{'fraction_non_alphanumeric': 0.028871391076115485, 'fraction_numerical': 0.020341207349081365, 'mean_word_length': 5.434599156118144, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Genome-wide Association Study-based Identification Genes Influencing Agronomic Traits in Rice (Oryza Sativa L.)


 BackgroundRice (Oryza sativa L.) is one of the most important cereal crops, providing the daily dietary intake for approximately 50% of the global human population. To needs of the rapidly increasing human population worldwide, cultivation of rice varieties with high yield and quality, more genes or QTLs association with yield traits are required.ResultsCurrently, correlations among different traits and gene interactions both affect the rice breeding. Here, we re-sequenced 259 rice accessions, generating 1, 371.65 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 GWAS. The result showed that 816 SNP signals were significantly associated (−log10P≥5) with the 13 agronomic traits. 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 though haplotype block construction. ConclusionsThis study provides an important genomic resource and valuable new information for breeding high yielding breeding rice cultivars through genomic selection.