Discovering local patterns of co-evolution

Yifat Felder, Tamir Tuller*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Co-evolution is the process in which a set of orthologs exhibits a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn about the functional interdependencies between sets of genes and cellular functions, about their complementary and backup relations, and more generally, for answering fundamental questions about the evolution of biological systems. Orthologs that exhibit strong signal of co-evolution in part of the evolutionary tree may show mild signal of co-evolution in other parts of the tree. The major reasons for this phenomenon are noise in the biological input, genes that gain or lose functions, and the fact that some measures of co-evolution relate to rare events such as positive evolution. Previous works in the field dealt with the problem of finding sets of genes that co-evolved along an entire underlying phylogenetic tree, without considering the fact that often co-evolution is local. In this work, we describe a new set of biological problems that are related to finding patterns of local co-evolution. We discuss their computational complexity and design algorithms for solving them. These algorithms outperform other bi-clustering methods as they are designed specifically for solving the set of problems mentioned above. We use our approach to trace the co-evolution of fungal and Eukaryotic genes at a high resolution across the different parts of the corresponding phylogenetic trees. Our analysis shows that local co-evolution is a wide-scale phenomenon.

Original languageEnglish
Title of host publicationComparative Genomics, International Workshop, RECOMB-CG 2008, Proceedings
Pages55-71
Number of pages17
DOIs
StatePublished - 2008
EventRECOMB Workshop on Comparative Genomics, RECOMB-CG 2008 - Paris, France
Duration: 13 Oct 200815 Oct 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5267 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceRECOMB Workshop on Comparative Genomics, RECOMB-CG 2008
Country/TerritoryFrance
CityParis
Period13/10/0815/10/08

Keywords

  • Bi-clustering
  • Co-evolution
  • Evolution rates
  • Functional ontology
  • Gene copy number
  • Gene deletion and duplication
  • Systems biology

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