Supriya Sachdeva, Rakesh Singh, Avantika Maurya, Vikas Kumar Singh, Uma Maheshwar Singh, Arvind Kumar, Gyanendra Pratap Singh

Front Plant Sci.; 2024 Jan 11: 14:1304388. doi: 10.3389/fpls.2023.1304388. 

Abstract

Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and FASTmrMLM) genome-wide association studies were conducted in a subset of 3K-RGP consisting of 198 rice accessions with 553,831 SNP markers. A total of 594 SNP markers were identified using the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by the ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grains with chalkiness (PGC, %). Finally, 39 QTNs were identified using single- and multi-locus GWAS methods. Among the 39 reliable QTNs, 20 novel QTNs were identified for the above-mentioned three quality-related traits. Based on annotation and previous studies, four functional candidate genes (LOC_Os01g66110, LOC_Os01g66140, LOC_Os07g44910, and LOC_Os02g14120) were found to influence AR, HRR (%), and PGC (%), which could be utilized in rice breeding to improve grain quality traits.

See https://pubmed.ncbi.nlm.nih.gov/38273959/

Figure 4

GWAS for grain quality traits in rice accessions. Manhattan and Quantile-Quantile plots derived through the mrMLM, FASTmrMLM, and FASTmeEMMA methods depicting the distribution of QTNs on 12 rice chromosomes for grain aroma (AR), head rice recovery HRR (%), and percentage with grain chalkiness PGC (%). Pink dots indicate all the QTNs mapped by more than one GWAS method, while all the QTNs identified by a single method are indicated by the light colored dots shown above the gray dotted lines. The known genes around QTNs are marked in red, and putative candidates around the identified QTNs are marked in dark blue.