A strategy to address dissociation-induced compositional and transcriptional bias for single-cell analysis of the human mammary gland
Single-cell transcriptomics provide insights into cellular heterogeneity and lineage dynamics that are key to better understanding normal mammary gland function as well as breast cancer initiation and progression. In contrast to murine tissue, human mammary glands require laborious dissociation protocols to isolate single cells. This leads to unavoidable procedure-induced compositional and transcriptional bias. Here, we present a new strategy on how to identify and minimize systematic error by combining different tissue dissociation strategies and then directly comparing composition and transcriptome of isolated cells using single-cell RNA sequencing and flow cytometry. Depending on the tissue isolation strategy, we found dramatic differences in abundance and heterogeneity of certain stromal cells types. Moreover, we identified lineage-specific dissociation-induced gene expression changes that, if left unchecked, could lead to misinterpretation of cellular heterogeneity and, since the basal epithelial population is particularly affected by this, wrongful assignment of putative stem cell populations.