Detection of Quantitative Trait Loci Influencing Recombination Using Recombinant Inbred Lines
The genetic basis of variation in recombination in higher plants is polygenic and poorly understood, despite its theoretical and practical importance. Here a method of detecting quantitative trait loci (QTL) influencing recombination in recombinant inbred lines (RILs) is proposed that relies upon th...
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description | The genetic basis of variation in recombination in higher plants is polygenic and poorly understood, despite its theoretical and practical importance. Here a method of detecting quantitative trait loci (QTL) influencing recombination in recombinant inbred lines (RILs) is proposed that relies upon the fact that genotype data within RILs carry the signature of past recombination. Behavior of the segregational genetic variance in numbers of chromosomal crossovers (recombination) over generations is described for self-, full-sib-, and half-sib-generated RILs with no dominance in true crossovers. This genetic variance, which as a fraction of the total phenotypic variance contributes to the statistical power of the method, was asymptotically greatest with half sibbing, less with sibbing, and least with selfing. The statistical power to detect a recombination QTL declined with diminishing QTL effect, genome target size, and marker density. For reasonably tight marker linkage power was greater with less intense inbreeding for later generations and vice versa for early generations. Generational optima for segregation variance and statistical power were found, whose onset and narrowness varied with marker density and mating design, being more pronounced for looser marker linkage. Application of this method to a maize RIL population derived from inbred lines Mo17 and B73 and developed by selfing suggested two putative QTL (LOD > 2.4) affecting certain chromosomes, and using a canonical transformation another putative QTL was detected. However, permutation tests failed to support their presence (experimentwise alpha = 0.05). Other populations with more statistical power and chosen specifically for recombination QTL segregation would be more effective. |
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Here a method of detecting quantitative trait loci (QTL) influencing recombination in recombinant inbred lines (RILs) is proposed that relies upon the fact that genotype data within RILs carry the signature of past recombination. Behavior of the segregational genetic variance in numbers of chromosomal crossovers (recombination) over generations is described for self-, full-sib-, and half-sib-generated RILs with no dominance in true crossovers. This genetic variance, which as a fraction of the total phenotypic variance contributes to the statistical power of the method, was asymptotically greatest with half sibbing, less with sibbing, and least with selfing. The statistical power to detect a recombination QTL declined with diminishing QTL effect, genome target size, and marker density. For reasonably tight marker linkage power was greater with less intense inbreeding for later generations and vice versa for early generations. Generational optima for segregation variance and statistical power were found, whose onset and narrowness varied with marker density and mating design, being more pronounced for looser marker linkage. Application of this method to a maize RIL population derived from inbred lines Mo17 and B73 and developed by selfing suggested two putative QTL (LOD > 2.4) affecting certain chromosomes, and using a canonical transformation another putative QTL was detected. However, permutation tests failed to support their presence (experimentwise alpha = 0.05). Other populations with more statistical power and chosen specifically for recombination QTL segregation would be more effective.</description><identifier>ISSN: 0016-6731</identifier><identifier>ISSN: 1943-2631</identifier><identifier>EISSN: 1943-2631</identifier><identifier>DOI: 10.1534/genetics.107.076679</identifier><identifier>PMID: 17947433</identifier><identifier>CODEN: GENTAE</identifier><language>eng</language><publisher>United States: Genetics Soc America</publisher><subject>chromosome mapping ; corn ; Gene loci ; genetic markers ; Genetic recombination ; genetic variance ; Genetic Variation ; Genomics ; Genotype ; inbred lines ; Inbreeding ; Investigations ; mathematics and statistics ; Models, Statistical ; phenotypic variation ; Poisson distribution ; quantitative trait loci ; Quantitative Trait Loci - genetics ; recombinant inbred lines ; Recombination, Genetic - genetics ; Zea mays ; Zea mays - genetics</subject><ispartof>Genetics (Austin), 2007-12, Vol.177 (4), p.2309-2319</ispartof><rights>Copyright Genetics Society of America Dec 2007</rights><rights>Copyright © 2007 by the Genetics Society of America</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c486t-d2170677f8418d435548fca3734127308d596f1953c2621c2545a467e6872bc13</citedby><cites>FETCH-LOGICAL-c486t-d2170677f8418d435548fca3734127308d596f1953c2621c2545a467e6872bc13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,777,781,882,27905,27906</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17947433$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dole, J</creatorcontrib><creatorcontrib>Weber, D.F</creatorcontrib><title>Detection of Quantitative Trait Loci Influencing Recombination Using Recombinant Inbred Lines</title><title>Genetics (Austin)</title><addtitle>Genetics</addtitle><description>The genetic basis of variation in recombination in higher plants is polygenic and poorly understood, despite its theoretical and practical importance. Here a method of detecting quantitative trait loci (QTL) influencing recombination in recombinant inbred lines (RILs) is proposed that relies upon the fact that genotype data within RILs carry the signature of past recombination. Behavior of the segregational genetic variance in numbers of chromosomal crossovers (recombination) over generations is described for self-, full-sib-, and half-sib-generated RILs with no dominance in true crossovers. This genetic variance, which as a fraction of the total phenotypic variance contributes to the statistical power of the method, was asymptotically greatest with half sibbing, less with sibbing, and least with selfing. The statistical power to detect a recombination QTL declined with diminishing QTL effect, genome target size, and marker density. For reasonably tight marker linkage power was greater with less intense inbreeding for later generations and vice versa for early generations. Generational optima for segregation variance and statistical power were found, whose onset and narrowness varied with marker density and mating design, being more pronounced for looser marker linkage. Application of this method to a maize RIL population derived from inbred lines Mo17 and B73 and developed by selfing suggested two putative QTL (LOD > 2.4) affecting certain chromosomes, and using a canonical transformation another putative QTL was detected. However, permutation tests failed to support their presence (experimentwise alpha = 0.05). Other populations with more statistical power and chosen specifically for recombination QTL segregation would be more effective.</description><subject>chromosome mapping</subject><subject>corn</subject><subject>Gene loci</subject><subject>genetic markers</subject><subject>Genetic recombination</subject><subject>genetic variance</subject><subject>Genetic Variation</subject><subject>Genomics</subject><subject>Genotype</subject><subject>inbred lines</subject><subject>Inbreeding</subject><subject>Investigations</subject><subject>mathematics and statistics</subject><subject>Models, Statistical</subject><subject>phenotypic variation</subject><subject>Poisson distribution</subject><subject>quantitative trait loci</subject><subject>Quantitative Trait Loci - genetics</subject><subject>recombinant inbred lines</subject><subject>Recombination, Genetic - genetics</subject><subject>Zea mays</subject><subject>Zea mays - genetics</subject><issn>0016-6731</issn><issn>1943-2631</issn><issn>1943-2631</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpdkd1rFDEUxYModlv9CwQdfKhPs-YmmSTzIkj9KiyI2n2UkM1kZlNmkzbJdPG_N-usH_Xpwr2_cziXg9AzwEtoKHs9WG-zM2kJWCyx4Fy0D9ACWkZrwik8RAuMgddcUDhBpyldY4x528jH6AREywSjdIG-v7PZmuyCr0JffZm0zy7r7O5sdRW1y9UqGFdd-n6crDfOD9VXa8Ju47z-JVqnezufC7uJtqtWztv0BD3q9Zjs0-M8Q-sP768uPtWrzx8vL96uasMkz3VHQGAuRC8ZyI7RpmGyN5oKyoAIimXXtLyHtqGGcAKGNKzRjAvLpSAbA_QMvZl9b6bNznbG-hz1qG6i2-n4QwXt1P2Ld1s1hDtFSHEFXgzOjwYx3E42ZbVzydhx1N6GKSneYi4JlwV8-R94Haboy3OKQEnbcnGIQ2fIxJBStP2fJIDVoTv1u7uyEGrurqie__vEX82xrAK8moGtG7Z7F61KOz2OBQe13-9BCMUUofhg9WImex2UHqJLav2NYKAYS84I5fQnxNGt0w</recordid><startdate>20071201</startdate><enddate>20071201</enddate><creator>Dole, J</creator><creator>Weber, D.F</creator><general>Genetics Soc America</general><general>Genetics Society of America</general><scope>FBQ</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>3V.</scope><scope>4T-</scope><scope>4U-</scope><scope>7QP</scope><scope>7SS</scope><scope>7TK</scope><scope>7TM</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>K9-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0K</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M2P</scope><scope>M7N</scope><scope>M7P</scope><scope>MBDVC</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20071201</creationdate><title>Detection of Quantitative Trait Loci Influencing Recombination Using Recombinant Inbred Lines</title><author>Dole, J ; Weber, D.F</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c486t-d2170677f8418d435548fca3734127308d596f1953c2621c2545a467e6872bc13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>chromosome mapping</topic><topic>corn</topic><topic>Gene loci</topic><topic>genetic markers</topic><topic>Genetic recombination</topic><topic>genetic variance</topic><topic>Genetic Variation</topic><topic>Genomics</topic><topic>Genotype</topic><topic>inbred lines</topic><topic>Inbreeding</topic><topic>Investigations</topic><topic>mathematics and statistics</topic><topic>Models, Statistical</topic><topic>phenotypic variation</topic><topic>Poisson distribution</topic><topic>quantitative trait loci</topic><topic>Quantitative Trait Loci - genetics</topic><topic>recombinant inbred lines</topic><topic>Recombination, Genetic - genetics</topic><topic>Zea mays</topic><topic>Zea mays - genetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dole, J</creatorcontrib><creatorcontrib>Weber, D.F</creatorcontrib><collection>AGRIS</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Docstoc</collection><collection>University Readers</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Genetics (Austin)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dole, J</au><au>Weber, D.F</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detection of Quantitative Trait Loci Influencing Recombination Using Recombinant Inbred Lines</atitle><jtitle>Genetics (Austin)</jtitle><addtitle>Genetics</addtitle><date>2007-12-01</date><risdate>2007</risdate><volume>177</volume><issue>4</issue><spage>2309</spage><epage>2319</epage><pages>2309-2319</pages><issn>0016-6731</issn><issn>1943-2631</issn><eissn>1943-2631</eissn><coden>GENTAE</coden><abstract>The genetic basis of variation in recombination in higher plants is polygenic and poorly understood, despite its theoretical and practical importance. Here a method of detecting quantitative trait loci (QTL) influencing recombination in recombinant inbred lines (RILs) is proposed that relies upon the fact that genotype data within RILs carry the signature of past recombination. Behavior of the segregational genetic variance in numbers of chromosomal crossovers (recombination) over generations is described for self-, full-sib-, and half-sib-generated RILs with no dominance in true crossovers. This genetic variance, which as a fraction of the total phenotypic variance contributes to the statistical power of the method, was asymptotically greatest with half sibbing, less with sibbing, and least with selfing. The statistical power to detect a recombination QTL declined with diminishing QTL effect, genome target size, and marker density. For reasonably tight marker linkage power was greater with less intense inbreeding for later generations and vice versa for early generations. Generational optima for segregation variance and statistical power were found, whose onset and narrowness varied with marker density and mating design, being more pronounced for looser marker linkage. Application of this method to a maize RIL population derived from inbred lines Mo17 and B73 and developed by selfing suggested two putative QTL (LOD > 2.4) affecting certain chromosomes, and using a canonical transformation another putative QTL was detected. However, permutation tests failed to support their presence (experimentwise alpha = 0.05). Other populations with more statistical power and chosen specifically for recombination QTL segregation would be more effective.</abstract><cop>United States</cop><pub>Genetics Soc America</pub><pmid>17947433</pmid><doi>10.1534/genetics.107.076679</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | chromosome mapping corn Gene loci genetic markers Genetic recombination genetic variance Genetic Variation Genomics Genotype inbred lines Inbreeding Investigations mathematics and statistics Models, Statistical phenotypic variation Poisson distribution quantitative trait loci Quantitative Trait Loci - genetics recombinant inbred lines Recombination, Genetic - genetics Zea mays Zea mays - genetics |
title | Detection of Quantitative Trait Loci Influencing Recombination Using Recombinant Inbred Lines |
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