Dataset Information

Identification of Loci Governing Agronomic Traits and Mutation Hotspots via a GBS-Based Genome-Wide Association Study in a Soybean Mutant Diversity Pool.

ABSTRACT: In this study, we performed a genotyping-by-sequencing analysis and a genome-wide association study of a soybean mutant diversity pool previously constructed by gamma irradiation. A GWAS was conducted to detect significant associations between 37,249 SNPs, 11 agronomic traits, and 6 phytochemical traits. In the merged data set, 66 SNPs on 13 chromosomes were highly associated (FDR p < 0.05) with the following 4 agronomic traits: days of flowering (33 SNPs), flower color (16 SNPs), node number (6 SNPs), and seed coat color (11 SNPs). These results are consistent with the findings of earlier studies on other genetic features (e.g., natural accessions and recombinant inbred lines). Therefore, our observations suggest that the genomic changes in the mutants generated by gamma irradiation occurred at the same loci as the mutations in the natural soybean population. These findings are indicative of the existence of mutation hotspots, or the acceleration of genome evolution in response to high doses of radiation. Moreover, this study demonstrated that the integration of GBS and GWAS to investigate a mutant population derived from gamma irradiation is suitable for dissecting the molecular basis of complex traits in soybeans.

SUBMITTER: Kim DG

PROVIDER: S-EPMC9499481 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of Loci Governing Agronomic Traits and Mutation Hotspots via a GBS-Based Genome-Wide Association Study in a Soybean Mutant Diversity Pool.

Kim Dong-Gun DG Lyu Jae Il JI Kim Jung Min JM Seo Ji Su JS Choi Hong-Il HI Jo Yeong Deuk YD Kim Sang Hoon SH Eom Seok Hyun SH Ahn Joon-Woo JW Bae Chang-Hyu CH Kwon Soon-Jae SJ

International journal of molecular sciences 20220909 18

In this study, we performed a genotyping-by-sequencing analysis and a genome-wide association study of a soybean mutant diversity pool previously constructed by gamma irradiation. A GWAS was conducted to detect significant associations between 37,249 SNPs, 11 agronomic traits, and 6 phytochemical traits. In the merged data set, 66 SNPs on 13 chromosomes were highly associated (FDR p < 0.05) with the following 4 agronomic traits: days of flowering (33 SNPs), flower color (16 SNPs), node number (6 ...[more]

PMID: 36142354

Similar Datasets

Project description:BackgroundIn recent years soybean is becoming one of the most important oilseed crops in Kazakhstan. Only within the last ten years (2006-2016), the area under soybean is expanded from 45 thousand hectares (ha) in 2006 to 120 thousand ha in 2016. The general trend of soybean expansion is from south-eastern to eastern and northern regions of the country, where average temperatures are lower and growing seasons are shorter. These new soybean growing territories were poorly examined in terms of general effects on productivity level among the diverse sample of soybean accessions. In this study, phenotypic data were collected in three separate regions of Kazakhstan and entire soybean sample was genotyped for identification of marker-trait associations (MTA).ResultsIn this study, the collection of 113 accessions representing five different regions of the World was planted in 2015-2016 in northern, eastern, and south-eastern regions of Kazakhstan. It was observed that North American accessions showed the highest yield in four out of six trials especially in Northern Kazakhstan in both years. The entire sample was genotyped with 6 K SNP Illumina array. 4442 SNPs found to be polymorphic and were used for whole genome genotyping purposes. Obtained SNP markers data and field data were used for GWAS (genome-wide association study). 30 SNPs appear to be very significant in 42 MTAs in six studied environments.ConclusionsThe study confirms the efficiency of GWAS for the identification of molecular markers which tag important agronomic traits. Overall thirty SNP markers associated with time to flowering and maturation, plant height, number of fertile nodes, seeds per plant and yield were identified. Physical locations of 32 identified out of 42 total MTAs coincide well with positions of known analogous QTLs. This result indicates importance of revealed MTAs for soybean growing regions in Kazakhstan. Obtained results would serve as required prerequisite for forming and realization of specific breeding programs towards effective adaptation and increased productivity of soybean in three different regions of Kazakhstan.

Project description:BackgroundLodging, a crucial agronomic trait linked to soybean yield, poses a significant challenge in soybean production. Nevertheless, there has been less research on soybean lodging compared to other important agronomic traits, hindering progress in breeding high-yield soybeans. Our goals were to investigate lodging, pinpoint quantitative trait loci (QTL) linked to lodging, and forecast potential candidate genes linked to this trait. To achieve this, we employed a recombinant inbred line (RIL) population derived from a cross between Guizao 1 and B13 (GB) across various environments.ResultsThe lodging score of the RIL population was found to be significantly positively correlated with flowering time, maturity time, plant height, number of main stem nodes, stem diameter, and internode length, with correlation coefficients ranging from 0.457 to 0.783. A total of 84 QTLs associated with soybean lodging and related traits were identified using the GB population. The contribution of phenotypic variance ranged from 1.26 to 66.87%, with LOD scores ranging from 2.52 to 69.22. Additionally, within these QTLs, a stable major QTL associated with lodging was newly discovered in the GB population. Out of the ten major QTLs associated with other related traits, nine of them were situated within the qLD-4-1 interval of the major lodging score locus, displaying phenotypic variations ranging from 12.10 to 66.87%. Specific alterations in gene expression were revealed through the analysis of resequencing data from the two parental lines, potentially indicating their significant roles in lodging. Subsequently, it was determined through qRT-PCR that four genes are likely to be the major genes controlling soybean lodging.ConclusionsThis study's findings offer valuable insights into the genetic underpinnings of soybean lodging resistance traits. By comprehending the potential genetic factors associated with lodging, this research lays the groundwork for breeding high-yield soybeans with improved lodging resistance.

Dataset Information

Identification of Loci Governing Agronomic Traits and Mutation Hotspots via a GBS-Based Genome-Wide Association Study in a Soybean Mutant Diversity Pool.

Publications

Identification of Loci Governing Agronomic Traits and Mutation Hotspots via a GBS-Based Genome-Wide Association Study in a Soybean Mutant Diversity Pool.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets