Co-evolutionary models for reconstructing ancestral genomic sequences: Computational issues and biological examples

Tamir Tuller*, Hadas Birin, Martin Kupiec, Eytan Ruppin

*Corresponding author for this work

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


The inference of ancestral genomes is a fundamental problem in molecular evolution. Due to the statistical nature of this problem, the most likely or the most parsimonious ancestral genomes usually include considerable error rates. In general, these errors cannot be abolished by utilizing more exhaustive computational approaches, by using longer genomic sequences, or by analyzing more taxa. In recent studies we showed that co-evolution is an important force that can be used for significantly improving the inference of ancestral genome content. In this work we formally define a computational problem for the inference of ancestral genome content by co-evolution. We show that this problem is NP-hard and present both a Fixed Parameter Tractable (FPT) algorithm, and heuristic approximation algorithms for solving it. The running time of these algorithms on simulated inputs with hundreds of protein families and hundreds of co-evolutionary relations was fast (up to four minutes) and it achieved an approximation ratio < 1.3. We use our approach to study the ancestral genome content of the Fungi. To this end, we implement our approach on a dataset of 33, 931 protein families and 20, 317 co-evolutionary relations. Our algorithm added and removed hundreds of proteins from the ancestral genomes inferred by maximum likelihood (ML) or maximum parsimony (MP) while slightly affecting the likelihood/parsimony score of the results. A biological analysis revealed various pieces of evidence that support the biological plausibility of the new solutions.

Original languageEnglish
Title of host publicationComparative Genomics - International Workshop, RECOMB-CG 2009, Proceedings
Number of pages17
StatePublished - 2009
Event7th International Workshop on Comparative Genomics, RECOMB-CG 2009 - Budapest, Hungary
Duration: 27 Sep 200929 Sep 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5817 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference7th International Workshop on Comparative Genomics, RECOMB-CG 2009


  • Co-evolution
  • Maximum likelihood
  • Maximum parsimony
  • Reconstruction of ancestral genomes


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