4738 results for "RNA AND sequencing OR transcriptome"

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• Uncovering Gene Regulatory Differences between Human and Chimpanzee Neural Cells

  A major challenge in human evolutionary biology is to pinpoint the genetic differences that underlie phenotypic changes in the human lineage, such as increased neuron number and a prolonged period of neuronal maturation. Here, we used human-chimpanzee tetraploid cells to distinguish changes in gene expression due to cis-acting sequence variants that change local gene regulation, from trans expression changes due to species differences in the cellular environment, in neural progenitor cells and excitatory neurons using RNA-seq and ATAC-seq. Using a CRISPR inhibition screen with scRNA-seq, transcription factor motif analyses with CUT&Tag, and downstream single-locus studies with RNA-seq, we further characterized cis-acting gene regulatory differences, including changes to FOS, TNIK, FOSL2, and MAZ, that influence neurogenesis and neuronal maturation. This study identifies specific genomic changes that may contribute to human neural specializations and provides a general framework for understanding genetic differences that underlie human traits.

  Study phs004053

• Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas

  RNA polymerase II mediates the transcription of all protein-coding genes in eukaryotic cells, a process that is fundamental to life. Genomic mutations in this enzyme have not been previously linked to any pathology in humans, a testament to its indispensable role in cell biology. Based on a combination of next-generation genomic analyses of 775 meningiomas, we report that recurrent somatic p.Gln403Lys or p.Leu438_His439del mutations in POLR2A, which encodes the catalytic subunit of RNA polymerase II1, are sufficient to hijack this essential enzyme and drive neoplasia. POLR2A mutant tumors reveal dysregulation of key meningeal identity genes, including WNT6 and ZIC1/ZIC42,3. In addition to POLR2A, NF2, SMARCB1, TRAF7, KLF4, AKT1, PIK3CA and SMO4-8, we also report somatic mutations in AKT3, PIK3R1, PRKAR1A, and SUFU in meningiomas. Our results identify a role for essential transcriptional machinery in driving tumorigenesis and define mutually exclusive meningioma subgroups with distinct clinical and pathological features.

  Study EGAS00001001916

• Widespread hypertranscription in aggressive human cancers

  Cancers are often defined by the dysregulation of specific transcriptional programs; however, the importance of global transcriptional changes is less understood. Hypertranscription is the genome-wide increase in RNA output. Hypertranscription’s prevalence, underlying drivers and prognostic significance are undefined in primary human cancer. This is due in part to limitations of expression profiling methods, which assume equal RNA output between samples. Here, we developed a computational method to directly measure hypertranscription in 7,494 human tumors, spanning 31 cancer types. Hypertranscription is ubiquitous across cancer, especially in aggressive disease. It defines patient subgroups with worse survival, even within well-established subtypes. Our data suggest that loss of transcriptional suppression underpins the hypertranscriptional phenotype. Single-cell analysis reveals hypertranscriptional clones, which dominate transcript production regardless of their size. Finally, patients with hypertranscribed mutations have improved response to immune checkpoint therapy. Our results provide fundamental insights into gene dysregulation across human cancers and may prove useful in identifying patients that would benefit from novel therapies.

  Study EGAS00001006365

• Small RNA sequencing of endometrial cancer patients with samples collected prior to diagnosis and controls

  This dataset contains unpaired FASTQ files of 316 endometrial cancer cases and 316 matched controls representing circulating RNAs. RNA count files are provided as the output of sncRNA pipeline and represent 12 RNA types (isomiR, lncRNA, precursor miRNA, miRNA, miscRNA, mRNA, piRNA, scaRNA, snoRNA, snRNA, tRF, and tRNA). We also provide metadata of the samples.

  Dataset EGAD50000000391

• Covacta RNAseq merged EGA metadata

  Sample metadata for the RNA-seq dataset. This dataset includes subject-level data and longitudinal visit day information for the corresponding samples.

  Dataset EGAD00001011162

• 10x Multiome from Human Fetal Heart

  We hope to uncover the genetic basis of congenital heart disease by examining how genetic variants, especially those in non-coding regions, influence heart development. To achieve this goal, our research team created a single-cell atlas of human fetal heart development. The study population consists of 41 structurally normal fetal hearts spanning 6 to 22 weeks post-conception. We profiled close to 750,000 using single-cell RNA sequencing and ATAC sequencing technologies via the 10x Genomics Multiome platform.The molecular technologies employed allowed for simultaneous analysis of gene expression and chromatin accessibility at the single-cell level. This approach identified numerous distinct cell types and states within the developing heart, offering detailed insights into gene activity and enhancer usage during critical stages of heart development.Principal findings include the characterization of diverse cell populations and the identification of specific gene expression patterns and regulatory elements active during heart formation. This high-resolution atlas provides valuable insights into how genetic variants may disrupt normal heart development, particularly those in non-coding regions that affect gene regulation.

  Study phs003778

• Genetic Neuroscience: How Human Genes and Alleles Shape Neuronal Phenotypes

  The goal of this collaborative, interdisciplinary project is to develop powerful, generalizable approaches for discovering how risk variants for psychiatric disorders shape neurobiological processes at multiple levels of analysis, and to identify the processes whose dysregulation underlies disease.Induced pluripotent stem cells (iPSCs) were used towards the development of these new experimental and inferential systems bridging gaps between human genetics and experimental biology. The largest publicly available collection of iPSCs (2607 lines) has been generated from 2184 donors by the California Institute for Regenerative Medicine (CIRM). To expand our donor collection, an additional 44 iPSC donors from the McLean_Levy cohort were identified. We wish to share the available SNP data for 2167 CIRM lines and whole genome sequence data generated at the Broad Institute for 473 of the CIRM and 44 McLean_Levy iPSC donors. These data can be used to identify (for experiments) lines with specific genotypes of interest and lines from donors with high or low polygenic risk scores for phenotypes of interest. The data can also be used to identify acquired mutations in the iPSC lines. The CIRM iPSC lines are available through Fujifilm Cellular Dynamics iPSC Repository (https://www.fujifilmcdi.com/cirm-ipsc-products/). The McLean_Levy lines are available through the NIMH Repository & Genomics Resource (https://www.nimhgenetics.org/).Additional project data registered with the study includes data from an iPSC line derived from an SMA patient (n=1), as well as single-cell RNA sequence data and supplemental processed genomic datasets in support of project publications.Molecular DatasetsSingle-cell RNA-seq: 10X Genomics, Illumina NovaSeqSupplemental "cell village" pooled genomic sequence data: Illumina NextSeqWhole Genome Genotyping: Infinium Global Screening Array-24 Kit, Illumina HumanCore chipWhole Genome Sequencing: Illumina NovaSeq

  Study phs002032

• Enhancer profiling identifies epigenetic markers of endocrine resistance and reveals therapeutic options for metastatic castration-resistant prostate cancer patients (LuCaP cell line data)

  Androgen Receptor (AR) signaling inhibitors, including enzalutamide, are treatment options for patients with metastatic castration-resistant prostate cancer (mCRPC), but resistance inevitably develops. Using metastatic samples from a prospective phase II clinical trial, we epigenetically profiled enhancer/promoter activities with H3K27ac chromatin immunoprecipitation followed by sequencing, before and after AR-targeted therapy. We identified a distinct subset of H3K27ac-differentially marked regions that associated with treatment responsiveness. These data were successfully validated in mCRPC patient-derived xenograft models (PDX). In silico analyses revealed HDAC3 as a critical factor that can drive resistance to hormonal interventions, which we validated in vitro. Critically, we identified the pan-HDAC inhibitor, vorinostat to be effective in decreasing tumor cell proliferation both in vitro and in vivo. Moreover, we uncovered evidence for HDAC3 working together with Glucocorticoid Receptor (GR) as a potential mechanism for this therapeutic effect. These findings demonstrate rationale for new therapeutic strategies including HDAC inhibitors to improve patient outcome in advanced stages of mCRPC. Project Goal: We identified H3K27ac regions associated with resistance in patient samples. Extensive analysis of these regions suggested that HDAC3 may play a role in resistance. To test this, we analyzed ChIP-seq and RNA-seq from cell lines generated from PDX LuCaP samples (recapitulating resistant and non-resistant) to validate findings in patient samples. ChIP-seq samples were used to verify the signals identified from specific factors, such as H3K27ac, AR, FOXA1, GR and HDAC3, their association with resistance and possible mechanisms of action. RNA-seq samples were analyzed to determine the effect of AR signaling in these samples in specific genes in the H3K27ac resistance-associated regions.

  Study EGAS50000000917

• Targeting FGFR1 for treatment of soft-tissue sarcoma (H021)

  Purpose: Altered FGFR1 signaling has emerged as therapeutic target in various epithelial malignancies. In contrast, the role of FGFR1 in soft-tissue sarcoma (STS) has not been established. Prompted by the detection and subsequent therapeutic inhibition of amplified FGFR1 in a patient with metastatic leiomyosarcoma, we investigated the oncogenic properties and potential as drug target of FGFR1 in STS.Experimental Design: The frequency of FGFR1 amplification and overexpression, as assessed by fluorescence in situ hybridization, microarray-based comparative genomic hybridization and mRNA expression profiling, SNP array profiling, and RNA sequencing, was determined in three independent patient cohorts. The sensitivity of STS cell lines with or without FGFR1 alterations to genetic and pharmacologic FGFR1 inhibition and the signaling pathways engaged by FGFR1 were investigated using short-term viability assays, long-term colony formation assays, and biochemical analysis.Results: Increased FGFR1 copy number was detected in 74 of 190 (38.9%; Cohort 1), 13 of 79 (16.5%; Cohort 2), and 80 of 254 (31.5%; Cohort 3) patients. FGFR1 overexpression occurred in 16 of 79 (20.2%, Cohort 2) and 39 of 254 (15.4%; Cohort 3) patients. Targeting of FGFR1 by short hairpin RNA-mediated knockdown and different small-molecule inhibitors (PD173074, AZD4547, BGJ398) revealed that the requirement for FGFR1 signaling in STS cells is primarily dictated by FGFR1 expression levels, and identified the MAPK-ERK1/2 axis as critical FGFR1 effector pathway.Conclusion: These data identify FGFR1 as driver gene in multiple STS subtypes and support FGFR1 inhibition, guided by patient selection according to FGFR1 expression and monitoring of MAPK-ERK1/2 signaling, as therapeutic option in this challenging group of diseases.H021

  Study EGAS00001001844

• RNA-seq of human embryonic heart, lung, and cerebellum

  Characterization of cell types in the human embronic heart, lung, and cerebellum.

  Study EGAS00001004375