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(PDF) Molecular Modeling of RNA Evolution and Optimization Processes

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"https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F104691308%2FMolecular_insights_into_evolution%3Fauto%3Ddownload"; window.loswp.translateUrl = "https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F104691308%2FMolecular_insights_into_evolution%3Fshow_translation%3Dtrue"; window.loswp.previewableAttachments = [{"id":104352442,"identifier":"Attachment_104352442","shouldShowBulkDownload":false}]; window.loswp.shouldDetectTimezone = true; window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":104691308,"created_at":"2023-07-18T06:24:51.791-07:00","from_world_paper_id":237555063,"updated_at":"2024-11-26T13:08:37.790-08:00","_data":{"publisher":"Springer Nature","ai_title_tag":"Molecular Modeling of RNA Evolution and Optimization Processes","grobid_abstract":"Evolution of ribonucleic acid (RNA) molecules in the test-tube provides a possibility to study evolutionary optimization and adaptation to the environment on time scales accessible to human observers. Diversity of genotypes, however, is prohibitive for a complete experimental recording of the process on the molecular level. The number of RNA sequences and structures is too large to be determined by means of currently available techniques. Computer simulation, in contrary, is able to handle large numbers of individual sequences and has no major problem with data retrieval. However, it can deal only with simpli ed relations between genotypes and phenotypes, being RNA sequences and structures, respectively. Based on a course-grained notion of structure, as represented by RNA secondary structures, for example, a comprehensive model of evolution has been developed that allows to follow optimization at full molecular resolution. This model describes the course of in vitro selection experiments and provides a straightforward explanation for the occurrence of steps observed in evolution. It initiated the development of new mathematical concepts which analyse evolution as a complex process viewed simultaneously in concentration space, sequence space and shape space.","publication_date":"1999,,","publication_name":"Artificial Life and Robotics","grobid_abstract_attachment_id":"104352442"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Molecular insights into evolution","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [11507755]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; window.loginModal = {}; window.loginModal.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;swp-splash-paper-cover&quot;,&quot;attachmentId&quot;:104352442,&quot;attachmentType&quot;:&quot;pdf&quot;}"><img alt="First page of “Molecular insights into evolution”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/104352442/mini_magick20230718-1-ibk7ke.png?1689686797" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/images/single_work_splash/adobe_icon.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Molecular insights into evolution</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="11507755" href="https://independent.academia.edu/PSchuster"><img alt="Profile image of Peter Schuster" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/11507755/5025271/5767664/s65_peter.schuster.jpg" />Peter Schuster</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">1999, Artificial Life and Robotics</p><div class="ds-work-card--work-metadata"><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">visibility</span><p class="ds2-5-body-sm" id="work-metadata-view-count">…</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">description</span><p class="ds2-5-body-sm">6 pages</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">link</span><p class="ds2-5-body-sm">1 file</p></div></div><script>(async () => { const workId = 104691308; 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if (!viewCountBody) { throw new Error('Failed to find work views element'); } viewCountBody.textContent = `${commaizedViewCount} views`; } catch (error) { // Remove the whole views element if there was some issue parsing. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); throw new Error(`Failed to parse view count: ${viewCount}`, error); } }; // If the DOM is still loading, wait for it to be ready before updating the view count. if (document.readyState === "loading") { document.addEventListener('DOMContentLoaded', () => { updateViewCount(viewCount); }); // Otherwise, just update it immediately. } else { updateViewCount(viewCount); } })();</script></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">Evolution of ribonucleic acid (RNA) molecules in the test-tube provides a possibility to study evolutionary optimization and adaptation to the environment on time scales accessible to human observers. Diversity of genotypes, however, is prohibitive for a complete experimental recording of the process on the molecular level. The number of RNA sequences and structures is too large to be determined by means of currently available techniques. Computer simulation, in contrary, is able to handle large numbers of individual sequences and has no major problem with data retrieval. However, it can deal only with simpli ed relations between genotypes and phenotypes, being RNA sequences and structures, respectively. Based on a course-grained notion of structure, as represented by RNA secondary structures, for example, a comprehensive model of evolution has been developed that allows to follow optimization at full molecular resolution. This model describes the course of in vitro selection experiments and provides a straightforward explanation for the occurrence of steps observed in evolution. It initiated the development of new mathematical concepts which analyse evolution as a complex process viewed simultaneously in concentration space, sequence space and shape space.</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;continue-reading-button--work-card&quot;,&quot;attachmentId&quot;:104352442,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;workUrl&quot;:&quot;https://www.academia.edu/104691308/Molecular_insights_into_evolution&quot;}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;download-pdf-button--work-card&quot;,&quot;attachmentId&quot;:104352442,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;workUrl&quot;:&quot;https://www.academia.edu/104691308/Molecular_insights_into_evolution&quot;}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="104352442" data-landing_url="https://www.academia.edu/104691308/Molecular_insights_into_evolution" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="69744749" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/69744749/Evolution_At_Molecular_Resolution">Evolution At Molecular Resolution</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="11507755" href="https://independent.academia.edu/PSchuster">Peter Schuster</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Conventional population genetics is extended by support dynamics and genotypephenotype mapping in order to conceive a comprehensive dynamical model of evolution. Support dynamics describes migration of populations through genotype space. The relation between genotypes and phenotypes is a core issue of evolution. In the simplest conceivable case, in vitro evolution of RNA molecules, both phenomena can be incorporated into computer simulations. Application of replication-mutation kinetics to processes in the space of genotypes led to the notion of quasispecies which has been applied successfully to evolution of molecules and viruses. In molecular evolution mapping of genotypes into phenotypes is tantamount to sequence-structure relations of RNA molecules. Systematic studies were performed on secondary structures. They revealed a number of regularities which are reported. The number of sequences is much larger than the number of secondary structures and thus neutrality is a central issue of sequence-structure mappings. Evolution of populations of RNA molecules towards a predefined target structure were carried out and analyzed in molecular detail. The results derived for RNA molecules suggested to define a statistical relation of nearness between phenotypes which constitutes a kind of statistical topology. This probabilistic concept of neighborhood in sequence space can be generalized and appears to be of widespread validity in evolution.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Evolution At Molecular Resolution&quot;,&quot;attachmentId&quot;:79722429,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/69744749/Evolution_At_Molecular_Resolution&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/69744749/Evolution_At_Molecular_Resolution"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="17939393" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/17939393/How_Mutational_Networks_Shape_Evolution_Lessons_from_RNA_Models">How Mutational Networks Shape Evolution: Lessons from RNA Models</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="38273700" href="https://independent.academia.edu/MatthewCowperthwaite">Matthew Cowperthwaite</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="37853997" href="https://independent.academia.edu/LaurenMeyers1">Lauren Meyers</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Annual Review of Ecology, Evolution, and Systematics, 2007</p><p class="ds-related-work--abstract ds2-5-body-sm">Recent advances in molecular biology and computation have enabled evolutionary biologists to develop models that explicitly capture molecular structure. By including complex and realistic maps from genotypes to phenotypes, such models are yielding important new insights into evolutionary processes. In particular, computer simulations of evolving RNA structure have inspired a new conceptual framework for thinking about patterns of mutational connectivity and general theories about the nature of evolutionary transitions, the evolutionary ascent of nonoptimal phenotypes, and the origins of mutational robustness and modular structures. Here, we describe this class of RNA models and review the major conceptual contributions they have made to evolutionary biology.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;How Mutational Networks Shape Evolution: Lessons from RNA Models&quot;,&quot;attachmentId&quot;:42033408,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/17939393/How_Mutational_Networks_Shape_Evolution_Lessons_from_RNA_Models&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/17939393/How_Mutational_Networks_Shape_Evolution_Lessons_from_RNA_Models"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="69744167" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/69744167/Genotypes_and_Phenotypes_in_the_Evolution_of_Molecules">Genotypes and Phenotypes in the Evolution of Molecules</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="11507755" href="https://independent.academia.edu/PSchuster">Peter Schuster</a></div><p class="ds-related-work--metadata ds2-5-body-xs">European Review, 2009</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Genotypes and Phenotypes in the Evolution of Molecules&quot;,&quot;attachmentId&quot;:79722124,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/69744167/Genotypes_and_Phenotypes_in_the_Evolution_of_Molecules&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/69744167/Genotypes_and_Phenotypes_in_the_Evolution_of_Molecules"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="79468986" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/79468986/Variation_in_fitness_in_molecular_evolution">Variation in fitness in molecular evolution</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="206002325" href="https://independent.academia.edu/sameerkujur3">sameer kujur</a></div><p class="ds-related-work--metadata ds2-5-body-xs">1972</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Variation in fitness in molecular evolution&quot;,&quot;attachmentId&quot;:86173615,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/79468986/Variation_in_fitness_in_molecular_evolution&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/79468986/Variation_in_fitness_in_molecular_evolution"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="18976105" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/18976105/Phenotypic_effect_of_mutations_in_evolving_populations_of_RNA_molecules">Phenotypic effect of mutations in evolving populations of RNA molecules</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="38521413" href="https://independent.academia.edu/SManrubia">Susanna Manrubia</a></div><p class="ds-related-work--metadata ds2-5-body-xs">BMC Evolutionary Biology, 2010</p><p class="ds-related-work--abstract ds2-5-body-sm">Background: The secondary structure of folded RNA sequences is a good model to map phenotype onto genotype, as represented by the RNA sequence. Computational studies of the evolution of ensembles of RNA molecules towards target secondary structures yield valuable clues to the mechanisms behind adaptation of complex populations. The relationship between the space of sequences and structures, the organization of RNA ensembles at mutation-selection equilibrium, the time of adaptation as a function of the population parameters, the presence of collective effects in quasispecies, or the optimal mutation rates to promote adaptation all are issues that can be explored within this framework. Results: We investigate the effect of microscopic mutations on the phenotype of RNA molecules during their in silico evolution and adaptation. We calculate the distribution of the effects of mutations on fitness, the relative fractions of beneficial and deleterious mutations and the corresponding selection coefficients for populations evolving under different mutation rates. Three different situations are explored: the mutation-selection equilibrium (optimized population) in three different fitness landscapes, the dynamics during adaptation towards a goal structure (adapting population), and the behavior under periodic population bottlenecks (perturbed population). Conclusions: The ratio between the number of beneficial and deleterious mutations experienced by a population of RNA sequences increases with the value of the mutation rate μ at which evolution proceeds. In contrast, the selective value of mutations remains almost constant, independent of μ, indicating that adaptation occurs through an increase in the amount of beneficial mutations, with little variations in the average effect they have on fitness. Statistical analyses of the distribution of fitness effects reveal that small effects, either beneficial or deleterious, are well described by a Pareto distribution. These results are robust under changes in the fitness landscape, remarkably when, in addition to selecting a target secondary structure, specific subsequences or low-energy folds are required. A population perturbed by bottlenecks behaves similarly to an adapting population, struggling to return to the optimized state. Whether it can survive in the long run or whether it goes extinct depends critically on the length of the time interval between bottlenecks.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Phenotypic effect of mutations in evolving populations of RNA molecules&quot;,&quot;attachmentId&quot;:40361883,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/18976105/Phenotypic_effect_of_mutations_in_evolving_populations_of_RNA_molecules&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/18976105/Phenotypic_effect_of_mutations_in_evolving_populations_of_RNA_molecules"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="69744592" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/69744592/Mathematical_modeling_of_evolution_Solved_and_open_problems">Mathematical modeling of evolution. Solved and open problems</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="11507755" href="https://independent.academia.edu/PSchuster">Peter Schuster</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Theory in Biosciences, 2011</p><p class="ds-related-work--abstract ds2-5-body-sm">Evolution is a highly complex multilevel process and mathematical modeling of evolutionary phenomenon requires proper abstraction and radical reduction to essential features. Examples are natural selection, Mendel&#39;s laws of inheritance, optimization by mutation and selection, and neutral evolution. An attempt is made to describe the roots of evolutionary theory in mathematical terms. Evolution can be studied in vitro outside cells with polynucleotide molecules. Replication and mutation are visualized as chemical reactions that can be resolved, analyzed, and modeled at the molecular level, and straightforward extension eventually results in a theory of evolution based upon biochemical kinetics. Error propagation in replication commonly results in an error threshold that provides an upper bound for mutation rates. Appearance and sharpness of the error threshold depend on the fitness landscape, being the distribution of fitness values in genotype or sequence space. In molecular terms, fitness landscapes are the results of two consecutive mappings from sequences into structures and from structures into the (nonnegative) real numbers. Some properties of genotypephenotype maps are illustrated well by means of sequencestructure relations of RNA molecules. Neutrality in the sense that many RNA sequences form the same (coarse grained) structure is one of these properties, and characteristic for such mappings. Evolution cannot be fully understood without considering fluctuations-each mutant originates form a single copy, after all. The existence of neutral sets of genotypes called neutral networks, in particular, necessitates stochastic modeling, which is introduced here by simulation of molecular evolution in a kind of flowreactor.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Mathematical modeling of evolution. Solved and open problems&quot;,&quot;attachmentId&quot;:79722367,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/69744592/Mathematical_modeling_of_evolution_Solved_and_open_problems&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/69744592/Mathematical_modeling_of_evolution_Solved_and_open_problems"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="10574386" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/10574386/Partitioning_the_Fitness_Components_of_RNA_Populations_Evolving_In_Vitro">Partitioning the Fitness Components of RNA Populations Evolving In Vitro</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="25879309" href="https://independent.academia.edu/CarolinaArenas3">Carolina Arenas</a></div><p class="ds-related-work--metadata ds2-5-body-xs">PLoS ONE, 2013</p><p class="ds-related-work--abstract ds2-5-body-sm">All individuals in an evolving population compete for resources, and their performance is measured by a fitness metric. The performance of the individuals is relative to their abilities and to the biotic surroundings -the conditions under which they are competing -and involves many components. Molecules evolving in a test tube can also face complex environments and dynamics, and their fitness measurements should reflect the complexity of various contributing factors as well. Here, the fitnesses of a set of ligase ribozymes evolved by the continuous in vitro evolution system were measured. During these evolution cycles there are three different catalytic steps, ligation, reverse transcription, and forward transcription, each with a potential differential influence on the total fitness of each ligase. For six distinct ligase ribozyme genotypes that resulted from continuous evolution experiments, the rates of reaction were measured for each catalytic step by tracking the kinetics of enzymes reacting with their substrates. The reaction products were analyzed for the amount of product formed per time. Each catalytic step of the evolution cycle was found to have a differential incidence in the total fitness of the ligases, and therefore the total fitness of any ligase cannot be inferred from only one catalytic step of the evolution cycle. Generally, the ribozyme-directed ligation step tends to impart the largest effect on overall fitness. Yet it was found that the ligase genotypes have different absolute fitness values, and that they exploit different stages of the overall cycle to gain a net advantage. This is a new example of molecular niche partitioning that may allow for coexistence of more than one species in a population. The dissection of molecular events into multiple components of fitness provides new insights into molecular evolutionary studies in the laboratory, and has the potential to explain heretofore counterintuitive findings.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Partitioning the Fitness Components of RNA Populations Evolving In Vitro&quot;,&quot;attachmentId&quot;:47291065,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/10574386/Partitioning_the_Fitness_Components_of_RNA_Populations_Evolving_In_Vitro&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/10574386/Partitioning_the_Fitness_Components_of_RNA_Populations_Evolving_In_Vitro"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="69744759" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/69744759/Present_Day_Biology_seen_in_the_Looking_Glass_of_Physics_of_Complexity">Present Day Biology seen in the Looking Glass of Physics of Complexity</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="11507755" href="https://independent.academia.edu/PSchuster">Peter Schuster</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2013</p><p class="ds-related-work--abstract ds2-5-body-sm">Darwin&#39;s theory of variation and selection in its simplest form is directly applicable to RNA evolution in vitro as well as to virus evolution, and it allows for quantitative predictions. Understanding evolution at the molecular level is ultimately related to the central paradigm of structural biology: sequence ⇒ structure ⇒ function. We elaborate on the state of the art in modeling and understanding evolution of RNA driven by reproduction and mutation. The focus will be laid on the landscape concept-originally introduced by Sewall Wright-and its application to problems in biology. The relation between genotypes and phenotypes is the result of two consecutive mappings from a space of genotypes called sequence space onto a space of phenotypes or structures, and fitness is the result of a mapping from phenotype space into non-negative real numbers. Realistic landscapes as derived from folding of RNA sequences into structures are characterized by two properties: (i) they are rugged in the sense that sequences lying nearby in sequence space may have very different fitness values and (ii) they are characterized by an appreciable degree of neutrality implying that a certain fraction of genotypes and/or phenotypes cannot be distinguished in the selection process. Evolutionary dynamics on realistic landscapes will be studied as a function of the mutation rate, and the role of neutrality in the selection process will be discussed.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Present Day Biology seen in the Looking Glass of Physics of Complexity&quot;,&quot;attachmentId&quot;:79722438,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/69744759/Present_Day_Biology_seen_in_the_Looking_Glass_of_Physics_of_Complexity&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/69744759/Present_Day_Biology_seen_in_the_Looking_Glass_of_Physics_of_Complexity"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="29401225" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/29401225/Populations_of_RNA_Molecules_as_Computational_Model_for_Evolution">Populations of RNA Molecules as Computational Model for Evolution</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="14164616" href="https://uaeh.academia.edu/CarlosBriones">Carlos Briones</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Evolutionary Biology – Concepts, Molecular and Morphological Evolution, 2010</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Populations of RNA Molecules as Computational Model for Evolution&quot;,&quot;attachmentId&quot;:49840584,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/29401225/Populations_of_RNA_Molecules_as_Computational_Model_for_Evolution&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/29401225/Populations_of_RNA_Molecules_as_Computational_Model_for_Evolution"><span class="ds2-5-text-link__content">View PDF</span><span 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You can download the paper by clicking the button above.</p></div></div></div></div><div class="ds-sidebar--container js-work-sidebar"><div class="ds-related-content--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="0" data-entity-id="15308488" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/15308488/EVOLUTION_STUDIED_USING_PROTEIN_STRUCTURE">EVOLUTION STUDIED USING PROTEIN STRUCTURE</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="34408923" href="https://independent.academia.edu/RubenValas">Ruben Valas</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2000</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" 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href="https://www.academia.edu/25459675/Novel_strategies_to_study_the_role_of_mutation_and_nucleic_acid_structure_in_evolution"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="4" data-entity-id="2904206" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/2904206/Biological_evolution_distribution_and_convergence_analysis_of_amino_acids">Biological evolution: distribution and convergence analysis of amino acids</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="3347370" href="https://uic.academia.edu/DSchonfeld">Dan Schonfeld</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2006</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Biological evolution: distribution and convergence analysis of amino acids&quot;,&quot;attachmentId&quot;:50542885,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/2904206/Biological_evolution_distribution_and_convergence_analysis_of_amino_acids&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/2904206/Biological_evolution_distribution_and_convergence_analysis_of_amino_acids"><span class="ds2-5-text-link__content">View 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