Briefings in BioinformaticsBioinformaticsPeer-reviewed journal article
Comparing orthology methods and their performance by recapitulating patterns of eukaryotic genome evolution.
Abstract
Insights into the evolution of ancestral complexes and pathways are generally achieved through careful and time-intensive manual analysis often using phylogenetic profiles of the constituent proteins. This manual analysis limits the possibility of including more protein-complex components, repeating the analyses for updated genome sets, or expanding the analyses to larger scales. Automated orthology inference should allow such large scale analyses, but substantial differences between orthologous groups generated by different approaches are observed. We evaluate orthology methods for their ability to recapitulate a number of observations that have been made with regards to genome evolution in eukaryotes. Specifically, we investigate phylogenetic profile similarity (co-occurrence of complexes), the Last Eukaryotic Common Ancestors gene content, pervasiveness of gene loss, and the overlap with manually determined orthologous groups. Moreover, we compare the inferred orthologies to each other. We find that most orthology methods reconstruct a large Last Eukaryotic Common Ancestor, with substantial gene loss, and can predict interacting proteins reasonably well when applying phylogenetic co-occurrence. At the same time derived orthologous groups show imperfect overlap with manually curated orthologous groups. There is no strong indication of which orthology method performs better than another on individual or all of these aspects. Counterintuitively, despite the orthology methods behaving similarly regarding large scale evaluation, the obtained orthologous groups differ vastly from one another. Availability and implementationThe data and code underlying this article are available in github and/or upon reasonable request to the corresponding author: https://github.com/ESDeutekom/ComparingOrthologies. SummaryO_LIWe compared multiple orthology inference methods by looking at how well they perform in recapitulating multiple observations made in eukaryotic genome evolution. C_LIO_LICo-occurrence of proteins is predicted fairly well by most methods and all show similar behaviour when looking at loss numbers and dynamics. C_LIO_LIAll the methods show imperfect overlap when compared to manually curated orthologous groups and when compared to orthologous groups of the other methods. C_LIO_LIDifferences are compared between methods by looking at how the inferred orthologies represent a high-quality set of manually curated orthologous groups. C_LIO_LIWe conclude that all methods behave similar when describing general patterns in eukaryotic genome evolution. However, there are large differences within the orthologies themselves, arising from how a method can differentiate between distant homology, recent duplications, or classifying orthologous groups. C_LI
- Citations
- 23
- FWCI
- 1.22
- Field percentile
- top 23%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Phylogenetic profiling in eukaryotes: The effect of species, orthologous group, and interactome selection on protein interaction prediction
Eva S. Deutekom, Teunis J. P. van Dam, Berend Snel·PLoS ONEPeer-reviewed·Apr 14, 2022
- OrthoFinder: phylogenetic orthology inference for comparative genomics
David Emms, Steven L. Kelly·Genome biologyPeer-reviewed·Nov 14, 2019
- Quantified duplications of proteins within complexes across eukaryotes
Ore Francis·bioRxiv·Feb 25, 2026
- OrthoHMM: Improved Inference of Ortholog Groups using Hidden Markov Models
Jacob Lucas Steenwyk, Thomas J. Buida, … Nicole King·bioRxiv·Dec 7, 2024
- Comparative Clustering (CompaCt) of eukaryote complexomes identifies novel interactions and sheds light on protein complex evolution
Joeri van Strien, Felix Evers, … Martijn A. Huynen·PLoS Computational BiologyPeer-reviewed·Aug 7, 2023
- OrthoFinder: scalable phylogenetic orthology inference for comparative genomics
David Emms, Yi Liu, … Steven L. Kelly·bioRxiv·Jul 15, 2025