Structure-guided isoform identification for the human transcriptome
Open accessPublished version of a preprint
Abstract
Recently developed methods to predict three-dimensional protein structure with high accuracy have opened new avenues for genome and proteome research. We explore a new hypothesis in genome annotation, namely whether computationally predicted structures can help to identify which of multiple possible gene isoforms represents a functional protein product. Guided by protein structure predictions, we evaluated over 230,000 isoforms of human protein-coding genes assembled from over 10,000 RNA sequencing experiments across many human tissues. From this set of assembled transcripts, we identified hundreds of isoforms with more confidently predicted structure and potentially superior function in comparison to canonical isoforms in the latest human gene database. We illustrate our new method with examples where structure provides a guide to function in combination with expression and evolutionary evidence. Additionally, we provide the complete set of structures as a resource to better understand the function of human genes and their isoforms. These results demonstrate the promise of protein structure prediction as a genome annotation tool, allowing us to refine even the most highly curated catalog of human proteins. More generally we demonstrate a practical, structure-guided approach that can be used to enhance the annotation of any genome.
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Self-citation
- Authors
- Sommer, M. J., Cha, S., Varabyou, A., Rincon, N., Park, S., Minkin, I., Pertea, M., Steinegger, M., & Salzberg, S. L.
- Affiliations
- Johns Hopkins University (US)
- Seoul National University (KR)
- Corresponding author
- Sommer, Markus J
- Steinegger, Martin
- Salzberg, Steven L
- ORCID
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2022-12-15
- Volume
- 11
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC9812405
- OpenAlex
- W4311579410
- Cited by
- 40
- References
- 13
- Citations by year
- 2026: 7 · 2025: 11 · 2024: 10 · 2023: 9 · 2022: 3
- FWCI
- 2.78
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Seoul National University Open Repository (Seoul National University) (submittedVersion)
- Funders
- National Institutes of Health (R01-HG006677, R35-GM130151)
- National Research Foundation of Korea (2019R1-A6A1-A10073437, 2020M3-A9G7-103933, 2021-R1C1-C102065, 2021-M3A9-I4021220)
- Seoul National University (Creative-Pioneering Researchers Program)
- Topics
- 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
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- protein isoforms, protein structure prediction, human transcriptome, genome annotation, gene function prediction, evolutionary conservation
- MeSH terms
- Humans, Genome, Sequence Analysis, RNA, Protein Isoforms, Molecular Sequence Annotation, Transcriptome
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