Analysis of QTL–allele system conferring drought tolerance at seedling stage in a nested association mapping population of soybean [Glycine max (L.) Merr.] using a novel GWAS procedure

Abstract

RTM-GWAS identified 111 DT QTLs, 262 alleles with high proportion of QEI and genetic variation accounting for 88.55-95.92% PV in NAM, from which QTL-allele matrices were established and candidate genes annotated. Drought tolerance (DT) is one of the major challenges for world soybean production. A nested association mapping (NAM) population with 403 lines comprising two recombinant inbred line (RIL) populations: M8206 × TongShan and ZhengYang × M8206 was tested for DT using polyethylene-glycol (PEG) treatment under spring and summer environments. The population was sequenced using restriction-site-associated DNA sequencing (RAD-seq) filtered with minor allele frequency (MAF) ≥ 0.01, 55,936 single nucleotide polymorphisms (SNPs) were obtained and organized into 6137 SNP linkage disequilibrium blocks (SNPLDBs). The restricted two-stage multi-locus genome-wide association studies (RTM-GWAS) identified 73 and 38 QTLs with 174 and 88 alleles contributed main effect 40.43 and 26.11% to phenotypic variance (PV) and QTL-environment interaction (QEI) effect 24.64 and 10.35% to PV for relative root length (RRL) and relative shoot length (RSL), respectively. The DT traits were characterized with high proportion of QEI variation (37.52-41.65%), plus genetic variation (46.90-58.40%) in a total of 88.55-95.92% PV. The identified QTLs-alleles were organized into main-effect and QEI-effect QTL-allele matrices, showing the genetic and QEI architecture of the three parents/NAM population. From the matrices, the possible best genotype was predicted to have a weighted average value over two indicators (WAV) of 1.873, while the top ten optimal crosses among RILs with 95th percentile WAV 1.098-1.132, transgressive over the parents (0.651-0.773) but much less than 1.873, implying further pyramiding potential. From the matrices, 134 candidate genes were annotated involved in nine biological processes. The present results provide a novel way for molecular breeding in QTL-allele-based genomic selection for optimal cross selection.

Editorial: The Applications of New Multi-Locus GWAS Methodologies in the Genetic Dissection of Complex Traits

“…Theoretically, correction for multiple tests is unnecessary in multi-locus GWAS because all the potential genes or loci for complex traits are fitted to a single linear model and their effects are estimated and tested simultaneously. For example, 0.05 was chosen as the P -value threshold in QTN detection of Khan et al (2018). Although relaxing the stringency of significance level in multi-locus GWAS can identify more hits, confidence in these hits will drop significantly.…”

Genetic dissection of photosynthetic performances in maize under drought-stressed and well-watered environments

“…The significance of total and residual variances of each trait in two F4 populations were estimated by the general linear model for univariate (GLM-Univariate) with one-way analysis of variance (ANOVA), respectively. The broad-sense heritability (ℎ 2 ) and GEI heritability (ℎ 2 ) for combined environments (i.e., WW and DS) were estimated as follows [30]: ℎ 2 = 2 /( 2 + 2 / + 2 /nr) (4) and ℎ 2 = ( 2 / )/( 2 + 2 / + 2 /nr) (5). Here, 2 was genotypic variance, 2 was environmental variance, 2 was error variance, 2 was GEI variance, n (n = 2) was the No.…”

Achievements and prospects of molecular breeding for drought tolerance in soybean [Glycine max (L.) merr.]

“…In this method, tightly linked SNPs are grouped into SNP linkage disequilibrium blocks (SNPLDBs) to generate multiple haplotypes or alleles per block/locus to match the multiple-allele property of the natural population. Quite recently KHAN et al, (2018) used this novel procedure and identified 73 and 38 QTLs with 174 and 88 alleles contributed main effect 40.43 and 26.11% to phenotypic variance (PV) and QTLenvironment interaction (QEI) effect 24.64 and 10.35% to PV for relative root length and relative shoot length that served as drought tolerance indicators, respectively. However the best approach would therefore be to combine the two methods of QTL mapping (traditional linkage mapping and AM) to minimize each other's limitations with maximum accuracy and utilization of resources (MAHUKU et al 2016).…”