The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
High-throughput annotation of full-length long noncoding RNAs with capture long-read sequencing
Open accessAbstract
RNA Capture Long Seq (CLS) is a new method for transcript annotation that combines targeted RNA capture with long-read sequencing. CLS reannotates GENCODE lncRNAs and increases the number of validated splice junctions and transcript models for targeted loci. Accurate annotation of genes and their transcripts is a foundation of genomics, but currently no annotation technique combines throughput and accuracy. As a result, reference gene collections remain incomplete—many gene models are fragmentary, and thousands more remain uncataloged, particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), which combines targeted RNA capture with third-generation long-read sequencing. Here we present an experimental reannotation of the GENCODE intergenic lncRNA populations in matched human and mouse tissues that resulted in novel transcript models for 3,574 and 561 gene loci, respectively. CLS approximately doubled the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enabled us to definitively characterize the genomic features of lncRNAs, including promoter and gene structure, and protein-coding potential. Thus, CLS removes a long-standing bottleneck in transcriptome annotation and generates manual-quality full-length transcript models at high-throughput scales.
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STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Self-citationAn integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
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
StringTie enables improved reconstruction of a transcriptome from RNA-seq reads
Pertea, M., Pertea, G. M., Antonescu, C. M., Chang, T.-C., Mendell, J. T., & Salzberg, S. L. (2015) · Nature Biotechnology · doi:10.1038/nbt.3122 · Cited by 14,298
Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D. R., Pimentel, H., Salzberg, S. L., Rinn, J. L., & Pachter, L. (2012) · Nature Protocols · doi:10.1038/nprot.2012.016 · Cited by 12,116
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368
Landscape of transcription in human cells
Djebali, S., Davis, C. A., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., Tanzer, A., Lagarde, J., Lin, W., Schlesinger, F., et al. (2012) · Nature · doi:10.1038/nature11233 · Cited by 5,187
Self-citationmiRBase: annotating high confidence microRNAs using deep sequencing data
Kozomara, A., & Griffiths-Jones, S. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1181 · Cited by 5,073
Derrien, T., Johnson, R., Bussotti, G., Tanzer, A., Djebali, S., Tilgner, H., Guernec, G., Martin, D., Merkel, A., Knowles, D. G., et al. (2012) · Genome Research · doi:10.1101/gr.132159.111 · Cited by 5,061
Self-citationGENCODE: The reference human genome annotation for The ENCODE Project
Harrow, J., Frankish, A., Gonzalez, J. M., Tapanari, E., Diekhans, M., Kokocinski, F., Aken, B. L., Barrell, D., Zadissa, A., Searle, S., et al. (2012) · Genome Research · doi:10.1101/gr.135350.111 · Cited by 4,585
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Gene regulation by long non-coding RNAs and its biological functions
Statello, L., Guo, C.-J., Chen, L.-L., & Huarte, M. (2021) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-020-00315-9 · Cited by 4,991
Frankish, A., Diekhans, M., Jungreis, I., Lagarde, J., Loveland, J. E., Mudge, J. M., Sisu, C., Wright, J. C., Armstrong, J., Barnes, I., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1087 · Cited by 1,334
Self-citationThe Third Revolution in Sequencing Technology
van Dijk, E. L., Jaszczyszyn, Y., Naquin, D., & Thermes, C. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.05.008 · Cited by 1,057
Towards a complete map of the human long non-coding RNA transcriptome
Uszczynska-Ratajczak, B., Lagarde, J., Frankish, A., Guigó, R., & Johnson, R. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0017-y · Cited by 616
Self-citationLNCipedia 5: towards a reference set of human long non-coding RNAs
Volders, P.-J., Anckaert, J., Verheggen, K., Nuytens, J., Martens, L., Mestdagh, P., & Vandesompele, J. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1031 · Cited by 547
Metadata
- Authors
- Lagarde, J., Uszczynska-Ratajczak, B., Carbonell, S., Pérez-Lluch, S., Abad, A., Davis, C., Gingeras, T. R., Frankish, A., Harrow, J., Guigo, R., & Johnson, R.
- Venue
- Nature Genetics
- Published
- 2017-11-06
- Volume
- 49
- Issue
- 12
- Pages
- 1731-1740
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- OpenAlex
- W2951972570
- Cited by
- 267
- References
- 57
- FWCI
- 10.48
- Type
- journal article
- Language
- en
- Open access
- hybrid
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