Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Targeted single cell RNA-sequencing of transcription factors facilitates biological insights from human cell experimental models [iPSC neuron pre-capture]

ABSTRACT: Single cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ~1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell-type identification, developmental trajectories and gene regulatory networks. This allowed us to resolve differences amongst neuronal populations, which were generated in two different labs using the same differentiation protocol. ScCapture-seq improved TF gene-regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signalling in the developmental divergence between these different neuronal populations. Our results demonstrate that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to any cellular models to improve scRNA-seq resolution

ORGANISM(S): Homo sapiens

PROVIDER: GSE168590 | GEO | 2021/03/10

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Targeted single cell RNA-sequencing of transcription factors facilitates biological insights from human cell experimental models [intestinal stromal cells pre-capture]

Project description:Single cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ~1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell-type identification, developmental trajectories and gene regulatory networks. This allowed us to resolve differences amongst neuronal populations, which were generated in two different labs using the same differentiation protocol. ScCapture-seq improved TF gene-regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signalling in the developmental divergence between these different neuronal populations. Our results demonstrate that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to any cellular models to improve scRNA-seq resolution

2021-03-10 | GSE168626 | GEO

Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models [iPSC-derived neurons]

2021-03-06 | GSE157835 | GEO

Single cell enhancer activity distinguishes GABAergic and cholinergic lineages in embryonic mouse basal ganglia

Project description:Enhancers integrate transcription factor signaling pathways that drive cell fate specification in the developing brain. We paired enhancer labeling and single-cell RNA-sequencing (scRNA-seq) to delineate and distinguish specification of neuronal lineages in mouse medial, lateral, and caudal ganglionic eminences (MGE, LGE, and CGE) at embryonic day (E)11.5. We show that scRNA-seq clustering using transcription factors improves resolution of regional and developmental populations, and that enhancer activities identify specific and overlapping GE-derived neuronal populations. First, we mapped the activities of seven evolutionarily conserved brain enhancers at single-cell resolution in vivo, finding that the selected enhancers had diverse activities in specific progenitor and neuronal populations across the GEs. We then applied enhancer-based labeling, scRNA-seq, and analysis of in situ hybridization data to distinguish transcriptionally distinct and spatially defined subtypes of MGE-derived GABAergic and cholinergic projection neurons and interneurons. Our results map developmental origins and specification paths underlying neurogenesis in the embryonic basal ganglia and showcase the power of scRNA-seq combined with enhancer-based labeling to resolve the complex paths of neuronal specification underlying mouse brain development.

2022-04-01 | GSE199352 | GEO

Combinatorial transcription factor profiles predict mature and functional human islet α and β cells

Project description:Islet-enriched transcription factors (TFs) exert broad control over cellular processes in pancreatic α and β cells and changes in their expression are associated with developmental state and diabetes. However, the implications of heterogeneity in TF expression across islet cell populations are not well understood. To define this TF heterogeneity and its consequences for cellular function, we profiled >40,000 cells from normal human islets by scRNA-seq and stratified α and β cells based on combinatorial TF expression. Subpopulations of islet cells co-expressing ARX/MAFB (α cells) and MAFA/MAFB (β cells) exhibited greater expression of key genes related to glucose sensing and hormone secretion relative to subpopulations expressing only one or neither TF. Moreover, all subpopulations were identified in native pancreatic tissue from multiple donors. By Patch-seq, MAFA/MAFB co-expressing β cells showed enhanced electrophysiological activity. Thus, these results indicate combinatorial TF expression in islet α and β cells predicts highly functional, mature subpopulations.

2021-09-09 | GSE183568 | GEO

Self-reporting transposons enable simultaneous readout of gene expression and transcription factor binding in single cells

Project description:In situ assays of transcription factor (TF) binding are confounded by cellular heterogeneity and represent averaged profiles in complex tissues. Single cell RNA-seq (scRNA-seq) is capable of resolving different cell types based on gene expression profiles, but no technology exists to directly link specific cell types to the binding pattern of TFs in those cell types. Here, we present self-reporting transposons (SRTs) and their use in single cell calling cards (scCC), a novel assay for simultaneously capturing gene expression profiles and mapping TF binding sites in single cells. First, we show how the genomic locations of SRTs can be recovered from mRNA. Next, we demonstrate that SRTs deposited by the piggyBac transposase can be used to map the genome-wide localization of the TFs SP1, through a direct fusion of the two proteins, and BRD4, through its native affinity for piggyBac. We then present the scCC method, which maps SRTs from scRNA-seq libraries, thus enabling concomitant identification of cell types and TF binding sites in those same cells. As a proof-of-concept, we use scCC to map the binding of BRD4 and three additional TFs in cultured cells. We then apply this technique to discover bromodomain-dependent cell state dynamics in K562 cells. Finally, we map BRD4 binding sites in the mouse cortex at single cell resolution, thus establishing a new technique for studying TF biology in situ.

2020-07-23 | GSE148448 | GEO

scATAC-seq of early brain organoid development from pluripotency

Project description:To study developmental trajectories in brain organoids, we conducted scRNA-seq and scATAC-seq in parallel on a dense timecourse of early development.

2022-08-18 | E-MTAB-11998 | biostudies-arrayexpress

scRNA-seq of early brain organoid development from pluripotency

Project description:To study developmental trajectories in brain organoids, we conducted scRNA-seq and scATAC-seq in parallel on a dense timecourse of early development.

2022-08-18 | E-MTAB-12001 | biostudies-arrayexpress

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites [Validation Set]

Project description:During cell division, transcription factors (TFs) are removed from chromatin twice, during DNA synthesis, and during condensation of chromosomes. How TFs can efficiently find their sites following these stages has been unclear. Here, we have analyzed the binding pattern of expressed TFs in human colorectal cancer cells. We find that binding of TFs is highly clustered, and that the clusters are enriched in binding motifs for several major TF classes. Strikingly, almost all clusters are formed around cohesin, and loss of cohesin decreases both DNA accessibility and binding of TFs to clusters. We show that cohesin remains bound in S phase, holding the nascent sister chromatids together at the TF cluster sites. Furthermore, cohesin remains bound to the cluster sites when TFs are evicted in early M-phase. These results suggest that cohesin binding functions as a cellular memory that promotes re- stablishment of TF clusters after DNA replication and chromatin condensation. Examination of TF binding by ChIP-seq in a CRC cell-line.

2013-09-25 | E-GEOD-51142 | biostudies-arrayexpress

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites

2013-08-15 | E-GEOD-49402 | biostudies-arrayexpress

Comparative binding patterns of Chromatin Regulators in normal versus leukemic hematopoiesis [ChIP-Seq]

Project description:Cellular differentiation-trajectories require extensive alterations in chromatin structure and function, elicited by a diverse array of chromatin-factors (CFs). Using haematopoiesis as a model-system, we combined bulk ex vivo and single-cell in vivo CRISPR screens to comprehensively characterise the role of CF families in cell-fate decisions. We uncover marked lineage specificities for many CFs, dissecting specific CF-dependencies in vivo at single-cell resolution. This highlights functional diversity among related CFs (i.e. BAF-subcomplexes, MLL-methyltransferases), but also reveals functional redundancy among unrelated Repressive-complexes that restrain excessive myeloid differentiation. Epigenetic-profiling, molecularly explains CF lineage-dependencies, identifying differentiation stage-specific interactions between individual CFs and lineage-determining Transcription Factors (TFs). Intriguingly, non-canonical BAF remodeler disruption abrogates myeloid-TF function generating a pre-leukaemia phenotype. Screening CF functions in leukemia, we show that leukaemia cells abrogate normal CF function, restraining differentiation trajectories by engaging in novel CF-TF interactions that suggest potential therapeutic avenues. Together, our work greatly elucidates the role of CFs and their TF-partners across normal and malignant haematopoiesis.

2023-05-23 | GSE213507 | 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