Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level?
Kernel dimensions (KD) contribute greatly to thousand-kernel weight (TKW) in wheat. In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related...
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| Veröffentlicht in: | Journal of genetics 2011-12, Vol.90 (3), p.409-425 |
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| creator | CUI, FA DING, ANMING LI, JUN ZHAO, CHUNHUA LI, XINGFENG FENG, DESHUN WANG, XIUQIN WANG, LIN GAO, JURONG WANG, HONGGANG |
| description | Kernel dimensions (KD) contribute greatly to thousand-kernel weight (TKW) in wheat. In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related F8:9 recombinant inbred line (RIL) populations, comprising 485 and 229 lines, respectively, were used in this study, and the trait phenotypes were evaluated in four environments. Unconditional QTL mapping analysis detected 77 additive QTL for four traits in two populations. Of these, 24 QTL were verified in at least three trials, and five of them were major QTL, thus being of great value for marker assisted selection in breeding programmes. Conditional QTL mapping analysis, compared with unconditional QTL mapping analysis, resulted in reduction in the number of QTL for TKW due to the elimination of TKW variations caused by its conditional traits; based on which we first dissected genetic control system involved in the synthetic process between TKW and KD at an individual QTL level. Results indicated that, at the QTL level, KW had the strongest influence on TKW, followed by KL, and KDR had the lowest level contribution to TKW. In addition, the present study proved that it is not all-inclusive to determine genetic relationships of a pairwise QTL for two related/causal traits based on whether they were co-located. Thus, conditional QTL mapping method should be used to evaluate possible genetic relationships of two related/causal traits. |
| doi_str_mv | 10.1007/s12041-011-0103-9 |
| format | Article |
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In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related F8:9 recombinant inbred line (RIL) populations, comprising 485 and 229 lines, respectively, were used in this study, and the trait phenotypes were evaluated in four environments. Unconditional QTL mapping analysis detected 77 additive QTL for four traits in two populations. Of these, 24 QTL were verified in at least three trials, and five of them were major QTL, thus being of great value for marker assisted selection in breeding programmes. Conditional QTL mapping analysis, compared with unconditional QTL mapping analysis, resulted in reduction in the number of QTL for TKW due to the elimination of TKW variations caused by its conditional traits; based on which we first dissected genetic control system involved in the synthetic process between TKW and KD at an individual QTL level. Results indicated that, at the QTL level, KW had the strongest influence on TKW, followed by KL, and KDR had the lowest level contribution to TKW. In addition, the present study proved that it is not all-inclusive to determine genetic relationships of a pairwise QTL for two related/causal traits based on whether they were co-located. Thus, conditional QTL mapping method should be used to evaluate possible genetic relationships of two related/causal traits.</description><identifier>ISSN: 0022-1333</identifier><identifier>EISSN: 0973-7731</identifier><identifier>DOI: 10.1007/s12041-011-0103-9</identifier><identifier>PMID: 22227928</identifier><language>eng</language><publisher>India: Springer-Verlag</publisher><subject>Animal Genetics and Genomics ; Biomarkers ; Biomedical and Life Sciences ; Chromosome Mapping ; Chromosomes, Plant - genetics ; Environment ; Evolutionary Biology ; Genetic Linkage ; Genetic Markers ; genetic relationships ; Genetics ; Genotype ; inbred lines ; Inbreeding ; Life Sciences ; marker-assisted selection ; Microbial Genetics and Genomics ; Phenotype ; Plant Genetics and Genomics ; Quantitative Trait Loci ; Research Article ; seeds ; Seeds - genetics ; Seeds - growth & development ; Triticum - genetics ; Triticum - growth & development ; Triticum aestivum ; Wheat</subject><ispartof>Journal of genetics, 2011-12, Vol.90 (3), p.409-425</ispartof><rights>Indian Academy of Sciences 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c428t-4e3b5040e6b5f461dc560f10568fb213cb705eec7760d327758ed3db9b8b3a673</citedby><cites>FETCH-LOGICAL-c428t-4e3b5040e6b5f461dc560f10568fb213cb705eec7760d327758ed3db9b8b3a673</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/s12041-011-0103-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12041-011-0103-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,777,781,27905,27906,41469,42538,51300</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22227928$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>CUI, FA</creatorcontrib><creatorcontrib>DING, ANMING</creatorcontrib><creatorcontrib>LI, JUN</creatorcontrib><creatorcontrib>ZHAO, CHUNHUA</creatorcontrib><creatorcontrib>LI, XINGFENG</creatorcontrib><creatorcontrib>FENG, DESHUN</creatorcontrib><creatorcontrib>WANG, XIUQIN</creatorcontrib><creatorcontrib>WANG, LIN</creatorcontrib><creatorcontrib>GAO, JURONG</creatorcontrib><creatorcontrib>WANG, HONGGANG</creatorcontrib><title>Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level?</title><title>Journal of genetics</title><addtitle>J Genet</addtitle><addtitle>J Genet</addtitle><description>Kernel dimensions (KD) contribute greatly to thousand-kernel weight (TKW) in wheat. In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related F8:9 recombinant inbred line (RIL) populations, comprising 485 and 229 lines, respectively, were used in this study, and the trait phenotypes were evaluated in four environments. Unconditional QTL mapping analysis detected 77 additive QTL for four traits in two populations. Of these, 24 QTL were verified in at least three trials, and five of them were major QTL, thus being of great value for marker assisted selection in breeding programmes. Conditional QTL mapping analysis, compared with unconditional QTL mapping analysis, resulted in reduction in the number of QTL for TKW due to the elimination of TKW variations caused by its conditional traits; based on which we first dissected genetic control system involved in the synthetic process between TKW and KD at an individual QTL level. Results indicated that, at the QTL level, KW had the strongest influence on TKW, followed by KL, and KDR had the lowest level contribution to TKW. In addition, the present study proved that it is not all-inclusive to determine genetic relationships of a pairwise QTL for two related/causal traits based on whether they were co-located. Thus, conditional QTL mapping method should be used to evaluate possible genetic relationships of two related/causal traits.</description><subject>Animal Genetics and Genomics</subject><subject>Biomarkers</subject><subject>Biomedical and Life Sciences</subject><subject>Chromosome Mapping</subject><subject>Chromosomes, Plant - genetics</subject><subject>Environment</subject><subject>Evolutionary Biology</subject><subject>Genetic Linkage</subject><subject>Genetic Markers</subject><subject>genetic relationships</subject><subject>Genetics</subject><subject>Genotype</subject><subject>inbred lines</subject><subject>Inbreeding</subject><subject>Life Sciences</subject><subject>marker-assisted selection</subject><subject>Microbial Genetics and Genomics</subject><subject>Phenotype</subject><subject>Plant Genetics and Genomics</subject><subject>Quantitative Trait Loci</subject><subject>Research Article</subject><subject>seeds</subject><subject>Seeds - genetics</subject><subject>Seeds - growth & development</subject><subject>Triticum - 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Academic</collection><jtitle>Journal of genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>CUI, FA</au><au>DING, ANMING</au><au>LI, JUN</au><au>ZHAO, CHUNHUA</au><au>LI, XINGFENG</au><au>FENG, DESHUN</au><au>WANG, XIUQIN</au><au>WANG, LIN</au><au>GAO, JURONG</au><au>WANG, HONGGANG</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level?</atitle><jtitle>Journal of genetics</jtitle><stitle>J Genet</stitle><addtitle>J Genet</addtitle><date>2011-12-01</date><risdate>2011</risdate><volume>90</volume><issue>3</issue><spage>409</spage><epage>425</epage><pages>409-425</pages><issn>0022-1333</issn><eissn>0973-7731</eissn><abstract>Kernel dimensions (KD) contribute greatly to thousand-kernel weight (TKW) in wheat. In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related F8:9 recombinant inbred line (RIL) populations, comprising 485 and 229 lines, respectively, were used in this study, and the trait phenotypes were evaluated in four environments. Unconditional QTL mapping analysis detected 77 additive QTL for four traits in two populations. Of these, 24 QTL were verified in at least three trials, and five of them were major QTL, thus being of great value for marker assisted selection in breeding programmes. Conditional QTL mapping analysis, compared with unconditional QTL mapping analysis, resulted in reduction in the number of QTL for TKW due to the elimination of TKW variations caused by its conditional traits; based on which we first dissected genetic control system involved in the synthetic process between TKW and KD at an individual QTL level. Results indicated that, at the QTL level, KW had the strongest influence on TKW, followed by KL, and KDR had the lowest level contribution to TKW. In addition, the present study proved that it is not all-inclusive to determine genetic relationships of a pairwise QTL for two related/causal traits based on whether they were co-located. Thus, conditional QTL mapping method should be used to evaluate possible genetic relationships of two related/causal traits.</abstract><cop>India</cop><pub>Springer-Verlag</pub><pmid>22227928</pmid><doi>10.1007/s12041-011-0103-9</doi><tpages>17</tpages></addata></record> |
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| ispartof | Journal of genetics, 2011-12, Vol.90 (3), p.409-425 |
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| source | MEDLINE; Indian Academy of Sciences; Springer Nature - Complete Springer Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | Animal Genetics and Genomics Biomarkers Biomedical and Life Sciences Chromosome Mapping Chromosomes, Plant - genetics Environment Evolutionary Biology Genetic Linkage Genetic Markers genetic relationships Genetics Genotype inbred lines Inbreeding Life Sciences marker-assisted selection Microbial Genetics and Genomics Phenotype Plant Genetics and Genomics Quantitative Trait Loci Research Article seeds Seeds - genetics Seeds - growth & development Triticum - genetics Triticum - growth & development Triticum aestivum Wheat |
| title | Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level? |
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