Expanding Omics Resources for Improvement of Soybean Seed Composition Traits

Abstract

Food resources of the modern world are strained due to the increasing population. There is an urgent need for innovative methods and approaches to augment food production. Legume seeds are major resources of human food and animal feed with their unique nutrient compositions including oil, protein, carbohydrates, and other beneficial nutrients. Recent advances in next-generation sequencing (NGS) together with "omics" technologies have considerably strengthened soybean research. The availability of well annotated soybean genome sequence along with hundreds of identified quantitative trait loci (QTL) associated with different seed traits can be used for gene discovery and molecular marker development for breeding applications. Despite the remarkable progress in these technologies, the analysis and mining of existing seed genomics data are still challenging due to the complexity of genetic inheritance, metabolic partitioning, and developmental regulations. Integration of "omics tools" is an effective strategy to discover key regulators of various seed traits. In this review, recent advances in "omics" approaches and their use in soybean seed trait investigations are presented along with the available databases and technological platforms and their applicability in the improvement of soybean. This article also highlights the use of modern breeding approaches, such as genome-wide association studies (GWAS), genomic selection (GS), and marker-assisted recurrent selection (MARS) for developing superior cultivars. A catalog of available important resources for major seed composition traits, such as seed oil, protein, carbohydrates, and yield traits are provided to improve the knowledge base and future utilization of this information in the soybean crop improvement programs.

Keywords: genome-wide association study (GWAS); genomics; legumes; next-generation sequencing (NGS); omics; quantitative trait loci (QTL); seed traits; soybean.

Figure 1

Different omics approaches and their integrated tools being used for soybean breeding.

Figure 2

Chromosomal locations of genomic hot-spots, promising genes, QTL, GWAS, and linked markers for soybean seed composition from several studies. Protein, Oil, Cysteine, Lysine, Methionine, Threonine, Sucrose, Stachyose (Vaughn et al., 2014); Protein and oil (Hwang et al., 2014); Protein, Oil (Sonah et al., 2015); Glucose, Sucrose, Fructose, Stachyose (Wang et al., 2014b); Protein, Oil (Pathan et al., 2013), Protein, Methionine (Warrington et al., 2015).