Allele specific gene expression in tissue
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE54252 | GEO | 2014/11/07
SECONDARY ACCESSION(S): PRJNA236052
REPOSITORIES: GEO
Similar Datasets
Project description:Most loci contributing to breast cancer susceptibility identified by the recent genome-wide association studies (GWAS) are predicted to have a regulatory function. Additionally, the early phases of the GWAS studies have generated long lists of possible candidates that need to be prioritised for follow-up studies. Integration of allelic expression mapping and disease association data should enable the identification of those GWAS hits with higher cis-regulatory potential. Our aims are (1) to assess how well functional data and disease risk are correlated and (2) to help prioritise and select the strongest candidates from the GWAS scan for further follow-up and functional analysis. We are performing genome-wide differential allelic expression (DAE) analysis to identify loci with cis-regulatory potential in sixty-four normal breast tissue samples. Using the Illumina Exon510S-Duo BeadChips, we have identified 34K informative SNPs of which approximately 8K (23.5%) displayed DAE. Two SNPs showed monoallelic expression suggesting possible new imprinted loci. We are mapping the cis-regulatory loci by fitting a linear regression model with permutations to DAE ratios vs genotype at SNPs within ±250kb of the RefSeq gene corresponding to the DAE SNP. We will combine our data with the UK GWAS1 and GWAS2 studies for breast cancer susceptibility, to generate a list of genes that show regulatory variation for further evaluation as candidates. This is the first genome-wide differential allelic expression study in normal breast tissue, and one of the first in a primary tissue. We predict that this will be a powerful approach to validate/identify susceptibility loci and to unravel some of the biology underlying breast cancer susceptibility. Allelic gene expression of normal breast sample from healthy controls.
2012-05-02 | E-GEOD-35023 | biostudies-arrayexpress
Project description:Most loci contributing to breast cancer susceptibility identified by the recent genome-wide association studies (GWAS) are predicted to have a regulatory function. Additionally, the early phases of the GWAS studies have generated long lists of possible candidates that need to be prioritised for follow-up studies. Integration of allelic expression mapping and disease association data should enable the identification of those GWAS hits with higher cis-regulatory potential. Our aims are (1) to assess how well functional data and disease risk are correlated and (2) to help prioritise and select the strongest candidates from the GWAS scan for further follow-up and functional analysis. We are performing genome-wide differential allelic expression (DAE) analysis to identify loci with cis-regulatory potential in sixty-four normal breast tissue samples. Using the Illumina Exon510S-Duo BeadChips, we have identified 34K informative SNPs of which approximately 8K (23.5%) displayed DAE. Two SNPs showed monoallelic expression suggesting possible new imprinted loci. We are mapping the cis-regulatory loci by fitting a linear regression model with permutations to DAE ratios vs genotype at SNPs within ±250kb of the RefSeq gene corresponding to the DAE SNP. We will combine our data with the UK GWAS1 and GWAS2 studies for breast cancer susceptibility, to generate a list of genes that show regulatory variation for further evaluation as candidates. This is the first genome-wide differential allelic expression study in normal breast tissue, and one of the first in a primary tissue. We predict that this will be a powerful approach to validate/identify susceptibility loci and to unravel some of the biology underlying breast cancer susceptibility.
2012-05-03 | GSE35023 | GEO
Project description:Most variants associated to diseases are located in non-coding regions of the genome, and are thought to be regulatory in nature. Cis-regulatory SNPs (cis-rSNPs) impacting transcription can be identified through the mapping of differences in allelic expression (AE). We mapped common cis-rSNPs of protein coding and non-coding genes in 3 distinct cell-types. We show 70% sharing across tissues and similar genetically controlled transcription for protein-coding genes and lincRNAs. Candidate cis-rSNPs altering the expression of 42 non-coding RNA overlap SNPs underlying GWAS associations for 39 diseases. We uncover a new class of cis-rSNPs leading to disruption of footprint-derived de novo motifs, predominantly bind by repressive factors and implicated in disease susceptibility through overlaps with GWAS SNPs. Finally, we provide proof-of-principle for a new approach for genome-wide functional validation of transcription factor M-bM-^@M-^S SNP interactions. We perturbed NFM-NM-:B action in lymphoblasts and identified 489 cis-regulated transcripts with altered AE after NFkB perturbation. Altogether, we performed a comprehensive analysis of cis-variation in four cell-populations, and provide new tools for the identification of functional variants associated to complex diseases. Mapping cis-rSNPs across 3 distinct cell types in humans
2014-11-03 | E-GEOD-53837 | biostudies-arrayexpress
Project description:Most variants associated to diseases are located in non-coding regions of the genome, and are thought to be regulatory in nature. Cis-regulatory SNPs (cis-rSNPs) impacting transcription can be identified through the mapping of differences in allelic expression (AE). We mapped common cis-rSNPs of protein coding and non-coding genes in 3 distinct cell-types. We show 70% sharing across tissues and similar genetically controlled transcription for protein-coding genes and lincRNAs. Candidate cis-rSNPs altering the expression of 42 non-coding RNA overlap SNPs underlying GWAS associations for 39 diseases. We uncover a new class of cis-rSNPs leading to disruption of footprint-derived de novo motifs, predominantly bind by repressive factors and implicated in disease susceptibility through overlaps with GWAS SNPs. Finally, we provide proof-of-principle for a new approach for genome-wide functional validation of transcription factor – SNP interactions. We perturbed NFκB action in lymphoblasts and identified 489 cis-regulated transcripts with altered AE after NFkB perturbation. Altogether, we performed a comprehensive analysis of cis-variation in four cell-populations, and provide new tools for the identification of functional variants associated to complex diseases.
2014-11-03 | GSE53837 | GEO
Project description:Introduction: Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism. Methods: We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in-silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analysed in-vitro and in-vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2754 carriers. Results: We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterised three cis-regulatory SNPs located at the promoter and two intronic regulatory elements, which affect the binding of the transcription factors C/EBPα, HMGA1, DBP and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele HR=0.85, 95%CI=0.72-1.00, P-trend=0.048). Conclusion: Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2, which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele. Total gene expression of normal breast sample from healthy controls. This submission represents transcriptome component of study.
2012-02-01 | E-GEOD-32124 | biostudies-arrayexpress
Project description:Introduction: Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism. Methods: We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in-silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analysed in-vitro and in-vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2754 carriers. Results: We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterised three cis-regulatory SNPs located at the promoter and two intronic regulatory elements, which affect the binding of the transcription factors C/EBPα, HMGA1, DBP and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele HR=0.85, 95%CI=0.72-1.00, P-trend=0.048). Conclusion: Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2, which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele. Genotype of normal breast sample from healthy controls.
2012-02-01 | E-GEOD-32258 | biostudies-arrayexpress
Project description:Next-generation sequencing has become an important tool for genome-wide quantification of DNA and RNA. However, a major technical hurdle lies in the need to map short sequence reads back to their correct locations in a reference genome. Here we investigate the impact of SNP variation on the reliability of read-mapping in the context of detecting allele-specific expression (ASE).We generated sixteen million 35 bp reads from mRNA of each of two HapMap Yoruba individuals. When we mapped these reads to the human genome we found that, at heterozygous SNPs, there was a significant bias towards higher mapping rates of the allele in the reference sequence, compared to the alternative allele. Masking known SNP positions in the genome sequence eliminated the reference bias but, surprisingly, did not lead to more reliable results overall. We find that even after masking, $\sim$5-10\% of SNPs still have an inherent bias towards more effective mapping of one allele. Filtering out inherently biased SNPs removes 40\% of the top signals of ASE. The remaining SNPs showing ASE are enriched in genes previously known to harbor cis-regulatory variation or known to show uniparental imprinting. Our results have implications for a variety of applications involving detection of alternate alleles from short-read sequence data. Scripts, written in Perl and R, for simulating short reads, masking SNP variation in a reference genome, and analyzing the simulation output are available upon request from JFD. RNA-Seq on two YRI Hapmap cell lines. Each individual sequenced on two lanes of the Illumina Genome Analyzer
2009-10-22 | E-GEOD-18156 | biostudies-arrayexpress
Project description:Multiple regulatory layers influence allele-specific expression (ASE), particularly through sequence-dependent and parent-of-origin-dependent mechanisms at the transcriptional level. However, little is known about allele-specific gene regulation at the post-transcriptional level. Here, we conduct transcriptome-wide analysis of allele-specific m6A in mice. Using early postnatal cerebellum and cerebrum samples from reciprocal crosses of two divergent mouse strains, we employed quantitative m6A assays to measure allelic differences in m6A at single-base resolution. Our study reveals widespread sequence-dependent allelic imbalance in m6A methylation, identifying thousands of allele-specific m6A (ASm6A) sites with statistically significant and reproducible allelic methylation differences across diverse samples. We find evidence of potential cis-regulatory variants within 50-nt flanking regions of these ASm6A sites, with the highest enrichment at the motif positions. Intriguingly, we detect parental effects on allelic methylation across m6A sites exhibiting parent-of-origin-dependent ASE. For both sequence- and parent-of-origin-dependent allelic m6A methylation, we observe opposing allelic preferences between methylation and expression, suggesting a potential role of ASm6A in regulating ASE through negative effects on gene expression. Overall, our findings reveal that both cis-acting and parent-of-origin effects influence ASm6A, offering new insights into post-transcriptional mechanisms of ASE regulation.
2024-04-26 | GSE265978 | GEO
Project description:Genotyping 323 Europeans in order to perform cis-eQTL analysis in 9 tissue cell types. Identification of regulatory modules across genes and tissues on the basis of correlated SNPs in expression associated patterns. Integration of cis-eQTLs regulatory modules with known 200 IBD loci.
2018-04-28 | E-MTAB-6666 | biostudies-arrayexpress
Project description:Multiple regulatory layers influence allele-specific expression (ASE), particularly through sequence-dependent and parent-of-origin-dependent mechanisms at the transcriptional level. However, little is known about allele-specific gene regulation at the post-transcriptional level. Here, we conduct transcriptome-wide analysis of allele-specific m6A in mice. Using early postnatal cerebellum and cerebrum samples from reciprocal crosses of two divergent mouse strains, we employed quantitative m6A assays to measure allelic differences in m6A at single-base resolution. Our study reveals widespread sequence-dependent allelic imbalance in m6A methylation, identifying thousands of allele-specific m6A (ASm6A) sites with statistically significant and reproducible allelic methylation differences across diverse samples. We find evidence of potential cis-regulatory variants within 50-nt flanking regions of these ASm6A sites, with the highest enrichment at the motif positions. Intriguingly, we detect parental effects on allelic methylation across m6A sites exhibiting parent-of-origin-dependent ASE. For both sequence- and parent-of-origin-dependent allelic m6A methylation, we observe opposing allelic preferences between methylation and expression, suggesting a potential role of ASm6A in regulating ASE through negative effects on gene expression. Overall, our findings reveal that both cis-acting and parent-of-origin effects influence ASm6A, offering new insights into post-transcriptional mechanisms of ASE regulation.
2024-04-26 | GSE265977 | GEO