Evidence map›Paper›PMID 39287475›Full record

ArticleAnalytical chemistry2024

DEPICT-seq: Single-Cell Transcriptomic Analysis of Rare Cell Subsets Isolated via Nucleic Acid Cytometry.

Kaixuan Bao, Xiaochun Jiang, Hong-Min Hu, Tiemin Liu, Jingwei Zhang

Abstract read
In one paragraph

Article in Analytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kaixuan BaoState Key Laboratory of Genetic Engineering, Human Phenome Institute, Department of Endocrinology and Metabolism, School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai 200438, China.ORCID 0000-0002-4502-0545
Xiaochun JiangImmuXell Biotech Ltd., Shanghai 201315, China.
Hong-Min HuImmuXell Biotech Ltd., Shanghai 201315, China.
Tiemin LiuState Key Laboratory of Genetic Engineering, Human Phenome Institute, Department of Endocrinology and Metabolism, School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai 200438, China.
Jingwei ZhangState Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to dive deep into specific rare cell populations is critical for understanding tissue physiology and pathology across various biological domains. As single-cell RNA-seq flourishes, many newly discovered cell subtypes are defined by their transcriptomic markers. However, our ability to retrieve and analyze cells based on their nucleic acid markers remains underdeveloped. Here, we present Double Emulsion PCR-Initiated Cell sorting and Transcriptomic Sequencing (DEPICT-seq), a high-throughput droplet nucleic acid cytometry method that integrates batch cell fixation for cellular information preservation, double emulsion digital PCR-based cell sorting to target nucleic acid markers of interest, and in-depth full-length transcriptomic analyses at single-cell resolution. We utilize DEPICT-seq to isolate and characterize T cell receptor (TCR)-engineered T cells within a mixed population and also demonstrate a variation of the workflow by incorporating an RNase H-dependent PCR step to enrich full-length TCR sequences for paired single-cell TCR sequencing and transcriptomic profiling.

Indexed as

Single-Cell AnalysisAnimalsFlow CytometryGene Expression ProfilingHumansNucleic AcidsPolymerase Chain ReactionReceptors, Antigen, T-CellT-LymphocytesTranscriptomeNucleic AcidsReceptors, Antigen, T-Cell

Identifiers

PMID39287475
PMCPMC11483345

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.