A resource for integrated genomic analysis of the human liver
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE179250 | GEO | 2022/09/22
REPOSITORIES: GEO
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Project description:African Americans (AAs) are disproportionately affected by metabolic diseases and adverse drug events, with limited publicly available genomic and transcriptomic data to advance the knowledge of the molecular underpinnings or genetic associations to these diseases or drug response phenotypes. To fill this gap, we obtained 60 primary hepatocyte cultures from AA liver donors for genome-wide mapping of expression quantitative trait loci (eQTL) using LAMatrix. We identified 277 eGenes and 19,770 eQTLs, of which 67 eGenes and 7,415 eQTLs are not observed in the Genotype-Tissue Expression Project (GTEx) liver eQTL analysis. Of the eGenes found in GTEx only 25 share the same lead eQTL. These AA-specific eQTLs are less correlated to GTEx eQTL in effect sizes and have larger Fst values compared to eQTLs found in both cohorts (overlapping eQTLs). We assessed the overlap between GWAS variants and their tagging variants with AA hepatocyte eQTLs and demonstrated that AA hepatocyte eQTLs can decrease the number of potential causal variants at GWAS loci. Additionally, we identified 75,002 exon QTLs of which 48.8% are not eQTLs in AA hepatocytes. Our analysis provides the first comprehensive characterization of AA hepatocyte eQTLs and highlights the unique discoveries that are made possible due to the increased genetic diversity within the African ancestry genome.
2020-03-27 | GSE147628 | GEO
Project description:The Genotype-Tissue Expression (GTEx) project aims to provide to the scientific community a resource with which to study human gene expression and regulation and its relationship to genetic variation. This project will collect and analyze multiple human tissues from donors who are also densely genotyped, to assess genetic variation within their genomes. By analyzing global RNA expression within individual tissues and treating the expression levels of genes as quantitative traits, variations in gene expression that are highly correlated with genetic variation can be identified as expression quantitative trait loci, or eQTLs. The present dataset contains RNA-seq from human reference/non-diseased tissues (thus, we have excluded K-562 cell line that is a chronic myelogenous leukemia cell line) from the Genotype-Tissue Expression (GTEx) Project (http://www.gtexportal.org/home/).
2016-12-07 | E-MTAB-5214 | biostudies-arrayexpress
Project description:Osteoporosis, characterized by low bone mineral density (BMD), is the most common complex disease affecting bone and constitutes a major societal health problem. Genome-wide association studies (GWASs) have identified over 1100 associations influencing BMD. It has been shown that perturbations to long non-coding RNAs (lncRNAs) influence BMD and the activities of bone cells; however, the extent to which lncRNAs are involved in the genetic regulation of BMD is unknown. Here, we combined the analysis of allelic imbalance (AI) in human acetabular bone fragments with a transcriptome-wide association study (TWAS) and expression quantitative trait loci (eQTL) colocalization analysis using data from the Genotype-Tissue Expression (GTEx) project to identify lncRNAs potentially responsible for GWAS associations. We identified 27 lncRNAs in bone that are located in proximity to a BMD GWAS association and harbor SNPs demonstrating AI. Using GTEx data we identified an additional 31 lncRNAs whose expression was associated (FDR correction<0.05) with BMD through TWAS and had a colocalizing eQTL (regional colocalization probability (RCP)>0.1). The 58 lncRNAs are located in 43 BMD associations. To further support a causal role for the identified lncRNAs, we show that 23 of the 58 lncRNAs are differentially expressed as a function of osteoblast differentiation. Our approach identifies lncRNAs that are potentially responsible for BMD GWAS associations and suggest that lncRNAs play a role in the genetics of osteoporosis.
2021-11-04 | GSE186922 | GEO
Project description:Age-related macular degeneration (AMD) is a complex multifactorial disease with at least 34 loci contributing to genetic susceptibility. To gain functional understanding of AMD genetics, we generated transcriptional profiles of retina from 453 individuals including both controls and cases at distinct stages of AMD. We integrated retinal transcriptomes, covering 13,662 protein-coding and 1,462 noncoding genes, with genotypes at over 9 million common single nucleotide polymorphisms (SNPs) for expression quantitative trait loci (eQTL) analysis of a tissue not included in Genotype-Tissue Expression (GTEx) and other large datasets. Cis-eQTL analysis revealed 10,474 genes under genetic regulation, including 4,541 eQTLs detected only in the retina. We then integrated the AMD-genome-wide association studies (GWAS) data with eQTLs and ascertained target genes at six loci. Furthermore, using transcriptome wide association analysis (TWAS), we identified 23 additional AMD-associated genes, including RLBP1, HIC1 and PARP12. Our studies expand the genetic landscape of AMD leading to direct targets for biological evaluation and establish the Genotype-Retina Expression (GREx) database as a resource for post-GWAS interpretation of retina-associated traits including glaucoma and diabetic retinopathy.
2019-02-11 | GSE115828 | GEO
Project description:More than 200 asthma-associated genetic variants have been identified in genome-wide association studies (GWASs). Expression quantitative trait loci (eQTL) data resources can help identify causal genes of the GWAS signals, but it can be difficult to find an eQTL that reflects the disease state because most eQTL data are obtained from normal healthy subjects. We performed a blood eQTL analysis using transcriptomic and genotypic data from 436 Korean asthma patients. To identify asthma-related genes, we carried out colocalization and Summary-based Mendelian Randomization (SMR) analysis using the results of asthma GWASs and eQTL data. In addition, we compared the results of disease eQTL data and asthma-related genes with two normal blood eQTL data from Genotype-Tissue Expression (GTEx) project and a Japanese study. We identified 342,054 cis-eQTL and 2,931 eGenes from asthmatic eQTL analysis. We compared the disease eQTL results with GTEx and a Japanese study and found that 63.2 % of the 2,931 eGenes overlapped with the GTEx eGenes and 38.5 % with the Japanese eGenes. Following the integrated analysis of the asthmatic eQTL data with asthma GWASs, using colocalization and SMR methods, we identified 13 asthma-related genes specific to the Korean asthmatic eQTL data. We provided Korean asthmatic cis-eQTL data and identified asthma-related genes by integrating them with GWAS data. In addition, we suggested these asthma-related genes as therapeutic targets for asthma. We envisage that our findings will contribute to understanding the etiological mechanisms of asthma and provide novel therapeutic targets.
2023-03-08 | GSE226825 | GEO
Project description:Here, we integrated genome-wide genotype, gene expression and phenotype (viremia level (VL) and weight gain (WG)) data to identify genetic variations and genes that are associated with variation in pigs’ response to PRRSV infection. RNA-seq analysis of peripheral blood samples collected just prior to experimental challenge (day 0) and at 4, 7, 10 and 14 days post infection from 44 pigs revealed 6430 differentially expressed genes after infection. We mapped genetic variations that are associated with inter-individual differences in expression at each day and found evidence of cis expression quantitative trait loci (cis-eQTL) for 1201 genes. Associations between cis-eQTL markers and phenotypes using 383 pigs indicated that host genotype-dependent reduced expression of GBP5, CD1D, PAK1, and USP18 contribute to higher VL or lower WG in response to PRRSV infection. We also validated that cis-eQTLs of these candidate genes for host response to PRRSV infection generally acted by a mechanism involving allele-specific expression.
2017-03-31 | GSE78762 | GEO
Project description:Genotype-Tissue Expression Project (GTEx)
| PRJNA158505 | ENA
Project description:<p><b>Lay Description</b></p> <p>The aim of the Genotype-Tissue Expression (GTEx) Project is to increase our understanding of how changes in our genes affect human health and disease with the ultimate goal of improving health care for future generations. GTEx will create a database that researchers can use to study how inherited changes in genes lead to common diseases.</p> <p>GTEx researchers are studying genes in different tissues obtained from many different people. The GTEx project also includes a study of the GTEx donor consent process - this study will help ensure that the consent process and other aspects of the project effectively address the concerns and expectations of participants in the study. GTEx is a pioneering project that uses state-of-the-art protocols for obtaining and storing a large range of organs and tissues, and for testing them in the lab. Until now, no project has analyzed genetic variation and expression in as many tissues from the same person in such a large population as planned for GTEx.</p> <p><b>Scientific Description</b></p> <p>Understanding the role of variation in the human genome is crucial to elucidating genetic contributions to human health and disease. Despite the results of genome-wide association studies (GWAS) documenting strong statistical associations between genetic variation and human traits, the functional role for most of these variants is largely unexplained. Nearly 90% of these GWAS-implicated sites lie outside of protein-coding sequences, suggesting that these variants might regulate gene expression.</p> <p>The goal of the Genotype-Tissue Expression (GTEx) project is to establish a resource database and tissue biobank in which to study the relationship between genetic variation and gene expression and other molecular phenotypes in reference/non-diseased tissues. The ultimate resource will include approximately 960 post-mortem donors with several dozen tissues from each, a resource large enough to study both <i>cis</i>- and <i>trans</i>- gene expression quantitative trait loci (eQTLs). Some tissue will also be banked for additional molecular analyses. To request biosamples, please see the <a href="http://www.gtexportal.org/home/samplesPage" target="_blank">Biobank page</a> for more information.</p> <p>GTEx was initially funded as a 2-year pilot project by the NIH Common Fund (CF) in 2010, and has been scaled up after demonstration of feasibility. The project will collect and analyze RNA levels in many different human tissues and each donor will be characterized for germline genetic variation through dense genotyping arrays and sequencing of either whole exomes or whole genomes.</p> <p>By treating RNA expression levels as quantitative traits, eQTLs will be identified as sites containing genetic variation that correlate with changes in RNA expression. Such eQTLs have been associated with 4%-12% of expressed human genes, and with common complex human diseases, including obesity, atherosclerosis, type 2 diabetes, Crohn's disease, and asthma. Additionally, few studies have examined the tissue specificity of eQTLs. A subset of banked tissue samples will also be analyzed for other molecular phenotypes, such as DNA methylation, DNaseI hypersensitivity sites, and proteomics. The GTEx project will thus serve as a resource database and tissue bank for many future studies, especially for understanding the functional basis of inherited susceptibility to disease.</p> <p>All GTEx releases since Version 5 follow the NIH Genomic Data Sharing (GDS) Policy whereby there are no restrictions on use or publication after release. Additional information about the GTEx Data Release and Publication policy can be found on the GTEx Data Portal at <a href="http://www.gtexportal.org" target="_blank">www.gtexportal.org</a>.</p>
| phs000424 | dbGaP
Project description:Induced pluripotent stem cells generated from patients with geographic atrophy as well as healthy individuals were differentiated to retinal pigment epithelium (RPE) cells. By integrating transcriptional profiles of 127,659 RPE cells generated from 43 individuals with geographic atrophy and 36 controls with genotype data, we identified 439 expression Quantitative Trait (eQTL) loci in cis that were associated with disease status and specific to subpopulations of RPE cells. We identified loci linked to two genes with known associations with geographic atrophy - PILRB and PRPH2, in addition to 43 genes with significant genotype x disease interactions that are candidates for novel genetic associations for geographic atrophy. On a transcriptome-only level, we identified molecular pathways significantly upregulated in geographic atrophy-RPE including in mitochondrial functions, metabolic pathways, and extracellular cellular matrix reorganisation. We subsequently implemented a large-scale proteomics analysis, confirming modification in proteins associated with these pathways. We also identified six significant protein (p) QTL that regulate protein expression in the RPE cells and in geographic atrophy - two of which share variants with cis-eQTL, including proteins involve in mitochondrial biology and neuodegeneration. Investigation of mitochondrial functions in the two cohorts confirmed a modification of respiration etc…. This study provides strong proof of concept of the validity of using iPSC for the modeling of complex diseases. It is the first to use a large scale patient -derived iPSC cohort to uncover important differences in RPE homeostasis associated with geographic atrophy. It clearly identifies mitochondrial activity as a core constitutive difference of the RPE from patients with geographic atrophy, and could be a target of potential therapies for this condition (STACEY/MATT).
2022-06-01 | PXD029501 | Pride
Project description:Elucidating the genetic basis underlying the variation in hepatic gene expression is of importance to understand disease etiology and drug metabolism variances. To date, no genome-wide eQTL analysis has been conducted in the Han Chinese, the largest ethnic group in the world. We performed a genome-wide eQTL mapping in a set of Han Chinese liver tissue (n=64). Normal (non-diseased) liver tissues were previously collected from 64 Chinese donors who provided informed consent. All samples were stored frozen at -80M-bM-^DM-^C from collection until processing for RNA and DNA extraction. DNA /Total RNA of the human liver tissue samples were extracted by using the RNA/DNA Mini Kit (Qiagen, Hilden, Germany).each RNA sample were labeled and hybridized to the One-Color Agilent 60-mer Whole Human Genome Microarray (G4112F, GPL4133) at the Agilent Microarray Facility of Shanghai genomePilot Technology, Inc. The genome-wide scan was performed using the Affymetrix Genome-Wide Human SNP Array 6.0. We tested all expression traits for their associations with each of the QC passed SNPs using PLINK's assoc function for quantitative traits, which correlates allele dosage with changes in the trait.
2015-01-02 | E-GEOD-53791 | biostudies-arrayexpress