Fine-mapping of QTLs for individual and total isoflavone content in soybean (Glycine max L.) using a high-density genetic map

Abstract

Fifteen stable QTLs were identified using a high-density soybean genetic map across multiple environments. One major QTL, qIF5-1, contributing to total isoflavone content explained phenotypic variance 49.38, 43.27, 46.59, 45.15 and 52.50%, respectively. Soybeans (Glycine max L.) are a major source of dietary isoflavones. To identify novel quantitative trait loci (QTL) underlying isoflavone content, and to improve the accuracy of marker-assisted breeding in soybean, a valuable mapping population comprised of 196 F recombinant inbred lines (RILs, Huachun 2 × Wayao) was utilized to evaluate individual and total isoflavone content in plants grown in four different environments in Guangdong. A high-density genetic linkage map containing 3469 recombination bin markers based on 0.2 × restriction site-associated DNA tag sequencing (RAD-seq) technology was used to finely map QTLs for both individual and total isoflavone contents. Correlation analyses showed that total isoflavone content, and that of five individual isoflavone, was significantly correlated across the four environments. Based on the high-density genetic linkage map, a total of 15 stable quantitative trait loci (QTLs) associated with isoflavone content across multiple environments were mapped onto chromosomes 02, 05, 07, 09, 10, 11, 13, 16, 17, and 19. Further, one of them, qIF5-1, localized to chromosomes 05 (38,434,171-39,045,620 bp) contributed to almost all isoflavone components across all environments, and explained 6.37-59.95% of the phenotypic variance, especially explained 49.38, 43.27, 46.59, 45.15 and 52.50% for total isoflavone. The results obtained in the present study will pave the way for a better understanding of the genetics of isoflavone accumulation and reveals the scope available for improvement of isoflavone content through marker-assisted selection.

Genotype and rhizobium inoculation modulate the assembly of soybean rhizobacterial communities

“…Though specific chemical cues that might be responsible for the observed rhizosphere differences were not identified, we propose that flavones or isoflavones might play important roles, as suggested by Cai et al (2018). Still, the specific chemicals responsible for changing rhizosphere microbial communities need to be identified and studied further.…”

Construction of a High-Density Genetic Map and Mapping of Firmness in Grapes (Vitis vinifera L.) Based on Whole-Genome Resequencing

“…Previous QTL studies of grape traits were mainly based on lower marker numbers (<1000) with relatively high QTL intervals, which affected the accuracy of QTLs and hard-to-locate candidate genes [33,78]. With the rapid development of sequencing technologies and bioinformatics, a large number of polymorphic molecular markers to meet the needs for high-density genetic map construction can be identified, and high-resolution linkage maps have been successfully used for QTL fine mapping in many crops, such as soybean, cotton, pear, and jujube [57][58][59]76]. In a previous grape study, Wang et al constructed the first high-density genetic map spanning a genetic distance of 1917.3 cM and with an average distance of 1.16 cM between markers [31].…”

“…As SNPs are the most abundant heritable variations in genomes and can be detected and genotyped automatically and in a high-throughput manner, they have revolutionized high-quality genetic map construction [55,56]. Next-generation sequencing is a high-throughput, low-cost technology that has been used to identify a large number of SNPs for high-density genetic map construction in various crops, such as soybean [57], cotton [58], and pear [59]. In recent years, several genetic maps for grapevine have been constructed on the basis of high-throughput sequencing technology; these maps have increased marker density and have led to the identification of some new QTLs [10,24,28,33,46].…”

Impacts of genomic research on soybean improvement in East Asia

“…To enhance the isoflavone contents in soybean seeds, a QTL mapping study identified 108 loci in a biparental population (Cai et al 2018c). Fifteen of these QTLs were consistently found in different environmental conditions, with each explaining at least 1.8% of the variations (Cai et al 2018c).…”

“…To enhance the isoflavone contents in soybean seeds, a QTL mapping study identified 108 loci in a biparental population (Cai et al 2018c). Fifteen of these QTLs were consistently found in different environmental conditions, with each explaining at least 1.8% of the variations (Cai et al 2018c). Among them, qIF5-1, spanning a 611-kb region on chromosome 5, could explain 6.37-59.95% of the observed variations in the acetyldaidzin, daidzin, genistin, daidzein, glycitin, malonyldaidzin, malonylglycitin, malonylgenistin, genistein, and total isoflavone contents in the mapping population (Cai et al 2018c).…”