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Synonymous and nonsynonymous polymorphisms versus divergences in bacterial genomes.

ABSTRACT: Comparison of the ratio of nonsynonymous to synonymous polymorphisms within species with the ratio of nonsynonymous to synonymous substitutions between species has been widely used as a supposed indicator of positive Darwinian selection, with the ratio of these 2 ratios being designated as a neutrality index (NI). Comparison of genome-wide polymorphism within 12 species of bacteria with divergence from an outgroup species showed substantial differences in NI among taxa. A low level of nonsynonymous polymorphism at a locus was the best predictor of NI < 1, rather than a high level of nonsynonymous substitution between species. Moreover, genes with NI < 1 showed a strong tendency toward the occurrence of rare nonsynonymous polymorphisms, as expected under the action of ongoing purifying selection. Thus, our results are more consistent with the hypothesis that a high relative rate of between-species nonsynonymous substitution reflects mainly the action of purifying selection within species to eliminate slightly deleterious mutations rather than positive selection between species. This conclusion is consistent with previous results highlighting an important role of slightly deleterious variants in bacterial evolution and suggests caution in the use of the McDonald-Kreitman test and related statistics as tests of positive selection.

SUBMITTER: Hughes AL

PROVIDER: S-EPMC2734133 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature

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Synonymous and nonsynonymous polymorphisms versus divergences in bacterial genomes.

Hughes Austin L AL Friedman Robert R Rivailler Pierre P French Jeffrey O JO

Molecular biology and evolution 20080730 10

Comparison of the ratio of nonsynonymous to synonymous polymorphisms within species with the ratio of nonsynonymous to synonymous substitutions between species has been widely used as a supposed indicator of positive Darwinian selection, with the ratio of these 2 ratios being designated as a neutrality index (NI). Comparison of genome-wide polymorphism within 12 species of bacteria with divergence from an outgroup species showed substantial differences in NI among taxa. A low level of nonsynonym ...[more]

PMID: 18667439

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Project description:Genomic data reveal single-nucleotide polymorphisms (SNPs) that may carry information about the evolutionary history of bacteria. However, it remains unclear what inferences about selection can be made from genomic SNP data. Bacterial species are often sampled during epidemic outbreaks or within hosts during the course of chronic infections. SNPs obtained from genomic analysis of these data are not necessarily fixed. Treating them as fixed during analysis by using measures such as the ratio of nonsynonymous to synonymous evolutionary changes (dN/dS) may lead to incorrect inferences about the strength and direction of selection. In this study, we consider data from a range of whole-genome sequencing studies of bacterial pathogens and explore patterns of nonsynonymous variation to assess whether evidence of selection can be identified by investigating SNP counts alone across multiple WGS studies. We visualize these SNP data in ways that highlight their relationship to neutral baseline expectations. These neutral expectations are based on a simple model of mutation, from which we simulate SNP accumulation to investigate how SNP counts are distributed under alternative assumptions about positive and negative selection. We compare these patterns with empirical SNP data and illustrate the general difficulty of detecting positive selection from SNP data. Finally, we consider whether SNP counts observed at the between-host population level diﬀer from those observed at the within-host level and find some evidence that suggests that dynamics across these two scales are driven by diﬀerent underlying processes.IMPORTANCE Identifying selection from SNP data obtained from whole-genome sequencing studies is challenging. Some current measures used to identify and quantify selection acting on genomes rely on fixed diﬀerences; thus, these are inappropriate for SNP data where variants are not fixed. With the increase in whole-genome sequencing studies, it is important to consider SNP data in the context of evolutionary processes. How SNPs are counted and analyzed can help in understanding mutation accumulation and trajectories of strains. We developed a tool for identifying possible evidence of selection and for comparative analysis with other SNP data. We propose a model that provides a rule-of-thumb guideline and two new visualization techniques that can be used to interpret and compare SNP data. We quantify the expected proportion of nonsynonymous SNPs in coding regions under neutrality and demonstrate its use in identifying evidence of positive and negative selection from simulations and empirical data.

Project description:BackgroundNonsynonymous mutations change the protein sequences and are frequently subjected to natural selection. The same goes for nonsense mutations that introduce pre-mature stop codons into CDSs (coding sequences). Synonymous mutations, however, are intuitively thought to be functionally silent and evolutionarily neutral. Now researchers know that the optimized synonymous codon usage is advantageous in the speedy mRNA translation process. With the advent of NGS technique, the explosion of NGS data generated from the tumor tissues help researchers identify driver mutations in cancer-related genes, but relatively less attention is paid to the SNP data in healthy human populations when studying cancer.MethodsHere, we analyzed the publically available human SNPs. We classified these SNPs according to their functional and evolutionary categories. By simply dividing the human genes into cancer-related genes and other genes, we compared the features of nonsynonymous, synonymous and nonsense mutations in these two gene sets from multiple aspects.ResultsWe provided lines of evidence that the nonsynonymous, synonymous and nonsense mutations in cancer-related genes undergo stronger purifying selection when compared to the expected pattern in other genes. The lower nonsynonymous to synonymous ratio observed in cancer-related genes suggests the suppression of amino acid substitutions in these genes. The synonymous SNPs, after excluding those in splicing regions, exhibit preferred changes in codon usage and higher codon frequencies in cancer-related genes compared to other genes, indicating the constraint exerted on these mutations. Nonsense mutations are less frequent and located closer to stop codons in cancer-related genes than in other genes, which putatively minimize their deleterious effects.ConclusionOur study demonstrated the evolutionary constraint on mutations in CDS of cancer-related genes without the requirement of data from cancer tissues or patients. Our work provides novel perspectives on interpreting the constraint on mutations in cancer-related genes. We reveal extra constraint on synonymous mutations in cancer-related genes which is related to codon usage bias and is in addition to the splicing effect.

Dataset Information

Synonymous and nonsynonymous polymorphisms versus divergences in bacterial genomes.

Publications

Synonymous and nonsynonymous polymorphisms versus divergences in bacterial genomes.

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