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Tree‐sequence recording in SLiM opens new horizons for forward‐time simulation of whole genomes
There is an increasing demand for evolutionary models to incorporate relatively realistic dynamics, ranging from selection at many genomic sites to complex demography, population structure, and ecological interactions. Such models can generally be implemented as individual‐based forward simulations,...
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Published in: | Molecular ecology resources 2019-03, Vol.19 (2), p.552-566 |
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description | There is an increasing demand for evolutionary models to incorporate relatively realistic dynamics, ranging from selection at many genomic sites to complex demography, population structure, and ecological interactions. Such models can generally be implemented as individual‐based forward simulations, but the large computational overhead of these models often makes simulation of whole chromosome sequences in large populations infeasible. This situation presents an important obstacle to the field that requires conceptual advances to overcome. The recently developed tree‐sequence recording method (Kelleher, Thornton, Ashander, & Ralph, 2018), which stores the genealogical history of all genomes in the simulated population, could provide such an advance. This method has several benefits: (1) it allows neutral mutations to be omitted entirely from forward‐time simulations and added later, thereby dramatically improving computational efficiency; (2) it allows neutral burn‐in to be constructed extremely efficiently after the fact, using “recapitation”; (3) it allows direct examination and analysis of the genealogical trees along the genome; and (4) it provides a compact representation of a population's genealogy that can be analysed in Python using the msprime package. We have implemented the tree‐sequence recording method in SLiM 3 (a free, open‐source evolutionary simulation software package) and extended it to allow the recording of non‐neutral mutations, greatly broadening the utility of this method. To demonstrate the versatility and performance of this approach, we showcase several practical applications that would have been beyond the reach of previously existing methods, opening up new horizons for the modelling and exploration of evolutionary processes. |
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Such models can generally be implemented as individual‐based forward simulations, but the large computational overhead of these models often makes simulation of whole chromosome sequences in large populations infeasible. This situation presents an important obstacle to the field that requires conceptual advances to overcome. The recently developed tree‐sequence recording method (Kelleher, Thornton, Ashander, & Ralph, 2018), which stores the genealogical history of all genomes in the simulated population, could provide such an advance. This method has several benefits: (1) it allows neutral mutations to be omitted entirely from forward‐time simulations and added later, thereby dramatically improving computational efficiency; (2) it allows neutral burn‐in to be constructed extremely efficiently after the fact, using “recapitation”; (3) it allows direct examination and analysis of the genealogical trees along the genome; and (4) it provides a compact representation of a population's genealogy that can be analysed in Python using the msprime package. We have implemented the tree‐sequence recording method in SLiM 3 (a free, open‐source evolutionary simulation software package) and extended it to allow the recording of non‐neutral mutations, greatly broadening the utility of this method. 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Such models can generally be implemented as individual‐based forward simulations, but the large computational overhead of these models often makes simulation of whole chromosome sequences in large populations infeasible. This situation presents an important obstacle to the field that requires conceptual advances to overcome. The recently developed tree‐sequence recording method (Kelleher, Thornton, Ashander, & Ralph, 2018), which stores the genealogical history of all genomes in the simulated population, could provide such an advance. This method has several benefits: (1) it allows neutral mutations to be omitted entirely from forward‐time simulations and added later, thereby dramatically improving computational efficiency; (2) it allows neutral burn‐in to be constructed extremely efficiently after the fact, using “recapitation”; (3) it allows direct examination and analysis of the genealogical trees along the genome; and (4) it provides a compact representation of a population's genealogy that can be analysed in Python using the msprime package. We have implemented the tree‐sequence recording method in SLiM 3 (a free, open‐source evolutionary simulation software package) and extended it to allow the recording of non‐neutral mutations, greatly broadening the utility of this method. To demonstrate the versatility and performance of this approach, we showcase several practical applications that would have been beyond the reach of previously existing methods, opening up new horizons for the modelling and exploration of evolutionary processes.</description><subject>background selection</subject><subject>Biological Evolution</subject><subject>coalescent</subject><subject>Computational Biology</subject><subject>Computer applications</subject><subject>Computer Simulation</subject><subject>Computing time</subject><subject>Demography</subject><subject>Evolution</subject><subject>genealogical history</subject><subject>Genealogy</subject><subject>Genetics, Population - methods</subject><subject>Genomes</subject><subject>Mathematical models</subject><subject>Mutation</subject><subject>pedigree recording</subject><subject>Population structure</subject><subject>Recording</subject><subject>selective sweeps</subject><subject>Simulation</subject><subject>Software</subject><subject>tree sequences</subject><issn>1755-098X</issn><issn>1755-0998</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNqFkU9PFDEYxhujEUTO3kgTL1wW2k7_XkgMATVZ9CAm3JqZzju7JTPt0u6wwZMfwc_oJ7Hj4ga92KTpv9_ztG8fhN5QckJLO6VKiBkxRp9QZqR-hvZ3O893c32zh17lfEuIJEbxl2ivIkIKrdk-ctcJ4Of3HxnuRggOcAIXU-vDAvuAv8z9FY4rCBkH2OBlTP5bLIsupqlv6tQW7doPgLMfxr5e-xhw7PBmGXvACwhxgPwavejqPsPh43iAvl5eXJ9_mM0_v_94_m4-c1wqPQNZSdYwQhm0laGEM14JoYk0DRiiVasbypVQjDtBoRGKdEoUUctY7TpBqgN0tvVdjc0ArYOwTnVvV8kPdXqwsfb275Pgl3YR762sTEW1KgbHjwYplu_Iazv47KDv6wBxzJZRoYVQhk93vf0HvY1jCqW8QmnJOKO8KtTplnIp5pyg2z2GEjsFaKeI7BSX_R1gURw9rWHH_0msAGILbHwPD__zs1cXn7bGvwCXSKeF</recordid><startdate>201903</startdate><enddate>201903</enddate><creator>Haller, Benjamin C.</creator><creator>Galloway, Jared</creator><creator>Kelleher, Jerome</creator><creator>Messer, Philipp W.</creator><creator>Ralph, Peter L.</creator><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7SS</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-7894-5253</orcidid><orcidid>https://orcid.org/0000-0003-1874-8327</orcidid><orcidid>https://orcid.org/0000-0002-9459-6866</orcidid><orcidid>https://orcid.org/0000-0001-8453-9377</orcidid></search><sort><creationdate>201903</creationdate><title>Tree‐sequence recording in SLiM opens new horizons for forward‐time simulation of whole genomes</title><author>Haller, Benjamin C. ; Galloway, Jared ; Kelleher, Jerome ; Messer, Philipp W. ; Ralph, Peter L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4678-e6362b2012ed39104243558069be9087d8b1475724c51eb570f75e63d22acf503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>background selection</topic><topic>Biological Evolution</topic><topic>coalescent</topic><topic>Computational Biology</topic><topic>Computer applications</topic><topic>Computer Simulation</topic><topic>Computing time</topic><topic>Demography</topic><topic>Evolution</topic><topic>genealogical history</topic><topic>Genealogy</topic><topic>Genetics, Population - methods</topic><topic>Genomes</topic><topic>Mathematical models</topic><topic>Mutation</topic><topic>pedigree recording</topic><topic>Population structure</topic><topic>Recording</topic><topic>selective sweeps</topic><topic>Simulation</topic><topic>Software</topic><topic>tree sequences</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Haller, Benjamin C.</creatorcontrib><creatorcontrib>Galloway, Jared</creatorcontrib><creatorcontrib>Kelleher, Jerome</creatorcontrib><creatorcontrib>Messer, Philipp W.</creatorcontrib><creatorcontrib>Ralph, Peter L.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Molecular ecology resources</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Haller, Benjamin C.</au><au>Galloway, Jared</au><au>Kelleher, Jerome</au><au>Messer, Philipp W.</au><au>Ralph, Peter L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Tree‐sequence recording in SLiM opens new horizons for forward‐time simulation of whole genomes</atitle><jtitle>Molecular ecology resources</jtitle><addtitle>Mol Ecol Resour</addtitle><date>2019-03</date><risdate>2019</risdate><volume>19</volume><issue>2</issue><spage>552</spage><epage>566</epage><pages>552-566</pages><issn>1755-098X</issn><eissn>1755-0998</eissn><abstract>There is an increasing demand for evolutionary models to incorporate relatively realistic dynamics, ranging from selection at many genomic sites to complex demography, population structure, and ecological interactions. 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This method has several benefits: (1) it allows neutral mutations to be omitted entirely from forward‐time simulations and added later, thereby dramatically improving computational efficiency; (2) it allows neutral burn‐in to be constructed extremely efficiently after the fact, using “recapitation”; (3) it allows direct examination and analysis of the genealogical trees along the genome; and (4) it provides a compact representation of a population's genealogy that can be analysed in Python using the msprime package. We have implemented the tree‐sequence recording method in SLiM 3 (a free, open‐source evolutionary simulation software package) and extended it to allow the recording of non‐neutral mutations, greatly broadening the utility of this method. 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subjects | background selection Biological Evolution coalescent Computational Biology Computer applications Computer Simulation Computing time Demography Evolution genealogical history Genealogy Genetics, Population - methods Genomes Mathematical models Mutation pedigree recording Population structure Recording selective sweeps Simulation Software tree sequences |
title | Tree‐sequence recording in SLiM opens new horizons for forward‐time simulation of whole genomes |
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