Genome-wide association study identifies loci and candidate genes for RVA parameters in wheat (Triticum aestivum L.) - Ullah, Rehmat; Yin, Mingyang; Li, Sen; Israr, Yasir; Wu, Ziyan; Wang, Xueping; Yu, Jiazheng; Li, Baoyun; Ni, Zhongfu; Liang, Rongqi (Frontiers in Plant Science, 2024)
The gelatinization and retrogradation characteristics of wheat starch affect the eating quality of Chinese-style food, and RVA parameters have been widely used as the important indicators to evaluate and improve wheat starch quality. In the present study, a natural population was genotyped by 90 K SNP arrays, while 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 Pasting Temperature (PTT), six parameters followed the normal distribution.Based on the General Linear Model, 969 significant association SNPs were detected by GWAS, and chromosomes 7A and 2B had 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 LD, 33 stable QTL were identified for single parameter in multiple environments, of which 12 were associated with BV, followed by Peak Time (PT) (8) and PTT (7). Meanwhile 67 pleiotropic QTL were identified for multiple parameters. Three candidate genes TasbeIIa, TasbeI and TassIIa were screened out for phenotyping analysis. Grain width and weight of TasbeIIa and Ta SSIIa Knockout (KO) lines were significantly lower than those of TasbeI KO lines and CK. The KO lines had smaller endosperm cells, smaller A-type starch granules and higher amylose content. The TasbeI KO lines showed the normal RVA curves, and the TasbeIIa KO lines showed the flat curves, but the TaSSIIa lines failed to paste under the RVA temperatures. Conclusively, our SNPs/QTLs significantly associated with RVA parameters and genetic resources with novel haplotypes could be used to improve wheat starch quality.