Abstract
Abstract: The objective of this work was to identify and validate single-nucleotide polymorphism (SNP) markers related to grain yield in rice (Oryza sativa) core collection. The genome-wide association studies (GWAS) methodology was applied for genotyping of 541 rice accessions by 167,470 SNPs. The grain yield of these accessions was estimated through the joint analysis of nine field experiments carried out in six Brazilian states. Fifteen SNPs were significantly associated with grain yield, and out of the ten SNPs converted to TaqMan assays, four discriminated the most productive accessions. These markers were used for the screening of rice accessions with favorable alleles. The selected accessions were, then, evaluated in field experiments in target environments, in order to select the most productive ones. This screening reduces the number of accessions evaluated experimentally, making it possible to prioritize those with higher productive potential, which allows of the increase of the number of replicates and, consequently, of the experimental accuracy.
Highlights
There is a consensus on the need to increase food production, to meet the demand of the growing world population
The combination of high-throughput DNA sequencing and phenotyping of rice (Oryza sativa L.) cultivars can identify genes related to quantitative traits, through quantitative trait loci (QTL) analysis and genome-wide association studies (GWAS) (Mochida et al, 2018)
The objective of this work was to identify and validate Single-nucleotide polymorphism (SNP) markers related to grain yield in rice core collection
Summary
There is a consensus on the need to increase food production, to meet the demand of the growing world population. A practical way to achieve this goal is to use molecular markers to increase the efficiency in the development of lines with a higher grain yield (Gupta et al, 2019). SNP markers can be used to genotype rice by medium (6K) or high-density chips (60K) (Tao et al, 2019), sequencing (Elshire et al, 2011), and resequencing (Barabaschi et al, 2016). The combination of high-throughput DNA sequencing and phenotyping of rice (Oryza sativa L.) cultivars can identify genes related to quantitative traits, through quantitative trait loci (QTL) analysis and genome-wide association studies (GWAS) (Mochida et al, 2018). Huang et al (2010) and Lu et al (2015) used the GWAS analysis to identify hundreds of SNP markers related to important agronomic traits in rice. The difficulty is to identify potentially useful molecular markers, and to convert them into a useful and reproducible tool for breeding programs (Platten et al, 2019)
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