ERC FUNDED PROJECTS

Faithful repair of double stranded DNA breaks (DSBs) is essential, as they are at the origin of genome instability, chromosomal translocations and cancer. Cells repair DSBs through different pathways, which can be faithful or mutagenic, and the balance between them at a given locus must be tightly regulated to preserve genome integrity. Although, much is known about DSB repair factors, how the choice between pathways is controlled within the nuclear environment is not understood. We have shown that nuclear architecture and non-random genome organization determine the frequency of chromosomal translocations and that pathway choice is dictated by the spatial organization of DNA in the nucleus. Nevertheless, what determines which pathway is activated in response to DSBs at specific genomic locations is not understood. Furthermore, the impact of 3D-genome folding on the kinetics and efficiency of DSB repair is completely unknown. Here we aim to understand how nuclear compartmentalization, chromatin structure and genome organization impact on the efficiency of detection, signaling and repair of DSBs. We will unravel what determines the DNA repair specificity within distinct nuclear compartments using protein tethering, promiscuous biotinylation and quantitative proteomics. We will determine how DNA repair is orchestrated at different heterochromatin structures using a CRISPR/Cas9-based system that allows, for the first time robust induction of DSBs at specific heterochromatin compartments. Finally, we will investigate the role of 3D-genome folding in the kinetics of DNA repair and pathway choice using single nucleotide resolution DSB-mapping coupled to 3D-topological maps. This proposal has significant implications for understanding the mechanisms controlling DNA repair within the nuclear environment and will reveal the regions of the genome that are susceptible to genomic instability and help us understand why certain mutations and translocations are recurrent in cancer

1 999 750 €

Start date: 2017-03-01, End date: 2022-02-28

Advanced capitalist economies experience large and persistent movements in asset prices that are difficult to justify with economic fundamentals. The internet bubble of the 1990s and the real state market bubble of the 2000s are two recent examples. The predominant view is that these bubbles are a market failure, and are caused by some form of individual irrationality on the part of market participants. This project is based instead on the view that market participants are individually rational, although this does not preclude sometimes collectively sub-optimal outcomes. Bubbles are thus not a source of market failure by themselves but instead arise as a result of a pre-existing market failure, namely, the existence of pockets of dynamically inefficient investments. Under some conditions, bubbles partly solve this problem, increasing market efficiency and welfare. It is also possible however that bubbles do not solve the underlying problem and, in addition, create negative side-effects. The main objective of this project is to develop this view of asset bubbles, and produce an empirically-relevant macroeconomic framework that allows us to address the following questions: (i) What is the relationship between bubbles and financial market frictions? Special emphasis is given to how the globalization of financial markets and the development of new financial products affect the size and effects of bubbles. (ii) What is the relationship between bubbles, economic growth and unemployment? The theory suggests the presence of virtuous and vicious cycles, as economic growth creates the conditions for bubbles to pop up, while bubbles create incentives for economic growth to happen. (iii) What is the optimal policy to manage bubbles? We need to develop the tools that allow policy makers to sustain those bubbles that have positive effects and burst those that have negative effects.

1 000 000 €

Start date: 2010-04-01, End date: 2015-03-31

The main objective of this research project is to contribute at bridging the gap between the two main branches of financial theory, namely corporate finance and asset pricing. It is motivated by the conviction that these two aspects of financial activity should and can be analyzed within a unified framework. This research will borrow from these two approaches in order to construct theoretical models that allow one to analyze the design and issuance of financial securities, as well as the dynamics of their valuations. Unlike asset pricing, which takes as given the price of the fundamentals, the goal is to derive security price processes from a precise description of firm’s operations and internal frictions. Regarding the latter, and in line with traditional corporate finance theory, the analysis will emphasize the role of agency costs within the firm for the design of its securities. But the analysis will be pushed one step further by studying the impact of these agency costs on key financial variables such as stock and bond prices, leverage, book-to-market ratios, default risk, or the holding of liquidities by firms. One of the contributions of this research project is to show how these variables are interrelated when firms and investors agree upon optimal financial arrangements. The final objective is to derive a rich set of testable asset pricing implications that would eventually be brought to the data.

1 000 000 €

Start date: 2008-11-01, End date: 2014-10-31

In mammals, gene dosage of X-chromosomal genes is equalized between sexes by random inactivation of either one of the two X chromosomes in female cells. In the initial phase of X chromosome inactivation (XCI), a counting and initiation process determines the number of X chromosomes per nucleus, and elects the future inactive X chromosome (Xi). Xist is an X-encoded gene that plays a crucial role in the XCI process. At the start of XCI Xist expression is up-regulated and Xist RNA accumulates on the future Xi thereby initiating silencing in cis. Recent work performed in my laboratory indicates that the counting and initiation process is directed by a stochastic mechanism, in which each X chromosome has an independent probability to be inactivated. We also found that this probability is determined by the X:ploïdy ratio. These results indicated the presence of at least one X-linked activator of XCI. With a BAC screen we recently identified X-encoded RNF12 to be a dose-dependent activator of XCI. Expression of RNF12 correlates with Xist expression, and a heterozygous deletion of Rnf12 results in a marked loss of XCI in female cells. The presence of a small proportion of cells that still initiate XCI, in Rnf12+/- cells, also indicated that more XCI-activators are involved in XCI. Here, we propose to investigate the molecular mechanism by which RNF12 activates XCI in mouse and human, and to search for additional XCI-activators. We will also attempt to establish the role of different inhibitors of XCI, including CTCF and the pluripotency factors OCT4, SOX2 and NANOG. We anticipate that these studies will significantly advance our understanding of XCI mechanisms, which is highly relevant for a better insight in the manifestation of X-linked diseases that are affected by XCI.

1 500 000 €

Start date: 2011-04-01, End date: 2016-03-31

Understanding how proteins respond to mutations is of paramount importance to biology and disease. While protein stability and misfolding have been instrumental in rationalizing the impact of mutations, we recently discovered that an alternative route is also frequent, where mutations at the surface of symmetric proteins trigger novel self-interactions that lead to infinite self-assembly. This mechanism can be involved in disease, as in sickle-cell anemia, but may also serve in adaptation. Importantly, it differs fundamentally from aggregation, because misfolding does not drive it. Thus, we term it “agglomeration”. The ease with which agglomeration can occur, even by single point mutations, shifts the paradigm of how quickly new protein assemblies can emerge, both in health and disease. This prompts us to determine the basic principles of protein agglomeration and explore its implications in cell physiology and human disease. We propose an interdisciplinary research program bridging atomic and cellular scales to explore agglomeration in three aims: (i) Map the landscape of protein agglomeration in response to mutation in endogenous yeast proteins; (ii) Characterize how yeast physiology impacts agglomeration by changes in gene expression or cell state, and, conversely, how protein agglomerates impact yeast fitness. (iii) Analyze agglomeration in relation to human disease via two approaches. First, by predicting single nucleotide polymorphisms that trigger agglomeration, prioritizing them using knowledge from Aims 1 & 2, and characterizing them experimentally. Second, by providing a proof-of-concept that agglomeration can be exploited in drug design, whereby drugs induce its formation, like mutations can do. Overall, through this research, we aim to establish agglomeration as a paradigm for protein assembly, with implications for our understanding of evolution, physiology, and disease.

2 574 819 €

Start date: 2019-04-01, End date: 2024-03-31

In most European countries social insurance programs, like welfare, unemployment insurance and disability insurance are characterized by low reemployment rates. Therefore, governments spend huge amounts of money on active labour market programs, which should help individuals in finding work. Recent surveys indicate that programs which aim at intensifying job search behaviour are much more effective than schooling programs for improving human capital. A second conclusion from these surveys is that despite the size of the spendings on these programs, evidence on its effectiveness is limited. This research proposal aims at developing an economic framework that will be used to evaluate the effectiveness of popular programs like offering reemployment bonuses, fraud detection, workfare and job search monitoring. The main innovation is that I will combine economic theory with recently developed econometric techniques and detailed administrative data sets, which have not been explored before. While most of the literature only focuses on short-term outcomes, the available data allow me to also consider the long-term effectiveness of programs. The key advantage of an economic model is that I can compare the effectiveness of the different programs, consider modifications of programs and combinations of programs. Furthermore, using an economic model I can construct profiling measures to improve the targeting of programs to subsamples of the population. This is particularly relevant if the effectiveness of programs differs between individuals or depends on the moment in time the program is offered. Therefore, the results from this research will not only be of scientific interest, but will also be of great value to policymakers.

550 000 €

Start date: 2008-07-01, End date: 2013-06-30

Anopheles gambiae mosquitoes are the major vectors of malaria, a disease with devastating consequences for human health. Novel methods for controlling the natural vector populations are urgently needed, given the evolution of insecticide resistance in mosquitoes and the lack of novel insecticidals. Understanding the processes at the bases of mosquito biology may help to roll back malaria. In this proposal, we will target mosquito reproduction, a major determinant of the An. gambiae vectorial capacity. This will be achieved at two levels: (i) fundamental research, to provide a deeper knowledge of the processes regulating reproduction in this species, and (ii) applied research, to identify novel targets and to develop innovative approaches for the control of natural populations. We will focus our analysis on three major players of mosquito reproduction: male accessory glands (MAGs), sperm, and spermatheca, in both laboratory and field settings. We will then translate this information into the identification of inhibitors of mosquito fertility. The experimental activities will be divided across three objectives. In Objective 1, we will unravel the role of the MAGs in shaping mosquito fertility and behaviour, by performing a combination of transcriptional and functional studies that will reveal the multifaceted activities of these tissues. In Objective 2 we will instead focus on the identification of the male and female factors responsible for sperm viability and function. Results obtained in both objectives will be validated in field mosquitoes. In Objective 3, we will perform screens aimed at the identification of inhibitors of mosquito reproductive success. This study will reveal as yet unknown molecular mechanisms underlying reproductive success in mosquitoes, considerably increasing our knowledge beyond the state-of-the-art and critically contributing with innovative tools and ideas to the fight against malaria.

1 500 000 €

Start date: 2011-01-01, End date: 2015-12-31

"A conventional assumption in dynamic models is that agents form their expectations in a very sophisticated manner. In particular, that they have Rational Expectations (RE). We develop some tools to relax this assumption while retaining fully optimal behaviour by agents. We study implications for asset pricing and macro policy. We assume that agents have a consistent set of beliefs that is close, but not equal, to RE. Agents are ""Internally Rational"", that is, they behave rationally given their system of beliefs. Thus, it is conceptually a small deviation from RE. It provides microfoundations for models of adaptive learning, since the learning algorithm is determined by agents’ optimal behaviour. In previous work we have shown that this framework can match stock price and housing price fluctuations, and that policy implications are quite different. In this project we intend to: i) develop further the foundations of internally rational (IR) learning, ii) apply this to explain observed asset price price behavior, such as stock prices, bond prices, inflation, commodity derivatives, and exchange rates, iii) extend the IR framework to the case when agents entertain various models, iv) optimal policy under IR learning and under private information when some hidden shocks are not revealed ex-post. Along the way we will address policy issues such as: effects of creating derivative markets, sovereign spread as a signal of sovereign default risk, tests of fiscal sustainability, fiscal policy when agents learn, monetary policy (more specifically, QE measures and interest rate policy), and the role of credibility in macro policy."

1 970 260 €

Start date: 2013-06-01, End date: 2018-08-31

Since the invention of the spinning frame, automation has been one of the drivers of economic growth. Yet, workers, economist or the general public have been concerned that automation may destroy jobs or create inequality. This concern is particularly prevalent today with the sustained rise in economic inequality and fast technological progress in IT, robotics or self-driving cars. The empirical literature has showed the impact of automation on income distribution. Yet, the level of wages itself should also affect the incentives to undertake automation innovations. Understanding this feedback is key to assess the long-term effect of policies. My project aims to provide the first quantitative account of the two-way relationship between automation and the income distribution. It is articulated around three parts. First, I will use patent data to study empirically the causal effect of wages on automation innovations. To do so, I will build firm-level variation in the wages of the customers of innovating firms by exploiting variations in firms’ exposure to international markets. Second, I will study empirically the causal effect of automation innovations on wages. There, I will focus on local labour market and use the patent data to build exogenous variations in local knowledge. Third, I will calibrate an endogenous growth model with firm dynamics and automation using Danish firm-level data. The model will replicate stylized facts on the labour share distribution across firms. It will be used to compute the contribution of automation to economic growth or the decline of the labour share. Moreover, as a whole, the project will use two different methods (regression analysis and calibrated model) and two different types of data, to answer questions of crucial policy importance such as: Taking into account the response of automation, what are the long-term effects on wages of an increase in the minimum wage, a reduction in labour costs, or a robot tax?

1 295 890 €

Start date: 2018-11-01, End date: 2023-10-31