Inferring rules of lineage commitment in haematopoiesis

Abstract

How the molecular programs of differentiated cells develop as cells transit from multipotency through lineage commitment remains unexplored. This reflects the inability to access cells undergoing commitment or located in the immediate vicinity of commitment boundaries. It remains unclear whether commitment constitutes a gradual process, or else represents a discrete transition. Analyses of in vitro self-renewing multipotent systems have revealed cellular heterogeneity with individual cells transiently exhibiting distinct biases for lineage commitment. Such systems can be used to molecularly interrogate early stages of lineage affiliation and infer rules of lineage commitment. In haematopoiesis, population-based studies have indicated that lineage choice is governed by global transcriptional noise, with self-renewing multipotent cells reversibly activating transcriptome-wide lineage-affiliated programs. We examine this hypothesis through functional and molecular analysis of individual blood cells captured from self-renewal cultures, during cytokine-driven differentiation and from primary stem and progenitor bone marrow compartments. We show dissociation between self-renewal potential and transcriptome-wide activation of lineage programs, and instead suggest that multipotent cells experience independent activation of individual regulators resulting in a low probability of transition to the committed state.

Stochastic NANOG fluctuations allow mouse embryonic stem cells to explore pluripotency

“…This increase occurs in any of the three different culture conditions used in our studies, although there is no obvious trend in the specific lineages that low-NANOG mESCs seem to be primed: in each of the tested conditions, the combination of lineage-affiliated genes with increased expression is qualitatively and quantitatively different, suggesting that lineage commitment does not occur through fixed and hierarchically organized pathways. Our results are more compatible with stochastic models of lineage decision (Pina et al, 2012;Teles et al, 2013), in which the initial events that bias cells to specific lineages are not predetermined, and mESCs can follow multiple trajectories into commitment, exploring the whole pluripotent decision space. These initial exploratory events are still revertible and occur when mESCs reach low NANOG levels; when fluctuating NANOG levels increase and mESCs move to a high-NANOG state, active lineage-specific genes are silenced and cells return to a naïve state.…”

Pluripotent stem cells reveal erythroid-specific activities of the GATA1 N-terminus

“…Our analysis of transcriptomes in progenitor populations showed that GATA1s mutations confer a strong bias toward myelo-megakaryocytic transcription. However, individual phenotypically matched stem and progenitor cells exhibit considerable heterogeneity in gene expression (32,33). Thus, subpopulations of cells within our iPSCderived progenitor pools could exhibit different fate biases.…”

Regulatory network control of blood stem cells

“…Recent technological advances in microfluidic technology now readily permit quantification of tens to hundreds of genes in hundreds and even thousands of single cells. In addition to providing insights into population heterogeneity and putative transition stages during blood cell differentiation, [45][46][47] the scale of these datasets provides a substrate for robust statistical analysis of gene expression correlation, as each single cell analyzed represents an independent biological measurement. 48 Moignard et al surveyed the expression of 18 transcription factor genes in 690 single blood stem and progenitor cells, 47 and went on to exploit pairwise correlation analysis to identify putative regulatory relationships between individual TFs.…”