ArticleGenome biology2025
IT-scC&T-seq streamlines scalable, parallel profiling of protein-DNA interactions in single cells.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
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Who cites it
2 citing papers in PubMed.
- Advances in scCUT&Tag and computational analysis for single-cell gene regulatory element mapping.Briefings in bioinformatics · 2026Review
- IT-scC&T-seq streamlines scalable, parallel profiling of protein-DNA interactions in single cells.Genome biology · 2025Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Single-cell profiling protein-chromatin interactions is often constrained by complex workflows, high cost, or dependence on specialized equipment. We present indexed tagmentation-based single-cell CUT&Tag-sequencing (IT-scC&T-seq), a modular, plate-based strategy using three-round combinatorial barcoding. IT-scC&T-seq robustly profiles histone modifications and transcription factors with high specificity and throughput, supporting simultaneous analysis of multiple samples and epitopes. Notably, it enables sensitive single-cell mapping of lamina-associated domains, low-abundance chromatin features previously difficult to resolve. Applied to adult mouse mammary gland, the method reveals cell-type-specific chromatin landscapes and lineage-regulatory dynamics. Together, IT-scC&T-seq provides a scalable, cost-effective, and broadly accessible approach for high-resolution chromatin profiling.
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Registered trials
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.