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Identifying a high fraction of the human genome to be under selective constraint using GERP++.

ABSTRACT: Computational efforts to identify functional elements within genomes leverage comparative sequence information by looking for regions that exhibit evidence of selective constraint. One way of detecting constrained elements is to follow a bottom-up approach by computing constraint scores for individual positions of a multiple alignment and then defining constrained elements as segments of contiguous, highly scoring nucleotide positions. Here we present GERP++, a new tool that uses maximum likelihood evolutionary rate estimation for position-specific scoring and, in contrast to previous bottom-up methods, a novel dynamic programming approach to subsequently define constrained elements. GERP++ evaluates a richer set of candidate element breakpoints and ranks them based on statistical significance, eliminating the need for biased heuristic extension techniques. Using GERP++ we identify over 1.3 million constrained elements spanning over 7% of the human genome. We predict a higher fraction than earlier estimates largely due to the annotation of longer constrained elements, which improves one to one correspondence between predicted elements with known functional sequences. GERP++ is an efficient and effective tool to provide both nucleotide- and element-level constraint scores within deep multiple sequence alignments.

SUBMITTER: Davydov EV

PROVIDER: S-EPMC2996323 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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Identifying a high fraction of the human genome to be under selective constraint using GERP++.

Davydov Eugene V EV Goode David L DL Sirota Marina M Cooper Gregory M GM Sidow Arend A Batzoglou Serafim S

PLoS computational biology 20101202 12

Computational efforts to identify functional elements within genomes leverage comparative sequence information by looking for regions that exhibit evidence of selective constraint. One way of detecting constrained elements is to follow a bottom-up approach by computing constraint scores for individual positions of a multiple alignment and then defining constrained elements as segments of contiguous, highly scoring nucleotide positions. Here we present GERP++, a new tool that uses maximum likelih ...[more]

PMID: 21152010

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Project description:As predicted by the nearly neutral model of evolution, numerous studies have shown that reduced N(e) accelerates the accumulation of slightly deleterious changes under genetic drift. While such studies have mostly focused on eukaryotes, bacteria also offer excellent models to explore the effects of N(e). Most notably, the genomes of host-dependent bacteria with small N(e) show signatures of genetic drift, including elevated K(a)/K(s). Here, I explore the utility of an alternative measure of selective constraint: the per-site rate of radical and conservative amino acid substitutions (D(r)/D(c)). I test the hypothesis that purifying selection against radical amino acid changes is less effective in two insect endosymbiont groups (Blochmannia of ants and Buchnera of aphids), compared to related gamma-Proteobacteria. Genome comparisons demonstrate a significant elevation in D(r)/D(c) in endosymbionts that affects the majority (66-79%) of shared orthologs examined. The elevation of D(r)/D(c) in endosymbionts affects all functional categories examined. Simulations indicate that D(r)/D(c) estimates are sensitive to codon frequencies and mutational parameters; however, estimation biases occur in the opposite direction as the patterns observed in genome comparisons, thereby making the inference of elevated D(r)/D(c) more conservative. Increased D(r)/D(c) and other signatures of genome degradation in endosymbionts are consistent with strong effects of genetic drift in their small populations, as well as linkage to selected sites in these asexual bacteria. While relaxed selection against radical substitutions may contribute, genome-wide processes such as genetic drift and linkage best explain the pervasive elevation in D(r)/D(c) across diverse functional categories that include basic cellular processes. Although the current study focuses on a few bacterial lineages, it suggests D(r)/D(c) is a useful gauge of selective constraint and may provide a valuable alternative to K(a)/K(s) when high sequence divergences preclude estimates of K(s). Broader application of D(r)/D(c) will benefit from approaches less prone to estimation biases.

Project description:BackgroundRegions of the genome that are under evolutionary constraint across multiple species have previously been used to identify functional sequences in the human genome. Furthermore, it is known that there is an inverse relationship between evolutionary constraint and the allele frequency of a mutation segregating in human populations, implying a direct relationship between interspecies divergence and fitness in humans. Here we utilise this relationship to test differences in the accumulation of putatively deleterious mutations both between populations and on the individual level.ResultsUsing whole genome and exome sequencing data from Phase 1 of the 1000 Genome Project for 1,092 individuals from 14 worldwide populations we show that minor allele frequency (MAF) varies as a function of constraint around both coding regions and non-coding sites genome-wide, implying that negative, rather than positive, selection primarily drives the distribution of alleles among individuals via background selection. We find a strong relationship between effective population size and the depth of depression in MAF around the most conserved genes, suggesting that populations with smaller effective size are carrying more deleterious mutations, which also translates into higher genetic load when considering the number of putatively deleterious alleles segregating within each population. Finally, given the extreme richness of the data, we are now able to classify individual genomes by the accumulation of mutations at functional sites using high coverage 1000 Genomes data. Using this approach we detect differences between 'healthy' individuals within populations for the distributions of putatively deleterious rare alleles they are carrying.ConclusionsThese findings demonstrate the extent of background selection in the human genome and highlight the role of population history in shaping patterns of diversity between human individuals. Furthermore, we provide a framework for the utility of personal genomic data for the study of genetic fitness and diseases.

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Identifying a high fraction of the human genome to be under selective constraint using GERP++.

Publications

Identifying a high fraction of the human genome to be under selective constraint using GERP++.

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