Dataset Information

Ascertaining regions affected by GC-biased gene conversion through weak-to-strong mutational hotspots.

ABSTRACT: A major objective for evolutionary biology is to identify regions affected by positive selection. High dN/dS values for proteins and accelerated lineage-specific substitution rates for non-coding regions are considered classic signatures of positive selection. However, these could also be the result of non-adaptive phenomena, such as GC-biased gene conversion (gBGC), which favors the fixation of strong (C/G) over weak (A/T) nucleotides. Recent estimates indicate that gBGC affected up to 20% of regions with signatures of positive selection. Here we evaluate the impact of gBGC through its molecular signature of weak-to-strong mutational hotspots. We implemented specific modifications to the test proposed by Tang and Lewontin (1999) for identifying regions of differential variability and applied it to regions previously investigated for the influence of gBGC. While we found significant agreement with previous reports, our results suggest a smaller influence of gBGC than previously estimated, warranting further development of methods for its detection.

SUBMITTER: Gotea V

PROVIDER: S-EPMC4527313 | biostudies-literature | 2014 May-Jun

REPOSITORIES: biostudies-literature

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Ascertaining regions affected by GC-biased gene conversion through weak-to-strong mutational hotspots.

Gotea Valer V Elnitski Laura L

Genomics 20140413 5-6

A major objective for evolutionary biology is to identify regions affected by positive selection. High dN/dS values for proteins and accelerated lineage-specific substitution rates for non-coding regions are considered classic signatures of positive selection. However, these could also be the result of non-adaptive phenomena, such as GC-biased gene conversion (gBGC), which favors the fixation of strong (C/G) over weak (A/T) nucleotides. Recent estimates indicate that gBGC affected up to 20% of r ...[more]

PMID: 24727706

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Project description:The characterization of functional elements in genomes relies on the identification of the footprints of natural selection. In this quest, taking into account neutral evolutionary processes such as mutation and genetic drift is crucial because these forces can generate patterns that may obscure or mimic signatures of selection. In mammals, and probably in many eukaryotes, another such confounding factor called GC-Biased Gene Conversion (gBGC) has been documented. This mechanism generates patterns identical to what is expected under selection for higher GC-content, specifically in highly recombining genomic regions. Recent results have suggested that a mysterious selective force favouring higher GC-content exists in Bacteria but the possibility that it could be gBGC has been excluded. Here, we show that gBGC is probably at work in most if not all bacterial species. First we find a consistent positive relationship between the GC-content of a gene and evidence of intra-genic recombination throughout a broad spectrum of bacterial clades. Second, we show that the evolutionary force responsible for this pattern is acting independently from selection on codon usage, and could potentially interfere with selection in favor of optimal AU-ending codons. A comparison with data from human populations shows that the intensity of gBGC in Bacteria is comparable to what has been reported in mammals. We propose that gBGC is not restricted to sexual Eukaryotes but also widespread among Bacteria and could therefore be an ancestral feature of cellular organisms. We argue that if gBGC occurs in bacteria, it can account for previously unexplained observations, such as the apparent non-equilibrium of base substitution patterns and the heterogeneity of gene composition within bacterial genomes. Because gBGC produces patterns similar to positive selection, it is essential to take this process into account when studying the evolutionary forces at work in bacterial genomes.

Dataset Information

Ascertaining regions affected by GC-biased gene conversion through weak-to-strong mutational hotspots.

Publications

Ascertaining regions affected by GC-biased gene conversion through weak-to-strong mutational hotspots.

Similar Datasets

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