Literature DB >> 33928243

CladeOScope: functional interactions through the prism of clade-wise co-evolution.

Tomer Tsaban1, Doron Stupp1, Dana Sherill-Rofe1, Idit Bloch1, Elad Sharon1, Ora Schueler-Furman2, Reuven Wiener3, Yuval Tabach1.   

Abstract

Mapping co-evolved genes via phylogenetic profiling (PP) is a powerful approach to uncover functional interactions between genes and to associate them with pathways. Despite many successful endeavors, the understanding of co-evolutionary signals in eukaryotes remains partial. Our hypothesis is that 'Clades', branches of the tree of life (e.g. primates and mammals), encompass signals that cannot be detected by PP using all eukaryotes. As such, integrating information from different clades should reveal local co-evolution signals and improve function prediction. Accordingly, we analyzed 1028 genomes in 66 clades and demonstrated that the co-evolutionary signal was scattered across clades. We showed that functionally related genes are frequently co-evolved in only parts of the eukaryotic tree and that clades are complementary in detecting functional interactions within pathways. We examined the non-homologous end joining pathway and the UFM1 ubiquitin-like protein pathway and showed that both demonstrated distinguished co-evolution patterns in specific clades. Our research offers a different way to look at co-evolution across eukaryotes and points to the importance of modular co-evolution analysis. We developed the 'CladeOScope' PP method to integrate information from 16 clades across over 1000 eukaryotic genomes and is accessible via an easy to use web server at http://cladeoscope.cs.huji.ac.il.
© The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.

Entities:  

Year:  2021        PMID: 33928243      PMCID: PMC8057497          DOI: 10.1093/nargab/lqab024

Source DB:  PubMed          Journal:  NAR Genom Bioinform        ISSN: 2631-9268


  6 in total

1.  Machine-learning of complex evolutionary signals improves classification of SNVs.

Authors:  Sapir Labes; Doron Stupp; Naama Wagner; Idit Bloch; Michal Lotem; Ephrat L Lahad; Paz Polak; Tal Pupko; Yuval Tabach
Journal:  NAR Genom Bioinform       Date:  2022-04-07

2.  Multi-omics data integration analysis identifies the spliceosome as a key regulator of DNA double-strand break repair.

Authors:  Dana Sherill-Rofe; Oded Raban; Steven Findlay; Dolev Rahat; Irene Unterman; Arash Samiei; Amber Yasmeen; Zafir Kaiser; Hellen Kuasne; Morag Park; William D Foulkes; Idit Bloch; Aviad Zick; Walter H Gotlieb; Yuval Tabach; Alexandre Orthwein
Journal:  NAR Cancer       Date:  2022-04-08

3.  Co-evolution based machine-learning for predicting functional interactions between human genes.

Authors:  Doron Stupp; Elad Sharon; Idit Bloch; Marinka Zitnik; Or Zuk; Yuval Tabach
Journal:  Nat Commun       Date:  2021-11-09       Impact factor: 14.919

4.  DEPCOD: a tool to detect and visualize co-evolution of protein domains.

Authors:  Fei Ji; Gracia Bonilla; Rustem Krykbaev; Gary Ruvkun; Yuval Tabach; Ruslan I Sadreyev
Journal:  Nucleic Acids Res       Date:  2022-05-10       Impact factor: 19.160

5.  Cross-species identification of cancer resistance-associated genes that may mediate human cancer risk.

Authors:  Nishanth Ulhas Nair; Kuoyuan Cheng; Lamis Naddaf; Elad Sharon; Lipika R Pal; Padma S Rajagopal; Irene Unterman; Kenneth Aldape; Sridhar Hannenhalli; Chi-Ping Day; Yuval Tabach; Eytan Ruppin
Journal:  Sci Adv       Date:  2022-08-03       Impact factor: 14.957

6.  Inverse Potts model improves accuracy of phylogenetic profiling.

Authors:  Tsukasa Fukunaga; Wataru Iwasaki
Journal:  Bioinformatics       Date:  2022-01-21       Impact factor: 6.937

  6 in total

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