Transcriptional diversity during lineage commitment of human blood progenitors

Abstract

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 identified extensive cell type-specific expression changes: 6711 genes and 10,724 transcripts, enriched in non-protein-coding elements at early stages of differentiation. In addition, we found 7881 novel splice junctions and 2301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrated experimentally cell-specific isoform usage, identifying nuclear factor I/B (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.

Figure

RNA-seq reads from human blood progenitors (opaque cells in A) were mapped to the transcriptome to quantify gene and transcript expression. Reads were also mapped to the genome to identify novel splice junctions and characterize alternative splicing events (B).

Fig. 1

Transcriptional atlas of hematopoietic progenitors and precursors. (A) Schematic representation of the current model of hematopoietic cell ontogeny and samples used in this study. Established ontological relationships are represented as solid lines, emerging ontological relationship are represented as dotted lines. A simplified representation of mature cells is shaded. Antigens used for selecting each population are also indicated. The bone marrow residing components are the hematopoietic stem cell (HSC, light blue), multipotent progenitor (MPP, dark blue), lymphoid-primed multipotent progenitor (LMPP), common lymphoid progenitor (CLP, light green), common myeloid progenitor (CMP, dark green), granulocyte monocyte progenitor (GMP, light red), megakaryocyte erythrocyte progenitor (MEP, red), erythroblast (EB, light orange), megakaryocyte (MK, orange). The blood residing components are platelets (P), erythrocyte (E), neutrophil (N), eosinophil (Eo), monocyte (M) and lymphocyte (L). (B) Data analysis strategy. Reads were mapped to the transcriptome to quantify expression at the gene and transcript levels as well as the transcript proportion (defined as the fraction of gene expression level from a given transcript). Complementary to that, reads were mapped to the genome to identify novel splice junctions and sites where alternative splicing occurs. (C) Schematic highlighting the difference between assessing differential expression by looking at transcript expression or at transcript proportion.

Fig. 2

Transcriptional changes at lineage commitment events. (A) River plot representing gene expression levels across cell types for key transcription factors (TFs) required for lineage commitment. Line width represents expression level in log2(FPKM+1) normalized to the highest expression per gene across cell types. The relative changes in gene expression recapitulate the current understanding of the role of these TFs in hematopoietic differentiation. (B) Summary of the number of transcriptional classes - genes, transcripts and transcript proportions - changing at each lineage commitment point. Bayesian polytomous analysis was used to classify these 3 quantities into 5 possible models, from top to bottom: NULL model (no change); three single models (only one cell type different); and a FULL model (all three estimates differ). The number of events up or down regulated were tallied only when the change occurred in at least two samples at each branching event with an expression FPKM >1. (C) Cell-specific enrichment of protein-coding and non-protein coding biotypes in up and down regulated transcripts for the polytomous models at each branching event. (D) Heatmap of expression of lineage specific transcripts. Polytomous analysis was used to identify genes that were expressed significantly higher in a given cell type relative to all others. Top 20 highest scoring transcripts based on the posterior probability of the model are displayed. The colors along the left axis reflect whether the gene is protein coding (green) or otherwise (lilac).

Fig. 3

Cell-type specific splicing and RNA-binding motif enrichment in hematopoiesis. (A) Distribution of splice junction definition, absolute count and cell-type-specific fractions within unannotated splice junctions. Blue: annotated exons and junctions; Red: unannotated exons and junctions. (B) Cell-type specificity of known, unannotated and novel splice junctions measured with Shannon’s entropy (). Lower entropy indicates that splice junctions are observed in a smaller number of cell types. (C) Region-specific patterns of RNA-binding protein motifs around spliced-in and spliced-out DSU cassette exons. The enrichment or depletion of motifs in three regions: the 300bp intronic region adjacent to the upstream of the 5′ splice site (blue); the exonic region of the cassette exon (orange); and the 300bp intronic region adjacent to the downstream of the 3′ splice site (green). The heatmaps present significant enrichment (yellow) or depletion (red) in -log10 P value, FDR< 0.05.

Fig. 4

A novel isoform of the transcription factor NFIB regulates megakaryopoiesis. (A) A novel TSS and novel exon of NFIB was detected using RNA-seq (blue) and validated using 5′ race PCR (red) and PacBio sequencing (green). Ensembl annotated transcripts in black. (B) Cartoon representation of the short and long isoforms of NFIB (NFIB-S and NFIB-L) highlighting the functional domains. (C) Western blot (WB) for NFIB, NFIC and Tubulin in megakaryocytes (MK), erythroblasts (EB) and monocytes (M) confirms that the short form of NFIB (NFIB-S) is predominantly expressed in MKs (* is either the protein product of one of the shorter transcripts of NFIB observed in the 5′ race, or is unspecific). (D) Coimmunoprecipitation of overexpressed combinations of NFIC-HA together with TAP (Flag plus CBP) tagged NFIC, NFIB-L and NFIB-S. The upper panel was probed with anti-NFIC antibodies, showing both NFIC TAP tagged (upper band) and NFIC-HA tagged (lower band); note the absence of NFIC-HA in lane 4 showing lack of interaction between NFIC and NFIB-S. The lower panel was probed with anti-Flag antibody (part of the TAP tag), showing the immunoprecipitated NFIC (lane 2), NFIB-L (lane 3) and NFIB-S (lane 4) (see also Figs. S30 and S31), (E). Flow cytometry dot plots of CD41a and CD61 staining of megakaryocyte cultures at day 10 after infection with shRNA of control, NFIB and NFIC. The proportions of double positive, upper right (megakaryocytic), versus double negative, lower left (undifferentiated), cells decreased relative to control shRNA by silencing either NFIB or NFIC. (F) Overexpression of NFIC or NFIB-S lead to a higher proportion of megakaryocytic cells relative to NFIB-L or control. CD41a and CD42b double positive MKs in cultures at day 10 after infection. The y-axis is the probit proportion of double positive MKs after adjusting for batch effects.