Jiajing Wang, Bo Hu, Shanshan Huang, Xiping Hu, Mahfishan Siyal, Chang Yang, Hengxing Zhao, Tao Yang, Haoran Li, Yongqin Hou, Cuiqiao Liu, Xu Sun, Raja Rameez Veesar, Wen-Xia Li, Hailong Ning
Crop and Pasture Science 73 (3), 222-237, (25 January 2022) https://doi.org/10.1071/CP21128
KEYWORDS: genes, GWAS, LINKAGE ANALYSIS, plant height, QTL, QTN, SNP-bin marker, soybean
As the major source of edible protein and oil, the global demand for soybean (Glycine max (L.) Merr.) is increasing. Plant height is closely related to yield; therefore, understanding the genetic basis of plant height will help to improve soybean plant type and increase seed yield. In this study, quantitative trait loci (QTLs) and nucleotides (QTNs) for soybean plant height were detected by linkage analysis and association analysis. A high-density map containing 2225 bin markers was constructed by using 108 342 SNPs of a recombinant inbred line population (named RIL3613) of 120 lines for linkage analysis. In total, 39 QTLs were detected, including 16 QTLs that were repeatedly detected in multiple environments. Association analysis was performed by using 63 306 SNPs from a germplasm population of 455 natural soybean accessions. In total, 62 QTNs were detected, and 26 QTNs were repeatedly detected by multiple methods. Fourteen QTNs were distributed in the intervals of six multiple-environment QTLs by comparing the results of association analysis and linkage analysis. With pathway analysis, six candidate genes were identified as being associated with plant height. These results contribute to analysis of the genetic basis of plant height and will promote marker-assisted selection for breeding ideal plant shape.