A major source of plant oil and protein for humans is the soybean (Glycine max (L.) Merr.), a crop cultivated all over the globe. The main objective for geneticists and breeders is to increase soybean production and quality.
The development of genomics has made it easier to study and breed crops and soybean. These days, data is growing quickly in both dimension and quantity, which makes it difficult for academics to handle the big omics data.
In a study published in Molecular Plant, researchers led by Zhixi Tian from the Chinese Academy of Sciences' Institute of Genetics and Developmental Biology (IGDB), Zhang Zhang and Shuhui Song from the Beijing Institute of Genomics/China National Center for Bioinformation, CAS, contributed to the development of an innovative framework for soybean multi-omics data and the database SoyOmics.
The researchers gathered 3,00 soybean germplasm samples and 38 million SNPs and INDELs from them, 29 de novo assembled genomes of various soybean accessions, 550 thousand large-scale structural variations (SVs), graph pan-genome, six genomes of species of subgenus Glycine, 28 or 9 tissue-stages gene expression data of ZH13/WM82 or pan-genome accessions, and 27,000 records of 115 soybean phenotypes from different years and planting regions.
The understanding of functional genes, genome-wide association studies (GWAS), and quantitative trait locus (QTL) was also present. The six fundamental components of the multi-omics data are the genome, variantome, transcriptome, phenome, homology, and synteny.
Based on these, researchers created analysis tools for BLAST search (BLAST), GWAS (easyGWAS), gene expression pattern (ExpPattern), haplotype (HapSnap), genome position transform (VersionMap), and Soybean array (SoyArray).
The search requirements for genomic areas, genes, variants, germplasms, traits, and/or any biological information linked to soybean can be met by soyomics. Each search results have a good crossover with other related entities in the database. The application toolkits provide several one-stop solutions for genomics, bioinformatics, and/or genetic research.
To maintain its status as a dynamic and up-to-date library, SoyOmics will be constantly updated. It values worldwide collaborations to establish itself as a beneficial resource for the entire global research community.
Liu, Y., et al. (2023). SoyOmics: A deeply integrated database on soybean multi-omics. Molecular Plant. doi.org/10.1016/j.molp.2023.03.011