Loading…
Inferring the age of a fixed beneficial allele
Estimating the age and strength of beneficial alleles is central to understanding how adaptation proceeds in response to changing environmental conditions. Several haplotype‐based estimators exist for inferring the age of segregating beneficial mutations. Here, we develop an approximate Bayesian‐bas...
Saved in:
Published in: | Molecular ecology 2016-01, Vol.25 (1), p.157-169 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c5188-8fac0535355d3b83a4aecefed8712a4504affdf9d699ff209baa7eb50f74b7223 |
---|---|
cites | cdi_FETCH-LOGICAL-c5188-8fac0535355d3b83a4aecefed8712a4504affdf9d699ff209baa7eb50f74b7223 |
container_end_page | 169 |
container_issue | 1 |
container_start_page | 157 |
container_title | Molecular ecology |
container_volume | 25 |
creator | Ormond, Louise Foll, Matthieu Ewing, Gregory B Pfeifer, Susanne P Jensen, Jeffrey D |
description | Estimating the age and strength of beneficial alleles is central to understanding how adaptation proceeds in response to changing environmental conditions. Several haplotype‐based estimators exist for inferring the age of segregating beneficial mutations. Here, we develop an approximate Bayesian‐based approach that rather estimates these parameters for fixed beneficial mutations in single populations. We integrate a range of existing diversity, site frequency spectrum, haplotype‐ and linkage disequilibrium‐based summary statistics. We show that for strong selective sweeps on de novo mutations the method can estimate allele age and selection strength even in nonequilibrium demographic scenarios. We extend our approach to models of selection on standing variation, and co‐infer the frequency at which selection began to act upon the mutation. Finally, we apply our method to estimate the age and selection strength of a previously identified mutation underpinning cryptic colour adaptation in a wild deer mouse population, and compare our findings with previously published estimates as well as with geological data pertaining to the presumed shift in selective pressure. |
doi_str_mv | 10.1111/mec.13478 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1782212945</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1782212945</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5188-8fac0535355d3b83a4aecefed8712a4504affdf9d699ff209baa7eb50f74b7223</originalsourceid><addsrcrecordid>eNqN0E1vEzEQBmALFdG0cOgfKCtxaQ-b-tveI4pKKQpwKBWIizW7Ow5uN7vBTkTy73HZtgekSvUcfHnmleYl5IjRKcvvbInNlAlp7AsyYUKrklfyxx6Z0ErzklEr9slBSjeUMsGVekX2uVZGGyUnZHrZe4wx9Iti_QsLWGAx-AIKH7bYFjX26EMToCug67DD1-Slhy7hm_v_kFx_OP82-1jOv15czt7Py0Yxa0vroaFK5FGtqK0ACdigx9YaxkEqKsH71letrirvOa1qAIO1ot7I2nAuDsnJmLuKw-8NprVbhtRg10GPwyY5ZiznLJ-pnkGN1poZxTJ99x-9GTaxz4dkpaQWUkmR1emomjikFNG7VQxLiDvHqLvr2-W-3b--sz2-T9zUS2wf5UPBGZyN4E_ocPd0kvt8PnuILMeNkNa4fdyAeOu0EUa5718unFU_r-aV0O5T9m9H72FwsIghuesrTpmmlFZU5Kv-AqgWnuo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1754634543</pqid></control><display><type>article</type><title>Inferring the age of a fixed beneficial allele</title><source>Wiley-Blackwell Read & Publish Collection</source><creator>Ormond, Louise ; Foll, Matthieu ; Ewing, Gregory B ; Pfeifer, Susanne P ; Jensen, Jeffrey D</creator><creatorcontrib>Ormond, Louise ; Foll, Matthieu ; Ewing, Gregory B ; Pfeifer, Susanne P ; Jensen, Jeffrey D</creatorcontrib><description>Estimating the age and strength of beneficial alleles is central to understanding how adaptation proceeds in response to changing environmental conditions. Several haplotype‐based estimators exist for inferring the age of segregating beneficial mutations. Here, we develop an approximate Bayesian‐based approach that rather estimates these parameters for fixed beneficial mutations in single populations. We integrate a range of existing diversity, site frequency spectrum, haplotype‐ and linkage disequilibrium‐based summary statistics. We show that for strong selective sweeps on de novo mutations the method can estimate allele age and selection strength even in nonequilibrium demographic scenarios. We extend our approach to models of selection on standing variation, and co‐infer the frequency at which selection began to act upon the mutation. Finally, we apply our method to estimate the age and selection strength of a previously identified mutation underpinning cryptic colour adaptation in a wild deer mouse population, and compare our findings with previously published estimates as well as with geological data pertaining to the presumed shift in selective pressure.</description><identifier>ISSN: 0962-1083</identifier><identifier>EISSN: 1365-294X</identifier><identifier>DOI: 10.1111/mec.13478</identifier><identifier>PMID: 26576754</identifier><language>eng</language><publisher>England: Blackwell Scientific Publications</publisher><subject>adaptation ; Adaptation, Biological - genetics ; Age ; age determination ; Alleles ; Animals ; Bayes Theorem ; color ; Computer Simulation ; ecological genetics ; Environmental changes ; Environmental conditions ; environmental factors ; Gene Frequency ; Genetics, Population ; Hair ; Haplotypes ; Linkage Disequilibrium ; Mice - genetics ; Models, Genetic ; Mutation ; Pigmentation - genetics ; population genetics - empirical ; population genetics - theoretical ; statistics</subject><ispartof>Molecular ecology, 2016-01, Vol.25 (1), p.157-169</ispartof><rights>2015 John Wiley & Sons Ltd</rights><rights>2015 John Wiley & Sons Ltd.</rights><rights>Copyright © 2016 John Wiley & Sons Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5188-8fac0535355d3b83a4aecefed8712a4504affdf9d699ff209baa7eb50f74b7223</citedby><cites>FETCH-LOGICAL-c5188-8fac0535355d3b83a4aecefed8712a4504affdf9d699ff209baa7eb50f74b7223</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26576754$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ormond, Louise</creatorcontrib><creatorcontrib>Foll, Matthieu</creatorcontrib><creatorcontrib>Ewing, Gregory B</creatorcontrib><creatorcontrib>Pfeifer, Susanne P</creatorcontrib><creatorcontrib>Jensen, Jeffrey D</creatorcontrib><title>Inferring the age of a fixed beneficial allele</title><title>Molecular ecology</title><addtitle>Mol Ecol</addtitle><description>Estimating the age and strength of beneficial alleles is central to understanding how adaptation proceeds in response to changing environmental conditions. Several haplotype‐based estimators exist for inferring the age of segregating beneficial mutations. Here, we develop an approximate Bayesian‐based approach that rather estimates these parameters for fixed beneficial mutations in single populations. We integrate a range of existing diversity, site frequency spectrum, haplotype‐ and linkage disequilibrium‐based summary statistics. We show that for strong selective sweeps on de novo mutations the method can estimate allele age and selection strength even in nonequilibrium demographic scenarios. We extend our approach to models of selection on standing variation, and co‐infer the frequency at which selection began to act upon the mutation. Finally, we apply our method to estimate the age and selection strength of a previously identified mutation underpinning cryptic colour adaptation in a wild deer mouse population, and compare our findings with previously published estimates as well as with geological data pertaining to the presumed shift in selective pressure.</description><subject>adaptation</subject><subject>Adaptation, Biological - genetics</subject><subject>Age</subject><subject>age determination</subject><subject>Alleles</subject><subject>Animals</subject><subject>Bayes Theorem</subject><subject>color</subject><subject>Computer Simulation</subject><subject>ecological genetics</subject><subject>Environmental changes</subject><subject>Environmental conditions</subject><subject>environmental factors</subject><subject>Gene Frequency</subject><subject>Genetics, Population</subject><subject>Hair</subject><subject>Haplotypes</subject><subject>Linkage Disequilibrium</subject><subject>Mice - genetics</subject><subject>Models, Genetic</subject><subject>Mutation</subject><subject>Pigmentation - genetics</subject><subject>population genetics - empirical</subject><subject>population genetics - theoretical</subject><subject>statistics</subject><issn>0962-1083</issn><issn>1365-294X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqN0E1vEzEQBmALFdG0cOgfKCtxaQ-b-tveI4pKKQpwKBWIizW7Ow5uN7vBTkTy73HZtgekSvUcfHnmleYl5IjRKcvvbInNlAlp7AsyYUKrklfyxx6Z0ErzklEr9slBSjeUMsGVekX2uVZGGyUnZHrZe4wx9Iti_QsLWGAx-AIKH7bYFjX26EMToCug67DD1-Slhy7hm_v_kFx_OP82-1jOv15czt7Py0Yxa0vroaFK5FGtqK0ACdigx9YaxkEqKsH71letrirvOa1qAIO1ot7I2nAuDsnJmLuKw-8NprVbhtRg10GPwyY5ZiznLJ-pnkGN1poZxTJ99x-9GTaxz4dkpaQWUkmR1emomjikFNG7VQxLiDvHqLvr2-W-3b--sz2-T9zUS2wf5UPBGZyN4E_ocPd0kvt8PnuILMeNkNa4fdyAeOu0EUa5718unFU_r-aV0O5T9m9H72FwsIghuesrTpmmlFZU5Kv-AqgWnuo</recordid><startdate>201601</startdate><enddate>201601</enddate><creator>Ormond, Louise</creator><creator>Foll, Matthieu</creator><creator>Ewing, Gregory B</creator><creator>Pfeifer, Susanne P</creator><creator>Jensen, Jeffrey D</creator><general>Blackwell Scientific Publications</general><general>Blackwell Publishing Ltd</general><scope>FBQ</scope><scope>BSCLL</scope><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></search><sort><creationdate>201601</creationdate><title>Inferring the age of a fixed beneficial allele</title><author>Ormond, Louise ; Foll, Matthieu ; Ewing, Gregory B ; Pfeifer, Susanne P ; Jensen, Jeffrey D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5188-8fac0535355d3b83a4aecefed8712a4504affdf9d699ff209baa7eb50f74b7223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>adaptation</topic><topic>Adaptation, Biological - genetics</topic><topic>Age</topic><topic>age determination</topic><topic>Alleles</topic><topic>Animals</topic><topic>Bayes Theorem</topic><topic>color</topic><topic>Computer Simulation</topic><topic>ecological genetics</topic><topic>Environmental changes</topic><topic>Environmental conditions</topic><topic>environmental factors</topic><topic>Gene Frequency</topic><topic>Genetics, Population</topic><topic>Hair</topic><topic>Haplotypes</topic><topic>Linkage Disequilibrium</topic><topic>Mice - genetics</topic><topic>Models, Genetic</topic><topic>Mutation</topic><topic>Pigmentation - genetics</topic><topic>population genetics - empirical</topic><topic>population genetics - theoretical</topic><topic>statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ormond, Louise</creatorcontrib><creatorcontrib>Foll, Matthieu</creatorcontrib><creatorcontrib>Ewing, Gregory B</creatorcontrib><creatorcontrib>Pfeifer, Susanne P</creatorcontrib><creatorcontrib>Jensen, Jeffrey D</creatorcontrib><collection>AGRIS</collection><collection>Istex</collection><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><jtitle>Molecular ecology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ormond, Louise</au><au>Foll, Matthieu</au><au>Ewing, Gregory B</au><au>Pfeifer, Susanne P</au><au>Jensen, Jeffrey D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Inferring the age of a fixed beneficial allele</atitle><jtitle>Molecular ecology</jtitle><addtitle>Mol Ecol</addtitle><date>2016-01</date><risdate>2016</risdate><volume>25</volume><issue>1</issue><spage>157</spage><epage>169</epage><pages>157-169</pages><issn>0962-1083</issn><eissn>1365-294X</eissn><abstract>Estimating the age and strength of beneficial alleles is central to understanding how adaptation proceeds in response to changing environmental conditions. Several haplotype‐based estimators exist for inferring the age of segregating beneficial mutations. Here, we develop an approximate Bayesian‐based approach that rather estimates these parameters for fixed beneficial mutations in single populations. We integrate a range of existing diversity, site frequency spectrum, haplotype‐ and linkage disequilibrium‐based summary statistics. We show that for strong selective sweeps on de novo mutations the method can estimate allele age and selection strength even in nonequilibrium demographic scenarios. We extend our approach to models of selection on standing variation, and co‐infer the frequency at which selection began to act upon the mutation. Finally, we apply our method to estimate the age and selection strength of a previously identified mutation underpinning cryptic colour adaptation in a wild deer mouse population, and compare our findings with previously published estimates as well as with geological data pertaining to the presumed shift in selective pressure.</abstract><cop>England</cop><pub>Blackwell Scientific Publications</pub><pmid>26576754</pmid><doi>10.1111/mec.13478</doi><tpages>13</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0962-1083 |
ispartof | Molecular ecology, 2016-01, Vol.25 (1), p.157-169 |
issn | 0962-1083 1365-294X |
language | eng |
recordid | cdi_proquest_miscellaneous_1782212945 |
source | Wiley-Blackwell Read & Publish Collection |
subjects | adaptation Adaptation, Biological - genetics Age age determination Alleles Animals Bayes Theorem color Computer Simulation ecological genetics Environmental changes Environmental conditions environmental factors Gene Frequency Genetics, Population Hair Haplotypes Linkage Disequilibrium Mice - genetics Models, Genetic Mutation Pigmentation - genetics population genetics - empirical population genetics - theoretical statistics |
title | Inferring the age of a fixed beneficial allele |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T03%3A26%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Inferring%20the%20age%20of%20a%20fixed%20beneficial%20allele&rft.jtitle=Molecular%20ecology&rft.au=Ormond,%20Louise&rft.date=2016-01&rft.volume=25&rft.issue=1&rft.spage=157&rft.epage=169&rft.pages=157-169&rft.issn=0962-1083&rft.eissn=1365-294X&rft_id=info:doi/10.1111/mec.13478&rft_dat=%3Cproquest_cross%3E1782212945%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c5188-8fac0535355d3b83a4aecefed8712a4504affdf9d699ff209baa7eb50f74b7223%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1754634543&rft_id=info:pmid/26576754&rfr_iscdi=true |