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PreprintCited by 0Genomics and Rare DiseasesProtein Structure and DynamicsRNA Research and Splicing

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Decoding Missense Variants by Incorporating Phase Separation via Machine Learning

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Feng, Mofan, Wei, Xiaoxi, Zheng, Xi, Liu, Liangjie, Lin, Lin, Xia, Manying, He, Guang, Shi, Yi, Lu, Qing·2024·bioRxiv (Cold Spring Harbor Laboratory)
DOI 10.1101/2024.04.01.587546

Preprint — published as 10.1038/s41467-024-52580-3 · Paper page

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Abstract

Computational models have made significant progress in predicting the effect of protein variants. However, deciphering numerous variants of unknown significance (VUS) located within intrinsically disordered regions (IDRs) remains challenging. To address this issue, we introduced phase separation (PS), which is tightly linked to IDRs, into the investigation of missense variants. Phase separation is vital for multiple physiological processes. By leveraging missense variants that alter phase separation propensity, we developed a machine learning approach named PSMutPred to predict the impact of missense mutations on phase separation. PSMutPred demonstrated robust performance in predicting missense variants that affect natural phase separation. In vitro experimental findings further underscore its validity. By applying PSMutPred on over 522,000 ClinVar missense variants, it significantly contributes to decoding the pathogenesis of disease variants, especially those in IDRs. Our work provides unique insights into the understanding of a vast number of VUSs in IDRs, thereby expediting clinical interpretation and diagnosis of disease variants.

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Metadata

Authors
Feng, M., Wei, X., Zheng, X., Liu, L., Lin, L., Xia, M., He, G., Shi, Y., & Lu, Q.
Affiliations
Shanghai Jiao Tong University (CN)
ORCID
Venue
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Published
2024-04-01
DOI
10.1101/2024.04.01.587546
OpenAlex
W4393446086
Cited by
0
References
3
Type
posted content
Language
en
Open access
Locations
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • Natural Science Foundation of Shanghai (21ZR1433000, 20511101900, 20ZR1427200, 2017SHZDZX01)
  • National Natural Science Foundation of China (82071262, 19Z103150073, 81671326, 2017SHZDZX01, 32300464)
  • China Postdoctoral Science Foundation (2017SHZDZX01, 2023M732266)
  • Shanghai Municipal Education Commission (2023ZKZD16)
  • Shanghai Jiao Tong University (YG2022QN111, YG2022ZD024, YG2023ZD26)
  • Shanghai Leading Academic Discipline Project
  • National Key Research and Development Program of China (2022YFE0125300, 2017SHZDZX01)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
Keywords
missense mutations, phase separation, intrinsically disordered regions, variants of uncertain significance, ClinVar, pathogenesis

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