PROBer Provides a General Toolkit for Analyzing Sequencing-Based Toeprinting Assays
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Abstract
A number of sequencing-based transcriptase drop-off assays have recently been developed to probe post-transcriptional dynamics of RNA-protein interaction, RNA structure, and RNA modification. Although these assays survey a diverse set of epitranscriptomic marks, we use the term toeprinting assays since they share methodological similarities. Their interpretation is predicated on addressing a similar computational challenge: how to learn isoform-specific chemical modification profiles in the face of complex read multi-mapping. We introduce PROBer, a statistical model and associated software, that addresses this challenge for the analysis of toeprinting assays. PROBer takes sequencing data as input and outputs estimated transcript abundances and isoform-specific modification profiles. Results on both simulated and biological data demonstrate that PROBer significantly outperforms individual methods tailored for specific toeprinting assays. Since the space of toeprinting assays is ever expanding and these assays are likely to be performed and analyzed together, we believe PROBer's unified data analysis solution will be valuable to the RNA community.
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Cites
Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566 · cited 2× · see citing works
“…(Roundtree and He, 2016), protein binding and the assembly of higher-order ribonucleoprotein complexes (Glisovic et al., 2008), and the ability of RNA molecules to fold into and switch between intricate 2-and 3-dimensional folds (Mortimer et al., 2014; Schwanhäusser et al., 2011; Wan et al., 2011).”
BackgroundStreaming fragment assignment for real-time analysis of sequencing experiments
Roberts, A., & Pachter, L. (2013) · Nature Methods · doi:10.1038/nmeth.2251 · Cited by 1,063 · see citing works
Self-citationIn vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features
Ding, Y., Tang, Y., Kwok, C. K., Zhang, Y., Bevilacqua, P. C., & Assmann, S. M. (2014) · Nature · doi:10.1038/nature12756 · Cited by 775 · see citing works
Rbfox proteins regulate alternative mRNA splicing through evolutionarily conserved RNA bridges
Lovci, M. T., Ghanem, D., Marr, H., Arnold, J., Gee, S., Parra, M., Liang, T. Y., Stark, T. J., Gehman, L. T., Hoon, S., et al. (2013) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2699 · Cited by 385 · see citing works
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- Authors
- Li, B., Tambe, A., Aviran, S., & Pachter, L.
- Affiliations
- University of California, Berkeley (US)
- University of California, Davis (US)
- California Institute of Technology (US)
- Corresponding author
- Pachter, Lior
- Venue
- Cell Systems
- Publisher
- Elsevier BV
- Published
- 2017-05
- Volume
- 4
- Issue
- 5
- Pages
- 568-574.e7
- ISSN
- 2405-4712 (ISSN-L)
- PMC
- PMC5758053
- OpenAlex
- W2612260255
- Cited by
- 15
- References
- 4
- Citations by year
- 2024: 1 · 2023: 1 · 2021: 1 · 2020: 2 · 2019: 2 · 2018: 6 · 2017: 1 · 2016: 1
- FWCI
- 1.23
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell Systems (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- NIH (R01 HG006129, R00 HG006860, P50GM102706, GM08295)
- Center for RNA Systems Biology
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA modifications and cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- RNA-protein interactions, RNA structure, RNA modification, epitranscriptomics, transcript abundance estimation, statistical models, RNA sequencing data analysis
- MeSH terms
- Algorithms, Animals, Humans, RNA, RNA Processing, Post-Transcriptional, Software, Models, Statistical, Sequence Analysis, RNA, Computational Biology, Protein Isoforms, High-Throughput Nucleotide Sequencing, Transcriptome
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