Association mapping reveals novel genes and genomic regions controlling grain size architecture in mini core accessions of Indian National Genebank wheat germplasm collection

Wheat ( Triticum aestivum L .) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associat...

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Vydáno v:	Frontiers in plant science Ročník 14; s. 1148658
Hlavní autoři:	Kumari, Jyoti, Lakhwani, Deepika, Jakhar, Preeti, Sharma, Shivani, Tiwari, Shailesh, Mittal, Shikha, Avashthi, Himanshu, Shekhawat, Neelam, Singh, Kartar, Mishra, Kaushlesh Kumar, Singh, Rakesh, Yadav, Mahesh C., Singh, Gyanendra Pratap, Singh, Amit Kumar
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland Frontiers Media SA 28.06.2023 Frontiers Media S.A
Témata:	ABC transporter Agricultural production Gene mapping Genes Genetic testing genome wide association studies Genomes Genomics Genotype & phenotype Germplasm Grain size Human populations mrMLM Nucleotides Particle size Plant breeding Plant Science Population Principal components analysis QTN Quantitative trait loci Seeds Single-nucleotide polymorphism Software Thioredoxin thousand grain weight Wheat QTN wheat thousand grain weight genome wide association studies mrMLM
ISSN:	1664-462X, 1664-462X
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Abstract	Wheat ( Triticum aestivum L .) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E 1 , E 2 , E 3 , E 4 , E 5 , E 5 , E 6 , and E 7 ). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties.
AbstractList	Wheat ( Triticum aestivum L .) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E1, E2, E3, E4, E5, E5, E6, and E7). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties. Wheat ( .) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E , E , E , E , E , E , E , and E ). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties. Wheat ( Triticum aestivum L .) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E 1 , E 2 , E 3 , E 4 , E 5 , E 5 , E 6 , and E 7 ). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties. Wheat (Triticum aestivum L.) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E1, E2, E3, E4, E5, E5, E6, and E7). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties.Wheat (Triticum aestivum L.) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E1, E2, E3, E4, E5, E5, E6, and E7). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties.
Author	Lakhwani, Deepika Mittal, Shikha Singh, Gyanendra Pratap Shekhawat, Neelam Tiwari, Shailesh Singh, Rakesh Yadav, Mahesh C. Singh, Kartar Avashthi, Himanshu Singh, Amit Kumar Mishra, Kaushlesh Kumar Kumari, Jyoti Sharma, Shivani Jakhar, Preeti
AuthorAffiliation	2 Jaypee University of Information Technology , Solan , India 4 Zonal Agricultural Research Station , Powarkheda , India 1 ICAR-National Bureau of Plant Genetic Resources , New Delhi , India 3 ICAR-National Bureau of Plant Genetic Resources, Regional Station , Jodhpur, Jodhpur , India
AuthorAffiliation_xml	– name: 4 Zonal Agricultural Research Station , Powarkheda , India – name: 2 Jaypee University of Information Technology , Solan , India – name: 1 ICAR-National Bureau of Plant Genetic Resources , New Delhi , India – name: 3 ICAR-National Bureau of Plant Genetic Resources, Regional Station , Jodhpur, Jodhpur , India
Author_xml	– sequence: 1 givenname: Jyoti surname: Kumari fullname: Kumari, Jyoti – sequence: 2 givenname: Deepika surname: Lakhwani fullname: Lakhwani, Deepika – sequence: 3 givenname: Preeti surname: Jakhar fullname: Jakhar, Preeti – sequence: 4 givenname: Shivani surname: Sharma fullname: Sharma, Shivani – sequence: 5 givenname: Shailesh surname: Tiwari fullname: Tiwari, Shailesh – sequence: 6 givenname: Shikha surname: Mittal fullname: Mittal, Shikha – sequence: 7 givenname: Himanshu surname: Avashthi fullname: Avashthi, Himanshu – sequence: 8 givenname: Neelam surname: Shekhawat fullname: Shekhawat, Neelam – sequence: 9 givenname: Kartar surname: Singh fullname: Singh, Kartar – sequence: 10 givenname: Kaushlesh Kumar surname: Mishra fullname: Mishra, Kaushlesh Kumar – sequence: 11 givenname: Rakesh surname: Singh fullname: Singh, Rakesh – sequence: 12 givenname: Mahesh C. surname: Yadav fullname: Yadav, Mahesh C. – sequence: 13 givenname: Gyanendra Pratap surname: Singh fullname: Singh, Gyanendra Pratap – sequence: 14 givenname: Amit Kumar surname: Singh fullname: Singh, Amit Kumar
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Copyright	Copyright © 2023 Kumari, Lakhwani, Jakhar, Sharma, Tiwari, Mittal, Avashthi, Shekhawat, Singh, Mishra, Singh, Yadav, Singh and Singh. 2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Copyright © 2023 Kumari, Lakhwani, Jakhar, Sharma, Tiwari, Mittal, Avashthi, Shekhawat, Singh, Mishra, Singh, Yadav, Singh and Singh 2023 Kumari, Lakhwani, Jakhar, Sharma, Tiwari, Mittal, Avashthi, Shekhawat, Singh, Mishra, Singh, Yadav, Singh and Singh
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Keywords	QTN wheat thousand grain weight genome wide association studies mrMLM
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Edited by: Shouvik Das, Regional Centre for Biotechnology (RCB), India These authors have contributed equally to this work Reviewed by: Revathi Ponnuswamy, Indian Institute of Rice Research (ICAR), India; Kumar Paritosh, University of Delhi, India
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Snippet	Wheat ( Triticum aestivum L .) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield... Wheat ( .) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this... Wheat ( Triticum aestivum L .) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield... Wheat (Triticum aestivum L.) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield...
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SubjectTerms	ABC transporter Agricultural production Gene mapping Genes Genetic testing genome wide association studies Genomes Genomics Genotype & phenotype Germplasm Grain size Human populations mrMLM Nucleotides Particle size Plant breeding Plant Science Population Principal components analysis QTN Quantitative trait loci Seeds Single-nucleotide polymorphism Software Thioredoxin thousand grain weight Wheat
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Title	Association mapping reveals novel genes and genomic regions controlling grain size architecture in mini core accessions of Indian National Genebank wheat germplasm collection
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