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Genomic variation in 3,010 diverse accessions of Asian cultivated rice
Open accessAbstract
Here we analyse genetic variation, population structure and diversity among 3,010 diverse Asian cultivated rice (Oryza sativa L.) genomes from the 3,000 Rice Genomes Project. Our results are consistent with the five major groups previously recognized, but also suggest several unreported subpopulations that correlate with geographic location. We identified 29 million single nucleotide polymorphisms, 2.4 million small indels and over 90,000 structural variations that contribute to within- and between-population variation. Using pan-genome analyses, we identified more than 10,000 novel full-length protein-coding genes and a high number of presence–absence variations. The complex patterns of introgression observed in domestication genes are consistent with multiple independent rice domestication events. The public availability of data from the 3,000 Rice Genomes Project provides a resource for rice genomics research and breeding. Analyses of genetic variation and population structure based on over 3,000 cultivated rice (Oryza sativa) genomes reveal subpopulations that correlate with geographic location and patterns of introgression consistent with multiple rice domestication events.
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Trimmomatic: a flexible trimmer for Illumina sequence data
Bolger, A. M., Lohse, M., & Usadel, B. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu170 · Cited by 65,548
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs
Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V., & Zdobnov, E. M. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv351 · Cited by 13,344
Second-generation PLINK: rising to the challenge of larger and richer datasets
Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015) · Gigascience · doi:10.1186/s13742-015-0047-8 · Cited by 12,709
Cd-hit: Accelerated for clustering the next-generation sequencing data
Fu, L., Niu, B., Zhu, Z., Wu, S., & Li, W. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts565 · Cited by 11,175
QUAST: quality assessment tool for genome assemblies
Gurevich, A., Saveliev, V., Vyahhi, N., & Tesler, G. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt086 · Cited by 11,172
OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes
Li, L., Stoeckert, C. J., & Roos, D. S. (2003) · Genome Research · doi:10.1101/gr.1224503 · Cited by 5,707
Genetic Structure and Diversity in Oryza sativa L.
Garris, A. J., Tai, T. H., Coburn, J., Kresovich, S., & McCouch, S. (2005) · Genetics · doi:10.1534/genetics.104.035642 · Cited by 1,137
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Liu, Y., Wang, H., Jiang, Z., Wang, W., Xu, R., Wang, Q., Zhang, Z., Li, A., Liang, Y., Ou, S., et al. (2021) · Nature · doi:10.1038/s41586-020-03091-w · Cited by 468
Self-citationXia, E., Tong, W., Hou, Y., An, Y., Chen, L., Wu, Q., Liu, Y., Yu, J., Li, F., Li, R., et al. (2020) · Molecular Plant · doi:10.1016/j.molp.2020.04.010 · Cited by 452
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Metadata
- Authors
- Wang, W., Mauleon, R., Hu, Z., Chebotarov, D., Tai, S., Wu, Z., Li, M., Zheng, T., Fuentes, R. R., Zhang, F., Mansueto, L., Copetti, D., Sanciangco, M., Palis, K. C., Xu, J., Sun, C., Fu, B., Zhang, H., Gao, Y., Zhao, X., Shen, F., Cui, X., Yu, H., Li, Z., Chen, M., Detras, J., Zhou, Y., Zhang, X., Zhao, Y., Kudrna, D., Wang, C., Li, R., Jia, B., Lu, J., He, X., Dong, Z., Xu, J., Li, Y., Wang, M., Shi, J., Li, J., Zhang, D., Lee, S., Hu, W., Poliakov, A., Dubchak, I., Ulat, V. J., Borja, F. N., Mendoza, J. R., Ali, J., Li, J., Gao, Q., Niu, Y., Yue, Z., Naredo, M. E. B., Talag, J., Wang, X., Li, J., Fang, X., Yin, Y., Glaszmann, J.-C., Zhang, J., Li, J., Hamilton, R. S., Wing, R. A., Ruan, J., Zhang, G., Wei, C., Alexandrov, N., McNally, K. L., Li, Z., & Leung, H.
- Venue
- Nature
- Published
- 2018-04-25
- Volume
- 557
- Issue
- 7703
- Pages
- 43-49
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2800434159
- Cited by
- 1,748
- References
- 10
- FWCI
- 95.23
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Wang, W., Mauleon, R., Hu, Z., Chebotarov, D., Tai, S., Wu, Z., Li, M., Zheng, T., Fuentes, R. R., Zhang, F., Mansueto, L., Copetti, D., Sanciangco, M., Palis, K. C., Xu, J., Sun, C., Fu, B., Zhang, H., Gao, Y., . . . Leung, H. (2018). Genomic variation in 3,010 diverse accessions of Asian cultivated rice. Nature. https://doi.org/10.1038/s41586-018-0063-9
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