Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.)
Harvest index is a measure of success in partitioning assimilated photosynthate. An improvement of harvest index means an increase in the economic portion of the plant. Our objective was to identify genetic markers associated with harvest index traits using 203 O. sativa accessions. The phenotyping...
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| description | Harvest index is a measure of success in partitioning assimilated photosynthate. An improvement of harvest index means an increase in the economic portion of the plant. Our objective was to identify genetic markers associated with harvest index traits using 203 O. sativa accessions. The phenotyping for 14 traits was conducted in both temperate (Arkansas) and subtropical (Texas) climates and the genotyping used 154 SSRs and an indel marker. Heading, plant height and weight, and panicle length had negative correlations, while seed set and grain weight/panicle had positive correlations with harvest index across both locations. Subsequent genetic diversity and population structure analyses identified five groups in this collection, which corresponded to their geographic origins. Model comparisons revealed that different dimensions of principal components analysis (PCA) affected harvest index traits for mapping accuracy, and kinship did not help. In total, 36 markers in Arkansas and 28 markers in Texas were identified to be significantly associated with harvest index traits. Seven and two markers were consistently associated with two or more harvest index correlated traits in Arkansas and Texas, respectively. Additionally, four markers were constitutively identified at both locations, while 32 and 24 markers were identified specifically in Arkansas and Texas, respectively. Allelic analysis of four constitutive markers demonstrated that allele 253 bp of RM431 had significantly greater effect on decreasing plant height, and 390 bp of RM24011 had the greatest effect on decreasing panicle length across both locations. Many of these identified markers are located either nearby or flanking the regions where the QTLs for harvest index have been reported. Thus, the results from this association mapping study complement and enrich the information from linkage-based QTL studies and will be the basis for improving harvest index directly and indirectly in rice. |
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An improvement of harvest index means an increase in the economic portion of the plant. Our objective was to identify genetic markers associated with harvest index traits using 203 O. sativa accessions. The phenotyping for 14 traits was conducted in both temperate (Arkansas) and subtropical (Texas) climates and the genotyping used 154 SSRs and an indel marker. Heading, plant height and weight, and panicle length had negative correlations, while seed set and grain weight/panicle had positive correlations with harvest index across both locations. Subsequent genetic diversity and population structure analyses identified five groups in this collection, which corresponded to their geographic origins. Model comparisons revealed that different dimensions of principal components analysis (PCA) affected harvest index traits for mapping accuracy, and kinship did not help. In total, 36 markers in Arkansas and 28 markers in Texas were identified to be significantly associated with harvest index traits. Seven and two markers were consistently associated with two or more harvest index correlated traits in Arkansas and Texas, respectively. Additionally, four markers were constitutively identified at both locations, while 32 and 24 markers were identified specifically in Arkansas and Texas, respectively. Allelic analysis of four constitutive markers demonstrated that allele 253 bp of RM431 had significantly greater effect on decreasing plant height, and 390 bp of RM24011 had the greatest effect on decreasing panicle length across both locations. Many of these identified markers are located either nearby or flanking the regions where the QTLs for harvest index have been reported. Thus, the results from this association mapping study complement and enrich the information from linkage-based QTL studies and will be the basis for improving harvest index directly and indirectly in rice.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0029350</identifier><identifier>PMID: 22291889</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Agricultural production ; Agriculture ; Agriculture - methods ; alleles ; Analysis ; Arkansas ; Biology ; Biomass ; Bumpers, Dale L ; chromosome mapping ; Chromosome Mapping - methods ; Climate ; Correlation ; Cultivars ; Efficiency - physiology ; Gene mapping ; Genetic aspects ; Genetic Association Studies ; Genetic diversity ; Genetic markers ; Genetic Markers - genetics ; Genetic Markers - physiology ; genetic variation ; Genotype ; Genotyping ; Geography ; Germplasm ; Grain ; Harvest ; harvest index ; heading ; inflorescences ; kinship ; Mapping ; Markers ; microsatellite repeats ; Models, Genetic ; Multivariate analysis ; Oryza - genetics ; Oryza sativa ; Phenotype ; Phenotyping ; Photosynthesis ; Phylogeny ; plants ; Population ; Population genetics ; Population structure ; principal component analysis ; Principal components analysis ; provenance ; Quantitative genetics ; Quantitative trait loci ; Quantitative Trait Loci - genetics ; Quantitative Trait Loci - physiology ; Rice ; Seed set ; Seeds - genetics ; Sorghum ; Subtropical climates ; subtropics ; Taxonomy ; temperate zones ; Texas</subject><ispartof>PloS one, 2012-01, Vol.7 (1), p.e29350-e29350</ispartof><rights>COPYRIGHT 2012 Public Library of Science</rights><rights>2012. This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. 2012</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c6630-b946d8908e388c1dec16f15c3705dfb90e693407657fd9e809706f2c75727433</citedby><cites>FETCH-LOGICAL-c6630-b946d8908e388c1dec16f15c3705dfb90e693407657fd9e809706f2c75727433</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/PMC3264563/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3264563/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22291889$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Xiaobai</creatorcontrib><creatorcontrib>Yan, Wengui</creatorcontrib><creatorcontrib>Agrama, Hesham</creatorcontrib><creatorcontrib>Jia, Limeng</creatorcontrib><creatorcontrib>Jackson, Aaron</creatorcontrib><creatorcontrib>Moldenhauer, Karen</creatorcontrib><creatorcontrib>Yeater, Kathleen</creatorcontrib><creatorcontrib>McClung, Anna</creatorcontrib><creatorcontrib>Wu, Dianxing</creatorcontrib><title>Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.)</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Harvest index is a measure of success in partitioning assimilated photosynthate. An improvement of harvest index means an increase in the economic portion of the plant. Our objective was to identify genetic markers associated with harvest index traits using 203 O. sativa accessions. The phenotyping for 14 traits was conducted in both temperate (Arkansas) and subtropical (Texas) climates and the genotyping used 154 SSRs and an indel marker. Heading, plant height and weight, and panicle length had negative correlations, while seed set and grain weight/panicle had positive correlations with harvest index across both locations. Subsequent genetic diversity and population structure analyses identified five groups in this collection, which corresponded to their geographic origins. Model comparisons revealed that different dimensions of principal components analysis (PCA) affected harvest index traits for mapping accuracy, and kinship did not help. In total, 36 markers in Arkansas and 28 markers in Texas were identified to be significantly associated with harvest index traits. Seven and two markers were consistently associated with two or more harvest index correlated traits in Arkansas and Texas, respectively. Additionally, four markers were constitutively identified at both locations, while 32 and 24 markers were identified specifically in Arkansas and Texas, respectively. Allelic analysis of four constitutive markers demonstrated that allele 253 bp of RM431 had significantly greater effect on decreasing plant height, and 390 bp of RM24011 had the greatest effect on decreasing panicle length across both locations. Many of these identified markers are located either nearby or flanking the regions where the QTLs for harvest index have been reported. Thus, the results from this association mapping study complement and enrich the information from linkage-based QTL studies and will be the basis for improving harvest index directly and indirectly in rice.</description><subject>Agricultural production</subject><subject>Agriculture</subject><subject>Agriculture - methods</subject><subject>alleles</subject><subject>Analysis</subject><subject>Arkansas</subject><subject>Biology</subject><subject>Biomass</subject><subject>Bumpers, Dale L</subject><subject>chromosome mapping</subject><subject>Chromosome Mapping - methods</subject><subject>Climate</subject><subject>Correlation</subject><subject>Cultivars</subject><subject>Efficiency - physiology</subject><subject>Gene mapping</subject><subject>Genetic aspects</subject><subject>Genetic Association Studies</subject><subject>Genetic diversity</subject><subject>Genetic markers</subject><subject>Genetic Markers - genetics</subject><subject>Genetic Markers - physiology</subject><subject>genetic variation</subject><subject>Genotype</subject><subject>Genotyping</subject><subject>Geography</subject><subject>Germplasm</subject><subject>Grain</subject><subject>Harvest</subject><subject>harvest index</subject><subject>heading</subject><subject>inflorescences</subject><subject>kinship</subject><subject>Mapping</subject><subject>Markers</subject><subject>microsatellite repeats</subject><subject>Models, Genetic</subject><subject>Multivariate analysis</subject><subject>Oryza - genetics</subject><subject>Oryza sativa</subject><subject>Phenotype</subject><subject>Phenotyping</subject><subject>Photosynthesis</subject><subject>Phylogeny</subject><subject>plants</subject><subject>Population</subject><subject>Population genetics</subject><subject>Population structure</subject><subject>principal component analysis</subject><subject>Principal components analysis</subject><subject>provenance</subject><subject>Quantitative genetics</subject><subject>Quantitative trait loci</subject><subject>Quantitative Trait Loci - genetics</subject><subject>Quantitative Trait Loci - physiology</subject><subject>Rice</subject><subject>Seed set</subject><subject>Seeds - genetics</subject><subject>Sorghum</subject><subject>Subtropical climates</subject><subject>subtropics</subject><subject>Taxonomy</subject><subject>temperate zones</subject><subject>Texas</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNk91r1TAYxosobk7_A9GCoNvFOeajTZobYQw_Dhw44DZvY5qkbUbbdEl73PzrTT3dPJUh0ouWN7_nSfrkfaPoJQRLiCl8f2UH14p62dlWLwFADKfgUXQIGUYLggB-vPd9ED3z_gqAFGeEPI0OEEIMZhk7jL5ftk5sdW3aMu4rHUvbdLW-iXsnTB_bIq6E22rfx6ZVofzD9FUsvLfSiN7YNm5E141a08bOSB0fb9ztTxH7sLoV8Xp58jx6Uoja6xfT-yi6-PTx4uzLYr35vDo7XS8kIRgscpYQlTGQaZxlEiotISlgKjEFqSpyBjRhOAGUpLRQTGeAUUAKJGlKEU0wPope72y72no-ZeM5xAhjyhCkgVjtCGXFFe-caYS75VYY_rtgXcmF642sNWeJVoipXOYqTTSVDBWpVAjkSKdYYhW8Pky7DXmjldRtyKuemc5XWlPx0m45RiRJyXjcd5OBs9dDyJc3xktd16LVdvCcQYYQzcBIHv-ThChEkmGQZAF98xf6cA4TVYrwq6YtbDihHE35aUJD3DBh47bLB6jwKN0YGVquMKE-E5zMBIHp9U1fisF7vjr_-v_s5tucfbvHVlrUfeVtPYzd5-dgsgOls947XdxfBwR8nJi7NPg4MXyamCB7tX-V96K7EfnTWYWwXJTOeH55jgDEALKUkuDyC91dGEU</recordid><startdate>20120123</startdate><enddate>20120123</enddate><creator>Li, Xiaobai</creator><creator>Yan, Wengui</creator><creator>Agrama, Hesham</creator><creator>Jia, Limeng</creator><creator>Jackson, Aaron</creator><creator>Moldenhauer, Karen</creator><creator>Yeater, Kathleen</creator><creator>McClung, Anna</creator><creator>Wu, Dianxing</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7S9</scope><scope>L.6</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20120123</creationdate><title>Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.)</title><author>Li, Xiaobai ; Yan, Wengui ; Agrama, Hesham ; Jia, Limeng ; Jackson, Aaron ; Moldenhauer, Karen ; Yeater, Kathleen ; McClung, Anna ; Wu, Dianxing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c6630-b946d8908e388c1dec16f15c3705dfb90e693407657fd9e809706f2c75727433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Agricultural production</topic><topic>Agriculture</topic><topic>Agriculture - methods</topic><topic>alleles</topic><topic>Analysis</topic><topic>Arkansas</topic><topic>Biology</topic><topic>Biomass</topic><topic>Bumpers, Dale L</topic><topic>chromosome mapping</topic><topic>Chromosome Mapping - methods</topic><topic>Climate</topic><topic>Correlation</topic><topic>Cultivars</topic><topic>Efficiency - physiology</topic><topic>Gene mapping</topic><topic>Genetic aspects</topic><topic>Genetic Association Studies</topic><topic>Genetic diversity</topic><topic>Genetic markers</topic><topic>Genetic Markers - genetics</topic><topic>Genetic Markers - physiology</topic><topic>genetic variation</topic><topic>Genotype</topic><topic>Genotyping</topic><topic>Geography</topic><topic>Germplasm</topic><topic>Grain</topic><topic>Harvest</topic><topic>harvest index</topic><topic>heading</topic><topic>inflorescences</topic><topic>kinship</topic><topic>Mapping</topic><topic>Markers</topic><topic>microsatellite repeats</topic><topic>Models, Genetic</topic><topic>Multivariate analysis</topic><topic>Oryza - genetics</topic><topic>Oryza sativa</topic><topic>Phenotype</topic><topic>Phenotyping</topic><topic>Photosynthesis</topic><topic>Phylogeny</topic><topic>plants</topic><topic>Population</topic><topic>Population genetics</topic><topic>Population structure</topic><topic>principal component analysis</topic><topic>Principal components analysis</topic><topic>provenance</topic><topic>Quantitative genetics</topic><topic>Quantitative trait loci</topic><topic>Quantitative Trait Loci - genetics</topic><topic>Quantitative Trait Loci - physiology</topic><topic>Rice</topic><topic>Seed set</topic><topic>Seeds - genetics</topic><topic>Sorghum</topic><topic>Subtropical climates</topic><topic>subtropics</topic><topic>Taxonomy</topic><topic>temperate zones</topic><topic>Texas</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Xiaobai</creatorcontrib><creatorcontrib>Yan, Wengui</creatorcontrib><creatorcontrib>Agrama, Hesham</creatorcontrib><creatorcontrib>Jia, Limeng</creatorcontrib><creatorcontrib>Jackson, Aaron</creatorcontrib><creatorcontrib>Moldenhauer, Karen</creatorcontrib><creatorcontrib>Yeater, Kathleen</creatorcontrib><creatorcontrib>McClung, Anna</creatorcontrib><creatorcontrib>Wu, Dianxing</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>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology 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>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</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>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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Academic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Xiaobai</au><au>Yan, Wengui</au><au>Agrama, Hesham</au><au>Jia, Limeng</au><au>Jackson, Aaron</au><au>Moldenhauer, Karen</au><au>Yeater, Kathleen</au><au>McClung, Anna</au><au>Wu, Dianxing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.)</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2012-01-23</date><risdate>2012</risdate><volume>7</volume><issue>1</issue><spage>e29350</spage><epage>e29350</epage><pages>e29350-e29350</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Harvest index is a measure of success in partitioning assimilated photosynthate. An improvement of harvest index means an increase in the economic portion of the plant. Our objective was to identify genetic markers associated with harvest index traits using 203 O. sativa accessions. The phenotyping for 14 traits was conducted in both temperate (Arkansas) and subtropical (Texas) climates and the genotyping used 154 SSRs and an indel marker. Heading, plant height and weight, and panicle length had negative correlations, while seed set and grain weight/panicle had positive correlations with harvest index across both locations. Subsequent genetic diversity and population structure analyses identified five groups in this collection, which corresponded to their geographic origins. Model comparisons revealed that different dimensions of principal components analysis (PCA) affected harvest index traits for mapping accuracy, and kinship did not help. In total, 36 markers in Arkansas and 28 markers in Texas were identified to be significantly associated with harvest index traits. Seven and two markers were consistently associated with two or more harvest index correlated traits in Arkansas and Texas, respectively. Additionally, four markers were constitutively identified at both locations, while 32 and 24 markers were identified specifically in Arkansas and Texas, respectively. Allelic analysis of four constitutive markers demonstrated that allele 253 bp of RM431 had significantly greater effect on decreasing plant height, and 390 bp of RM24011 had the greatest effect on decreasing panicle length across both locations. Many of these identified markers are located either nearby or flanking the regions where the QTLs for harvest index have been reported. Thus, the results from this association mapping study complement and enrich the information from linkage-based QTL studies and will be the basis for improving harvest index directly and indirectly in rice.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>22291889</pmid><doi>10.1371/journal.pone.0029350</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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| recordid | cdi_plos_journals_1323379217 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Agricultural production Agriculture Agriculture - methods alleles Analysis Arkansas Biology Biomass Bumpers, Dale L chromosome mapping Chromosome Mapping - methods Climate Correlation Cultivars Efficiency - physiology Gene mapping Genetic aspects Genetic Association Studies Genetic diversity Genetic markers Genetic Markers - genetics Genetic Markers - physiology genetic variation Genotype Genotyping Geography Germplasm Grain Harvest harvest index heading inflorescences kinship Mapping Markers microsatellite repeats Models, Genetic Multivariate analysis Oryza - genetics Oryza sativa Phenotype Phenotyping Photosynthesis Phylogeny plants Population Population genetics Population structure principal component analysis Principal components analysis provenance Quantitative genetics Quantitative trait loci Quantitative Trait Loci - genetics Quantitative Trait Loci - physiology Rice Seed set Seeds - genetics Sorghum Subtropical climates subtropics Taxonomy temperate zones Texas |
| title | Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.) |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T23%3A09%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Unraveling%20the%20complex%20trait%20of%20harvest%20index%20with%20association%20mapping%20in%20rice%20(Oryza%20sativa%20L.)&rft.jtitle=PloS%20one&rft.au=Li,%20Xiaobai&rft.date=2012-01-23&rft.volume=7&rft.issue=1&rft.spage=e29350&rft.epage=e29350&rft.pages=e29350-e29350&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0029350&rft_dat=%3Cgale_plos_%3EA477051493%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1323379217&rft_id=info:pmid/22291889&rft_galeid=A477051493&rft_doaj_id=oai_doaj_org_article_94ed29dbcbd54e7c92f5cd20b2e53c3d&rfr_iscdi=true |