Tempo of degeneration across independently evolved non-recombining regions

Recombination is beneficial over the long term, allowing more effective selection. Despite long-term advantages of recombination, local recombination suppression is known to evolve and lead to genomic degeneration, in particular on sex and mating-type chromosomes, sometimes linked to severe genetic diseases. Here, we investigated the tempo of degeneration in non-recombining regions, i.e., the function curve for the accumulation of deleterious mutations over time, taking advantage of 17 independent events of large recombination suppression identified on mating-type chromosomes of anther-smut fungi, including five newly identified in the present study. Using high-quality genomes assemblies of alternative mating types of 13 Microbotryum species, we estimated the degeneration levels in terms of accumulation of non-optimal codons and non-synonymous substitutions in non-recombining regions. We found a reduced frequency of optimal codons in the non-recombining regions on mating-type chromosomes compared to autosomes. We showed that the lower frequency of optimal codons in non-recombining regions was not due to less frequent GC-biased gene conversion or lower ancestral expression levels compared to recombining regions. We estimated that the frequency of optimal codon usage decreased linearly at a rate of 0.989 per My. The non-synonymous over synonymous substitution rate (dN/dS) increased rapidly after recombination suppression and then reached a plateau. To our knowledge this is the first study to disentangle effects of reduced selection efficacy from GC-biased gene conversion in the evolution of optimal codon usage to quantify the tempo of degeneration in non-recombining regions, leveraging on multiple independent recombination suppression events. Understanding the tempo of degeneration is important for our knowledge on genomic evolution, on the origin of genetic diseases and on the maintenance of regions without recombination.

Signatures of optimal codon usage in metabolic genes inform budding yeast ecology

Reverse ecology is the inference of ecological information from patterns of genomic variation. One rich, heretofore underutilized, source of ecologically relevant genomic information is codon optimality or adaptation. Bias toward codons that match the tRNA pool is robustly associated with high gene expression in diverse organisms, suggesting that codon optimization could be used in a reverse ecology framework to identify highly expressed, ecologically relevant genes. To test this hypothesis, we examined the relationship between optimal codon usage in the classic galactose metabolism (GAL) pathway and known ecological niches for 329 species of budding yeasts, a diverse subphylum of fungi. We find that optimal codon usage in the GAL pathway is positively correlated with quantitative growth on galactose, suggesting that GAL codon optimization reflects increased capacity to grow on galactose. Optimal codon usage in the GAL pathway is also positively correlated with human-associated ecological niches in yeasts of the CUG-Ser1 clade and with dairy-associated ecological niches in the family Saccharomycetaceae. For example, optimal codon usage of GAL genes is greater than 85% of all genes in the genome of the major human pathogen Candida albicans (CUG-Ser1 clade) and greater than 75% of genes in the genome of the dairy yeast Kluyveromyces lactis (family Saccharomycetaceae). We further find a correlation between optimization in the GALactose pathway genes and several genes associated with nutrient sensing and metabolism. This work suggests that codon optimization harbors information about the metabolic ecology of microbial eukaryotes. This information may be particularly useful for studying fungal dark matter—species that have yet to be cultured in the lab or have only been identified by genomic material.

Optimal Evolution of the Standard Genetic Code

The Standard Genetic Code (SGC) exists in every known organism on Earth. SGC evolution via early unique codon assignment, then later wobble, yields coding resembling the near-universal code. Below, later wobble is shown to also create an optimal route to accurate codon assignment. Time of optimal codon assignment matches the previously defined mean time for ordered coding, exhibiting ≥ 90% of SGC order. Accurate evolution is also accessible, sufficiently frequent to appear in populations of 103 to 104 codes. SGC-like coding capacity, code order, and accurate assignments therefore arise together, in one attainable evolutionary intermediate. Examples, which plausibly resemble coding at evolutionary domain separation, are characterized.

Design principles of gene evolution for niche adaptation through changes in protein–protein interaction networks

In contrast to fossorial and above-ground organisms, subterranean species have adapted to the extreme stresses of living underground. We analyzed the predicted protein–protein interactions (PPIs) of all gene products, including those of stress-response genes, among nine subterranean, ten fossorial, and 13 aboveground species. We considered 10,314 unique orthologous protein families and constructed 5,879,879 PPIs in all organisms using ChiPPI. We found strong association between PPI network modulation and adaptation to specific habitats, noting that mutations in genes and changes in protein sequences were not linked directly with niche adaptation in the organisms sampled. Thus, orthologous hypoxia, heat-shock, and circadian clock proteins were found to cluster according to habitat, based on PPIs rather than on sequence similarities. Curiously, "ordered" domains were preserved in aboveground species, while "disordered" domains were conserved in subterranean organisms, and confirmed for proteins in DistProt database. Furthermore, proteins with disordered regions were found to adopt significantly less optimal codon usage in subterranean species than in fossorial and above-ground species. These findings reveal design principles of protein networks by means of alterations in protein domains, thus providing insight into deep mechanisms of evolutionary adaptation, generally, and particularly of species to underground living and other confined habitats.

Signatures of optimal codon usage predict metabolic ecology in budding yeasts

ABSTRACTReverse ecology is the inference of ecological information from patterns of genomic variation. One rich, heretofore underutilized, source of ecologically-relevant genomic information is codon optimality or adaptation. Bias toward codons that match the tRNA pool is robustly associated with high gene expression in diverse organisms, suggesting that codon optimization could be used in a reverse ecology framework to identify highly expressed, ecologically relevant genes. To test this hypothesis, we examined the relationship between optimal codon usage in the classic galactose metabolism (GAL) pathway and known ecological niches for 329 species of budding yeasts, a diverse subphylum of fungi. We find that optimal codon usage in the GAL pathway is positively correlated with quantitative growth on galactose, suggesting that GAL codon optimization reflects increased capacity to grow on galactose. Optimal codon usage in the GAL pathway is also positively correlated with human-associated ecological niches in yeasts of the CUG-Ser1 clade and with dairy-associated ecological niches in the family Saccharomycetaceae. For example, optimal codon usage of GAL genes is greater than 85% of all genes in the major human pathogen Candida albicans (CUG-Ser1 clade) and greater than 75% of genes in the dairy yeast Kluyveromyces lactis (family Saccharomycetaceae). We further find a correlation between optimization in the thiamine biosynthesis and GAL pathways. As a result, optimal codon usage in thiamine biosynthesis genes is also associated with dairy ecological niches in Saccharomycetaceae, which may reflect competition with co-occurring microbes for extracellular thiamine. This work highlights the potential of codon optimization as a tool for gaining insights into the metabolic ecology of microbial eukaryotes. Doing so may be especially illuminating for studying fungal dark matter—species that have yet to be cultured in the lab or have only been identified by genomic material.

Codon optimization: a mathematical programing approach

Motivation Synthesizing proteins in heterologous hosts is an important tool in biotechnology. However, the genetic code is degenerate and the codon usage is biased in many organisms. Synonymous codon changes that are customized for each host organism may have a significant effect on the level of protein expression. This effect can be measured by using metrics, such as codon adaptation index, codon pair bias, relative codon bias and relative codon pair bias. Codon optimization is designing codons that improve one or more of these objectives. Currently available algorithms and software solutions either rely on heuristics without providing optimality guarantees or are very rigid in modeling different objective functions and restrictions. Results We develop an effective mixed integer linear programing (MILP) formulation, which considers multiple objectives. Our numerical study shows that this formulation can be effectively used to generate (Pareto) optimal codon designs even for very long amino acid sequences using a standard commercial solver. We also show that one can obtain designs in the efficient frontier in reasonable solution times and incorporate other complex objectives, such as mRNA secondary structures in codon design using MILP formulations. Availability and implementation http://alpersen.bilkent.edu.tr/codonoptimization/CodonOptimization.zip.

Combinations of slow translating codon clusters can increase mRNA half-life

The introduction of a single, non-optimal codon cluster into a transcript was found to cause ribosomes to queue upstream of it and decrease the transcript’s half-life through the action of the dead box protein Dhh1p, which interacts with stalled ribosomes and promotes transcript degradation. Naturally occurring transcripts often contain multiple slow codon clusters, but the influence of these combinations of clusters on a transcript’s half-life is unknown. Using a kinetic model that describes translation and mRNA degradation, we find that the introduction of a second slow codon cluster into a transcript near the 5′-end can have the opposite effect than that of the first cluster by increasing the mRNA’s half-life. We experimentally validate this finding by showing that S. cerevisiae transcripts that only have a slow codon cluster towards the 3′-end of the coding sequence have shorter half-lives than transcripts with non-optimal clusters at both 3′ and 5′ -ends. The origin of this increase in half-life arises from the 5′-end cluster suppressing the formation of ribosome queues upstream of the second cluster, thereby decreasing the opportunities for translation-dependent degradation machinery, such as the Dhh1p protein, to interact with stalled ribosomes. We also find in the model that in the presence of two slow codon clusters the cluster closest to 5′-end is the primary determinant of mRNA half-life. These results identify two of the rules governing the influence of slow codon clusters on mRNA half-life, demonstrate that multiple slow codon clusters can have synergistic effects, and indicate that codon usage bias can play a more nuanced role in controlling cellular protein levels than previously thought.

Unfolded Protein Response Suppression in Yeast by Loss of tRNA Modifications

Modifications in the anticodon loop of transfer RNAs (tRNAs) have been shown to ensure optimal codon translation rates and prevent protein homeostasis defects that arise in response to translational pausing. Consequently, several yeast mutants lacking important anticodon loop modifications were shown to accumulate protein aggregates. Here we analyze whether this includes the activation of the unfolded protein response (UPR), which is commonly triggered by protein aggregation within the endoplasmic reticulum (ER). We demonstrate that two different aggregation prone tRNA modification mutants (elp6 ncs2; elp3 deg1) lacking combinations of 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2U: elp3; elp6; ncs2) and pseudouridine (Ψ: deg1) reduce, rather than increase, splicing of HAC1 mRNA, an event normally occurring as a precondition of UPR induction. In addition, tunicamycin (TM) induced HAC1 splicing is strongly impaired in the elp3 deg1 mutant. Strikingly, this mutant displays UPR independent resistance against TM, a phenotype we found to be rescued by overexpression of tRNAGln(UUG), the tRNA species usually carrying the mcm5s2U34 and Ψ38 modifications. Our data indicate that proper tRNA anticodon loop modifications promote rather than impair UPR activation and reveal that protein synthesis and homeostasis defects in their absence do not routinely result in UPR induction but may relieve endogenous ER stress.