Identification of novel soybean oil content-related genes using QTL-based collinearity analysis from the collective soybean genome

Abstract

Soybean is a global principal source of edible plant oil. As more soybean oil-related quantitative trait loci (QTLs) have been located in the collective genome, it is urgent to establish a classification system for these distributed QTLs. A collinear platform may be useful to characterize and identify relationships among QTLs as well as aid in novel gene discovery. In this study, the collinearity MCScanX algorithm and collective soybean genomic information were used to construct collinearity blocks, to which soybean oil-related QTLs were mapped. The results demonstrated that 666 collinearity blocks were detected in the soybean genome across 20 chromosomes, and 521 collinearity relationships existed in 231 of the 242 effective soybean oil-related QTLs. This included 214 inclusion relationships and 307 intersecting relationships. Among them, the collinearity among QTLs that are related to soybean oil content was shown on a maximum of seven chromosomes and minimum of one chromosome, with the majority of QTLs having collinearity on two chromosomes. Using overlapping hotspot regions in the soybean oil QTLs with collinearity, we mined for novel oil content-related genes. Overall, we identified 23 putatively functional genes associated with oil content in soybean and annotated them using a number of annotation databases. Our findings provide a valuable framework for elucidating evolutionary relationships between soybean oil-related QTLs and lay a foundation for functional marker-assisted breeding relating to soybean oil content.

Keywords

• soybean oil QTLs
• collinearity analysis
• candidate genes