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Semi-automated IT-scATAC-seq profiles cell-specific chromatin accessibility in differentiation and peripheral blood populations

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Abstract Single-cell ATAC-seq (scATAC-seq) enables high-resolution mapping of chromatin accessibility but is often limited by throughput, cost, and equipment requirements. Here, we present indexed Tn5 tagmentation-based scATAC-seq (IT-scATAC-seq), a semi-automated, cost-effective, and scalable approach that leverages indexed Tn5 transposomes and a three-round barcoding strategy. This workflow prepares libraries for up to 10,000 cells in a single day, reduces the per-cell cost to approximately $0.01, and maintains high data quality. Comprehensive benchmarking demonstrates that IT-scATAC-seq achieves robust library complexity, high signal specificity, and improved cost-efficiency compared to existing methods. We apply IT-scATAC-seq to mouse embryonic stem cells, capturing chromatin remodelling during early differentiation, and to human peripheral blood mononuclear cells, resolving cell-type–specific regulatory programs. Here, we show that IT-scATAC-seq provides a robust and efficient approach for high-resolution single-cell epigenomic investigations, balancing scalability, data quality, and accessibility.
Title: Semi-automated IT-scATAC-seq profiles cell-specific chromatin accessibility in differentiation and peripheral blood populations
Description:
Abstract Single-cell ATAC-seq (scATAC-seq) enables high-resolution mapping of chromatin accessibility but is often limited by throughput, cost, and equipment requirements.
Here, we present indexed Tn5 tagmentation-based scATAC-seq (IT-scATAC-seq), a semi-automated, cost-effective, and scalable approach that leverages indexed Tn5 transposomes and a three-round barcoding strategy.
This workflow prepares libraries for up to 10,000 cells in a single day, reduces the per-cell cost to approximately $0.
01, and maintains high data quality.
Comprehensive benchmarking demonstrates that IT-scATAC-seq achieves robust library complexity, high signal specificity, and improved cost-efficiency compared to existing methods.
We apply IT-scATAC-seq to mouse embryonic stem cells, capturing chromatin remodelling during early differentiation, and to human peripheral blood mononuclear cells, resolving cell-type–specific regulatory programs.
Here, we show that IT-scATAC-seq provides a robust and efficient approach for high-resolution single-cell epigenomic investigations, balancing scalability, data quality, and accessibility.

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