Abstract
BackgroundImproving the overall production of rice with high quality is a major target of breeders. Mining potential yield-related loci have been geared towards developing efficient rice breeding strategies. In this study, one single-locus genome-wide association studies (SL-GWAS) method (MLM) in conjunction with five multi-locus genome-wide association studies (ML-GWAS) approaches (mrMLM, FASTmrMLM, pLARmEB, pKWmEB, and ISIS EM-BLASSO) were conducted in a panel consisting of 529 rice core varieties with 607,201 SNPs.ResultsA total of 152, 106, 12, 111, and 64 SNPs were detected by the MLM model associated with the five yield-related traits, namely grain length (GL), grain width (GW), grain thickness (GT), thousand-grain weight (TGW), and yield per plant (YPP), respectively. Furthermore, 74 significant quantitative trait nucleotides (QTNs) were presented across at least two ML-GWAS methods to be associated with the above five traits successively. Finally, 20 common QTNs were simultaneously discovered by both SL-GWAS and ML-GWAS methods. Based on genome annotation, gene expression analysis, and previous studies, two candidate key genes (LOC_Os09g02830 and LOC_Os07g31450) were characterized to affect GW and TGW, separately.ConclusionsThese outcomes will provide an indication for breeding high-yielding rice varieties in the immediate future.
Highlights
Improving the overall production of rice with high quality is a major target of breeders
We aim to investigate common Quantitative trait nucleotide (QTN) via multiple methodologies and deduce potential candidate genes to accelerate molecular marker-assisted breeding and boost rice production
Phenotypic variation Five yield-related traits were selected to examine whether significant phenotypic variances exist in the yield among the 529 rice varieties
Summary
Improving the overall production of rice with high quality is a major target of breeders. Mining potential yield-related loci have been geared towards developing efficient rice breeding strategies. In 2018, the total rice output accounted for 32.24% of the total grain production in China followed by maize (http://www.stats.gov.cn/). The average production of rice from 1994 to 2019 is 654.78 million tonnes per year, accounting for 27.28% of total cereals output (http://www.fao.org/faostat/en/#data/QC/ visualize). The growing global population and the deteriorating environment issue new challenges to the breeding of high-yielding crops [2]. Rice yield is a complex quantitative agronomic trait multiplicatively governed by three. The overexpression of WTG1 showed narrow, thin, and long rice grains as a result of slim cells. The OsSPL13 is a SQUAMOSA promoter-binding-like protein [9, 10], which was reported controlling rice grain length, grain number, grain size, and yield
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