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. 2021 Aug 13;16(8):e0255761.
doi: 10.1371/journal.pone.0255761. eCollection 2021.

Genome-wide association study and genomic selection for yield and related traits in soybean

Waltram Ravelombola  1 , Jun Qin  2 , Ainong Shi  1 , Qijian Song  3 , Jin Yuan  2 , Fengmin Wang  2 , Pengyin Chen  4 , Long Yan  2 , Yan Feng  2 , Tiantian Zhao  2 , Yaning Meng  2 , Kexin Guan  2 , Chunyan Yang  2 , Mengchen Zhang  2
Affiliations

Genome-wide association study and genomic selection for yield and related traits in soybean

Waltram Ravelombola et al. PLoS One. .

Abstract

Soybean [Glycine max (L.) Merr.] is a crop of great interest worldwide. Exploring molecular approaches to increase yield genetic gain has been one of the main challenges for soybean breeders and geneticists. Agronomic traits such as maturity, plant height, and seed weight have been found to contribute to yield. In this study, a total of 250 soybean accessions were genotyped with 10,259 high-quality SNPs postulated from genotyping by sequencing (GBS) and evaluated for grain yield, maturity, plant height, and seed weight over three years. A genome-wide association study (GWAS) was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model. Genomic selection (GS) was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that 20, 31, 37, and 23 SNPs were significantly associated with maturity, plant height, seed weight, and yield, respectively; Many SNPs were mapped to previously described maturity and plant height loci (E2, E4, and Dt1) and a new plant height locus was mapped to chromosome 20. Candidate genes were found in the vicinity of the two SNPs with the highest significant levels associated with yield, maturity, plant height, seed weight, respectively. A 11.5-Mb region of chromosome 10 was associated with both yield and seed weight. Overall, the accuracy of GS was dependent on the trait, year, and population structure, and high accuracy indicates that these agronomic traits can be selected in molecular breeding through GS. The SNP markers identified in this study can be used to improve yield and agronomic traits through the marker-assisted selection and GS in breeding programs.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1
Manhattan plots and QQ-plots for maturity in 2008 (A), 2009 (B), 2010 (C), and the average data over 3 years (D).
Fig 2
Fig 2. Genomic selection accuracy for yield, maturity, plant height, and seed weight using training/testing sets from all 250 soybean accessions (all samples), samples derived from Q1, and samples from the Q2 subpopulation.
Cross-validation was conducted using the data from the same year.
Fig 3
Fig 3. Genomic selection accuracy for yield, maturity, plant height, and seed weight using training/testing sets from all 250 soybean accessions (all samples), samples derived from Q1, and samples from the Q2 subpopulation.
Cross-validation was conducted in a way that the data from a year was used to predict that of from the succeeding year(s).
See this image and copyright information in PMC

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Grants and funding

This study was funded by (1) National Natural Science Foundation of China (32072092); (2) S&T Program of Hebei, Soybean modern seed industry science and technology innovation team (21326313D); (3) China Agriculture Research System of MOF and MARA (CARS-04); (4) Hebei Natural Science Foundation (2020301020). There was no additional external funding received for this study.