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

TITLE=Multi-model genome-wide association studies for appearance quality in rice

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 14 - 2023

YEAR=2024

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2023.1304388

DOI=10.3389/fpls.2023.1304388

ISSN=1664-462X

ABSTRACT=Improving the appearance quality of rice is critical to meet the market acceptance. Mining putative qualityrelated genes has been geared towards development of effective breeding approaches in rice. In the present investigation, two SL-GWAS (CMLM, MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, FASTmrMLM) genome-wide association studies methods 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 by the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grain with chalkiness (PGC, %). Finally, 39 QTNs were discovered in common using single-and multi-locus GWAS methods. Among these 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 characterized to influence AR, HRR (%), and PGC (%), separately that could possibly be utilized in rice breeding for improving grain quality traits.