SoySNP618K array: A high-resolution single nucleotide polymorphism platform as a valuable genomic resource for soybean genetics and breeding

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

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.

Flowering time regulator qFT13-3 involved in soybean adaptation to high latitudes

Soybean is a short-day plant that typically flowers earlier when exposed to short-day conditions. However, the identification of genes associated with earlier flowering time but without a yield penalty is rare. In this study, we conducted genome-wide association studies (GWAS) using two re-sequencing datasets that included 113 wild soybeans (G. soja) and 1192 cultivated soybeans (G. max), respectively, and simultaneously identified a candidate flowering gene, qFT13-3, which encodes a protein homologous to the pseudo-response regulator (PRR) transcription factor. We identified four major haplotypes of qFT13-3 in the natural population, with haplotype H4 (qFT13-3H4) being lost during domestication, while qFT13-3H1 underwent natural and artificial selection, increasing in proportion from 4.5% in G. soja to 43.8% in landrace and to 81.9% in improve cultivars. Notably, most cultivars harbouring qFT13-3H1 were located in high-latitude regions. Knockout of qFT13-3 accelerated flowering and maturity time under long-day conditions, indicating that qFT13-3 functions as a flowering inhibitor. Our results also showed that qFT13-3 directly downregulates the expression of GmELF3b-2 which is a component of the circadian clock evening complex. Field trials revealed that the qft13-3 mutants shorten the maturity period by 11 days without a concomitant penalty on yield. Collectively, qFT13-3 can be utilized for the breeding of high-yield cultivars with a short maturity time suitable for high latitudes.

QTL mapping reveals key factors related to the isoflavone contents and agronomic traits of soybean (Glycine max)

BACKGROUND

Soybean is a valuable source of edible protein and oil, as well as secondary metabolites that can be used in food products, cosmetics, and medicines. However, because soybean isoflavone content is a quantitative trait influenced by polygenes and environmental interactions, its genetic basis remains unclear.

RESULTS

This study was conducted to identify causal quantitative trait loci (QTLs) associated with soybean isoflavone contents. A mutant-based F2 population (190 individuals) was created by crossing the Korean cultivar Hwanggeum with low isoflavone contents (1,558 µg g-1) and the soybean mutant DB-088 with high isoflavone contents (6,393 µg g-1). A linkage map (3,049 cM) with an average chromosome length of 152 cM was constructed using the 180K AXIOM® SoyaSNP array. Thirteen QTLs related to agronomic traits were mapped to chromosomes 2, 3, 11, 13, 19, and 20, whereas 29 QTLs associated with isoflavone contents were mapped to chromosomes 1, 3, 8, 11, 14, 15, and 17. Notably, the qMGLI11, qMGNI11, qADZI11, and qTI11, which located Gm11_9877690 to Gm11_9955924 interval on chromosome 11, contributed to the high isoflavone contents and explained 11.9% to 20.1% of the phenotypic variation. This QTL region included four candidate genes, encoding β-glucosidases 13, 14, 17-1, and 17-2. We observed significant differences in the expression levels of these genes at various seed developmental stages. Candidate genes within the causal QTLs were functionally characterized based on enriched GO terms and KEGG pathways, as well as the results of a co-expression network analysis. A correlation analysis indicated that certain agronomic traits (e.g., days to flowering, days to maturity, and plant height) are positively correlated with isoflavone content.

CONCLUSIONS

Herein, we reported that the major QTL associated with isoflavone contents was located in the interval from Gm11_9877690 to Gm11_9955924 (78 kb) on chromosome 11. Four β-glucosidase genes were identified that may be involved in high isoflavone contents of soybean DB-088. Thus, the mutant alleles from soybean DB-088 may be useful for marker-assisted selection in developing soybean lines with high isoflavone contents and superior agronomic traits.

The elite variations in germplasms for soybean breeding

The genetic base of soybean cultivars (Glycine max (L.) Merr.) has been narrowed through selective domestication and specific breeding improvement, similar to other crops. This presents challenges in breeding new cultivars with improved yield and quality, reduced adaptability to climate change, and increased susceptibility to diseases. On the other hand, the vast collection of soybean germplasms offers a potential source of genetic variations to address those challenges, but it has yet to be fully leveraged. In recent decades, rapidly improved high-throughput genotyping technologies have accelerated the harness of elite variations in soybean germplasm and provided the important information for solving the problem of a narrowed genetic base in breeding. In this review, we will overview the situation of maintenance and utilization of soybean germplasms, various solutions provided for different needs in terms of the number of molecular markers, and the omics-based high-throughput strategies that have been used or can be used to identify elite alleles. We will also provide an overall genetic information generated from soybean germplasms in yield, quality traits, and pest resistance for molecular breeding.

Multi-omics assisted breeding for biotic stress resistance in soybean

Biotic stress is a critical factor limiting soybean growth and development. Soybean responses to biotic stresses such as insects, nematodes, fungal, bacterial, and viral pathogens are governed by complex regulatory and defense mechanisms. Next-generation sequencing has availed research techniques and strategies in genomics and post-genomics. This review summarizes the available information on marker resources, quantitative trait loci, and marker-trait associations involved in regulating biotic stress responses in soybean. We discuss the differential expression of related genes and proteins reported in different transcriptomics and proteomics studies and the role of signaling pathways and metabolites reported in metabolomic studies. Recent advances in omics technologies offer opportunities to reshape and improve biotic stress resistance in soybean by altering gene regulation and/or other regulatory networks. We suggest using 'integrated omics' to precisely understand how soybean responds to different biotic stresses. We also discuss the potential challenges of integrating multi-omics for the functional analysis of genes and their regulatory networks and the development of biotic stress-resistant cultivars. This review will help direct soybean breeding programs to develop resistance against different biotic stresses.

Identification of major quantitative trait loci and candidate genes for seed weight in soybean

Four major quantitative trait loci for 100-seed weight were identified in a soybean RIL population under five environments, and the most likely candidate genes underlying these loci were identified. Seed weight is an important target of soybean breeding. However, the genes underlying the major quantitative trait loci (QTL) controlling seed weight remain largely unknown. In this study, a soybean population of 300 recombinant inbred lines (RILs) derived from a cross between PI595843 (PI) and WH was used to map the QTL and identify candidate genes for seed weight. The RIL population was genotyped through whole genome resequencing, and phenotyped for 100-seed weight under five environments. A total of 38 QTL were detected, and four major QTL, each explained at least 10% of the variation in 100-seed weight, were identified. Six candidate genes within these four major QTL regions were identified by analyses of their tissue expression patterns, gene annotations, and differential gene expression levels in soybean seeds during four developmental stages between two parental lines. Further sequence variation analyses revealed a C to T substitution in the first exon of the Glyma.19G143300, resulting in an amino acid change between PI and WH, and thus leading to a different predicted kinase domain, which might affect its protein function. Glyma.19G143300 is highly expressed in soybean seeds and encodes a leucine-rich repeat receptor-like protein kinase (LRR-RLK). Its predicted protein has typical domains of LRR-RLK family, and phylogenetic analyses reveled its similarity with the known LRR-RLK protein XIAO (LOC_Os04g48760), which is involved in controlling seed size. The major QTL and candidate genes identified in this study provide useful information for molecular breeding of new soybean cultivars with desirable seed weight.

Soybean genetic resources contributing to sustainable protein production

KEY MESSAGE

Genetic resources contributes to the sustainable protein production in soybean. Soybean is an important crop for food, oil, and forage and is the main source of edible vegetable oil and vegetable protein. It plays an important role in maintaining balanced dietary nutrients for human health. The soybean protein content is a quantitative trait mainly controlled by gene additive effects and is usually negatively correlated with agronomic traits such as the oil content and yield. The selection of soybean varieties with high protein content and high yield to secure sustainable protein production is one of the difficulties in soybean breeding. The abundant genetic variation of soybean germplasm resources is the basis for overcoming the obstacles in breeding for soybean varieties with high yield and high protein content. Soybean has been cultivated for more than 5000 years and has spread from China to other parts of the world. The rich genetic resources play an important role in promoting the sustainable production of soybean protein worldwide. In this paper, the origin and spread of soybean and the current status of soybean production are reviewed; the genetic characteristics of soybean protein and the distribution of resources are expounded based on phenotypes; the discovery of soybean seed protein-related genes as well as transcriptomic, metabolomic, and proteomic studies in soybean are elaborated; the creation and utilization of high-protein germplasm resources are introduced; and the prospect of high-protein soybean breeding is described.