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Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice

Abstract

A genome-wide association study (GWAS) can be a powerful tool for the identification of genes associated with agronomic traits in crop species, but it is often hindered by population structure and the large extent of linkage disequilibrium. In this study, we identified agronomically important genes in rice using GWAS based on whole-genome sequencing, followed by the screening of candidate genes based on the estimated effect of nucleotide polymorphisms. Using this approach, we identified four new genes associated with agronomic traits. Some genes were undetectable by standard SNP analysis, but we detected them using gene-based association analysis. This study provides fundamental insights relevant to the rapid identification of genes associated with agronomic traits using GWAS and will accelerate future efforts aimed at crop improvement.

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Figure 1: Phenotypic diversity and genetic structure of the Japanese rice varieties.
Figure 2: GWAS for days to heading and identification of the causal gene for the peak on chromosome 1.
Figure 3: GWAS for plant height and panicle length, and identification of the causal gene for the peak on chromosome 11.
Figure 4: GWAS for panicle number per plant, spikelet number per panicle and leaf blade width, and identification of the causal gene for the peak on chromosome 4.
Figure 5: Analyses of the peak for days to heading on chromosome 6.
Figure 6: GWAS for awn length and identification of the causal gene for the peak on chromosome 8.

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Acknowledgements

This work was supported by the Japan Society for the Promotion of Science through a Grant in Aid for Scientific Research (A) (26252001), Council for Science, Technology and Innovation (CSTI), Cross-Ministerial Strategic Innovation Promotion Program (SIP), “Technologies for Creating Next-Generation Agriculture, Forestry and Fisheries” (funding agency: Bio-oriented Technology Research Advancement Institution, NARO), and by Grant in Aid for JSPS Fellows Grant Number 16J08722.

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Authors and Affiliations

Authors

Contributions

K.Y., K.A., H.T., P.-C.L. and L.H. performed the field experiments and analyzed the results. K.Y., K.A. and H.T. performed the genotyping and the genome data analyses. M.Y. and S.Y. prepared the population material. K.Y. produced the constructs and generated and analyzed the transformants. K.Y., E.Y., K.A., H.K., K.H. and M.M. designed the research and wrote the manuscript.

Corresponding authors

Correspondence to Eiji Yamamoto or Makoto Matsuoka.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–21 and Supplementary Tables 1, 3–5, 13 and 14. (PDF 8299 kb)

Supplementary Table 2

Phenotypic data of the seven traits observed in 2013 and 2014. (XLSX 60 kb)

Supplementary Table 6

List of the top 50 P-value-ranked genes in the gene-based association analysis of days to heading. (XLSX 63 kb)

Supplementary Table 7

List of the top 50 P-value-ranked genes in the gene-based association analysis of plant height. (XLSX 99 kb)

Supplementary Table 8

List of the top 50 P-value-ranked genes in the gene-based association analysis of panicle length. (XLSX 57 kb)

Supplementary Table 9

List of the top 50 P-value-ranked genes in the gene-based association analysis of panicle number per plant. (XLSX 61 kb)

Supplementary Table 10

List of the top 50 P-value-ranked genes in the gene-based association analysis of leaf blade width. (XLSX 54 kb)

Supplementary Table 11

List of the top 50 P-value-ranked genes in the gene-based association analysis of spikelet number per panicle. (XLSX 65 kb)

Supplementary Table 12

List of the top 50 P-value-ranked genes in the gene-based association analysis of awn length. (XLSX 99 kb)

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Yano, K., Yamamoto, E., Aya, K. et al. Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nat Genet 48, 927–934 (2016). https://doi.org/10.1038/ng.3596

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