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Identifying Mutations by High Resolution Melting in a TILLING Population of Rice
Published on: September 2, 2019
Genetic basis underlying tiller angle in rice (Oryza sativa L.) by genome-wide association study
Shaoxing Bai1, Jun Hong1, Su Su1
1Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
Key Message:
Novel alleles of two reported tiller angle genes and eleven candidate genes for rice tiller angle were identified by combining GWAS with transcriptomic, qRT-PCR and haplotype analysis. Rice tiller angle is a key agronomic trait determining rice grain yield. Several quantitative trait loci (QTLs) affecting rice tiller angle have been mapped in the past decades. Little is known about the genetic base of tiller angle in rice, because rice tiller angle is a complex polygenic trait. In this study, we performed genome-wide association study (GWAS) on tiller angle in rice using a population of 164 japonica varieties derived from the 3 K Rice Genomes Project (3 K RGP). We detected a total of 18 QTLs using 1135519 single-nucleotide polymorphisms (SNP) based on three GWAS models (GLM, FastLMM and FarmCPU). Among them, two identified QTLs, qTA8.3 and qTA8.4, overlapped with PAY1 and TIG1, respectively, and additional 16 QTLs were identified for the first time. Combined with haplotype and expression analyses, we further revealed that PAY1 harbors one non-synonymous variation at its coding region, likely leading to variable tiller angle in the population, and that nature variations in the promoter of TIG1 significantly affect its expression, closely correlating with tiller angle phenotypes observed. Similarly, using qRT-PCR and haplotype analysis, we identified 1 and 7 candidate genes in qTA6.1 and qTA8.1 that were commonly detected by two GWAS models, respectively. In addition, we identified 3 more candidate genes in the remaining 14 novel QTLs after filtering by transcriptome analysis and qRT-PCR. In summary, this study provides new insights into the genetic architecture of rice tiller angle and candidate genes for rice breeding.
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