Ontology highlight
ABSTRACT:
PROVIDER: PRJNA380233 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5368450.fastq.gz | Fastqsanger.gz | |||
| SRR5368460.fastq.gz | Fastqsanger.gz | |||
| SRR5368451.fastq.gz | Fastqsanger.gz | |||
| SRR5368461.fastq.gz | Fastqsanger.gz | |||
| SRR5368452.fastq.gz | Fastqsanger.gz |
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Project description:Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples.
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Project description:Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples. We capture type I and type II muscle fiber signatures, which are generally missed by existing single-cell RNA-seq methods. We perform cross-modality and cross-species integrative analyses on 33,862 nuclei and identify seven cell types ranging in abundance from 59.6% to 1.0% of all nuclei. We introduce a regression-based approach to infer cell types by comparing transcription start site-distal ATAC-seq peaks to reference enhancer maps and show consistency with RNA-based marker gene cell type assignments. We find heterogeneity in enrichment of genetic variants linked to complex phenotypes from the UK Biobank and diabetes genome wide association studies in cell-specific ATAC-seq peaks, with the most striking enrichment patterns in muscle mesenchymal stem cells (~3.5% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, transcription factor motifs, and target genes for type 2 diabetes signals. These chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for nominating causal GWAS SNPs and cell types.
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Project description:<p>The Finland-United States Investigation of NIDDM Genetics (FUSION) study is a long-term effort to identify genetic variants that predispose to type 2 diabetes (T2D) or that impact the variability of T2D-related quantitative traits (QTs). Skeletal muscle and adipose are major insulin target tissues and play key roles in insulin resistance. We hypothesize that a subset of T2D and related QT variants alter gene expression in skeletal muscle and adipose tissue. For this FUSION Tissue Biopsy Study, we have obtained and are analyzing RNA-Seq, microRNA (miRNA)-Seq, and DNA methylation (methyl)-Seq data on biopsy samples from 331 individuals from across the range of glucose tolerance: 124 normal glucose tolerance (NGT), 77 impaired glucose tolerance (IGT), 44 impaired fasting glucose (IFG), and 86 newly-diagnosed T2Ds. Participants completed two study visits, two weeks apart. First visits comprised most of the clinical phenotyping, including four-point OGTT (fasting, and 30, 60, and 120 minute post-load); BMI, WHR; lipids; blood pressure; and many other variables. Participants also completed FUSION health history, medication, and lifestyle questionnaires. At second visit, we obtained ~250mg <i>vastus lateralis</i> skeletal muscle, ~750mg abdominal subcutaneous adipose, and a ~5x15mm section of abdominal skin. Visits were completed in March 2013. RNA isolation is ongoing in the Collins laboratory at the NIH, RNA and miRNA sequencing at the NIH Intramural Sequencing Center (NISC), and genotyping at the Center for Inherited Disease Research (CIDR). Individual-level data is available here for the 306 individuals who consented to data deposit.</p> <p>To focus on evaluation of gene expression and its regulation in skeletal muscle, we analyzed mRNA extracted from <i>vastus lateralis</i> skeletal muscle obtained from 271 of the 331 individual subjects from Finland, along with genome-wide genotypes. Individual-level data is available here for the 250 subjects who reconsented to the use of their data. Release phs001048.v2.p1 adds muscle data for an additional 42 subjects and data from adipose tissue for 276 subjects. Total RNA was isolated using Trizol extraction in the Collins laboratory at the NIH. The mRNA was poly-A selected, 24-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol and RNA sequencing was performed on HiSeq2000 sequencers using 101bp paired-end reads at NISC. miRNA libraries were prepared from total RNA from 296 muscle and 270 adipose samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. Data for 272 muscle and 251 adipose samples are available here for individuals with consent for data deposit. DNA was extracted from blood in the Collins laboratory, and genotyping on the Illumina Omni2.5M array was performed at CIDR. Genotypes were imputed using the HRC 2016 reference panel. In order to assess regions of open chromatin in skeletal muscle, we obtained muscle tissue from a commercial provider to perform ATAC-seq; these samples were sequenced at the University of Michigan DNA Sequencing Core.</p> <p>Greater than 90% of the approximately 80 loci associated with T2D and the 100s of loci associated with T2D-related traits (glucose and insulin, anthropometrics, lipids) through genome-wide association studies occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Regulatory element activity is often tissue-specific, which further complicates discovery of the causal/functional variation. Therefore, there is a critical need to understand the full spectrum of genetic variation and regulatory element usage in T2D-relevant tissues. To that end, this study contains whole genome sequence and whole genome bisulfite sequence, and/or Illumina MethylationEPIC Array data, of two tissues relevant to T2D: skeletal muscle and adipose tissue from individuals with glucose tolerance categories ranging from normal to T2D, providing a comprehensive survey of both individual genetic variation as well as DNA methylation across different tissues from multiple individuals.</p>
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Project description:To gain new insights into molecular changes in skeletal muscle aging and disease with a special focus on differential alternative splicing and senescence, we performed RNA-seq on rat gastrocnemius muscles of animals aged 6, 12, 18, 21, 24 and 27 months, using a rat sarcopenia model we had previously established.
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Project description:Identfification of MEF2A target genes using ChIP-exo in skeletla muscle and primary cardiomyocytes. Identfification of MEF2A target genes using ChIP-exo and RNA-seq in skeletal muscle and primary cardiomyocytes. MEF2 plays a profound role in the regulation of transcription in cardiac and skeletal muscle lineages. To define the overlapping and unique MEF2A genomic targets, we utilized ChIP-exo analysis of cardiomyocytes and skeletal myoblasts. Of the 2783 and 1648 MEF2A binding peaks in skeletal myoblasts and cardiomyocytes, respectively, 294 common binding sites were identified. Genomic targets were compared to differentially expressed genes in RNA-seq analysis of MEF2A depleted myogenic cells. MEF2A target genes were identified in 48 hr DM C2C12 myoblasts cells and primary cardiomyocytes using ChIP-exo. Binding profiles on MEF2A in each cell type were compared. Cross sectional-analysis between ChIP-exo identified targets and RNA-seq analysis of MEF2A deplted myoblasts was also done.
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