Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (Arachis hypogaea L.)
The genetic architecture determinants of yield traits in peanut ( Arachis hypogaea L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loc...
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| Veröffentlicht in: | Molecular breeding 2017-02, Vol.37 (2), p.17-14, Article 17 |
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| creator | Chen, Yuning Ren, Xiaoping Zheng, Yanli Zhou, Xiaojing Huang, Li Yan, Liying Jiao, Yongqing Chen, Weigang Huang, Shunmou Wan, Liyun Lei, Yong Liao, Boshou Huai, Dongxin Wei, Wenhui Jiang, Huifang |
| description | The genetic architecture determinants of yield traits in peanut (
Arachis hypogaea
L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of
Arachis
. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. The trait-by-trait meta-analysis revealed 33 consensus QTLs. The consensus QTLs and other QTLs were further integrated into 29 pleiotropic unique QTLs with the confidence interval of 1.86 cM on average. The significant co-localization of QTLs was consistent with the significant phenotypic correlations among these traits. The complexity of the genetic architecture of yield traits was demonstrated. The present QTLs for pod- and seed-related traits could be the most fundamental genetic factors contributing to the yield traits in peanut. The results provide a good foundation for fine mapping, cloning and designing molecular breeding of favorable genes in peanut. |
| doi_str_mv | 10.1007/s11032-016-0587-3 |
| format | Article |
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Arachis hypogaea
L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of
Arachis
. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. The trait-by-trait meta-analysis revealed 33 consensus QTLs. The consensus QTLs and other QTLs were further integrated into 29 pleiotropic unique QTLs with the confidence interval of 1.86 cM on average. The significant co-localization of QTLs was consistent with the significant phenotypic correlations among these traits. The complexity of the genetic architecture of yield traits was demonstrated. The present QTLs for pod- and seed-related traits could be the most fundamental genetic factors contributing to the yield traits in peanut. The results provide a good foundation for fine mapping, cloning and designing molecular breeding of favorable genes in peanut.</description><identifier>ISSN: 1380-3743</identifier><identifier>EISSN: 1572-9788</identifier><identifier>DOI: 10.1007/s11032-016-0587-3</identifier><identifier>PMID: 28216998</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Arachis hypogaea ; Architecture ; Biomedical and Life Sciences ; Biotechnology ; chromosome mapping ; Cloning ; Collinearity ; confidence interval ; Confidence intervals ; crop yield ; diploidy ; Gene loci ; Gene mapping ; genes ; Genetic factors ; inbred lines ; Inbreeding ; Legumes ; Life Sciences ; Localization ; loci ; Mapping ; Marker-assisted selection ; meta-analysis ; Molecular biology ; Peanuts ; phenotypic correlation ; phenotypic variation ; Phenotypic variations ; Plant biology ; Plant Genetics and Genomics ; Plant Pathology ; Plant Physiology ; Plant Sciences ; Quantitative trait loci</subject><ispartof>Molecular breeding, 2017-02, Vol.37 (2), p.17-14, Article 17</ispartof><rights>The Author(s) 2017</rights><rights>Copyright Springer Science & Business Media 2017</rights><rights>Molecular Breeding is a copyright of Springer, (2017). All Rights Reserved. © 2017. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c531t-44c0dcfb482d8ce4530f5c4d393ea716fc12ccadf7dbfebc01d3d82266163cfb3</citedby><cites>FETCH-LOGICAL-c531t-44c0dcfb482d8ce4530f5c4d393ea716fc12ccadf7dbfebc01d3d82266163cfb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11032-016-0587-3$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11032-016-0587-3$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28216998$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, Yuning</creatorcontrib><creatorcontrib>Ren, Xiaoping</creatorcontrib><creatorcontrib>Zheng, Yanli</creatorcontrib><creatorcontrib>Zhou, Xiaojing</creatorcontrib><creatorcontrib>Huang, Li</creatorcontrib><creatorcontrib>Yan, Liying</creatorcontrib><creatorcontrib>Jiao, Yongqing</creatorcontrib><creatorcontrib>Chen, Weigang</creatorcontrib><creatorcontrib>Huang, Shunmou</creatorcontrib><creatorcontrib>Wan, Liyun</creatorcontrib><creatorcontrib>Lei, Yong</creatorcontrib><creatorcontrib>Liao, Boshou</creatorcontrib><creatorcontrib>Huai, Dongxin</creatorcontrib><creatorcontrib>Wei, Wenhui</creatorcontrib><creatorcontrib>Jiang, Huifang</creatorcontrib><title>Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (Arachis hypogaea L.)</title><title>Molecular breeding</title><addtitle>Mol Breeding</addtitle><addtitle>Mol Breed</addtitle><description>The genetic architecture determinants of yield traits in peanut (
Arachis hypogaea
L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of
Arachis
. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. The trait-by-trait meta-analysis revealed 33 consensus QTLs. The consensus QTLs and other QTLs were further integrated into 29 pleiotropic unique QTLs with the confidence interval of 1.86 cM on average. The significant co-localization of QTLs was consistent with the significant phenotypic correlations among these traits. The complexity of the genetic architecture of yield traits was demonstrated. The present QTLs for pod- and seed-related traits could be the most fundamental genetic factors contributing to the yield traits in peanut. The results provide a good foundation for fine mapping, cloning and designing molecular breeding of favorable genes in peanut.</description><subject>Arachis hypogaea</subject><subject>Architecture</subject><subject>Biomedical and Life Sciences</subject><subject>Biotechnology</subject><subject>chromosome mapping</subject><subject>Cloning</subject><subject>Collinearity</subject><subject>confidence interval</subject><subject>Confidence intervals</subject><subject>crop yield</subject><subject>diploidy</subject><subject>Gene loci</subject><subject>Gene mapping</subject><subject>genes</subject><subject>Genetic factors</subject><subject>inbred lines</subject><subject>Inbreeding</subject><subject>Legumes</subject><subject>Life Sciences</subject><subject>Localization</subject><subject>loci</subject><subject>Mapping</subject><subject>Marker-assisted selection</subject><subject>meta-analysis</subject><subject>Molecular biology</subject><subject>Peanuts</subject><subject>phenotypic correlation</subject><subject>phenotypic variation</subject><subject>Phenotypic variations</subject><subject>Plant biology</subject><subject>Plant Genetics and Genomics</subject><subject>Plant Pathology</subject><subject>Plant Physiology</subject><subject>Plant Sciences</subject><subject>Quantitative trait loci</subject><issn>1380-3743</issn><issn>1572-9788</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkt9rFDEQxxdRbK3-Ab5IwJf2YWt-J_silLM9Dw4E0eeQS7K3KbvJmuwW7q1_ulmuliqoTxMyn_kOM_OtqrcIXiIIxYeMECS4hojXkElRk2fVKWIC142Q8nl5EwlrIig5qV7lfAtLTcP5y-oES4x408jT6n7tgpu8AYMeRx_2ILbg4F1vwZS0nzKY8_L7dbMFYxznXk8-BmBd8nfOgjbFAdzMppt1AJ90CblzBdfBgs1qzYlgi-DodJgncH6VtOl8Bt1hjHvtNNheXryuXrS6z-7NQzyrvt9cf1t9rrdf1pvV1bY2jKCpptRAa9odldhK4ygjsGWGWtIQpwXirUHYGG1bYXet2xmILLESY84RJ6WOnFUfj7rjvBucNS6UAXs1Jj_odFBRe_V7JvhO7eOdYlgyipoicP4gkOKP2eVJDT4b1_c6uDhnhct6GZGU4f-iSArIKSyHKej7P9DbOKdQNqEwZg0tJGP_opCUUDCGG14odKRMijkn1z5Oh6BaDKOOhlHFMGoxjFr6v3u6lseKXw4pAD4CuaTC3qUnrf-q-hOVsMsL</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Chen, Yuning</creator><creator>Ren, Xiaoping</creator><creator>Zheng, Yanli</creator><creator>Zhou, Xiaojing</creator><creator>Huang, Li</creator><creator>Yan, Liying</creator><creator>Jiao, Yongqing</creator><creator>Chen, Weigang</creator><creator>Huang, Shunmou</creator><creator>Wan, Liyun</creator><creator>Lei, Yong</creator><creator>Liao, Boshou</creator><creator>Huai, Dongxin</creator><creator>Wei, Wenhui</creator><creator>Jiang, Huifang</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X2</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</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>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M0K</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><scope>5PM</scope></search><sort><creationdate>20170201</creationdate><title>Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (Arachis hypogaea L.)</title><author>Chen, Yuning ; Ren, Xiaoping ; Zheng, Yanli ; Zhou, Xiaojing ; Huang, Li ; Yan, Liying ; Jiao, Yongqing ; Chen, Weigang ; Huang, Shunmou ; Wan, Liyun ; Lei, Yong ; Liao, Boshou ; Huai, Dongxin ; Wei, Wenhui ; Jiang, Huifang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c531t-44c0dcfb482d8ce4530f5c4d393ea716fc12ccadf7dbfebc01d3d82266163cfb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Arachis hypogaea</topic><topic>Architecture</topic><topic>Biomedical and Life Sciences</topic><topic>Biotechnology</topic><topic>chromosome mapping</topic><topic>Cloning</topic><topic>Collinearity</topic><topic>confidence interval</topic><topic>Confidence intervals</topic><topic>crop yield</topic><topic>diploidy</topic><topic>Gene loci</topic><topic>Gene mapping</topic><topic>genes</topic><topic>Genetic factors</topic><topic>inbred lines</topic><topic>Inbreeding</topic><topic>Legumes</topic><topic>Life Sciences</topic><topic>Localization</topic><topic>loci</topic><topic>Mapping</topic><topic>Marker-assisted selection</topic><topic>meta-analysis</topic><topic>Molecular biology</topic><topic>Peanuts</topic><topic>phenotypic correlation</topic><topic>phenotypic variation</topic><topic>Phenotypic variations</topic><topic>Plant biology</topic><topic>Plant Genetics and Genomics</topic><topic>Plant Pathology</topic><topic>Plant Physiology</topic><topic>Plant Sciences</topic><topic>Quantitative trait loci</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Yuning</creatorcontrib><creatorcontrib>Ren, Xiaoping</creatorcontrib><creatorcontrib>Zheng, Yanli</creatorcontrib><creatorcontrib>Zhou, Xiaojing</creatorcontrib><creatorcontrib>Huang, Li</creatorcontrib><creatorcontrib>Yan, Liying</creatorcontrib><creatorcontrib>Jiao, Yongqing</creatorcontrib><creatorcontrib>Chen, Weigang</creatorcontrib><creatorcontrib>Huang, Shunmou</creatorcontrib><creatorcontrib>Wan, Liyun</creatorcontrib><creatorcontrib>Lei, Yong</creatorcontrib><creatorcontrib>Liao, Boshou</creatorcontrib><creatorcontrib>Huai, Dongxin</creatorcontrib><creatorcontrib>Wei, Wenhui</creatorcontrib><creatorcontrib>Jiang, Huifang</creatorcontrib><collection>Springer Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</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>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Biological Sciences</collection><collection>Agriculture Science Database</collection><collection>Biological Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Molecular breeding</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Yuning</au><au>Ren, Xiaoping</au><au>Zheng, Yanli</au><au>Zhou, Xiaojing</au><au>Huang, Li</au><au>Yan, Liying</au><au>Jiao, Yongqing</au><au>Chen, Weigang</au><au>Huang, Shunmou</au><au>Wan, Liyun</au><au>Lei, Yong</au><au>Liao, Boshou</au><au>Huai, Dongxin</au><au>Wei, Wenhui</au><au>Jiang, Huifang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (Arachis hypogaea L.)</atitle><jtitle>Molecular breeding</jtitle><stitle>Mol Breeding</stitle><addtitle>Mol Breed</addtitle><date>2017-02-01</date><risdate>2017</risdate><volume>37</volume><issue>2</issue><spage>17</spage><epage>14</epage><pages>17-14</pages><artnum>17</artnum><issn>1380-3743</issn><eissn>1572-9788</eissn><abstract>The genetic architecture determinants of yield traits in peanut (
Arachis hypogaea
L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of
Arachis
. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. The trait-by-trait meta-analysis revealed 33 consensus QTLs. The consensus QTLs and other QTLs were further integrated into 29 pleiotropic unique QTLs with the confidence interval of 1.86 cM on average. The significant co-localization of QTLs was consistent with the significant phenotypic correlations among these traits. The complexity of the genetic architecture of yield traits was demonstrated. The present QTLs for pod- and seed-related traits could be the most fundamental genetic factors contributing to the yield traits in peanut. The results provide a good foundation for fine mapping, cloning and designing molecular breeding of favorable genes in peanut.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>28216998</pmid><doi>10.1007/s11032-016-0587-3</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Molecular breeding, 2017-02, Vol.37 (2), p.17-14, Article 17 |
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| source | Springer Online Journals |
| subjects | Arachis hypogaea Architecture Biomedical and Life Sciences Biotechnology chromosome mapping Cloning Collinearity confidence interval Confidence intervals crop yield diploidy Gene loci Gene mapping genes Genetic factors inbred lines Inbreeding Legumes Life Sciences Localization loci Mapping Marker-assisted selection meta-analysis Molecular biology Peanuts phenotypic correlation phenotypic variation Phenotypic variations Plant biology Plant Genetics and Genomics Plant Pathology Plant Physiology Plant Sciences Quantitative trait loci |
| title | Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (Arachis hypogaea L.) |
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