Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell assay examining chromatin accessibility reveals transcriptional regulatory variation in the proinflammatory milieu of uremia

ABSTRACT: A single-cell assay for transposase-accessible chromatin with high-throughput sequencing (scATAC-seq) was applied to compare the single-cell chromatin accessibility profiles of peripheral blood mononuclear cells (PBMCs) that were obtained from healthy volunteers and uremia patients. Besides, we further revealed the biological functions and regulatory modes of the uremia-related transcription factors (TFs). We principally identified 8 leukocytic clusters using promoter sums of cell type-specific marker genes. Representative TF motifs related to immune cell phenotype identification were found. The comparison of cells from uremia patients and healthy individuals revealed differential candidate TF motifs driving the uremia-associated transcriptomic signature changes, thereby resulting in variation of multiple immune-inflammatory pathways, virus infection-related pathways, and tumor-associated pathways.Our findings reveal transcriptional regulatory variation in uremia-derived PBMCs from an epigenetic perspective, providing a foundational framework for studies examining proinflammatory mechanisms in uremia and establishing a foundation for future research investigating epigenetic therapy.

ORGANISM(S): Homo sapiens

PROVIDER: GSE158280 | GEO | 2022/04/27

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Single-cell assay examining chromatin accessibility reveals transcriptional regulatory variation in the proinflammatory milieu of uremia

Project description:Single-cell assay examining chromatin accessibility reveals transcriptional regulatory variation in the proinflammatory milieu of uremia

| PRJNA664740 | ENA

Identification of differential gene expression in blood vessels from patients with uremia (data set 2)

Project description:Identification of differential gene expression in blood vessels from patients with uremia

2020-09-11 | GSE38751 | GEO

Identification of differential gene expression in blood vessels from patients with uremia (data set 1)

Project description:Identification of differential gene expression in blood vessels from patients with uremia

2020-09-11 | GSE38750 | GEO

Gene-regulatory network analysis of ankylosing spondylitis with a single-cell chromatin accessible assay

Project description:A detailed understanding of the gene-regulatory network in ankylosing spondylitis (AS) is vital for elucidating the mechanisms of AS pathogenesis. Assaying transposase-accessible chromatin in single cell sequencing (scATAC-seq) is a suitable method for revealing such networks. Thus, scATAC-seq was applied to define the landscape of active regulatory DNA in AS. As a result, there was a significant change in the percent of CD8+ T cells in PBMCs, and 37 differentially accessible transcription factor (TF) motifs were identified. T cells, monocytes-1 and dendritic cells were found to be crucial for the IL-17 signaling pathway and TNF signaling pathway, since they had 73 potential target genes regulated by 8 TF motifs with decreased accessibility in AS. Moreover, natural killer cells were involved in AS by increasing the accessibility to TF motifs TEAD1 and JUN to induce cytokine-cytokine receptor interactions. In addition, CD4+ T cells and CD8+ T cells may be vital for altering host immune functions through increasing the accessibility of TF motifs NR1H4 and OLIG (OLIGI and OLIG2), respectively. These results explain clear gene regulatory variation in PBMCs from AS patients, providing a foundational framework for the study of personal regulomes and delivering insights into epigenetic therapy.

2020-11-18 | GSE157595 | GEO

Project description:Transcription factor (TF) binding specificities (motifs) are essential to the analysis of noncoding DNA and gene regulation. Accurate prediction of TF sequence specificities is critical, because the hundreds of sequenced eukaryotic genomes encompass hundreds of thousands of TFs, and assaying each is currently infeasible. There is ongoing controversy regarding the efficacy of motif prediction methods, as well as the degree of motif diversification among related species. Here, we describe Similarity Regression (SR), a significantly improved method for predicting motifs. We have updated and expanded the Cis-BP database using SR, and validate its predictive capacity with new data from diverse eukaryotic TFs. SR inherently quantifies TF motif evolution, and we show that previous claims of near-complete conservation of motifs between human and Drosophila are grossly inflated, with nearly half the motifs in each species absent from the other. We conclude that diversification in DNA binding motifs is pervasive, and present a new tool and updated resource to study TF diversity and gene regulation across eukaryotes.

2019-03-08 | GSE121420 | GEO

Mapping and Analysis of Caenorhabditis elegans Transcription Factor Binding Specificities

Project description:The nematode Caenorhabditis elegans is a powerful model for studying gene regulation, as it has a compact genome and a wealth of genomic tools. However, identification of regulatory elements has been hampered by the fact that DNA binding motifs are known for only 71 (9%) of the estimated 763 high-confidence sequence-specific transcription factors (TFs). To address this problem, we performed protein binding microarray (PBM) experiments on representatives of canonical TF families in the C. elegans TF repertoire, obtaining motifs for 129 distinct TFs. Moreover, we can infer motifs for 97 additional TFs that have DNA binding domains that are very similar to those already characterized, resulting in a total coverage of binding specificities for almost 40% of the C. elegans TF repertoire. These data highlight the diversification of binding motifs for the nuclear hormone receptor (NHR) and C2H2 zinc finger families, and reveal unexpected diversity of motifs for others, including the T-box and DM families. Enrichment of motifs in the promoters of functionally related genes is consistent with known biology in many cases, and also identifies putative new regulatory roles for poorly characterized TFs. The motifs are available at http:// http://cisbp.ccbr.utoronto.ca. Protein binding microarray (PBM) experiments were performed for a set of 129 diverse C. elegans transcription factors. Briefly, the PBMs involved binding GST-tagged DNA-binding proteins to two double-stranded 44K Agilent microarrays, each containing a different DeBruijn sequence design, in order to determine their sequence preferences. Details of the PBM protocol are described in Berger et al., Nature Biotechnology 2006.

2015-04-23 | E-GEOD-65719 | biostudies-arrayexpress

Mapping and Analysis of Caenorhabditis elegans Transcription Factor Binding Specificities

2015-04-23 | GSE65719 | GEO

Identification of Breast Cancer Associated Variants That Modulate Transcription Factor Binding

Project description:GWAS have discovered thousands of genomic loci that are associated with disease risk and quantitative traits, but most of the variants responsible for risk remain uncharacterized. The vast majority of GWAS-identified loci contain non-coding SNPs and defining molecular mechanism of risk is challenging. Many non-coding causal SNPs are hypothesized to alter Transcription Factor (TF) binding sites as the mechanism by which they affect organismal phenotypes. We employed an integrative genomics approach to identify candidate TF binding motifs that confer breast cancer-specific phenotypes identified by GWAS. We performed de novo motif analysis of regulatory elements, analyzed evolutionary conservation of identified motifs, and assayed TF footprinting data to identify sequence elements that recruit TFs and maintain chromatin landscape in breast cancer-relevant tissue and cell lines. Regulatory elements for MCF10A were mapped with ATAC-seq.We identified top candidate causal SNPs that are predicted to alter TF binding, within breast cancer-relevant regulatory regions, and in strong linkage disequilibrium with the GWAS SNPs. This integrative analysis pipeline is a general framework to identify candidate causal variants within regulatory regions and TF binding sites that confer phenotypic variation and disease risk.

2016-12-19 | GSE89013 | GEO

Leveraging genetic variation to identify divergent functions of distinct NF-kB factors on the activity of regulatory elements in macrophages

Project description:Genetic variation in regulatory elements can alter transcription factor (TF) binding by mutating a TF binding motif, which in turn may affect the activity of the regulatory elements. However, it is unclear which motifs are prone to impact transcriptional regulation if mutated. Current motif analysis tools either prioritize TFs based on motif enrichment without linking to a function or are limited in their applications due to the assumption of linearity between motifs and their functional effects. We present MAGGIE, a novel method for identifying motifs mediating TF binding and function. By leveraging measurements from diverse genotypes, MAGGIE uses a statistical approach to link mutations of a motif to changes of an epigenomic feature without assuming a linear relationship. We benchmark MAGGIE across various applications using both simulated and biological datasets and demonstrate its improvement in sensitivity and specificity compared to the state-of-the-art motif analysis approaches. We use MAGGIE to gain novel insights into the divergent functions of distinct NF-κB factors in pro-inflammatory macrophages, revealing the association of p65-p50 co-binding with transcriptional activation and the association of p50 binding lacking p65 with repression. The Python package for MAGGIE is freely available at https://github.com/zeyang-shen/maggie

2020-07-17 | GSE144070 | GEO

Position-dependent function of human sequence-specific transcription factors

Project description:Patterns of transcriptional activity are encoded in our genome through regulatory elements such as promoters or enhancers that, paradoxically, often contain similar assortments of sequence-specific transcription factor (TF) binding sites. Knowledge of how these sequence motifs encode multiple, often overlapping gene expression programs is central to understanding gene regulation and how mutations in non-coding DNA manifest in disease. Exploiting natural genetic variation, perturbation of endogenous TF protein levels, and analysis of synthetic regulatory elements using a novel transcription start site (TSS) capturing massively parallel reporter assay approach, here we show that the outcome of TF binding on transcription initiation is position dependent. Analyzing TF motif occurrences relative to the TSS, we identified several motifs with highly preferential and superhelical positioning. We show that these patterns are a combination of a TF's distinct functional profiles: many TFs, including canonical activators like NRF1, NFY, Sp1 or YY1, activate or repress transcription initiation depending on their precise position relative to the TSS. As such, TFs can collectively guide the site and frequency of transcription initiation. More broadly, these findings reveal how similar assortments of TFs, but with different spatial relationships, can result in distinct gene regulatory outcomes and underscore a critical role for TSS data in decoding the regulatory information of our genome.

2024-04-26 | GSE199431 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data