Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Fast and flexible profiling of chromatin accessibility and total RNA expression in single nucleus using Microwell-seq3 [MW3_Tumor]

ABSTRACT: Chromatin accessibility and transcriptome profiling are the most critical tools in single-cell technologies. Here, we present Microwell-seq3, a high-throughput and easy-to-handle platform for high-sensitive single-nucleus chromatin accessibility or full-length gene expression profiling. The method combined pre-indexing and a dual-pass “chip-in-tube” strategy for nuclei loading and DNA amplification. Therefore, Microwell-seq3 does not require specialized equipment and is suitable for any molecular biology lab with simple consumables and thermal cycler. We applied Microwell-seq3 to profile the chromatin accessibility in more than 200,000 single nuclei and the full-length transcriptome in about 50,000 nuclei from multiple adult mouse tissues. Joint analysis of cell-type specific regulatory elements and total RNA uncovered cell type heterogeneity and differentially expressed genes in brain compared with previous polyadenylated transcripts capturing methods. Gene regulatory networks based on full-length transcriptome and chromatin accessibility provided improved cell-cell communications in neurons and glia. Finally, we applied Microwell-seq3 to comprehensively characterize malignant cells in spontaneous tumors from aging mouse.

ORGANISM(S): Mus musculus

PROVIDER: GSE225132 | GEO | 2024/01/03

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Fast and flexible profiling of chromatin accessibility and total RNA expression in single nucleus using Microwell-seq3 [MW3_WT]

Project description:Chromatin accessibility and transcriptome profiling are the most critical tools in single-cell technologies. Here, we present Microwell-seq3, a high-throughput and easy-to-handle platform for high-sensitive single-nucleus chromatin accessibility or full-length gene expression profiling. The method combined pre-indexing and a dual-pass “chip-in-tube” strategy for nuclei loading and DNA amplification. Therefore, Microwell-seq3 does not require specialized equipment and is suitable for any molecular biology lab with simple consumables and thermal cycler. We applied Microwell-seq3 to profile the chromatin accessibility in more than 200,000 single nuclei and the full-length transcriptome in about 50,000 nuclei from multiple adult mouse tissues. Joint analysis of cell-type specific regulatory elements and total RNA uncovered cell type heterogeneity and differentially expressed genes in brain compared with previous polyadenylated transcripts capturing methods. Gene regulatory networks based on full-length transcriptome and chromatin accessibility provided improved cell-cell communications in neurons and glia. Finally, we applied Microwell-seq3 to comprehensively characterize malignant cells in spontaneous tumors from aging mouse.

2024-01-03 | GSE225133 | GEO

Fast and flexible profiling of chromatin accessibility and total RNA expression in single nucleus using Microwell-seq3

Project description:Fast and flexible profiling of chromatin accessibility and total RNA expression in single nucleus using Microwell-seq3

| PRJNA934073 | ENA

Fast and flexible profiling of chromatin accessibility and total RNA expression in single nucleus using Microwell-seq3 [MW3_WT]

Project description:Fast and flexible profiling of chromatin accessibility and total RNA expression in single nucleus using Microwell-seq3 [MW3_WT]

| PRJNA934473 | ENA

Fast and flexible profiling of chromatin accessibility and total RNA expression in single nucleus using Microwell-seq3 [MW3_Tumor]

Project description:Fast and flexible profiling of chromatin accessibility and total RNA expression in single nucleus using Microwell-seq3 [MW3_Tumor]

| PRJNA934469 | ENA

Multi-modal single-cell sequencing of differentiating mESCs using Smart-seq3 and scATAC-seq

Project description:We report dynamics of X-chromosome upregulation (XCU) along X-chromosome inactivation (XCI) in mESCs as they differentiate into EpiSCs. F1 hybrid C57BL6/J × CAST/EiJ male and female mESCs were grown in serum/LIF conditions were differentiated using Fgf2 and Activin A for 1, 2, 4 and 7 days to induce random XCI in female cells. Multi-modal single-cell sequencing was performed using scATAC on nuclei and Smart-seq3 to assay chromatin accessibility and poly-A+ RNA expression, respectively. Allelic resolution is achieved using strain-specific SNPs in the data. We reveal dynamic balancing of X alleles as cells undergo XCI to compensate dosage imbalances between sexes as well as between X and autosomes. Furthermore, we reveal that female naïve mESCs with two active X chromosomes lack XCU on both alleles which has major implications for reprogramming studies. Finally, we estimate allelic transcriptional burst kinetics from the data and find that progressively increased burst frequencies underlies the XCU process.

2022-02-14 | E-MTAB-10714 | biostudies-arrayexpress

Single-cell RNA counting at allele- and isoform-resolution using Smart-seq3

Project description:Large-scale sequencing of RNAs from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states. However, current single-cell RNA-sequencing (scRNA-seq) methods have limited ability to count RNAs at allele- and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells. Here, we introduce Smart-seq3 that combines full-length transcriptome coverage with a 5’ unique molecular identifier (UMI) RNA counting strategy that enabled in silico reconstruction of thousands of RNA molecules per cell. Importantly, a large portion of counted and reconstructed RNA molecules could be directly assigned to specific isoforms and allelic origin, and we identified significant transcript isoform regulation in mouse strains and human cell types. Moreover, Smart-seq3 showed a dramatic increase in sensitivity and typically detected thousands more genes per cell than Smart-seq2. Altogether, we developed a short-read sequencing strategy for single-cell RNA counting at isoform and allele-resolution applicable to large-scale characterization of cell types and states across tissues and organisms.

2020-04-14 | E-MTAB-8735 | biostudies-arrayexpress

Mapping Mouse Cell Atlas by Microwell-seq

Project description:We developed Microwell-seq, a high-throughput and low-cost scRNA-seq platform using simple, inexpensive devices. Using Microwell-seq, we constructed a basic scheme for the Mouse Cell Atlas. We reveal single cell hierarchy for many tissues that have not been well previously characterized. Our study demonstrates the wide applicability of the Microwell-seq technology and the Mouse Cell Atlas resource.

2018-02-14 | GSE108097 | GEO

Single-cell RNA sequencing of differentiating mESCs using Smart-seq3

Project description:We report dynamics of X-chromosome upregulation (XCU) along X-chromosome inactivation (XCI) in mESCs as they differentiate into EpiSCs. F1 hybrid C57BL6/J × CAST/EiJ male and female mESCs were adapted to 2i/LIF and female cells grown in serum/LIF conditions were differentiated using Fgf2 and Activin A for 1, 2, 4 and 7 days to induce random XCI. scRNA-seq was performed using the Smart-seq3 protocol, providing full-length coverage together with molecular counting using UMIs. Allelic resolution is achieved using strain-specific SNPs in the data. We reveal dynamic balancing of X alleles as cells undergo XCI to compensate dosage imbalances between sexes as well as between X and autosomes. Furthermore, we reveal that female naïve mESCs with two active X chromosomes lack XCU on both alleles which has major implications for reprogramming studies. Finally, we estimate allelic transcriptional burst kinetics from the data and find that progressively increased burst frequencies underlies the XCU process.

2022-02-14 | E-MTAB-9324 | biostudies-arrayexpress

High-throughput Microwell-seq 2.0 reveals massively multiplexed chemical perturbation

Project description:Combining in-cell RT and Microwell-seq 1.0, we established Microwell-seq 2.0 for cost-effective HTS with scRNA-seq-based phenotyping. To assess the fidelity of the Microwell-seq 2.0, we performed a species-mixing experiment with cultured human (293T) and mouse (3T3) cells. Moreover, we assessed the platform on tissue cells with more heterogeneous cell types. By harnessing the power of Microwell-seq 2.0, we analyzed massively multiplexed chemical perturbation of human embryonic stem cells (hESCs) at the single-cell resolution.

2021-11-09 | GSE175413 | GEO

Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3 [10X]

Project description:We developed an automated high-throughput Smart-seq3 (HT Smart-seq3) workflow via robotic implementation and established best practices to consistently achieve high cell capture efficiency and data quality. In comparison with the 10X platform, HT Smart-seq3 analysis of primary CD4+ T-cells demonstrated superior sensitivity in gene detection and similar capability to capture major cellular heterogeneity upon sufficient scaling up. Notably, through T-cell receptor (TCR) reconstruction, HT Smart-seq3 identified more productive pairs of alpha and beta chains without additional primer design, enabling more comprehensive profiling of TCRs. Collectively, HT Smart-seq3 provides a cost-effective and scalable method for characterization of single-cell transcriptomes and immune repertoires.

2024-07-02 | GSE270917 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

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