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42 results for “exome data”
GWAS Summary Statistics for Publication: Identifying novel genetic and phenotypic associations to genomic features by leveraging off-target reads in exome sequencing data
<p>This dataset contains summary statistics for genome-wide association studies (GWAS) conducted on genomic features derived from off-target reads in whole-exome sequencing (WES) data. The study utilized tools like Seeing Beyond the Target (SBT) and ImReP to construct novel phenotypic features from unmapped reads in ~50,000 participants in the UK Biobank. Features include mitochondrial DNA (mtDNA) copy number, ribosomal DNA (rDNA) copy number (5S, 18S, 28S), immune repertoire metrics (e.g., T-cell receptor alpha diversity), and microvial genome load (viral and fungal).</p> <p>Summary statistics can be used for replication studies, meta-analyses, or further exploration of these phenotypes.</p>
Exome data: Phoxinellus alepidotus and Telestes ukliva
<p>Reference exome and variant files for Phoxinellus alepidotus and Telestes ukliva</p> <p>Published in : Daane, J.M., Rohner, N., Konstantinidis, P., Djuranovic, S. and Harris M.P. (2016). Parallelism and epistasis in skeletal evolution identified through use of phylogenomic mapping strategies. <em>Mol Biol. Evol. </em>33:162-173.</p>
Training data for 'Exome sequencing data analysis' tutorial (Galaxy Training Material)
<p>The data used in this tutorial are a subset of the data published previously in <a href="https://zenodo.org/record/3243160">Training material for the course "Exome analysis with GALAXY"</a>. Credit for uploading the original data goes to Paolo Uva and Gianmauro Cuccuru!</p> <p>Specifically, you may need the following datasets for following the tutorial:</p> <p><strong>Raw sequencing reads</strong></p> <ul> <li><a href="https://zenodo.org/record/3243160/files/father_R1.fq.gz?download=1">https://zenodo.org/record/3243160/files/father_R1.fq.gz</a></li> <li><a href="https://zenodo.org/record/3243160/files/father_R2.fq.gz?download=1">https://zenodo.org/record/3243160/files/father_R2.fq.gz</a></li> <li><a href="https://zenodo.org/record/3243160/files/mother_R1.fq.gz?download=1">https://zenodo.org/record/3243160/files/mother_R1.fq.gz</a></li> <li><a href="https://zenodo.org/record/3243160/files/mother_R2.fq.gz?download=1">https://zenodo.org/record/3243160/files/mother_R2.fq.gz</a></li> <li><a href="https://zenodo.org/record/3243160/files/proband_R1.fq.gz?download=1">https://zenodo.org/record/3243160/files/proband_R1.fq.gz</a></li> <li><a href="https://zenodo.org/record/3243160/files/proband_R2.fq.gz?download=1">https://zenodo.org/record/3243160/files/proband_R2.fq.gz</a></li> </ul> <p><strong>Premapped sequencing reads</strong></p> <ul> <li><a href="https://zenodo.org/record/3243160/files/mapped_reads_father.bam?download=1">https://zenodo.org/record/3243160/files/mapped_reads_father.bam</a></li> <li><a href="https://zenodo.org/record/3243160/files/mapped_reads_mother.bam?download=1">https://zenodo.org/record/3243160/files/mapped_reads_mother.bam</a></li> <li><a href="https://zenodo.org/record/3243160/files/mapped_reads_proband.bam?download=1">https://zenodo.org/record/3243160/files/mapped_reads_proband.bam</a></li> </ul> <p><strong>Reference sequence (human chromosome 8)</strong></p> <ul> <li><a href="https://zenodo.org/record/3243160/files/hg19_chr8.fa.gz?download=1">https://zenodo.org/record/3243160/files/hg19_chr8.fa.gz</a></li> </ul> <p> </p> <p>If you would just like to play with GEMINI rather than work through the full tutorial, you'll find below a prebuilt GEMINI database (for GEMINI version 0.20.1) for the family trio. You can start exploring this database without having to run GEMINI load and, in fact, without having to install GEMINI's bundled annotation data.</p>
Data from: Association genetics of growth and adaptive traits in loblolly pine (Pinus taeda L.) using whole-exome-discovered polymorphisms
In the United States, forest genetics research began over 100 years ago and loblolly pine breeding programs were established in the 1950s. However, the genetics underlying complex traits of loblolly pine remains to be discovered. To address this, adaptive and growth traits were measured and analyzed in a clonally tested loblolly pine (Pinus taeda L.) population. Over 2.8 million single nucleotide polymorphism (SNP) markers detected from exome sequencing were used to test for single locus associations, SNP-SNP interactions and correlation of individual heterozygosity with phenotypic traits. A total of 36 SNP-trait associations were found for specific leaf area (5 SNPs), branch angle (2), crown width (3), stem diameter (4), total height (9), carbon isotope discrimination (4), nitrogen concentration (2), and pitch canker resistance traits (7). Eleven SNP-SNP interactions were found to be associated with branch angle (1 SNP-SNP interaction), crown width (2), total height (2), carbon isotope discrimination (2), nitrogen concentration (1), and pitch canker resistance (3). Non-additive effects imposed by dominance and epistasis account for a large fraction of the genetic variance for the quantitative traits. Genes that contain the identified SNPs have a wide spectrum of functions. Individual heterozygosity positively correlated with water use efficiency and nitrogen concentration. In conclusion, multiple effects identified in this study influence the performance of loblolly pines, provide resources for understanding the genetic control of complex traits, and have potential value for assessing with breeding through marker assisted selection and genomic selection.
Simulated exome-sequencing data for a family study of lymphoid cancer
<p>This repository contains all the data files for a simulated exome-sequencing study of 150 families, ascertained to contain at least four members affected with lymphoid cancer. Please note that previous versions of this repository omitted a key file linking the genotypes of individuals to their family and individual IDs; this file, geno_key.txt, is now included. All other files remain the same as in previous versions.</p> <p>The simulated data can be found in the files section below. The files are:</p> <ol> <li>SLiM_output.txt - contains the SLiM-simulated, exome-wide, SNV data generated under an American-admixture demographic model, for the American-admixed sub-population only.</li> <li>SLiM_output_chr8&9.txt - contains the SLiM-simulated data above for all source populations as well as the American-admixed sub-population, but only for chromosomes 8 and 9.</li> <li>sample_info.txt - contains pedigree information of all the disease-affected individuals and individuals connecting them along a line of descent, for all 150 ascertained pedigrees.</li> <li>Genotypes.zip - a zipfile that contains 22 text files of genotypes for each chromosome. The genotypes are for simulated single-nucleotide variants on the exome and are in gene-dosage format. </li> <li>geno_key.txt – a plain-text file that links the genotyped individuals to their family and individual IDs.</li> <li>SNVmaps.zip - a zipfile that contains 22 text files giving the single-nucleotide variant information for each chromosome. </li> <li>familial_cRV.txt - contains the familial causal rare variants for all 150 ascertained pedigrees.</li> <li>study_peds.txt - contains the 150 pedigrees ascertained to contain four or more relatives affected with lymphoid cancer.</li> <li>PLINKfiles.zip - a zipfile that contains PLINK .fam, .bim and .bed files for all 22 of the chromosomes.</li> </ol> <p>All the scripts used to generate these data can be found in the GitHub repository archived at <a href="../records/12694914">https://zenodo.org/records/12694914</a></p> <p>We have also uploaded one intermediate .Rdata file, Chromwide.Rdata, to save the user substantial time when running the associated RMarkdown script for the simulation. We recommend loading Chromwide.Rdata into your R work-space rather than generating it from scratch.</p>
Data files for manuscript "Re-evaluation and Re-analysis of 152 research exomes five years after the initial report reveals clinically relevant changes in 18%"
<p>#2023-06-16<br> #Summary<br> This ZIP-file contains the data files used for all analyses for the manuscript "Re-evaluation and Re-analysis of 152 research exomes five years after the initial report reveals clinically relevant changes in 18%".</p> <p><br> #File structure<br> README.txt This README file.<br> File S02 ("FileS2_conNDD-cohort.xlsx") All variants identified by Reuter et al. previously with reevaluated variants and addition variants identified in this <br> project togetehr with information about the families, individuals, samplesand the BAM files assessed in this project.<br> File S03 ("FileS3_conNDD-variants.xlsx") All variant data analyzed from the cohort. Including a sheet with thresholdes for in silico predictions tools used to predict effect of variants, <br> a table with exome wide homozygous variants in 4 categories (A45, LGD, Missense, Splice), a table with exome wide variants in 4 categories (A45, LGD, Missense, Splice)<br> filtered for domiant genes associated with neurodevelopmental disorders in SysID (Prime and Candidate list), a table with exome wide variants in 4 categories (A45, LGD, Missense, Splice) filtered for recessive genes associated with neurodevelopmental disorders in SysID (Prime and Candidate list), a table withcopy number (CN) calls for the cohort and a table withcalls for runs of homozygosity (RoH) regions.</p> <p>#Files and checksums<br> 29c4b2f3dd8985d268f50dd3e0265798 ./FileS2_conNDD-cohort.xlsx<br> a054334637b8b22a9bf743db1e348663 ./FileS3_conNDD-variants.xlsx<br> </p>
Data from: Association genetics of growth and adaptive traits in loblolly pine (Pinus taeda L.) using whole-exome-discovered polymorphisms
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Data from: Using transcriptome sequencing and pooled exome capture to study local adaptation in the giga-genome of Pinus cembra
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Data from: Optimizing exome captures in species with large genomes using species-specific repetitive DNA blocker
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Data from: Exome resequencing reveals signatures of demographic and adaptive processes across the genome and range of black cottonwood (Populus trichocarpa)
Extant variation in temperate and boreal plant species has been influenced by both demographic histories associated with Pleistocene glacial cycles and adaptation to local climate. We used sequence capture to investigate the role of these neutral and adaptive processes in shaping diversity in black cottonwood (Populus trichocarpa). Nucleotide diversity and Tajima's D were lowest at replacement sites and highest at intergenic sites, while LD showed the opposite pattern. With samples grouped into three populations arrayed latitudinally, effective population size was highest in the north, followed by south and centre, and LD was highest in the south followed by the north and centre, suggesting a possible northern glacial refuge. FST outlier analysis revealed that promoter, 5′-UTR and intronic sites were enriched for outliers compared with coding regions, while no outliers were found among intergenic sites. Codon usage bias was evident, and genes with synonymous outliers had 30% higher average expression compared with genes containing replacement outliers. These results suggest divergent selection related to regulation of gene expression is important to local adaptation in P. trichocarpa. Finally, within-population selective sweeps were much more pronounced in the central population than in putative northern and southern refugia, which may reflect the different demographic histories of the populations and concomitant effects on signatures of genetic hitchhiking from standing variation.
Simulated exome-sequencing data for a family study of lymphoid cancer
<p>This repository contains all the data files for a simulated exome-sequencing study of 150 families ascertained to contain at least four members affected with lymphoid cancer.</p> <p>The simulated data can be found in the files section below. The files are:</p> <ol> <li>SLiM_output.txt - contains the SLiM-simulated, exome-wide, SNV data generated under an American-admixture demographic model, for the American-admixed sub-population only.</li> <li>SLiM_output_chr8&9.txt - contains the SLiM-simulated data above for all source populations as well as the American-admixed sub-population, but only for chromosomes 8 and 9.</li> <li>sample_info.txt - contains pedigree information of all the disease-affected individuals and individuals connecting them along a line of descent, for all 150 ascertained pedigrees.</li> <li>Genotypes.zip - a zipfile that contains 22 text files of genotypes for each chromosome. The genotypes are for simulated single-nucleotide variants on the exome and are in gene-dosage format. </li> <li>SNVmaps.zip - a zipfile that contains 22 text files giving the single-nucleotide variant information for each chromosome. </li> <li>familial_cRV.txt - contains the familial causal rare variants for all 150 ascertained pedigrees.</li> <li>study_peds.txt - contains the 150 pedigrees ascertained to contain four or more relatives affected with lymphoid cancer.</li> <li>PLINKfiles.zip - a zipfile that contains PLINK .fam, .bim and .bed files for all 22 of the chromosomes.</li> </ol> <p>All the scripts used to generate these data can be found in the GitHub repository archived at <a href="https://zenodo.org/record/6505385">https://zenodo.org/record/6505385</a> .</p> <p>We have also uploaded one intermediate .Rdata file, Chromwide.Rdata, to save the user substantial time when running the associated RMarkdown script for the simulation. We recommend loading Chromwide.Rdata into your R work-space rather than generating it from scratch.</p>
Data files for manuscript "Exome first approach to reduce diagnostic costs and time – retrospective analysis of 111 individuals with rare neurodevelopmental disorders"
<p>#2021-07-23<br> #Summary<br> This ZIP-file contains the Excel files used for the clinical and variant analyses for the manuscript "Exome first approach to reduce diagnostic costs and time – retrospective analysis of 111 individuals with rare neurodevelopmental disorders".</p> <p>#Folder structure<br> ./ (parent directory containing this README file and all subfolders)<br> ./Clinical/ (contains an Excel sheets with complete clinical data, costs and criteria)<br> ./Variants/ (contains an Excel sheet with all variant annotation)</p> <p>#Files and checksums<br> 6DB0EF10BE7A7AF5A18E523F33FB662A ./Clinical/FileS2_Clinical.xlsx<br> 0B0C1AFA0751B63A35DC99DB25546A38 ./Variants/FileS3_Variants.xlsx</p>
Data from: Exome resequencing reveals signatures of demographic and adaptive processes across the genome and range of black cottonwood (Populus trichocarpa)
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Data from: Genomic prediction accuracies in space and time for height and wood density of Douglas-fir using exome capture as the genotyping platform
Background Genomic selection (GS) can offer unprecedented gains, in terms of cost efficiency and generation turnover, to forest tree selective breeding; especially for late expressing and low heritability traits. Here, we used: 1) exome capture as a genotyping platform for 1372 Douglas-fir trees representing 37 full-sib families growing on three sites in British Columbia, Canada and 2) height growth and wood density (EBVs), and deregressed estimated breeding values (DEBVs) as phenotypes. Representing models with (EBVs) and without (DEBVs) pedigree structure. Ridge regression best linear unbiased predictor (RR-BLUP) and generalized ridge regression (GRR) were used to assess their predictive accuracies over space (within site, cross-sites, multi-site, and multi-site to single site) and time (age-age/ trait-trait). Results The RR-BLUP and GRR models produced similar predictive accuracies across the studied traits. Within-site GS prediction accuracies with models trained on EBVs were high (RR-BLUP: 0.79–0.91 and GRR: 0.80–0.91), and were generally similar to the multi-site (RR-BLUP: 0.83–0.91, GRR: 0.83–0.91) and multi-site to single-site predictive accuracies (RR-BLUP: 0.79–0.92, GRR: 0.79–0.92). Cross-site predictions were surprisingly high, with predictive accuracies within a similar range (RR-BLUP: 0.79–0.92, GRR: 0.78–0.91). Height at 12 years was deemed the earliest acceptable age at which accurate predictions can be made concerning future height (age-age) and wood density (trait-trait). Using DEBVs reduced the accuracies of all cross-validation procedures dramatically, indicating that the models were tracking pedigree (family means), rather than marker-QTL LD. Conclusions While GS models' prediction accuracies were high, the main driving force was the pedigree tracking rather than LD. It is likely that many more markers are needed to increase the chance of capturing the LD between causal genes and markers.
Data from: A high-density exome capture genotype-by-sequencing panel for forestry breeding in Pinus radiata
Development of genome-wide resources for application in genomic selection or genome-wide association studies, in the absences of full reference genomes, present a challenge to the forestry industry, where longer breeding cycles could benefit from the accelerated selection possible through marker-based breeding value predictions. In particular, large conifer megagenomes require a strategy to reduce complexity, whilst ensuring genome-wide coverage is achieved. Using a transcriptome-based reference template, we have successfully developed a high density exome capture genotype-by-sequencing panel for radiata pine (Pinus radiata D.Don), capable of capturing in excess of 80,000 single nucleotide polymorphism (SNP) markers with a minor allele frequency above 0.03 in the population tested. This represents approximately 29,000 gene models from a core set of 48,914 probes. A set of 704 SMP markers capable of pedigree reconstruction and differentiating individual genotypes were tested within two full-sib mapping populations. While as few as 70 markers could reconstruct parentage in almost all cases, the impact of missing genotypes was noticeable in several offspring. Therefore, sets of 60 sets of 110 randomly selected SNP markers were compared for both parentage reconstruction and clone differentiation. The performance in parentage reconstruction showed little variation over 60 iterations. However, there was notable variation in discriminatory power between closely related individuals, indicating a higher density SNP marker panel may be required to elucidate hidden relationships in complex pedigrees.
Schistosoma mansoni raw genotype calls from exome data
<p><em>Schistosoma mansoni, </em>a snail-vectored, blood fluke that infects humans, was introduced into the Americas from Africa during the Trans-Atlantic slave trade. As this parasite shows strong specificity to the snail intermediate host, we expected that adaptation to S. American <em>Biomphalaria</em> spp. snails would result in population bottlenecks and strong signatures of selection. We scored 475,081 single nucleotide variants (SNVs) in 143 <em>S. mansoni</em> from the Americas (Brazil, Guadeloupe, and Puerto Rico) and Africa (Cameroon, Niger, Senegal, Tanzania, and Uganda), and used these data to ask: (i) Was there a population bottleneck during colonization? (ii) Can we identify signatures of selection associated with colonization? And (iii) what were the source populations for colonizing parasites? We found a 2.4-2.9-fold reduction in diversity and much slower decay in linkage disequilibrium (LD) in parasites from East to West Africa. However, we observed similar nuclear diversity and LD in West Africa and Brazil, suggesting no strong bottlenecks and limited barriers to colonization. We identified five genome regions showing selection in the Americas, compared with three in West Africa and none in East Africa, which we speculate may reflect adaptation during colonization. Finally, we infer that unsampled African populations from central African regions between Benin and Angola, with contributions from Niger, are likely the major source(s) for Brazilian <em>S. mansoni</em>. The absence of a bottleneck suggests that this is a rare case of a serendipitous invasion, where <em>S. mansoni </em>parasites were preadapted to the Americas and were able to establish with relative ease.</p>
Scalable mixed model approaches for set-based association studies on large-scale categorical data analysis and its application to 450k exome sequencing data in UK Biobank
<p>The ongoing release of large-scale sequencing data in the UK Biobank allows for identifying associations between rare variants and complex traits. SAIGE-GENE+ is a valid approach to conducting set-based association tests for quantitative and binary traits. However, for ordinal categorical phenotypes, applying SAIGE-GENE+ with treating the trait as quantitative or binarizing the trait can cause inflated type I error rates or power loss. In this study, we propose a novel method for rare-variant association tests, POLMM-GENE, in which a proportional odds logistic mixed model was used to characterize ordinal categorical phenotypes while adjusting for sample relatedness. POLMM-GENE fully utilizes the categorical nature of phenotypes and thus can well control type I error rates while remaining powerful. In the analyses of UK Biobank 450k whole exome-sequencing data for 5 ordinal categorical traits, POLMM-GENE identified 54 gene-phenotype associations.</p>
Data from: HyRAD-X, a versatile method combining exome capture and RAD sequencing to extract genomic information from ancient DNA
Over the last decade, protocols aimed at reproducibly sequencing reduced-genome subsets in non-model organisms have been widely developed. Their use is however limited to DNA of relatively high molecular weight. During the last year, several methods exploiting hybridization capture using probes based on RAD-sequencing loci have circumvented this limitation and opened avenues to the study of samples characterized by degraded DNA, such as historical specimens. Here, we present a major update to those methods, namely Hybridization capture from RAD-derived probes obtained from a reduced eXome template (hyRAD-X), a technique applying RAD-sequencing to messenger RNA from one or few fresh specimens to elaborate bench-top produced probes, i.e., a reduced representation of the exome, further used to capture homologous DNA from a samples set. In contrast to previous hybridization-capture methods, the reference catalog on which reads are aligned does not rely on de novo assembly of anonymous RAD-sequencing loci, but on an assembled transcriptome obtained from RNAseq data, thus increasing the accuracy of loci definition and Single-Nucleotide-Polmorphisms (SNP) call, and targeting, specifically, expressed genes. Finally, the capture step of hyRAD-X relies on RNA probes, increasing stringency of hybridization, making it well suited for low-content DNA samples. As a proof of concept, we applied hyRAD-X to subfossil needles from the coniferous tree Abies alba, collected in lake sediments (Origlio, Switzerland) and dating back from 7200-5800 years before present (BP). More specifically we investigated genetic variation before, during, and after an anthropogenic perturbation that caused an abrupt decrease in Abies alba population size, 6500-6200 years BP. HyRAD-X produced a matrix encompassing 524 exome-derived SNPs. Despite a lower observed heterozygosity was observed during the 6.500-6.200 years BP time slice, genetic composition was nearly identical before and after the perturbation, indicating that re-expansion of the population after the decline was driven by autochthonous specimens. To the best of our knowledge, this is the first time a population genomic study incorporating ancient DNA samples of tree subfossils is conducted at a moderate cost using reproducible exome-reduced complexity.
Combining Exome and Transcriptome Data to Unravel the Genetic Basis of the Lissencephalies
ClinicalTrials.gov study NCT05185414. IPD Sharing: NO. Countries: 1. Publications: 4.
Data from: A high-density exome capture genotype-by-sequencing panel for forestry breeding in Pinus radiata
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