DUET-seq: An Open-Source Droplet Platform for High-Fidelity Joint Chromatin and Transcriptome Profiling Reveals Temporal Regulatory Decoupling in Single Cells.

Authors

Dong Cheng, Zijun Meng, Lan Wei, Pingjing Yang, Fanfan Zhang, Zhiyi Luo, Ting Lai, Chunli Li, Mengyao Zhao, Mengqin Xu, Jiaqi Wang, Linjun Li, Huarong Chen, Jin Li, Ailong Huang, Youquan Bu, Liuyang Zhao

Published in

Advanced science (Weinheim, Baden-Wurttemberg, Germany). Pages e77986. Sep 27, 2026. Epub Sep 27, 2026.

Abstract

Joint profiling of chromatin accessibility and gene expression in the same cell enables direct linkage of regulatory elements to transcriptional output, but existing approaches remain limited by low co-capture sensitivity, proprietary platforms, and high costs. Here we present DUET-seq, an open-source droplet microfluidic platform for joint profiling of chromatin accessibility and gene expression from the same nucleus. DUET-seq combines programmable dissolvable dual-linker hydrogel beads with one-step intra-droplet RT-PCR to physically co-index RNA and transposed chromatin fragments, completing library preparation within 12 h. Optimization of joint reaction conditions, including suppression of residual Tn5 activity, achieves ∼3,200 genes per HEK293T cell while maintaining high-quality chromatin accessibility profiles. By providing a fully disclosed reagent-and-device ecosystem, DUET-seq enables researchers to optimize lysis and reaction chemistry for non-standard tissues without proprietary constraints. We demonstrate the platform's versatility by mapping over 14,000 cis-regulatory element-to-gene linkages in adult mouse brain and by profiling ∼29,000 nuclei across six stages of postnatal spermatogenesis, where paired measurements reveal two modes of temporal regulatory decoupling-epigenetic priming and chromatin inertia-that are inaccessible to unimodal assays. DUET-seq thus provides an accessible, cost-effective framework for joint single-nucleus multi-omic profiling, with broad applicability across developmental biology, disease epigenomics, and functional genomics.

PMID:
42801560
Bibliographic data and abstract were imported from PubMed on 28 Sep 2026.

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