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

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.

Genome-wide association mapping of quantitative trait loci for chalkiness-related traits in rice (Oryza sativa L.)

“…By combining the information reported at the Gramene ( http://www.gramene.org/markers/ ), BLAST ( http://blast.ncbi.nlm.nih.gov/Blast.cgi ), and China Rice Data Center database ( http://www.ricedata.cn/gene/list/1499.htm ) websites, the QTLs identified in this study were compared with those reported previously for controlling the DEC/PGWC. We compared the results identified in this study with those reported previously by Misra et al (2019 , 2021) and Sachdeva et al (2024) and found that none of the identified loci were common, which could be related to the large differences in the geographical origins and characteristics of the varieties used. The varieties used by Misra et al (2019 , 2021) and Sachdeva et al (2024) included indica, aus, tropical japonica from the IRRI South Asia Regional Center, Varanasi, Uttar Pradesh, India, whereas the materials used in this study included indica mainly from South China, East China, Central China, Vietnam, Philippines, and Indonesia as well as temperate japonica rice from East China, North China, and Northeast China.…”

“…We compared the results identified in this study with those reported previously by Misra et al (2019 , 2021) and Sachdeva et al (2024) and found that none of the identified loci were common, which could be related to the large differences in the geographical origins and characteristics of the varieties used. The varieties used by Misra et al (2019 , 2021) and Sachdeva et al (2024) included indica, aus, tropical japonica from the IRRI South Asia Regional Center, Varanasi, Uttar Pradesh, India, whereas the materials used in this study included indica mainly from South China, East China, Central China, Vietnam, Philippines, and Indonesia as well as temperate japonica rice from East China, North China, and Northeast China. The results obtained in this study were also compared with those reported previously by Xin et al (2022) , and none of the loci identified were common; this may be attributed to the fact that the genetic backgrounds of the materials used were very different.…”