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A genome-wide association study reveals the genetic architecture of 19 agronomic traits in broomcorn millet (Panicum miliaceum L.)

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Title: A genome-wide association study reveals the genetic architecture of 19 agronomic traits in broomcorn millet (Panicum miliaceum L.)
Authors: Guo, Shuqing1 (AUTHOR), Han, Fei2 (AUTHOR), Liu, Minxuan3 (AUTHOR), Han, Huibing1 (AUTHOR), Dong, Kongjun4 (AUTHOR), Yang, Junxue5 (AUTHOR), Zhang, Liyuan6 (AUTHOR), Gao, Xiaoli1 (AUTHOR), Feng, Baili1 (AUTHOR), Yang, Pu1 (AUTHOR) yangpu5532@hotmail.com
Source: Theoretical & Applied Genetics. Apr2025, Vol. 138 Issue 4, p1-29. 29p.
Abstract: Key message: The genetic architecture of 19 growth and development and yield-related traits was dissected by a GWAS in multi-environment of a diverse population consisting of 301 broomcorn millet accessions. Broomcorn millet (Panicum miliaceum L.) is an ideal replant crop due to its advantages of drought resistance, short growth period, and strong adaptability. Understanding the genetic basis of agronomic traits is crucial for improving the efficiency of molecular breeding in broomcorn millet. In this study, a natural population consisting of 301 worldwide broomcorn millet accessions was genotyped using 208,169 high-quality single-nucleotide polymorphisms (SNPs). Nineteen agronomic traits, including growth period, plant architecture, and yield-related traits, were investigated across ten environments. Based on genomic and phenotypic data, a genome-wide association study (GWAS) was performed to identify significant marker–trait associations (MTAs) affecting these traits. Using the linear mixed model, 662 significant MTAs were identified for 19 traits, with 56 stable MTAs repeatedly identified over two environments. Among these stable SNPs, 40 were located in genomic regions where no relevant loci had been reported previously. Notably, superior alleles of four significant SNPs chr1_2925777, chr7_157147, chr4_3971792, and chr5_2126999 associated with panicle length (PL) and the whole growth period (GP) exhibited significantly higher phenotypic levels. Ultimately, 174 genes within the flanking regions of these four significant SNPs were annotated. Among these, six genes were identified as candidate genes associated with PL and GP. Further haplotype analysis identified seven haplotypes for longmi011379 and longmi011388. Phenotypic assessment of major haplotypes revealed significant differences between Hap1 and Hap2. These results provide a valuable resource for understanding the genetic mechanisms of growth and development and yield-related traits and developing marker-assisted selection breeding in broomcorn millet. [ABSTRACT FROM AUTHOR]
Copyright of Theoretical & Applied Genetics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A genome-wide association study reveals the genetic architecture of 19 agronomic traits in broomcorn millet (Panicum miliaceum L.)
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  Data: <searchLink fieldCode="JN" term="%22Theoretical+%26+Applied+Genetics%22">Theoretical & Applied Genetics</searchLink>. Apr2025, Vol. 138 Issue 4, p1-29. 29p.
– Name: Abstract
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  Data: Key message: The genetic architecture of 19 growth and development and yield-related traits was dissected by a GWAS in multi-environment of a diverse population consisting of 301 broomcorn millet accessions. Broomcorn millet (Panicum miliaceum L.) is an ideal replant crop due to its advantages of drought resistance, short growth period, and strong adaptability. Understanding the genetic basis of agronomic traits is crucial for improving the efficiency of molecular breeding in broomcorn millet. In this study, a natural population consisting of 301 worldwide broomcorn millet accessions was genotyped using 208,169 high-quality single-nucleotide polymorphisms (SNPs). Nineteen agronomic traits, including growth period, plant architecture, and yield-related traits, were investigated across ten environments. Based on genomic and phenotypic data, a genome-wide association study (GWAS) was performed to identify significant marker–trait associations (MTAs) affecting these traits. Using the linear mixed model, 662 significant MTAs were identified for 19 traits, with 56 stable MTAs repeatedly identified over two environments. Among these stable SNPs, 40 were located in genomic regions where no relevant loci had been reported previously. Notably, superior alleles of four significant SNPs chr1_2925777, chr7_157147, chr4_3971792, and chr5_2126999 associated with panicle length (PL) and the whole growth period (GP) exhibited significantly higher phenotypic levels. Ultimately, 174 genes within the flanking regions of these four significant SNPs were annotated. Among these, six genes were identified as candidate genes associated with PL and GP. Further haplotype analysis identified seven haplotypes for longmi011379 and longmi011388. Phenotypic assessment of major haplotypes revealed significant differences between Hap1 and Hap2. These results provide a valuable resource for understanding the genetic mechanisms of growth and development and yield-related traits and developing marker-assisted selection breeding in broomcorn millet. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Theoretical & Applied Genetics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Apr2025
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