Identification of QTL for branch traits in soybean (Glycine max L.) and its application in genomic selection

Branches are important for soybean yield, and previous studies examining branch traits have primarily focused on branch number (BN), while research assessing branch internode number (BIN), branch length (BL), and branch internode length (BIL) remains insufficient.

A recombinant inbred line (RIL) population consisting of 364 lines was constructed by crossing ZD41 and ZYD02878. Based on the RIL population, we genetically analyzed four branch traits using four different GWAS methods including efficient mixed-model association expedited, restricted two-stage multi-locus genome-wide association analysis, trait analysis by association, evolution and linkage, and three-variance-component multi-locus random-SNP-effect mixed linear model analyses. Additionally, we screened candidate genes for the major QTL and constructed a genomic selection (GS) model to assess the prediction accuracy of the four branch traits.

In this study, four branch traits (BN, BIN, BL, and BIL) were phenotypically analyzed using the F₆-F₉ generations of a RIL population consisting of 364 lines. Among these four traits, BL exhibited the strongest correlation with BIN (0.92), and BIN exhibited the strongest broad-sense heritability (0.89). Furthermore, 99, 43, 50, and 59 QTL were associated with BN, BIN, BL, and BIL, respectively, based on four different methods, and a major QTL region (Chr10:45,050,047..46,781,943) was strongly and simultaneously associated with all four branch traits. For the 207 genes within this region, nine genes were retained as candidates after SNP variation analysis, fixation index (F ), spatial and temporal expression analyses and functionality assessment that involved the regulation of phytohormones, transcription factors, cell wall and cell wall cellulose synthesis. Genomic selection (GS) prediction accuracies for BN, BIN, BL, and BIL in the different environments were 0.59, 0.49, 0.48, and 0.56, respectively, according to GBLUP. This study lays the genetic foundation for BN, BIN, BL, and BIL and provides a reference for functional validation of regulatory genes in the future.