title: Essential Genes Embody Increased Mutational Robustness to Compensate for the Lack of Backup Genetic Redundancy.
abstract: Genetic robustness is a hallmark of cells, occurring through many mechanisms and at many levels. Essential genes lack the common robustness mechanism of genetic redundancy (i.e., existing alongside other genes with the same function), and thus appear at first glance to leave cells highly vulnerable to genetic or environmental perturbations. Here we explore a hypothesis that cells might protect against essential gene loss through mechanisms that occur at various cellular levels aside from the level of the gene. Using Escherichia coli and Saccharomyces cerevisiae as models, we find that essential genes are enriched over non-essential genes for properties we call "coding efficiency" and "coding robustness", denoting respectively a gene's efficiency of translation and robustness to non-synonymous mutations. The coding efficiency levels of essential genes are highly positively correlated with their evolutionary conservation levels, suggesting that this feature plays a key role in protecting conserved, evolutionarily important genes. We then extend our hypothesis into the realm of metabolic networks, showing that essential metabolic reactions are encoded by more "robust" genes than non-essential reactions, and that essential metabolites are produced by more reactions than non-essential metabolites. Taken together, these results testify that robustness at the gene-loss level and at the mutation level (and more generally, at two cellular levels that are usually treated separately) are not decoupled, but rather, that cellular vulnerability exposed due to complete gene loss is compensated by increased mutational robustness. Why some genes are backed up primarily against loss and others against mutations still remains an open question.
authors.affiliation: School of Computer Sciences and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
authors.forename: Osher
authors.initials: O
authors.lastname: Cohen
authors.affiliation: Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, United States of America.
authors.forename: Matthew
authors.initials: M
authors.lastname: Oberhardt
authors.affiliation: School of Computer Sciences and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
authors.forename: Keren
authors.initials: K
authors.lastname: Yizhak
authors.affiliation: School of Computer Sciences and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, United States of America.
authors.forename: Eytan
authors.initials: E
authors.lastname: Ruppin
mesh_terms: D053263:Gene Regulatory Networks; D005800:Genes, Fungal; D008957:Models, Genetic; D009154:Mutation; D012441:Saccharomyces cerevisiae / Q000235:genetics* / Q000378:metabolism