Time series single-cell RNA sequencing of murine hematopoetic stem and progenitors (HSPCs) following in vivo IFNa treatment

The molecular and cellular dynamics of hematopoietic stem and progenitor cells (HSPCs) during the course of inflammation remain poorly studied. It has been challenging to characterize inflammation in HSPCs due to changes in cell type-specific surface markers. To address this challenge, we performed single-cell RNA sequencing of HSPCs at multiple time points (3, 24, and 72 hours) after treatment with the pro-inflammatory cytokine IFNa and developed a computational pipeline suitable for processing and analyzing single-cell time series dataset. Using a semi-supervised response-pseudotime inference approach, we discover a variety of different gene responses of the HSPCs to the treatment. Interestingly, we were able to associate the myeloid abundance changes with downregulated myeloid differentiation programs in HSCs and progenitors following IFNa treatment. Using single-cell time series we have been able to unbiasedly study the heterogeneous and dynamic impact of IFNa on the HSPCs Overall design: We performed a time course single-cell RNA sequencing experiment. Bone marrow (BM) cells were collected from four different mice for each timepoint (including four control mice injected with PBS). Using oligo-tagged antibodies, or hashtags, we labeled the cells from each biological replicate and timepoint to address inter-animal heterogeneity of the inflammatory stress response. Following cell hashing, BM cells from mice of the same treatment were pooled together. BM cells were then sorted by using the broad lineage negative (Lin-) and c-kit positive (c-Kit+) (LK) gating strategy to capture a wide spectrum of the HSPC transcriptional landscape. To guarantee sufficient numbers of HSCs for analysis, we additionally enriched the sorted populations with LKSLAMCD34-, since they are much less frequent than the other populations in the LK gate. The cells from all four experimental time points (control, 3h, 24h, and 72h) were sequenced simultaneously using the 10x Genomics platform.