Transcriptomics of whole brain tissue in heterogeneous stock rats
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ABSTRACT:
ORGANISM(S): Rattus norvegicus
PROVIDER: GSE319591 | GEO | 2026/02/18
REPOSITORIES: GEO
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Project description:Genome-wide association studies (GWASs) have identified many sources of genetic variation associated with bone mineral density (BMD), a clinical predictor of fracture risk and osteoporosis. Aside from the identification of causal genes, other difficult challenges to informing GWAS include characterizing the roles of predicted causal genes in disease and providing additional functional context, such as the cell type predictions or biological pathways in which causal genes operate. Leveraging single-cell transcriptomics (scRNA-seq) can assist in informing BMD GWAS by linking disease-associated variants to genes and providing a cell type context for which these causal genes drive disease. Here, we use large-scale scRNA-seq data from bone marrow–derived stromal cells cultured under osteogenic conditions (BMSC-OBs) from Diversity Outbred (DO) mice to generate cell type-specific networks and contextualize BMD GWAS-implicated genes. Using trajectories inferred from the scRNA-seq data, we identify networks enriched with genes that exhibit the most dynamic changes in expression across trajectories. We discover 21 network driver genes, which are likely to be causal for human BMD GWAS associations that colocalize with expression/splicing quantitative trait loci (eQTL/sQTL). These driver genes, including Fgfrl1 and Tpx2, along with their associated networks, are predicted to be novel regulators of BMD via their roles in the differentiation of mesenchymal lineage cells. In this work, we showcase the use of single-cell transcriptomics from mouse bone-relevant cells to inform human BMD GWAS and prioritize genetic targets with potential causal roles in the development of osteoporosis.
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Project description:Bicuspid aortic valve (BAV) is a frequent congenital heart defect with a high heritability. Identification of genes associated with the disease and the molecular mechanisms required genetic studies including genome-wide association studies (GWAS) meta-analysis. To prioritize genes identified through such meta-analysis several additional data are required including transcriptomic of aortic valve at early fetal and adult stages. RNA-sequencing was carried out on human fœtal aortic valves at 9, 13, and 22 post conceptional week (PCW) and adult controls. These data were used to compare gene expression profile of several genes identified in a GWAS meta-analysis. Comparing the expression of these genes in valve RNA-sequencing dataset we identified several genes with higher expression in fœtal tissues suggesting their involvement in aortic valve development. In conclusion, we performed integrative analyses taking advantage of human aortic valve transcriptome data to prioritize candidate causal gene of BAV.
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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: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.
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Project description:Reliably generating rice varieties with low glycemic index (GI) is an important nutritional intervention given the high rates of Type II diabetes incidences in Asia where rice is staple diet. We integrated a genome-wide association study (GWAS) with a transcriptome-wide association study (TWAS) to determine the genetic basis of the GI in rice. GWAS utilized 305 re-sequenced diverse indica panel comprising ~2.4 million single nucleotide polymorphisms (SNPs) enriched in genic regions. A novel association signal was detected at a synonymous SNP in exon 2 of LOC_Os05g03600 for intermediate-to-high GI phenotypic variation. Another major hotspot region was predicted for contributing intermediate-to-high GI variation, involves 26 genes on chromosome 6 (GI6.1). These set of genes included GBSSI, two hydrolase genes, genes involved in signalling and chromatin modification. The TWAS and methylome sequencing data revealed cis-acting functionally relevant genetic variants with differential methylation patterns in the hot spot GI6.1 region, narrowing the target to 13 genes. Conversely, the promoter region of GBSSI and its alternative splicing allele (G allele of Wxa) explained the intermediate-to-high GI variation. A SNP (C>T) at exon-10 was also highlighted in the preceding analyses to influence final viscosity (FV), which is independent of amylose content/GI. The low GI line with GC haplotype confirmed soft texture, while other two low GI lines with GT haplotype were characterized as hard and cohesive. The low GI lines were further confirmed through clinical in vivo studies. Gene regulatory network analysis highlighted the role of the non‑starch polysaccharide pathway in lowering GI.
2019-02-01 | GSE123616 | GEO
Project description:Coronary artery disease (CAD) is the leading cause of mortality and morbidity driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with CAD and myocardial infarction (MI) susceptibility in multi-ethnic populations. The majority of these variants reside in non-coding regulatory regions and are co-inherited with hundreds of candidate regulatory SNPs. Herein, we use integrative genomic, epigenomic, and transcriptomic fine-mapping in human coronary artery smooth muscle cells (HCASMC) and tissues to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps we prioritize 65 candidate variants and perform allele-specific binding and expression analyses on 7 top candidates. We validate our findings in two independent cohorts of diseased human arterial expression quantitative trait loci (eQTL), which together demonstrate fundamental links between CAD associations and regulatory function in the appropriate disease context.
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Project description:Background: The identification of causal variants responsible for disease associations from genome-wide association studies (GWAS) facilitates functional understanding of the disease mechanisms implicated by GWAS. One of the earliest GWAS associations to COPD spans an intragenic region within FAM13A, but the causal variants at this loci have not yet been identified. Massively parallel reporter assays (MPRA) can be used to prioritize functional regulatory variants in a high-throughput manner. Methods: We used an integrated approach using fine-mapping in over 10,000 subjects from COPD GWAS studies, two MPRA experiments, traditional reporter assays, chromatin conformation capture, and CRISPR-based gene editing to characterize COPD-associated regulatory variants in FAM13A in human bronchial epithelial cell lines. Results: Conditional genetic association and fine mapping analyses identified two independent COPD association signals in FAM13A. MPRA identified 45 common functional regulatory variants, and six COPD-associated putative functional variants were prioritized for further functional investigation. Three variants demonstrated significant activity in traditional reporter assays, and one variant, rs2013701, was selected for further testing in the endogenous genomic context based on a direction of effect consistent with postulated mechanisms of FAM13A-mediated COPD susceptibility. CRISPR-based genome editing for this variant confirmed allele-specific effects on FAM13A expression and altered rates of cellular proliferation, providing multiple levels of functional characterization for this COPD-associated variant. Conclusions: Comprehensive screening for regulatory variants near FAM13A identified the presence of extensive functional regulatory variation within a 250kb window of FAM13A in HBECs. Focused functional evaluation of the COPD-associated functional variants in LD with the two independent association signals in this region prioritized the common variant rs2013701, for which multiple parallel lines of functional evidence confirm allelic effects on FAM13A regulation.
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Project description:Genome-wide association studies (GWAS) have identified thousands of genomic loci associated with a variety of common, complex human traits. The contribution of genetic variants to gene expression regulation has been well studied, supporting the idea that gene expression plays a causal role at some complex trait-associated loci. However, many current studies have not comprehensively investigated the impact of genetic variation on chromatin accessibility at a large scale within a single tissue. Genetic variants associated with differences in chromatin accessibility, known as chromatin accessibility quantitative trait loci (caQTLs), are major contributors to gene expression differences and GWAS signals. We assessed chromatin accessibility in 189 human liver tissue samples using ATAC-seq and identified over two million accessible chromatin regions enriched for gene regulatory characteristics. We integrated chromatin accessibility and genotype data from 175 samples and identified 14,076 caQTLs. Using publicly available blood lipid GWAS data, we found 157 loci where the colocalization of caQTLs, expression quantitative trait loci (eQTLs), and GWAS signals generated specific molecular hypotheses about causal regulatory elements, affected genes, and, in some cases, transcription factors, resolving these associations to single-nucleotide resolution. We performed a comprehensive analysis of the GWAS signals that remain without a proposed mechanism beyond liver caQTLs and eQTLs. After incorporating additional potential regulatory mechanism data, we found that approximately 26% of blood lipid GWAS signals remain without a proposed mechanism. Overall, our results demonstrate the benefits of integrating multiple datasets to improve our understanding of GWAS signals while emphasizing the need for additional experiments to fully characterize them.
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Project description:Genetic variation modulating risk of sporadic Parkinson’s disease (PD) has been primarily explored through genome wide association studies (GWAS). However, like many other common genetic diseases, the impacted genes remain largely unknown. Here, we used single-cell RNA-seq to characterize dopaminergic (DA) neuron populations in the mouse brain at embryonic and early postnatal timepoints. These data facilitated unbiased identification of DA neuron subpopulations through their unique transcriptional profiles, including a novel postnatal neuroblast population and substantia nigra (SN) DA neurons. We use these population-specific data to develop a scoring system to prioritize candidate genes in all 49 GWAS intervals implicated in PD risk, including known PD genes and many with extensive supporting literature. As proof of principle, we confirm that the nigrostriatal pathway is compromised in Cplx1 null mice. Ultimately, this systematic approach establishes biologically pertinent candidates and testable hypotheses for sporadic PD, informing a new era of PD genetic research.
2018-01-31 | GSE108020 | GEO