Ontology highlight
ABSTRACT:
PROVIDER: PRJNA679966 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13104481.fastq.gz | Fastqsanger.gz | |||
| SRR13104482.fastq.gz | Fastqsanger.gz | |||
| SRR13104483.fastq.gz | Fastqsanger.gz | |||
| SRR13104484.fastq.gz | Fastqsanger.gz | |||
| SRR13104485.fastq.gz | Fastqsanger.gz |
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Project description:Genome-wide association studies (GWAS) have identified multiple lung cancer risk loci including those that are distinct in the major histological types. However, most of these loci have not been functionally characterized. Here we employed massively parallel reporter assays (MPRA) to assess allelic transcriptional activity of risk-associated variants en masse. We tested 2,245 variants in 42 loci from 3 recent GWASs of East Asian and European populations in the context of lung adenocarcinoma and squamous cell carcinoma cells while incorporating exposure to a tobacco-smoke carcinogen, benzo[a]pyrene. At FDR < 0.01, we identified 844 MPRA-significant variants with allelic transcriptional activity across 88% of lung cancer loci. Further variant scoring using lung-specific epigenomic annotation demonstrated that 63% of the loci harbored multiple equally functional variants in linkage disequilibrium. Cell-type-specific variants were observed in 72% of the loci, a subset of which aligned with histology-specific association in the GWAS. Distinct subsets of transcription factors were predicted to bind to cell-type-specific variants and those affecting multiple GWAS loci in trans. Linking MPRA-significant variants to target genes based on four different approaches identified candidate susceptibility genes including essential genes for lung cancer cell growth. CRISPR-interference of a high-scoring MPRA-significant variant validated multiple variant-gene connections from different datasets, including RTEL1, SOX18, and ARFRP1. Our data provide a comprehensive catalog of functional characterization of lung cancer GWAS loci and the molecular basis of heterogeneity and polygenicity of lung cancer susceptibility.
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Project description:The most recent genome-wide association study (GWAS) of cutaneous melanoma identified 54 risk-associated loci, but functional variants and their target genes for most have not been established. Here, we performed massively parallel reporter assays (MPRA) using malignant melanoma and normal melanocyte cells and further integrated multi-layer annotation to systematically prioritize functional variants and susceptibility genes from these GWAS loci. Of 1,992 risk-associated variants tested in MPRA, we identified 285 from 42 loci (78% of the known loci) displaying significant allelic transcriptional activities in either cell type (FDR < 1%). We further characterized MPRA-significant variants by motif prediction, epigenomic annotation, and statistical/functional fine-mapping to create integrative variant scores, which prioritized one to six plausible candidate variants per locus for the 42 loci and nominated a single variant for 43% of these loci. Overlaying the MPRA-significant variants with genome-wide significant expression or methylation quantitative trait loci (QTLs) from melanocytes or melanomas identified candidate susceptibility genes for 60% of variants (172 of 285 variants). CRISPRi of top-scoring variants validated their cis-regulatory effect on the eQTL target genes, MAFF (22q13.1) and GPRC5A (12p13.1). Finally, we identified 36 melanoma-specific and 45 melanocyte-specific MPRA-significant variants, a subset of which are linked to cell-type-specific target genes. Analyses of transcription factor availability in MPRA datasets and variant-transcription factor interaction in eQTL datasets highlighted the roles of transcription factors in cell-type-specific variant functionality. In conclusion, MPRA along with variant scoring effectively prioritized plausible candidates for most melanoma GWAS loci and highlighted cellular contexts where the susceptibility variants are functional.
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Project description:The most recent genome-wide association study (GWAS) of cutaneous melanoma identified 54 risk-associated loci, but functional variants and their target genes for most have not been established. Here, we performed massively parallel reporter assays (MPRA) using malignant melanoma and normal melanocyte cells and further integrated multi-layer annotation to systematically prioritize functional variants and susceptibility genes from these GWAS loci. Of 1,992 risk-associated variants tested in MPRA, we identified 285 from 42 loci (78% of the known loci) displaying significant allelic transcriptional activities in either cell type (FDR < 1%). We further characterized MPRA-significant variants by motif prediction, epigenomic annotation, and statistical/functional fine-mapping to create integrative variant scores, which prioritized one to six plausible candidate variants per locus for the 42 loci and nominated a single variant for 43% of these loci. Overlaying the MPRA-significant variants with genome-wide significant expression or methylation quantitative trait loci (QTLs) from melanocytes or melanomas identified candidate susceptibility genes for 60% of variants (172 of 285 variants). CRISPRi of top-scoring variants validated their cis-regulatory effect on the eQTL target genes, MAFF (22q13.1) and GPRC5A (12p13.1). Finally, we identified 36 melanoma-specific and 45 melanocyte-specific MPRA-significant variants, a subset of which are linked to cell-type-specific target genes. Analyses of transcription factor availability in MPRA datasets and variant-transcription factor interaction in eQTL datasets highlighted the roles of transcription factors in cell-type-specific variant functionality. In conclusion, MPRA along with variant scoring effectively prioritized plausible candidates for most melanoma GWAS loci and highlighted cellular contexts where the susceptibility variants are functional.
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Project description:Genome-wide association studies (GWAS) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium (LD) makes it challenging to discern causal variants. Computational finemapping prioritized thousands of credible variants, ~98% of which lie within poorly characterized non-coding regions. To functionally validate their regulatory effects, we performed a massively parallel reporter assay (MPRA) on 5,173 finemapped schizophrenia GWAS variants in primary human neural progenitors (HNPs). We identified 440 variants with allelic regulatory effects (MPRA-positive variants), with 72% of GWAS loci containing at least one MPRA-positive variant. Transcription factor binding had modest predictive power for predicting the allelic activity of MPRA-positive variants, while GWAS association, finemap posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit eQTL signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. MPRA-positive variants differed from eQTLs, as they were more frequently located in distal neuronal enhancers. Therefore, we leveraged neuronal 3D chromatin architecture to identify 273 genes that physically interact with MPRA-positive variants. These genes annotated by chromatin interactome displayed higher mutational constraints and regulatory complexity than genes annotated by eQTLs, recapitulating a recent finding that eQTL- and GWAS-detected variants map to genes with different properties. Finally, we propose a model in which allelic activity of multiple variants within a GWAS locus can be aggregated to predict gene expression by taking chromatin contact frequency and accessibility into account. In conclusion, we demonstrate that MPRA can effectively identify functional regulatory variants and delineate previously unknown regulatory principles of schizophrenia.
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Project description:We designed a massively parallel reporter assay (MPRA) in an Epstein-Barr virus transformed B cell line to directly characterize the potential for histone post-translational modifications, i.e., histone quantitative trait loci (hQTLs), expression QTLs (eQTLs), and variants on SLE and autoimmune (AI) disease risk haplotypes to modulate regulatory activity in an allele dependent manner. Our study demonstrates that hQTLs, as a group, are more likely to modulate regulatory activity in an MPRA compared to other variant classes tested, including a set of eQTLs previously shown to interact with hQTLs and tested AI risk variants. In addition, we nominate 17 variants (including 11 previously unreported) as putative causal variants for SLE and another 14 for various other AI diseases, prioritizing these variants for future functional studies primary and immortalized B cells. Thus, we uncover important insights into the mechanistic relationships between genotype, epigenetics, and gene expression in SLE and AI disease phenotypes.
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Project description:Performing GWAS on multiple myeloma in relation to the development of the toxicity neuropathy. This set was used as validation set. We performed a genome-wide association study using Affymetrix HD-SNP arrays 6.0 to identify risk variants for developing bortezomib-induced peripheral neuropathy (BiPN) in 469 multiple myeloma (MM) patients who received bortezomib-dexamethasone therapy prior to autologous stem-cell transplantation and conducted validation in an independent cohort of 116 MM patients. We identified one previously unreported BiPN risk locus at 21q22.3 (rs2839629, PKNOX1; OR = 0.53, 95% CI: [0.40-0.69]). PKNOX1 is known to regulate MCP-1, a potent mediator of chemotherapy-induced peripheral neuropathy. rs2839629 is in strong linkage disequilibrium ( r2 = 0.87) with rs915854, localized 6.5kb centromeric to CBS encoding endogenous H2S-producing enzyme. CBS-H2S signalling pathway is implicated in the pathogenesis of a variety of neurodegenerative and inflammatory disorders, and specifically in neuropathy models. Our data provide conclusive evidence for genetic susceptibility to BiPN in MM and new potential targets in neuro-protective strategies of treatment.
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Project description:Multiple Myeloma Genomic Study (MMGS)
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