Interventions with HMb and MMb mice
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB23029 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR2173820.fastq.gz | Fastqsanger.gz | |||
| ERR2173830.fastq.gz | Fastqsanger.gz | |||
| ERR2173840.fastq.gz | Fastqsanger.gz | |||
| ERR2173850.fastq.gz | Fastqsanger.gz | |||
| ERR2173821.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 38 |
Similar Datasets
Project description:Genome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we used Diversity Outbred (DO) mice to directly address these limitations by performing the first systems genetics analysis of over 50 complex skeletal phenotypes. We applied a network approach to cortical bone RNA-seq data to discover 46 genes likely to be causal for human BMD GWAS associations, including the novel genes SERTAD4 and GLT8D2. We also performed GWAS in the DO for a wide-range of bone traits and identify Qsox1 as a novel gene influencing cortical bone accrual and bone strength. Our results provide a new perspective on the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.
2020-06-20 | GSE152806 | GEO
Project description:Genome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we used Diversity Outbred (DO) mice to directly address these limitations by performing the first systems genetics analysis of over 50 complex skeletal phenotypes. We applied a network approach to cortical bone RNA-seq data to discover 46 genes likely to be causal for human BMD GWAS associations, including the novel genes SERTAD4 and GLT8D2. We also performed GWAS in the DO for a wide-range of bone traits and identify Qsox1 as a novel gene influencing cortical bone accrual and bone strength. Our results provide a new perspective on the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.
2020-06-18 | GSE152708 | GEO
Project description:To date, genome-wide association studies (GWAS) have revealed over 200 genetic risk loci associated with prostate cancer; yet, true disease-causing variants in gene regulatory regions remain elusive. Identification of causal variants and their targets from association signals relevant to prostate cancer is complicated by high linkage disequilibrium and limited availability of functional genomics data for specific tissue/cell types. Here, we integrated statistical fine-mapping and functional annotation from prostate-specific epigenomic profiles, high resolution 3D genome features, and quantitative trait loci data to distinguish causal variants from associations and identify target genes they regulate. Our fine-mapping analysis yielded 1,892 likely causal variants, and multiscale functional annotation linked them to 406 target genes. We prioritized rs10486567, located in an enhancer, as a genome-wide top-ranked SNP and predicted HOTTIP as its target. Deletion of the rs10486567-associated enhancer in prostate cancer cells decreased their capacity for invasive migration. HOTTIP overexpression in an enhancer-KO cell line rescued defective invasive migration. Furthermore, we found that rs10486567 regulates HOTTIP through allele-specific long- range chromatin interaction.
2023-02-25 | GSE197819 | GEO
Project description:To date, genome-wide association studies (GWAS) have revealed over 200 genetic risk loci associated with prostate cancer; yet, true disease-causing variants in gene regulatory regions remain elusive. Identification of causal variants and their targets from association signals relevant to prostate cancer is complicated by high linkage disequilibrium and limited availability of functional genomics data for specific tissue/cell types. Here, we integrated statistical fine-mapping and functional annotation from prostate-specific epigenomic profiles, high resolution 3D genome features, and quantitative trait loci data to distinguish causal variants from associations and identify target genes they regulate. Our fine-mapping analysis yielded 1,892 likely causal variants, and multiscale functional annotation linked them to 406 target genes. We prioritized rs10486567, located in an enhancer, as a genome-wide top-ranked SNP and predicted HOTTIP as its target. Deletion of the rs10486567-associated enhancer in prostate cancer cells decreased their capacity for invasive migration. HOTTIP overexpression in an enhancer-KO cell line rescued defective invasive migration. Furthermore, we found that rs10486567 regulates HOTTIP through allele-specific long- range chromatin interaction.
2023-02-25 | GSE197818 | GEO
Project description:To date, genome-wide association studies (GWAS) have revealed over 200 genetic risk loci associated with prostate cancer; yet, true disease-causing variants in gene regulatory regions remain elusive. Identification of causal variants and their targets from association signals relevant to prostate cancer is complicated by high linkage disequilibrium and limited availability of functional genomics data for specific tissue/cell types. Here, we integrated statistical fine-mapping and functional annotation from prostate-specific epigenomic profiles, high resolution 3D genome features, and quantitative trait loci data to distinguish causal variants from associations and identify target genes they regulate. Our fine-mapping analysis yielded 1,892 likely causal variants, and multiscale functional annotation linked them to 406 target genes. We prioritized rs10486567, located in an enhancer, as a genome-wide top-ranked SNP and predicted HOTTIP as its target. Deletion of the rs10486567-associated enhancer in prostate cancer cells decreased their capacity for invasive migration. HOTTIP overexpression in an enhancer-KO cell line rescued defective invasive migration. Furthermore, we found that rs10486567 regulates HOTTIP through allele-specific long- range chromatin interaction.
2023-02-25 | GSE197817 | GEO
Project description:To date, genome-wide association studies (GWAS) have revealed over 200 genetic risk loci associated with prostate cancer; yet, true disease-causing variants in gene regulatory regions remain elusive. Identification of causal variants and their targets from association signals relevant to prostate cancer is complicated by high linkage disequilibrium and limited availability of functional genomics data for specific tissue/cell types. Here, we integrated statistical fine-mapping and functional annotation from prostate-specific epigenomic profiles, high resolution 3D genome features, and quantitative trait loci data to distinguish causal variants from associations and identify target genes they regulate. Our fine-mapping analysis yielded 1,892 likely causal variants, and multiscale functional annotation linked them to 406 target genes. We prioritized rs10486567, located in an enhancer, as a genome-wide top-ranked SNP and predicted HOTTIP as its target. Deletion of the rs10486567-associated enhancer in prostate cancer cells decreased their capacity for invasive migration. HOTTIP overexpression in an enhancer-KO cell line rescued defective invasive migration. Furthermore, we found that rs10486567 regulates HOTTIP through allele-specific long- range chromatin interaction.
2023-02-25 | GSE197816 | GEO
Project description:Purpose: Genome wide association studies (GWAS) have identified 14 loci for atrial fibrillation, but the mechanisms responsible for these associations as well as the causal genetic variants remain enigmatic. Genetic variants altering expression levels of nearby genes is one such plausible mechanism.
2015-06-16 | GSE69890 | GEO
Project description:Identifying potential polymicrobial pathogens: Moving beyond differential abundance to driver species
| PRJDB9133 | ENA
Project description:Precise identification of causal variants within credible intervals of eQTL associations is needed to identify regulatory GWAS variants. We show that CROPseq, namely multiplex CRISPR-Cas9 genome editing combined with single cell RNAseq, is a viable strategy for fine mapping regulatory SNPs. Mutations were induced nearby 67 SNPs in three genes, two of which, rs2251039 and rs17523802, significantly altered CISD1 and PARK7 expression, respectively, and overlap with chromatin accessibility peaks.
2019-11-28 | GSE140553 | GEO
Project description:Multiple causal variants underlie genetic associations in humans
| PRJNA730497 | ENA