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7 results for “DGRP”
Liftover of Drosoophila melanogaster genotypes, DGRP sample, from dm3 to dm6 reference assembly.
<p>Genotype data for Drosophila melanogaster DGRP collection.<strong> </strong>Variant positions relative to reference genome version dm6.<strong> </strong>Variant identifiers are in NCBI format.<strong> </strong>Processing code (including original data, reference sequences, perl scripts, etc).</p> <p>The initial intention of performing this 'liftover' was to allow comparison with data from a different melanogaster sample which had been analysed against a dm6 reference assembly. At the time of writing I am not aware that a dataset like this one exists.</p> <p>I've uploaded it in case it is useful to anyone in the future - and also as a trial of zenodo.</p> <p>See README.txt and flylifter.sh for more info.</p> <p> </p>
Liftover of DGRP D.melanogaster genotypes to reference genome assembly v6.0, with QC graph
<p>Output are vcf and plink-format genotype files. Also provided are the run code in bash and R, the logs, summary statistics, and a graph showing how the positions of SNPs have changed.</p>
Data from: The Drosophila Genetic Reference Panel (DGRP) on locomotor activity across different environmental conditions
<p>In nature, organisms are exposed to variable and occasionally stressful environmental conditions. Responses to diurnal and seasonal fluctuations, such as temperature and food accessibility, involve adaptive behavioral and physiological changes. While much work has been done on understanding the genetic architecture and evolutionary potential of stress tolerance traits under constant thermal conditions, there has been less focus on the quantitative genetic background in variable environments. In this study, we use the <em>Drosophila</em> Genetic Reference Panel (DGRP) to investigate locomotor activity, a key behavioral trait, under variable natural thermal conditions during the summer in a temperate environment. Male flies from 100 DGRP lines were exposed to natural thermal and light conditions in <em>Drosophila</em> activity monitors across three experimental days. We found that activity was highly temperature- and time-dependent and varied between lines both within and between days. Further, we observed variation in genetic and environmental variance components, with low to moderate estimates of the heritability for locomotor activity, consistently peaking in the afternoons. Moreover, we showed that the estimated genetic correlations of locomotor activity between two time points decreased as the absolute differences in ambient temperature was increased. In conclusion, we find that the genetic background for locomotor activity is environment specific and we conclude that more variable and unpredictable future temperatures will likely have a strong impact on the evolutionary trajectories of behavioral traits in ectotherms.</p>
ArchiHeart - Dataset : Software containers, SQlite database and DGRP data
<p><strong>Title : </strong>Genetic architecture of natural variation of cardiac performance in flies</p> <p><strong>Abstract : </strong>Deciphering the genetic architecture of human cardiac disorders is of fundamental importance but their underlying complexity is a major hurdle. We investigated the natural variation of cardiac performance in the sequenced inbred lines of the Drosophila Genetic Reference Panel (DGRP)1. Genome Wide Associations Studies (GWAS) identified genetic networks associated with natural variation of cardiac traits which were extensively validated with <em>in vivo</em> cardiac-specific gene manipulation<em>.</em> Specifically, non-coding variants that we identified were used to map potential regulatory non-coding regions, which in turn were employed to predict Transcription Factors (TFs) binding sites. Cognate TFs, many of which themselves bear polymorphisms associated with variations of cardiac performance, were also validated by heart specific knockdown. Although rarely studied, the genetic control of phenotypic variability is of primary importance, with both medical and fundamental implications. We showed that the natural variations associated with variability in cardiac performance affect a set of genes overlapping with those associated with average traits but through different variants in the same genes. Furthermore, we showed that phenotypic variability is also associated with gene regulatory network deviations. More importantly, we documented correlations between genes associated with cardiac phenotypes in both flies and humans, which supports a conserved genetic architecture regulating adult cardiac function from arthropods to mammals. Specifically, roles for PAX9 and EGR2 in the regulation of the cardiac rhythm were established in both models, illustrating that the characteristics of natural variations in cardiac function identified in Drosophila can accelerate discovery in humans.</p> <p><strong>Data</strong> :</p> <ul> <li>phenosnip_singleageanalysis.img : singularity v2.6 image with R 3.4.4 and python 2.7, used for preliminary statistical analysis.</li> <li>phenosnip_singleagegwas.img : singualrity v2.6 image with FastLMM and plink, used for GWAS analysis</li> <li>phenosnip_singleageepistasis.img : singualrity c2.6 image with fastEpistasis and plink, used for epistasis analysis</li> <li>Phenosnip.sqlite.tar.gz : SQlite database containing the genotype information from DGRP consortium and the phenotype data of the study (1 week aged drosophila)</li> <li>dgrp2.tar.gz : BED, BIM and FAM files with genetic information of the DGRP lines (data issued from the DGRP consortium)</li> <li>datasets_saha_et_al.zip : raw data (individual phenotypes of DGRP lines / variants identified by GWAS / individual phenotypes from validation experiments) and large scale datasets used for analyses (PPI and genetic interactions / regulatory variants) </li> </ul>
Data from: The Drosophila Genetic Reference Panel (DGRP) on locomotor activity across different environmental conditions
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RNA-sequencing of the female adult fly guts from 38 DGRP lines with and without oral infection with Pseudomonas entomophila
GEO Series GSE118142. Drosophila melanogaster. 76 samples. Type: Expression profiling by high throughput sequencing.
Bulk ATAC-seq on whole brain across DGRP lines (homozigous fly lines)
GEO Series GSE181494. Drosophila melanogaster. 44 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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International Brain Laboratory public data
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OpenNeuro
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