The DOI matches its Crossref record; 135 of the 135 references it cites were found in a registry or an index.
A super pan-genomic landscape of rice
Open accessAbstract
Pan-genomes from large natural populations can capture genetic diversity and reveal genomic complexity. Using de novo long-read assembly, we generated a graph-based super pan-genome of rice consisting of a 251-accession panel comprising both cultivated and wild species of Asian and African rice. Our pan-genome reveals extensive structural variations (SVs) and gene presence/absence variations. Additionally, our pan-genome enables the accurate identification of nucleotide-binding leucine-rich repeat genes and characterization of their inter- and intraspecific diversity. Moreover, we uncovered grain weight-associated SVs which specify traits by affecting the expression of their nearby genes. We characterized genetic variants associated with submergence tolerance, seed shattering and plant architecture and found independent selection for a common set of genes that drove adaptation and domestication in Asian and African rice. This super pan-genome facilitates pinpointing of lineage-specific haplotypes for trait-associated genes and provides insights into the evolutionary events that have shaped the genomic architecture of various rice species.
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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
Thompson, J. D., Higgins, D. G., & Gibson, T. J. (1994) · Nucleic Acids Research · doi:10.1093/nar/22.22.4673 · Cited by 64,617
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
MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets
Kumar, S., Stecher, G., & Tamura, K. (2016) · Molecular Biology and Evolution · doi:10.1093/molbev/msw054 · Cited by 44,059
BLAST+: architecture and applications
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-421 · Cited by 22,074
The variant call format and VCFtools
Danecek, P., Auton, A., Abecasis, G., Albers, C. A., Banks, E., DePristo, M. A., Handsaker, R. E., Lunter, G., Marth, G. T., Sherry, S. T., et al. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr330 · Cited by 16,200
Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J., Salzberg, S. L., Wold, B. J., & Pachter, L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1621 · Cited by 15,556
Twelve years of SAMtools and BCFtools
Danecek, P., Bonfield, J. K., Liddle, J., Marshall, J., Ohan, V., Pollard, M. O., Whitwham, A., Keane, T., McCarthy, S. A., Davies, R. M., et al. (2021) · GigaScience · doi:10.1093/gigascience/giab008 · Cited by 15,343
Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype
Kim, D., Paggi, J. M., Park, C., Bennett, C., & Salzberg, S. L. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0201-4 · Cited by 15,022
Minimap2: Pairwise alignment for nucleotide sequences
Li, H. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty191 · Cited by 14,807
Cited by
NextDenovo: an efficient error correction and accurate assembly tool for noisy long reads
Hu, J., Wang, Z., Sun, Z., Hu, B., Ayoola, A. O., Liang, F., Li, J., Sandoval, J. R., Cooper, D. N., Ye, K., et al. (2024) · Genome Biology · doi:10.1186/s13059-024-03252-4 · Cited by 431
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Metadata
- Authors
- Shang, L., Li, X., He, H., Yuan, Q., Song, Y., Wei, Z., Lin, H., Hu, M., Zhao, F., Zhang, C., Li, Y., Gao, H., Wang, T., Liu, X., Zhang, H., Zhang, Y., Cao, S., Yu, X., Zhang, B., Zhang, Y., Tan, Y., Qin, M., Ai, C., Yang, Y., Zhang, B., Hu, Z., Wang, H., Lv, Y., Wang, Y., Ma, J., Wang, Q., Lu, H., Wu, Z., Liu, S., Sun, Z., Zhang, H., Guo, L., Li, Z., Zhou, Y., Li, J., Zhu, Z., Xiong, G., Ruan, J., & Qian, Q.
- Venue
- Cell Research
- Published
- 2022-07-12
- Volume
- 32
- Issue
- 10
- Pages
- 878-896
- ISSN
- 1001-0602 (ISSN-L)
- 1748-7838
- OpenAlex
- W4285093403
- Cited by
- 369
- References
- 135
- FWCI
- 40.93
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Shang, L., Li, X., He, H., Yuan, Q., Song, Y., Wei, Z., Lin, H., Hu, M., Zhao, F., Zhang, C., Li, Y., Gao, H., Wang, T., Liu, X., Zhang, H., Zhang, Y., Cao, S., Yu, X., Zhang, B., . . . Qian, Q. (2022). A super pan-genomic landscape of rice. Cell Research. https://doi.org/10.1038/s41422-022-00685-z
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