Detection of QTLs for outcrossing-related traits in rice (Oryza sativa L.) by association mapping and the RSTEP-LRT method
The outcrossing traits in rice affect the yield of hybrid rice seed production. In this study, 30 quantitative trait loci (QTLs) were detected in a natural population composed of 522 accessions by using a mixed linear model for the four outcrossing-related traits in 2017 and 2018. We detected 3, 4,...
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| Veröffentlicht in: | Euphytica 2019-12, Vol.215 (12), p.1-17, Article 204 |
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| creator | Bux, Lal Li, Dalu Faheem, Muhammad Sowadan, Ognigamal Dong, Zhiyao Liu, Erbao Ali, Mehtab Li, Yanhui Sitoe, Helder Manuel Mirani, Abdul Aziz Hong, Delin |
| description | The outcrossing traits in rice affect the yield of hybrid rice seed production. In this study, 30 quantitative trait loci (QTLs) were detected in a natural population composed of 522 accessions by using a mixed linear model for the four outcrossing-related traits in 2017 and 2018. We detected 3, 4, 9 and 14 QTLs for flag leaf length (FLL), flag leaf width (FLW), flag leaf angle (FLA) and panicle neck length (PNL), respectively, among which 26 QTLs were novel. The favorable alleles and their carrier varieties were noticed with the largest phenotypic effect value. For FLL, marker allele RM6997-105 bp on chromosome 4 carried by Yue96 cultivar showed the highest phenotypic effect value (PEV), allele RM562-280 bp on chromosome 1 carried by Wanzhongqiu genotype for FLW, allele RM152-375 bp on chromosome 8 in typical carrier variety Zhongzuo93 for FLA and allele RM134-150 bp on chromosome 7 carried by Yue34 cultivar for PNL showed the highest PEVs. Additionally, nine QTLs were detected for the 4 traits with percentage of phenotypic variance explained (PVE) ranging from 16.24% (RM21) to 28.75% (RM5479) using a chromosome segment substitution line (CSSL) population. Among these detected QTLs,
qFLL-12
and
qFLW-12
showed 19.85% and 19.57% PVE, respectively. Four QTLs (
qFLA-10
,
qFLA-11
,
qFLA-12.1
,
qFLA-12.2
) detected for FLA showed PVEs ranging from 16.24% to 28.75%. For PNL,
qPNL-7
,
qPNL-12.1
,
qPNL-12.2
were observed with PVEs of 20.14%, 17.39% and 28.36%, respectively. The favorable allele RM125-145 bp on chromosome 7 for PNL was detected in both the natural population and CSSL population and was carried by Yue38 accession and parent Xiushui79. The detected favorable alleles could be used to improve target traits. |
| doi_str_mv | 10.1007/s10681-019-2528-9 |
| format | Article |
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qFLL-12
and
qFLW-12
showed 19.85% and 19.57% PVE, respectively. Four QTLs (
qFLA-10
,
qFLA-11
,
qFLA-12.1
,
qFLA-12.2
) detected for FLA showed PVEs ranging from 16.24% to 28.75%. For PNL,
qPNL-7
,
qPNL-12.1
,
qPNL-12.2
were observed with PVEs of 20.14%, 17.39% and 28.36%, respectively. The favorable allele RM125-145 bp on chromosome 7 for PNL was detected in both the natural population and CSSL population and was carried by Yue38 accession and parent Xiushui79. The detected favorable alleles could be used to improve target traits.</description><identifier>ISSN: 0014-2336</identifier><identifier>EISSN: 1573-5060</identifier><identifier>DOI: 10.1007/s10681-019-2528-9</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Alleles ; Analysis ; Biomedical and Life Sciences ; Biotechnology ; Chromosome 1 ; Chromosome 4 ; Chromosome 7 ; Chromosome 8 ; Chromosomes ; Crop production ; Cultivars ; Gene mapping ; Genotypes ; Leaf angle ; Leaves ; Life Sciences ; Mapping ; Methods ; Phenotypic variations ; Plant Genetics and Genomics ; Plant Pathology ; Plant Physiology ; Plant Sciences ; Population ; Quantitative genetics ; Quantitative trait loci ; Rice ; Seed industry</subject><ispartof>Euphytica, 2019-12, Vol.215 (12), p.1-17, Article 204</ispartof><rights>Springer Nature B.V. 2019</rights><rights>COPYRIGHT 2019 Springer</rights><rights>Euphytica is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c355t-83fa570811ea1d09ada34a7c228dcf775b925f303fcd7b40df42ad586b6631973</citedby><cites>FETCH-LOGICAL-c355t-83fa570811ea1d09ada34a7c228dcf775b925f303fcd7b40df42ad586b6631973</cites><orcidid>0000-0001-6251-4830</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10681-019-2528-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10681-019-2528-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Bux, Lal</creatorcontrib><creatorcontrib>Li, Dalu</creatorcontrib><creatorcontrib>Faheem, Muhammad</creatorcontrib><creatorcontrib>Sowadan, Ognigamal</creatorcontrib><creatorcontrib>Dong, Zhiyao</creatorcontrib><creatorcontrib>Liu, Erbao</creatorcontrib><creatorcontrib>Ali, Mehtab</creatorcontrib><creatorcontrib>Li, Yanhui</creatorcontrib><creatorcontrib>Sitoe, Helder Manuel</creatorcontrib><creatorcontrib>Mirani, Abdul Aziz</creatorcontrib><creatorcontrib>Hong, Delin</creatorcontrib><title>Detection of QTLs for outcrossing-related traits in rice (Oryza sativa L.) by association mapping and the RSTEP-LRT method</title><title>Euphytica</title><addtitle>Euphytica</addtitle><description>The outcrossing traits in rice affect the yield of hybrid rice seed production. In this study, 30 quantitative trait loci (QTLs) were detected in a natural population composed of 522 accessions by using a mixed linear model for the four outcrossing-related traits in 2017 and 2018. We detected 3, 4, 9 and 14 QTLs for flag leaf length (FLL), flag leaf width (FLW), flag leaf angle (FLA) and panicle neck length (PNL), respectively, among which 26 QTLs were novel. The favorable alleles and their carrier varieties were noticed with the largest phenotypic effect value. For FLL, marker allele RM6997-105 bp on chromosome 4 carried by Yue96 cultivar showed the highest phenotypic effect value (PEV), allele RM562-280 bp on chromosome 1 carried by Wanzhongqiu genotype for FLW, allele RM152-375 bp on chromosome 8 in typical carrier variety Zhongzuo93 for FLA and allele RM134-150 bp on chromosome 7 carried by Yue34 cultivar for PNL showed the highest PEVs. Additionally, nine QTLs were detected for the 4 traits with percentage of phenotypic variance explained (PVE) ranging from 16.24% (RM21) to 28.75% (RM5479) using a chromosome segment substitution line (CSSL) population. Among these detected QTLs,
qFLL-12
and
qFLW-12
showed 19.85% and 19.57% PVE, respectively. Four QTLs (
qFLA-10
,
qFLA-11
,
qFLA-12.1
,
qFLA-12.2
) detected for FLA showed PVEs ranging from 16.24% to 28.75%. For PNL,
qPNL-7
,
qPNL-12.1
,
qPNL-12.2
were observed with PVEs of 20.14%, 17.39% and 28.36%, respectively. The favorable allele RM125-145 bp on chromosome 7 for PNL was detected in both the natural population and CSSL population and was carried by Yue38 accession and parent Xiushui79. The detected favorable alleles could be used to improve target traits.</description><subject>Alleles</subject><subject>Analysis</subject><subject>Biomedical and Life Sciences</subject><subject>Biotechnology</subject><subject>Chromosome 1</subject><subject>Chromosome 4</subject><subject>Chromosome 7</subject><subject>Chromosome 8</subject><subject>Chromosomes</subject><subject>Crop production</subject><subject>Cultivars</subject><subject>Gene mapping</subject><subject>Genotypes</subject><subject>Leaf angle</subject><subject>Leaves</subject><subject>Life Sciences</subject><subject>Mapping</subject><subject>Methods</subject><subject>Phenotypic variations</subject><subject>Plant Genetics and Genomics</subject><subject>Plant Pathology</subject><subject>Plant Physiology</subject><subject>Plant Sciences</subject><subject>Population</subject><subject>Quantitative genetics</subject><subject>Quantitative trait loci</subject><subject>Rice</subject><subject>Seed industry</subject><issn>0014-2336</issn><issn>1573-5060</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kU1rGzEQhpfSQN2kP6A3QS_tQe5IWq12jyFN28BCPuqexVgfjoK9ciU54Pz6KtlCTmUOA8P7zNfbNB8ZLBmA-poZdD2jwAbKJe_p8KZZMKkEldDB22YBwFrKhejeNe9zfgCAQUlYNE_fXHGmhDiR6MntaszEx0TioZgUcw7Thia3xeIsKQlDySRMJAXjyOfrdHxCkrGERyTj8gtZHwnmHE3Al3473O8rT3Cq7L0jd79Wlzd0vFuRnSv30Z41Jx632X34l0-b398vVxc_6Xj94-rifKRGSFloLzxKBT1jDpmFAS2KFpXhvLfGKyXXA5degPDGqnUL1rccrey7ddcJNihx2nya--5T_HNwueiHeEhTHam5YJIDH3hXVctZtcGt02Hysd5rali3CyZOzodaP1esBSVU11aAzcDLo5Lzep_CDtNRM9DPnujZE1090c-e6KEyfGZy1U4bl15X-T_0F0zsjdw</recordid><startdate>20191201</startdate><enddate>20191201</enddate><creator>Bux, Lal</creator><creator>Li, Dalu</creator><creator>Faheem, Muhammad</creator><creator>Sowadan, Ognigamal</creator><creator>Dong, Zhiyao</creator><creator>Liu, Erbao</creator><creator>Ali, Mehtab</creator><creator>Li, Yanhui</creator><creator>Sitoe, Helder Manuel</creator><creator>Mirani, Abdul Aziz</creator><creator>Hong, Delin</creator><general>Springer Netherlands</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SN</scope><scope>7SS</scope><scope>7T7</scope><scope>7TM</scope><scope>7X2</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>M0K</scope><scope>M2P</scope><scope>M7N</scope><scope>P64</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>RC3</scope><orcidid>https://orcid.org/0000-0001-6251-4830</orcidid></search><sort><creationdate>20191201</creationdate><title>Detection of QTLs for outcrossing-related traits in rice (Oryza sativa L.) by association mapping and the RSTEP-LRT method</title><author>Bux, Lal ; Li, Dalu ; Faheem, Muhammad ; Sowadan, Ognigamal ; Dong, Zhiyao ; Liu, Erbao ; Ali, Mehtab ; Li, Yanhui ; Sitoe, Helder Manuel ; Mirani, Abdul Aziz ; Hong, Delin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c355t-83fa570811ea1d09ada34a7c228dcf775b925f303fcd7b40df42ad586b6631973</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Alleles</topic><topic>Analysis</topic><topic>Biomedical and Life Sciences</topic><topic>Biotechnology</topic><topic>Chromosome 1</topic><topic>Chromosome 4</topic><topic>Chromosome 7</topic><topic>Chromosome 8</topic><topic>Chromosomes</topic><topic>Crop production</topic><topic>Cultivars</topic><topic>Gene mapping</topic><topic>Genotypes</topic><topic>Leaf angle</topic><topic>Leaves</topic><topic>Life Sciences</topic><topic>Mapping</topic><topic>Methods</topic><topic>Phenotypic variations</topic><topic>Plant Genetics and Genomics</topic><topic>Plant Pathology</topic><topic>Plant Physiology</topic><topic>Plant Sciences</topic><topic>Population</topic><topic>Quantitative genetics</topic><topic>Quantitative trait loci</topic><topic>Rice</topic><topic>Seed industry</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bux, Lal</creatorcontrib><creatorcontrib>Li, Dalu</creatorcontrib><creatorcontrib>Faheem, Muhammad</creatorcontrib><creatorcontrib>Sowadan, Ognigamal</creatorcontrib><creatorcontrib>Dong, Zhiyao</creatorcontrib><creatorcontrib>Liu, Erbao</creatorcontrib><creatorcontrib>Ali, Mehtab</creatorcontrib><creatorcontrib>Li, Yanhui</creatorcontrib><creatorcontrib>Sitoe, Helder Manuel</creatorcontrib><creatorcontrib>Mirani, Abdul Aziz</creatorcontrib><creatorcontrib>Hong, Delin</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Agricultural Science Database</collection><collection>Science Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental 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>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><jtitle>Euphytica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bux, Lal</au><au>Li, Dalu</au><au>Faheem, Muhammad</au><au>Sowadan, Ognigamal</au><au>Dong, Zhiyao</au><au>Liu, Erbao</au><au>Ali, Mehtab</au><au>Li, Yanhui</au><au>Sitoe, Helder Manuel</au><au>Mirani, Abdul Aziz</au><au>Hong, Delin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detection of QTLs for outcrossing-related traits in rice (Oryza sativa L.) by association mapping and the RSTEP-LRT method</atitle><jtitle>Euphytica</jtitle><stitle>Euphytica</stitle><date>2019-12-01</date><risdate>2019</risdate><volume>215</volume><issue>12</issue><spage>1</spage><epage>17</epage><pages>1-17</pages><artnum>204</artnum><issn>0014-2336</issn><eissn>1573-5060</eissn><abstract>The outcrossing traits in rice affect the yield of hybrid rice seed production. In this study, 30 quantitative trait loci (QTLs) were detected in a natural population composed of 522 accessions by using a mixed linear model for the four outcrossing-related traits in 2017 and 2018. We detected 3, 4, 9 and 14 QTLs for flag leaf length (FLL), flag leaf width (FLW), flag leaf angle (FLA) and panicle neck length (PNL), respectively, among which 26 QTLs were novel. The favorable alleles and their carrier varieties were noticed with the largest phenotypic effect value. For FLL, marker allele RM6997-105 bp on chromosome 4 carried by Yue96 cultivar showed the highest phenotypic effect value (PEV), allele RM562-280 bp on chromosome 1 carried by Wanzhongqiu genotype for FLW, allele RM152-375 bp on chromosome 8 in typical carrier variety Zhongzuo93 for FLA and allele RM134-150 bp on chromosome 7 carried by Yue34 cultivar for PNL showed the highest PEVs. Additionally, nine QTLs were detected for the 4 traits with percentage of phenotypic variance explained (PVE) ranging from 16.24% (RM21) to 28.75% (RM5479) using a chromosome segment substitution line (CSSL) population. Among these detected QTLs,
qFLL-12
and
qFLW-12
showed 19.85% and 19.57% PVE, respectively. Four QTLs (
qFLA-10
,
qFLA-11
,
qFLA-12.1
,
qFLA-12.2
) detected for FLA showed PVEs ranging from 16.24% to 28.75%. For PNL,
qPNL-7
,
qPNL-12.1
,
qPNL-12.2
were observed with PVEs of 20.14%, 17.39% and 28.36%, respectively. The favorable allele RM125-145 bp on chromosome 7 for PNL was detected in both the natural population and CSSL population and was carried by Yue38 accession and parent Xiushui79. The detected favorable alleles could be used to improve target traits.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10681-019-2528-9</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0001-6251-4830</orcidid></addata></record> |
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| ispartof | Euphytica, 2019-12, Vol.215 (12), p.1-17, Article 204 |
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| source | SpringerNature Journals |
| subjects | Alleles Analysis Biomedical and Life Sciences Biotechnology Chromosome 1 Chromosome 4 Chromosome 7 Chromosome 8 Chromosomes Crop production Cultivars Gene mapping Genotypes Leaf angle Leaves Life Sciences Mapping Methods Phenotypic variations Plant Genetics and Genomics Plant Pathology Plant Physiology Plant Sciences Population Quantitative genetics Quantitative trait loci Rice Seed industry |
| title | Detection of QTLs for outcrossing-related traits in rice (Oryza sativa L.) by association mapping and the RSTEP-LRT method |
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