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Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
Published on: May 21, 2020
Genome-wide association study-based identification genes influencing agronomic traits in rice (Oryza sativa L.)
Aijun Wang1, Yuqi Jiang1, Xinyue Shu1
1College of Agronomy, Sichuan Agricultural University, Chengdu, China; State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, China; Rice Research Institute of Sichuan Agricultural University, Chengdu, China.
Abstract:
Rice is one of the most important cereal crops, providing the daily dietary intake for approximately 50% of the global human population. Here, we re-sequenced 259 rice accessions, generating 1371.65 Gb of raw data. Furthermore, we performed genome-wide association studies (GWAS) on 13 agronomic traits using 2.8 million single nucleotide polymorphisms (SNPs) characterized in 259 rice accessions. Phenotypic data and best linear unbiased prediction (BLUP) values of each of the 13 traits over two years of each trait were used for the GWAS. The results showed that 816 SNP signals were significantly associated with the 13 agronomic traits. Then we detected candidate genes related to target traits within 200 kb upstream and downstream of the associated SNP loci, based on linkage disequilibrium (LD) blocks in the whole rice genome. These candidate genes were further identified through haplotype block constructions. This comprehensive study provides a timely and important genomic resource for breeding high yielding rice cultivars.
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