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266 results for “selection analysis”
Selecting a window size for the analysis of whole genome alignments using AIC
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Selection pressure analysis of dengue virus complete genome and E gene nucleotide sequences from Pakistan
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Social selection analysis reveals limited effect of neighbors’ traits in Tree swallows
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Beyond mutations: accounting for selection and self-organization in the analysis of protein evolution
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Why the long teeth? Morphometric analysis suggests different selective pressures on functional occlusal traits in Plio-Pleistocene African suids
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Identification and selection of optimal reference genes for qPCR-based gene expression analysis in Fucus distichus under various abiotic stresses
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Arabidopsis BioCON evolutionary study:Arabidopsis thaliana, Bromus inermis phenotypic selection analysis
We know a lot about the potential ecological effects of increasing concentrations to atmospheric CO2; however, we know relatively little about whether increased concentrations will also affect evolution. In collaboration with Jennifer Lau (KBS and Michigan State University), Peter Reich (U of MN Forestry) and Ruth Shaw (U of MN EEB) we are using a combination traditional quantitative genetic and QTL approaches to determine the effect elevated CO2 has on; patterns of selection, responses to selection, and the genetic basis of phenotypic variation.
Data from: A framework for the integrated analysis of the magnitude, selectivity, and biotic effects of extinction and origination
The taxonomic and ecologic composition of Earth's biota has shifted dramatically through geologic time, with some clades going extinct while others diversified. Here, we derive a metric that quantifies the change in biotic composition due to extinction or origination and show that it equals the product of extinction/origination magnitude and selectivity (variation in magnitude among groups). We also define metrics that describe the extent to which a recovery (1) reinforced or reversed the effects of extinction on biotic composition and (2) changed composition in ways uncorrelated with the extinction. To demonstrate the approach, we analyzed an updated compilation of stratigraphic ranges of marine animal genera. We show that mass extinctions were not more selective than background intervals at the phylum level; rather, they tended to drive greater taxonomic change due to their higher magnitudes. Mass extinctions did not represent a separate class of events with respect to either strength of selectivity or effect. Similar observations apply to origination during recoveries from mass extinctions, and on average, extinction and origination were similarly selective and drove similar amounts of biotic change. Elevated origination during recoveries drove bursts of compositional change that varied considerably in effect. In some cases, origination partially reversed the effects of extinction, returning the biota towards the pre-extinction composition; in others, it reinforced the effects of the extinction, magnifying biotic change. Recoveries were as important as extinction events in shaping the marine biota, and their selectivity deserves systematic study alongside that of extinction.
Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis
<p>Native cattle breeds can carry specific signatures of selection reflecting their adaptation to the local environmental conditions and response to the breeding strategy used. In this study, we comprehensively analysed high-density single nucleotide polymorphism (SNP) genotypes to characterise the population structure and detect the selection signatures in Russian native Yaroslavl and Kholmogor dairy cattle breeds, which have been little influenced by introgression with transboundary breeds. Fifty-six samples of pedigree-recorded purebred animals, originating from different breeding farms and representing different sire lines, of the two studied breeds were genotyped using a genome-wide bovine genotyping array (Bovine HD BeadChip). Three statistical analyses—calculation of fixation index (<i>F</i><sub>ST</sub>) for each SNP for the comparison of the pairs of breeds, hapFLK analysis, and estimation of the runs of homozygosity (ROH) islands shared in more than 50% of animals—were combined for detecting the selection signatures in the genome of the studied cattle breeds. We confirmed nine and six known regions under putative selection in the genomes of Yaroslavl and Kholmogor cattle, respectively; the flanking positions of most of these regions were elucidated. Only two of the selected regions (localised on BTA 14 at 24.4–25.1 Mbp and on BTA 16 at 42.5–43.5 Mb) overlapped in Yaroslavl, Kholmogor and Holstein breeds. In addition, we detected three novel selection sweeps in the genome of Yaroslavl (BTA 4 at 4.74–5.36 Mbp, BTA 15 at 17.80–18.77 Mbp, and BTA 17 at 45.59–45.61 Mbp) and Kholmogor breeds (BTA 12 at 82.40–81.69 Mbp, BTA 15 at 16.04–16.62 Mbp, and BTA 18 at 0.19–1.46 Mbp) by using at least two of the above-mentioned methods. We expanded the list of candidate genes associated with the selected genomic regions and performed their functional annotation. We discussed the possible involvement of the identified candidate genes in artificial selection in connection with the origin and development of the breeds. Our findings on the Yaroslavl and Kholmogor breeds obtained using high-density SNP genotyping and three different statistical methods allowed the detection of novel putative genomic regions and candidate genes that might be under selection. These results might be useful for the sustainable development and conservation of these two oldest Russian native cattle breeds.</p>
Wang et al Narrow-leafed lupin selective sweep analysis results
<p>Narrow-leafed lupin selective sweep analysis results, supplementary datasets. </p>
Data from: Microevolution in time and space: SNP analysis of historical DNA reveals dynamic signatures of selection in Atlantic cod
Little is known about how quickly natural populations adapt to changes in their environment and how temporal and spatial variation in selection pressures interact to shape patterns of genetic diversity. We here address these issues with a series of genome scans in four overfished populations of Atlantic cod (Gadus morhua) studied over an 80-year period. Screening of >1000 gene-associated single-nucleotide polymorphisms (SNPs) identified 77 loci that showed highly elevated levels of differentiation, likely as an effect of directional selection, in either time, space or both. Exploratory analysis suggested that temporal allele frequency shifts at certain loci may correlate with local temperature variation and with life history changes suggested to be fisheries induced. Interestingly, however, largely nonoverlapping sets of loci were temporal outliers in the different populations and outliers from the 1928 to 1960 period showed almost complete stability during later decades. The contrasting microevolutionary trajectories among populations resulted in sequential shifts in spatial outliers, with no locus maintaining elevated spatial differentiation throughout the study period. Simulations of migration coupled with observations of temporally stable spatial structure at neutral loci suggest that population replacement or gene flow alone could not explain all the observed allele frequency variation. Thus, the genetic changes are likely to at least partly be driven by highly dynamic temporally and spatially varying selection. These findings have important implications for our understanding of local adaptation and evolutionary potential in high gene flow organisms and underscore the need to carefully consider all dimensions of biocomplexity for evolutionarily sustainable management.
Data from: Patterns of MHC-dependent mate selection in humans and non-human primates: a meta-analysis
Genes of the major histocompatibility complex (MHC) in vertebrates are integral for effective adaptive immune response and are associated with sexual selection. Evidence from a range of vertebrates supports MHC-based preference for diverse and dissimilar mating partners, but evidence from human mate choice studies has been disparate and controversial. Methodologies and sampling peculiarities specific to human studies make it difficult to know whether wide discrepancies in results among human populations are real or artefact. To better understand what processes may affect MHC-mediated mate choice across humans and nonhuman primates, we performed phylogenetically controlled meta-analyses using 58 effect sizes from 30 studies across seven primate species. Primates showed a general trend favouring more MHC-diverse mates, which was statistically significant for humans. In contrast, there was no tendency for MHC-dissimilar mate choice, and for humans, we observed effect sizes indicating selection of both MHC-dissimilar and MHC-similar mates. Focusing on MHC-similar effect sizes only, we found evidence that preference for MHC similarity was an artefact of population ethnic heterogeneity in observational studies but not among experimental studies with more control over sociocultural biases. This suggests that human assortative mating biases may be responsible for some patterns of MHC-based mate choice. Additionally, the overall effect sizes of primate MHC-based mating preferences are relatively weak (Fisher's Z correlation coefficient for dissimilarity Zr = 0.044, diversity Zr = 0.153), calling for careful sampling design in future studies. Overall, our results indicate that preference for more MHC-diverse mates is significant for humans and likely conserved across primates.
Data from: Identifying signatures of sexual selection using genomewide selection components analysis
Sexual selection must affect the genome for it to have an evolutionary impact, yet signatures of selection remain elusive. Here we use an individual-based model to investigate the utility of genome-wide selection components analysis, which compares allele frequencies of individuals at different life history stages within a single population to detect selection without requiring a priori knowledge of traits under selection. We modeled a diploid, sexually reproducing population and introduced strong mate choice on a quantitative trait to simulate sexual selection. Genome-wide allele frequencies in adults and offspring were compared using weighted FST values. The average number of outlier peaks (i.e., those with significantly large FST values) with a quantitative trait locus in close proximity ("real" peaks) represented correct diagnoses of loci under selection, whereas peaks above the FST significance threshold without a quantitative trait locus reflected spurious peaks. We found that, even with moderate sample sizes, signatures of strong sexual selection were detectable, but larger sample sizes improved detection rates. The model was better able to detect selection with more neutral markers, and when quantitative trait loci and neutral markers were distributed across multiple chromosomes. Although environmental variation decreased detection rates, the identification of real peaks nevertheless remained feasible. We also found that detection rates can be improved by sampling multiple populations experiencing similar selection regimes. In short, genome-wide selection components analysis is a challenging but feasible approach for the identification of regions of the genome under selection.
Data from: Detecting genomic signatures of natural selection with principal component analysis: application to the 1000 Genomes data
To characterize natural selection, various analytical methods for detecting candidate genomic regions have been developed. We propose to perform genome-wide scans of natural selection using principal component analysis (PCA). We show that the common FST index of genetic differentiation between populations can be viewed as the proportion of variance explained by the principal components. Considering the correlations between genetic variants and each principal component provides a conceptual framework to detect genetic variants involved in local adaptation without any prior definition of populations. To validate the PCA-based approach, we consider the 1000 Genomes data (phase 1) considering 850 individuals coming from Africa, Asia, and Europe. The number of genetic variants is of the order of 36 millions obtained with a low-coverage sequencing depth (3×). The correlations between genetic variation and each principal component provide well-known targets for positive selection (EDAR, SLC24A5, SLC45A2, DARC), and also new candidate genes (APPBPP2, TP1A1, RTTN, KCNMA, MYO5C) and noncoding RNAs. In addition to identifying genes involved in biological adaptation, we identify two biological pathways involved in polygenic adaptation that are related to the innate immune system (beta defensins) and to lipid metabolism (fatty acid omega oxidation). An additional analysis of European data shows that a genome scan based on PCA retrieves classical examples of local adaptation even when there are no well-defined populations. PCA-based statistics, implemented in the PCAdapt R package and the PCAdapt fast open-source software, retrieve well-known signals of human adaptation, which is encouraging for future whole-genome sequencing project, especially when defining populations is difficult.
Data from: Signatures of selection in the Iberian honey bee (Apis mellifera iberiensis) revealed by a genome scan analysis of single nucleotide polymorphisms
Understanding the genetic mechanisms of adaptive population divergence is one of the most fundamental endeavours in evolutionary biology and is becoming increasingly important as it will allow predictions about how organisms will respond to global environmental crisis. This is particularly important for the honey bee, a species of unquestionable ecological and economical importance that has been exposed to increasing human-mediated selection pressures. Here, we conducted a single nucleotide polymorphism (SNP)-based genome scan in honey bees collected across an environmental gradient in Iberia and used four FST-based outlier tests to identify genomic regions exhibiting signatures of selection. Additionally, we analysed associations between genetic and environmental data for the identification of factors that might be correlated or act as selective pressures. With these approaches, 4.4% (17 of 383) of outlier loci were cross-validated by four FST-based methods, and 8.9% (34 of 383) were cross-validated by at least three methods. Of the 34 outliers, 15 were found to be strongly associated with one or more environmental variables. Further support for selection, provided by functional genomic information, was particularly compelling for SNP outliers mapped to different genes putatively involved in the same function such as vision, xenobiotic detoxification and innate immune response. This study enabled a more rigorous consideration of selection as the underlying cause of diversity patterns in Iberian honey bees, representing an important first step towards the identification of polymorphisms implicated in local adaptation and possibly in response to recent human-mediated environmental changes.
Spatial point pattern analysis of traces (SPPAT): an approach for visualizing and quantifying site-selectivity patterns of drilling predators
<p>Site-selectivity analysis in drilling predation may provide useful behavioral information of a predator interacting with its prey. However, traditional approaches exclude some spatial information (i.e., oversimplified trace position) and are dependent on the scale of analysis (e.g., arbitrary grid system used to divide the prey skeleton into sectors). Here we introduce the spatial point pattern analysis of traces (<i>SPPAT</i>), an approach for visualizing and quantifying the distribution of traces on shelled invertebrate prey, which includes improved collection of spatial information inherent to drillhole location (morphometric-based estimation), improved visualization of spatial trends (Kernel density and hotspot mapping), and distance-based statistics for hypothesis testing (<i>K</i>-, <i>L</i>-, and pair correlation functions). We illustrate the <i>SPPAT</i> approach through case studies of fossil samples, modern beach-collected samples, and laboratory feeding trials of naticid gastropod predation on bivalve prey. Overall results show that Kernel density and hotspot maps enable visualization of subtle variations in regions of the shell with higher density of predation traces, which can be combined with the maximum clustering distance metric to generate hypotheses on predatory behavior and anti-predatory responses of prey across time and geographic space. Distance-based statistics also capture the major features in the distribution of traces across the prey skeleton, including aggregated and segregated clusters, likely associated with different combinations of two modes of drilling predation, edge- and wall-drilling. The <i>SPPAT </i>approach is transferrable to other paleoecologic and taphonomic data such as encrustation and bioerosion, allowing for standardized investigation of a wide range of biotic interactions.</p>
Data from: Genome-wide analysis of colonization history and concomitant selection in Arabidopsis lyrata
The high climatic variability in the past hundred thousand years has affected the demographic and adaptive processes in many species, especially in boreal and temperate regions undergoing glacial cycles. This has also influenced the patterns of genome-wide nucleotide variation, but the details of these effects are largely unknown. Here we study the patterns of genome-wide variation to infer colonization history and patterns of selection of the perennial herb species Arabidopsis lyrata, in locally adapted populations from different parts of its distribution range (Germany, UK, Norway, Sweden, and USA) representing different environmental conditions. Using site frequency spectra based demographic modelling we found strong reduction in the effective population size of the species in general within the past 100 000 years, with more pronounced effects in the colonizing populations. We further found that the northwestern European A. lyrata populations (UK and Scandinavian) are more closely related to each other than with the Central European populations, and coalescent based population split modelling suggests that western European and Scandinavian populations became isolated relatively recently after the glacial retreat. We also highlighted loci showing evidence for local selection associated with the Scandinavian colonization. The results presented here give new insights into post-glacial Scandinavian colonization history and its genome-wide effects.
Systematic review and meta-analysis of the occurrence of Listeria monocytogenes in fresh produce in selected developing countries
<p>This dataset contain the supplementary data for "<a><span>Sy</span></a><span><span></span></span><span>stematic review and meta-analysis of the occurrence of <em>Listeria monocytogenes</em> in fresh produce in selected developing countries"</span></p>
Data for behavioral state-dependent habitat selection analysis of translocated female greater sage-grouse, North Dakota 2018-2020
<p>This dataset is associated with the article, "Behavioral state-dependent habitat selection and implications for animal translocations" (Picardi et al., 2021, Journal of Applied Ecology).</p> <p>Post-release monitoring of translocated animals can be used to inform future translocation protocols. In particular, quantifying habitat selection of translocated individuals may help identify features that characterize suitable settlement habitat and inform the choice of future release sites; however, because translocated animals undergo post-release behavioral modification, the underlying behavioral state needs to be taken into account.</p> <p>We analyzed behavioral state-dependent habitat selection in female greater sage-grouse (<i>Centrocercus urophasianus</i>) translocated from Wyoming to North Dakota, USA, using Hidden Markov Models in combination with Integrated Step Selection Analysis. This dataset includes GPS tracks (resampled at a 6-hour resolution using a Continuous Time Movement Model) for 48 individuals translocated between 2018 and 2020, along with environmental variables associated with each location. We segmented each track into behavioral phases corresponding to an exploratory state, characterized by broad and directed movements, and a restricted state, characterized by short and tortuous movements. Then, we quantified habitat selection in each state while also accounting for seasonality and individual reproductive status.</p> <p>Habitat selection of translocated sage-grouse differed between the post-release exploration and the settlement phase. While in the exploratory state, sage-grouse exhibited natal habitat preference induction by selecting for high sagebrush cover, typical of their natal area but not of the release area. In the restricted state, sage-grouse selected for gentle topography and also adjusted their habitat selection based on the season and their reproductive needs.</p>
Characteristics of studies selected for the meta-analysis
<p>Characteristics of studies selected for the meta-analysis</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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