Developing an SNP dataset for efficiently evaluating soybean germplasm resources using the genome sequencing data of 3,661 soybean accessions

Autor: Yongchao Niu, Wai-Shing Yung, Ching-Ching Sze, Fuk-Ling Wong, Man-Wah Li, Gyuhwa Chung, Hon-Ming Lam
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: BMC Genomics, Vol 25, Iss 1, Pp 1-11 (2024)
Druh dokumentu: article
ISSN: 1471-2164
DOI: 10.1186/s12864-024-10382-3
Popis: Abstract Background Single nucleotide polymorphism (SNP) markers play significant roles in accelerating breeding and basic crop research. Several soybean SNP panels have been developed. However, there is still a lack of SNP panels for differentiating between wild and cultivated populations, as well as for detecting polymorphisms within both wild and cultivated populations. Results This study utilized publicly available resequencing data from over 3,000 soybean accessions to identify differentiating and highly conserved SNP and insertion/deletion (InDel) markers between wild and cultivated soybean populations. Additionally, a naturally occurring mutant gene library was constructed by analyzing large-effect SNPs and InDels in the population. Conclusion The markers obtained in this study are associated with numerous genes governing agronomic traits, thus facilitating the evaluation of soybean germplasms and the efficient differentiation between wild and cultivated soybeans. The natural mutant gene library permits the quick identification of individuals with natural mutations in functional genes, providing convenience for accelerating soybean breeding using reverse genetics.
Databáze: Directory of Open Access Journals
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