Genome-wide association study identifies loci and candidate genes for RVA parameters in wheat ( L.).

The gelatinization and retrogradation characteristics of wheat starch affect the eating quality of Chinese-style food. Rapid Visco Analyzer (RVA) parameters have been widely used as important indicators to evaluate and improve the quality of wheat starch. However, the genetic basis of RVA parameters remains to be further explored. In the present study, a natural population was genotyped using 90K single nucleotide polymorphism (SNP) arrays, and the RVA parameters of this population grown in five environments were evaluated. The results showed that 22,068 high-quality SNP markers were identified and distributed unequally on the chromosomes. According to the genetic distance, 214 wheat materials were divided into four groups. Except for the pasting temperature (PTT), six parameters followed a normal distribution. Based on the general linear model, 969 significant association SNPs were detected by genome-wide association studies (GWAS), and chromosomes 7A and 2B had the most associated SNPs. Breakdown viscosity (BV) was associated with the most SNPs ( = 238), followed by PTT ( = 186), peak viscosity (PV; = 156), trough viscosity (TV; = 127), and final viscosity (FV; = 126). According to the average linkage disequilibrium (LD), 33 stable quantitative trait loci (QTLs) were identified for single parameters in multiple environments, of which 12 were associated with BV, followed by peak time (PT; = 8) and PTT ( = 7). On the other hand, 67 pleiotropic QTLs were identified for multiple parameters. Three candidate genes-, and -were screened for phenotyping analysis. The grain width and the weight of the and SS knockout (KO) lines were significantly lower than those of the KO lines and the control (CK). The KO lines had smaller endosperm cells, smaller A-type starch granules, and higher amylose content. The KO lines showed normal RVA curves, while the KO lines showed flat curves. However, the lines failed to paste under the RVA temperatures. Conclusively, the SNPs/QTLs significantly associated with the RVA parameters and genetic resources with novel haplotypes could be used to improve the quality of wheat starch.