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Background Over the past decade, experimental procedures such as metabolic labeling for determining RNA turnover rates at the transcriptome-wide scale have been widely adopted and are now turning to single cell measurements. Several computational methods to estimate RNA synthesis, processing and degradation rates from such experiments have been suggested, but they all require several RNA sequencing samples. Here we present a method that can estimate those three rates from a single sample. Methods Our method relies on the analytical solution to the Zeisel model of RNA dynamics. It was validated on metabolic labeling experiments performed on mouse embryonic stem cells. Resulting degradation rates were compared both to previously published rates on the same system and to a state-of-the-art method applied to the same data. Results Our method is computationally efficient and outputs rates that correlate well with previously published data sets. Using it on a single sample, we were able to reproduce the observation that dynamic biological processes tend to involve genes with higher metabolic rates, while stable processes involve genes with lower rates. This supports the hypothesis that cells control not only the mRNA steady-state abundance, but also its responsiveness, i.e., how fast steady state is reached. Moreover, degradation rates obtained with our method compare favourably with the other tested method. Conclusions In addition to saving experimental work and computational time, estimating rates for a single sample has several advantages. It does not require an error-prone normalization across samples and enables the use of replicates to estimate uncertainty and assess sample quality. Finally the method and theoretical results described here are general enough to be useful in other contexts such as nucleotide conversion methods and single cell metabolic labeling experiments.

Periodic organization of cells is required for the function of many organs and tissues. The development of such periodic patterns is typically associated with mechanisms based on intercellular signaling such as lateral inhibition and Turing patterning. Here we show that the transition from disordered to ordered checkerboard-like pattern of hair cells and supporting cells in the mammalian hearing organ, the organ of Corti, is likely based on mechanical forces rather than signaling events. Using time-lapse imaging of mouse cochlear explants, we show that hair cells rearrange gradually into a checkerboard-like pattern through a tissue-wide shear motion that coordinates intercalation and delamination events. Using mechanical models of the tissue, we show that global shear and local repulsion forces on hair cells are sufficient to drive the transition from disordered to ordered cellular pattern. Our findings suggest that mechanical forces drive ordered hair cell patterning in a process strikingly analogous to the process of shear-induced crystallization in polymer and granular physics., The periodic organization of cells is typically associated with mechanisms based on intercellular signaling such as lateral inhibition and Turing patterning. Here the authors show that hair cells in the inner ear rearrange gradually into a checkerboard-like pattern through a tissue-wide shear motion that coordinates intercalation and delamination events.

G protein-coupled receptors (GPCRs) constitute a large family of receptors that activate intracellular signaling pathways upon detecting specific extracellular ligands. While many aspects of GPCR signaling have been uncovered through decades of studies, some fundamental properties, like its channel capacity—a measure of how much information a given transmission system can reliably transduce—are still debated. Previous studies concluded that GPCRs in individual cells could transmit around one bit of information about the concentration of the ligands, allowing only for a reliable on or off response. Using muscarinic receptor-induced calcium response measured in individual cells upon repeated stimulation, we show that GPCR signaling systems possess a significantly higher capacity. We estimate the channel capacity of this system to be above two, implying that at least four concentration levels of the agonist can be distinguished reliably. These findings shed light on the basic principles of GPCR signaling., G protein-coupled receptors (GPCRs) activate intracellular signalling pathways upon extracellular stimulation. Here authors record single cell responses of GPCR signalling which allows the direct estimation of its channel capacity for each cell along with the reproducibility of its response.

Precise cellular organizations are required for the function of many organs and tissues. It is often unclear, however, how such precise patterns emerge during development. The mammalian hearing organ, the organ of Corti, consists of a remarkably organized pattern of four rows of hair cells (HCs) interspersed by non-sensory supporting cells (SCs). This checkerboard-like pattern of HCs and SCs emerges from a disordered epithelium over several days, yet the transition to an ordered cellular pattern is not well understood. Using a combination of quantitative morphological analysis and time-lapse imaging of mouse cochlear explants, we show here that patterning of the organ of Corti involves dynamic reorganizations that include lateral shear motion, cell intercalations, and delaminations. A mathematical model, where tissue morphology is described in terms of the mechanical forces that act on cells and cellular junctions, suggests that global shear on HCs and local repulsion between HCs are sufficient to drive the tissue into the final checkerboard-like pattern. Our findings suggest that precise patterns can emerge during development from reorganization processes, driven by a combination of global and local forces in a process analogous to shear-induced crystallization.

In shade-intolerant plants, the perception of proximate neighbors rapidly induces architectural changes resulting in elongated stems and reduced leaf size. Sensing and signaling steps triggering this modified growth program have been identified. However, the underlying changes in resource allocation that fuel stem growth remain poorly understood. Through 14CO2 pulse labeling of Brassica rapa seedlings, we show that perception of the neighbor detection signal, low ratio of red to far-red light (R:FR), leads to increased carbon allocation from the major site of photosynthesis (cotyledons) to the elongating hypocotyl. While carbon fixation and metabolite levels remain similar in low R:FR, partitioning to all downstream carbon pools within the hypocotyl is increased. Genetic analyses using Arabidopsis thaliana mutants indicate that low-R:FR–induced hypocotyl elongation requires sucrose transport from the cotyledons and is regulated by a PIF7-dependent metabolic response. Moreover, our data suggest that starch metabolism in the hypocotyl has a growth-regulatory function. The results reveal a key mechanism by which metabolic adjustments can support rapid growth adaptation to a changing environment., Proceedings of the National Academy of Sciences of the United States of America, 115 (42), ISSN:0027-8424, ISSN:1091-6490

Significance In dense communities, plants compete for light and sense potentially threatening neighbors prior to actual shading. In response to neighbor proximity cues, shade-intolerant plants selectively elongate stem-like structures, thereby enhancing access to unfiltered sunlight. Although key steps in plant proximity sensing and signaling have been identified, we know little about the metabolic adaptations underlying enhanced stem growth. Here, we show that, following the detection of neighbor proximity cues, seedlings allocate more carbon fixed in the cotyledons to the faster elongating hypocotyl. Moreover, we show that sucrose transport and a transcription factor responding to light and metabolic cues control hypocotyl elongation. Collectively, our work provides important insights into the metabolic changes underlying organ-specific growth adaptations to an environmental stress signal., In shade-intolerant plants, the perception of proximate neighbors rapidly induces architectural changes resulting in elongated stems and reduced leaf size. Sensing and signaling steps triggering this modified growth program have been identified. However, the underlying changes in resource allocation that fuel stem growth remain poorly understood. Through 14CO2 pulse labeling of Brassica rapa seedlings, we show that perception of the neighbor detection signal, low ratio of red to far-red light (R:FR), leads to increased carbon allocation from the major site of photosynthesis (cotyledons) to the elongating hypocotyl. While carbon fixation and metabolite levels remain similar in low R:FR, partitioning to all downstream carbon pools within the hypocotyl is increased. Genetic analyses using Arabidopsis thaliana mutants indicate that low-R:FR–induced hypocotyl elongation requires sucrose transport from the cotyledons and is regulated by a PIF7-dependent metabolic response. Moreover, our data suggest that starch metabolism in the hypocotyl has a growth-regulatory function. The results reveal a key mechanism by which metabolic adjustments can support rapid growth adaptation to a changing environment.

Closed-form solutions are traditionally used in computer vision for estimating rigid body transformations. Here we suggest an iterative solution for estimating rigid body transformations and prove its global convergence. We show that for a number of applications involving repeated estimations of rigid body transformations, an iterative scheme is preferable to a closed-form solution. We illustrate this experimentally on two applications, 3D object tracking and image registration with Iterative Closest Point. Our results show that for those problems using an iterative and continuous estimation process is more robust than using many independent closed-form estimations.

We study a reaching movement controller for a redundant serial arm manipulator, based on two principles believed to be central to biological motion control: multi-referential control and dynamical system control. The resulting controller is based on two concurrent dynamical systems acting on different, yet redundant variables. The first dynamical system acts on the end-effector location variables and the second one acts on the joint angle variables. Coherence constraints are enforced between those two redundant representations of the movement and can be used to modulate the relative influence of each dynamical system. We illustrate the advantages of such a redundant representation of the movement regarding singularities and joint angle avoidance.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access. Nearly three-quarters of the 143 genetic signals associated with platelet and erythrocyte phenotypes identified by meta-analyses of genome-wide association (GWA) studies are located at non-protein-coding regions. Here, we assessed the role of candidate regulatory variants associated with cell type-restricted, closely related hematological quantitative traits in biologically relevant hematopoietic cell types. We used formaldehyde-assisted isolation of regulatory elements followed by next-generation sequencing (FAIRE-seq) to map regions of open chromatin in three primary human blood cells of the myeloid lineage. In the precursors of platelets and erythrocytes, as well as in monocytes, we found that open chromatin signatures reflect the corresponding hematopoietic lineages of the studied cell types and associate with the cell type-specific gene expression patterns. Dependent on their signal strength, open chromatin regions showed correlation with promoter and enhancer histone marks, distance to the transcription start site, and ontology classes of nearby genes. Cell type-restricted regions of open chromatin were enriched in sequence variants associated with hematological indices. The majority (63.6%) of such candidate functional variants at platelet quantitative trait loci (QTLs) coincided with binding sites of five transcription factors key in regulating megakaryopoiesis. We experimentally tested 13 candidate regulatory variants at 10 platelet QTLs and found that 10 (76.9%) affected protein binding, suggesting that this is a frequent mechanism by which regulatory variants influence quantitative trait levels. Our findings demonstrate that combining large-scale GWA data with open chromatin profiles of relevant cell types can be a powerful means of dissecting the genetic architecture of closely related quantitative traits. Marie-Curie Initial Training Network NETSIM British Heart Foundation RG/09/12/28096 National Institutes for Health RP-PG-0310-1002 Wellcome Trust 098051 info:eu-repo/grantAgreement/EC/FP7/282510

During development, cells undergo dramatic changes in their morphology. By affecting contact geometry, these morphological changes could influence cellular communication. However, it has remained unclear whether and how signaling depends on contact geometry. This question is particularly relevant for Notch signaling, which coordinates neighboring cell fates through direct cell-cell signaling. Using micropatterning with a receptor trans-endocytosis assay, we show that signaling between pairs of cells correlates with their contact area. This relationship extends across contact diameters ranging from micrometers to tens of micrometers. Mathematical modeling predicts that dependence of signaling on contact area can bias cellular differentiation in Notch-mediated lateral inhibition processes, such that smaller cells are more likely to differentiate into signal-producing cells. Consistent with this prediction, analysis of developing chick inner ear revealed that ligand-producing hair cell precursors have smaller apical footprints than non-hair cells. Together, these results highlight the influence of cell morphology on fate determination processes.

Increased male prevalence has been repeatedly reported in several neurodevelopmental disorders (NDs), leading to the concept of a "female protective model." We investigated the molecular basis of this sex-based difference in liability and demonstrated an excess of deleterious autosomal copy-number variants (CNVs) in females compared to males (odds ratio [OR] = 1.46, p = 8 × 10(-10)) in a cohort of 15,585 probands ascertained for NDs. In an independent autism spectrum disorder (ASD) cohort of 762 families, we found a 3-fold increase in deleterious autosomal CNVs (p = 7 × 10(-4)) and an excess of private deleterious single-nucleotide variants (SNVs) in female compared to male probands (OR = 1.34, p = 0.03). We also showed that the deleteriousness of autosomal SNVs was significantly higher in female probands (p = 0.0006). A similar bias was observed in parents of probands ascertained for NDs. Deleterious CNVs (400 kb) were maternally inherited more often (up to 64%, p = 10(-15)) than small CNVs400 kb (OR = 1.45, p = 0.0003). In the ASD cohort, increased maternal transmission was also observed for deleterious CNVs and SNVs. Although ASD females showed higher mutational burden and lower cognition, the excess mutational burden remained, even after adjustment for those cognitive differences. These results strongly suggest that females have an increased etiological burden unlinked to rare deleterious variants on the X chromosome. Carefully phenotyped and genotyped cohorts will be required for identifying the symptoms, which show gender-specific liability to mutational burden.

Red blood cell (RBC) traits are routinely measured in clinical practice as important markers of health. Deviations from the physiological ranges are usually a sign of disease, although variation between healthy individuals also occurs, at least partly due to genetic factors. Recent large scale genetic studies identified loci associated with one or more of these traits; further characterization of known loci and identification of new loci is necessary to better understand their role in health and disease and to identify potential molecular mechanisms. We performed meta-analysis of Metabochip association results for six RBC traits-hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV) and red blood cell count (RCC)-in 11 093 Europeans from seven studies of the UCL-LSHTM-Edinburgh-Bristol (UCLEB) Consortium. We identified 394 non-overlapping SNPs in five loci at genome-wide significance: 6p22.1-6p21.33 (with HFE among others), 6q23.2 (with HBS1L among others), 6q23.3 (contains no genes), 9q34.3 (only ABO gene) and 22q13.1 (with TMPRSS6 among others), replicating previous findings of association with RBC traits at these loci and extending them by imputation to 1000 Genomes. We further characterized associations between ABO SNPs and three traits: hemoglobin, hematocrit and red blood cell count, replicating them in an independent cohort. Conditional analyses indicated the independent association of each of these traits with ABO SNPs and a role for blood group O in mediating the association. The 15 most significant RBC-associated ABO SNPs were also associated with five cardiometabolic traits, with discordance in the direction of effect between groups of traits, suggesting that ABO may act through more than one mechanism to influence cardiometabolic risk.

Phototropism allows plants to redirect their growth towards the light to optimize photosynthesis under reduced light conditions. Phototropin 1 (phot1) is the primary low blue light-sensing receptor triggering phototropism in Arabidopsis. Light-induced autophosphorylation of phot1, an AGC-class protein kinase, constitutes an essential step for phototropism. However, apart from the receptor itself, substrates of phot1 kinase activity are less clearly established. Phototropism is also influenced by the cryptochromes and phytochromes photoreceptors that do not provide directional information but influence the process through incompletely characterized mechanisms. Here, we show that Phytochrome Kinase Substrate 4 (PKS4), a known element of phot1 signalling, is a substrate of phot1 kinase activity in vitro that is phosphorylated in a phot1-dependent manner in vivo. PKS4 phosphorylation is transient and regulated by a type 2-protein phosphatase. Moreover, phytochromes repress the accumulation of the light-induced phosphorylated form of PKS4 showing a convergence of photoreceptor activity on this signalling element. Our physiological analyses suggest that PKS4 phosphorylation is not essential for phototropism but is part of a negative feedback mechanism.

Phototropin photoreceptors (phot1 and phot2 in Arabidopsis thaliana) enable responses to directional light cues (e.g., positive phototropism in the hypocotyl). In Arabidopsis, phot1 is essential for phototropism in response to low light, a response that is also modulated by phytochrome A (phyA), representing a classical example of photoreceptor coaction. The molecular mechanisms underlying promotion of phototropism by phyA remain unclear. Most phyA responses require nuclear accumulation of the photoreceptor, but interestingly, it has been proposed that cytosolic phyA promotes phototropism. By comparing the kinetics of phototropism in seedlings with different subcellular localizations of phyA, we show that nuclear phyA accelerates the phototropic response, whereas in the fhy1 fhl mutant, in which phyA remains in the cytosol, phototropic bending is slower than in the wild type. Consistent with this data, we find that transcription factors needed for full phyA responses are needed for normal phototropism. Moreover, we show that phyA is the primary photoreceptor promoting the expression of phototropism regulators in low light (e.g., PHYTOCHROME KINASE SUBSTRATE1 [PKS1] and ROOT PHOTO TROPISM2 [RPT2]). Although phyA remains cytosolic in fhy1 fhl, induction of PKS1 and RPT2 expression still occurs in fhy1 fhl, indicating that a low level of nuclear phyA signaling is still present in fhy1 fhl.

We present an algorithm enabling a humanoid robot to visually learn its body schema, knowing only the number of degrees of freedom in each limb. By "body schema" we mean the joint positions and orientations and thus the kinematic function. The learning is performed by visually observing its end-effectors when moving them. With simulations involving a body schema of more than 20 degrees of freedom, results show that the system is scalable to a high number of degrees of freedom. Real robot experiments confirm the practicality of our approach. Our results illustrate how subjective space representation can develop as a result of sensorimotor contingencies.

Concentration gradients provide spatial information for tissue patterning and cell organization, and their robustness under natural fluctuations is an evolutionary advantage. In rod-shaped Schizosaccharomyces pombe cells, the DYRK-family kinase Pom1 gradients control cell division timing and placement. Upon dephosphorylation by a Tea4-phosphatase complex, Pom1 associates with the plasma membrane at cell poles, where it diffuses and detaches upon auto-phosphorylation. Here, we demonstrate that Pom1 auto-phosphorylates intermolecularly, both in vitro and in vivo, which confers robustness to the gradient. Quantitative imaging reveals this robustness through two system's properties: The Pom1 gradient amplitude is inversely correlated with its decay length and is buffered against fluctuations in Tea4 levels. A theoretical model of Pom1 gradient formation through intermolecular auto-phosphorylation predicts both properties qualitatively and quantitatively. This provides a telling example where gradient robustness through super-linear decay, a principle hypothesized a decade ago, is achieved through autocatalysis. Concentration-dependent autocatalysis may be a widely used simple feedback to buffer biological activities.

Plants such as Arabidopsis thaliana respond to foliar shade and neighbors who may become competitors for light resources by elongation growth to secure access to unfiltered sunlight. Challenges faced during this shade avoidance response (SAR) are different under a light-absorbing canopy and during neighbor detection where light remains abundant. In both situations, elongation growth depends on auxin and transcription factors of the phytochrome interacting factor (PIF) class. Using a computational modeling approach to study the SAR regulatory network, we identify and experimentally validate a previously unidentified role for long hypocotyl in far red 1, a negative regulator of the PIFs. Moreover, we find that during neighbor detection, growth is promoted primarily by the production of auxin. In contrast, in true shade, the system operates with less auxin but with an increased sensitivity to the hormonal signal. Our data suggest that this latter signal is less robust, which may reflect a cost-to-robustness tradeoff, a system trait long recognized by engineers and forming the basis of information theory.

There is an error in the key for Figure 2. The correct key for Figure 2 is: black dots: iso1 green dots: iso10 blue dots: ctr red dots: ate

From its onset, the discipline of Artificial Intelligence aimed at understanding intelligence through a synthetic approach. Over time, progress has been made by considering lower and lower levels of intelligence. I argue that this trend should be completed by its next step by considering pre-neural forms of intelligence as models for AI. To justify the relevance of such primitive cognition to intelligence, I recall the works of Piaget, Jonas and Maturana and Varela. By considering how these authors relate to the question of teleology, I illustrate the kind of insights a pre-neural AI could provide,which pertain to fundamental aspects of natural cognition.

Item does not contain fulltext Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

Because of their unique capacity to cross-present Ags to CD8+ T cells, mouse lymphoid tissue–resident CD8+ dendritic cells (DCs) and their migratory counterparts are critical for priming antiviral T cell responses. High expression of the dsRNA sensor TLR3 is a distinctive feature of these cross-presenting DC subsets. TLR3 engagement in CD8+ DCs promotes cross-presentation and the acquisition of effector functions required for driving antiviral T cell responses. In this study, we performed a comprehensive analysis of the TLR3-induced antiviral program and cell-autonomous immunity in CD8+ DC lines and primary CD8+ DCs. We found that TLR3-ligand polyinosinic-polycytidylic acid and human rhinovirus infection induced a potent antiviral protection against Sendai and vesicular stomatitis virus in a TLR3 and type I IFN receptor–dependent manner. Polyinosinic-polycytidylic acid–induced antiviral genes were identified by mass spectrometry–based proteomics and transcriptomics in the CD8+ DC line. Nanostring nCounter experiments confirmed that these antiviral genes were induced by TLR3 engagement in primary CD8+ DCs, and indicated that many are secondary TLR3-response genes requiring autocrine IFN-β stimulation. TLR3-activation thus establishes a type I IFN–dependent antiviral program in a DC subtype playing crucial roles in priming adaptive antiviral immune responses. This mechanism is likely to shield the priming of antiviral responses against inhibition or abrogation by the viral infection. It could be particularly relevant for viruses detected mainly by TLR3, which may not trigger type I IFN production by DCs that lack TLR3, such as plasmacytoid DCs or CD8− DCs.

In this paper we combine kinesthetic demonstrations and dynamical systems to enable a humanoid robot to imitate constrained reaching gestures directed toward a target. Using a learning algorithm based on Gaussian Mixture Regression, the task constraints are extracted from several demonstrations. Those constraints take the form of desired velocity profiles for the end-effector and joint angle variables, with associated covariance matrices describing the variations allowed around the desired profiles. Those constraints are then used to modulate a dynamical system which has the reaching target as attractor. This way, the reaching trajectory can be reshaped in order to satisfy the constraints of the task, while preserving the adaptability and robustness provided by the dynamical system. In particular, the system can adapt to changes in the initial conditions and to target displacements occurring during the movement execution. We first evaluate the potential of this method on experiments involving the Hoap3 humanoid robot putting an object into a box. We then show how a manipulation tasks can be executed as sequences of such constrained reaching movement. This is illustrated on a packaging task performed by the robot.

This paper presents a robotic arm controller for reaching motions. This controller applies two principles inspired by current theories of human reaching motions, namely the multi-referential control of movements and the dynamical system approach to biological control. The controller consists of a stable dynamical system active in a hybrid cartesian-joint angle frame of reference. Our results show that this controller has interesting properties in terms of stability and robustness to perturbations, and that its redundancy can be exploited for a simple solution to the joint limit avoidance problem

In this paper, we extend the Hopfield Associative Memory for storing multiple sequences of varying duration. We apply the model for learning, recognizing and encoding a set of human gestures. We measure systematically the performance of the model against noise.

β-blockers and β-agonists are primarily used to treat cardiovascular diseases. Inter-individual variability in response to both drug classes is well recognized, yet the identity and relative contribution of the genetic players involved are poorly understood. This work is the first genome-wide association study (GWAS) addressing the values and susceptibility of cardiovascular-related traits to a selective β(1)-blocker, Atenolol (ate), and a β-agonist, Isoproterenol (iso). The phenotypic dataset consisted of 27 highly heritable traits, each measured across 22 inbred mouse strains and four pharmacological conditions. The genotypic panel comprised 79922 informative SNPs of the mouse HapMap resource. Associations were mapped by Efficient Mixed Model Association (EMMA), a method that corrects for the population structure and genetic relatedness of the various strains. A total of 205 separate genome-wide scans were analyzed. The most significant hits include three candidate loci related to cardiac and body weight, three loci for electrocardiographic (ECG) values, two loci for the susceptibility of atrial weight index to iso, four loci for the susceptibility of systolic blood pressure (SBP) to perturbations of the β-adrenergic system, and one locus for the responsiveness of QTc (p

We present a system for robust robot skill acquisition from kinesthetic demonstrations. This system allows a robot to learn a simple goal-directed gesture, and correctly reproduce it despite changes in the initial conditions, and perturbations in the environment. It combines a dynamical system control approach with tools of statistical learning theory and provides a solution to the inverse kinematics problem, when dealing with a redundant manipulator. The system is validated on two experiments involving a humanoid robot: putting an object into a box, and reaching for and grasping an object.

Platelets are the second most abundant cell type in blood and are essential for maintaining haemostasis. Their count and volume are tightly controlled within narrow physiological ranges, but there is only limited understanding of the molecular processes controlling both traits. Here we carried out a high-powered meta-analysis of genome-wide association studies (GWAS) in up to 66,867 individuals of European ancestry, followed by extensive biological and functional assessment. We identified 68 genomic loci reliably associated with platelet count and volume mapping to established and putative novel regulators of megakaryopoiesis and platelet formation. These genes show megakaryocyte-specific gene expression patterns and extensive network connectivity. Using gene silencing in Danio rerio and Drosophila melanogaster, we identified 11 of the genes as novel regulators of blood cell formation. Taken together, our findings advance understanding of novel gene functions controlling fate-determining events during megakaryopoiesis and platelet formation, providing a new example of successful translation of GWAS to function. © 2011 Macmillan Publishers Limited. All rights reserved.