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505 results for “genome-wide association”
Genome-wide association analysis identifies naturally segregating genetic variation associated with the rapid evolution of diapause in Aedes albopictus, an invasive vector mosquito.
<p>The raw data for genotype calls, the output files from the genotype calls, the code to replicate the analysis, and the output of the analysis.</p>
Genome-wide association study identifies 18 novel loci associated with left atrial volume and function
<p><strong>README</strong></p> <p>Publication: Genome-wide association study identifies 18 novel loci associated with left atrial volume and function</p> <p>Ahlberg and Andreasen et al.</p> <p>Published: 29 July 2021, doi: <a href="https://doi.org/10.1093/eurheartj/ehab466">https://doi.org/10.1093/eurheartj/ehab466</a></p> <p>summary statistics for LAmax: rntrn_ilamax.bgen.stats.betastd.tsv.gz <br> summary statistics for LAmin: rntrn_ilamin.bgen.stats.betastd.tsv.gz <br> summary statistics for LAAEF: rntrn_laaef.bgen.stats.betastd.tsv.gz <br> summary statistics for LAPEF: rntrn_lapef.bgen.stats.betastd.tsv.gz <br> summary statistics for LATEF: rntrn_latef.bgen.stats.betastd.tsv.gz </p> <p> </p> <p>Description:</p> <p>SNP: rs number or ID string<br> CHR: chromosome<br> BP: physical (base pair) position<br> GENPOS: genetic position either from bim file or interpolated from genetic map<br> ALLELE1: first allele in bim file (usually the minor allele), used as the effect allele<br> ALLELE0: second allele in bim file, used as the reference allele<br> A1FREQ: frequency of first allele<br> F_MISS: fraction of individuals with missing genotype at this SNP<br> BETA: effect size from BOLT-LMM approximation to infinitesimal mixed model<br> SE: standard error of effect size<br> P_BOLT_LMM_INF: infinitesimal mixed model association test p-value<br> P_BOLT_LMM: non-infinitesimal mixed model association test p-value<br> N: sample size <br> bstd: standardized effect size from BOLT-LMM <br> sestd: standardized standard error of effect size</p>
Data from: Genome-wide variation in DNA methylation is associated with stress resilience and plumage brightness in a wild bird
Individuals often differ in their ability to cope with challenging environmental and social conditions. Evidence from model systems suggests that patterns of DNA methylation are associated with variation in coping ability. These associations could arise directly if methylation plays a role in controlling the physiological response to stressors by, among other things, regulating the release of glucocorticoids in response to challenges. Alternatively, the association could arise indirectly if methylation and resilience have a common cause, such as early life conditions. In either case, methylation might act as a biomarker for coping ability. At present, however, relatively little is known about whether variation in methylation is associated with organismal performance and resilience under natural conditions. We studied genome-wide patterns of DNA methylation in free-living female tree swallows (Tachycineta bicolor) using methylated DNA immunoprecipitation (MeDIP) and a tree swallow genome that was assembled for this study. We identified areas of the genome that were differentially methylated with respect to social signal expression (breast brightness) and physiological traits (ability to terminate the glucocorticoid stress response through negative feedback). We also asked whether methylation predicted resilience to a subsequent experimentally imposed challenge. Individuals with brighter breast plumage and higher stress resilience had lower methylation at differentially methylated regions across the genome. Thus, widespread differences in methylation predicted both social signal expression and the response to future challenges under natural conditions. These results have implications for predicting individual differences in resilience, and for understanding the mechanistic basis of resilience and its environmental and social mediators.
Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle
<p>Fourier-transform mid-infrared (FT-MIR) spectroscopy provides a high-throughput and inexpensive method for predicting milk composition and other novel traits from milk samples. Whilst there have been many genome-wide association studies (GWAS) conducted on FT-MIR predicted traits, there have been few GWAS for individual FT-MIR wavenumbers. Here we examine associations between genomic regions and individual FT-MIR wavenumber phenotypes within a population of 38,085 mixed-breed New Zealand dairy cattle with imputed whole-genome sequence. GWAS were conducted for each of 895 individual FT-MIR wavenumber phenotypes and three FT-MIR predicted milk composition traits, and gene annotation and mammary tissue gene expression datasets were employed to identify candidate causative genes and variants. This resulted in the identification of 38 co-locating, co-segregating expression QTL (eQTL), and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the latter including a null mutation in <i>ABO</i> that has a potential role in changing milk oligosaccharide profiles. For the candidate causative genes implicated in these analyses, the strength of association between relevant loci and each wavenumber across the mid-infrared spectrum revealed shared association patterns for groups of genomically-distant loci, highlighting clusters of loci linked through their biological roles in lactation and their presumed impacts on the chemical composition of milk.</p>
Data from: Genome-wide association studies across environmental and genetic contexts reveal complex genetic architecture of symbiotic extended phenotypes
<p>A goal of modern biology is to develop the genotype-phenotype (G→P) map, a predictive understanding of how genomic information generates trait variation that forms the basis of both natural and managed communities. As microbiome research advances, however, it has become clear that many of these traits are symbiotic extended phenotypes, being governed by genetic variation encoded not only by the host's own genome, but also by the genomes of myriad cryptic symbionts. Building a reliable G→P map therefore requires accounting for the multitude of interacting genes and even genomes involved in symbiosis. Here we use naturally-occurring genetic variation in 191 strains of the model microbial symbiont <em>Sinorhizobium meliloti</em> paired with two genotypes of the host <em>Medicago truncatula</em> in four genome-wide association studies (GWAS) to determine the genomic architecture of a key symbiotic extended phenotype – partner quality, or the fitness benefit conferred to a host by a particular symbiont genotype, within and across environmental contexts and host genotypes. We define three novel categories of loci in rhizobium genomes that must be accounted for if we want to build a reliable G→P map of partner quality; namely, 1) loci whose identities depend on the environment, 2) those that depend on the host genotype with which rhizobia interact, and 3) universal loci that are likely important in all or most environments.</p> <p><span>IMPORTANCE:</span><strong> </strong>Given the rapid rise of research on how microbiomes can be harnessed to improve host health, understanding the contribution of microbial genetic variation to host phenotypic variation is pressing, and will better enable us to predict the evolution of (and select more precisely for) symbiotic extended phenotypes that impact host health. We uncover extensive context-dependency in both the identity and functions of symbiont loci that control host growth, which makes predicting the genes and pathways important for determining symbiotic outcomes under different conditions more challenging. Despite this context-dependency, we also resolve a core set of universal loci that are likely important in all or most environments, and thus, serve as excellent targets both for genetic engineering and future coevolutionary studies of symbiosis.</p>
Data: Genome-wide association study reveals white lupin candidate gene involved in anthracnose resistance
<p>White lupin (<em>Lupinus albus </em>L.) is a re-emerging protein crop and promising alternative to soybean. Its cultivation, however, is severely threatened by anthracnose disease caused by the fungal pathogen <em>Colletotrichum lupini</em>. To dissect the genetic architecture for anthracnose resistance, genotyping-by-sequencing (GBS) was performed on white lupin accessions collected from the center of domestication and traditional cultivation regions. GBS resulted in 4,611 high-quality single-nucleotide polymorphisms (SNPs) for 181 accessions, which were combined with resistance data observed under controlled conditions to perform a genome-wide association study (GWAS). Obtained disease phenotypes were shown to highly correlate to overall three-year disease assessments under Swiss field conditions (r > 0.8). GWAS results identified two significant SNPs associated with anthracnose resistance on gene <em>Lalb_Chr05_g0216161</em> encoding a RING zinc-finger E3 ubiquitin ligase which is potentially involved in plant immunity. Population analysis showed a remarkably fast linkage disequilibrium (LD) decay, weak population structure and grouping of commercial varieties with landraces, corresponding to the slow domestication history and scarcity of modern breeding efforts in white lupin. Together with 15 highly resistant accessions identified in the resistance assay, our findings show promise for further crop improvement. This study provides the basis for marker-assisted selection, genomic prediction and studies aimed at understanding anthracnose resistance mechanisms in white lupin and contributes to improving breeding programs worldwide.</p>
Data from: Genome-wide analysis reveals associations between climate and regional patterns of adaptive divergence and dispersal in American pikas
<p>Understanding the role of adaptation in species responses to climate change is important for evaluating the evolutionary potential of populations and informing conservation efforts. Population genomics provides a useful approach for identifying putative signatures of selection and the underlying environmental factors or biological processes that may be involved. Here, we employed a population genomic approach within a space-for-time study design to investigate the genetic basis of local adaptation and reconstruct patterns of movement across rapidly changing environments in a thermally-sensitive mammal, the American pika (<i>Ochotona princeps</i>). Using genotypic data at 49,074 single nucleotide polymorphisms (SNPs), we analyzed patterns of genome-wide diversity, structure, and migration along three independent elevational transects located at the northern extent (Tweedsmuir South Provincial Park, British Columbia, Canada) and core (North Cascades National Park, Washington, USA) of the Cascades lineage. We identified 899 robust outlier SNPs within- and among-transects. Of those annotated to genes with known function, many were linked with cellular processes related to climate stress including ATP-binding, ATP citrate synthase activity, ATPase activity, hormone activity, metal ion-binding, and protein-binding. Moreover, we detected evidence for contrasting patterns of directional migration along transects across geographic regions that suggest an increased propensity for American pikas to disperse among lower elevation populations at higher latitudes where environments are generally cooler. Ultimately, our data indicate that fine-scale demographic patterns and adaptive processes may vary among populations of American pikas, providing an important context for evaluating biotic responses to climate change in this species and other alpine-adapted mammals.</p>
Lifecourse genome-wide association study meta-analysis refines the critical life stages for adiposity’s influence on breast cancer risk
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Canine genome-wide association study identifies DENND1B as an obesity gene in dogs and humans
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Data from: Genome-wide variation in DNA methylation is associated with stress resilience and plumage brightness in a wild bird
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Genome-wide association study concerning idiopathic epilepsy in Petit Basset Griffon Vendeen
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Data from: Genome-wide association studies across environmental and genetic contexts reveal complex genetic architecture of symbiotic extended phenotypes
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Genome-wide association study identifies genomic regions associated with key reproductive traits in Korean Hanwoo cows
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Variants and QTL associated with variation in genome-wide crossover number
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Dataset for genome-wide association study of maize phosphorus efficiency
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Multi-locus genome-wide association study for grain yield and drought tolerance indices in sorghum accessions
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Heritability and genome-wide association study of vaccine-induced immune response in Beagles: A pilot study
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Improving genome-wide association discovery and genomic prediction accuracy in biobank data
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Data from: Genome-wide association study for traits related to cold tolerance and recovery during seedling stage in rice
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Natural selection drives genome-wide evolution via chance genetic associations
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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.
International Brain Laboratory public data
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
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.