Single cell RNA sequencing (scRNA-seq) has become an established and powerful method to investigate transcriptomic cell-to-cell variation, revealing new cell types, and providing insights into developmental processes and transcriptional stochasticity. The array of published scRNA-seq protocols allow one to sequence transcriptomes from minute amounts of starting material. A key question is how these various protocols compare in terms of sensitivity of detection of mRNA molecules, and accuracy of quantification of expression. Here, we present an assessment of sensitivity and accuracy of many published data sets by spike-in standards with uniform data processing, including development of a flexible Unique Molecular Identifier (UMI) counting tool (https://github.com/vals/umis). We computationally compare 15 protocols, and experimentally assess 4 protocols on batch-matched cell populations, as well as investigating the impact of spike-in molecule degradation on two types of spike-ins. Our analysis provides an integrated framework for comparing different scRNA-seq protocols.

Blood cells derive from hematopoietic stem cells through stepwise fating events. To characterize gene expression programs driving lineage choice we sequenced RNA from eight primary human hematopoietic progenitor populations representing the major myeloid commitment stages and the main lymphoid stage. We identify extensive cell-type specific expression changes: 6,711 genes and 10,724 transcripts, enriched in non-protein coding elements at early stages of differentiation. In addition, we discovered 7,881 novel splice junctions and 2,301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrate experimentally cell specific isoform usage, identifying NFIB as a regulator of megakaryocyte maturation -the platelet precursor. Our data highlight the complexity of fating events in closely related progenitor populations, the understanding of which is essential for the advancement of transplantation and regenerative medicine.

Lysine acetylation modulates the activities of nonhistone regulatory proteins and plays a critical role in the regulation of cellular gene transcription. In this study, we showed that the transcriptional coactivator p300 acetylated ␤-catenin at lysine 345, located in arm repeat 6, in vitro and in vivo. Acetylation of this residue increased the affinity of ␤-catenin for Tcf4, and the cellular Tcf4-bound pool of ␤-catenin was significantly enriched in acetylated form. We demonstrated that the acetyltransferase activity of p300 was required for efficient activation of transcription mediated by ␤-catenin/Tcf4 and that the cooperation between p300 and ␤-catenin was severely reduced by the K345R mutation, implying that acetylation of ␤-catenin plays a part in the coactivation of ␤-catenin by p300. Interestingly, acetylation of ␤-catenin had opposite, negative effects on the binding of ␤-catenin to the androgen receptor. Our data suggest that acetylation of ␤-catenin in the arm 6 domain regulates ␤-catenin transcriptional activity by differentially modulating its affinity for Tcf4 and the androgen receptor. Thus, our results describe a new mechanism by which p300 might regulate ␤-catenin transcriptional activity.

SummaryThe transcriptional programs that govern hematopoiesis have been investigated primarily by population-level analysis of hematopoietic stem and progenitor cells, which cannot reveal the continuous nature of the differentiation process. Here we applied single-cell RNA-sequencing to a population of hematopoietic cells in zebrafish as they undergo thrombocyte lineage commitment. By reconstructing their developmental chronology computationally, we were able to place each cell along a continuum from stem cell to mature cell, refining the traditional lineage tree. The progression of cells along this continuum is characterized by a highly coordinated transcriptional program, displaying simultaneous suppression of genes involved in cell proliferation and ribosomal biogenesis as the expression of lineage specific genes increases. Within this program, there is substantial heterogeneity in the expression of the key lineage regulators. Overall, the total number of genes expressed, as well as the total mRNA content of the cell, decreases as the cells undergo lineage commitment.