Identification of QTL for ear row number and two-ranked versus many-ranked ear in maize across four environments
Ear row number (ERN) is not only a key trait involved in maize ( Zea mays L.) evolution but also an important component directly related to grain yield. In this report, 325 recombinant inbred lines (RILs, F 6:7 ) derived from a cross between B73 with 16 rows and SICAU1212 with four rows (two-ranked...
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description | Ear row number (ERN) is not only a key trait involved in maize (
Zea mays
L.) evolution but also an important component directly related to grain yield. In this report, 325 recombinant inbred lines (RILs, F
6:7
) derived from a cross between B73 with 16 rows and SICAU1212 with four rows (two-ranked with two rows per rank) were utilized to detect quantitative trait loci (QTL) associated with ERN and two-ranked versus many-ranked ears (TR). Compared to modern maize that formed approximately 8–20 rows, SICAU1212 with four rows was the extreme case. A total of 12 and 8 QTLs were associated with ERN and TR across four environments through single-environment mapping, respectively. Each QTL responsible for ERN explained 2.33–21.28 % of the phenotypic variation. And the TR variation contributed by individual TR QTL ranged from 2.09 to 12.99 %. Notably, only three QTLs,
qERN2
-
1
(bin 2.02),
qERN8
-
1
(bin 8.02) and
qERN8
-
2
(bin 8.04), were consistently detected in each environment and by joint analysis among all environments, which simultaneously influenced ERN and TR. One of the three QTLs,
qERN8
-
1
was also identified as interacting with environment. In addition, nine pairs of significant epistatic interactions (two for ERN and seven for TR) were detected among all QTLs. The epistasis between
qTR2
-
1
and
qTR8
-
1
was consistent in most environments. This present study may provide the understanding of the genetic basis of ERN and TR and a foundation for further fine-mapping of these common QTLs. |
doi_str_mv | 10.1007/s10681-015-1466-4 |
format | Article |
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Zea mays
L.) evolution but also an important component directly related to grain yield. In this report, 325 recombinant inbred lines (RILs, F
6:7
) derived from a cross between B73 with 16 rows and SICAU1212 with four rows (two-ranked with two rows per rank) were utilized to detect quantitative trait loci (QTL) associated with ERN and two-ranked versus many-ranked ears (TR). Compared to modern maize that formed approximately 8–20 rows, SICAU1212 with four rows was the extreme case. A total of 12 and 8 QTLs were associated with ERN and TR across four environments through single-environment mapping, respectively. Each QTL responsible for ERN explained 2.33–21.28 % of the phenotypic variation. And the TR variation contributed by individual TR QTL ranged from 2.09 to 12.99 %. Notably, only three QTLs,
qERN2
-
1
(bin 2.02),
qERN8
-
1
(bin 8.02) and
qERN8
-
2
(bin 8.04), were consistently detected in each environment and by joint analysis among all environments, which simultaneously influenced ERN and TR. One of the three QTLs,
qERN8
-
1
was also identified as interacting with environment. In addition, nine pairs of significant epistatic interactions (two for ERN and seven for TR) were detected among all QTLs. The epistasis between
qTR2
-
1
and
qTR8
-
1
was consistent in most environments. This present study may provide the understanding of the genetic basis of ERN and TR and a foundation for further fine-mapping of these common QTLs.</description><identifier>ISSN: 0014-2336</identifier><identifier>EISSN: 1573-5060</identifier><identifier>DOI: 10.1007/s10681-015-1466-4</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Analysis ; Biomedical and Life Sciences ; Biotechnology ; Corn ; Gene mapping ; Genetic markers ; Genotype & phenotype ; Life Sciences ; Phenotypic variations ; Plant Genetics and Genomics ; Plant Pathology ; Plant Physiology ; Plant populations ; Plant Sciences ; Quantitative genetics ; Rankings ; Selective breeding</subject><ispartof>Euphytica, 2015-11, Vol.206 (1), p.33-47</ispartof><rights>Springer Science+Business Media Dordrecht 2015</rights><rights>COPYRIGHT 2015 Springer</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c454t-d000556e21a52c280e466464e7582b9fd090e68031bfc11a376dc21204fbc2bc3</citedby><cites>FETCH-LOGICAL-c454t-d000556e21a52c280e466464e7582b9fd090e68031bfc11a376dc21204fbc2bc3</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/s10681-015-1466-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10681-015-1466-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Yang, Cong</creatorcontrib><creatorcontrib>Tang, Dengguo</creatorcontrib><creatorcontrib>Zhang, Lei</creatorcontrib><creatorcontrib>Liu, Jian</creatorcontrib><creatorcontrib>Rong, Tingzhao</creatorcontrib><title>Identification of QTL for ear row number and two-ranked versus many-ranked ear in maize across four environments</title><title>Euphytica</title><addtitle>Euphytica</addtitle><description>Ear row number (ERN) is not only a key trait involved in maize (
Zea mays
L.) evolution but also an important component directly related to grain yield. In this report, 325 recombinant inbred lines (RILs, F
6:7
) derived from a cross between B73 with 16 rows and SICAU1212 with four rows (two-ranked with two rows per rank) were utilized to detect quantitative trait loci (QTL) associated with ERN and two-ranked versus many-ranked ears (TR). Compared to modern maize that formed approximately 8–20 rows, SICAU1212 with four rows was the extreme case. A total of 12 and 8 QTLs were associated with ERN and TR across four environments through single-environment mapping, respectively. Each QTL responsible for ERN explained 2.33–21.28 % of the phenotypic variation. And the TR variation contributed by individual TR QTL ranged from 2.09 to 12.99 %. Notably, only three QTLs,
qERN2
-
1
(bin 2.02),
qERN8
-
1
(bin 8.02) and
qERN8
-
2
(bin 8.04), were consistently detected in each environment and by joint analysis among all environments, which simultaneously influenced ERN and TR. One of the three QTLs,
qERN8
-
1
was also identified as interacting with environment. In addition, nine pairs of significant epistatic interactions (two for ERN and seven for TR) were detected among all QTLs. The epistasis between
qTR2
-
1
and
qTR8
-
1
was consistent in most environments. This present study may provide the understanding of the genetic basis of ERN and TR and a foundation for further fine-mapping of these common QTLs.</description><subject>Analysis</subject><subject>Biomedical and Life Sciences</subject><subject>Biotechnology</subject><subject>Corn</subject><subject>Gene mapping</subject><subject>Genetic markers</subject><subject>Genotype & phenotype</subject><subject>Life Sciences</subject><subject>Phenotypic variations</subject><subject>Plant Genetics and Genomics</subject><subject>Plant Pathology</subject><subject>Plant Physiology</subject><subject>Plant populations</subject><subject>Plant Sciences</subject><subject>Quantitative genetics</subject><subject>Rankings</subject><subject>Selective breeding</subject><issn>0014-2336</issn><issn>1573-5060</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kc1qHDEQhEWwwWvHD-CbIGc53RpJs3s0Jj-GhRBwzkKjaRk5Hmkjzdo4Tx9NJoFcgg6Cpr7qaoqxK4RrBOjfVwSzRQGoBSpjhHrDNqj7TmgwcMI2AKiE7Dpzxs5rfQSAXa9hww53I6U5hujdHHPiOfCv93secuHkCi_5hafjNFDhLo18fsmiuPSdRv5MpR4rn1x6_TtagJjaKP4k7nzJtTajY3NKz7HkNLVN9S07De6p0uWf_4J9-_jh_vaz2H_5dHd7sxdeaTWLsSXU2pBEp6WXW6B2lTKKer2Vwy6MsAMyW-hwCB7Rdb0ZvUQJKgxeDr67YO9W30PJP45UZ_vYoqS20mIvUesOpGqq61X14J7IxhTyXJxvb6Qp-pwoxDa_6VFBrzu9ALgCv88rFOyhxMmVV4tglybs2oRtTdilCbswcmVq06YHKv9E-S_0CxPFiwo</recordid><startdate>20151101</startdate><enddate>20151101</enddate><creator>Yang, Cong</creator><creator>Tang, Dengguo</creator><creator>Zhang, Lei</creator><creator>Liu, Jian</creator><creator>Rong, Tingzhao</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>AEUYN</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></search><sort><creationdate>20151101</creationdate><title>Identification of QTL for ear row number and two-ranked versus many-ranked ear in maize across four environments</title><author>Yang, Cong ; Tang, Dengguo ; Zhang, Lei ; Liu, Jian ; Rong, Tingzhao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c454t-d000556e21a52c280e466464e7582b9fd090e68031bfc11a376dc21204fbc2bc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Analysis</topic><topic>Biomedical and Life Sciences</topic><topic>Biotechnology</topic><topic>Corn</topic><topic>Gene mapping</topic><topic>Genetic markers</topic><topic>Genotype & phenotype</topic><topic>Life Sciences</topic><topic>Phenotypic variations</topic><topic>Plant Genetics and Genomics</topic><topic>Plant Pathology</topic><topic>Plant Physiology</topic><topic>Plant populations</topic><topic>Plant Sciences</topic><topic>Quantitative genetics</topic><topic>Rankings</topic><topic>Selective breeding</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Cong</creatorcontrib><creatorcontrib>Tang, Dengguo</creatorcontrib><creatorcontrib>Zhang, Lei</creatorcontrib><creatorcontrib>Liu, Jian</creatorcontrib><creatorcontrib>Rong, Tingzhao</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 One Sustainability</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>Yang, Cong</au><au>Tang, Dengguo</au><au>Zhang, Lei</au><au>Liu, Jian</au><au>Rong, Tingzhao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of QTL for ear row number and two-ranked versus many-ranked ear in maize across four environments</atitle><jtitle>Euphytica</jtitle><stitle>Euphytica</stitle><date>2015-11-01</date><risdate>2015</risdate><volume>206</volume><issue>1</issue><spage>33</spage><epage>47</epage><pages>33-47</pages><issn>0014-2336</issn><eissn>1573-5060</eissn><abstract>Ear row number (ERN) is not only a key trait involved in maize (
Zea mays
L.) evolution but also an important component directly related to grain yield. In this report, 325 recombinant inbred lines (RILs, F
6:7
) derived from a cross between B73 with 16 rows and SICAU1212 with four rows (two-ranked with two rows per rank) were utilized to detect quantitative trait loci (QTL) associated with ERN and two-ranked versus many-ranked ears (TR). Compared to modern maize that formed approximately 8–20 rows, SICAU1212 with four rows was the extreme case. A total of 12 and 8 QTLs were associated with ERN and TR across four environments through single-environment mapping, respectively. Each QTL responsible for ERN explained 2.33–21.28 % of the phenotypic variation. And the TR variation contributed by individual TR QTL ranged from 2.09 to 12.99 %. Notably, only three QTLs,
qERN2
-
1
(bin 2.02),
qERN8
-
1
(bin 8.02) and
qERN8
-
2
(bin 8.04), were consistently detected in each environment and by joint analysis among all environments, which simultaneously influenced ERN and TR. One of the three QTLs,
qERN8
-
1
was also identified as interacting with environment. In addition, nine pairs of significant epistatic interactions (two for ERN and seven for TR) were detected among all QTLs. The epistasis between
qTR2
-
1
and
qTR8
-
1
was consistent in most environments. This present study may provide the understanding of the genetic basis of ERN and TR and a foundation for further fine-mapping of these common QTLs.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10681-015-1466-4</doi><tpages>15</tpages></addata></record> |
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source | SpringerLink Journals - AutoHoldings |
subjects | Analysis Biomedical and Life Sciences Biotechnology Corn Gene mapping Genetic markers Genotype & phenotype Life Sciences Phenotypic variations Plant Genetics and Genomics Plant Pathology Plant Physiology Plant populations Plant Sciences Quantitative genetics Rankings Selective breeding |
title | Identification of QTL for ear row number and two-ranked versus many-ranked ear in maize across four environments |
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