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Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus
In the last few years, efforts have been made to identify large effect QTL for grain yield under drought in rice. However, identification of most precise and consistent QTL across the environments and genetics backgrounds is essential for their successful use in Marker-assisted Selection. In this st...
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Published in: | BMC genomics 2011-06, Vol.12 (1), p.319-319, Article 319 |
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description | In the last few years, efforts have been made to identify large effect QTL for grain yield under drought in rice. However, identification of most precise and consistent QTL across the environments and genetics backgrounds is essential for their successful use in Marker-assisted Selection. In this study, an attempt was made to locate consistent QTL regions associated with yield increase under drought by applying a genome-wide QTL meta-analysis approach.
The integration of 15 maps resulted in a consensus map with 531 markers and a total map length of 1821 cM. Fifty-three yield QTL reported in 15 studies were projected on a consensus map and meta-analysis was performed. Fourteen meta-QTL were obtained on seven chromosomes. MQTL1.2, MQTL1.3, MQTL1.4, and MQTL12.1 were around 700 kb and corresponded to a reasonably small genetic distance of 1.8 to 5 cM and they are suitable for use in marker-assisted selection (MAS). The meta-QTL for grain yield under drought coincided with at least one of the meta-QTL identified for root and leaf morphology traits under drought in earlier reports. Validation of major-effect QTL on a panel of random drought-tolerant lines revealed the presence of at least one major QTL in each line. DTY12.1 was present in 85% of the lines, followed by DTY4.1 in 79% and DTY1.1 in 64% of the lines. Comparative genomics of meta-QTL with other cereals revealed that the homologous regions of MQTL1.4 and MQTL3.2 had QTL for grain yield under drought in maize, wheat, and barley respectively. The genes in the meta-QTL regions were analyzed by a comparative genomics approach and candidate genes were deduced for grain yield under drought. Three groups of genes such as stress-inducible genes, growth and development-related genes, and sugar transport-related genes were found in clusters in most of the meta-QTL.
Meta-QTL with small genetic and physical intervals could be useful in Marker-assisted selection individually and in combinations. Validation and comparative genomics of the major-effect QTL confirmed their consistency within and across the species. The shortlisted candidate genes can be cloned to unravel the molecular mechanism regulating grain yield under drought. |
doi_str_mv | 10.1186/1471-2164-12-319 |
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The integration of 15 maps resulted in a consensus map with 531 markers and a total map length of 1821 cM. Fifty-three yield QTL reported in 15 studies were projected on a consensus map and meta-analysis was performed. Fourteen meta-QTL were obtained on seven chromosomes. MQTL1.2, MQTL1.3, MQTL1.4, and MQTL12.1 were around 700 kb and corresponded to a reasonably small genetic distance of 1.8 to 5 cM and they are suitable for use in marker-assisted selection (MAS). The meta-QTL for grain yield under drought coincided with at least one of the meta-QTL identified for root and leaf morphology traits under drought in earlier reports. Validation of major-effect QTL on a panel of random drought-tolerant lines revealed the presence of at least one major QTL in each line. DTY12.1 was present in 85% of the lines, followed by DTY4.1 in 79% and DTY1.1 in 64% of the lines. Comparative genomics of meta-QTL with other cereals revealed that the homologous regions of MQTL1.4 and MQTL3.2 had QTL for grain yield under drought in maize, wheat, and barley respectively. The genes in the meta-QTL regions were analyzed by a comparative genomics approach and candidate genes were deduced for grain yield under drought. Three groups of genes such as stress-inducible genes, growth and development-related genes, and sugar transport-related genes were found in clusters in most of the meta-QTL.
Meta-QTL with small genetic and physical intervals could be useful in Marker-assisted selection individually and in combinations. Validation and comparative genomics of the major-effect QTL confirmed their consistency within and across the species. The shortlisted candidate genes can be cloned to unravel the molecular mechanism regulating grain yield under drought.</description><identifier>ISSN: 1471-2164</identifier><identifier>EISSN: 1471-2164</identifier><identifier>DOI: 10.1186/1471-2164-12-319</identifier><identifier>PMID: 21679437</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Agriculture ; Chromosome Mapping ; Consensus ; Droughts ; Edible Grain - genetics ; Edible Grain - growth & development ; Environmental aspects ; Genes, Plant - genetics ; Genetic aspects ; Genetic Markers - genetics ; Genomics - methods ; Philippines ; Physiological aspects ; Poaceae - genetics ; Poaceae - growth & development ; Quantitative trait loci ; Quantitative Trait Loci - genetics ; Reproducibility of Results ; Rice</subject><ispartof>BMC genomics, 2011-06, Vol.12 (1), p.319-319, Article 319</ispartof><rights>COPYRIGHT 2011 BioMed Central Ltd.</rights><rights>Copyright ©2011 Swamy et al; licensee BioMed Central Ltd. 2011 Swamy et al; licensee BioMed Central Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b622t-ee940eda28c9904735c2623bb020b0a4588336ab00214fd2d9520c88c3f3b97e3</citedby><cites>FETCH-LOGICAL-b622t-ee940eda28c9904735c2623bb020b0a4588336ab00214fd2d9520c88c3f3b97e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3155843/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3155843/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,37013,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21679437$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Swamy, B P Mallikarjuna</creatorcontrib><creatorcontrib>Vikram, Prashant</creatorcontrib><creatorcontrib>Dixit, Shalabh</creatorcontrib><creatorcontrib>Ahmed, H U</creatorcontrib><creatorcontrib>Kumar, Arvind</creatorcontrib><title>Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus</title><title>BMC genomics</title><addtitle>BMC Genomics</addtitle><description>In the last few years, efforts have been made to identify large effect QTL for grain yield under drought in rice. However, identification of most precise and consistent QTL across the environments and genetics backgrounds is essential for their successful use in Marker-assisted Selection. In this study, an attempt was made to locate consistent QTL regions associated with yield increase under drought by applying a genome-wide QTL meta-analysis approach.
The integration of 15 maps resulted in a consensus map with 531 markers and a total map length of 1821 cM. Fifty-three yield QTL reported in 15 studies were projected on a consensus map and meta-analysis was performed. Fourteen meta-QTL were obtained on seven chromosomes. MQTL1.2, MQTL1.3, MQTL1.4, and MQTL12.1 were around 700 kb and corresponded to a reasonably small genetic distance of 1.8 to 5 cM and they are suitable for use in marker-assisted selection (MAS). The meta-QTL for grain yield under drought coincided with at least one of the meta-QTL identified for root and leaf morphology traits under drought in earlier reports. Validation of major-effect QTL on a panel of random drought-tolerant lines revealed the presence of at least one major QTL in each line. DTY12.1 was present in 85% of the lines, followed by DTY4.1 in 79% and DTY1.1 in 64% of the lines. Comparative genomics of meta-QTL with other cereals revealed that the homologous regions of MQTL1.4 and MQTL3.2 had QTL for grain yield under drought in maize, wheat, and barley respectively. The genes in the meta-QTL regions were analyzed by a comparative genomics approach and candidate genes were deduced for grain yield under drought. Three groups of genes such as stress-inducible genes, growth and development-related genes, and sugar transport-related genes were found in clusters in most of the meta-QTL.
Meta-QTL with small genetic and physical intervals could be useful in Marker-assisted selection individually and in combinations. Validation and comparative genomics of the major-effect QTL confirmed their consistency within and across the species. The shortlisted candidate genes can be cloned to unravel the molecular mechanism regulating grain yield under drought.</description><subject>Agriculture</subject><subject>Chromosome Mapping</subject><subject>Consensus</subject><subject>Droughts</subject><subject>Edible Grain - genetics</subject><subject>Edible Grain - growth & development</subject><subject>Environmental aspects</subject><subject>Genes, Plant - genetics</subject><subject>Genetic aspects</subject><subject>Genetic Markers - genetics</subject><subject>Genomics - methods</subject><subject>Philippines</subject><subject>Physiological aspects</subject><subject>Poaceae - genetics</subject><subject>Poaceae - growth & development</subject><subject>Quantitative trait loci</subject><subject>Quantitative Trait Loci - genetics</subject><subject>Reproducibility of Results</subject><subject>Rice</subject><issn>1471-2164</issn><issn>1471-2164</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp1kk1v1DAQhiMEoqVw54QscUAcUvyV2LkgVSsKKy1CQDlbE39kXWXjYifQ_fd4SVk1UpEPtmbe97FnxkXxkuBzQmT9jnBBSkpqXhJaMtI8Kk6Pocf3zifFs5SuMSZC0uppcZJjouFMnBb6sx2hhAH6ffIJBYe6CH5Ae297g75ebZA3dhi989YgM0U_dAi66PXUj1OEHpkYpm47ouzJzpRsQmkbfme1DkOyQ5rS8-KJgz7ZF3f7WfHj8sPV6lO5-fJxvbrYlG1N6Vha23BsDVCpmwZzwSpNa8raFlPcYuCVlIzV0GJMCXeGmqaiWEupmWNtIyw7K9Yz1wS4VjfR7yDuVQCv_gZC7BTE0eveKiGEBuwANNZctEbKGmTN8z2OMeFkZr2fWTdTu7NG5x7kahfQZWbwW9WFX4qRqpKcZcBqBrQ-_AewzOiwU4eBqcPAFKGZ1GTKm7tnxPBzsmlUO5-07XsYbJiSyi2RvG4qkZWvZ2UHuT4_uJCp-qBWF7SuKKOMk6w6f0CVl7E7nwdmnc_xheHtwpA1o70dO5hSUuvv35ZaPGt1DClF647VEqwO__Wh-l7db_PR8O-Dsj-NluUA</recordid><startdate>20110616</startdate><enddate>20110616</enddate><creator>Swamy, B P Mallikarjuna</creator><creator>Vikram, Prashant</creator><creator>Dixit, Shalabh</creator><creator>Ahmed, H U</creator><creator>Kumar, Arvind</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</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>ISR</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20110616</creationdate><title>Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus</title><author>Swamy, B P Mallikarjuna ; Vikram, Prashant ; Dixit, Shalabh ; Ahmed, H U ; Kumar, Arvind</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b622t-ee940eda28c9904735c2623bb020b0a4588336ab00214fd2d9520c88c3f3b97e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Agriculture</topic><topic>Chromosome Mapping</topic><topic>Consensus</topic><topic>Droughts</topic><topic>Edible Grain - genetics</topic><topic>Edible Grain - growth & development</topic><topic>Environmental aspects</topic><topic>Genes, Plant - genetics</topic><topic>Genetic aspects</topic><topic>Genetic Markers - genetics</topic><topic>Genomics - methods</topic><topic>Philippines</topic><topic>Physiological aspects</topic><topic>Poaceae - genetics</topic><topic>Poaceae - growth & development</topic><topic>Quantitative trait loci</topic><topic>Quantitative Trait Loci - genetics</topic><topic>Reproducibility of Results</topic><topic>Rice</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Swamy, B P Mallikarjuna</creatorcontrib><creatorcontrib>Vikram, Prashant</creatorcontrib><creatorcontrib>Dixit, Shalabh</creatorcontrib><creatorcontrib>Ahmed, H U</creatorcontrib><creatorcontrib>Kumar, Arvind</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC genomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Swamy, B P Mallikarjuna</au><au>Vikram, Prashant</au><au>Dixit, Shalabh</au><au>Ahmed, H U</au><au>Kumar, Arvind</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus</atitle><jtitle>BMC genomics</jtitle><addtitle>BMC Genomics</addtitle><date>2011-06-16</date><risdate>2011</risdate><volume>12</volume><issue>1</issue><spage>319</spage><epage>319</epage><pages>319-319</pages><artnum>319</artnum><issn>1471-2164</issn><eissn>1471-2164</eissn><abstract>In the last few years, efforts have been made to identify large effect QTL for grain yield under drought in rice. However, identification of most precise and consistent QTL across the environments and genetics backgrounds is essential for their successful use in Marker-assisted Selection. In this study, an attempt was made to locate consistent QTL regions associated with yield increase under drought by applying a genome-wide QTL meta-analysis approach.
The integration of 15 maps resulted in a consensus map with 531 markers and a total map length of 1821 cM. Fifty-three yield QTL reported in 15 studies were projected on a consensus map and meta-analysis was performed. Fourteen meta-QTL were obtained on seven chromosomes. MQTL1.2, MQTL1.3, MQTL1.4, and MQTL12.1 were around 700 kb and corresponded to a reasonably small genetic distance of 1.8 to 5 cM and they are suitable for use in marker-assisted selection (MAS). The meta-QTL for grain yield under drought coincided with at least one of the meta-QTL identified for root and leaf morphology traits under drought in earlier reports. Validation of major-effect QTL on a panel of random drought-tolerant lines revealed the presence of at least one major QTL in each line. DTY12.1 was present in 85% of the lines, followed by DTY4.1 in 79% and DTY1.1 in 64% of the lines. Comparative genomics of meta-QTL with other cereals revealed that the homologous regions of MQTL1.4 and MQTL3.2 had QTL for grain yield under drought in maize, wheat, and barley respectively. The genes in the meta-QTL regions were analyzed by a comparative genomics approach and candidate genes were deduced for grain yield under drought. Three groups of genes such as stress-inducible genes, growth and development-related genes, and sugar transport-related genes were found in clusters in most of the meta-QTL.
Meta-QTL with small genetic and physical intervals could be useful in Marker-assisted selection individually and in combinations. Validation and comparative genomics of the major-effect QTL confirmed their consistency within and across the species. The shortlisted candidate genes can be cloned to unravel the molecular mechanism regulating grain yield under drought.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>21679437</pmid><doi>10.1186/1471-2164-12-319</doi><oa>free_for_read</oa></addata></record> |
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subjects | Agriculture Chromosome Mapping Consensus Droughts Edible Grain - genetics Edible Grain - growth & development Environmental aspects Genes, Plant - genetics Genetic aspects Genetic Markers - genetics Genomics - methods Philippines Physiological aspects Poaceae - genetics Poaceae - growth & development Quantitative trait loci Quantitative Trait Loci - genetics Reproducibility of Results Rice |
title | Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus |
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