title: 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.
authors.affiliation: Stem Cell Laboratory, UCL Cancer Institute, University College London, London WC1E 6BT, UK.
authors.forename: Cristina
authors.initials: C
authors.lastname: Pina
authors.forename: Cristina
authors.initials: C
authors.lastname: Fugazza
authors.forename: Alex J
authors.initials: AJ
authors.lastname: Tipping
authors.forename: John
authors.initials: J
authors.lastname: Brown
authors.forename: Shamit
authors.initials: S
authors.lastname: Soneji
authors.forename: Jose
authors.initials: J
authors.lastname: Teles
authors.forename: Carsten
authors.initials: C
authors.lastname: Peterson
authors.forename: Tariq
authors.initials: T
authors.lastname: Enver
mesh_terms: D000818:Animals; D018952:Antigens, CD34 / Q000235:genetics / Q000378:metabolism; D000950:Antigens, Ly / Q000235:genetics / Q000378:metabolism; D001854:Bone Marrow Cells / Q000378:metabolism; D002454:Cell Differentiation / Q000187:drug effects / Q000235:genetics; D002461:Cell Line, Transformed; D019070:Cell Lineage / Q000235:genetics*; D002478:Cells, Cultured; D016000:Cluster Analysis; D016207:Cytokines / Q000494:pharmacology; D041905:Erythroid Cells / Q000378:metabolism; D020869:Gene Expression Profiling / Q000379:methods; D006410:Hematopoiesis / Q000235:genetics*; D006412:Hematopoietic Stem Cells / Q000378:metabolism*; D015151:Immunoblotting; D008565:Membrane Proteins / Q000235:genetics / Q000378:metabolism; D051379:Mice; D008810:Mice, Inbred C57BL; D008856:Microscopy, Fluorescence; D039902:Multipotent Stem Cells / Q000378:metabolism*; D020411:Oligonucleotide Array Sequence Analysis; D020133:Reverse Transcriptase Polymerase Chain Reaction; D013997:Time Factors; D059467:Transcriptome
chemical_list: D018952:Antigens, CD34; D000950:Antigens, Ly; D016207:Cytokines; C074650:Ly6a protein, mouse; D008565:Membrane Proteins