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

Jun Wu1, Md Wahiduzzaman1, Pengfei Yin1

  • 1School of Biomedical Sciences, Hunan University, Fubuhe Road, Yuelu District, Changsha 410082, Hunan, China.

Briefings in Bioinformatics
|January 29, 2026
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Summary

Single-cell CUT&Tag (scCUT&Tag) enables high-resolution epigenomic profiling of histone modifications and transcription factors in individual cells. This review provides a bioinformatics perspective on scCUT&Tag methods, analysis, and challenges.

Keywords:
bioinformaticscomputational analysisscCUT&Tagsingle-cell epigenomicstranscriptional regulation

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Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Histone modifications (HMs) and transcription factors (TFs) are crucial for gene regulation.
  • Conventional bulk methods like ChIP-seq have limitations for heterogeneous samples.
  • Single-cell CUT&Tag (scCUT&Tag) offers high-resolution profiling of HMs and TFs in individual cells, expanding single-cell epigenomics.

Purpose of the Study:

  • To provide a systematic overview of scCUT&Tag research from a bioinformatics perspective.
  • To catalog applications, computational workflows, and analytical considerations for scCUT&Tag.
  • To identify challenges and offer perspectives for exploring gene regulatory machinery at single-cell resolution.

Main Methods:

  • Comprehensive review of existing scCUT&Tag studies and public datasets.
  • Delineation of a typical computational workflow from matrix generation to functional annotation.
  • Survey and comparison of computational tools and algorithms for scCUT&Tag and scATAC-seq.

Main Results:

  • Cataloged diverse applications of scCUT&Tag across various chromatin features and experimental designs.
  • Detailed a typical computational workflow, highlighting differences from scATAC-seq analysis.
  • Compared analytical features of scCUT&Tag and scATAC-seq, discussing integration challenges.

Conclusions:

  • scCUT&Tag is a transformative technology in single-cell epigenomics.
  • A structured bioinformatics reference is provided for understanding scCUT&Tag landscape.
  • Offers computational perspectives for researchers studying gene regulation at single-cell resolution.