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74 results for “genome scan”
Data and Code for "Cell Type-specific Genome Scans of DNA Methylation Diversity Indicate an Important Role for Transposable Elements"
<p>This is a release of the gitlab repository "meta-methylome" (https://gitlab.com/okartal/meta-methylome.git) that, in addition to the code, also contains the resulting genomic data.</p> <p>Extract the directory on the command line using</p> <pre><code class="language-bash">$ tar -xhzvf meta-methylome.tar.gz</code></pre> <p>to preserve the symbolic links.</p>
Data for: Bivariate Genome-Wide Association Scan Identifies 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease.
<p>Summary of Bivariate GWAS scan results reported in:<br> <a href="https://pubmed.ncbi.nlm.nih.gov/30525989/">Bivariate Genome-Wide Association Scan Identifies 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease. </a>Siewert KM, Voight BF. Circ Genom Precis Med. 2018 Dec;11(12):e002239. doi: 10.1161/CIRCGEN.118.002239.</p> <p>PMID: 30525989 </p>
Genome wide scan of Orthomam for associations to several phenotypes
<p>Scan results of the Orthomam database using Pelican, including predictions at the level of sites and their aggregation at the level of genes.</p> <p>Annotation of the Orthomam phylogeny is provided for each phenotype under consideration :</p> <ul> <li>echolocation</li> <li>diurnality/nocturnality</li> <li>aquatic environment</li> <li>marine environment</li> <li>subterranean environment</li> <li>vocal learning</li> <li>domestication</li> <li>diet (herbivore/carnivore/omnivore)</li> </ul>
Data from: Genome-wide scans reveal selection signatures and cross-population variation in South African and European beef cattle breeds
<p>In genetics and evolutionary biology, the concept of selection signatures is used to describe specific patterns in the genome that are associated with the process of natural selection. These selection signatures provide insights into how evolutionary forces have shaped a population over time.In this study, a total of 96 samples were collected in several farms from four different cattle breeds, namely South African indigenous Nguni (n = 28) and Bonsmara (n = 21), Scottish Angus (n = 22), and Swedish Simmental (n = 25). Genotyped samples were subjected to quality control, and a total of 105,675 SNPs from 78 individuals remained for further analysis. Genomic signatures of positive selection within each breed were identified using the Integrated Haplotype Score (iHS) method, and cross-population comparison analysis using cross-population extended haplotype homozygosity ( XP-EHH), relative extended haplotype homozygosity (Rsb), and fixation index (Fst) methods, to assess the genetic differences between breeds. The results from the iHS method revealed selection signatures in two genomic regions for Bonsmara, six for Simmental, four for Nguni, and one for Angus cattle. Ten regions were found to be under selection, with BTA 12 being shared between Nguni and Bonsmara. Comparisons across populations using Rsb, and Fst methods performed better and revealed the most specific genomic regions that varied in selection between breeds. Gene annotation analyses linked candidate genes to several Quantitative Trait Loci (QTL). For example, in Simmental cattle's FAM110B gene was linked to carcass weight and body confirmation score. Bonsmara showed fewer candidate genes, such as CDK8 and FLT1, whereas Angus had none on BTA 18. Nguni identified potential genes such as CRB1, PLAG2GA, and VASH2, with CDK8 shared by Bonsmara and Nguni on BTA 12. Further cross-population studies revealed candidate genes associated with certain traits, genes including as PLCXD3, FAM149B1, and GRIK2 for Bonsmara versus Nguni, and SLIT2 and TSPAN9 for Simmental vs Angus. The study also emphasised gene related to meat quality, reproduction, health, illnesses, fertility, and body conformation score. Gene interaction study with the STRING database revealed a network of 63 candidate genes, demonstrating the structure of genetic connections, some biological processes. The study found that iHS performed well in population analysis with Nguni cattle, having exhibited the highest number of signatures across the genome, and significant signatures were also seen in comparisons between Nguni and Bonsmara using the Fst and Rsb methods. Furthermore, the study discovered that a bigger number of genes were connected with various traits, including sperm count and insemination per conception, sensitivity to bovine respiratory disease, and ease of calving. This genomic analysis underlined the relevance of the genetic relying which distinguishes distinct breeds. This understanding has the potential to significantly enhance selective breeding and increase desirable traits in cattle herds. This genomic analysis underlined the significance of the genetic basis for breed-specific traits. This understanding has the potential to drastically improve selective breeding and increase desirable traits in cattle herds.</p>
FIGURE 2 in Scanning Electron Microscopy Vouchers And Genomic Data From An Individual Specimen: Maximizing The Utility Of Delicate And Rare Specimens
FIGURE 2: Image of agarose gel showing bright bands representing positive amplification of COI. A – Erythraeus sp; B – Trichosmaris sp; C – Raoiella indica; - negative control.
FIGURE 3 in Scanning Electron Microscopy Vouchers And Genomic Data From An Individual Specimen: Maximizing The Utility Of Delicate And Rare Specimens
FIGURE 3: Images (40X) of slide mounted Raoiella indica specimen (dorsal view on left, ventral view on right) after LTSEM imaging, DNA extraction, and KOH soak.
Data from: Genome-wide scans reveal selection signatures and cross-population variation in South African and European beef cattle breeds
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Data from: VolcanoFinder: genomic scans for adaptive introgression
<p>Recent research shows that introgression between closely-related species is an important source of adaptive alleles for a wide range of taxa. Typically, detection of adaptive introgression from genomic data relies on comparative analyses that require sequence data from both the recipient and the donor species. However, in many cases, the donor is unknown or the data is not currently available. Here, we introduce a genome-scan method---VolcanoFinder---to detect recent events of adaptive introgression using polymorphism data from the recipient species only. VolcanoFinder detects adaptive introgression sweeps from the pattern of excess intermediate-frequency polymorphism they produce in the flanking region of the genome, a pattern which appears as a volcano-shape in pairwise genetic diversity. Using coalescent theory, we derive analytical predictions for these patterns. Based on these results, we develop a composite-likelihood test to detect signatures of adaptive introgression relative to the genomic background. Simulation results show that VolcanoFinder has high statistical power to detect these signatures, even for older sweeps and for soft sweeps initiated by multiple migrant haplotypes. Finally, we implement VolcanoFinder to detect archaic introgression in European and sub-Saharan African human populations, and uncovered interesting candidates in both populations, such as TSHR in Europeans and TCHH-RPTN in Africans. We discuss their biological implications and provide guidelines for identifying and circumventing artifactual signals during empirical applications of VolcanoFinder.</p>
Data from: Genome scan identifies flowering-independent effects of barley HsDry2.2 locus on yield traits under water deficit
Increasing crop productivity under climate change requires the identification, selection and utilization of novel alleles for breeding. We analyzed the genotype and field phenotype of the barley HEB-25 multi-parent mapping population under well-watered and water-limited (WW and WL) environments for two years. A genome-wide association study (GWAS) for genotype by-environment interactions was performed for ten traits including flowering time (HEA) and plant grain yield (PGY). Comparison of the GWAS for traits per-se to that for QTL-by-environment interactions (QxE), indicates the prevalence of QxE mostly for reproductive traits. One QxE locus on chromosome 2, Hordeum spontaneum Dry2.2 (HsDry2.2), showed a positive and conditional effect on PGY and grain number (GN). The wild allele significantly reduced HEA, however this earliness was not conditioned by water deficit. Furthermore, BC2F1 lines segregating for the HsDry2.2 showed the wild allele confers an advantage over the cultivated in PGY, GN and harvest index as well as modified shoot morphology , longer grain filling period and reduced senescence (only under drought), therefore suggesting adaptation mechanism against water deficit other than escape. This study highlights the value of evaluating wild relatives in search of novel alleles and clues to resilience mechanism underlying crop adaptation to abiotic stress.
Data from: A genome scan for selection signatures comparing farmed Atlantic salmon with two wild populations: testing co-localization among outlier markers, candidate genes, and QTLs for production traits
Comparative genome scans can be used to identify chromosome regions, but not traits, that are putatively under selection. Identification of targeted traits may be more likely in recently domesticated populations under strong artificial selection for increased production. We used a North American Atlantic salmon 6K SNP dataset to locate genome regions of an aquaculture strain (Saint John River) that were highly diverged from that of its putative wild founder population (Tobique River). First, admixed individuals with partial European ancestry were detected using STRUCTURE and removed from the dataset. Outlier loci were then identified as those showing extreme differentiation between the aquaculture population and the founder population. All Arlequin methods identified an overlapping subset of 17 outlier loci, 3 of which were also identified by BayeScan. Many outlier loci were near candidate genes and some were near published quantitative trait loci (QTLs) for growth, appetite, maturity, or disease-resistance. Parallel comparisons using a wild, non-founder population (Stewiacke River) yielded only one overlapping outlier locus as well as a known maturity QTL. We conclude that genome scans comparing a recently domesticated strain with its wild founder population can facilitate identification of candidate genes for traits known to have been under strong artificial selection.
Data from: Composite measures of selection can improve the signal-to-noise ratio in genome scans
The growing wealth of genomic data is yielding new insights into the genetic basis of adaptation, but it also presents the challenge of extracting the relevant signal from multi-dimensional datasets. Different statistical approaches vary in their power to detect selection depending on the demographic history, type of selection, genetic architecture and experimental design. Here, we develop and evaluate new approaches for combining results from multiple tests, including multivariate distance measures and methods for combining P-values. We evaluate these methods on (i) simulated landscape genetic data analysed for differentiation outliers and genetic-environment associations and (ii) empirical genomic data analysed for selective sweeps within dog breeds for loci known to be selected for during domestication. We also introduce and evaluate how robust statistical algorithms can be used for parameter estimation in statistical genomics. On the simulated data, many of the composite measures performed well and had decreased variation in outcomes across many sampling designs. On the empirical dataset, methods based on combining P-values generally performed better with clearer signals of selection, higher significance of the signal, and in closer proximity to the known selected locus. Although robust algorithms could identify neutral loci in our simulations, they did not universally improve power to detect selection. Overall, a composite statistic that measured a robust multivariate distance from rank-based P-values performed the best. We found that composite measures of selection could improve the signal of selection in many cases, but they were not a panacea and their power is limited by the power of the univariate statistics they summarize. Since genome scans are widely used, improving inference for prioritizing candidate genes may be beneficial to medicine, agriculture, and breeding. Our results also have application to outlier detection in high-dimensional datasets and to combining results in meta-analyses in many disciplines. The compound measures we evaluate are implemented in the r package minotaur.
Data from: Genome-wide scans detect adaptation to aridity in a widespread forest tree species.
Patterns of adaptive variation within plant species are best studied through common garden experiments, but these are costly and time-consuming, especially for trees that have long generation times. We explored whether genome-wide scanning technology combined with outlier marker detection could be used to detect adaptation to climate and provide an alternative to common garden experiments. As a case study, we sampled nine provenances of the widespread forest tree species, Eucalyptus tricarpa, across an aridity gradient in southeastern Australia. Using a Bayesian analysis we identified a suite of 94 putatively adaptive (outlying) sequence-tagged markers across the genome. Population-level allele frequencies of these outlier markers were strongly correlated with temperature and moisture availability at the site of origin, and with population differences in functional traits measured in two common gardens. Using the output from a canonical analysis of principal coordinates we devised a metric that provides a holistic measure of genomic adaptation to aridity that could be used to guide assisted migration or genetic augmentation.
Data from: Selection and genomic differentiation during ecological speciation: isolating the contributions of host association via a comparative genome scan of Neochlamisus bebbianae leaf beetles
This study uses a comparative genome scan to evaluate the contributions of host plant related divergent selection to genetic differentiation and ecological speciation in maple- and willow-associated populations of Neochlamisus bebbianae leaf beetles. For each of 15 pairwise population comparisons, we identified "outlier loci" whose strong differentiation putatively reflects divergent selection. Of 447 AFLP loci, 15% were outliers across multiple population comparisons, and low linkage disequilibrium indicated that these outliers derived from multiple regions of the genome. Outliers were further classified as "host-specific" if repeatedly observed in "different-host" population comparisons but never in "same-host" comparisons. Outliers exhibiting the opposite pattern were analogously classified as "host-independent." Host-specific outliers represented 5% of all loci and were more frequent than host-independent outliers, thus revealing a large role for host-adaptation in population genomic differentiation. Evidence that host-related selection can promote divergence despite gene flow was provided by population trees. These were structured by host-association when datasets included host-specific outliers, but not when based on neutral loci, which united sympatric populations. Lastly, three host-specific outliers were highly differentiated in all nine different-host comparisons. Because host-adaptation promotes reproductive isolation in these beetles, these loci provide promising candidate gene regions for future molecular studies of ecological speciation.
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.
Data from: AFLP genome scans suggest divergent selection on colour patterning in allopatric colour morphs of a cichlid fish
Genome scan-based tests for selection are directly applicable to natural populations to study the genetic and evolutionary mechanisms behind phenotypic differentiation. We conducted AFLP genome scans in three distinct geographic colour morphs of the cichlid fish Tropheus moorii to assess whether the extant, allopatric colour pattern differentiation can be explained by drift and to identify markers mapping to genomic regions possibly involved in colour patterning. The tested morphs occupy adjacent shore sections in southern Lake Tanganyika and are separated from each other by major habitat barriers. The genome scans revealed significant genetic structure between morphs, but a very low proportion of loci fixed for alternative AFLP alleles in different morphs. This high level of polymorphism within morphs suggested that colour pattern differentiation did not result exclusively from neutral processes. Outlier detection methods identified six loci with excess differentiation in the comparison between a bluish and a yellow-blotch morph and five different outlier loci in comparisons of each of these morphs with a red morph. As population expansions and the genetic structure of Tropheus make the outlier approach prone to false-positive signals of selection, we examined the correlation between outlier locus alleles and colour phenotypes in a genetic and phenotypic cline between two morphs. Distributions of allele frequencies at one outlier locus were indeed consistent with linkage to a colour locus. Despite the challenges posed by population structure and demography, our results encourage the cautious application of genome scans to studies of divergent selection in subdivided and recently expanded populations.
Data from: Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation
Domestication and selective breeding has resulted in over 1000 extant cattle breeds. Many of these breeds do not excel in important traits but are adapted to local environments. These adaptations are a valuable source of genetic material for efforts to improve commercial breeds. As a step toward this goal we identified candidate regions to be under selection in genomes of nine Russian native cattle breeds adapted to survive in harsh climates. After comparing our data to other breeds of European and Asian origins we found known and novel candidate genes that could potentially be related to domestication, economically important traits and environmental adaptations in cattle. The Russian cattle breed genomes contained regions under putative selection with genes that may be related to adaptations to harsh environments (e.g., AQP5, RAD50, and RETREG1). We found genomic signatures of selective sweeps near key genes related to economically important traits, such as the milk production (e.g., DGAT1, ABCG2), growth (e.g., XKR4), and reproduction (e.g., CSF2). Our data point to candidate genes which should be included in future studies attempting to identify genes to improve the extant breeds and facilitate generation of commercial breeds that fit better into the environments of Russia and other countries with similar climates.
Data from: Effects of gene action, marker density, and time since selection on the performance of landscape genomic scans of local adaptation
Genomic "scans" to identify loci that contribute to local adaptation are becoming increasingly common. Many methods used for such studies have assumed that local adaptation is created by loci experiencing antagonistic pleiotropy and that the selected locus itself is assayed, and few consider how signals of selection change through time. However, most empirical data sets have marker density too low to assume that a selected locus itself is assayed, researchers seldom know when selection was first imposed, and many locally adapted loci likely experience not antagonistic pleiotropy but conditional neutrality. We simulated data to evaluate how these factors affect the performance of tests for genotype-environment association. We found that three types of regression-based analyses (linear models, mixed linear models, and latent factor mixed models) and an implementation of BayEnv all performed well, with high rates of true positives and low rates of false positives, when the selected locus experienced antagonistic pleiotropy, and when the selected locus was assayed directly. However, all tests had reduced power to detect loci experiencing conditional neutrality, and the probability of detecting associations was sharply reduced when physically linked rather than causative loci were sampled. Antagonistic pleiotropy also maintained detectable genotype-environment associations much longer than conditional neutrality. Our analyses suggest that if local adaptation is often driven by loci experiencing conditional neutrality, genome-scan methods will have limited capacity to find loci responsible for local adaptation.
A Genome-Wide Scan For Quantitative Trait Loci of Serum Bilirubin - A Framingham Study
ClinicalTrials.gov study NCT00340509. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Whole Genome Scan of Extended Families With Familial Vocal Cord Paralysis
ClinicalTrials.gov study NCT00382369. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Genomic scans reveal multiple mito‐nuclear incompatibilities in population crosses of the copepod Tigriopus californicus
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