Large‐scale metabolite quantitative trait locus analysis provides new insights for high‐quality maize improvement
Summary It is generally recognized that many favorable genes which were lost during domestication, including those related to both nutritional value and stress resistance, remain hidden in wild relatives. To uncover such genes in teosinte, an ancestor of maize, we conducted metabolite profiling in a...
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Veröffentlicht in: | The Plant journal : for cell and molecular biology 2019-07, Vol.99 (2), p.216-230 |
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creator | Li, Kun Wen, Weiwei Alseekh, Saleh Yang, Xiaohong Guo, Huan Li, Wenqiang Wang, Luxi Pan, Qingchun Zhan, Wei Liu, Jie Li, Yanhua Wu, Xiao Brotman, Yariv Willmitzer, Lothar Li, Jiansheng Fernie, Alisdair R. Yan, Jianbing |
description | Summary
It is generally recognized that many favorable genes which were lost during domestication, including those related to both nutritional value and stress resistance, remain hidden in wild relatives. To uncover such genes in teosinte, an ancestor of maize, we conducted metabolite profiling in a BC2F7 population generated from a cross between the maize wild relative (Zea mays ssp. mexicana) and maize inbred line Mo17. In total, 65 primary metabolites were quantified in four tissues (seedling‐stage leaf, grouting‐stage leaf, young kernel and mature kernel) with clear tissue‐specific patterns emerging. Three hundred and fifty quantitative trait loci (QTLs) for these metabolites were obtained, which were distributed unevenly across the genome and included two QTL hotspots. Metabolite concentrations frequently increased in the presence of alleles from the teosinte genome while the opposite was observed for grain yield and shape trait QTLs. Combination of the multi‐tissue transcriptome and metabolome data provided considerable insight into the metabolic variations between maize and its wild relatives. This study thus identifies favorable genes hidden in the wild relative which should allow us to balance high yield and quality in future modern crop breeding programs.
Significance Statement
A large scale QTL mapping of primary metabolite traits in a teosinte‐maize population reveals robust advantages existing in teosinte primary metabolism. |
doi_str_mv | 10.1111/tpj.14317 |
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It is generally recognized that many favorable genes which were lost during domestication, including those related to both nutritional value and stress resistance, remain hidden in wild relatives. To uncover such genes in teosinte, an ancestor of maize, we conducted metabolite profiling in a BC2F7 population generated from a cross between the maize wild relative (Zea mays ssp. mexicana) and maize inbred line Mo17. In total, 65 primary metabolites were quantified in four tissues (seedling‐stage leaf, grouting‐stage leaf, young kernel and mature kernel) with clear tissue‐specific patterns emerging. Three hundred and fifty quantitative trait loci (QTLs) for these metabolites were obtained, which were distributed unevenly across the genome and included two QTL hotspots. Metabolite concentrations frequently increased in the presence of alleles from the teosinte genome while the opposite was observed for grain yield and shape trait QTLs. Combination of the multi‐tissue transcriptome and metabolome data provided considerable insight into the metabolic variations between maize and its wild relatives. This study thus identifies favorable genes hidden in the wild relative which should allow us to balance high yield and quality in future modern crop breeding programs.
Significance Statement
A large scale QTL mapping of primary metabolite traits in a teosinte‐maize population reveals robust advantages existing in teosinte primary metabolism.</description><identifier>ISSN: 0960-7412</identifier><identifier>EISSN: 1365-313X</identifier><identifier>DOI: 10.1111/tpj.14317</identifier><identifier>PMID: 30888713</identifier><language>eng</language><publisher>England: Blackwell Publishing Ltd</publisher><subject>Cluster Analysis ; Corn ; Crop yield ; Crosses, Genetic ; Domestication ; Gene expression ; Gene Expression Profiling ; Gene mapping ; Genes ; Genes, Plant ; genetic basis ; Genomes ; Grouting ; Inbreeding ; Kernels ; Leaves ; maize ; Metabolites ; Metabolomics ; Nutrient deficiency ; Nutritive value ; Nutritive Value - genetics ; Plant breeding ; primary metabolism ; Quantitative Trait Loci ; quantitative trait locus ; Seedlings ; teosinte ; Zea luxurians ; Zea mays - genetics ; Zea mays - growth & development ; Zea mays - metabolism</subject><ispartof>The Plant journal : for cell and molecular biology, 2019-07, Vol.99 (2), p.216-230</ispartof><rights>2019 The Authors The Plant Journal © 2019 John Wiley & Sons Ltd</rights><rights>2019 The Authors The Plant Journal © 2019 John Wiley & Sons Ltd.</rights><rights>Copyright © 2019 John Wiley & Sons Ltd and the Society for Experimental Biology</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4547-a1bf4597449d7fc6b821c117ac4544f6e14edcb83431c970ded4b1f7ca9ccc333</citedby><cites>FETCH-LOGICAL-c4547-a1bf4597449d7fc6b821c117ac4544f6e14edcb83431c970ded4b1f7ca9ccc333</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Ftpj.14317$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Ftpj.14317$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,1427,27903,27904,45553,45554,46387,46811</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30888713$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Kun</creatorcontrib><creatorcontrib>Wen, Weiwei</creatorcontrib><creatorcontrib>Alseekh, Saleh</creatorcontrib><creatorcontrib>Yang, Xiaohong</creatorcontrib><creatorcontrib>Guo, Huan</creatorcontrib><creatorcontrib>Li, Wenqiang</creatorcontrib><creatorcontrib>Wang, Luxi</creatorcontrib><creatorcontrib>Pan, Qingchun</creatorcontrib><creatorcontrib>Zhan, Wei</creatorcontrib><creatorcontrib>Liu, Jie</creatorcontrib><creatorcontrib>Li, Yanhua</creatorcontrib><creatorcontrib>Wu, Xiao</creatorcontrib><creatorcontrib>Brotman, Yariv</creatorcontrib><creatorcontrib>Willmitzer, Lothar</creatorcontrib><creatorcontrib>Li, Jiansheng</creatorcontrib><creatorcontrib>Fernie, Alisdair R.</creatorcontrib><creatorcontrib>Yan, Jianbing</creatorcontrib><title>Large‐scale metabolite quantitative trait locus analysis provides new insights for high‐quality maize improvement</title><title>The Plant journal : for cell and molecular biology</title><addtitle>Plant J</addtitle><description>Summary
It is generally recognized that many favorable genes which were lost during domestication, including those related to both nutritional value and stress resistance, remain hidden in wild relatives. To uncover such genes in teosinte, an ancestor of maize, we conducted metabolite profiling in a BC2F7 population generated from a cross between the maize wild relative (Zea mays ssp. mexicana) and maize inbred line Mo17. In total, 65 primary metabolites were quantified in four tissues (seedling‐stage leaf, grouting‐stage leaf, young kernel and mature kernel) with clear tissue‐specific patterns emerging. Three hundred and fifty quantitative trait loci (QTLs) for these metabolites were obtained, which were distributed unevenly across the genome and included two QTL hotspots. Metabolite concentrations frequently increased in the presence of alleles from the teosinte genome while the opposite was observed for grain yield and shape trait QTLs. Combination of the multi‐tissue transcriptome and metabolome data provided considerable insight into the metabolic variations between maize and its wild relatives. This study thus identifies favorable genes hidden in the wild relative which should allow us to balance high yield and quality in future modern crop breeding programs.
Significance Statement
A large scale QTL mapping of primary metabolite traits in a teosinte‐maize population reveals robust advantages existing in teosinte primary metabolism.</description><subject>Cluster Analysis</subject><subject>Corn</subject><subject>Crop yield</subject><subject>Crosses, Genetic</subject><subject>Domestication</subject><subject>Gene expression</subject><subject>Gene Expression Profiling</subject><subject>Gene mapping</subject><subject>Genes</subject><subject>Genes, Plant</subject><subject>genetic basis</subject><subject>Genomes</subject><subject>Grouting</subject><subject>Inbreeding</subject><subject>Kernels</subject><subject>Leaves</subject><subject>maize</subject><subject>Metabolites</subject><subject>Metabolomics</subject><subject>Nutrient deficiency</subject><subject>Nutritive value</subject><subject>Nutritive Value - genetics</subject><subject>Plant breeding</subject><subject>primary metabolism</subject><subject>Quantitative Trait Loci</subject><subject>quantitative trait locus</subject><subject>Seedlings</subject><subject>teosinte</subject><subject>Zea luxurians</subject><subject>Zea mays - genetics</subject><subject>Zea mays - growth & development</subject><subject>Zea mays - metabolism</subject><issn>0960-7412</issn><issn>1365-313X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kUtOwzAQhi0EglJYcAFkiQ0sApnYiZMlqniqEixAYhc5zqR1lUexnaKy4gickZPgUmCBhDe2NJ-_0cxPyAGEp-DPmZvPToEzEBtkACyJAwbsaZMMwiwJA8Eh2iG71s7CEARL-DbZYWGapgLYgPRjaSb48fZulayRNuhk0dXaIX3uZeu0k04vkDojtaN1p3pLZSvrpdWWzk230CVa2uIL1a3Vk6mztOoMnfqnd3qFVy1pI_UrUt2sPmCDrdsjW5WsLe5_30PyeHnxMLoOxndXN6PzcaB4zEUgoah4nAnOs1JUKinSCBSAkKsyrxIEjqUqUuZnV5kISyx5AZVQMlNKMcaG5Hjt9Z2fe7Qub7RVWNeyxa63eQQZhziKIfbo0R901vXGj-qpKBZZyjK_vSE5WVPKdNYarPK50Y00yxzCfJVF7rPIv7Lw7OG3sS8aLH_Jn-V74GwNvOgal_-b8of727XyE3X3l8s</recordid><startdate>201907</startdate><enddate>201907</enddate><creator>Li, Kun</creator><creator>Wen, Weiwei</creator><creator>Alseekh, Saleh</creator><creator>Yang, Xiaohong</creator><creator>Guo, Huan</creator><creator>Li, Wenqiang</creator><creator>Wang, Luxi</creator><creator>Pan, Qingchun</creator><creator>Zhan, Wei</creator><creator>Liu, Jie</creator><creator>Li, Yanhua</creator><creator>Wu, Xiao</creator><creator>Brotman, Yariv</creator><creator>Willmitzer, Lothar</creator><creator>Li, Jiansheng</creator><creator>Fernie, Alisdair R.</creator><creator>Yan, Jianbing</creator><general>Blackwell Publishing Ltd</general><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>7QO</scope><scope>7QP</scope><scope>7QR</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>201907</creationdate><title>Large‐scale metabolite quantitative trait locus analysis provides new insights for high‐quality maize improvement</title><author>Li, Kun ; Wen, Weiwei ; Alseekh, Saleh ; Yang, Xiaohong ; Guo, Huan ; Li, Wenqiang ; Wang, Luxi ; Pan, Qingchun ; Zhan, Wei ; Liu, Jie ; Li, Yanhua ; Wu, Xiao ; Brotman, Yariv ; Willmitzer, Lothar ; Li, Jiansheng ; Fernie, Alisdair R. ; Yan, Jianbing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4547-a1bf4597449d7fc6b821c117ac4544f6e14edcb83431c970ded4b1f7ca9ccc333</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Cluster Analysis</topic><topic>Corn</topic><topic>Crop yield</topic><topic>Crosses, Genetic</topic><topic>Domestication</topic><topic>Gene expression</topic><topic>Gene Expression Profiling</topic><topic>Gene mapping</topic><topic>Genes</topic><topic>Genes, Plant</topic><topic>genetic basis</topic><topic>Genomes</topic><topic>Grouting</topic><topic>Inbreeding</topic><topic>Kernels</topic><topic>Leaves</topic><topic>maize</topic><topic>Metabolites</topic><topic>Metabolomics</topic><topic>Nutrient deficiency</topic><topic>Nutritive value</topic><topic>Nutritive Value - genetics</topic><topic>Plant breeding</topic><topic>primary metabolism</topic><topic>Quantitative Trait Loci</topic><topic>quantitative trait locus</topic><topic>Seedlings</topic><topic>teosinte</topic><topic>Zea luxurians</topic><topic>Zea mays - genetics</topic><topic>Zea mays - growth & development</topic><topic>Zea mays - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Kun</creatorcontrib><creatorcontrib>Wen, Weiwei</creatorcontrib><creatorcontrib>Alseekh, Saleh</creatorcontrib><creatorcontrib>Yang, Xiaohong</creatorcontrib><creatorcontrib>Guo, Huan</creatorcontrib><creatorcontrib>Li, Wenqiang</creatorcontrib><creatorcontrib>Wang, Luxi</creatorcontrib><creatorcontrib>Pan, Qingchun</creatorcontrib><creatorcontrib>Zhan, Wei</creatorcontrib><creatorcontrib>Liu, Jie</creatorcontrib><creatorcontrib>Li, Yanhua</creatorcontrib><creatorcontrib>Wu, Xiao</creatorcontrib><creatorcontrib>Brotman, Yariv</creatorcontrib><creatorcontrib>Willmitzer, Lothar</creatorcontrib><creatorcontrib>Li, Jiansheng</creatorcontrib><creatorcontrib>Fernie, Alisdair R.</creatorcontrib><creatorcontrib>Yan, Jianbing</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>The Plant journal : for cell and molecular biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Kun</au><au>Wen, Weiwei</au><au>Alseekh, Saleh</au><au>Yang, Xiaohong</au><au>Guo, Huan</au><au>Li, Wenqiang</au><au>Wang, Luxi</au><au>Pan, Qingchun</au><au>Zhan, Wei</au><au>Liu, Jie</au><au>Li, Yanhua</au><au>Wu, Xiao</au><au>Brotman, Yariv</au><au>Willmitzer, Lothar</au><au>Li, Jiansheng</au><au>Fernie, Alisdair R.</au><au>Yan, Jianbing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Large‐scale metabolite quantitative trait locus analysis provides new insights for high‐quality maize improvement</atitle><jtitle>The Plant journal : for cell and molecular biology</jtitle><addtitle>Plant J</addtitle><date>2019-07</date><risdate>2019</risdate><volume>99</volume><issue>2</issue><spage>216</spage><epage>230</epage><pages>216-230</pages><issn>0960-7412</issn><eissn>1365-313X</eissn><abstract>Summary
It is generally recognized that many favorable genes which were lost during domestication, including those related to both nutritional value and stress resistance, remain hidden in wild relatives. To uncover such genes in teosinte, an ancestor of maize, we conducted metabolite profiling in a BC2F7 population generated from a cross between the maize wild relative (Zea mays ssp. mexicana) and maize inbred line Mo17. In total, 65 primary metabolites were quantified in four tissues (seedling‐stage leaf, grouting‐stage leaf, young kernel and mature kernel) with clear tissue‐specific patterns emerging. Three hundred and fifty quantitative trait loci (QTLs) for these metabolites were obtained, which were distributed unevenly across the genome and included two QTL hotspots. Metabolite concentrations frequently increased in the presence of alleles from the teosinte genome while the opposite was observed for grain yield and shape trait QTLs. Combination of the multi‐tissue transcriptome and metabolome data provided considerable insight into the metabolic variations between maize and its wild relatives. This study thus identifies favorable genes hidden in the wild relative which should allow us to balance high yield and quality in future modern crop breeding programs.
Significance Statement
A large scale QTL mapping of primary metabolite traits in a teosinte‐maize population reveals robust advantages existing in teosinte primary metabolism.</abstract><cop>England</cop><pub>Blackwell Publishing Ltd</pub><pmid>30888713</pmid><doi>10.1111/tpj.14317</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Cluster Analysis Corn Crop yield Crosses, Genetic Domestication Gene expression Gene Expression Profiling Gene mapping Genes Genes, Plant genetic basis Genomes Grouting Inbreeding Kernels Leaves maize Metabolites Metabolomics Nutrient deficiency Nutritive value Nutritive Value - genetics Plant breeding primary metabolism Quantitative Trait Loci quantitative trait locus Seedlings teosinte Zea luxurians Zea mays - genetics Zea mays - growth & development Zea mays - metabolism |
title | Large‐scale metabolite quantitative trait locus analysis provides new insights for high‐quality maize improvement |
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