Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

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

ABSTRACT: Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3 [Bulk]

PROVIDER: PRJNA1127433 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR29506383_1.fastq.gz	Fastqsanger.gz
	SRR29506383_2.fastq.gz	Fastqsanger.gz
	SRR29506384_1.fastq.gz	Fastqsanger.gz
	SRR29506384_2.fastq.gz	Fastqsanger.gz
	SRR29506385_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 16

Similar Datasets

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

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

2024-06-24 | GSE270511 | GEO

Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3 [HT SS3]

2024-07-02 | GSE270928 | GEO

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

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

| PRJNA1129021 | ENA

Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3 [HT SS3]

Project description:Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3 [HT SS3]

| PRJNA1129044 | ENA

Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3.

Project description:We developed an automated high-throughput Smart-seq3 (HT Smart-seq3) workflow that integrates best practices and an optimized protocol to enhance efficiency, scalability, and method reproducibility. This workflow consistently produces high-quality data with high cell capture efficiency and gene detection sensitivity. In a rigorous comparison with the 10X platform using human primary CD4 + T-cells, HT Smart-seq3 demonstrated higher cell capture efficiency, greater gene detection sensitivity, and lower dropout rates. Additionally, when sufficiently scaled, HT Smart-seq3 achieved a comparable resolution of cellular heterogeneity to 10X. Notably, through T-cell receptor (TCR) reconstruction, HT Smart-seq3 identified a greater number of productive alpha and beta chain pairs without the need for additional primer design to amplify full-length V(D)J segments, enabling more comprehensive TCR profiling across a broader range of species. Taken together, HT Smart-seq3 overcomes key technical challenges, offering distinct advantages that position it as a promising solution for the characterization of single-cell transcriptomes and immune repertoires, particularly well-suited for low-input, low-RNA content samples.

| S-EPMC11583680 | biostudies-literature

K562+mESC Smart-seq3

Project description:Single cell sequencing with Smart-seq3 of K562 and mESC cells

| PRJEB67545 | ENA

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

Allelic dilution series series of C57BL6/J:CAST/EiJ RNA using Smart-seq3

Project description:Technical control for allelic detection using Smart-seq3. Liver RNA from pure C57BL6/J and CAST/EiJ strains was combined at varying ratios (0:1, 1:7, 1:3, 3:5, 1:1, 5:3, 3:1, 7:1, 1:0) for a total of 200 pg RNA per sample.

2022-02-14 | E-MTAB-10709 | biostudies-arrayexpress

Allele-resolved scRNA-seq of primary mouse fibroblasts using Smart-seq3

Project description:Allele-sensitive RNA sequencing of single-cells can be used to infer the kinetics of transcriptional bursts in eukaryotic cells. Here, we used the Smart-seq3 protocol to prepare libraries from two 384-well plates of primary mouse fibroblasts. The fibroblasts were derived from tail explants of a male adult mouse (F1 offspring of C57 x CAST cross). The samples were sequenced to high depth using MGI's DNBSEQ G400RS platform using paired-end 100 bp reads.

2021-02-25 | E-MTAB-10148 | biostudies-arrayexpress

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