Conflicting selection pressures on synonymous codon use in yeast suggest selection on mRNA secondary structures

<p>Abstract</p> <p>Background</p> <p>Eukaryotic mRNAs often contain secondary structures in their untranslated regions that are involved in expression regulation. Whether secondary structures in the protein coding regions are of functional importance remains unclear: laboratory studies suggest stable secondary structures within the protein coding sequence interfere with translation, while several bioinformatic studies indicate stable mRNA structures are more frequent than expected.</p> <p>Results</p> <p>In contrast to several studies testing for unexpected structural stabilities, I directly compare the selective constraint of sites that differ in their structural importance. I.e. for each nucleotide, I identify whether it is paired with another nucleotide, or unpaired, in the predicted secondary structure. I assume paired sites are more important for the predicted secondary structure than unpaired sites. I look at protein coding yeast sequences and use optimal codons and synonymous substitutions to test for structural constraints. As expected under selection for secondary structures, paired sites experience higher constraint than unpaired sites, i.e. significantly lower numbers of conserved optimal codons and consistently lower numbers of synonymous substitutions. This is true for structures predicted by different algorithms.</p> <p>Conclusion</p> <p>The results of this study are consistent with purifying selection on mRNA secondary structures in yeast protein coding sequences and suggest their biological importance. One should be aware, however, that accuracy of structure prediction is unknown for mRNAs and interrelated selective forces may contribute as well. Note that if selection pressures alternative to translational selection affect synonymous (and optimal) codon use, this may lead to under- or over-estimates of selective strength on optimal codon use depending on strength and direction of translational selection.</p

The assessment of science: the relative merits of post- publication review, the impact factor, and the number of citations

The assessment of scientific publications is an integral part of the scientific process. Here we investigate three methods of assessing the merit of a scientific paper: subjective post-publication peer review, the number of citations gained by a paper, and the impact factor of the journal in which the article was published. We investigate these methods using two datasets in which subjective post-publication assessments of scientific publications have been made by experts. We find that there are moderate, but statistically significant, correlations between assessor scores, when two assessors have rated the same paper, and between assessor score and the number of citations a paper accrues. However, we show that assessor score depends strongly on the journal in which the paper is published, and that assessors tend to over-rate papers published in journals with high impact factors. If we control for this bias, we find that the correlation between assessor scores and between assessor score and the number of citations is weak, suggesting that scientists have little ability to judge either the intrinsic merit of a paper or its likely impact. We also show that the number of citations a paper receives is an extremely error-prone measure of scientific merit. Finally, we argue that the impact factor is likely to be a poor measure of merit, since it depends on subjective assessment. We conclude that the three measures of scientific merit considered here are poor; in particular subjective assessments are an error-prone, biased, and expensive method by which to assess merit. We argue that the impact factor may be the most satisfactory of the methods we have considered, since it is a form of pre-publication review. However, we emphasise that it is likely to be a very error-prone measure of merit that is qualitative, not quantitative

Reduced local mutation density in regulatory DNA of cancer genomes is linked to DNA repair

Carcinogenesis and neoplastic progression are mediated by the accumulation of somatic mutations. Here we report that the local density of somatic mutations in cancer genomes is highly reduced specifically in accessible regulatory DNA defined by DNase I hypersensitive sites. This reduction is independent of any known factors influencing somatic mutation density and is observed in diverse cancer types, suggesting a general mechanism. By analyzing individual cancer genomes1, we show that the reduced local mutation density within regulatory DNA is linked to intact global genome repair machinery, with nearly complete abrogation of the hypomutation phenomenon in individual cancers that possess mutations in multiple nucleotide excision repair components. Together, our results connect chromatin structure, gene regulation and cancer-associated somatic mutation

The surprising negative correlation of gene length and optimal codon use - disentangling translational selection from GC-biased gene conversion in yeast

<p>Abstract</p> <p>Background</p> <p>Surprisingly, in several multi-cellular eukaryotes optimal codon use correlates negatively with gene length. This contrasts with the expectation under selection for translational accuracy. While suggested explanations focus on variation in strength and efficiency of translational selection, it has rarely been noticed that the negative correlation is reported only in organisms whose optimal codons are biased towards codons that end with G or C (-GC). This raises the question whether forces that affect base composition - such as GC-biased gene conversion - contribute to the negative correlation between optimal codon use and gene length.</p> <p>Results</p> <p>Yeast is a good organism to study this as equal numbers of optimal codons end in -GC and -AT and one may hence compare frequencies of optimal GC- with optimal AT-ending codons to disentangle the forces. Results of this study demonstrate in yeast frequencies of GC-ending (optimal AND non-optimal) codons decrease with gene length and increase with recombination. A decrease of GC-ending codons along genes contributes to the negative correlation with gene length. Correlations with recombination and gene expression differentiate between GC-ending and optimal codons, and also substitution patterns support effects of GC-biased gene conversion.</p> <p>Conclusion</p> <p>While the general effect of GC-biased gene conversion is well known, the negative correlation of optimal codon use with gene length has not been considered in this context before. Initiation of gene conversion events in promoter regions and the presence of a gene conversion gradient most likely explain the observed decrease of GC-ending codons with gene length and gene position.</p

Charting the dynamics of translation

Codon usage bias (CUB) is the well-known phenomenon that the frequency of synonymous codons is unequal. This is presumably the result of adaptive pressures favouring some codons over others. The underlying reason for this pressure is unknown, although a large number of possible driver mechanisms have been proposed. According to one hypothesis, the decoding time could be such a driver. A tacit assumption of this hypothesis is that faster codons lead to a higher translation rate which in turn is more resource efficient. While it is generally assumed that there is such a link, there are no rigorous studies to establish under which conditions the link between translation speed and rate actually exists. Using a computational simulation model and explicitly calculated codon decoding times, this contribution maps the entire range of dynamical regimes of translation. These simulations make it possible to understand precisely under which conditions translation speed and rate are linked

Mutation Bias is the Driving Force of Codon Usage in the Gallus gallus genome

Synonymous codons are used with different frequencies both among species and among genes within the same genome and are controlled by neutral processes (such as mutation and drift) as well as by selection. Up to now, a systematic examination of the codon usage for the chicken genome has not been performed. Here, we carried out a whole genome analysis of the chicken genome by the use of the relative synonymous codon usage (RSCU) method and identified 11 putative optimal codons, all of them ending with uracil (U), which is significantly departing from the pattern observed in other eukaryotes. Optimal codons in the chicken genome are most likely the ones corresponding to highly expressed transfer RNA (tRNAs) or tRNA gene copy numbers in the cell. Codon bias, measured as the frequency of optimal codons (Fop), is negatively correlated with the G + C content, recombination rate, but positively correlated with gene expression, protein length, gene length and intron length. The positive correlation between codon bias and protein, gene and intron length is quite different from other multi-cellular organism, as this trend has been only found in unicellular organisms. Our data displayed that regional G + C content explains a large proportion of the variance of codon bias in chicken. Stepwise selection model analyses indicate that G + C content of coding sequence is the most important factor for codon bias. It appears that variation in the G + C content of CDSs accounts for over 60% of the variation of codon bias. This study suggests that both mutation bias and selection contribute to codon bias. However, mutation bias is the driving force of the codon usage in the Gallus gallus genome. Our data also provide evidence that the negative correlation between codon bias and recombination rates in G. gallus is determined mostly by recombination-dependent mutational patterns

Inference of Natural Selection from Interspersed Genomic Elements Based on Polymorphism and Divergence

Complete genome sequences contain valuable information about natural selection, but extracting this information for short, widely scattered noncoding elements remains a challenging problem. Here we introduce a new computational method for addressing this problem called Inference of Natural Selection from Interspersed Genomically coHerent elemenTs (INSIGHT). INSIGHT uses a generative probabilistic model to contrast patterns of polymorphism and divergence in the elements of interest with those in flanking neutral sites, pooling weak information from many short elements in a manner that accounts for variation among loci in mutation rates and genealogical backgrounds. The method is able to disentangle the contributions of weak negative, strong negative, and positive selection based on their distinct effects on patterns of polymorphism and divergence. Information about divergence is obtained from multiple outgroup genomes using a full phylogenetic model. The model is efficiently fitted to genome-wide data by decomposing the maximum likelihood estimation procedure into three straightforward stages. The key selection-related parameters are estimated by expectation maximization. Using simulations, we show that INSIGHT can accurately estimate several parameters of interest even in complex demographic scenarios. We apply our methods to noncoding RNAs, promoter regions, and transcription factor binding sites in the human genome, and find clear evidence of natural selection. We also present a detailed analysis of particular nucleotide positions within GATA2 binding sites and primary micro-RNA transcripts.Comment: 21 page manuscript, 4 figure, 4 tables + 3 supp figures + 3 supp tables + supp methods. V4: additional results on human noncoding RNAs annotated by GENCODE + refinement of previous versions + additional supplementary material included to main document. V5: some minor modifications. V6: this is an electronic version of an article published in Mol Biol Evol, 201

Unique Cost Dynamics Elucidate the Role of Frameshifting Errors in Promoting Translational Robustness

There is now considerable evidence supporting the view that codon usage is frequently under selection for translational accuracy. There are, however, multiple forms of inaccuracy (missense, premature termination, and frameshifting errors) and pinpointing a particular error process behind apparently adaptive mRNA anatomy is rarely straightforward. Understanding differences in the fitness costs associated with different types of translational error can help us devise critical tests that can implicate one error process to the exclusion of others. To this end, we present a model that captures distinct features of frameshifting cost and apply this to 641 prokaryotic genomes. We demonstrate that, although it is commonly assumed that the ribosome encounters an off-frame stop codon soon after the frameshift and costs of mis-elongation are therefore limited, genomes with high GC content typically incur much larger per-error costs. We go on to derive the prediction, unique to frameshifting errors, that differences in translational robustness between the 5′ and 3′ ends of genes should be less pronounced in genomes with higher GC content. This prediction we show to be correct. Surprisingly, this does not mean that GC-rich organisms necessarily carry a greater fitness burden as a consequence of accidental frameshifting. Indeed, increased per-error costs are often more than counterbalanced by lower predicted error rates owing to more diverse anticodon repertoires in GC-rich genomes. We therefore propose that selection on tRNA repertoires may operate to reduce frameshifting errors

A Universal Trend of Reduced mRNA Stability near the Translation-Initiation Site in Prokaryotes and Eukaryotes

Recent studies have suggested that the thermodynamic stability of mRNA secondary structure near the start codon can regulate translation efficiency in Escherichia coli, and that translation is more efficient the less stable the secondary structure. We survey the complete genomes of 340 species for signals of reduced mRNA secondary structure near the start codon. Our analysis includes bacteria, archaea, fungi, plants, insects, fishes, birds, and mammals. We find that nearly all species show evidence for reduced mRNA stability near the start codon. The reduction in stability generally increases with increasing genomic GC content. In prokaryotes, the reduction also increases with decreasing optimal growth temperature. Within genomes, there is variation in the stability among genes, and this variation correlates with gene GC content, codon bias, and gene expression level. For birds and mammals, however, we do not find a genome-wide trend of reduced mRNA stability near the start codon. Yet the most GC rich genes in these organisms do show such a signal. We conclude that reduced stability of the mRNA secondary structure near the start codon is a universal feature of all cellular life. We suggest that the origin of this reduction is selection for efficient recognition of the start codon by initiator-tRNA