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Fitting background-selection predictions to levels of nucleotide variation and divergence along the human autosomes.

ABSTRACT: The roles of positive directional selection (selective sweeps) and negative selection (background selection) in shaping the genome-wide distribution of genetic variation in humans remain largely unknown. Here, we optimize the parameter values of a model of the removal of deleterious mutations (background selection) to observed levels of human polymorphism, controlling for mutation rate heterogeneity by using interspecific divergence. A point of "best fit" was found between background-selection predictions and estimates of human effective population sizes, with reasonable parameter estimates whose uncertainty was assessed by bootstrapping. The results suggest that the purging of deleterious alleles has had some influence on shaping levels of human variation, although the effects may be subtle over the majority of the human genome. A significant relationship was found between background-selection predictions and measures of skew in the allele frequency distribution. The genome-wide action of selection (positive and/or negative) is required to explain this observation.

SUBMITTER: Reed FA

PROVIDER: S-EPMC1199535 | biostudies-literature | 2005 Sep

REPOSITORIES: biostudies-literature

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Fitting background-selection predictions to levels of nucleotide variation and divergence along the human autosomes.

Reed Floyd A FA Akey Joshua M JM Aquadro Charles F CF

Genome research 20050901 9

The roles of positive directional selection (selective sweeps) and negative selection (background selection) in shaping the genome-wide distribution of genetic variation in humans remain largely unknown. Here, we optimize the parameter values of a model of the removal of deleterious mutations (background selection) to observed levels of human polymorphism, controlling for mutation rate heterogeneity by using interspecific divergence. A point of "best fit" was found between background-selection p ...[more]

PMID: 16140989

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Project description:The constant removal of deleterious mutations by natural selection causes a reduction in neutral diversity and efficacy of selection at genetically linked sites (a process called Background Selection, BGS). Population genetic studies, however, often ignore BGS effects when investigating demographic events or the presence of other types of selection. To obtain a more realistic evolutionary expectation that incorporates the unavoidable consequences of deleterious mutations, we generated high-resolution landscapes of variation across the Drosophila melanogaster genome under a BGS scenario independent of polymorphism data. We find that BGS plays a significant role in shaping levels of variation across the entire genome, including long introns and intergenic regions distant from annotated genes. We also find that a very large percentage of the observed variation in diversity across autosomes can be explained by BGS alone, up to 70% across individual chromosome arms at 100-kb scale, thus indicating that BGS predictions can be used as baseline to infer additional types of selection and demographic events. This approach allows detecting several outlier regions with signal of recent adaptive events and selective sweeps. The use of a BGS baseline, however, is particularly appropriate to investigate the presence of balancing selection and our study exposes numerous genomic regions with the predicted signature of higher polymorphism than expected when a BGS context is taken into account. Importantly, we show that these conclusions are robust to the mutation and selection parameters of the BGS model. Finally, analyses of protein evolution together with previous comparisons of genetic maps between Drosophila species, suggest temporally variable recombination landscapes and, thus, local BGS effects that may differ between extant and past phases. Because genome-wide BGS and temporal changes in linkage effects can skew approaches to estimate demographic and selective events, future analyses should incorporate BGS predictions and capture local recombination variation across genomes and along lineages.

Dataset Information

Fitting background-selection predictions to levels of nucleotide variation and divergence along the human autosomes.

Publications

Fitting background-selection predictions to levels of nucleotide variation and divergence along the human autosomes.

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