Genome-wide association study reveals the advantaged genes regulating japonica rice grain shape traits in northern
Hongwei Chen1, Xue Zhang1, Shujun Tian1
1Rice Research Institute of Liaoning Province, Liaoning Academy of Agricultural Sciences, Shenyang, China.
Background:
Rice, a staple food for over half of the global population, exhibits significant diversity in grain shape characteristics, which impact not only appearance and milling quality but also grain weight and yield. Identifying genes and loci underlying these traits is crucial for improving rice breeding programs. Previous studies have identified multiple quantitative trait loci (QTLs) and genes regulating grain length, width, and length-width ratio; however, further investigation is necessary to elucidate their regulatory pathways and their practical application in crop improvement.
Methods:
This study employed a genome-wide association study (GWAS) on 280 japonica rice varieties from northern China to decipher the genetic basis of grain shape traits. Phenotyping included measurements of 11 grain-related traits, such as grain length, width, and area, along with their brown and white rice counterparts. High-density single nucleotide polymorphism (SNP) markers (33,579) were utilized for genotyping, and GWAS was performed using a mixed linear model (MLM) incorporating principal component analysis (PCA) and kinship (K) matrix to account for population structure and relatedness.
Results:
Our analysis detected 15 QTLs associated with the 11 grain shape traits, of which five major QTL clusters emerged as crucial. Candidate genes, including LOC_Os01g50720 (qGL1), OsMKK4 (LOC_Os02g54600, influencing qBA2, qWL2, and qWA2), GW5 (LOC_Os05g09520, controlling qGW5, qBW5, qBR5, qWW5, and qWR5), GW6a (LOC_Os06g44100, associated with qGW6, qBW6, qBR6, qWW6, and qWR6), and FZP (LOC_Os07g47330, linked to qWL7), were identified based on functional annotations and haplotype analysis. These findings offer valuable insights into the genetic mechanisms underlying rice grain shape and suggest promising targets for marker-assisted selection to enhance rice quality and yield.
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