EvoProDom: evolutionary modeling of protein families by assessing translocations of protein domains

  • Gon Carmi
  • , Alessandro Gorohovski
  • , Milana Frenkel-Morgenstern

Research output: Contribution to journalArticlepeer-review

Abstract

Here, we introduce a novel ‘evolution of protein domains’ (EvoProDom) model for describing the evolution of proteins based on the ‘mix and merge’ of protein domains. We assembled and integrated genomic and proteomic data comprising protein domain content and orthologous proteins from 109 organisms. In EvoProDom, we characterized evolutionary events, particularly, translocations, as reciprocal exchanges of protein domains between orthologous proteins in different organisms. We showed that protein domains that translocate with highly frequency are generated by transcripts enriched in trans-splicing events, that is, the generation of novel transcripts from the fusion of two distinct genes. In EvoProDom, we describe a general method to collate orthologous protein annotation from KEGG, and protein domain content from protein sequences using tools such as KoFamKOAL and Pfam. To summarize, EvoProDom presents a novel model for protein evolution based on the ‘mix and merge’ of protein domains rather than DNA-based evolution models. This confers the advantage of considering chromosomal alterations as drivers of protein evolutionary events.

Original languageEnglish
Pages (from-to)2507-2524
Number of pages18
JournalFEBS Open Bio
Volume11
Issue number9
DOIs
StatePublished - Sep 2021

Bibliographical note

Publisher Copyright:
© 2021 The Authors. FEBS Open Bio published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies

Funding

We thank Dr. Eivatar Nevo for his expertise and helpful comments on the manuscript. This work was supported by a Grant for Biomarkers for treatment of Arthritis patients (Israel Innovation Authority, 66824, 1.7.2019‐30.6.2020) and The Roland and Dawn Arnall Foundation (Research Grant, 205227 1.9.2018‐31.8.2019). M.F.M. is a member of the Dangoor Center for Personalized Medicine, and the Data Science Institute (DSI), Bar‐Ilan University, Israel. We thank Dr. Eivatar Nevo for his expertise and helpful comments on the manuscript. This work was supported by a Grant for Biomarkers for treatment of Arthritis patients (Israel Innovation Authority, 66824, 1.7.2019-30.6.2020) and The Roland and Dawn Arnall Foundation (Research Grant, 205227 1.9.2018-31.8.2019). M.F.M. is a member of the Dangoor Center for Personalized Medicine, and the Data Science Institute (DSI), Bar-Ilan University, Israel.

FundersFunder number
Arthritis patients
Bar-Ilan University, Israel
Data Science Institute
Israel Innovation Authority1.7.2019‐30.6.2020, 66824
Roland and Dawn Arnall Foundation205227 1.9.2018‐31.8.2019

    Keywords

    • protein domains
    • protein evolution
    • translocations

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