Whole genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes
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ABSTRACT:
PROVIDER: EGAS00001004379 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:<p>Non-coding elements in our genomes that play critical roles in complex disease are frequently marked by highly unstable RNA species. Sequencing nascent RNAs attached to an actively transcribing RNA polymerase complex can identify unstable RNAs, including those templated from gene-distal enhancers (eRNAs). However, nascent RNA sequencing techniques remain challenging to apply in some cell lines and especially to intact tissues, limiting broad applications in fields such as cancer genomics and personalized medicine. Here we report the development of chromatin run-on and sequencing (ChRO-seq), a novel run-on technology that maps the location of RNA polymerase using virtually any frozen tissue sample, including samples with degraded RNA that are intractable to conventional RNA-seq. We used ChRO-seq to develop the first maps of nascent transcription in 23 human glioblastoma (GBM) brain tumors and patient derived xenografts. Remarkably, >90,000 distal enhancers discovered using the signature of eRNA biogenesis within primary GBMs closely resemble those found in the normal human brain, and diverge substantially from GBM cell models. Despite extensive overall similarity, 12% of enhancers in each GBM distinguish normal and malignant brain tissue. These enhancers drive regulatory programs similar to the developing nervous system and are enriched for transcription factor binding sites that specify a stem-like cell fate. These results demonstrate that GBMs largely retain the enhancer landscape associated with their tissue of origin, but selectively adopt regulatory programs that are responsible for driving stem-like cell properties. We also identified enhancers and their associated transcription factors that regulate genes characteristic of each known GBM subtype, and discovered a core group of transcription factors that control the expression of genes associated with clinical outcomes. This study uncovers new insights into the molecular etiology of GBM and introduces ChRO-seq which can now be used to map regulatory programs contributing to a variety of complex diseases.</p>
| phs001646 | dbGaP
Project description:Understanding the regulatory landscape of the human genome is a central question in complex trait genetics. Most single nucleotide polymorphisms (SNPs) associated with cancer risk lie in non protein-coding regions, implicating regulatory DNA elements as functional targets of susceptibility variants. Here, we describe genome-wide annotation of regions of open chromatin and histone modification in fallopian tube and ovarian surface epithelial cells (FTSECs, OSECs), the debated cellular origins of high-grade serous ovarian cancers (HGSOCs), and in endometriosis epithelial cells (EECs), the likely precursor of clear cell ovarian carcinomas (CCOCs). The regulatory architecture of these cell types was compared to normal human mammary epithelial cells (HMECs) and LNCaP prostate cancer cells. We observed similar positional patterns of global enhancer signatures across the three different ovarian cancer precursor cell types, and evidence of tissues specific regulatory signatures to non-gynecological cell types. We found significant enrichment for risk-associated SNPs intersecting regulatory biofeatures at 17 known HGSOC susceptibility loci in FTSECs (P=3.8x10-30) OSECs (P=2.4x10-23) and HMECs (P=6.7x10-15) but not for EECs (P=0.45) or LNCaP cells (P=0.88). Hierarchical clustering of risk SNPs conditioned on the six different cell types indicates FTSECs and OSECs are highly related (96% of samples using multi-scale bootstrapping) indicating both cell types may be precursors of HGSOC. These data represent the first description of regulatory catalogues of normal precursor cells for different ovarian cancer subtypes, and provide unique insights into the tissue specific regulatory variation with respect to the likely functional targets germline genetic susceptibility variants for ovarian cancer FAIRE-Seq and ChIP-Seq of 2 different histone modifications in 5 cell types.
2015-04-22 | E-GEOD-68104 | biostudies-arrayexpress
Project description:Here, by mapping H3K27ac deposition, we analyze the active regulatory landscapes across primary GBM biopsies, normal brain tissues, and cell line counterparts. Analysis of differentially regulated enhancers, especially super-enhancers between GBM and normal brain tissues, as well as among GBM samples with matched RNA-sequencing data, uncovered unrecognized layers of oncogenic core transcriptional dependency and inter-tumor heterogeneity. Moreover, we demonstrate the functional relevance of leading candidates of super-enhancer-driven transcriptional factors, long non-coding RNAs, and druggable targets in GBM. Through profiling of transcriptional enhancers, our integrative study provides clinically relevant insights into GBM molecular classification, pathogenesis, and therapeutic innovations.
2021-05-05 | GSE145645 | GEO
Project description:Here, by mapping H3K27ac deposition, we analyze the active regulatory landscapes across primary GBM biopsies, normal brain tissues, and cell line counterparts. Analysis of differentially regulated enhancers, especially super-enhancers between GBM and normal brain tissues, as well as among GBM samples with matched RNA-sequencing data, uncovered unrecognized layers of oncogenic core transcriptional dependency and inter-tumor heterogeneity. Moreover, we demonstrate the functional relevance of leading candidates of super-enhancer-driven transcriptional factors, long non-coding RNAs, and druggable targets in GBM. Through profiling of transcriptional enhancers, our integrative study provides clinically relevant insights into GBM molecular classification, pathogenesis, and therapeutic innovations.
2021-05-05 | GSE145644 | GEO
Project description:Understanding the regulatory landscape of the human genome is a central question in complex trait genetics. Most single nucleotide polymorphisms (SNPs) associated with cancer risk lie in non protein-coding regions, implicating regulatory DNA elements as functional targets of susceptibility variants. Here, we describe genome-wide annotation of regions of open chromatin and histone modification in fallopian tube and ovarian surface epithelial cells (FTSECs, OSECs), the debated cellular origins of high-grade serous ovarian cancers (HGSOCs), and in endometriosis epithelial cells (EECs), the likely precursor of clear cell ovarian carcinomas (CCOCs). The regulatory architecture of these cell types was compared to normal human mammary epithelial cells (HMECs) and LNCaP prostate cancer cells. We observed similar positional patterns of global enhancer signatures across the three different ovarian cancer precursor cell types, and evidence of tissues specific regulatory signatures to non-gynecological cell types. We found significant enrichment for risk-associated SNPs intersecting regulatory biofeatures at 17 known HGSOC susceptibility loci in FTSECs (P=3.8x10-30) OSECs (P=2.4x10-23) and HMECs (P=6.7x10-15) but not for EECs (P=0.45) or LNCaP cells (P=0.88). Hierarchical clustering of risk SNPs conditioned on the six different cell types indicates FTSECs and OSECs are highly related (96% of samples using multi-scale bootstrapping) indicating both cell types may be precursors of HGSOC. These data represent the first description of regulatory catalogues of normal precursor cells for different ovarian cancer subtypes, and provide unique insights into the tissue specific regulatory variation with respect to the likely functional targets germline genetic susceptibility variants for ovarian cancer
2015-04-22 | GSE68104 | GEO
Project description:We used RNA sequencing to analyze transcript profiles of ten autopsy brain regions from ten subjects. RNA sequencing techniques were designed to detect both coding and non-coding RNA, splice isoform composition, and allelic expression. Brain regions were selected from five subjects with a documented history of smoking and five non-smokers. Paired-end RNA sequencing was performed on SOLiD instruments to a depth of >40 million reads, using linearly amplified, ribosomally depleted RNA. 12 thousand protein coding and 2 thousand lncRNA transcripts were detectable at a conservative threshold. Of the aligned reads, 52% were exonic, 34% intronic and 14% intergenic. A majority of protein coding genes (65%) was expressed in all regions, whereas ncRNAs displayed a more restricted distribution. Profiles of RNA isoforms varied across brain regions and subjects at multiple gene loci, with neurexin 3 (NRXN3) a prominent example. Allelic RNA ratios deviating from unity were identified in > 400 genes, detectable in both protein-coding and non-coding genes, indicating the presence of cis-acting regulatory variants. RNA sequencing identifies distinct and consistent differences in gene expression between brain regions, with non-coding RNA displaying greater diversity between brain regions than mRNAs. Numerous RNAs exhibit robust allele selective expression, proving a means for discovery of cis-acting regulatory factors with potential clinical relevance. Sequenced whole transcriptomes of 10 brain regions from 10 individuals, 5 smokers and 5 nonsmokers
2015-09-01 | E-GEOD-68559 | biostudies-arrayexpress
Project description:Temozolomide (TMZ) resistance may contribute to the treatment failure in patients with glioblastoma (GBM). Hence, understanding the underlying mechanisms and developing effective strategies against TMZ resistance are highly desired in the clinic. long non-coding RNAs (lncRNAs) have emerged as new regulatory molecules with diverse functions in biological processes and been deregulated in many pathologies, involved in the therapeutic resistance. It is urgent to elucidate the underlying lncRNA-based mechanisms of TMZ resistance in GBM patients.
2019-04-12 | GSE113510 | GEO
Project description:Glioblastoma multiforme(GBM) is the most common and lethal malignant primary brain tumor. Long non-coding RNAs (lncRNAs) are aberrantly expressed in many cancers and are involved in their cell proliferation, apoptosis, angiogenesis, and invasion. To systematically study the role of lncRNAs in GBM, we built gene expression profiles of GBM and non-tumor tissues using lncRNA and mRNA gene expression microarrays.
2020-06-30 | GSE100675 | GEO
Project description:In this study was determined the global expression pattern of long non-coding RNAs, mRNAs, and miRNAs in pediatric astrocytoma of different histological grades. The Affymetrix HTA 2.0 array showed expression changes on one hundred-sixty two and two hundred-fifteen long non-coding RNAs in tumors (versus the control) and in GBM (versus low-grade astrocytoma), respectively. A total of seven astrocytic tumors and two control tissues were collected during the period of 2012–2014: four low-grade Ast (three pilocytic Ast (PAst) and one diffuse Ast (DAst)) and four high-grade Ast (four glioblastoma multiforme (GBM)).RNA was extracted from tissue samples using TRIzol (Ambion life technologies, Thermo Scientific Inc.) following the methodology described by Hongbao et al. 2008 and with certain modifications described by Vujovic et al. 2013. For expression analysis, Human Transcriptome Array 2.0 (HTA) (Santa Clara, CA, USA) was employed. in this study was determined the global expression pattern of long non-coding RNAs, mRNAs, and miRNAs in pediatric astrocytoma of different histological grades. The HTA 2.0 array showed expression changes on one hundred-sixty two and two hundred-fifteen long non-coding RNAs in tumors (versus the control) and in GBM (versus low-grade astrocytoma), respectively.
2015-08-25 | E-GEOD-72269 | biostudies-arrayexpress
Project description:We used RNA sequencing to analyze transcript profiles of ten autopsy brain regions from ten subjects. RNA sequencing techniques were designed to detect both coding and non-coding RNA, splice isoform composition, and allelic expression. Brain regions were selected from five subjects with a documented history of smoking and five non-smokers. Paired-end RNA sequencing was performed on SOLiD instruments to a depth of >40 million reads, using linearly amplified, ribosomally depleted RNA. 12 thousand protein coding and 2 thousand lncRNA transcripts were detectable at a conservative threshold. Of the aligned reads, 52% were exonic, 34% intronic and 14% intergenic. A majority of protein coding genes (65%) was expressed in all regions, whereas ncRNAs displayed a more restricted distribution. Profiles of RNA isoforms varied across brain regions and subjects at multiple gene loci, with neurexin 3 (NRXN3) a prominent example. Allelic RNA ratios deviating from unity were identified in > 400 genes, detectable in both protein-coding and non-coding genes, indicating the presence of cis-acting regulatory variants. RNA sequencing identifies distinct and consistent differences in gene expression between brain regions, with non-coding RNA displaying greater diversity between brain regions than mRNAs. Numerous RNAs exhibit robust allele selective expression, proving a means for discovery of cis-acting regulatory factors with potential clinical relevance.
2015-09-01 | GSE68559 | GEO