Translational Selection Is Ubiquitous in Prokaryotes

Abstract

Codon usage bias in prokaryotic genomes is largely a consequence of background substitution patterns in DNA, but highly expressed genes may show a preference towards codons that enable more efficient and/or accurate translation. We introduce a novel approach based on supervised machine learning that detects effects of translational selection on genes, while controlling for local variation in nucleotide substitution patterns represented as sequence composition of intergenic DNA. A cornerstone of our method is a Random Forest classifier that outperformed previous distance measure-based approaches, such as the codon adaptation index, in the task of discerning the (highly expressed) ribosomal protein genes by their codon frequencies. Unlike previous reports, we show evidence that translational selection in prokaryotes is practically universal: in 460 of 461 examined microbial genomes, we find that a subset of genes shows a higher codon usage similarity to the ribosomal proteins than would be expected from the local sequence composition. These genes constitute a substantial part of the genome—between 5% and 33%, depending on genome size—while also exhibiting higher experimentally measured mRNA abundances and tending toward codons that match tRNA anticodons by canonical base pairing. Certain gene functional categories are generally enriched with, or depleted of codon-optimized genes, the trends of enrichment/depletion being conserved between Archaea and Bacteria. Prominent exceptions from these trends might indicate genes with alternative physiological roles; we speculate on specific examples related to detoxication of oxygen radicals and ammonia and to possible misannotations of asparaginyl–tRNA synthetases. Since the presence of codon optimizations on genes is a valid proxy for expression levels in fully sequenced genomes, we provide an example of an “adaptome” by highlighting gene functions with expression levels elevated specifically in thermophilic Bacteria and Archaea.

Evolution of optimal codon choices in the family Enterobacteriaceae

“…In contrast, B. aphidicola, W. glossinidia, D. dadantii, Serratia proteamaculans and Sodalis glossinidius showed the lowest selection coefficients. These results agree with those reported by Supek et al (2010) and Retchless & Lawrence (2011). The estimated correlation coefficient between MELP and ENC9 values also supports the observed trends among the analysed organisms (data not shown).…”

Extensive complementarity between gene function prediction methods

“…Fifth, evolution of codon usage biases relates to phenotypic divergence (Man and Pilpel, 2007) and can be used to predict the role of genes in environmental adaptation (Supek et al, 2010;Kriško et al, 2014). The translation efficiency profiles (TEP) (Kriško et al, 2014) measure codon biases associated to gene expression; similarity of such profiles suggests co-evolution of expression levels (Fraser et al, 2004).…”

Visual Gene Ontology Based Knowledge Discovery in Functional Genomics

“…As disadvantage, the compartment-like display of treemaps, far from the familiar graph structure of the Gene Ontology, might be dis-appealing for untrained users and this may explain the lesser use of this solution. Finally, one of the few tools that offer functionalities for reducing the complexity of large GO graphs is REViGO (Supek F, 2010). REViGO is a web server that can take long lists of Gene Ontology terms and summarize them by removing redundant GO terms.…”