78 research outputs found
Reconstructing Gene Regulatory Networks That Control Hematopoietic Commitment.
Hematopoietic stem cells (HSCs) reside at the apex of the hematopoietic hierarchy, possessing the ability to self-renew and differentiate toward all mature blood lineages. Along with more specialized progenitor cells, HSCs have an essential role in maintaining a healthy blood system. Incorrect regulation of cell fate decisions in stem/progenitor cells can lead to an imbalance of mature blood cell populations-a situation seen in diseases such as leukemia. Transcription factors, acting as part of complex regulatory networks, are known to play an important role in regulating hematopoietic cell fate decisions. Yet, discovering the interactions present in these networks remains a big challenge. Here, we discuss a computational method that uses single-cell gene expression data to reconstruct Boolean gene regulatory network models and show how this technique can be applied to enhance our understanding of transcriptional regulation in hematopoiesis.Work in the authorâs laboratory is supported by grants from the Wellcome,
Bloodwise, Cancer Research UK, NIH-NIDDK and core support grants by the Wellcome to the Cambridge Institute for Medical Research and Wellcome & MRC Cambridge Stem Cell Institute. F.K.H. is a recipient of a Medical Research Council PhD Studentship
Synthesising executable gene regulatory networks in haematopoiesis from single-cell gene expression data
A fundamental challenge in biology is to understand the complex gene regulatory networks which control tissue development in the mammalian embryo, and maintain homoeostasis in the adult. The cell fate decisions underlying these processes are ultimately made at the level of individual cells. Recent experimental advances in biology allow researchers to obtain gene expression profiles at single-cell resolution over thousands of cells at once. These single-cell measurements provide snapshots of the states of the cells that make up a tissue, instead of the population-level averages provided by conventional high-throughput experiments. The aim of this PhD was to investigate the possibility of using this new high resolution data to reconstruct mechanistic computational models of gene regulatory networks.
In this thesis I introduce the idea of viewing single-cell gene expression profiles as states of an asynchronous Boolean network, and frame model inference as the problem of reconstructing a Boolean network from its state space. I then give a scalable algorithm to solve this synthesis problem. In order to achieve scalability, this algorithm works in a modular way, treating different aspects of a graph data structure separately before encoding the search for logical rules as Boolean satisfiability problems to be dispatched to a SAT solver.
Together with experimental collaborators, I applied this method to understanding the process of early blood development in the embryo, which is poorly understood due to the small number of cells present at this stage. The emergence of blood from Flk1+ mesoderm was studied by single cell expression analysis of 3934 cells at four sequential developmental time points. A mechanistic model recapitulating blood development was reconstructed from this data set, which was consistent with known biology and the bifurcation of blood and endothelium. Several model predictions were validated experimentally, demonstrating that HoxB4 and Sox17 directly regulate the haematopoietic factor Erg, and that Sox7 blocks primitive erythroid development.
A general-purpose graphical tool was then developed based on this algorithm, which can be used by biological researchers as new single-cell data sets become available. This tool can deploy computations to the cloud in order to scale up larger high-throughput data sets. The results in this thesis demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the gene regulatory networks that underpin organogenesis. Rapid technological advances in our ability to perform single-cell profiling suggest that my tool will be applicable to other organ systems and may inform the development of improved cellular programming strategies.Microsoft Research PhD Scholarshi
Quelles compétences et littératies pour les humanités numériques ?
Un atelier qui concerne également l'identification de compétences. Question qui se pose souvent dans le cadre de projet. L'idée serait d'identifier ces compétences afin de contribuer à la définition de formations pour pouvoir disposer des personnes qui aient cette somme de compétences nécessaire pour monter des projets ambitieux. Sans doute faire un début de cartographie avec du mindmapping pour identifier des compétences clefs à développer dans les formations. L'objectif est de débattre sur les compétences et littératies nécessaires pour s'investir dans les humanités numériques. Quelles sont les compétences numériques, informatiques et intellectuelles pour y parvenir. Faut-il faire évoluer les formations actuelles ? L'objectif est de tenter de dessiner une matrice des compétences minimales et d'envisager celles qui seront nécessaires à l'avenir pour accueillir et former les futurs chercheurs notamment en SHS.
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CHD7 and Runx1 interaction provides a braking mechanism for hematopoietic differentiation.
Hematopoietic stem and progenitor cell (HSPC) formation and lineage differentiation involve gene expression programs orchestrated by transcription factors and epigenetic regulators. Genetic disruption of the chromatin remodeler chromodomain-helicase-DNA-binding protein 7 (CHD7) expanded phenotypic HSPCs, erythroid, and myeloid lineages in zebrafish and mouse embryos. CHD7 acts to suppress hematopoietic differentiation. Binding motifs for RUNX and other hematopoietic transcription factors are enriched at sites occupied by CHD7, and decreased RUNX1 occupancy correlated with loss of CHD7 localization. CHD7 physically interacts with RUNX1 and suppresses RUNX1-induced expansion of HSPCs during development through modulation of RUNX1 activity. Consequently, the RUNX1:CHD7 axis provides proper timing and function of HSPCs as they emerge during hematopoietic development or mature in adults, representing a distinct and evolutionarily conserved control mechanism to ensure accurate hematopoietic lineage differentiation.Bloodwise, CRUK, MRC, Wellcome Trust, NIH, Leukemia and Lymphoma Societ
SCOUP: a probabilistic model based on the OrnsteinâUhlenbeck process to analyze single-cell expression data during differentiation
Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis
Cellular decision-making is mediated by a complex interplay of external stimuli with the intracellular environment, in particular transcription factor regulatory networks. Here we have determined the expression of a network of 18 key haematopoietic transcription factors in 597 single primary blood stem and progenitor cells isolated from mouse bone marrow. We demonstrate that different stem/progenitor populations are characterized by distinctive transcription factor expression states, and through comprehensive bioinformatic analysis reveal positively and negatively correlated transcription factor pairings, including previously unrecognized relationships between Gata2, Gfi1 and Gfi1b. Validation using transcriptional and transgenic assays confirmed direct regulatory interactions consistent with a regulatory triad in immature blood stem cells, where Gata2 may function to modulate cross-inhibition between Gfi1 and Gfi1b. Single-cell expression profiling therefore identifies network states and allows reconstruction of network hierarchies involved in controlling stem cell fate choices, and provides a blueprint for studying both normal development and human disease
Resolving early mesoderm diversification through single-cell expression profiling.
In mammals, specification of the three major germ layers occurs during gastrulation, when cells ingressing through the primitive streak differentiate into the precursor cells of major organ systems. However, the molecular mechanisms underlying this process remain unclear, as numbers of gastrulating cells are very limited. In the mouse embryo at embryonic day 6.5, cells located at the junction between the extra-embryonic region and the epiblast on the posterior side of the embryo undergo an epithelial-to-mesenchymal transition and ingress through the primitive streak. Subsequently, cells migrate, either surrounding the prospective ectoderm contributing to the embryo proper, or into the extra-embryonic region to form the yolk sac, umbilical cord and placenta. Fate mapping has shown that mature tissues such as blood and heart originate from specific regions of the pre-gastrula epiblast, but the plasticity of cells within the embryo and the function of key cell-type-specific transcription factors remain unclear. Here we analyse 1,205 cells from the epiblast and nascent Flk1(+) mesoderm of gastrulating mouse embryos using single-cell RNA sequencing, representing the first transcriptome-wide in vivo view of early mesoderm formation during mammalian gastrulation. Additionally, using knockout mice, we study the function of Tal1, a key haematopoietic transcription factor, and demonstrate, contrary to previous studies performed using retrospective assays, that Tal1 knockout does not immediately bias precursor cells towards a cardiac fate.We thank M. de Bruijn, A. Martinez-Arias, J. Nichols and C. Mulas for discussion, the Cambridge Institute for Medical Research Flow Cytometry facility for their expertise in single-cell index sorting, and S. Lorenz from the Sanger Single Cell Genomics Core for supervising purification of Tal1â/â sequencing libraries. ChIP-seq reads were processed by R. Hannah. Research in the authorsâ laboratories is supported by the Medical Research Council, Cancer Research UK, the Biotechnology and Biological Sciences Research Council, Bloodwise, the Leukemia and Lymphoma Society, and the Sanger-EBI Single Cell Centre, and by core support grants from the Wellcome Trust to the Cambridge Institute for Medical Research and Wellcome Trust - MRC Cambridge Stem Cell Institute and by core funding from Cancer Research UK and the European Molecular Biology Laboratory. Y.T. was supported by a fellowship from the Japan Society for the Promotion of Science. W.J. is a Wellcome Trust Clinical Research Fellow. A.S. is supported by the Sanger-EBI Single Cell Centre. This work was funded as part of Wellcome Trust Strategic Award 105031/D/14/Z âTracing early mammalian lineage decisions by single-cell genomicsâ awarded to W. Reik, S. Teichmann, J. Nichols, B. Simons, T. Voet, S. Srinivas, L. Vallier, B. Göttgens and J. Marioni.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nature1863
Single-cell RNA-seq reveals novel regulators of human embryonic stem cell differentiation to definitive endoderm
Serial entrepreneurs and focused human intentionality in the development of the Cambridge technopole
It has been argued by some researchers that intention is a defining trait in the character of serial entrepreneurs. Recently, Zohar and Marshall (2004) have highlighted the contrast between business practice based on a narrow linear assumption of human nature and motivation for short-term gain, and 'a culture driven by fundamental values and a deep sense of purpose' focused on wealth creation and the common good. This is referred to as spiritual capital. This paper evaluates the relationships between intuition, focused human intentionality, and spiritual intelligence of 12 hi-tech serial entrepreneurs, the performance of the Cambridge technopole, and experimental measures of non-local intention. Such understanding of the intellectual, emotional and spiritual intelligence components of decision making and the reality of intention to serial entrepreneurs will improve entrepreneurship teaching pedagogy and development of serial entrepreneurs
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