Construction of high-density genetic map and QTL mapping of yield-related and two quality traits in soybean RILs population by RAD-sequencing

Abstract

BackgroundOne of the overarching goals of soybean breeding is to develop lines that combine increased yield with improved quality characteristics. High-density-marker QTL mapping can serve as an effective strategy to identify novel genomic information to facilitate crop improvement. In this study, we genotyped a recombinant inbred line (RIL) population (Zhonghuang 24 × Huaxia 3) using a restriction-site associated DNA sequencing (RAD-seq) approach. A high-density soybean genetic map was constructed and used to identify several QTLs that were shown to influence six yield-related and two quality traits.ResultsA total of 47,472 single-nucleotide polymorphisms (SNPs) were detected for the RILs that were integrated into 2639 recombination bin units, with an average distance of 1.00 cM between adjacent markers. Forty seven QTLs for yield-related traits and 13 QTLs for grain quality traits were found to be distributed on 16 chromosomes in the 2 year studies. Among them, 18 QTLs were stable, and were identified in both analyses. Twenty six QTLs were identified for the first time, with a single QTL (qNN19a) in a 56 kb region explaining 32.56% of phenotypic variation, and an additional 10 of these were novel, stable QTLs. Moreover, 8 QTL hotpots on four different chromosomes were identified for the correlated traits.ConclusionsWith RAD-sequencing, some novel QTLs and important QTL clusters for both yield-related and quality traits were identified based on a new, high-density bin linkage map. Three predicted genes were selected as candidates that likely have a direct or indirect influence on both yield and quality in soybean. Our findings will be helpful for understanding common genetic control mechanisms of co-localized traits and to select cultivars for further analysis to predictably modulate soybean yield and quality simultaneously.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3854-8) contains supplementary material, which is available to authorized users.

Identification of major QTLs associated with agronomical traits and candidate gene mining in soybean

“…Among the QTLs related to seed set four per pod, two QTLs were detected, with additive effects of À4.2785 and À4.2216 and relatively large LOD values of 16.8139 and 15.0703, respectively, indicating that a concentrated area of QTLs is associated with seed set four per pod. A number of QTLs associated with pod number at the same position on chromosome Gm11 (satt197-sat_123) were also found to be related to pod numbers in previous studies [40]. The QTLs related to plant height had the highest additive values and LOD values.…”

“…We identified four QTLs related to oil only in the 6013 population, with additive effects of À0.0592, À0.0156, 0.0351 and À0.0648. One of these QTLs (Gm15; 39.16-56.7 cM) associated with the soybean oil index is located in the same segment as a previously identified oil QTL [24,[37][38][39][40], indicating that there is a high probability that this region contains one or several important genes that control oil traits.…”

Exploring the QTL–allele constitution of main stem node number and its differentiation among maturity groups in a Northeast China soybean population

“…After a careful search of SoyBase (http://soybase.org) and journals, altogether 65 MSN QTLs were published in 12 reports, each with 1–14 QTLs, including those identified from biparental populations, such as recombinant inbred line (RIL) populations, and those identified from germplasm populations (Chang et al., 2018; Chen et al., 2007; Fang et al., 2017; Gai, Wang, Wu, & Chen, 2007; Li, Sun, Han, Teng, & Li, 2010; Liu, Li, Fan. et al., 2017; Liu et al., 2011; Liu, Li, Hu, et al., 2017; Moongkanna et al., 2011; Wang et al., 2012; Yao et al., 2015; Zhang et al., 2004). In comparison, 76 QTLs with 183 alleles and three QEI QTLs, with total contribution of 70.09% to PV, were identified from a single germplasm population in our results.…”

“…Soybean [ Glycine max (L.) Merr. ], originated in ancient central China, has been disseminated to all around the world, especially to the Americas where ∼85% of world soybean production is from, due to its high protein and oil contents (Chang, Lee, & Hungria, 2015; Hartman, West, & Herman, 2011; Liu, Wu, et al., 2017; Watanabe, Harada, & Abe, 2012). Northeast China (NEC) is a major soybean production region in China, where the soybean germplasm is a secondary gene pool derived from those in central China (Liu, 2015).…”

High-resolution mapping of a major and consensus quantitative trait locus for oil content to a ~ 0.8-Mb region on chromosome A08 in peanut (Arachis hypogaea L.)

“…This method combines reduced representation libraries with multiplex sequencing strategies, which could overcome the complexity of the genome and reduce the cost of sequencing. Employing this technology has led to the successful development of high-density genetic maps (HDGMs) for conducting highresolution mapping of QTLs in many crops (Chen et al 2017;Chutimanitsakun et al 2011;Liu et al 2017;Pfender et al 2011).…”