Sampling time-dependent artifacts in single-cell genomics studies

Robust protocols and automation now enable large-scale single-cell RNA and ATAC sequencing experiments and their application on biobank and clinical cohorts. However, technical biases introduced during sample acquisition can hinder solid, reproducible results and a systematic benchmarking is required before entering large-scale data production. Here, we report the existence and extent of gene expression and chromatin accessibility artifacts introduced during sampling and identify experimental and computational solutions for their prevention. We designed benchmarking experiments to systematically test the effect of varying processing times on single-cell transcriptome and epigenome profiles from healthy and diseased donors, while controlling for technical variability (e.g. batch effects). We isolated peripheral blood mononuclear cells from healthy donors (PBMC) and from patients affected with chronic lymphocytic leukemia (CLL), the most common adult leukemia in the Western world. Samples were either preserved immediately (0 hours) or after 2, 4, 6, 8, 24 and 48 hours; simulating common scenarios in biobank and clinical routines. Single-cell 3`-transcript counting, full-length transcriptome and scATAC-seq were performed to monitor gene expression, RNA integrity and open chromatin variance across preservation time points.