f34f95c1d6f1ba8c367158860eb4a414" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240598,"asset_id":79570864,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240598/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570864"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570864"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570864; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570864]").text(description); $(".js-view-count[data-work-id=79570864]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570864; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570864']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570863"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570863/Measurably_evolving_populations"><img alt="Research paper thumbnail of Measurably evolving populations" class="work-thumbnail" src="https://attachments.academia-assets.com/86240600/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570863/Measurably_evolving_populations">Measurably evolving populations</a></div><div class="wp-workCard_item"><span>Trends in Ecology &amp; Evolution</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The availability of nucleotide and amino acid sequences sampled at different points in time has f...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The availability of nucleotide and amino acid sequences sampled at different points in time has fostered the development of new statistical methods that exploit this temporal dimension. Such sequences enable us to observe evolution in action and to estimate the rate and magnitude of evolutionary processes through time. Populations for which such studies are possiblemeasurably evolving populations (MEPs)-are characterized by sufficiently long or numerous sampled sequences and a fast mutation rate relative to the available range of sequence sampling times. The impact of sequences sampled through time has been most apparent in the disciplines of RNA viral evolution and ancient DNA, where they enable us to estimate divergence times without paleontological calibrations, and to analyze temporal changes in population size, population structure and substitution rates. Thus, MEPs could increase our understanding of evolutionary processes in diverse organisms, from viruses to vertebrates.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4ca6c2cec4bc3659dbc90d1f15a22893" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240600,"asset_id":79570863,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240600/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570863"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570863"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570863; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570863]").text(description); $(".js-view-count[data-work-id=79570863]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570863; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570863']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570862"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570862/A_comparative_method_for_finding_and_folding_RNA_secondary_structures_within_protein_coding_regions"><img alt="Research paper thumbnail of A comparative method for finding and folding RNA secondary structures within protein-coding regions" class="work-thumbnail" src="https://attachments.academia-assets.com/86240608/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570862/A_comparative_method_for_finding_and_folding_RNA_secondary_structures_within_protein_coding_regions">A comparative method for finding and folding RNA secondary structures within protein-coding regions</a></div><div class="wp-workCard_item"><span>Nucleic Acids Research</span><span>, 2004</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Existing computational methods for RNA secondarystructure prediction tacitly assume RNA to only e...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Existing computational methods for RNA secondarystructure prediction tacitly assume RNA to only encode functional RNA structures. However, experimental studies have revealed that some RNA sequences, e.g. compact viral genomes, can simultaneously encode functional RNA structures as well as proteins, and evidence is accumulating that this phenomenon may also be found in Eukaryotes. We here present the first comparative method, called RNA-DECODER, which explicitly takes the known proteincoding context of an RNA-sequence alignment into account in order to predict evolutionarily conserved secondary-structure elements, which may span both coding and non-coding regions. RNA-DECODER employs a stochastic context-free grammar together with a set of carefully devised phylogenetic substitution-models, which can disentangle and evaluate the different kinds of overlapping evolutionary constraints which arise. We show that RNA-DECODER's parameters can be automatically trained to successfully fold known secondary structures within the HCV genome. We scan the genomes of HCV and polio virus for conserved secondary-structure elements, and analyze performance as a function of available evolutionary information. On known secondary structures, RNA-DECODER shows a sensitivity similar to the programs MFOLD, PFOLD and RNAALIFOLD. When scanning the entire genomes of HCV and polio virus for structure elements, RNA-DECODER's results indicate a markedly higher specificity than MFOLD, PFOLD and RNAALIFOLD.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ee219c1650ff9c7d314602f69acc932f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240608,"asset_id":79570862,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240608/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570862"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570862"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570862; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570862]").text(description); $(".js-view-count[data-work-id=79570862]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570862; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570862']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ee219c1650ff9c7d314602f69acc932f" } } $('.js-work-strip[data-work-id=79570862]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570862,"title":"A comparative method for finding and folding RNA secondary structures within protein-coding regions","internal_url":"https://www.academia.edu/79570862/A_comparative_method_for_finding_and_folding_RNA_secondary_structures_within_protein_coding_regions","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[{"id":86240608,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/86240608/thumbnails/1.jpg","file_name":"4925.pdf","download_url":"https://www.academia.edu/attachments/86240608/download_file","bulk_download_file_name":"A_comparative_method_for_finding_and_fol.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/86240608/4925-libre.pdf?1653125989=\u0026response-content-disposition=attachment%3B+filename%3DA_comparative_method_for_finding_and_fol.pdf\u0026Expires=1741326391\u0026Signature=SIo4j-0VNO7oD~wmieVEGjk0kt9folBxsusJA-LDgeiQYNnS3W8zKHH6DtFiXn49WnE~SQexyRjcTfy~wy1aWI3bj7RWL78u8u~fsZestf2P6so62nLQQVEXfYyTOBuKGKhvm5N7yorr4kZLrN7zuycw5qMg7xjiBTHDA4RCYNQk~7f9rDpR~7maBtDGiYv5UmgWu4Nqsxy-eOcr1OYP6vosQKAXtbMDS6G86LPmsLDSWjlflC7BjwhYfm9GClb8~XTC6h8-bRqXZuyVhYyPo4LSRx-0GNjuVU97ezEdPjsNiXtk1cdl8lexBSMEeuVBB9LHndHM3SIx3DrShqAF7Q__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570861"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570861/Divergence_Time_of_Porcine_Reproductive_and_Respiratory_Syndrome_Virus_Subtypes"><img alt="Research paper thumbnail of Divergence Time of Porcine Reproductive and Respiratory Syndrome Virus Subtypes" class="work-thumbnail" src="https://attachments.academia-assets.com/86240596/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570861/Divergence_Time_of_Porcine_Reproductive_and_Respiratory_Syndrome_Virus_Subtypes">Divergence Time of Porcine Reproductive and Respiratory Syndrome Virus Subtypes</a></div><div class="wp-workCard_item"><span>Molecular Biology and Evolution</span><span>, 2005</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Porcine reproductive and respiratory syndrome virus (PRRSV) recently emerged in domestic pigs of ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Porcine reproductive and respiratory syndrome virus (PRRSV) recently emerged in domestic pigs of Western Europe and North America. Although time of emergence was identical on the two continents, genetic composition was markedly different with a clear geographical subtype structure, indicating that subtypes diverged in separate reservoirs prior to emergence. Genetic analyses have shown that the most recent common ancestor (MRCA) of Western European isolates existed around 1980 and that these originate from Eastern European pigs. These findings are challenged by a study of Hanada et al. who place the MRCA of all PRRSV isolates around 1980 and find that no significant subtype divergence occurred before emergence. Here, I discuss problems of information content, methodology, and biological plausibility associated with this study. Using alternative methodology, I reanalyze the existing data and conclude that the MRCA of all PRRSV isolates existed around 1880, 100 years before the date estimated by Hanada et al.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d6fc7b222034f06eb9f0331a628522ef" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240596,"asset_id":79570861,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240596/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570861"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570861"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570861; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570861]").text(description); $(".js-view-count[data-work-id=79570861]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570861; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570861']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "d6fc7b222034f06eb9f0331a628522ef" } } $('.js-work-strip[data-work-id=79570861]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570861,"title":"Divergence Time of Porcine Reproductive and Respiratory Syndrome Virus Subtypes","internal_url":"https://www.academia.edu/79570861/Divergence_Time_of_Porcine_Reproductive_and_Respiratory_Syndrome_Virus_Subtypes","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[{"id":86240596,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/86240596/thumbnails/1.jpg","file_name":"msi208.pdf","download_url":"https://www.academia.edu/attachments/86240596/download_file","bulk_download_file_name":"Divergence_Time_of_Porcine_Reproductive.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/86240596/msi208-libre.pdf?1653125988=\u0026response-content-disposition=attachment%3B+filename%3DDivergence_Time_of_Porcine_Reproductive.pdf\u0026Expires=1741326391\u0026Signature=QWs96pwI15HRIdyFtv65zC8jr8Htw2eZ65PlcxLI01UzaIljtMcyf5eW7bLdcr9-lPgwuzfYDgSeAqFVUvXuUMQJ0mMhl0cq3yn~p4oOiN3yMvlY8emZERG0tBZ93FM3fe8V5Yy-apyXcTEFNiI332RtpsHF7IgO9s8RKvIAmMpvrAatwLuFWffTfWv69NAz-jnsyIMna70MEuToI7N7Ujigd6L3jfkv179fPMUH5ALt-~CJSdYxlR3WKFoU~bnYeneLDyaJwnqb9l7-A1FpG~ngdYNCfahH5bQvWwlEtAbTVN2I-3hk1Hd0pz3LWdqrq31wh~kDQA--yy7JpRgiRw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570860"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570860/A_Codon_Based_Model_of_Host_Specific_Selection_in_Parasites_with_an_Application_to_the_Influenza_A_Virus"><img alt="Research paper thumbnail of A Codon-Based Model of Host-Specific Selection in Parasites, with an Application to the Influenza A Virus" class="work-thumbnail" src="https://attachments.academia-assets.com/86240604/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570860/A_Codon_Based_Model_of_Host_Specific_Selection_in_Parasites_with_an_Application_to_the_Influenza_A_Virus">A Codon-Based Model of Host-Specific Selection in Parasites, with an Application to the Influenza A Virus</a></div><div class="wp-workCard_item"><span>Molecular Biology and Evolution</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Parasites sometimes expand their host range by acquiring a new host species. After a host change ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Parasites sometimes expand their host range by acquiring a new host species. After a host change event, the selective regime acting on a given parasite gene may change as a result of host-specific adaptive alterations of protein functionality or host-specific immune-mediated selection. We present a codon-based model that attempts to include these effects by allowing the position-specific substitution process to change in conjunction with a host change event. Following maximum-likelihood parameter estimation, we employ an empirical Bayesian procedure to identify candidate sites potentially involved in host-specific adaptation. We discuss the applicability of the model to the more general problem of ascertaining whether the selective regime differs in two groups of related organisms. The utility of the model is illustrated on a data set of nucleoprotein sequences from the influenza A virus obtained from avian and human hosts.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="1a1ea157b049f5fff70c46066ba6eff0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240604,"asset_id":79570860,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240604/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570860"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570860"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570860; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570859"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570859/An_Evolutionary_Model_for_Protein_Coding_Regions_with_Conserved_RNA_Structure"><img alt="Research paper thumbnail of An Evolutionary Model for Protein-Coding Regions with Conserved RNA Structure" class="work-thumbnail" src="https://attachments.academia-assets.com/86240612/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570859/An_Evolutionary_Model_for_Protein_Coding_Regions_with_Conserved_RNA_Structure">An Evolutionary Model for Protein-Coding Regions with Conserved RNA Structure</a></div><div class="wp-workCard_item"><span>Molecular Biology and Evolution</span><span>, 2004</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Here we present a model of nucleotide substitution in protein-coding regions that also encode the...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Here we present a model of nucleotide substitution in protein-coding regions that also encode the formation of conserved RNA structures. In such regions, apparent evolutionary context dependencies exist, both between nucleotides occupying the same codon and between nucleotides forming a base pair in the RNA structure. The overlap of these fundamental dependencies is sufficient to cause ''contagious'' context dependencies which cascade across many nucleotide sites. Such large-scale dependencies challenge the use of traditional phylogenetic models in evolutionary inference because they explicitly assume evolutionary independence between short nucleotide tuples. In our model we address this by replacing context dependencies within codons by annotation-specific heterogeneity in the substitution process. Through a general procedure, we fragment the alignment into sets of short nucleotide tuples based on both the protein coding and the structural annotation. These individual tuples are assumed to evolve independently, and the different tuple sets are assigned different annotation-specific substitution models shared between their members. This allows us to build a composite model of the substitution process from components of traditional phylogenetic models. We applied this to a data set of full-genome sequences from the hepatitis C virus where five RNA structures are mapped within the coding region. This allowed us to partition the effects of selection on different structural elements and to test various hypotheses concerning the relation of these effects. Of particular interest, we found evidence of a functional role of loop and bulge regions, as these were shown to evolve according to a different and more constrained selective regime than the nonpairing regions outside the RNA structures. Other potential applications of the model include comparative RNA structure prediction in coding regions and RNA virus phylogenetics.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="3026342e7e9b208e85f6c6b92a042908" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240612,"asset_id":79570859,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240612/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570859"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570859"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570859; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570859]").text(description); $(".js-view-count[data-work-id=79570859]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570859; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570859']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570858"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570858/Inferring_Evolutionary_Rates_Using_Serially_Sampled_Sequences_from_Several_Populations"><img alt="Research paper thumbnail of Inferring Evolutionary Rates Using Serially Sampled Sequences from Several Populations" class="work-thumbnail" src="https://attachments.academia-assets.com/86240597/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570858/Inferring_Evolutionary_Rates_Using_Serially_Sampled_Sequences_from_Several_Populations">Inferring Evolutionary Rates Using Serially Sampled Sequences from Several Populations</a></div><div class="wp-workCard_item"><span>Molecular Biology and Evolution</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The estimation of evolutionary rates from serially sampled sequences has recently been the focus ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The estimation of evolutionary rates from serially sampled sequences has recently been the focus of several studies. In this paper, we extend these analyzes to allow the estimation of a joint rate of substitution, x, from several evolving populations from which serial samples are drawn. In the case of viruses evolving in different hosts, therapy may halt replication and therefore the accumulation of substitutions in the population. In such cases, it may be that only a proportion, p, of subjects are nonresponders who have viral populations that continue to evolve. We develop two likelihood-based procedures to jointly estimate p and x, and empirical Bayes' tests of whether an individual should be classified as a responder or nonresponder. An example data set comprising HIV-1 partial envelope sequences from six patients on highly active antiretroviral therapy is analyzed.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="6832f77389f07e42d05120487956c147" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240597,"asset_id":79570858,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240597/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570858"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570858"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570858; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570858]").text(description); $(".js-view-count[data-work-id=79570858]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570858; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570858']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "6832f77389f07e42d05120487956c147" } } $('.js-work-strip[data-work-id=79570858]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570858,"title":"Inferring Evolutionary Rates Using Serially Sampled Sequences from Several Populations","internal_url":"https://www.academia.edu/79570858/Inferring_Evolutionary_Rates_Using_Serially_Sampled_Sequences_from_Several_Populations","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[{"id":86240597,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/86240597/thumbnails/1.jpg","file_name":"2010.pdf","download_url":"https://www.academia.edu/attachments/86240597/download_file","bulk_download_file_name":"Inferring_Evolutionary_Rates_Using_Seria.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/86240597/2010-libre.pdf?1653125989=\u0026response-content-disposition=attachment%3B+filename%3DInferring_Evolutionary_Rates_Using_Seria.pdf\u0026Expires=1741326391\u0026Signature=OrtTB8AkEMUnXL-8JCDrSjyjMbb3BIku7-bH611bQi9amkY4wW-a29~dtc8gOaMm-cC7nj2KUjqSjloKzyTWYn0Mib~I~oRIVE0rvzfx5sZE5UNHkxNDiAJ9lzNVN4ea8oOgLf8JygutAPiXnaggNSPqJxtnzZPRTKKonXIzwUd9yZanP5KKOcwy9~r30iGlAIxJ6KMeTrPMNHl~qN~vHE0bWhcwzZlg0pTH-HpIBsSml9pb~yU26SBlSxCAayDRpkKovzosuUzaIXThKqs35NeJ5JcGEpfIW2neKkyaebX6OjKGd8EkGpZcqJDKBANsmGUfECi4RDUZMOE5rr4QEw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570857"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570857/The_Inference_of_Stepwise_Changes_in_Substitution_Rates_Using_Serial_Sequence_Samples"><img alt="Research paper thumbnail of The Inference of Stepwise Changes in Substitution Rates Using Serial Sequence Samples" class="work-thumbnail" src="https://attachments.academia-assets.com/86240599/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570857/The_Inference_of_Stepwise_Changes_in_Substitution_Rates_Using_Serial_Sequence_Samples">The Inference of Stepwise Changes in Substitution Rates Using Serial Sequence Samples</a></div><div class="wp-workCard_item"><span>Molecular Biology and Evolution</span><span>, 2001</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">It is frequently true that molecular sequences do not evolve in a strictly clocklike manner. Inst...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">It is frequently true that molecular sequences do not evolve in a strictly clocklike manner. Instead, substitution rate may vary for a number of reasons, including changes in selection pressure and effective population size, as well as changes in mean generation time. Here we present two new methods for estimating stepwise changes in substitution rates when serially sampled molecular sequences are available. These methods are based on multiple rates with dated tips (MRDT) models and allow different rates to be estimated for different intervals of time. These intervals may correspond to the sampling intervals or to a priori-defined intervals that are not coincident with the times the serial samples are obtained. Two methods for obtaining estimates of multiple rates are described. The first is an extension of the phylogeny-based maximum-likelihood estimation procedure introduced by Rambaut. The second is a new parameterization of the pairwise distance least-squares procedure used by Drummond and Rodrigo. The utility of these methods is demonstrated on a genealogy of HIV sequences obtained at five different sampling times from a single patient over a period of 34 months. Recently, two papers have independently described methods to estimate substitution rate, , from serial samples under the assumption of a molecular clock. Rambaut (2000) shows how a phylogeny-based maximum-likelihood estimate (MLE) of the constant substitution rate, , expressing the divergence between dated</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d864ddc6c2d8ad8b45d97e34b314bd44" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240599,"asset_id":79570857,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240599/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570857"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570857"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570857; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570856"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570856/Evolution_of_the_fish_rhabdovirus_viral_haemorrhagic_septicaemia_virus"><img alt="Research paper thumbnail of Evolution of the fish rhabdovirus viral haemorrhagic septicaemia virus" class="work-thumbnail" src="https://attachments.academia-assets.com/86240589/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570856/Evolution_of_the_fish_rhabdovirus_viral_haemorrhagic_septicaemia_virus">Evolution of the fish rhabdovirus viral haemorrhagic septicaemia virus</a></div><div class="wp-workCard_item"><span>Journal of General Virology</span><span>, 2004</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Viral haemorrhagic septicaemia (VHS) caused by the rhabdovirus VHSV is economically the most impo...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Viral haemorrhagic septicaemia (VHS) caused by the rhabdovirus VHSV is economically the most important viral disease in European rainbow trout farming. Until 1989, this virus was mainly isolated from freshwater salmonids but in the last decade, it has also been isolated from an increasing number of free-living marine fish species. To study the genetic evolution of VHSV, the entire G gene from 74 isolates was analysed. VHSV from wild marine species caught in the Baltic Sea, Skagerrak, Kattegat, North Sea, and English Channel and European freshwater isolates, appeared to share a recent common ancestor. Based on the estimated nucleotide substitution rate, the ancestor of the European fresh water isolates was dated some 50 years ago. This finding fits with the initial reports in the 1950s on clinical observations of VHS in Danish freshwater rainbow trout farms. The study also indicates that European marine VHSV and the North American marine line separated approx. 500 years ago. The codo...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="63664b746296aa414467991a0a9463bc" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240589,"asset_id":79570856,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240589/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570856"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570856"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570856; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="14967049" id="papers"><div class="js-work-strip profile--work_container" data-work-id="79570875"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570875/Introduction_of_Viral_Hemorrhagic_Septicemia_Virus_into_Freshwater_Cultured_Rainbow_Trout_Is_Followed_by_Bursts_of_Adaptive_Evolution"><img alt="Research paper thumbnail of Introduction of Viral Hemorrhagic Septicemia Virus into Freshwater Cultured Rainbow Trout Is Followed by Bursts of Adaptive Evolution" class="work-thumbnail" src="https://attachments.academia-assets.com/86240595/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570875/Introduction_of_Viral_Hemorrhagic_Septicemia_Virus_into_Freshwater_Cultured_Rainbow_Trout_Is_Followed_by_Bursts_of_Adaptive_Evolution">Introduction of Viral Hemorrhagic Septicemia Virus into Freshwater Cultured Rainbow Trout Is Followed by Bursts of Adaptive Evolution</a></div><div class="wp-workCard_item"><span>Journal of Virology</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Viral hemorrhagic septicemia virus (VHSV), a rhabdovirus infecting teleost fish, has repeatedly c...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Viral hemorrhagic septicemia virus (VHSV), a rhabdovirus infecting teleost fish, has repeatedly crossed the boundary from marine fish species to freshwater cultured rainbow trout. These naturally replicated cross-species transmission events permit the study of general and repeatable evolutionary events occurring in connection with viral emergence in a novel host species. The purpose of the present study was to investigate the adaptive molecular evolution of the VHSV glycoprotein, one of the key virus proteins involved in viral emergence, following emergence from marine species into freshwater cultured rainbow trout. A comprehensive phylogenetic reconstruction of the complete coding region of the VHSV glycoprotein was conducted, and adaptive molecular evolution was investigated using a maximum likelihood approach to compare different codon substitution models allowing for heterogeneous substitution rate ratios among amino acid sites. Evidence of positive selection was detected at six...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="890ab83e1033d64e98f201813ef2a0b8" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240595,"asset_id":79570875,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240595/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570875"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570875"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570875; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570874"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570874/Molecular_Epidemiology_of_PRRSV"><img alt="Research paper thumbnail of Molecular Epidemiology of PRRSV" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570874/Molecular_Epidemiology_of_PRRSV">Molecular Epidemiology of PRRSV</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570874"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570874"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570874; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570874]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570874,"title":"Molecular Epidemiology of PRRSV","internal_url":"https://www.academia.edu/79570874/Molecular_Epidemiology_of_PRRSV","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570873"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570873/Reversion_of_a_live_porcine_reproductive_and_respiratory_syndrome_virus_vaccine_investigated_by_parallel_mutations"><img alt="Research paper thumbnail of Reversion of a live porcine reproductive and respiratory syndrome virus vaccine investigated by parallel mutations" class="work-thumbnail" src="https://attachments.academia-assets.com/86240606/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570873/Reversion_of_a_live_porcine_reproductive_and_respiratory_syndrome_virus_vaccine_investigated_by_parallel_mutations">Reversion of a live porcine reproductive and respiratory syndrome virus vaccine investigated by parallel mutations</a></div><div class="wp-workCard_item"><span>Journal of General Virology</span><span>, 2001</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A live attenuated porcine reproductive and respiratory syndrome (PRRS) vaccine virus has been sho...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">A live attenuated porcine reproductive and respiratory syndrome (PRRS) vaccine virus has been shown to revert to virulence under field conditions. In order to identify genetic virulence determinants, ORF1 from the attenuated vaccine virus and three Danish vaccine-derived field isolates was sequenced and compared with the parental strain of the vaccine virus (VR2332). This revealed five mutations that had occurred independently in all three vaccine-derived field isolates, indicating strong parallel selective pressure on these positions in the vaccine virus when used in swine herds. Two of these parallel mutations were direct reversions to the parental VR2332 sequence and were situated in a papain-like cysteine protease domain and in the helicase domain. The remaining parallel mutations might be seen as second-site compensatory mutations for one or more of the mutations that accumulated in the vaccine virus sequence during cell-culture adaptation. Evaluation of the remaining mutations...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="be63b1f09a9524383386254bd83da8eb" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240606,"asset_id":79570873,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240606/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570873"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570873"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570873; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570873]").text(description); $(".js-view-count[data-work-id=79570873]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570873; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570873']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "be63b1f09a9524383386254bd83da8eb" } } $('.js-work-strip[data-work-id=79570873]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570873,"title":"Reversion of a live porcine reproductive and respiratory syndrome virus vaccine investigated by parallel mutations","internal_url":"https://www.academia.edu/79570873/Reversion_of_a_live_porcine_reproductive_and_respiratory_syndrome_virus_vaccine_investigated_by_parallel_mutations","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[{"id":86240606,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/86240606/thumbnails/1.jpg","file_name":"abf1703976ba265d3866e4e18666e5aa8a92.pdf","download_url":"https://www.academia.edu/attachments/86240606/download_file","bulk_download_file_name":"Reversion_of_a_live_porcine_reproductive.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/86240606/abf1703976ba265d3866e4e18666e5aa8a92-libre.pdf?1653125988=\u0026response-content-disposition=attachment%3B+filename%3DReversion_of_a_live_porcine_reproductive.pdf\u0026Expires=1741326391\u0026Signature=XVVrzk0ktbKra4Ulpbr1cOtdhUD~A32MApv2D-fcyNCC2BUAfUidHxHT~NaHhkjqhJQRirTOEMTb3tlkCAmkg7Db31C5Brh9PHdYowatgQtwJ8Siyw6ZOJmdc5eQ8rBHdiTWLfxEXFmiUFiNAHcnJLlFO7-EIXRKhuqijxFMZEBonKV6cUg7ssMyGiKI7g9OAwsYFslxMF-xnZStuOqB57T0oaaNaxMkMdHDw8sIMFcNOc6jdIcj8hlMXEhwBLB1y83zu84Unaj8rbc6R-iNaEE6S2Y66xk7j8SLd7wjoeOT~vE5h1spNG4eto6KcLNsl5ZF2zvKH2fSr3RYFxqfgQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570872"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570872/The_Genetic_Diversity_of_European_Type_PRRSV_Is_Similar_to_That_of_the_North_American_Type_but_Is_Geographically_Skewed_within_Europe"><img alt="Research paper thumbnail of The Genetic Diversity of European Type PRRSV Is Similar to That of the North American Type but Is Geographically Skewed within Europe" class="work-thumbnail" src="https://attachments.academia-assets.com/86240601/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570872/The_Genetic_Diversity_of_European_Type_PRRSV_Is_Similar_to_That_of_the_North_American_Type_but_Is_Geographically_Skewed_within_Europe">The Genetic Diversity of European Type PRRSV Is Similar to That of the North American Type but Is Geographically Skewed within Europe</a></div><div class="wp-workCard_item"><span>Virology</span><span>, 2002</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Porcine reproductive and respiratory syndrome virus (PRRSV) is a recently emerged pathogen. Two P...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Porcine reproductive and respiratory syndrome virus (PRRSV) is a recently emerged pathogen. Two PRRSV genotypes exist, North American and European, which are only 55-70% identical at the nucleotide level. Previous studies have shown high nucleotide diversity in the North American genotype and low nucleotide diversity in the European genotype. Here, we analyzed the ORF5 and ORF7 genes for a large number of new European type PRRSV isolates in conjunction with existing database sequences. This new analysis showed that contrary to previous assumptions, genetic diversity is at least as high in the European genotype as in the North American genotype. Furthermore, we showed that genetic diversity of European type PRRSV has a marked geographical pattern, with exceptionally high genetic diversity among Italian sequences. The geographical pattern of diversity in relation to the epidemiology of PRRSV in Europe is discussed. Discrepancies between ORF5-and ORF7-based genealogies were observed, and further analysis of the data set confirmed the presence of recombination. We were therefore able to report the first observation of recombination in wild-type isolates of European genotype PRRSV.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ae5c1b3e22ee7e79e0c46b02fde6bd7c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240601,"asset_id":79570872,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240601/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570872"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570872"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570872; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570872]").text(description); $(".js-view-count[data-work-id=79570872]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570872; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570872']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ae5c1b3e22ee7e79e0c46b02fde6bd7c" } } $('.js-work-strip[data-work-id=79570872]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570872,"title":"The Genetic Diversity of European Type PRRSV Is Similar to That of the North American Type but Is Geographically Skewed within Europe","internal_url":"https://www.academia.edu/79570872/The_Genetic_Diversity_of_European_Type_PRRSV_Is_Similar_to_That_of_the_North_American_Type_but_Is_Geographically_Skewed_within_Europe","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[{"id":86240601,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/86240601/thumbnails/1.jpg","file_name":"aHR0cDovL2FwaS5lbHNldmllci5jb20vY29udGVudC9hcnRpY2xlL3BpaS9zMDA0MjY4MjIwMjkxNDUwOQ__.pdf","download_url":"https://www.academia.edu/attachments/86240601/download_file","bulk_download_file_name":"The_Genetic_Diversity_of_European_Type_P.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/86240601/aHR0cDovL2FwaS5lbHNldmllci5jb20vY29udGVudC9hcnRpY2xlL3BpaS9zMDA0MjY4MjIwMjkxNDUwOQ__-libre.pdf?1653125984=\u0026response-content-disposition=attachment%3B+filename%3DThe_Genetic_Diversity_of_European_Type_P.pdf\u0026Expires=1741326391\u0026Signature=ZTnbLclPwVqyRdgvoNZnuO0NWXh7CnuLCCDGhaP5u~9vIYboBI-FUD~uU-DQD-GCdg1lYmvtAn34eXmguvxYyjZHAzw-TaAHnoXEc6SPNC3RxjJCzuuUhRqbLXMBw8Usl7KFfXiXJd9hYj1CR5zEUIKpEO-0hxqcevc5TdXjppfpKQVcfJrnE25IWtQefhJCInmokVB4slej6~fFLHIgrS5BreK0bVB2FicjVxFKDeukQMoHYmuQXhy7oWRLPgV1gpQhlPkkKPA1IQ93C-Iiw9N8nK9NuQaCBSvHgmkoEyD82fBmAVVt-crjnGVGJpML6sWfIjPQa64YujPbj4ALEg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570871"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570871/Abstract_5332_Comparison_of_variant_calling_from_whole_exome_and_transcriptome_sequencing_using_CLC_Cancer_Research_Workbench"><img alt="Research paper thumbnail of Abstract 5332: Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570871/Abstract_5332_Comparison_of_variant_calling_from_whole_exome_and_transcriptome_sequencing_using_CLC_Cancer_Research_Workbench">Abstract 5332: Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The now commonplace application of whole exome and genome sequencing in cancer research and diagn...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The now commonplace application of whole exome and genome sequencing in cancer research and diagnostics has allowed for rapid identification of SNPs and InDels in protein coding regions, but neither method is able to reveal situations of incomplete penetrance. That is, while possible cancer causing allele variants can be detected with these methods, this does not mean these alleles are actually expressed. Reasons for this are various and include epigenetic effects and changes, transcription regulation mechanisms, mRNA degradation and epistasis. By contrast, transcriptome sequencing (RNA-seq) can be used to identify the alleles being expressed. This method has the additional benefits of providing insight into the transcript expression levels, expressed allele isoforms and offers the possibility of identifying instances of fusion transcripts. Such knowledge about variants expressed in tumor cells is crucial for the identification of effective drug targets. Here, we illustrate the benefits of combining whole exome sequencing with RNA-seq by analyzing whole exome and RNA-seq datasets from uveal melanoma samples with our newly developed CLC Cancer Research Workbench. This software suite enables the complete analysis of both approaches, including variant calling, followed by the comparison of the called variants. The analysis will be carried out using user-friendly, automated workflows distributed with the CLC Cancer Research Workbench. In this work, we discuss and compare variants identified in the exome and RNA-seq datasets using our algorithms, and focus particularly on variants identified in the exome data that appear not to be expressed in the tumor samples. Citation Format: Anne Arens, Anne-Mette K. Hein, Uwe Appelt, Anika Joecker, Soren Monsted, Bjarne Knudsen, Naomi Thomson, Richard Lussier, Cecilie Boysen, Roald Forsberg. Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5332. doi:10.1158/1538-7445.AM2014-5332</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570871"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570871"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570871; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570871]").text(description); $(".js-view-count[data-work-id=79570871]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570871; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570871']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570871]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570871,"title":"Abstract 5332: Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench","internal_url":"https://www.academia.edu/79570871/Abstract_5332_Comparison_of_variant_calling_from_whole_exome_and_transcriptome_sequencing_using_CLC_Cancer_Research_Workbench","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570870"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570870/Abstract_4181_Accurate_and_fast_detection_and_comparison_of_larger_clinically_relevant_insertions_and_deletions"><img alt="Research paper thumbnail of Abstract 4181: Accurate and fast detection and comparison of larger clinically relevant insertions and deletions" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570870/Abstract_4181_Accurate_and_fast_detection_and_comparison_of_larger_clinically_relevant_insertions_and_deletions">Abstract 4181: Accurate and fast detection and comparison of larger clinically relevant insertions and deletions</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Larger somatic insertions and deletions in tumor samples are often of significant clinical impact...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Larger somatic insertions and deletions in tumor samples are often of significant clinical impact. Many of them are cancer driver mutations and play an important role in drug treatment1. Detecting the accurate breakpoints of larger insertions and deletions is often problematic and inaccurate. Furthermore, due to ambiguous positioning of them in the human genome, they are hard to compare with known deletions and insertions in publicly available databases. Here we present a complete analysis workflow to accurate identify, filter and annotate larger insertions and deletions with information from publicly available databases such as COSMIC. We apply our pipeline on publicly available tumor/normal matched pair data from a patient with Massive Acinic Cell Carcinoma (A. Nichols et al. (2013) Case Reports in Oncological Medicine, Article ID 270362), which has not been investigated for larger insertions and deletions before. We show that we can identify insertions and deletions, which should be reported as part of the list of somatic variants, the authors have presented. Moreover, we will point out potential challenges and how to solve them while comparing own results to data in databases. Citation Format: Anne-Mette K. Hein, Patrick Dekker, Anika Joecker, Cecilie Boysen, Naomi Thomson, Bodil Oester, Anne Arens, Bjarne Knudsen, Thomas Knudsen, Roald Forsberg. Accurate and fast detection and comparison of larger clinically relevant insertions and deletions. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4181. doi:10.1158/1538-7445.AM2014-4181</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570870"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570870"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570870; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570870]").text(description); $(".js-view-count[data-work-id=79570870]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570870; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570870']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570870]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570870,"title":"Abstract 4181: Accurate and fast detection and comparison of larger clinically relevant insertions and deletions","internal_url":"https://www.academia.edu/79570870/Abstract_4181_Accurate_and_fast_detection_and_comparison_of_larger_clinically_relevant_insertions_and_deletions","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570869"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570869/Abstract_2334_Identification_of_differentially_expressed_genes_and_somatic_mutations_in_esophageal_adenocarinoma_cancer_patients"><img alt="Research paper thumbnail of Abstract 2334: Identification of differentially expressed genes and somatic mutations in esophageal adenocarinoma cancer patients" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570869/Abstract_2334_Identification_of_differentially_expressed_genes_and_somatic_mutations_in_esophageal_adenocarinoma_cancer_patients">Abstract 2334: Identification of differentially expressed genes and somatic mutations in esophageal adenocarinoma cancer patients</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">High throughput sequencing technologies are currently revolutionizing the cancer research area wi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">High throughput sequencing technologies are currently revolutionizing the cancer research area with rapid improvements in sequencing capacity and time consumption. As a result the most time consuming step has moved from being the sequencing process itself to being the bioinformatic data analysis. RNA sequencing (RNA-Seq) is used in an increasing number of transcriptomic studies. The great advantage of using RNA-Seq is its ability to precisely quantify transcript levels and identify novel transcripts, isoforms, and splice junctions, while further providing information of the mutational landscape down to single base resolution. To ease the hurdles associated with RNA-Seq data analysis there is an increasing demand for tools that are specifically tailored to RNA-Seq data. Here we describe how the newly developed CLC Cancer Research Workbench can be used to analyze and visualize RNA-Seq data with ready-to-use workflows that automatically map, quantify, and annotate transcriptomes. We identify differentially expressed genes and transcripts in Illumina HiSeq transcriptomic data from matched tumor and normal samples from four esophageal adenocarinoma cancer patients, and compare the mutational patterns in the samples with the expression values of the corresponding genes. Results are visualized in a track based genome browser view, which provides the means for quick and easy navigation as well as allowing the user to simultaneously view and annotate multiple samples and different data types (e.g. genes, transcript expression levels, and detected variants). Citation Format: Bodil Oster, Anika Joecker, Anne-Mette K. Hein, Patrick Dekker, Robert O9Neill, Adam Krejci, Anne Arens, Naomi Thomson, Cecilie Boysen, Soren Monsted, Roald Forsberg, Bjarne Knudsen, Thomas Knudsen, Richard Lussier, Ted R. Hupp. Identification of differentially expressed genes and somatic mutations in esophageal adenocarinoma cancer patients. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2334. doi:10.1158/1538-7445.AM2014-2334</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570869"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570869"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570869; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570869]").text(description); $(".js-view-count[data-work-id=79570869]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570869; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570869']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570869]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570869,"title":"Abstract 2334: Identification of differentially expressed genes and somatic mutations in esophageal adenocarinoma cancer patients","internal_url":"https://www.academia.edu/79570869/Abstract_2334_Identification_of_differentially_expressed_genes_and_somatic_mutations_in_esophageal_adenocarinoma_cancer_patients","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570868"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570868/Abstract_2227_An_automatic_pipeline_to_find_and_annotate_rare_subclonal_somatic_variants_in_a_paired_tumor_normal_sample"><img alt="Research paper thumbnail of Abstract 2227: An automatic pipeline to find and annotate rare subclonal somatic variants in a paired tumor/normal sample" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570868/Abstract_2227_An_automatic_pipeline_to_find_and_annotate_rare_subclonal_somatic_variants_in_a_paired_tumor_normal_sample">Abstract 2227: An automatic pipeline to find and annotate rare subclonal somatic variants in a paired tumor/normal sample</a></div><div class="wp-workCard_item"><span>Cancer Research</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Identifying and characterizing somatic variants in deep genome sequence data from tumor samples r...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Identifying and characterizing somatic variants in deep genome sequence data from tumor samples remains challenging and time-consuming. Of special interest in cancer research and diagnostics is the detection and annotation of rare subclonal somatic variants found only in a small proportion of primary tumor cells. Such variants can drive tumor spread and recurrence, but are often neglected in choosing treatments. Currently, few tools reliably distinguish such rare subclonal variants from sequencing errors. And even among real somatic variants, drivers (of tumor growth, spread, or resistance) are hard to distinguish from passengers. Doing so entails integrating diverse information on variants, genes, pathways, cancer-relevant phenotypes, and treatments (including insights on population allele frequencies and broader evolutionary conservation; known/likely effects on gene product structure, function, expression, and interaction; and relations among gene products, phenotypes, and drugs). Software for effectively integrating such data in light of genomic variation in samples, to highlight relevant findings through clear visualization, has been a pressing need. Here we present an end-to-end analysis workflow for finding and functionally characterizing rare subclonal variants, using the newly developed CLC Cancer Research Workbench to feed the interpretive platform of Ingenuity Variant Analysis, to identify cancer driver mutations in paired tumor/normal samples. We will show new interesting results from this analysis, which were not shown beforehand on this publicly available cancer dataset (Case Reports in Oncological Medicine, Volume 2013 (2013), Article ID 270362) from a patient with massive acinic cell carcinoma. Citation Format: Anika Joecker, Nathan Pearson, Cecilie Boysen, Naomi Thomson, Anne-Mette Hein, Bodil Oster, Anne Arens, Bjarne Knudsen, Thomas Knudsen, Dan Richards, Roald Forsberg. An automatic pipeline to find and annotate rare subclonal somatic variants in a paired tumor/normal sample. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2227. doi:10.1158/1538-7445.AM2014-2227</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570868"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570868"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570868; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570868]").text(description); $(".js-view-count[data-work-id=79570868]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570868; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570868']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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</script> <div class="js-work-strip profile--work_container" data-work-id="79570867"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570867/CLC_Bio_Integrated_Platform_for_Handling_and_Analysis_of_Tag_Sequencing_Data"><img alt="Research paper thumbnail of CLC Bio Integrated Platform for Handling and Analysis of Tag Sequencing Data" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570867/CLC_Bio_Integrated_Platform_for_Handling_and_Analysis_of_Tag_Sequencing_Data">CLC Bio Integrated Platform for Handling and Analysis of Tag Sequencing Data</a></div><div class="wp-workCard_item"><span>KAHL:TAG BASED SEQUENCING O-BK</span><span>, 2012</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570867"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570867"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570867; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570867]").text(description); $(".js-view-count[data-work-id=79570867]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570867; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570867']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570867]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570867,"title":"CLC Bio Integrated Platform for Handling and Analysis of Tag Sequencing Data","internal_url":"https://www.academia.edu/79570867/CLC_Bio_Integrated_Platform_for_Handling_and_Analysis_of_Tag_Sequencing_Data","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570866"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570866/A_computer_simulator_for_assessing_different_challenges_and_strategies_of_de_novo_sequence_assembly"><img alt="Research paper thumbnail of A computer simulator for assessing different challenges and strategies of de novo sequence assembly" class="work-thumbnail" src="https://attachments.academia-assets.com/86240593/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570866/A_computer_simulator_for_assessing_different_challenges_and_strategies_of_de_novo_sequence_assembly">A computer simulator for assessing different challenges and strategies of de novo sequence assembly</a></div><div class="wp-workCard_item"><span>Genes</span><span>, 2010</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This study presents a new computer program for assessing the effects of different factors and seq...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This study presents a new computer program for assessing the effects of different factors and sequencing strategies on de novo sequence assembly. The program uses reads from actual sequencing studies or from simulations with a reference genome that may also be real or simulated. The simulated reads can be created with our read simulator. They can be of differing length and coverage, consist of paired reads with varying distance, and include sequencing errors such as color space miscalls to imitate SOLiD data. The simulated or real reads are mapped to their reference genome and our assembly simulator is then used to obtain optimal assemblies that are limited only by the distribution of repeats. By way of this mapping, the assembly simulator determines which contigs are theoretically possible, or conversely (and perhaps more importantly), which are not. We illustrate the application and utility of our new simulation tools with several experiments that test the effects of genome comple...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5085d8515f7d7cbedd8744b3c3dc855b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240593,"asset_id":79570866,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240593/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570866"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570866"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570866; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "5085d8515f7d7cbedd8744b3c3dc855b" } } $('.js-work-strip[data-work-id=79570866]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570866,"title":"A computer simulator for assessing different challenges and strategies of de novo sequence assembly","internal_url":"https://www.academia.edu/79570866/A_computer_simulator_for_assessing_different_challenges_and_strategies_of_de_novo_sequence_assembly","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[{"id":86240593,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/86240593/thumbnails/1.jpg","file_name":"pdf.pdf","download_url":"https://www.academia.edu/attachments/86240593/download_file","bulk_download_file_name":"A_computer_simulator_for_assessing_diffe.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/86240593/pdf-libre.pdf?1653125993=\u0026response-content-disposition=attachment%3B+filename%3DA_computer_simulator_for_assessing_diffe.pdf\u0026Expires=1741326391\u0026Signature=EfWB1DMCpRYQZDr~cKmLd99TsDsfPqGnoOtY2p93CfTT2HkeMjAiJIFBk-siy3P1Vxbzh0hT4BuLJQNzbAqq5JxZlIu~D6kX6Mhn1e4l~pe9A16lSe3bE-dsPIWn2LeG6S9WFXi2JwSmS23zLi~cgudxyozszi~tw2sA08dL2VTDCLCrWfYPHCuPTHE4E2UXLlRtqLYfaZECrrEAuXJVk~HAYBIZ3p2TNcNjA~xjQyvw0l4hNDYK5EIzgBf5t7tQL3meLJ--TyNiLjvDFWcSwNFacH1JMy53zl4fxXvxTqzKWgh1fYBifEJ5zGL7O00BkdMbHfRQv5fyUYJqjDSwXg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570865"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/79570865/Using_NGS_Data_to_Facilitate_Plant_Breeding"><img alt="Research paper thumbnail of Using NGS Data to Facilitate Plant Breeding" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/79570865/Using_NGS_Data_to_Facilitate_Plant_Breeding">Using NGS Data to Facilitate Plant Breeding</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We are developing a platform withing the CLC suite to optimise bulk segregant analysis on the pop...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We are developing a platform withing the CLC suite to optimise bulk segregant analysis on the population of plants derived from all possible pairwise crosses of a small number of elite parental lines. Parental DNA, as well as pooled progeny DNA from the individuals having extreme values of a trait of interest, has been sequenced. Implemented outcomes would be facilitation of genome-wide selection, assignment of &#39;breeding values&#39; to elite parents, and identification of individual markers/genes affecting the trait.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570865"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570865"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570865; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570865]").text(description); $(".js-view-count[data-work-id=79570865]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570865; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570865']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=79570865]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570865,"title":"Using NGS Data to Facilitate Plant Breeding","internal_url":"https://www.academia.edu/79570865/Using_NGS_Data_to_Facilitate_Plant_Breeding","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570864"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570864/A_Molecular_Clock_Dates_the_Common_Ancestor_of_European_type_Porcine_Reproductive_and_Respiratory_Syndrome_Virus_at_More_Than_10_Years_before_the_Emergence_of_Disease"><img alt="Research paper thumbnail of A Molecular Clock Dates the Common Ancestor of European-type Porcine Reproductive and Respiratory Syndrome Virus at More Than 10 Years before the Emergence of Disease" class="work-thumbnail" src="https://attachments.academia-assets.com/86240598/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570864/A_Molecular_Clock_Dates_the_Common_Ancestor_of_European_type_Porcine_Reproductive_and_Respiratory_Syndrome_Virus_at_More_Than_10_Years_before_the_Emergence_of_Disease">A Molecular Clock Dates the Common Ancestor of European-type Porcine Reproductive and Respiratory Syndrome Virus at More Than 10 Years before the Emergence of Disease</a></div><div class="wp-workCard_item"><span>Virology</span><span>, 2001</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The disease caused by porcine reproductive and respiratory syndrome virus (PRRSV) emerged indepen...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The disease caused by porcine reproductive and respiratory syndrome virus (PRRSV) emerged independently and almost simultaneously in Europe (1990) and North America (1987). The original reservoir of the virus and the date it entered the pig populations is not known. In this study, we demonstrate an accurate molecular clock for the European PRRSV ORF 3 gene, place the root in the genealogy, estimate the rate of nucleotide substitution, and date the most recent common viral ancestor of the data set to 1979; more than 10 years before the onset of the European epidemic. Based on these findings, we conclude that PRRSV virus most likely entered the pig population some time before the epidemic emergence of the virus, and hence, that emergence of European-type PRRSV is not the result of a recent species transmission event. Together, our results show that ORF3 sequencing is a valuable epidemiologic tool for examining the emergence and spread of PRRSV in Europe. As such, the panel of well-characterized and highly divergent ORF3 sequences described in this study provides a reference point for future molecular epidemiologic studies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f34f95c1d6f1ba8c367158860eb4a414" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240598,"asset_id":79570864,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240598/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570864"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570864"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570864; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570864]").text(description); $(".js-view-count[data-work-id=79570864]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570864; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570864']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570863"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570863/Measurably_evolving_populations"><img alt="Research paper thumbnail of Measurably evolving populations" class="work-thumbnail" src="https://attachments.academia-assets.com/86240600/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570863/Measurably_evolving_populations">Measurably evolving populations</a></div><div class="wp-workCard_item"><span>Trends in Ecology &amp; Evolution</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The availability of nucleotide and amino acid sequences sampled at different points in time has f...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The availability of nucleotide and amino acid sequences sampled at different points in time has fostered the development of new statistical methods that exploit this temporal dimension. Such sequences enable us to observe evolution in action and to estimate the rate and magnitude of evolutionary processes through time. Populations for which such studies are possiblemeasurably evolving populations (MEPs)-are characterized by sufficiently long or numerous sampled sequences and a fast mutation rate relative to the available range of sequence sampling times. The impact of sequences sampled through time has been most apparent in the disciplines of RNA viral evolution and ancient DNA, where they enable us to estimate divergence times without paleontological calibrations, and to analyze temporal changes in population size, population structure and substitution rates. Thus, MEPs could increase our understanding of evolutionary processes in diverse organisms, from viruses to vertebrates.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4ca6c2cec4bc3659dbc90d1f15a22893" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240600,"asset_id":79570863,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240600/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570863"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570863"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570863; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570863]").text(description); $(".js-view-count[data-work-id=79570863]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570863; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570863']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "4ca6c2cec4bc3659dbc90d1f15a22893" } } $('.js-work-strip[data-work-id=79570863]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570863,"title":"Measurably evolving populations","internal_url":"https://www.academia.edu/79570863/Measurably_evolving_populations","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[{"id":86240600,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/86240600/thumbnails/1.jpg","file_name":"MeasurablyEvolvingPopulations.pdf","download_url":"https://www.academia.edu/attachments/86240600/download_file","bulk_download_file_name":"Measurably_evolving_populations.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/86240600/MeasurablyEvolvingPopulations-libre.pdf?1653125998=\u0026response-content-disposition=attachment%3B+filename%3DMeasurably_evolving_populations.pdf\u0026Expires=1741326391\u0026Signature=c~RQln3-6MBCI-I013QYojeDtb-gnbzONUiDNjxw~bZk60G6dkaw58f6cIAm9xc8Z59eF~wwRwYFgeIcItAJURTLwgy6WRF~dtw~~tlmrofvOq1uDV3r-60j1mlqC8Ge-reCkGUaxDt5kSh7mRPLb14jw6uVuFv2RvVhH5LINivYCpuuRzUtGUt56A20oDSHjnqRXOl59aoxSsjtoCn3ndy-TJA3dlR8N4P9SROczI11d644KM7UXaea0QuJlT6VjwjuTaS3phsYKKJsnCWshFLwRKgcJZdLMyJhT6TWeTxeIAmgPgbdo4cJY5TAR9FIEe2NNYj~OVna0XLbcBeV8A__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570862"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570862/A_comparative_method_for_finding_and_folding_RNA_secondary_structures_within_protein_coding_regions"><img alt="Research paper thumbnail of A comparative method for finding and folding RNA secondary structures within protein-coding regions" class="work-thumbnail" src="https://attachments.academia-assets.com/86240608/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570862/A_comparative_method_for_finding_and_folding_RNA_secondary_structures_within_protein_coding_regions">A comparative method for finding and folding RNA secondary structures within protein-coding regions</a></div><div class="wp-workCard_item"><span>Nucleic Acids Research</span><span>, 2004</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Existing computational methods for RNA secondarystructure prediction tacitly assume RNA to only e...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Existing computational methods for RNA secondarystructure prediction tacitly assume RNA to only encode functional RNA structures. However, experimental studies have revealed that some RNA sequences, e.g. compact viral genomes, can simultaneously encode functional RNA structures as well as proteins, and evidence is accumulating that this phenomenon may also be found in Eukaryotes. We here present the first comparative method, called RNA-DECODER, which explicitly takes the known proteincoding context of an RNA-sequence alignment into account in order to predict evolutionarily conserved secondary-structure elements, which may span both coding and non-coding regions. RNA-DECODER employs a stochastic context-free grammar together with a set of carefully devised phylogenetic substitution-models, which can disentangle and evaluate the different kinds of overlapping evolutionary constraints which arise. We show that RNA-DECODER's parameters can be automatically trained to successfully fold known secondary structures within the HCV genome. We scan the genomes of HCV and polio virus for conserved secondary-structure elements, and analyze performance as a function of available evolutionary information. On known secondary structures, RNA-DECODER shows a sensitivity similar to the programs MFOLD, PFOLD and RNAALIFOLD. When scanning the entire genomes of HCV and polio virus for structure elements, RNA-DECODER's results indicate a markedly higher specificity than MFOLD, PFOLD and RNAALIFOLD.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ee219c1650ff9c7d314602f69acc932f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240608,"asset_id":79570862,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240608/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570862"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570862"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570862; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570862]").text(description); $(".js-view-count[data-work-id=79570862]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570862; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570862']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ee219c1650ff9c7d314602f69acc932f" } } $('.js-work-strip[data-work-id=79570862]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570862,"title":"A comparative method for finding and folding RNA secondary structures within protein-coding regions","internal_url":"https://www.academia.edu/79570862/A_comparative_method_for_finding_and_folding_RNA_secondary_structures_within_protein_coding_regions","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[{"id":86240608,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/86240608/thumbnails/1.jpg","file_name":"4925.pdf","download_url":"https://www.academia.edu/attachments/86240608/download_file","bulk_download_file_name":"A_comparative_method_for_finding_and_fol.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/86240608/4925-libre.pdf?1653125989=\u0026response-content-disposition=attachment%3B+filename%3DA_comparative_method_for_finding_and_fol.pdf\u0026Expires=1741326391\u0026Signature=SIo4j-0VNO7oD~wmieVEGjk0kt9folBxsusJA-LDgeiQYNnS3W8zKHH6DtFiXn49WnE~SQexyRjcTfy~wy1aWI3bj7RWL78u8u~fsZestf2P6so62nLQQVEXfYyTOBuKGKhvm5N7yorr4kZLrN7zuycw5qMg7xjiBTHDA4RCYNQk~7f9rDpR~7maBtDGiYv5UmgWu4Nqsxy-eOcr1OYP6vosQKAXtbMDS6G86LPmsLDSWjlflC7BjwhYfm9GClb8~XTC6h8-bRqXZuyVhYyPo4LSRx-0GNjuVU97ezEdPjsNiXtk1cdl8lexBSMEeuVBB9LHndHM3SIx3DrShqAF7Q__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570861"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570861/Divergence_Time_of_Porcine_Reproductive_and_Respiratory_Syndrome_Virus_Subtypes"><img alt="Research paper thumbnail of Divergence Time of Porcine Reproductive and Respiratory Syndrome Virus Subtypes" class="work-thumbnail" src="https://attachments.academia-assets.com/86240596/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570861/Divergence_Time_of_Porcine_Reproductive_and_Respiratory_Syndrome_Virus_Subtypes">Divergence Time of Porcine Reproductive and Respiratory Syndrome Virus Subtypes</a></div><div class="wp-workCard_item"><span>Molecular Biology and Evolution</span><span>, 2005</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Porcine reproductive and respiratory syndrome virus (PRRSV) recently emerged in domestic pigs of ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Porcine reproductive and respiratory syndrome virus (PRRSV) recently emerged in domestic pigs of Western Europe and North America. Although time of emergence was identical on the two continents, genetic composition was markedly different with a clear geographical subtype structure, indicating that subtypes diverged in separate reservoirs prior to emergence. Genetic analyses have shown that the most recent common ancestor (MRCA) of Western European isolates existed around 1980 and that these originate from Eastern European pigs. These findings are challenged by a study of Hanada et al. who place the MRCA of all PRRSV isolates around 1980 and find that no significant subtype divergence occurred before emergence. Here, I discuss problems of information content, methodology, and biological plausibility associated with this study. Using alternative methodology, I reanalyze the existing data and conclude that the MRCA of all PRRSV isolates existed around 1880, 100 years before the date estimated by Hanada et al.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d6fc7b222034f06eb9f0331a628522ef" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240596,"asset_id":79570861,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240596/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570861"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570861"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570861; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570860"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570860/A_Codon_Based_Model_of_Host_Specific_Selection_in_Parasites_with_an_Application_to_the_Influenza_A_Virus"><img alt="Research paper thumbnail of A Codon-Based Model of Host-Specific Selection in Parasites, with an Application to the Influenza A Virus" class="work-thumbnail" src="https://attachments.academia-assets.com/86240604/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570860/A_Codon_Based_Model_of_Host_Specific_Selection_in_Parasites_with_an_Application_to_the_Influenza_A_Virus">A Codon-Based Model of Host-Specific Selection in Parasites, with an Application to the Influenza A Virus</a></div><div class="wp-workCard_item"><span>Molecular Biology and Evolution</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Parasites sometimes expand their host range by acquiring a new host species. After a host change ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Parasites sometimes expand their host range by acquiring a new host species. After a host change event, the selective regime acting on a given parasite gene may change as a result of host-specific adaptive alterations of protein functionality or host-specific immune-mediated selection. We present a codon-based model that attempts to include these effects by allowing the position-specific substitution process to change in conjunction with a host change event. Following maximum-likelihood parameter estimation, we employ an empirical Bayesian procedure to identify candidate sites potentially involved in host-specific adaptation. We discuss the applicability of the model to the more general problem of ascertaining whether the selective regime differs in two groups of related organisms. The utility of the model is illustrated on a data set of nucleoprotein sequences from the influenza A virus obtained from avian and human hosts.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="1a1ea157b049f5fff70c46066ba6eff0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240604,"asset_id":79570860,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240604/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570860"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570860"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570860; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570860]").text(description); $(".js-view-count[data-work-id=79570860]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570860; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570860']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570859"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570859/An_Evolutionary_Model_for_Protein_Coding_Regions_with_Conserved_RNA_Structure"><img alt="Research paper thumbnail of An Evolutionary Model for Protein-Coding Regions with Conserved RNA Structure" class="work-thumbnail" src="https://attachments.academia-assets.com/86240612/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570859/An_Evolutionary_Model_for_Protein_Coding_Regions_with_Conserved_RNA_Structure">An Evolutionary Model for Protein-Coding Regions with Conserved RNA Structure</a></div><div class="wp-workCard_item"><span>Molecular Biology and Evolution</span><span>, 2004</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Here we present a model of nucleotide substitution in protein-coding regions that also encode the...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Here we present a model of nucleotide substitution in protein-coding regions that also encode the formation of conserved RNA structures. In such regions, apparent evolutionary context dependencies exist, both between nucleotides occupying the same codon and between nucleotides forming a base pair in the RNA structure. The overlap of these fundamental dependencies is sufficient to cause ''contagious'' context dependencies which cascade across many nucleotide sites. Such large-scale dependencies challenge the use of traditional phylogenetic models in evolutionary inference because they explicitly assume evolutionary independence between short nucleotide tuples. In our model we address this by replacing context dependencies within codons by annotation-specific heterogeneity in the substitution process. Through a general procedure, we fragment the alignment into sets of short nucleotide tuples based on both the protein coding and the structural annotation. These individual tuples are assumed to evolve independently, and the different tuple sets are assigned different annotation-specific substitution models shared between their members. This allows us to build a composite model of the substitution process from components of traditional phylogenetic models. We applied this to a data set of full-genome sequences from the hepatitis C virus where five RNA structures are mapped within the coding region. This allowed us to partition the effects of selection on different structural elements and to test various hypotheses concerning the relation of these effects. Of particular interest, we found evidence of a functional role of loop and bulge regions, as these were shown to evolve according to a different and more constrained selective regime than the nonpairing regions outside the RNA structures. Other potential applications of the model include comparative RNA structure prediction in coding regions and RNA virus phylogenetics.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="3026342e7e9b208e85f6c6b92a042908" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240612,"asset_id":79570859,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240612/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570859"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570859"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570859; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570859]").text(description); $(".js-view-count[data-work-id=79570859]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570859; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570859']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "3026342e7e9b208e85f6c6b92a042908" } } $('.js-work-strip[data-work-id=79570859]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":79570859,"title":"An Evolutionary Model for Protein-Coding Regions with Conserved RNA Structure","internal_url":"https://www.academia.edu/79570859/An_Evolutionary_Model_for_Protein_Coding_Regions_with_Conserved_RNA_Structure","owner_id":104999990,"coauthors_can_edit":true,"owner":{"id":104999990,"first_name":"Roald","middle_initials":null,"last_name":"Forsberg","page_name":"RoaldForsberg","domain_name":"independent","created_at":"2019-03-14T02:43:24.353-07:00","display_name":"Roald Forsberg","url":"https://independent.academia.edu/RoaldForsberg"},"attachments":[{"id":86240612,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/86240612/thumbnails/1.jpg","file_name":"1913.pdf","download_url":"https://www.academia.edu/attachments/86240612/download_file","bulk_download_file_name":"An_Evolutionary_Model_for_Protein_Coding.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/86240612/1913-libre.pdf?1653125984=\u0026response-content-disposition=attachment%3B+filename%3DAn_Evolutionary_Model_for_Protein_Coding.pdf\u0026Expires=1741326391\u0026Signature=A2fv5wJy7w4d3ymAlDxL82o--6No24R7YOjzKpen1gLWgyQP6SZf1t04eX~wkf7pn1yS~q82aOANJGw2HvzcxSQCqOGMOBg9izXq0k8ojawtGWVm99iyp1LcSnS6~vuGq6rqMm0pwd7x6i~ttdgcTQnMq~mDivNSgdeRBe2SD8wupu3pxyMyuWNgLvwAtfrMu4WbZD4pFrCNFJUu6ZBNVHhxe19FarKigP4ElHhbJKlfNjs4iMei6Jm7R47IP4Zo19ZFzPQoKwQ6ghPO9NDWwbaQyL1YwClbCZhy1JnsdVa1XCDoFQMoDLZmkXpzySXj7WYDqnjpvLqerWUDhX545A__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570858"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570858/Inferring_Evolutionary_Rates_Using_Serially_Sampled_Sequences_from_Several_Populations"><img alt="Research paper thumbnail of Inferring Evolutionary Rates Using Serially Sampled Sequences from Several Populations" class="work-thumbnail" src="https://attachments.academia-assets.com/86240597/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570858/Inferring_Evolutionary_Rates_Using_Serially_Sampled_Sequences_from_Several_Populations">Inferring Evolutionary Rates Using Serially Sampled Sequences from Several Populations</a></div><div class="wp-workCard_item"><span>Molecular Biology and Evolution</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The estimation of evolutionary rates from serially sampled sequences has recently been the focus ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The estimation of evolutionary rates from serially sampled sequences has recently been the focus of several studies. In this paper, we extend these analyzes to allow the estimation of a joint rate of substitution, x, from several evolving populations from which serial samples are drawn. In the case of viruses evolving in different hosts, therapy may halt replication and therefore the accumulation of substitutions in the population. In such cases, it may be that only a proportion, p, of subjects are nonresponders who have viral populations that continue to evolve. We develop two likelihood-based procedures to jointly estimate p and x, and empirical Bayes' tests of whether an individual should be classified as a responder or nonresponder. An example data set comprising HIV-1 partial envelope sequences from six patients on highly active antiretroviral therapy is analyzed.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="6832f77389f07e42d05120487956c147" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240597,"asset_id":79570858,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240597/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570858"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570858"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570858; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570857"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570857/The_Inference_of_Stepwise_Changes_in_Substitution_Rates_Using_Serial_Sequence_Samples"><img alt="Research paper thumbnail of The Inference of Stepwise Changes in Substitution Rates Using Serial Sequence Samples" class="work-thumbnail" src="https://attachments.academia-assets.com/86240599/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570857/The_Inference_of_Stepwise_Changes_in_Substitution_Rates_Using_Serial_Sequence_Samples">The Inference of Stepwise Changes in Substitution Rates Using Serial Sequence Samples</a></div><div class="wp-workCard_item"><span>Molecular Biology and Evolution</span><span>, 2001</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">It is frequently true that molecular sequences do not evolve in a strictly clocklike manner. Inst...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">It is frequently true that molecular sequences do not evolve in a strictly clocklike manner. Instead, substitution rate may vary for a number of reasons, including changes in selection pressure and effective population size, as well as changes in mean generation time. Here we present two new methods for estimating stepwise changes in substitution rates when serially sampled molecular sequences are available. These methods are based on multiple rates with dated tips (MRDT) models and allow different rates to be estimated for different intervals of time. These intervals may correspond to the sampling intervals or to a priori-defined intervals that are not coincident with the times the serial samples are obtained. Two methods for obtaining estimates of multiple rates are described. The first is an extension of the phylogeny-based maximum-likelihood estimation procedure introduced by Rambaut. The second is a new parameterization of the pairwise distance least-squares procedure used by Drummond and Rodrigo. The utility of these methods is demonstrated on a genealogy of HIV sequences obtained at five different sampling times from a single patient over a period of 34 months. Recently, two papers have independently described methods to estimate substitution rate, , from serial samples under the assumption of a molecular clock. Rambaut (2000) shows how a phylogeny-based maximum-likelihood estimate (MLE) of the constant substitution rate, , expressing the divergence between dated</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d864ddc6c2d8ad8b45d97e34b314bd44" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240599,"asset_id":79570857,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240599/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570857"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570857"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570857; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=79570857]").text(description); $(".js-view-count[data-work-id=79570857]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 79570857; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='79570857']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="79570856"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/79570856/Evolution_of_the_fish_rhabdovirus_viral_haemorrhagic_septicaemia_virus"><img alt="Research paper thumbnail of Evolution of the fish rhabdovirus viral haemorrhagic septicaemia virus" class="work-thumbnail" src="https://attachments.academia-assets.com/86240589/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/79570856/Evolution_of_the_fish_rhabdovirus_viral_haemorrhagic_septicaemia_virus">Evolution of the fish rhabdovirus viral haemorrhagic septicaemia virus</a></div><div class="wp-workCard_item"><span>Journal of General Virology</span><span>, 2004</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Viral haemorrhagic septicaemia (VHS) caused by the rhabdovirus VHSV is economically the most impo...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Viral haemorrhagic septicaemia (VHS) caused by the rhabdovirus VHSV is economically the most important viral disease in European rainbow trout farming. Until 1989, this virus was mainly isolated from freshwater salmonids but in the last decade, it has also been isolated from an increasing number of free-living marine fish species. To study the genetic evolution of VHSV, the entire G gene from 74 isolates was analysed. VHSV from wild marine species caught in the Baltic Sea, Skagerrak, Kattegat, North Sea, and English Channel and European freshwater isolates, appeared to share a recent common ancestor. Based on the estimated nucleotide substitution rate, the ancestor of the European fresh water isolates was dated some 50 years ago. This finding fits with the initial reports in the 1950s on clinical observations of VHS in Danish freshwater rainbow trout farms. The study also indicates that European marine VHSV and the North American marine line separated approx. 500 years ago. The codo...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="63664b746296aa414467991a0a9463bc" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":86240589,"asset_id":79570856,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/86240589/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="79570856"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="79570856"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 79570856; 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