Shared quantitative trait loci underlying the genetic correlation between continuous traits
We review genetic correlations among quantitative traits in light of their underlying quantitative trait loci (QTL). We derive an expectation of genetic correlation from the effects of underlying loci and test whether published genetic correlations can be explained by the QTL underlying the traits....
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Veröffentlicht in: | Molecular ecology 2007-10, Vol.16 (20), p.4195-4209 |
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description | We review genetic correlations among quantitative traits in light of their underlying quantitative trait loci (QTL). We derive an expectation of genetic correlation from the effects of underlying loci and test whether published genetic correlations can be explained by the QTL underlying the traits. While genetically correlated traits shared more QTL (33%) on average than uncorrelated traits (11%), the actual number of shared QTL shared was small. QTL usually predicted the sign of the correlation with good accuracy, but the quantitative prediction was poor. Approximately 25% of trait pairs in the data set had at least one QTL with antagonistic effects. Yet a significant minority (20%) of such trait pairs have net positive genetic correlations due to such antagonistic QTL 'hidden' within positive genetic correlations. We review the evidence on whether shared QTL represent single pleiotropic loci or closely linked monotropic genes, and argue that strict pleiotropy can be viewed as one end of a continuum of recombination rates where r = 0. QTL studies of genetic correlation will likely be insufficient to predict evolutionary trajectories over long time spans in large panmictic populations, but will provide important insights into the trade-offs involved in population and species divergence. |
doi_str_mv | 10.1111/j.1365-294X.2007.03499.x |
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We derive an expectation of genetic correlation from the effects of underlying loci and test whether published genetic correlations can be explained by the QTL underlying the traits. While genetically correlated traits shared more QTL (33%) on average than uncorrelated traits (11%), the actual number of shared QTL shared was small. QTL usually predicted the sign of the correlation with good accuracy, but the quantitative prediction was poor. Approximately 25% of trait pairs in the data set had at least one QTL with antagonistic effects. Yet a significant minority (20%) of such trait pairs have net positive genetic correlations due to such antagonistic QTL 'hidden' within positive genetic correlations. We review the evidence on whether shared QTL represent single pleiotropic loci or closely linked monotropic genes, and argue that strict pleiotropy can be viewed as one end of a continuum of recombination rates where r = 0. QTL studies of genetic correlation will likely be insufficient to predict evolutionary trajectories over long time spans in large panmictic populations, but will provide important insights into the trade-offs involved in population and species divergence.</description><subject>antagonistic pleiotropy</subject><subject>constraint</subject><subject>genetic correlation</subject><subject>Genetic Speciation</subject><subject>Genetic Variation</subject><subject>linkage</subject><subject>Linkage Disequilibrium - genetics</subject><subject>Models, Genetic</subject><subject>Plants - classification</subject><subject>Plants - genetics</subject><subject>Quantitative Trait Loci - genetics</subject><subject>trade-off</subject><issn>0962-1083</issn><issn>1365-294X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkktv1DAUhS0EokPhL0BW7BL8zGPBAg3tUKmURVsVwcJy7Ouph0zS2g6d-fd1yKgswRv72t85tu4xQhnBBUnjw6YgrBQ5bfj3gmJcFZjxpil2z9Di6eA5WuCmpDnBNTtCr0LYYEwYFeIlOiJVLTCt6AL9vLxVHkx2P6o-uqii-w1Z9MrFrBu0y8begO_2rl9n8RayNfQQnc704D10iR76rIX4ANCnveTQj8MYZoPwGr2wqgvw5jAfo-vTk6vll_z82-ps-ek814LgJm_AECAAQjOhS01aJqARWuiat8waA2AqaK2yqWgFAWMJsSBMiSkX1lB2jN7Pvnd-uB8hRLl1QUPXqR7Sa2RZM05Ixf8JUlxy2lQ4gfUMaj-E4MHKO--2yu8lwXJKQG7k1Gg5NVpOCcg_Cchdkr493DG2WzB_hYeWJ-DjDDy4Dvb_bSy_niynVdLns96FCLsnvfK_ZFmxSsibi5XkPz6vmquLU3mT-Hczb9Ug1dq7IK8vafoKGNcEE16yR8ARsOA</recordid><startdate>200710</startdate><enddate>200710</enddate><creator>GARDNER, KYLE M</creator><creator>LATTA, ROBERT G</creator><general>Oxford, UK : Blackwell Publishing Ltd</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>7ST</scope><scope>7U6</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>200710</creationdate><title>Shared quantitative trait loci underlying the genetic correlation between continuous traits</title><author>GARDNER, KYLE M ; LATTA, ROBERT G</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5109-9ed1e1ee5c35c6c1b35e95c5c84b3fddeed7ebfaf3fdb51edf11fe5d60245fd23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>antagonistic pleiotropy</topic><topic>constraint</topic><topic>genetic correlation</topic><topic>Genetic Speciation</topic><topic>Genetic Variation</topic><topic>linkage</topic><topic>Linkage Disequilibrium - genetics</topic><topic>Models, Genetic</topic><topic>Plants - classification</topic><topic>Plants - genetics</topic><topic>Quantitative Trait Loci - genetics</topic><topic>trade-off</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>GARDNER, KYLE M</creatorcontrib><creatorcontrib>LATTA, ROBERT G</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>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</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>GARDNER, KYLE M</au><au>LATTA, ROBERT G</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Shared quantitative trait loci underlying the genetic correlation between continuous traits</atitle><jtitle>Molecular ecology</jtitle><addtitle>Mol Ecol</addtitle><date>2007-10</date><risdate>2007</risdate><volume>16</volume><issue>20</issue><spage>4195</spage><epage>4209</epage><pages>4195-4209</pages><issn>0962-1083</issn><eissn>1365-294X</eissn><abstract>We review genetic correlations among quantitative traits in light of their underlying quantitative trait loci (QTL). We derive an expectation of genetic correlation from the effects of underlying loci and test whether published genetic correlations can be explained by the QTL underlying the traits. While genetically correlated traits shared more QTL (33%) on average than uncorrelated traits (11%), the actual number of shared QTL shared was small. QTL usually predicted the sign of the correlation with good accuracy, but the quantitative prediction was poor. Approximately 25% of trait pairs in the data set had at least one QTL with antagonistic effects. Yet a significant minority (20%) of such trait pairs have net positive genetic correlations due to such antagonistic QTL 'hidden' within positive genetic correlations. We review the evidence on whether shared QTL represent single pleiotropic loci or closely linked monotropic genes, and argue that strict pleiotropy can be viewed as one end of a continuum of recombination rates where r = 0. QTL studies of genetic correlation will likely be insufficient to predict evolutionary trajectories over long time spans in large panmictic populations, but will provide important insights into the trade-offs involved in population and species divergence.</abstract><cop>Oxford, UK</cop><pub>Oxford, UK : Blackwell Publishing Ltd</pub><pmid>17850272</pmid><doi>10.1111/j.1365-294X.2007.03499.x</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | antagonistic pleiotropy constraint genetic correlation Genetic Speciation Genetic Variation linkage Linkage Disequilibrium - genetics Models, Genetic Plants - classification Plants - genetics Quantitative Trait Loci - genetics trade-off |
title | Shared quantitative trait loci underlying the genetic correlation between continuous traits |
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