Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Genetic Basis of Transcriptomic Diversity in Drosophila melanogaster

ABSTRACT: Understanding how DNA sequence variation is translated into variation for complex phenotypes has remained elusive, but is essential for predicting adaptive evolution, selecting agriculturally important animals and crops, and personalized medicine. Here, we quantified genome-wide genetic variation in gene expression in the sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. We found that a substantial fraction of the Drosophila transcriptome is genetically variable and organized into modules of genetically correlated transcripts, which provide functional context for newly identified novel transcribed regions. We identified regulatory variants for the mean and variance of gene expression, both of which showed oligogenic genetic architecture. Expression quantitative trait loci the mean, but not the variance, of gene expression were concentrated near genes. This comprehensive characterization of transcriptomic diversity and its genetic basis in the DGRP is critically important for a systems understanding of quantitative trait variation.

ORGANISM(S): Drosophila melanogaster

SUBMITTER: Mary Anna Carbone

PROVIDER: E-MTAB-3216 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Rheumatoid arthritis is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1-12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-α, IL-6, IL-12p70, and IFN-γ. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis. A total of 559 human sera were profiled using a custom made panel of putative rheumatoid arthritis associated autoantigens. The cohort was comprised of 79 patients with clinical RA for whom stored serum was available from 1-10 years prior to disease onset and 80 control subjects without RA that were matched to cases based on age, gender, race, region of assignment, and time of serum sampling.

Project description:Rheumatoid arthritis is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1-12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-?, IL-6, IL-12p70, and IFN-?. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis. A total of 556 human sera were profiled using multiplex cytokine and chemokine assays. The cohort was comprised of 80 patients with clinical RA for whom stored serum was available from 1-10 years prior to disease onset and 78 control subjects without RA matched to cases based on age, gender, race, region of assignment, and time of serum sampling.

Dataset Information

Genetic Basis of Transcriptomic Diversity in Drosophila melanogaster

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure