An evolutionary compass for detecting signals of polygenic selection and mutational bias.
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ABSTRACT:
SUBMITTER: Uricchio LH
PROVIDER: S-EPMC6369964 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Genomic traits such as codon usage and the lengths of noncoding sequences may be subject to stabilizing selection rather than purifying selection. Mutations affecting these traits are often biased in one direction. To investigate the potential role of stabilizing selection on genomic traits, the effects of mutational bias on the equilibrium value of a trait under stabilizing selection in a finite population were investigated, using two different mutational models. Numerical results were generated using a matrix method for calculating the probability distribution of variant frequencies at sites affecting the trait, as well as by Monte Carlo simulations. Analytical approximations were also derived, which provided useful insights into the numerical results. A novel conclusion is that the scaled intensity of selection acting on individual variants is nearly independent of the effective population size over a wide range of parameter space and is strongly determined by the logarithm of the mutational bias parameter. This is true even when there is a very small departure of the mean from the optimum, as is usually the case. This implies that studies of the frequency spectra of DNA sequence variants may be unable to distinguish between stabilizing and purifying selection. A similar investigation of purifying selection against deleterious mutations was also carried out. Contrary to previous suggestions, the scaled intensity of purifying selection with synergistic fitness effects is sensitive to population size, which is inconsistent with the general lack of sensitivity of codon usage to effective population size.
| S-EPMC3730922 | biostudies-literature
Project description:The incorporation of annotated sequence information from multiple related species in commonly used databases (Ensembl, Flybase, Saccharomyces Genome Database, Wormbase, etc.) has increased dramatically over the last few years. This influx of information has provided a considerable amount of raw material for evaluation of evolutionary relationships. To aid in the process, we have developed JCoDA (Java Codon Delimited Alignment) as a simple-to-use visualization tool for the detection of site specific and regional positive/negative evolutionary selection amongst homologous coding sequences.JCoDA accepts user-inputted unaligned or pre-aligned coding sequences, performs a codon-delimited alignment using ClustalW, and determines the dN/dS calculations using PAML (Phylogenetic Analysis Using Maximum Likelihood, yn00 and codeml) in order to identify regions and sites under evolutionary selection. The JCoDA package includes a graphical interface for Phylip (Phylogeny Inference Package) to generate phylogenetic trees, manages formatting of all required file types, and streamlines passage of information between underlying programs. The raw data are output to user configurable graphs with sliding window options for straightforward visualization of pairwise or gene family comparisons. Additionally, codon-delimited alignments are output in a variety of common formats and all dN/dS calculations can be output in comma-separated value (CSV) format for downstream analysis. To illustrate the types of analyses that are facilitated by JCoDA, we have taken advantage of the well studied sex determination pathway in nematodes as well as the extensive sequence information available to identify genes under positive selection, examples of regional positive selection, and differences in selection based on the role of genes in the sex determination pathway.JCoDA is a configurable, open source, user-friendly visualization tool for performing evolutionary analysis on homologous coding sequences. JCoDA can be used to rapidly screen for genes and regions of genes under selection using PAML. It can be freely downloaded at http://www.tcnj.edu/~nayaklab/jcoda.
| S-EPMC2887424 | biostudies-literature
Project description:We used comparative and population genomics to study intron evolutionary dynamics in the fungal model genus Neurospora. For our investigation, we used well-annotated genomes of N. crassa, N. discreta, and N. tetrasperma, and 92 resequenced genomes of N. tetrasperma from natural populations. By analyzing the four well-annotated genomes, we identified 9495 intron sites in 7619 orthologous genes. Our data supports nonhomologous end joining (NHEJ) and tandem duplication as mechanisms for intron gains in the genus and the RT-mRNA process as a mechanism for intron loss. We found a moderate intron gain rate (5.78-6.89 × 10(-13) intron gains per nucleotide site per year) and a high intron loss rate (7.53-13.76 × 10(-10) intron losses per intron sites per year) as compared to other eukaryotes. The derived intron gains and losses are skewed to high frequencies, relative to neutral SNPs, in natural populations of N. tetrasperma, suggesting that selection is involved in maintaining a high intron turnover. Furthermore, our analyses of the association between intron population-level frequency and genomic features suggest that selection is involved in shaping a 5' intron position bias and a low intron GC content. However, intron sequence analyses suggest that the gained introns were not exposed to recent selective sweeps. Taken together, this work contributes to our understanding of the importance of mutational bias and selection in shaping the intron distribution in eukaryotic genomes.
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Project description:Insertions and deletions (collectively indels) obviously have a major impact on genome evolution. However, before large-scale data on indel polymorphism became available, it was difficult to estimate the strength of selection acting on indel mutations. Here, we analyze indel polymorphism and divergence in different compartments of the Drosophila melanogaster genome: exons, introns of different lengths, and intergenic regions. Data on low-frequency polymorphisms indicate that 0.036-0.039 short (1-30 nt) insertion mutations and 0.085-0.092 short deletion mutations, with mean lengths 3.23 and 4.78, respectively, occur per single-nucleotide substitution. The excess of short deletion over short insertion mutations implies that indel mutations of these lengths should lead to a loss of approximately 0.30 nt per single-nucleotide replacement. However, polymorphism and divergence data show that this deletion bias is almost completely compensated by selection: Negative selection is stronger against deletions, whereas insertions are more likely to be favored by positive selection. Among the inframe low-frequency polymorphic mutations in exons, long introns, and intergenic regions, selection prevents a larger fraction of deletions (80-87%, depending on the type of the compartment) than of insertions (70-82%) or single-nucleotide substitutions (49-73%), from reaching high frequencies. The corresponding fractions were the lowest in short introns: 66%, 47%, and 15%, respectively, consistent with the weakest selective constraint in them. The McDonald-Kreitman test shows that 32-46% of the deletions and 60-73% of the insertions that were fixed in the recent evolution of D. melanogaster are adaptive, whereas this fraction is only 0-29% for single-nucleotide substitutions.
| S-EPMC3622295 | biostudies-literature
Project description:Assessing the compatibility between gene family phylogenies is a crucial and often computationally demanding step in many phylogenomic analyses. Here, we describe the Evolutionary Similarity Index (IES), a means to assess shared evolution between gene families using a weighted orthogonal distance regression model applied to sequence distances. The utilization of pairwise distance matrices circumvents comparisons between gene tree topologies, which are inherently uncertain and sensitive to evolutionary model choice, phylogenetic reconstruction artifacts, and other sources of error. Furthermore, IES enables the many-to-many pairing of multiple copies between similarly evolving gene families. This is done by selecting non-overlapping pairs of copies, one from each assessed family, and yielding the least sum of squared residuals. Analyses of simulated gene family data sets show that IES's accuracy is on par with popular tree-based methods while also less susceptible to noise introduced by sequence alignment and evolutionary model fitting. Applying IES to an empirical data set of 1,322 genes from 42 archaeal genomes identified eight major clusters of gene families with compatible evolutionary trends. The most cohesive cluster consisted of 62 genes with compatible evolutionary signal, which occur as both single-copy and multiple homologs per genome; phylogenetic analysis of concatenated alignments from this cluster produced a tree closely matching previously published species trees for Archaea. Four other clusters are mainly composed of accessory genes with limited distribution among Archaea and enriched toward specific metabolic functions. Pairwise evolutionary distances obtained from these accessory gene clusters suggest patterns of interphyla horizontal gene transfer. An IES implementation is available at https://github.com/lthiberiol/evolSimIndex.
| S-EPMC8483891 | biostudies-literature
Project description:An open question in human evolution is the importance of polygenic adaptation: adaptive changes in the mean of a multifactorial trait due to shifts in allele frequencies across many loci. In recent years, several methods have been developed to detect polygenic adaptation using loci identified in genome-wide association studies (GWAS). Though powerful, these methods suffer from limited interpretability: they can detect which sets of populations have evidence for polygenic adaptation, but are unable to reveal where in the history of multiple populations these processes occurred. To address this, we created a method to detect polygenic adaptation in an admixture graph, which is a representation of the historical divergences and admixture events relating different populations through time. We developed a Markov chain Monte Carlo (MCMC) algorithm to infer branch-specific parameters reflecting the strength of selection in each branch of a graph. Additionally, we developed a set of summary statistics that are fast to compute and can indicate which branches are most likely to have experienced polygenic adaptation. We show via simulations that this method-which we call PolyGraph-has good power to detect polygenic adaptation, and applied it to human population genomic data from around the world. We also provide evidence that variants associated with several traits, including height, educational attainment, and self-reported unibrow, have been influenced by polygenic adaptation in different populations during human evolution.
| S-EPMC5887149 | biostudies-literature
Project description:For over 50 years, the great tit (Parus major) has been a model species for research in evolutionary, ecological and behavioural research; in particular, learning and cognition have been intensively studied. Here, to provide further insight into the molecular mechanisms behind these important traits, we de novo assemble a great tit reference genome and whole-genome re-sequence another 29 individuals from across Europe. We show an overrepresentation of genes related to neuronal functions, learning and cognition in regions under positive selection, as well as increased CpG methylation in these regions. In addition, great tit neuronal non-CpG methylation patterns are very similar to those observed in mammals, suggesting a universal role in neuronal epigenetic regulation which can affect learning-, memory- and experience-induced plasticity. The high-quality great tit genome assembly will play an instrumental role in furthering the integration of ecological, evolutionary, behavioural and genomic approaches in this model species.
| S-EPMC4737754 | biostudies-literature
Project description:The regulatory mechanisms of determining which genes specifically expressed in which tissues are still not fully elucidated, especially in plants. Using internal correspondence analysis, I first establish that tissue-specific genes exhibit significantly different synonymous codon usage in rice, although this effect is weak. The variability of synonymous codon usage between tissues accounts for 5.62% of the total codon usage variability, which has mainly arisen from the neutral evolutionary forces, such as GC content variation among tissues. Moreover, tissue-specific genes are under differential selective constraints, inferring that natural selection also contributes to the codon usage divergence between tissues. These findings may add further evidence in understanding the differentiation and regulation of tissue-specific gene products in plants.
| S-EPMC3483185 | biostudies-literature
Project description:Functional effects of different mutations are known to combine to the total effect in highly nontrivial ways. For the trait under evolutionary selection ('fitness'), measured values over all possible combinations of a set of mutations yield a fitness landscape that determines which mutational states can be reached from a given initial genotype. Understanding the accessibility properties of fitness landscapes is conceptually important in answering questions about the predictability and repeatability of evolutionary adaptation. Here we theoretically investigate accessibility of the globally optimal state on a wide variety of model landscapes, including landscapes with tunable ruggedness as well as neutral 'holey' landscapes. We define a mutational pathway to be accessible if it contains the minimal number of mutations required to reach the target genotype, and if fitness increases in each mutational step. Under this definition accessibility is high, in the sense that at least one accessible pathway exists with a substantial probability that approaches unity as the dimensionality of the fitness landscape (set by the number of mutational loci) becomes large. At the same time the number of alternative accessible pathways grows without bounds. We test the model predictions against an empirical 8-locus fitness landscape obtained for the filamentous fungus Aspergillus niger. By analyzing subgraphs of the full landscape containing different subsets of mutations, we are able to probe the mutational distance scale in the empirical data. The predicted effect of high accessibility is supported by the empirical data and is very robust, which we argue reflects the generic topology of sequence spaces. Together with the restrictive assumptions that lie in our definition of accessibility, this implies that the globally optimal configuration should be accessible to genome wide evolution, but the repeatability of evolutionary trajectories is limited owing to the presence of a large number of alternative mutational pathways.
| S-EPMC3158036 | biostudies-other
Project description:BACKGROUND:In spite of extensive research on the effect of mutation and selection on codon usage, a general model of codon usage bias due to mutational bias has been lacking. Because most amino acids allow synonymous GC content changing substitutions in the third codon position, the overall GC bias of a genome or genomic region is highly correlated with GC3, a measure of third position GC content. For individual amino acids as well, G/C ending codons usage generally increases with increasing GC bias and decreases with increasing AT bias. Arginine and leucine, amino acids that allow GC-changing synonymous substitutions in the first and third codon positions, have codons which may be expected to show different usage patterns. PRINCIPAL FINDINGS:In analyzing codon usage bias in hundreds of prokaryotic and plant genomes and in human genes, we find that two G-ending codons, AGG (arginine) and TTG (leucine), unlike all other G/C-ending codons, show overall usage that decreases with increasing GC bias, contrary to the usual expectation that G/C-ending codon usage should increase with increasing genomic GC bias. Moreover, the usage of some codons appears nonlinear, even nonmonotone, as a function of GC bias. To explain these observations, we propose a continuous-time Markov chain model of GC-biased synonymous substitution. This model correctly predicts the qualitative usage patterns of all codons, including nonlinear codon usage in isoleucine, arginine and leucine. The model accounts for 72%, 64% and 52% of the observed variability of codon usage in prokaryotes, plants and human respectively. When codons are grouped based on common GC content, 87%, 80% and 68% of the variation in usage is explained for prokaryotes, plants and human respectively. CONCLUSIONS:The model clarifies the sometimes-counterintuitive effects that GC mutational bias can have on codon usage, quantifies the influence of GC mutational bias and provides a natural null model relative to which other influences on codon bias may be measured.
| S-EPMC2965080 | biostudies-literature