Transcriptome-wide identification of RNA-binding protein binding sites using seCLIP-seq

Eric L. Van Nostrand, Steven M. Blue, Gabriel A. Pratt, Gene W. Yeo, Brian A. Yee, Jasmine R. Mueller, Samuel S. Park, Alexander A. Shishkin, Anne C. Starner

Published: 2022-03-22 DOI: 10.1038/s41596-022-00680-z

RNA-binding proteins

bioinformatics pipeline

seCLIP-seq

transcriptome-wide analysis

RBP/RNA complexes

AI 解读

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2.

Reporting Summary

Supplementary Data 1

Source data for Supplementary Fig. 2.

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Gerstberger, S., Hafner, M. & Tuschl, T. A census of human RNA-binding proteins. Nat. Rev. Genet. 15, 829–845 (2014).
Hentze, M. W., Castello, A., Schwarzl, T. & Preiss, T. A brave new world of RNA-binding proteins. Nat. Rev. Mol. Cell Biol. 19, 327–341 (2018).
Lukong, K. E., Chang, K., Khandjian, E. W. & Richard, S. RNA-binding proteins in human genetic disease. Trends Genet. 24, 416–425 (2008).
Nussbacher, J. K., Batra, R., Lagier-Tourenne, C. & Yeo, G. W. RNA-binding proteins in neurodegeneration: Seq and you shall receive. Trends Neurosci. 38, 226–236 (2015).
Brinegar, A. E. & Cooper, T. A. Roles for RNA-binding proteins in development and disease. Brain Res. 1647, 1–8 (2016).
Conlon, E. G. & Manley, J. L. RNA-binding proteins in neurodegeneration: mechanisms in aggregate. Genes Dev. 31, 1509–1528 (2017).
Lee, F. C. Y. & Ule, J. Advances in CLIP technologies for studies of protein–RNA interactions. Mol. Cell 69, 354–369 (2018).
Ule, J. et al. CLIP identifies Nova-regulated RNA networks in the brain. Science 302, 1212–1215 (2003).
Van Nostrand, E. L. et al. Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP). Nat. Methods 13, 508–514 (2016).
Van Nostrand, E. L. et al. Robust, cost-effective profiling of RNA binding protein targets with single-end crosslinking and immunoprecipitation (seCLIP). Methods Mol. Biol. 1648, 177–200 (2017).
Van Nostrand, E. L. et al. Principles of RNA processing from analysis of enhanced CLIP maps for 150 RNA binding proteins. Genome Biol. 21, 90 (2020).
Shah, A., Qian, Y., Weyn-Vanhentenryck, S. M. & Zhang, C. CLIP Tool Kit (CTK): a flexible and robust pipeline to analyze CLIP sequencing data. Bioinformatics 33, 566–567 (2017).
Haberman, N. et al. Insights into the design and interpretation of iCLIP experiments. Genome Biol. 18, 7 (2017).
Wheeler, E. C., Van Nostrand, E. L. & Yeo, G. W. Advances and challenges in the detection of transcriptome-wide protein-RNA interactions. Wiley Interdiscip. Rev. RNA 9, 397–414 (2018).
Zarnegar, B. J. et al. irCLIP platform for efficient characterization of protein–RNA interactions. Nat. Methods 13, 489–492 (2016).
Huppertz, I. et al. iCLIP: protein-RNA interactions at nucleotide resolution. Methods 65, 274–287 (2014).
Buchbender, A. et al. Improved library preparation with the new iCLIP2 protocol. Methods 178, 33–48 (2020).
Kaczynski, T., Hussain, A. & Farkas, M. Quick-irCLIP: interrogating protein-RNA interactions using a rapid and simple cross-linking and immunoprecipitation technique. MethodsX 6, 1292–1304 (2019).
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, e10 (2011).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Smith, T., Heger, A. & Sudbery, I. UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy. Genome Res. 27, 491–499 (2017).
Merkel, D. Docker: lightweight Linux containers for consistent development and deployment. Linux J. 2014, 81–84 (2014).
Kurtzer, G. M., Sochat, V. & Bauer, M. W. Singularity: scientific containers for mobility of compute. PLoS One 12, e0177459 (2017).
Crusoe, M. R. Methods included: standardizing computational reuse and portability with the Common Workflow Language. Preprint at http://doi.org/10.48550/arXiv.2105.07028 (2021).
Köster, J. & Rahmann, S. Snakemake—a scalable bioinformatics workflow engine. Bioinformatics 28, 2520–2522 (2012).
Di Tommaso, P. et al. Nextflow enables reproducible computational workflows. Nat. Biotechnol. 35, 316–319 (2017).
Voss, K., Van der Auwera, G. & Gentry, J. Full-stack Genomics Pipelining with GATK4 + WDL + Cromwell [version 1; not peer reviewed]. F1000Res http://f1000research.com/slides/6-1381 (2017).
Deelman, E. et al. Pegasus, a workflow management system for science automation. Future Gener. Comput. Syst. 46, 17–35 (2015).
Van Nostrand, E. L. et al. A large-scale binding and functional map of human RNA-binding proteins. Nature 583, 711–719 (2020).
Conway, A. E. et al. Enhanced CLIP uncovers IMP protein-RNA targets in human pluripotent stem cells important for cell adhesion and survival. Cell Rep. 15, 666–679 (2016).
Van Nostrand, E. L. et al. CRISPR/Cas9-mediated integration enables TAG-eCLIP of endogenously tagged RNA binding proteins. Methods 118–119, 50–59 (2017).
Krach, F. et al. Transcriptome-pathology correlation identifies interplay between TDP-43 and the expression of its kinase CK1E in sporadic ALS. Acta Neuropathol. 136, 405–423 (2018).
Di Stefano, B. et al. The RNA helicase DDX6 controls cellular plasticity by modulating P-body homeostasis. Cell Stem Cell 25, 622–638.e13 (2019).
Xu, Q. et al. Enhanced crosslinking immunoprecipitation (eCLIP) method for efficient identification of protein-bound RNA in mouse testis. J. Vis. Exp. 2019, e59681 (2019).
Ke, S. et al. A majority of m6A residues are in the last exons, allowing the potential for 3′ UTR regulation. Genes Dev. 29, 2037–2053 (2015).
Linder, B. et al. Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome. Nat. Methods 12, 767–772 (2015).
Patil, D. P., Pickering, B. F. & Jaffrey, S. R. Reading m6A in the transcriptome: m6A-binding proteins. Trends Cell Biol. 28, 113–127 (2018).
Li, X. et al. Base-resolution mapping reveals distinct m1A methylome in nuclear- and mitochondrial-encoded transcripts. Mol. Cell 68, 993–1005.e9 (2017).
Roberts, J. T., Porman, A. M. & Johnson, A. M. Identification of m6A residues at single-nucleotide resolution using eCLIP and an accessible custom analysis pipeline. RNA 27, 527–541 (2021).
Kadumuri, R. V. & Janga, S. C. Epitranscriptomic code and its alterations in human disease. Trends Mol. Med. 24, 886–903 (2018).
Tran, S. S. et al. Widespread RNA editing dysregulation in brains from autistic individuals. Nat. Neurosci. 22, 25–36 (2019).
Landt, S. G. et al. ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res. 22, 1813–1831 (2012).
Li, Q., Brown, J. B., Huang, H. & Bickel, P. J. Measuring reproducibility of high-throughput experiments. Ann. Appl. Stat. 5, 1752–1779 (2011).
Vivian, J. et al. Toil enables reproducible, open source, big biomedical data analyses. Nat. Biotechnol. 35, 314–316 (2017).
Sundararaman, B. et al. Resources for the comprehensive discovery of functional RNA elements. Mol. Cell 61, 903–913 (2016).
Bao, W., Kojima, K. K. & Kohany, O. Repbase Update, a database of repetitive elements in eukaryotic genomes. Mob. DNA 6, 11 (2015).
Smith, T. & Sudbery, I. FAQ. UMI-tools. http://umi-tools.readthedocs.io/en/latest/faq.html (2020).
Wang, Z. F., Whitfield, M. L., Ingledue, T. C., Dominski, Z. & Marzluff, W. F. The protein that binds the 3′ end of histone mRNA: a novel RNA-binding protein required for histone pre-mRNA processing. Genes Dev. 10, 3028–3040 (1996).
Yee, B., Domissy, A. & Crusoe, M. R. YeoLab/eclip. http://github.com/yeolab/eclip (2021).

Transcriptome-wide identification of RNA-binding protein binding sites using seCLIP-seq

Supplementary information

Supplementary Information

Reporting Summary

Supplementary Data 1

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