Cited by 583RNA Research and SplicingBioinformatics and Genomic NetworksAdvanced Proteomics Techniques and Applications

Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing

Open access
Yang, Xinping, Coulombe-Huntington, Jasmin, Kang, Shuli, Sheynkman, Gloria M., Hao, Tong, Richardson, Aaron, Sun, Song, Yang, Fan +30 more·2016·Cell

Abstract

While alternative splicing is known to diversify the functional characteristics of some genes, the extent to which protein isoforms globally contribute to functional complexity on a proteomic scale remains unknown. To address this systematically, we cloned full-length open reading frames of alternatively spliced transcripts for a large number of human genes and used protein-protein interaction profiling to functionally compare hundreds of protein isoform pairs. The majority of isoform pairs share less than 50% of their interactions. In the global context of interactome network maps, alternative isoforms tend to behave like distinct proteins rather than minor variants of each other. Interaction partners specific to alternative isoforms tend to be expressed in a highly tissue-specific manner and belong to distinct functional modules. Our strategy, applicable to other functional characteristics, reveals a widespread expansion of protein interaction capabilities through alternative splicing and suggests that many alternative "isoforms" are functionally divergent (i.e., "functional alloforms").

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.cell.2016.01.029

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The interacting partners for minor isoforms from a given human gene are as different as those for proteins encoded by entirely different genes.

    “Recently, functional consequences of alternative splicing were explored 12 , showing that the interacting partners for minor isoforms from a given human gene are as different as those for proteins encoded by entirely different genes.”

    From How many human proteoforms are there? (2018) · cites this paper as [12]

    The Results section, “Interactome Network Analysis of Isoform-Specific Interaction Partners” (page unavailable), finds that partners of alternative isoforms are much farther apart in the interaction network than partners of a single protein, and only marginally closer than partners of proteins encoded by separate genes. But that latter difference is statistically significant, and the paper reports a range of differences between isoform pairs. The claim overstates the finding by presenting equal divergence as a general rule for minor isoforms. (LLM, conf=0.87)

    Experimental — accuracy not yet measured
  • Different splice variants can have distinct interaction partners and biological functions.

    “RNA-seq can also distinguish between the expression of different splice variants [46, 47], which can have distinct interaction partners [48] and biological functions [49].”
  • Protein isoforms differ by cell type.

    “Protein isoforms vary by cell type (11, 12).”
  • Splice variants from one gene can yield proteins whose functional differences are as large as those between proteins from completely different genes.

    “Yang et al. (2) recently showed that the functions of proteins produced from splice variants from a given gene—different proteoforms—can be as different as those for proteins encoded by entirely different genes.”

    From Proteoforms as the next proteomics currency (2018) · cites this paper as [2]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

No citation lists for this paper

No citation lists for this paper yet — checked again daily.

References 46 · Cited by 583

Authors
Yang, X., Coulombe-Huntington, J., Kang, S., Sheynkman, G. M., Hao, T., Richardson, A., Sun, S., Yang, F., Shen, Y. A., Murray, R. R., Spirohn, K., Begg, B. E., Duran-Frigola, M., MacWilliams, A., Pevzner, S. J., Zhong, Q., Wanamaker, S. A., Tam, S., Ghamsari, L., Sahni, N., Yi, S., Rodriguez, M. D., Balcha, D., Tan, G., Costanzo, M., Andrews, B., Boone, C., Zhou, X. J., Salehi-Ashtiani, K., Charloteaux, B., Chen, A. A., Calderwood, M. A., Aloy, P., Roth, F. P., Hill, D. E., Iakoucheva, L. M., Xia, Y., & Vidal, M.
Affiliations
  • Harvard University (US)
  • University of California San Diego (US)
  • Uppsala University (SE)
  • Mount Sinai Hospital (CA)
  • Boston University (US)
  • University of Toronto (CA)
  • University of Southern California (US)
  • Institució Catalana de Recerca i Estudis Avançats (ES)
  • Canadian Institute for Advanced Research (CA)
  • Dana-Farber Cancer Institute (US)
Corresponding author
  • Iakoucheva, Lilia M.
  • Xia, Yu
  • Vidal, Marc
Venue
Cell
Publisher
Elsevier BV
Published
2016-02
Volume
164
Issue
4
Pages
805-817
ISSN
0092-8674 (ISSN-L)
OpenAlex
W2258573009
Cited by
583
References
46
Citations by year
2026: 54 · 2025: 41 · 2024: 48 · 2023: 50 · 2022: 53 · 2021: 77 · 2020: 72 · 2019: 64 · 2018: 55 · 2017: 45 · 2016: 23 · 2012: 1
FWCI
32.75
Type
journal article
Language
en
Open access
Locations
  • Cell (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • ORBi (University of Liège) (submittedVersion)
Funders
  • NHGRI CEGS (P50HG004233)
  • NHGRI (U01HG001715)
  • Ellison Foundation
  • NCI (R33CA132073)
  • Krembil Foundation
  • Canada Excellence Research Chair Award
  • Ontario Research Fund-Research Excellence Award
  • E.K. Shriver NICHD (R01HD065288)
  • NIMH (R01MH091350, R01MH105524, R21MH104766)
  • NSF (CCF-1219007)
  • NSERC (RGPIN-2014-03892)
  • Canada Foundation for Innovation (JELF-33732)
  • Canada Research Chairs Program
  • NIH (T32CA009361)
  • NSERC fellowship
  • NIGMS (R01GM105431)
  • Swedish Research Council International Postdoc Grant
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
Keywords
alternative splicing, protein isoforms, protein-protein interaction, protein-protein interaction network, tissue-specific gene expression, human genes
MeSH terms
Animals, Cloning, Molecular, Humans, Models, Molecular, Open Reading Frames, Alternative Splicing, Evolution, Molecular, Protein Isoforms, Proteome, Protein Interaction Domains and Motifs, Protein Interaction Maps

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review