SC-RNA-seq assisted synthesis of a Boolean network to model early haematopoiesis aging
Hematopoietic stem cell (HSC) aging is a multifactorial event that leads to changes in HSC properties and function. These changes are intrinsically coordinated and affect the early hematopoiesis, involving hematopoietic stem and progenitor cells (HSPCs). The objective of this work is to better understand the mechanisms and factors controlling these changes. We have therefore developed an original strategy to construct a Boolean network of genes explaining the priming and homeostasis of HSCs (graphical abstract). Based on our previous scRNA-seq data, we performed an exhaustive analysis of the transcriptional network and identified active transcription modules or regulons along the differentiation trajectory of selected HSPC states. This global view of transcriptional regulation led us to focus on 15 components, 13 selected TFs (Tal1, Fli1, Gata2, Gata1, Zfpm1, Egr1, Junb, Ikzf1, Myc, Cebpa, Bclaf1, Klf1, Spi1) and 2 complexes regulating the ability of HSC to cycle (CDK4/6 - Cyclin D and CIP/KIP). We then defined the connections controlling the differentiation dynamics of HSC states and constructed an influence graph between the TFs involved in the dynamics by mixing observations from our scRNA-seq data and knowledge from the literature. Then, using answer set programming (ASP) and in silico perturbation analysis, we obtained a Boolean model which is the solution of a Boolean satisfiability problem. Finally, perturbation of the model based on age-related changes revealed important regulations, such as the overactivation of Egr1 and Junb or the loss of Cebpa activation by Gata2, which were found to be relevant for the myeloid bias of aged HSC. Our work shows the efficiency of the combination of manual and systematic methods to elaborate a Boolean model. The developed strategy led to the proposal of new regulatory mechanisms underlying the differentiation bias of aged HSCs, explaining the decreased transcriptional priming of HSCs to all mature cell types except megakaryocytes. Graphical abstractFrom single cell RNA-seq (scRNA-seq) data and current knowledge in early hematopoiesis (literature and biological database investigation), 3 inputs were obtained to define the network synthesis as a Boolean Satisfiability Problem depending on observations of states in the differentiation process: O_LIInfluence graph between selected components. C_LIO_LIDiscretized component activity levels in the considered states (blue: 0/inactive, white: */unknown or free, red: 1/active). C_LIO_LIDynamic relations (stable states, (non) reachability) between the considered states. Then, these inputs were encoded as constraints in Answer Set Programing (ASP) thanks to the Bonesis tool. After the solving, a Boolean model of early hematopoiesis is obtained. This model is altered according to the characteristics of aging observed in our scRNA-seq data, in order to identify the main molecular actors and mechanisms of aging. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC="FIGDIR/small/479548v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@fbf1d1org.highwire.dtl.DTLVardef@c0ee97org.highwire.dtl.DTLVardef@70365corg.highwire.dtl.DTLVardef@100ff60_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract:C_FLOATNO Overview of the scRNA-seq assisted gene Boolean network synthesis strategy. C_FIG