Identification of loci contributing to maize drought tolerance in a genome-wide association study
Genome-wide association studies (GWAS) have been used widely to analyze the genetic control of complex traits in crops. In the present study, seven related phenotypic traits were analyzed in combination to study their association with 41,101 SNPs in 201 maize inbred lines that had been evaluated in...
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| Veröffentlicht in: | Euphytica 2016-07, Vol.210 (2), p.165-179 |
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| creator | Wang, Nan Wang, Zhen-ping Liang, Xiao-ling Weng, Jian-feng Lv, Xiang-ling Zhang, De-gui Yang, Jie Yong, Hong-jun Li, Ming-shun Li, Feng-hai Jiang, Li-yan Zhang, Shi-huang Hao, Zhuan-fang Li, Xin-hai |
| description | Genome-wide association studies (GWAS) have been used widely to analyze the genetic control of complex traits in crops. In the present study, seven related phenotypic traits were analyzed in combination to study their association with 41,101 SNPs in 201 maize inbred lines that had been evaluated in seven environments (year/location combinations) under water-stressed (WS) or well-watered (WW) regimes. By comparing the association signals with a fixed
P
value, GWAS showed that the number of association signals identified varied among traits and in different environments. Data that were missing under the severe water stress treatment had a great impact on the results of this GWAS. A total of 206 significant SNPs were associated with 115 candidate genes for drought tolerance and related traits including final grain yield, total number of ears per plot, kernel number per row, plant height, anthesis-silking interval, days to anthesis (DtA), and days to silking (DtS). Among these, four genes were associated with at least two different related traits, and six genes associated with traits were detected in at least two environments under water stress. Nine candidate QTL identified by GWAS were also discovered, three of which co-located to a consensus QTL region meta-analyzed by linkage mapping for drought tolerance. Some regulatory genes related to abiotic stress responses might also make a strong contribution to drought tolerance. The comprehensive information presented here regarding consensus QTL combined with candidate genes derived from GWAS provides an important reference tool for improving maize drought tolerance. |
| doi_str_mv | 10.1007/s10681-016-1688-0 |
| format | Article |
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P
value, GWAS showed that the number of association signals identified varied among traits and in different environments. Data that were missing under the severe water stress treatment had a great impact on the results of this GWAS. A total of 206 significant SNPs were associated with 115 candidate genes for drought tolerance and related traits including final grain yield, total number of ears per plot, kernel number per row, plant height, anthesis-silking interval, days to anthesis (DtA), and days to silking (DtS). Among these, four genes were associated with at least two different related traits, and six genes associated with traits were detected in at least two environments under water stress. Nine candidate QTL identified by GWAS were also discovered, three of which co-located to a consensus QTL region meta-analyzed by linkage mapping for drought tolerance. Some regulatory genes related to abiotic stress responses might also make a strong contribution to drought tolerance. The comprehensive information presented here regarding consensus QTL combined with candidate genes derived from GWAS provides an important reference tool for improving maize drought tolerance.</description><identifier>ISSN: 0014-2336</identifier><identifier>EISSN: 1573-5060</identifier><identifier>DOI: 10.1007/s10681-016-1688-0</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Analysis ; Aquatic resources ; Biomedical and Life Sciences ; Biotechnology ; Corn ; Crop yields ; Drought ; Drought resistance ; Gene loci ; Genetic research ; Genomes ; Genomics ; Life Sciences ; Plant Genetics and Genomics ; Plant Pathology ; Plant Physiology ; Plant Sciences ; Plant tolerance ; Quantitative genetics ; Single nucleotide polymorphisms ; Water stress ; Zea mays</subject><ispartof>Euphytica, 2016-07, Vol.210 (2), p.165-179</ispartof><rights>Springer Science+Business Media Dordrecht 2016</rights><rights>COPYRIGHT 2016 Springer</rights><rights>Euphytica is a copyright of Springer, 2016.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c388t-e4abf8986340d31044889c183ac75361af4d1b9d4a781b448ef07cabefc1f8073</citedby><cites>FETCH-LOGICAL-c388t-e4abf8986340d31044889c183ac75361af4d1b9d4a781b448ef07cabefc1f8073</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/s10681-016-1688-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10681-016-1688-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Wang, Nan</creatorcontrib><creatorcontrib>Wang, Zhen-ping</creatorcontrib><creatorcontrib>Liang, Xiao-ling</creatorcontrib><creatorcontrib>Weng, Jian-feng</creatorcontrib><creatorcontrib>Lv, Xiang-ling</creatorcontrib><creatorcontrib>Zhang, De-gui</creatorcontrib><creatorcontrib>Yang, Jie</creatorcontrib><creatorcontrib>Yong, Hong-jun</creatorcontrib><creatorcontrib>Li, Ming-shun</creatorcontrib><creatorcontrib>Li, Feng-hai</creatorcontrib><creatorcontrib>Jiang, Li-yan</creatorcontrib><creatorcontrib>Zhang, Shi-huang</creatorcontrib><creatorcontrib>Hao, Zhuan-fang</creatorcontrib><creatorcontrib>Li, Xin-hai</creatorcontrib><title>Identification of loci contributing to maize drought tolerance in a genome-wide association study</title><title>Euphytica</title><addtitle>Euphytica</addtitle><description>Genome-wide association studies (GWAS) have been used widely to analyze the genetic control of complex traits in crops. In the present study, seven related phenotypic traits were analyzed in combination to study their association with 41,101 SNPs in 201 maize inbred lines that had been evaluated in seven environments (year/location combinations) under water-stressed (WS) or well-watered (WW) regimes. By comparing the association signals with a fixed
P
value, GWAS showed that the number of association signals identified varied among traits and in different environments. Data that were missing under the severe water stress treatment had a great impact on the results of this GWAS. A total of 206 significant SNPs were associated with 115 candidate genes for drought tolerance and related traits including final grain yield, total number of ears per plot, kernel number per row, plant height, anthesis-silking interval, days to anthesis (DtA), and days to silking (DtS). Among these, four genes were associated with at least two different related traits, and six genes associated with traits were detected in at least two environments under water stress. Nine candidate QTL identified by GWAS were also discovered, three of which co-located to a consensus QTL region meta-analyzed by linkage mapping for drought tolerance. Some regulatory genes related to abiotic stress responses might also make a strong contribution to drought tolerance. The comprehensive information presented here regarding consensus QTL combined with candidate genes derived from GWAS provides an important reference tool for improving maize drought tolerance.</description><subject>Analysis</subject><subject>Aquatic resources</subject><subject>Biomedical and Life Sciences</subject><subject>Biotechnology</subject><subject>Corn</subject><subject>Crop yields</subject><subject>Drought</subject><subject>Drought resistance</subject><subject>Gene loci</subject><subject>Genetic research</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Life Sciences</subject><subject>Plant Genetics and Genomics</subject><subject>Plant Pathology</subject><subject>Plant Physiology</subject><subject>Plant Sciences</subject><subject>Plant tolerance</subject><subject>Quantitative genetics</subject><subject>Single nucleotide polymorphisms</subject><subject>Water stress</subject><subject>Zea mays</subject><issn>0014-2336</issn><issn>1573-5060</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kUFrFjEQhoMo-Fn7A7wFvHhJnelmN_mOpWgtFLzoOWSzk23KblKTLFJ_vflYD1IoOQQmzzPM5GXsA8IFAqjPBWHQKAAHgYPWAl6xA_aqEz0M8JodAFCKy64b3rJ3pTwAwFH1cGD2dqJYgw_O1pAiT54vyQXuUqw5jFsNceY18dWGP8SnnLb5vrbCQtlGRzxEbvlMMa0kfoeJuC2l-XuzUrfp6T174-1S6PzffcZ-fv3y4_qbuPt-c3t9dSdcp3UVJO3o9VEPnYSpQ5BS66ND3Vmn-m5A6-WE43GSVmkc2yt5UM6O5B16Dao7Y5_2vo85_dqoVLOG4mhZbKS0FYMaWvPT2g39-Ax9SFuObbpGDb3USvWyURc7NduFTIg-1WxdOxOtof0P-dDqVwolKKkBm4C74HIqJZM3jzmsNj8ZBHNKyewpmZaSOaVkoDmXu1MaG2fK_43yovQX7OSU1g</recordid><startdate>20160701</startdate><enddate>20160701</enddate><creator>Wang, Nan</creator><creator>Wang, Zhen-ping</creator><creator>Liang, Xiao-ling</creator><creator>Weng, Jian-feng</creator><creator>Lv, Xiang-ling</creator><creator>Zhang, De-gui</creator><creator>Yang, Jie</creator><creator>Yong, Hong-jun</creator><creator>Li, Ming-shun</creator><creator>Li, Feng-hai</creator><creator>Jiang, Li-yan</creator><creator>Zhang, Shi-huang</creator><creator>Hao, Zhuan-fang</creator><creator>Li, Xin-hai</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>20160701</creationdate><title>Identification of loci contributing to maize drought tolerance in a genome-wide association study</title><author>Wang, Nan ; Wang, Zhen-ping ; Liang, Xiao-ling ; Weng, Jian-feng ; Lv, Xiang-ling ; Zhang, De-gui ; Yang, Jie ; Yong, Hong-jun ; Li, Ming-shun ; Li, Feng-hai ; Jiang, Li-yan ; Zhang, Shi-huang ; Hao, Zhuan-fang ; Li, Xin-hai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c388t-e4abf8986340d31044889c183ac75361af4d1b9d4a781b448ef07cabefc1f8073</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Analysis</topic><topic>Aquatic resources</topic><topic>Biomedical and Life Sciences</topic><topic>Biotechnology</topic><topic>Corn</topic><topic>Crop yields</topic><topic>Drought</topic><topic>Drought resistance</topic><topic>Gene loci</topic><topic>Genetic research</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Life Sciences</topic><topic>Plant Genetics and Genomics</topic><topic>Plant Pathology</topic><topic>Plant Physiology</topic><topic>Plant Sciences</topic><topic>Plant tolerance</topic><topic>Quantitative genetics</topic><topic>Single nucleotide polymorphisms</topic><topic>Water stress</topic><topic>Zea mays</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Nan</creatorcontrib><creatorcontrib>Wang, Zhen-ping</creatorcontrib><creatorcontrib>Liang, Xiao-ling</creatorcontrib><creatorcontrib>Weng, Jian-feng</creatorcontrib><creatorcontrib>Lv, Xiang-ling</creatorcontrib><creatorcontrib>Zhang, De-gui</creatorcontrib><creatorcontrib>Yang, Jie</creatorcontrib><creatorcontrib>Yong, Hong-jun</creatorcontrib><creatorcontrib>Li, Ming-shun</creatorcontrib><creatorcontrib>Li, Feng-hai</creatorcontrib><creatorcontrib>Jiang, Li-yan</creatorcontrib><creatorcontrib>Zhang, Shi-huang</creatorcontrib><creatorcontrib>Hao, Zhuan-fang</creatorcontrib><creatorcontrib>Li, Xin-hai</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>Wang, Nan</au><au>Wang, Zhen-ping</au><au>Liang, Xiao-ling</au><au>Weng, Jian-feng</au><au>Lv, Xiang-ling</au><au>Zhang, De-gui</au><au>Yang, Jie</au><au>Yong, Hong-jun</au><au>Li, Ming-shun</au><au>Li, Feng-hai</au><au>Jiang, Li-yan</au><au>Zhang, Shi-huang</au><au>Hao, Zhuan-fang</au><au>Li, Xin-hai</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of loci contributing to maize drought tolerance in a genome-wide association study</atitle><jtitle>Euphytica</jtitle><stitle>Euphytica</stitle><date>2016-07-01</date><risdate>2016</risdate><volume>210</volume><issue>2</issue><spage>165</spage><epage>179</epage><pages>165-179</pages><issn>0014-2336</issn><eissn>1573-5060</eissn><abstract>Genome-wide association studies (GWAS) have been used widely to analyze the genetic control of complex traits in crops. In the present study, seven related phenotypic traits were analyzed in combination to study their association with 41,101 SNPs in 201 maize inbred lines that had been evaluated in seven environments (year/location combinations) under water-stressed (WS) or well-watered (WW) regimes. By comparing the association signals with a fixed
P
value, GWAS showed that the number of association signals identified varied among traits and in different environments. Data that were missing under the severe water stress treatment had a great impact on the results of this GWAS. A total of 206 significant SNPs were associated with 115 candidate genes for drought tolerance and related traits including final grain yield, total number of ears per plot, kernel number per row, plant height, anthesis-silking interval, days to anthesis (DtA), and days to silking (DtS). Among these, four genes were associated with at least two different related traits, and six genes associated with traits were detected in at least two environments under water stress. Nine candidate QTL identified by GWAS were also discovered, three of which co-located to a consensus QTL region meta-analyzed by linkage mapping for drought tolerance. Some regulatory genes related to abiotic stress responses might also make a strong contribution to drought tolerance. The comprehensive information presented here regarding consensus QTL combined with candidate genes derived from GWAS provides an important reference tool for improving maize drought tolerance.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10681-016-1688-0</doi><tpages>15</tpages></addata></record> |
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| subjects | Analysis Aquatic resources Biomedical and Life Sciences Biotechnology Corn Crop yields Drought Drought resistance Gene loci Genetic research Genomes Genomics Life Sciences Plant Genetics and Genomics Plant Pathology Plant Physiology Plant Sciences Plant tolerance Quantitative genetics Single nucleotide polymorphisms Water stress Zea mays |
| title | Identification of loci contributing to maize drought tolerance in a genome-wide association study |
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