Single-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to signals, and human disease. Recent advances have allowed paired capture of protein abundance and transcriptomic state, but a lack of epigenetic information in these assays has left a missing link to gene regulation. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases signal-to-noise and allows paired measurement of cell surface markers and chromatin accessibility: integrated cellular indexing of chromatin landscape and epitopes, called ICICLE-seq. We extended this approach using a droplet-based multiomics platform to develop a trimodal assay that simultaneously measures transcriptomics (scRNA-seq), epitopes, and chromatin accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.

Multimodal analysis for human ex vivo studies shows extensive molecular changes from delays in blood processing 1) Flow Cytometry 2) Single-Cell RNAseq 3) Plasma Proteomics PBMC Time to Blood Processing (hours) PBMC Plasma Plasma Minimal Change Over 18 hours Extensive Change After 4 hours Extensive Change After 4 hours 2 4 6 Highlights Studies of human blood cells and plasma are highly sensitive to process variability Time variability distorts biology in cutting-edge single-cell and multiplex assays Longitudinal, multimodal, and aligned data enable data qualification and exploration Dataset holds potential novel, multi-modal biological correlations and hypotheses

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Profiling of open chromatin regions at the single cell level using ATAC-seq (scATAC-seq) has been instrumental in understanding the heterogeneous usage of transcription factors that drive differentiation, cellular responses to extracellular signals, and human disease states. The large size of the human genome and processing artefacts resulting in DNA damage are an inherent source of background in scATAC-seq. Furthermore, the downstream analysis of scATAC-seq to derive meaningful biological information is complicated by the lack of clear phenotypic information on each analyzed cell to allow an association between chromatin state and cell type. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases signal-to-noise ratio and allows simultaneous measurement of cell surface markers: Integrated Cellular Indexing of Chromatin Landscape and Epitopes (ICICLE-seq). Combining cell surface marker barcoding with high quality scATAC-seq offers a novel tool to identify type-specific regulatory regions based on phenotypically defined cell types.