Identifying loci under positive selection in complex population histories.
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ABSTRACT:
SUBMITTER: Refoyo-Martinez A
PROVIDER: S-EPMC6724678 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Jeju Black cattle is one of the aboriginal Korean cattle breeds that has been isolated in Jeju island for a long time, while Yellow Hanwoo cattle has been extensively selected for beef production traits for the last several decades. Aiming to investigate broader patterns of selection, we genotyped 352 Yellow Hanwoo and 169 Jeju Black cattle using a customized 150 K bovine chip. Our composite selection signals' analysis to identify selection signatures (cross-population extended haplotype homozygosity [XP-EHH], ΔSAF, and F ST) identified recent and strong signature of selection near many loci with mutations affecting the traits under strong selection as outlier in Yellow Hanwoo, including SCP2 (P = 8.41 × 10-10) that may be involved in the meat quality. We found nine candidate regions with significant clusters of selection signals, and further bioinformatics analyses of the genes located within these regions revealed mainly genes involved in G-protein coupled receptor signaling pathway (GO:0007186) or olfactory transduction (bta04740), which may be due to adaptation to natural environments in Jeju island. Based on the stronger correlation of Ne10/Ne100 ratio between Yellow Hanwoo (0.61) and Jeju Black (0.66) cattle, our results suggest that the difference of chromosomal regions of selection signature between the 2 cattle breeds was due to a consequence of selection processes to adapt to environmental differences between Jeju island and the main inland, Korean peninsula.
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Project description:Adaptive genetic variation is a function of both selective and neutral forces. To accurately identify adaptive loci, it is thus critical to account for demographic history. Theory suggests that signatures of selection can be inferred using the coalescent, following the premise that genealogies of selected loci deviate from neutral expectations. Here, we build on this theory to develop an analytical framework to identify loci under selection via explicit demographic models (LSD). Under this framework, signatures of selection are inferred through deviations in demographic parameters, rather than through summary statistics directly, and demographic history is accounted for explicitly. Leveraging the property of demographic models to incorporate directionality, we show that LSD can provide information on the environment in which selection acts on a population. This can prove useful in elucidating the selective processes underlying local adaptation, by characterizing genetic trade-offs and extending the concepts of antagonistic pleiotropy and conditional neutrality from ecological theory to practical application in genomic data. We implement LSD via approximate Bayesian computation and demonstrate, via simulations, that LSD (a) has high power to identify selected loci across a large range of demographic-selection regimes, (b) outperforms commonly applied genome-scan methods under complex demographies and (c) accurately infers the directionality of selection for identified candidates. Using the same simulations, we further characterize the behaviour of isolation-with-migration models conducive to the study of local adaptation under regimes of selection. Finally, we demonstrate an application of LSD by detecting loci and characterizing genetic trade-offs underlying flower colour in Antirrhinum majus.
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Project description:When divergence occurs in the presence of gene flow, there can arise an interesting dynamic in which selection against gene flow, at sites associated with population-specific adaptations or genetic incompatibilities, can cause net gene flow to vary across the genome. Loci linked to sites under selection may experience reduced gene flow and may experience genetic bottlenecks by the action of nearby selective sweeps. Data from histories such as these may be poorly fitted by conventional neutral model approaches to demographic inference, which treat all loci as equally subject to forces of genetic drift and gene flow. To allow for demographic inference in the face of such histories, as well as the identification of loci affected by selection, we developed an isolation-with-migration model that explicitly provides for variation among genomic regions in migration rates and/or rates of genetic drift. The method allows for loci to fall into any of multiple groups, each characterized by a different set of parameters, thus relaxing the assumption that all loci share the same demography. By grouping loci, the method can be applied to data with multiple loci and still have tractable dimensionality and statistical power. We studied the performance of the method using simulated data, and we applied the method to study the divergence of two subspecies of European rabbits (Oryctolagus cuniculus).
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Project description:India is home to a large and diverse buffalo population. The Murrah breed of North India is known for its milk production, and it has been used in breeding programs in several countries. Selection signature analysis yield valuable information about how the natural and artificial selective pressures have shaped the genomic landscape of modern-day livestock species. Genotype information was generated on six buffalo breeds of India, namely, Murrah, Bhadawari, Mehsana, Pandharpuri, Surti, and Toda using ddRAD sequencing protocol. Initially, the genotypes were used to carry out population diversity and structure analysis among the six breeds, followed by pair-wise comparisons of Murrah with the other five breeds through XP-EHH and F ST methodologies to identify regions under selection in Murrah. Admixture results showed significant levels of Murrah inheritance in all the breeds except Pandharpuri. The selection signature analysis revealed six regions in Murrah, which were identified in more than one pair-wise comparison through both XP-EHH and F ST analyses. The significant regions overlapped with QTLs for milk production, immunity, and body development traits. Genes present in these regions included SLC37A1, PDE9A, PPBP, CXCL6, RASSF6, AFM, AFP, ALB, ANKRD17, CNTNAP2, GPC5, MYLK3, and GPT2. These genes emerged as candidates for future polymorphism studies of adaptability and performance traits in buffaloes. The results also suggested ddRAD sequencing as a useful cost-effective alternative for whole-genome sequencing to carry out diversity analysis and discover selection signatures in Indian buffalo breeds.
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Project description:Bacterial CRISPR-Cas systems provide insight into recent population history because they rapidly incorporate, in a unidirectional manner, short fragments (spacers) from coexisting infective virus populations into host chromosomes. Immunity is achieved by sequence identity between transcripts of spacers and their targets. Here, we used metagenomics to study the stability and dynamics of the type I-E CRISPR-Cas locus of Leptospirillum group II bacteria in biofilms sampled over 5 years from an acid mine drainage (AMD) system. Despite recovery of 452,686 spacers from CRISPR amplicons and metagenomic data, rarefaction curves of spacers show no saturation. The vast repertoire of spacers is attributed to phage/plasmid population diversity and retention of old spacers, despite rapid evolution of the targeted phage/plasmid genome regions (proto-spacers). The oldest spacers (spacers found at the trailer end) are conserved for at least 5 years, and 12% of these retain perfect or near-perfect matches to proto-spacer targets. The majority of proto-spacer regions contain an AAG proto-spacer adjacent motif (PAM). Spacers throughout the locus target the same phage population (AMDV1), but there are blocks of consecutive spacers without AMDV1 target sequences. Results suggest long-term coexistence of Leptospirillum with AMDV1 and periods when AMDV1 was less dominant. Metagenomics can be applied to millions of cells in a single sample to provide an extremely large spacer inventory, allow identification of phage/plasmids and enable analysis of previous phage/plasmid exposure. Thus, this approach can provide insights into prior bacterial environment and genetic interplay between hosts and their viruses.
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Project description:As the methodologies available for the detection of positive selection from genomic data vary in terms of assumptions and execution, weak correlations are expected among them. However, if there is any given signal that is consistently supported across different methodologies, it is strong evidence that the locus has been under past selection. In this paper, a straightforward frequentist approach based on the Stouffer Method to combine P-values across different tests for evidence of recent positive selection in common variations, as well as strategies for extracting biological information from the detected signals, were described and applied to high density single nucleotide polymorphism (SNP) data generated from dairy and beef cattle (taurine and indicine). The ancestral Bovinae allele state of over 440,000 SNP is also reported. Using this combination of methods, highly significant (P<3.17×10(-7)) population-specific sweeps pointing out to candidate genes and pathways that may be involved in beef and dairy production were identified. The most significant signal was found in the Cornichon homolog 3 gene (CNIH3) in Brown Swiss (P = 3.82×10(-12)), and may be involved in the regulation of pre-ovulatory luteinizing hormone surge. Other putative pathways under selection are the glucolysis/gluconeogenesis, transcription machinery and chemokine/cytokine activity in Angus; calpain-calpastatin system and ribosome biogenesis in Brown Swiss; and gangliosides deposition in milk fat globules in Gyr. The composite method, combined with the strategies applied to retrieve functional information, may be a useful tool for surveying genome-wide selective sweeps and providing insights in to the source of selection.
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Project description:Most marine fish species express life-history changes across temperature gradients, such as faster growth, earlier maturation, and higher mortality at higher temperature. However, such climate-driven effects on life histories and population dynamics remain unassessed for most fishes. For 332 Indo-Pacific fishes, we show positive effects of temperature on body growth (but with decreasing asymptotic length), reproductive rates (including earlier age-at-maturation), and natural mortality for all species, with the effect strength varying among habitat-related species groups. Reef and demersal fishes are more sensitive to temperature changes than pelagic and bathydemersal fishes. Using a life table, we show that the combined changes of life histories upon increasing temperature tend to facilitate population growth for slow life-history populations, but reduce it for fast life-history ones. Within our data, lower proportions (25-30%) of slow life-history fishes but greater proportions of fast life-history fishes (42-60%) show declined population growth rates under 1 °C warming. Together, these findings suggest prioritizing sustainable management for fast life-history species.
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Project description:An excess of nonsynonymous over synonymous substitution at individual amino acid sites is an important indicator that positive selection has affected the evolution of a protein between the extant sequences under study and their most recent common ancestor. Several methods exist to detect the presence, and sometimes location, of positively selected sites in alignments of protein-coding sequences. This article describes the "sitewise likelihood-ratio" (SLR) method for detecting nonneutral evolution, a statistical test that can identify sites that are unusually conserved as well as those that are unusually variable. We show that the SLR method can be more powerful than currently published methods for detecting the location of positive selection, especially in difficult cases where the strength of selection is low. The increase in power is achieved while relaxing assumptions about how the strength of selection varies over sites and without elevated rates of false-positive results that have been reported with some other methods. We also show that the SLR method performs well even under circumstances where the results from some previous methods can be misleading.
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Project description:We used a comparative genomics approach to identify genes that are under positive selection in six strains of Escherichia coli and Shigella flexneri, including five strains that are human pathogens. We find that positive selection targets a wide range of different functions in the E. coli genome, including cell surface proteins such as beta barrel porins, presumably because of the involvement of these genes in evolutionary arms races with other bacteria, phages, and/or the host immune system. Structural mapping of positively selected sites on trans-membrane beta barrel porins reveals that the residues under positive selection occur almost exclusively in the extracellular region of the proteins that are enriched with sites known to be targets of phages, colicins, or the host immune system. More surprisingly, we also find a number of other categories of genes that show very strong evidence for positive selection, such as the enigmatic rhs elements and transposases. Based on structural evidence, we hypothesize that the selection acting on transposases is related to the genomic conflict between transposable elements and the host genome.
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Project description:Advances in genomic sequencing have enormous potential to revolutionize personalized medicine, however distinguishing disease-causing from benign variants remains a challenge. The increasing number of human genome and exome sequences available has revealed areas where unfavourable variation is removed through purifying selection. Here, we present the MTR-Viewer, a web-server enabling easy visualization at the gene or variant level of the Missense Tolerance Ratio (MTR), a measure of regional intolerance to missense variation calculated using variation from 240 000 exome and genome sequences. The MTR-Viewer enables exploration of MTR calculations, using different sliding windows, for over 18 000 human protein-coding genes and 85 000 alternative transcripts. Users can also view MTR scores calculated for specific ethnicities, to enable easy exploration of regions that may be under different selective pressure. The spatial distribution of population and known disease variants is also displayed on the protein's domain structure. Intolerant regions were found to be highly enriched for ClinVar pathogenic and COSMIC somatic missense variants (Mann-Whitney U test P < 2.2 × 10-16). As the MTR is not biased by known domains and protein features, it can highlight functionally important regions within genes overlooked or inaccessible by traditional methods. MTR-Viewer is freely available via a user friendly web-server at http://biosig.unimelb.edu.au/mtr-viewer/.
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