Identification of candidate genes and genomic prediction of soybean fatty acid components in two soybean populations
Soybean, a source of plant-derived lipids, contains an array of fatty acids essential for health. A comprehensive understanding of the fatty acid profiles in soybean is crucial for enhancing soybean cultivars and augmenting their qualitative attributes. Here, 180 F 10 generation recombinant inbred l...
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| Veröffentlicht in: | Theoretical and applied genetics 2024-09, Vol.137 (9), p.211, Article 211 |
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| creator | Wang, Fengmin Zhao, Tiantian Feng, Yan Ji, Zengfa Zhao, Qingsong Meng, Qingmin Liu, Bingqiang Liu, Luping Chen, Qiang Qi, Jin Zhu, Zhengge Yang, Chunyan Qin, Jun |
| description | Soybean, a source of plant-derived lipids, contains an array of fatty acids essential for health. A comprehensive understanding of the fatty acid profiles in soybean is crucial for enhancing soybean cultivars and augmenting their qualitative attributes. Here, 180 F
10
generation recombinant inbred lines (RILs), derived from the cross-breeding of the cultivated soybean variety ‘Jidou 12’ and the wild soybean ‘
Y
9,’ were used as primary experimental subjects. Using inclusive composite interval mapping (ICIM), this study undertook a quantitative trait locus (QTL) analysis on five distinct fatty acid components in the RIL population from 2019 to 2021. Concurrently, a genome-wide association study (GWAS) was conducted on 290 samples from a genetically diverse natural population to scrutinize the five fatty acid components during the same timeframe, thereby aiming to identify loci closely associated with fatty acid profiles. In addition, haplotype analysis and the Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed to predict candidate genes. The QTL analysis elucidated 23 stable QTLs intricately associated with the five fatty acid components, exhibiting phenotypic contribution rates ranging from 2.78% to 25.37%. In addition, GWAS of the natural population unveiled 102 significant loci associated with these fatty acid components. The haplotype analysis of the colocalized loci revealed that
Glyma.06G221400
on chromosome 6 exhibited a significant correlation with stearic acid content, with Hap1 showing a markedly elevated stearic acid level compared with Hap2 and Hap3. Similarly,
Glyma.12G075100
on chromosome 12 was significantly associated with the contents of oleic, linoleic, and linolenic acids, suggesting its involvement in fatty acid biosynthesis. In the natural population, candidate genes associated with the contents of palmitic and linolenic acids were predominantly from the fatty acid metabolic pathway, indicating their potential role as pivotal genes in the critical steps of fatty acid metabolism. Furthermore, genomic selection (GS) for fatty acid components was conducted using ridge regression best linear unbiased prediction based on both random single nucleotide polymorphisms (SNPs) and SNPs significantly associated with fatty acid components identified by GWAS. GS accuracy was contingent upon the SNP set used. Notably, GS efficiency was enhanced when using SNPs derived from QTL mapping analysis and GWAS compared with random SNPs, a |
| doi_str_mv | 10.1007/s00122-024-04716-8 |
| format | Article |
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10
generation recombinant inbred lines (RILs), derived from the cross-breeding of the cultivated soybean variety ‘Jidou 12’ and the wild soybean ‘
Y
9,’ were used as primary experimental subjects. Using inclusive composite interval mapping (ICIM), this study undertook a quantitative trait locus (QTL) analysis on five distinct fatty acid components in the RIL population from 2019 to 2021. Concurrently, a genome-wide association study (GWAS) was conducted on 290 samples from a genetically diverse natural population to scrutinize the five fatty acid components during the same timeframe, thereby aiming to identify loci closely associated with fatty acid profiles. In addition, haplotype analysis and the Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed to predict candidate genes. The QTL analysis elucidated 23 stable QTLs intricately associated with the five fatty acid components, exhibiting phenotypic contribution rates ranging from 2.78% to 25.37%. In addition, GWAS of the natural population unveiled 102 significant loci associated with these fatty acid components. The haplotype analysis of the colocalized loci revealed that
Glyma.06G221400
on chromosome 6 exhibited a significant correlation with stearic acid content, with Hap1 showing a markedly elevated stearic acid level compared with Hap2 and Hap3. Similarly,
Glyma.12G075100
on chromosome 12 was significantly associated with the contents of oleic, linoleic, and linolenic acids, suggesting its involvement in fatty acid biosynthesis. In the natural population, candidate genes associated with the contents of palmitic and linolenic acids were predominantly from the fatty acid metabolic pathway, indicating their potential role as pivotal genes in the critical steps of fatty acid metabolism. Furthermore, genomic selection (GS) for fatty acid components was conducted using ridge regression best linear unbiased prediction based on both random single nucleotide polymorphisms (SNPs) and SNPs significantly associated with fatty acid components identified by GWAS. GS accuracy was contingent upon the SNP set used. Notably, GS efficiency was enhanced when using SNPs derived from QTL mapping analysis and GWAS compared with random SNPs, and reached a plateau when the number of SNP markers exceeded 3,000. This study thus indicates that
Glyma.06G221400
and
Glyma.12G075100
are genes integral to the synthesis and regulatory mechanisms of fatty acids. It provides insights into the complex biosynthesis and regulation of fatty acids, with significant implications for the directed improvement of soybean oil quality and the selection of superior soybean varieties. The SNP markers delineated in this study can be instrumental in establishing an efficacious pipeline for marker-assisted selection and GS aimed at improving soybean fatty acid components.</description><identifier>ISSN: 0040-5752</identifier><identifier>ISSN: 1432-2242</identifier><identifier>EISSN: 1432-2242</identifier><identifier>DOI: 10.1007/s00122-024-04716-8</identifier><identifier>PMID: 39210238</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Agriculture ; Biochemistry ; Biomedical and Life Sciences ; Biosynthesis ; Biotechnology ; Chromosome 12 ; Chromosome 6 ; Chromosome Mapping - methods ; Cross-breeding ; Cultivars ; Fatty acids ; Fatty Acids - metabolism ; Gene regulation ; Genes, Plant ; Genetic Association Studies ; Genome-wide association studies ; Genome-Wide Association Study ; Genomic analysis ; Glycine max - genetics ; Glycine max - metabolism ; Haplotypes ; Inbreeding ; Life Sciences ; Lipids ; Marker-assisted selection ; Metabolic pathways ; Original Article ; Phenotype ; Plant Biochemistry ; Plant Breeding ; Plant Breeding/Biotechnology ; Plant Genetics and Genomics ; Plants ; Polymorphism, Single Nucleotide ; Population genetics ; Population studies ; Quantitative Trait Loci ; Single-nucleotide polymorphism ; Soybeans ; Stearic acid</subject><ispartof>Theoretical and applied genetics, 2024-09, Vol.137 (9), p.211, Article 211</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c256t-3bf36817dd7e52495412a6bdb6152a6a457a7bb89cdb0e7114670943cd03c38f3</cites><orcidid>0000-0002-8136-0416</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/s00122-024-04716-8$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00122-024-04716-8$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,781,785,27926,27927,41490,42559,51321</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39210238$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Fengmin</creatorcontrib><creatorcontrib>Zhao, Tiantian</creatorcontrib><creatorcontrib>Feng, Yan</creatorcontrib><creatorcontrib>Ji, Zengfa</creatorcontrib><creatorcontrib>Zhao, Qingsong</creatorcontrib><creatorcontrib>Meng, Qingmin</creatorcontrib><creatorcontrib>Liu, Bingqiang</creatorcontrib><creatorcontrib>Liu, Luping</creatorcontrib><creatorcontrib>Chen, Qiang</creatorcontrib><creatorcontrib>Qi, Jin</creatorcontrib><creatorcontrib>Zhu, Zhengge</creatorcontrib><creatorcontrib>Yang, Chunyan</creatorcontrib><creatorcontrib>Qin, Jun</creatorcontrib><title>Identification of candidate genes and genomic prediction of soybean fatty acid components in two soybean populations</title><title>Theoretical and applied genetics</title><addtitle>Theor Appl Genet</addtitle><addtitle>Theor Appl Genet</addtitle><description>Soybean, a source of plant-derived lipids, contains an array of fatty acids essential for health. A comprehensive understanding of the fatty acid profiles in soybean is crucial for enhancing soybean cultivars and augmenting their qualitative attributes. Here, 180 F
10
generation recombinant inbred lines (RILs), derived from the cross-breeding of the cultivated soybean variety ‘Jidou 12’ and the wild soybean ‘
Y
9,’ were used as primary experimental subjects. Using inclusive composite interval mapping (ICIM), this study undertook a quantitative trait locus (QTL) analysis on five distinct fatty acid components in the RIL population from 2019 to 2021. Concurrently, a genome-wide association study (GWAS) was conducted on 290 samples from a genetically diverse natural population to scrutinize the five fatty acid components during the same timeframe, thereby aiming to identify loci closely associated with fatty acid profiles. In addition, haplotype analysis and the Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed to predict candidate genes. The QTL analysis elucidated 23 stable QTLs intricately associated with the five fatty acid components, exhibiting phenotypic contribution rates ranging from 2.78% to 25.37%. In addition, GWAS of the natural population unveiled 102 significant loci associated with these fatty acid components. The haplotype analysis of the colocalized loci revealed that
Glyma.06G221400
on chromosome 6 exhibited a significant correlation with stearic acid content, with Hap1 showing a markedly elevated stearic acid level compared with Hap2 and Hap3. Similarly,
Glyma.12G075100
on chromosome 12 was significantly associated with the contents of oleic, linoleic, and linolenic acids, suggesting its involvement in fatty acid biosynthesis. In the natural population, candidate genes associated with the contents of palmitic and linolenic acids were predominantly from the fatty acid metabolic pathway, indicating their potential role as pivotal genes in the critical steps of fatty acid metabolism. Furthermore, genomic selection (GS) for fatty acid components was conducted using ridge regression best linear unbiased prediction based on both random single nucleotide polymorphisms (SNPs) and SNPs significantly associated with fatty acid components identified by GWAS. GS accuracy was contingent upon the SNP set used. Notably, GS efficiency was enhanced when using SNPs derived from QTL mapping analysis and GWAS compared with random SNPs, and reached a plateau when the number of SNP markers exceeded 3,000. This study thus indicates that
Glyma.06G221400
and
Glyma.12G075100
are genes integral to the synthesis and regulatory mechanisms of fatty acids. It provides insights into the complex biosynthesis and regulation of fatty acids, with significant implications for the directed improvement of soybean oil quality and the selection of superior soybean varieties. The SNP markers delineated in this study can be instrumental in establishing an efficacious pipeline for marker-assisted selection and GS aimed at improving soybean fatty acid components.</description><subject>Agriculture</subject><subject>Biochemistry</subject><subject>Biomedical and Life Sciences</subject><subject>Biosynthesis</subject><subject>Biotechnology</subject><subject>Chromosome 12</subject><subject>Chromosome 6</subject><subject>Chromosome Mapping - methods</subject><subject>Cross-breeding</subject><subject>Cultivars</subject><subject>Fatty acids</subject><subject>Fatty Acids - metabolism</subject><subject>Gene regulation</subject><subject>Genes, Plant</subject><subject>Genetic Association Studies</subject><subject>Genome-wide association studies</subject><subject>Genome-Wide Association Study</subject><subject>Genomic analysis</subject><subject>Glycine max - genetics</subject><subject>Glycine max - metabolism</subject><subject>Haplotypes</subject><subject>Inbreeding</subject><subject>Life Sciences</subject><subject>Lipids</subject><subject>Marker-assisted selection</subject><subject>Metabolic pathways</subject><subject>Original Article</subject><subject>Phenotype</subject><subject>Plant Biochemistry</subject><subject>Plant Breeding</subject><subject>Plant Breeding/Biotechnology</subject><subject>Plant Genetics and Genomics</subject><subject>Plants</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Population genetics</subject><subject>Population studies</subject><subject>Quantitative Trait Loci</subject><subject>Single-nucleotide polymorphism</subject><subject>Soybeans</subject><subject>Stearic acid</subject><issn>0040-5752</issn><issn>1432-2242</issn><issn>1432-2242</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kctKxTAQhoMoery8gAsJuHFTndyadiniDQQ3ug5pkkrkNKlNipy3N8fjBVy4mhnyzT-BD6FjAucEQF4kAEJpBZRXwCWpq2YLLQhntKKU0220AOBQCSnoHtpP6RUAqAC2i_ZYSwlQ1ixQvrcuZN97o7OPAcceGx2stzo7_OKCS7iM6y4O3uBxctabbzLFVed0wL3OeYW18RabOIwxlMiEfcD5Pf5AYxzn5eeRdIh2er1M7uirHqDnm-unq7vq4fH2_uryoTJU1LliXc_qhkhrpROUt4ITquvOdjURpdFcSC27rmmN7cBJQngtoeXMWGCGNT07QGeb3HGKb7NLWQ0-Gbdc6uDinBSDtm0ABCMFPf2DvsZ5CuV3a6oRtGVcFIpuKDPFlCbXq3Hyg55WioBaO1EbJ6o4UZ9OVFOWTr6i525w9mflW0IB2AZI5Sm8uOn39j-xH3bYl6k</recordid><startdate>20240901</startdate><enddate>20240901</enddate><creator>Wang, Fengmin</creator><creator>Zhao, Tiantian</creator><creator>Feng, Yan</creator><creator>Ji, Zengfa</creator><creator>Zhao, Qingsong</creator><creator>Meng, Qingmin</creator><creator>Liu, Bingqiang</creator><creator>Liu, Luping</creator><creator>Chen, Qiang</creator><creator>Qi, Jin</creator><creator>Zhu, Zhengge</creator><creator>Yang, Chunyan</creator><creator>Qin, Jun</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</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>7SS</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-8136-0416</orcidid></search><sort><creationdate>20240901</creationdate><title>Identification of candidate genes and genomic prediction of soybean fatty acid components in two soybean populations</title><author>Wang, Fengmin ; Zhao, Tiantian ; Feng, Yan ; Ji, Zengfa ; Zhao, Qingsong ; Meng, Qingmin ; Liu, Bingqiang ; Liu, Luping ; Chen, Qiang ; Qi, Jin ; Zhu, Zhengge ; Yang, Chunyan ; Qin, Jun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c256t-3bf36817dd7e52495412a6bdb6152a6a457a7bb89cdb0e7114670943cd03c38f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Agriculture</topic><topic>Biochemistry</topic><topic>Biomedical and Life Sciences</topic><topic>Biosynthesis</topic><topic>Biotechnology</topic><topic>Chromosome 12</topic><topic>Chromosome 6</topic><topic>Chromosome Mapping - methods</topic><topic>Cross-breeding</topic><topic>Cultivars</topic><topic>Fatty acids</topic><topic>Fatty Acids - metabolism</topic><topic>Gene regulation</topic><topic>Genes, Plant</topic><topic>Genetic Association Studies</topic><topic>Genome-wide association studies</topic><topic>Genome-Wide Association Study</topic><topic>Genomic analysis</topic><topic>Glycine max - genetics</topic><topic>Glycine max - metabolism</topic><topic>Haplotypes</topic><topic>Inbreeding</topic><topic>Life Sciences</topic><topic>Lipids</topic><topic>Marker-assisted selection</topic><topic>Metabolic pathways</topic><topic>Original Article</topic><topic>Phenotype</topic><topic>Plant Biochemistry</topic><topic>Plant Breeding</topic><topic>Plant Breeding/Biotechnology</topic><topic>Plant Genetics and Genomics</topic><topic>Plants</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Population genetics</topic><topic>Population studies</topic><topic>Quantitative Trait Loci</topic><topic>Single-nucleotide polymorphism</topic><topic>Soybeans</topic><topic>Stearic acid</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Fengmin</creatorcontrib><creatorcontrib>Zhao, Tiantian</creatorcontrib><creatorcontrib>Feng, Yan</creatorcontrib><creatorcontrib>Ji, Zengfa</creatorcontrib><creatorcontrib>Zhao, Qingsong</creatorcontrib><creatorcontrib>Meng, Qingmin</creatorcontrib><creatorcontrib>Liu, Bingqiang</creatorcontrib><creatorcontrib>Liu, Luping</creatorcontrib><creatorcontrib>Chen, Qiang</creatorcontrib><creatorcontrib>Qi, Jin</creatorcontrib><creatorcontrib>Zhu, Zhengge</creatorcontrib><creatorcontrib>Yang, Chunyan</creatorcontrib><creatorcontrib>Qin, Jun</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Theoretical and applied genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Fengmin</au><au>Zhao, Tiantian</au><au>Feng, Yan</au><au>Ji, Zengfa</au><au>Zhao, Qingsong</au><au>Meng, Qingmin</au><au>Liu, Bingqiang</au><au>Liu, Luping</au><au>Chen, Qiang</au><au>Qi, Jin</au><au>Zhu, Zhengge</au><au>Yang, Chunyan</au><au>Qin, Jun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of candidate genes and genomic prediction of soybean fatty acid components in two soybean populations</atitle><jtitle>Theoretical and applied genetics</jtitle><stitle>Theor Appl Genet</stitle><addtitle>Theor Appl Genet</addtitle><date>2024-09-01</date><risdate>2024</risdate><volume>137</volume><issue>9</issue><spage>211</spage><pages>211-</pages><artnum>211</artnum><issn>0040-5752</issn><issn>1432-2242</issn><eissn>1432-2242</eissn><abstract>Soybean, a source of plant-derived lipids, contains an array of fatty acids essential for health. A comprehensive understanding of the fatty acid profiles in soybean is crucial for enhancing soybean cultivars and augmenting their qualitative attributes. Here, 180 F
10
generation recombinant inbred lines (RILs), derived from the cross-breeding of the cultivated soybean variety ‘Jidou 12’ and the wild soybean ‘
Y
9,’ were used as primary experimental subjects. Using inclusive composite interval mapping (ICIM), this study undertook a quantitative trait locus (QTL) analysis on five distinct fatty acid components in the RIL population from 2019 to 2021. Concurrently, a genome-wide association study (GWAS) was conducted on 290 samples from a genetically diverse natural population to scrutinize the five fatty acid components during the same timeframe, thereby aiming to identify loci closely associated with fatty acid profiles. In addition, haplotype analysis and the Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed to predict candidate genes. The QTL analysis elucidated 23 stable QTLs intricately associated with the five fatty acid components, exhibiting phenotypic contribution rates ranging from 2.78% to 25.37%. In addition, GWAS of the natural population unveiled 102 significant loci associated with these fatty acid components. The haplotype analysis of the colocalized loci revealed that
Glyma.06G221400
on chromosome 6 exhibited a significant correlation with stearic acid content, with Hap1 showing a markedly elevated stearic acid level compared with Hap2 and Hap3. Similarly,
Glyma.12G075100
on chromosome 12 was significantly associated with the contents of oleic, linoleic, and linolenic acids, suggesting its involvement in fatty acid biosynthesis. In the natural population, candidate genes associated with the contents of palmitic and linolenic acids were predominantly from the fatty acid metabolic pathway, indicating their potential role as pivotal genes in the critical steps of fatty acid metabolism. Furthermore, genomic selection (GS) for fatty acid components was conducted using ridge regression best linear unbiased prediction based on both random single nucleotide polymorphisms (SNPs) and SNPs significantly associated with fatty acid components identified by GWAS. GS accuracy was contingent upon the SNP set used. Notably, GS efficiency was enhanced when using SNPs derived from QTL mapping analysis and GWAS compared with random SNPs, and reached a plateau when the number of SNP markers exceeded 3,000. This study thus indicates that
Glyma.06G221400
and
Glyma.12G075100
are genes integral to the synthesis and regulatory mechanisms of fatty acids. It provides insights into the complex biosynthesis and regulation of fatty acids, with significant implications for the directed improvement of soybean oil quality and the selection of superior soybean varieties. The SNP markers delineated in this study can be instrumental in establishing an efficacious pipeline for marker-assisted selection and GS aimed at improving soybean fatty acid components.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>39210238</pmid><doi>10.1007/s00122-024-04716-8</doi><orcidid>https://orcid.org/0000-0002-8136-0416</orcidid></addata></record> |
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| source | MEDLINE; SpringerNature Journals |
| subjects | Agriculture Biochemistry Biomedical and Life Sciences Biosynthesis Biotechnology Chromosome 12 Chromosome 6 Chromosome Mapping - methods Cross-breeding Cultivars Fatty acids Fatty Acids - metabolism Gene regulation Genes, Plant Genetic Association Studies Genome-wide association studies Genome-Wide Association Study Genomic analysis Glycine max - genetics Glycine max - metabolism Haplotypes Inbreeding Life Sciences Lipids Marker-assisted selection Metabolic pathways Original Article Phenotype Plant Biochemistry Plant Breeding Plant Breeding/Biotechnology Plant Genetics and Genomics Plants Polymorphism, Single Nucleotide Population genetics Population studies Quantitative Trait Loci Single-nucleotide polymorphism Soybeans Stearic acid |
| title | Identification of candidate genes and genomic prediction of soybean fatty acid components in two soybean populations |
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