ERC FUNDED PROJECTS

Malaria parasite infection in humans has been called “the strongest known force for evolutionary selection in the recent history of the human genome”, and I hypothesize that a similar statement may apply to the mosquito vector, which is the definitive host of the malaria parasite. We previously discovered efficient malaria-resistance mechanisms in natural populations of the African malaria vector, Anopheles gambiae. Aim 1 of the proposed project will implement a novel genetic mapping design to systematically survey the mosquito population for common and rare genetic variants of strong effect against the human malaria parasite, Plasmodium falciparum. A product of the mapping design will be living mosquito families carrying the resistance loci. Aim 2 will use the segregating families to functionally dissect the underlying molecular mechanisms controlled by the loci, including determination of the pathogen specificity spectra of the host-defense traits. Aim 3 targets arbovirus transmission, where Anopheles mosquitoes transmit human malaria but not arboviruses such as Dengue and Chikungunya, even though the two mosquitoes bite the same people and are exposed to the same pathogens, often in malaria-arbovirus co-infections. We will use deep-sequencing to detect processing of the arbovirus dsRNA intermediates of replication produced by the RNAi pathway of the mosquitoes. The results will reveal important new information about differences in the efficiency and quality of the RNAi response between mosquitoes, which is likely to underlie at least part of the host specificity of arbovirus transmission. The 3 Aims will make significant contributions to understanding malaria and arbovirus transmission, major global public health problems, will aid the development of a next generation of vector surveillance and control tools, and will produce a definitive description of the major genetic factors influencing host-pathogen interactions in mosquito immunity.

2 307 800 €

Start date: 2013-03-01, End date: 2018-02-28

Celiac disease affects at least 1% of the world population. Its onset is triggered by gluten, a common dietary protein, however, its etiology is poorly understood. More than 80% of patients are not properly diagnosed and they therefore do not follow a gluten-free diet, thereby increasing their risk for disease-associated complications and early death. A better understanding of the disease biology would improve the diagnosis, prevention, and treatment of celiac disease. This project investigates the disease mechanisms in celiac disease by using predisposing genes and genetic variants as disease initiating factors. Specifically, it will investigate if long, intergenic non-coding RNAs (lincRNAs) are causally involved in celiac disease pathogenesis by regulating protein-coding genes and pathways associated with the disease. This project is based on two important observations by my group: (1) Our genetic studies, which led to identifying 39 celiac disease risk loci, suggest that the mechanism underlying the disease is largely governed by dysregulation of gene expression. (2) We uncovered a previously unrecognized role for lincRNAs that provides clues as to exactly how genetic variation causes disease, as this class of biologically important RNA molecules regulate gene expression. The research will be performed in CD4+ T cells, a severely affected cell type in disease pathology. I will first use celiac disease-associated protein-coding genes to delineate their regulatory pathways and then study the transcriptional programs of lincRNAs present in celiac disease loci. Next I will combine the information and investigate if the expressed lincRNAs modulate the pathways and affect T cell function, thereby discovering if lincRNAs are a missing link between non-coding genetic variation and protein-coding genes. Our findings may well lead to potential therapeutic targets and provide a solid scientific basis for new diagnostic markers, particularly biomarkers, based on genetics.

2 319 914 €

Start date: 2013-02-01, End date: 2018-11-30

Embryonic development is very robust: In the midst of segregating mutations and fluctuating environments, a fertilized egg has the remarkable capacity to give rise to a precisely patterned embryo. The stereotypic progression of development is driven by tightly regulated programs of gene expression. However, this deterministic view from genetics is at odds with an emerging view of transcription from genomics as a “noisy” process, variable and changing both within and between individuals. How variable transcriptional programs can regulate robust embryonic development remains a long-standing question, which this proposal aims to address. By combining population genetics, genomics, and developmental genetics in Drosophila we will dissect the relationship between DNA sequence variation, transcription factor (TF) occupancy, and the regulatory control of developmental gene expression. The backdrop for this work is extensive information generated by my lab on the location and function of over 12,000 developmental cis-regulatory elements, including accurate, predictive models of their spatio-temporal activity. To understand the impact of variation on transcription and development, we will make use of a powerful experimental resource – 192 sequenced Drosophila strains, collected from a highly genetically diverse wild population. The proposed research has three Specific Aims: 1) Perform the first high-resolution study associating SNPs and structural variants (eQTLs) with gene expression variation during embryonic development, 2) Quantify in vivo the relationship between cis-regulatory variation, TF occupancy, and gene expression, 3) Incorporate these data into an integrated, predictive model of transcription. These Aims, together with our cis-regulatory data, will offer unique, mechanistic insights into how cis-regulatory variation impacts developmental gene regulation, and into the molecular bases of robustness in developmental regulatory networks.

2 260 116 €

Start date: 2013-09-01, End date: 2018-08-31

The adult human organism contains heterogeneous reservoirs of pluripotent stem cells characterized by a diversified differentiation potential. Understanding their biology at a system level would advance our ability to selectively activate and control their differentiation potential. Aside from the basic implications this would represent a substantial progress in regenerative medicine by providing a rational framework for using small molecules to control cell trans-determination and reprogramming. Here we propose a combined experimental and modelling approach to assemble a predictive model of mesoderm stem cell differentiation. Different cell states are identified by a vector in the differentiation hyperspace, the coordinates of the vector being the activation levels of a large number of nodes of a logic model linking the cell signalling network to the transcription regulatory network. The premise of this proposal is that differentiation is equivalent to rewiring the cell regulatory network as a consequence of induced perturbation of the gene expression program. This process can be rationally controlled by perturbing specific nodes of the signalling network that in turn control transcription factor activation. We will develop this novel strategy using the mesoangioblast ex vivo differentiation system. Mesoangioblasts are one of the many different types of mesoderm stem/progenitor cells that exhibit myogenic potential. Ex vivo, they readily differentiate into striated muscle. However, under appropriate conditions they can also differentiate, into smooth muscle and adipocytes, albeit less efficiently. We will start by assembling, training and optimizing different predictive models for the undifferentiated mesoangioblast. Next by a combination of experiments and modelling approaches we will learn how, by perturbing the signalling models with different inhibitors and activators we can rewire the cell networks to induce trans-determination or reprogramming.

2 639 804 €

Start date: 2013-04-01, End date: 2018-09-30