Evidence map›Paper›PMID 41609358›Full record

ReviewBriefings in bioinformatics2026

Advances in scCUT&Tag and computational analysis for single-cell gene regulatory element mapping.

Jun Wu, Md Wahiduzzaman, Pengfei Yin, Puxuan Sun, Haoping Chen, Yongwen Ding, Jiankang Wang

Abstract readReview
In one paragraph

Review in Briefings in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed.

  1. Review
  2. Review
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

7 authors.

Jun WuSchool of Biomedical Sciences, Hunan University, Fubuhe Road, Yuelu District, Changsha 410082, Hunan, China.ORCID 0000-0002-1717-0378
Md WahiduzzamanSchool of Biomedical Sciences, Hunan University, Fubuhe Road, Yuelu District, Changsha 410082, Hunan, China.
Pengfei YinSchool of Biomedical Sciences, Hunan University, Fubuhe Road, Yuelu District, Changsha 410082, Hunan, China.
Puxuan SunSchool of Biomedical Sciences, Hunan University, Fubuhe Road, Yuelu District, Changsha 410082, Hunan, China.
Haoping ChenSchool of Biomedical Sciences, Hunan University, Fubuhe Road, Yuelu District, Changsha 410082, Hunan, China.
Yongwen DingSchool of Biomedical Sciences, Hunan University, Fubuhe Road, Yuelu District, Changsha 410082, Hunan, China.
Jiankang WangSchool of Biomedical Sciences, Hunan University, Fubuhe Road, Yuelu District, Changsha 410082, Hunan, China.ORCID 0000-0003-3110-0605

Funding

Changsha Municipal Natural Science Foundation kq2402059Fundamental Research Funds for the Central Universities 541109030087Guangdong Basic and Applied Basic Research Foundation 2023A1515110873Guangdong Basic and Applied Basic Research Foundation 2025A1515012822Hunan Provincial Natural Science Foundation of China 2024JJ6131National Natural Science Foundation of China 32400526
6 · The paper itself

Abstract

Histone modifications (HMs) and transcription factors (TFs) are central to chromatin dynamics and transcriptional regulation. Conventional bulk approaches like ChIP-seq require large cell populations, limiting applicability to heterogeneous studies and tissue samples. In contrast, single-cell cleavage under targets and tagmentation (scCUT&Tag) and its variants have enabled high-resolution profiling of HMs and TFs for investigating gene regulatory mechanisms in individual cells, transformatively broadening single-cell epigenomics beyond chromatin accessibility measured by scATAC-seq. Despite rapid advances in scCUT&Tag-related methods and the accumulation of ~21 public datasets, a systematic overview of the current research status, especially the forefront of computational analysis and ensuing challenges, remains lacking. Here, we comprehensively overview current scCUT&Tag studies from a bioinformatics perspective. We catalog representative applications spanning diverse chromatin features, experimental designs, and data characteristics. We delineate a typical computational workflow from matrix generation to downstream functional annotations, emphasizing distinctions from scATAC-seq analysis, and highlighting critical analytical considerations. We extensively survey commonly used computational tools and key algorithms, compare analytical features between scCUT&Tag and scATAC-seq, and discuss major challenges in integrative analysis. This work provides a structured reference for understanding the current research landscape of scCUT&Tag and offers computational perspectives for researchers aiming to explore gene regulatory machinery at single-cell resolution.

Indexed as

Computational BiologyRegulatory Elements, TranscriptionalRegulatory Sequences, Nucleic AcidSingle-Cell AnalysisAlgorithmsAnimalsChromatinEpigenomicsHumansTranscription FactorsChromatinTranscription Factorsbioinformaticscomputational analysisscCUT&Tagsingle-cell epigenomicstranscriptional regulation

Identifiers

PMID41609358
PMCPMC12853305

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.