Tissue-specific chromatin accessibility cis-regulatory regions in rat white adipose and muscle
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ABSTRACT:
ORGANISM(S): Rattus norvegicus
PROVIDER: GSE168328 | GEO | 2022/02/07
REPOSITORIES: GEO
Similar Datasets
Project description:Chromatin accessibility is a key factor influencing gene expression. We developed a modified protocol, ruptor-ATAC, which together with RNA-seq was used to investigate regulatory elements underlying tissue-specific gene expression in rat white adipose and skeletal muscle, two tissues with contrasting metabolic functions. While promoter accessibility correlated with RNA expression, integration of the two datasets identified tissue-specific differentially accessible regions (DARs) that predominantly localized in intergenic and intron regions. DARs mapped to differentially expressed genes that were enriched in distinct biological processes in each tissue. Motif enrichment analysis on tissue-specific DARs predicted binding sites for transcription factors (TFs), several of which were up-regulated in the corresponding tissue. Positive relationship between DARs and target gene expression further supported a functional role for these TF binding motifs. Our study identifies cis-regulatory regions that likely play a major role in the regulation of tissue-specific gene expression in adipose and muscle.
2022-02-07 | GSE171923 | GEO
Project description:Tissue-specific chromatin accessibility cis-regulatory regions in rat white adipose and muscle
| PRJNA706933 | ENA
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>
| phs001048 | dbGaP
Project description:Variations in noncoding regulatory sequences play a central role in evolution but interpreting such variations remains difficult even in the context of defined attributes such as transcription factor (TF) binding sites. Here, we systematically link variations in cis-regulatory sequences to TF binding by profiling the allele-specific binding of 27 TFs expressed in a yeast hybrid, which contains two related genomes within the same nucleus. TFs localize preferentially to sites containing their known binding motifs, but occupy only a small fraction of the potential motif-coding genomic sites. Differential binding of TFs to the two orthologues is well explained by sequence variations that alter the consensus core motif, while changes in chromatin accessibility were of little apparent effect. Motif variations that abolish binding when present in one allele show only moderately reduced binding when common to both alleles, suggesting evolutionary compensation. At the promoter level, we report cases of turnover, where binding in the two orthologues localized to different promoter regions, yet most interspecies differences resulted from higher number of binding sites in one of the alleles. Our results suggest that cis variations affecting TF binding occur primarily through the gain and loss of cis-regulatory motifs at accessible regions.
2022-04-29 | GSE196451 | GEO
Project description:Contemporary high throughput technologies permit the rapid identification of transcription factor (TF) target genes on a genome-wide scale, yet the functional significance of TFs requires knowledge of target gene expression patterns, cooperating TFs and cis-regulatory element (CRE) structures. Here we investigated the myogenic regulatory network downstream of the Drosophila zinc finger TF Lame duck (Lmd) by combining both previously published and newly performed genomic data sets, including chromatin immunoprecipitation sequencing (ChIP-seq), genome-wide mRNA profiling, cell-specific expression patterns of putative transcriptional targets, analysis of histone mark signatures, studies of TF co-occupancy by additional mesodermal regulators, TF binding site determination using protein binding microarrays (PBMs), and machine learning of candidate CRE motif compositions. Our findings suggest that Lmd orchestrates an extensive myogenic regulatory network, a conclusion supported by the identification of Lmd-dependent genes, histone signatures of Lmd-bound genomic regions, and the relationship of these features to cell-specific gene expression patterns. The heterogeneous co-occupancy of Lmd-bound regions with additional mesodermal regulators revealed that different transcriptional inputs are used to mediate similar myogenic gene expression patterns. Machine learning further demonstrated diverse combinatorial motif patterns within tissue-specific Lmd-bound regions. PBM analysis established the complete spectrum of Lmd DNA binding specificities, and site-directed mutagenesis of Lmd and additional, newly discovered motifs in known enhancers demonstrated the critical role of these TF binding sites in supporting full enhancer activity. Collectively, these findings provide new insights into the transcriptional codes regulating muscle gene expression, and offer a generalizable approach for similar studies in other systems. Examination of Lmd occupancy to genomic DNA from sorted mesodermal cells
2012-11-13 | E-GEOD-38402 | biostudies-arrayexpress
Project description:We report sustained changes in the chromatin accessibility landscape of adipose tissue macrophages (ATMs) from high fat diet (HFD)-fed mice persist long after return to regular diet (RD). We compared the data of ATAC-seq performed on nuclei extracted from FACS-sorted ATMs isolated from HFD, RD-RD and HFD-RD-fed mice. Inter-group comparisons revealed the highest diversity and hence the greatest number of differentially accessible regions (DARs) to occur between ATMs from RD-RD and HFD-RD-fed mice, and considerably fewer DARs were identified between ATMs from HFD-RD vs HFD-fed mice. Association of DARs with the nearest gene and gene ontology (GO) enrichment analysis revealed considerable pathway enrichment, especially pathways coding for angiogenesis and inflammatory response, in HFD-RD group when compared to RD-RD group. The results altogether indicated that most changes in chromatin landscape induced by HFD-feeding are maintained as open chromatin positions for a long time, suggesting that HFD-feeding leads to long-term reprograming of ATMs and renders them prone to pro-angiogenic and pro-inflammatory responses.
2024-01-25 | GSE175614 | GEO
Project description:Spatiotemporal gene regulation during embryonic development is driven by cis-regulatory DNA sequences called enhancers. Enhancers are activated through a combination of transcription factors (TFs) that bind to short sequence motifs within these sequences, but the order of events by which TFs read out motifs is not clear. Some TFs can only bind chromatin that is already accessible, while other TFs called pioneers can open chromatin themselves. Identifying motifs and the order by which they drive chromatin accessibility is very challenging. The recent implementation of convolutional neural networks, which learn complex cis-regulatory sequence rules that are predictive for genomics data, provides an unprecedented opportunity to dissect this problem. Here, we trained base-resolution deep learning models and applied them to high-resolution TF binding and chromatin accessibility data from the well-studied early Drosophila embryo. We uncover a clear hierarchical relationship between the pioneer Zelda and the TFs involved in the spatiotemporal patterning of the embryo, consistent with Zelda being a pioneer. However, the models predict that patterning TFs can also augment chromatin accessibility in a context-specific manner. Using a series of Drosophila mutant strains, we find that the two types of TFs increase chromatin accessibility by distinct mechanisms. Zelda’s pioneering is proportional to motif affinity, while the patterning TFs specifically increase chromatin accessibility when they mediate enhancer activation. This was conclusive because Dorsal can function both as activator and repressor, and the effect on chromatin accessibility depended on Dorsal’s transactivation effect and not on its binding per se. In conclusion, chromatin accessibility occurs in two phases: one through pioneering, which makes regions first accessible but not necessarily active, and a second when the correct combination of transcription factors lead to enhancer activation.
2022-12-20 | GSE218849 | GEO
Project description:Spatiotemporal gene regulation during embryonic development is driven by cis-regulatory DNA sequences called enhancers. Enhancers are activated through a combination of transcription factors (TFs) that bind to short sequence motifs within these sequences, but the order of events by which TFs read out motifs is not clear. Some TFs can only bind chromatin that is already accessible, while other TFs called pioneers can open chromatin themselves. Identifying motifs and the order by which they drive chromatin accessibility is very challenging. The recent implementation of convolutional neural networks, which learn complex cis-regulatory sequence rules that are predictive for genomics data, provides an unprecedented opportunity to dissect this problem. Here, we trained base-resolution deep learning models and applied them to high-resolution TF binding and chromatin accessibility data from the well-studied early Drosophila embryo. We uncover a clear hierarchical relationship between the pioneer Zelda and the TFs involved in the spatiotemporal patterning of the embryo, consistent with Zelda being a pioneer. However, the models predict that patterning TFs can also augment chromatin accessibility in a context-specific manner. Using a series of Drosophila mutant strains, we find that the two types of TFs increase chromatin accessibility by distinct mechanisms. Zelda’s pioneering is proportional to motif affinity, while the patterning TFs specifically increase chromatin accessibility when they mediate enhancer activation. This was conclusive because Dorsal can function both as activator and repressor, and the effect on chromatin accessibility depended on Dorsal’s transactivation effect and not on its binding per se. In conclusion, chromatin accessibility occurs in two phases: one through pioneering, which makes regions first accessible but not necessarily active, and a second when the correct combination of transcription factors lead to enhancer activation.
2022-12-20 | GSE218848 | GEO
Project description:Spatiotemporal gene regulation during embryonic development is driven by cis-regulatory DNA sequences called enhancers. Enhancers are activated through a combination of transcription factors (TFs) that bind to short sequence motifs within these sequences, but the order of events by which TFs read out motifs is not clear. Some TFs can only bind chromatin that is already accessible, while other TFs called pioneers can open chromatin themselves. Identifying motifs and the order by which they drive chromatin accessibility is very challenging. The recent implementation of convolutional neural networks, which learn complex cis-regulatory sequence rules that are predictive for genomics data, provides an unprecedented opportunity to dissect this problem. Here, we trained base-resolution deep learning models and applied them to high-resolution TF binding and chromatin accessibility data from the well-studied early Drosophila embryo. We uncover a clear hierarchical relationship between the pioneer Zelda and the TFs involved in the spatiotemporal patterning of the embryo, consistent with Zelda being a pioneer. However, the models predict that patterning TFs can also augment chromatin accessibility in a context-specific manner. Using a series of Drosophila mutant strains, we find that the two types of TFs increase chromatin accessibility by distinct mechanisms. Zelda’s pioneering is proportional to motif affinity, while the patterning TFs specifically increase chromatin accessibility when they mediate enhancer activation. This was conclusive because Dorsal can function both as activator and repressor, and the effect on chromatin accessibility depended on Dorsal’s transactivation effect and not on its binding per se. In conclusion, chromatin accessibility occurs in two phases: one through pioneering, which makes regions first accessible but not necessarily active, and a second when the correct combination of transcription factors lead to enhancer activation.
2022-12-20 | GSE218851 | GEO
Project description:Spatiotemporal gene regulation during embryonic development is driven by cis-regulatory DNA sequences called enhancers. Enhancers are activated through a combination of transcription factors (TFs) that bind to short sequence motifs within these sequences, but the order of events by which TFs read out motifs is not clear. Some TFs can only bind chromatin that is already accessible, while other TFs called pioneers can open chromatin themselves. Identifying motifs and the order by which they drive chromatin accessibility is very challenging. The recent implementation of convolutional neural networks, which learn complex cis-regulatory sequence rules that are predictive for genomics data, provides an unprecedented opportunity to dissect this problem. Here, we trained base-resolution deep learning models and applied them to high-resolution TF binding and chromatin accessibility data from the well-studied early Drosophila embryo. We uncover a clear hierarchical relationship between the pioneer Zelda and the TFs involved in the spatiotemporal patterning of the embryo, consistent with Zelda being a pioneer. However, the models predict that patterning TFs can also augment chromatin accessibility in a context-specific manner. Using a series of Drosophila mutant strains, we find that the two types of TFs increase chromatin accessibility by distinct mechanisms. Zelda’s pioneering is proportional to motif affinity, while the patterning TFs specifically increase chromatin accessibility when they mediate enhancer activation. This was conclusive because Dorsal can function both as activator and repressor, and the effect on chromatin accessibility depended on Dorsal’s transactivation effect and not on its binding per se. In conclusion, chromatin accessibility occurs in two phases: one through pioneering, which makes regions first accessible but not necessarily active, and a second when the correct combination of transcription factors lead to enhancer activation.
2022-12-20 | GSE218850 | GEO