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Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice
Open accessAbstract
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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Biological insights from 108 schizophrenia-associated genetic loci
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Ridge Regression and Other Kernels for Genomic Selection with R Package rrBLUP
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Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines
Atwell, S., Huang, Y. S., Vilhjálmsson, B. J., Willems, G., Horton, M., Li, Y., Meng, D., Platt, A., Tarone, A. M., Hu, T. T., et al. (2010) · Nature · doi:10.1038/nature08800 · Cited by 1,780
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Cited by
Efficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2
Yoon, S., Nguyen, H. C. T., Yoo, Y. J., Kim, J., Baik, B., Kim, S., Kim, J., Kim, S., & Nam, D. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky175 · Cited by 81
Metadata
- Authors
- Yano, K., Yamamoto, E., Aya, K., Takeuchi, H., Lo, P.-C., Hu, L., Yamasaki, M., Yoshida, S., Kitano, H., Hirano, K., & Matsuoka, M.
- Venue
- Nature Genetics
- Published
- 2016-06-20
- Volume
- 48
- Issue
- 8
- Pages
- 927-934
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- OpenAlex
- W2462342490
- Cited by
- 671
- References
- 8
- FWCI
- 41.10
- Type
- journal article
- Language
- en
- Open access
- green
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- Yano, K., Yamamoto, E., Aya, K., Takeuchi, H., Lo, P.-C., Hu, L., Yamasaki, M., Yoshida, S., Kitano, H., Hirano, K., & Matsuoka, M. (2016). Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nature Genetics. https://doi.org/10.1038/ng.3596
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