Human Lung Tissue eQTL Study
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA505743 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:<p>Genetic risks underlying respiratory diseases (e.g. COPD and asthma) are carefully studied by large genome-wide association studies (GWAS), where many loci were identified. In the post-GWAS era, the main challenge is to find the causal genes and pathways in GWAS-nominated chromosomal regions and to characterize etiology mechanism. The Lung eQTL Consortium is an international effort to systematically capture the genetic architecture of gene expression regulation in human lung. By studying lung specimens from 1,103 individuals of mostly European ancestry, we report a large number of genetic variants affecting gene expression in the lung, or lung expression quantitative trait loci (eQTL). These lung eQTLs will serve as an important resource to aid in the understanding of the molecular underpinnings of lung biology and its disruption in disease.</p>
| phs001745 | dbGaP
Project description:Understanding how the genetic control of gene expression varies between cell types and contexts is key for our understanding of complex traits including disease. To this end, we leveraged single cell RNA sequencing (scRNA-seq) to characterize the genetic architecture of gene regulation in an organ with one of the most cellularly diverse organs, the human lung. We profile these effects across two conditions, tissue samples from healthy controls and patients with pulmonary fibrosis (PF), a chronic, progressive condition characterized by the scarring of lung tissue. In total, we have generated expression profiles of 475,047 cells from primary human lung tissue from 116 individuals, including 67 with PF and 49 unaffected donors. Employing a pseudo-bulk approach, we have mapped expression quantitative trait loci (eQTL) across 38 cell types, identifying shared and cell type-specific effects. Further, we identify disease-interaction eQTL demonstrating this class of associations are more likely to be cell-type specific and linked to key drivers of dysregulation in PF. Finally, we connect PF risk variants implicated by genome-wide association studies to their regulatory targets in disease-relevant cell types. This study represents the first use of scRNA-seq to identify cell type level eQTL in the human lung, and one of only a small number of studies to carry out these characterizations in solid tissues. These results provide valuable insights into lung biology and disease risk.
2023-03-20 | GSE227136 | GEO
Project description:Background: Cases where genotype-phenotype relationships depend on environmental factors have been quantified for many complex diseases. Such genotype-environment interactions (GEI or GxE) may also affect expression Quantitative Trait Loci (eQTL) present in tissues critical for the manifestation of disease. To assess this hypothesis, we performed an analysis of eQTL-GEI resulting from an individual's smoking environment in the lung small airway epithelium (SAE). While the SAE is challenging to sample, this is the cell population that shows the first signs of smoking related stress and gene expression in the SAE appears to play a role in mediating smoking effects on lung disease. Results: We used expression microarrays to assay the SAE transcriptome for a small sample of African-American individuals and we analyzed SNPs genotyped genome-wide to identify GEI affecting eQTL. While a genome-wide trans- analysis identified few instances of GEI after a multiple test correction, an analysis of cis-genotypes identified a small but significant number of GEI affecting lung SAE gene expression. We determined that significant cases of eQTL-GEI were not driven by outliers and we were also able to find corroborative evidence for a few of these eQTL-GEI in a small, independent sample of individuals of European ancestry. Conclusion: Given that the power of GEI tests is low compared to tests of genotype association and that the total sample size of our study was small, including only 61 African American individuals in our focal population, the identification of significant GEI in our study implies that there may be considerable genotype-specific effects on eQTL due to smoking environment. We discuss individual cases of GEI of interest for lung disease, such as SDC1 and ZAK, as well as the broader implications of our results for the analysis of eQTL and for genome-wide association analysis of complex diseases.
2024-06-05 | GSE23087 | GEO
Project description:Human lung tissue treated with interferons
| PRJNA779735 | ENA
Project description:LungMAP: Molecular Atlas of Lung Development – Human Lung Tissue
| PRJNA600058 | ENA
Project description:LungMAP: Molecular Atlas of Lung Development – Human Lung Tissue
| PRJNA600059 | ENA
Project description:In this study we use RNAseq to explore allele specific expression (ASE) in adipose tissue of male and female F1 mice, produced from reciprocal crosses of C57BL/6J and DBA/2J strains. Comparison of the identified cis-eQTLs, to local-eQTLs, that were obtained from adipose tissue expression in two previous population based studies in our laboratory, yields poor overlap between the two mapping approaches, while both local-eQTL studies show highly concordant results. Specifically, local-eQTL studies show ~60% overlap between themselves, while only 15-20% of local-eQTLs are identified as cis by ASE, and less than 50% of ASE genes are recovered in local-eQTL studies. Utilizing recently published ENCODE data, we also find that ASE genes show significant bias for SNPs prevalence in DNase I hypersensitive sites that is ASE direction specific. We suggest a new approach to analysis of allele specific expression that is more sensitive and accurate than the commonly used fisher or chi-square statistics. Our analysis indicates that technical differences between the cis and local-eQTL approaches, such as differences in genomic background or sex specificity, account for relatively small fraction of the discrepancy. Therefore, we suggest that the differences between two eQTL mapping approaches may facilitate sorting of SNP-eQTL interactions into true cis and trans, and that a considerable portion of local-eQTL may actually represent trans interactions.
2014-06-05 | GSE58239 | GEO
Project description:Genome-wide association studies (GWAS) have identified over 300 loci associated with the inflammatory bowel diseases (IBD), but putative causal genes for most are unknown. We conducted the largest disease-focused expression quantitative trait loci (eQTL) analysis using colon tissue from 252 IBD patients to determine genetic effects on gene expression and potential contribution to IBD. Combined with two non-IBD colon eQTL studies, we identified 194 potential target genes for 108 GWAS loci. eQTL in IBD tissue were enriched for IBD GWAS loci colocalizations, provided novel evidence for IBD-associated genes such as ABO and TNFRSF14, and identified additional target genes compared to non-IBD tissue eQTL. IBD-associated eQTL unique to diseased tissue had distinct regulatory and functional characteristics with increased effect sizes. Together, these highlight the importance of eQTL studies in diseased tissue for understanding functional consequences of genetic variants, and elucidating molecular mechanisms and regulation of key genes involved in IBD.
2024-10-16 | GSE279302 | GEO
Project description:Cell type-specific and disease-associated eQTL in the human lung
| PRJNA945854 | ENA