Motivation: Cell populations are never truly homoge-neous; individual cells exist in biochemical states that define functional differences between them. New technology based on microfluidic arrays combined with multiplexed quantita-tive polymerase chain reactions (qPCR) now enables high-throughput single-cell gene expression measurement, allow-ing assessment of cellular heterogeneity. However very little analytic tools have been developed specifically for the sta-tistical and analytical challenges of single-cell qPCR data. Results: We present a statistical framework for the ex-ploration, quality control, and analysis of single-cell gene expression data from microfluidic arrays. We assess accu-racy and within-sample heterogeneity of single-cell expres-sion and develop quality control criteria to filter unreliable

Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis Citation for published version:

All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.

Haematopoietic stem cells (HSCs) are characterised by their ability to execute a wide range of cell fate choices, including self-renewal, quiescence and differentiation into the many different mature blood lineages. Cell fate decision making in HSCs, as indeed in other cell types, is driven by the interplay of external stimuli and intracellular regulatory programs. Given the pivotal nature of HSC decision making for both normal and aberrant haematopoiesis, substantial research efforts have been invested over the past few decades into deciphering some of the underlying mechanisms. Central to the intracellular decision making processes are transcription factor proteins and their interactions within gene regulatory networks. Over 50 transcription factors have been shown to affect the functionality of HSCs. However, much remains to be learned about the way in which individual factors are connected within wider regulatory networks, and how the topology of HSC regulatory networks might affect HSC function. Nevertheless, important progress has been made in recent years, and new emerging technologies suggest that the pace of progress is likely to accelerate. This review will introduce key concepts, provide an integrated view of selected recent studies, and conclude with an outlook on possible future directions for this field.

Diabetic vascular pathology is largely attributable to impairments in tissue recovery from hypoxia. Circulating progenitor cells have been postulated to play a role in ischemic recovery, and deficiencies in these cells have been well described in diabetic patients. Here, we examine bone marrow–derived mesenchymal progeni-tor cells (BM-MPCs) that have previously been shown to be important for new blood vessel formation and demonstrate significant deficits in the context of diabe-tes. Further, we determine that this dysfunction is attrib-utable to intrinsic defects in diabetic BM-MPCs that are not correctable by restoring glucose homeostasis. We identify two transcriptionally distinct subpopulations that are selectively depleted by both type 1 and type 2 diabetes, and these subpopulations have provasculo-

Characterisation of transcriptional networks in blood stem and progenitor cells using high-throughput single cell gene

Transcriptional mechanisms of cell fate decisions revealed by single cell expression profiling Victoria Moignard1)2)3) and Berthold G€ottgens1)2)3) Transcriptional networks regulate cell fate decisions, which occur at the level of individual cells. However, much of what we know about their structure and function comes from studies averaging measurements over large pop-ulations of cells, many of which are functionally hetero-geneous. Such studies conceal the variability between cells and so prevent us from determining the nature of heterogeneity at the molecular level. In recent years, many protocols and platforms have been developed that allow the high throughput analysis of gene expression in single cells, opening the door to a new era of biology. Here, we discuss the need for single cell gene expression analysis to gain deeper insights into the transcriptional control of cell fate decisions, and consider the insights it has provided so far into transcriptional regulatory networks in development. Keywords:.cell fate control; single cell analysis; transcriptional networks

Full list of author information is available at the end of the article[1]. Although the exact mechanism underlying this path-ology remains unknown, there is evidence for diabetes-associated dysfunction at both the cellular and molecular level. Specifically, diabetes has been linked to impairments in the functionality of diabetic endothelial progenitor cells (EPCs) and resident tissue fibroblast in vitro [2,3]. Additionally, reduced local expression of the vasculo-genic and regenerative cytokines vascular endothelial A variety of treatment approaches that seek to address the specific deficiencies present in diabetic wounds have been developed. Cell-based therapies, in particular, repre-sent an appealing treatment paradigm, as they potentially contribute both cytokines and a cellular framework to the tissue regeneration process. In support of this ap-proach, multiple cell-based products delivering fibro-blasts or fibroblast-keratinocyte mixtures have a proven clinical efficacy for the treatment of diabetic wounds [6]. Moreover, advanced biomaterials are being devel-oped to optimize cell survival and functionality within the harsh wound environment [7-9].

Data exploration, quality control and testing in single-cell