The Evolutionary Traceability of a Protein

The Evolutionary Traceability of a Protein

Abstract

Orthologs document the evolution of genes and metabolic capacities encoded in extant and ancient genomes. However, the similarity between orthologs decays with time, and ultimately it becomes insufficient to infer common ancestry. This leaves ancient gene set reconstructions incomplete and distorted to an unknown extent. Here we introduce the “evolutionary traceability” as a measure that quantifies, for each protein, the evolutionary distance beyond which the sensitivity of the ortholog search becomes limiting. Using yeast, we show that genes that were thought to date back to the last universal common ancestor are of high traceability. Their functions mostly involve catalysis, ion transport, and ribonucleoprotein complex assembly. In turn, the fraction of yeast genes whose traceability is not sufficient to infer their presence in last universal common ancestor is enriched for regulatory functions. Computing the traceabilities of genes that have been experimentally characterized as being essential for a self-replicating cell reveals that many of the genes that lack orthologs outside bacteria have low traceability. This leaves open whether their orthologs in the eukaryotic and archaeal domains have been overlooked. Looking at the example of REC8, a protein essential for chromosome cohesion, we demonstrate how a traceability-informed adjustment of the search sensitivity identifies hitherto missed orthologs in the fast-evolving microsporidia. Taken together, the evolutionary traceability helps to differentiate between true absence and nondetection of orthologs, and thus improves our understanding about the evolutionary conservation of functional protein networks. “protTrace,” a software tool for computing evolutionary traceability, is freely available at https://github.com/BIONF/protTrace.git; last accessed February 10, 2019.

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Authors
  • Jain, Arpit
  • Perisa, Dominik
  • Fliedner, Fabian
  • von Haeseler, Arndt
  • Ebersberger, Ingo
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Shortfacts
Category
Journal Paper
Divisions
Bioinformatics and Computational Biology
Journal or Publication Title
Genome Biology and Evolution
ISSN
1759-6653
Publisher
Oxford University Press
Place of Publication
Oxford
Page Range
pp. 531-545
Number
2
Volume
11
Date
15 January 2019
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