Dissecting seed pigmentation-associated genomic loci and genes by employing dual approaches of reference-based and k-mer-based GWAS with 438 Glycine accessions

Abstract

The soybean is agro-economically the most important among all cultivated legume crops, and its seed color is considered one of the most attractive factors in the selection-by-breeders. Thus, genome-wide identification of genes and loci associated with seed colors is critical for the precision breeding of crop soybeans. To dissect seed pigmentation-associated genomic loci and genes, we employed dual approaches by combining reference-based genome-wide association study (rbGWAS) and k-mer-based reference-free GWAS (rfGWAS) with 438 Glycine accessions. The dual analytical strategy allowed us to identify four major genomic loci (designated as SP1-SP4 in this study) associated with the seed colors of soybeans. The k-mer analysis enabled us to find an important recombination event that occurred between subtilisin and I-cluster B in the soybean genome, which could describe a special structural feature of ii allele within the I locus (SP3). Importantly, mapping analyses of both mRNAs and small RNAs allowed us to reveal that the subtilisin-CHS1/CHS3 chimeric transcripts generate and act as an initiator towards ‘mirtron (i.e., intron-harboring miRNA precursor)’-triggered silencing of chalcone synthase (CHS) genes. Consequently, the results led us to propose a working model of ‘mirtron-triggered gene silencing (MTGS)’ to elucidate a long-standing puzzle in the genome-wide CHS gene silencing mechanism. In summary, our study reports four major genomic loci, lists of key genes and genome-wide variations that are associated with seed pigmentation in soybeans. In addition, we propose that the MTGS mechanism plays a crucial role in the genome-wide silencing of CHS genes, thereby suggesting a clue to currently predominant soybean cultivars with the yellow seed coat. Finally, this study will provide a broad insight into the interactions and correlations among seed color-associated genes and loci within the context of anthocyanin biosynthetic pathways.

Genetic Diversity of Soybeans (Glycine max (L.) Merr.) with Black Seed Coats and Green Cotyledons in Korean Germplasm

“…The W1 locus, flavonoid 3 ,5 -hydroxylase (F3 5 H), plays an important role in the accumulation of delphinidin 3-O-glucoside, petunidin 3-O-glucoside, and malvidin 3-O-glucoside under the genetic background of the iiTT genotype [80]. Recently, Kim et al [81] reported that the iiRRTTw1w1 genotype would prohibit the accumulation of delphinidin 3-O-glucoside and petunidin 3-O-glucoside compounds, whereas the T locus, flavonoid 3 -hydroxylase (F3 H), can control the production of cyanidin-derived and delphinidin-derived anthocyanin compounds. The result of this study was that the purple flower (W1W1) produced~5.0 mg/g more total anthocyanin (Figure 6B).…”

SoyPedi: A searchable pedigree‐linked web interface for phenotypic data of soybean cultivars

“…To investigate the correlation between pedigrees and genomic inheritance, a whole genome‐derived phylogenetic tree was constructed using previously resequenced data for soybean cultivars (Kim et al., 2020). This analysis was based on assumption that artificial (but, occurring via natural mechanism in principle) recombination of genomes, like the breeding process, would enforce the inheritance of genetic variations from parental lines chosen for human‐directed crossing of breeding lines.…”

“…In addition to the text type data, phenotype‐related photographs (e.g., flower, pod, and leaf of soybean cultivars) were newly produced using an in‐house‐made portable studio. In addition, whole genome resequencing data for 43 Korean soybean cultivars, which were generated in the previous study (Kim et al., 2020), was used for the phylogenetic analysis.…”

“…More detailed information for quantitative and qualitative phenotypes is provided mainly by the bar charts via retractable windows, which are hidden in the first page. In addition, phenotypic comparison between the chosen cultivar and another is feasible by clicking a cultivar of interest constructed using previously resequenced data for soybean cultivars (Kim et al, 2020). This analysis was based on assumption that artificial (but, occurring via natural mechanism in principle) recombination of genomes, like the breeding process, would enforce the inheritance of genetic variations from parental lines chosen for human-directed crossing of breeding lines.…”

Two decades of association mapping: Insights on disease resistance in major crops

“…In maize k -mers were used in GWAS analysis for cob and kernel color traits and also identify associated k -mers efficiently ( He et al., 2021 ). In another study k -mers based reference free GWAS analysis was conducted in soybean and identified four genomic loci for seed pigmentation ( Kim et al., 2020 ). Collectively, it is suggested that, k -mers based GWAS may be an alternative approach for identifying genomic regions or genes for economically important traits like disease resistant.…”