ERC FUNDED PROJECTS

Mechanisms governing interaction between multicellular organisms and microbes are central for understanding pathogenesis, symbiosis and the function of ecosystems. We propose to address these mechanisms by pioneering an interdisciplinary approach for understanding cellular signalling, response processes and organ development. The challenge is to determine factors synchronising three processes, organogenesis, infection thread formation and bacterial infection, running in parallel to build a root nodule hosting symbiotic bacteria. We aim to exploit the unique possibilities for analysing endocytosis of bacteria in model legumes and to develop genomic, genetic and biological chemistry tools to break new ground in our understanding of carbohydrates in plant development and plant-microbe interaction. Surface exposed rhizobial polysaccharides play a crucial but poorly understood role in infection thread formation and rhizobial invasion resulting in endocytosis. We will undertake an integrated functional characterisation of receptor-ligand mechanisms mediating recognition of secreted polysaccharides and subsequent signal amplification. So far progress in this field has been limited by the complex nature of carbohydrate polymers, lack of a suitable experimental model system where both partners in an interaction could be manipulated and lack of corresponding methods for carbohydrate synthesis, analysis and interaction studies. In this context our legume model system and the discovery that the legume Nod-factor receptors recognise bacterial lipochitin-oligosaccharide signals at their LysM domains provides a new opportunity. Combined with advanced bioorganic chemistry and nanobioscience approaches this proposal will engage the above mentioned limitations.

2 399 127 €

Start date: 2011-05-01, End date: 2016-04-30

As evolutionary biologists we are of course motivated by the desire to gain further insight in to the evolution of natural populations. The main goals of this proposal are to (i) develop theory and methodology that will enable the identification of adaptively evolving genomic regions using polymorphism data, (ii) develop theory and methodology for the estimation of whole-genome rates of adaptive evolution, and (iii) apply the developed theory in two strategic collaborative applications. Capitalizing on recently available and soon-to-be available whole genome polymorphism data across multiple taxa, these approaches are expected to significantly improve the identification and localization of recent selective events, as well as provide long sought after information regarding the genomic distributions of selective effects. Additionally, through these on-going collaborations with empirical and experimental labs, this methodology will allow for specific hypothesis testing that will further illuminate classical examples of adaptation. Together, this proposal seeks to Describe Evolution with Theoretical, Empirical and Computational Tools (DETECT), seeking to accurately describe the very mode and tempo of Darwinian adaptation.

1 071 729 €

Start date: 2013-01-01, End date: 2017-08-31

"Regulation and fidelity of gene expression is fundamental to the differentiation and maintenance of all living organisms. While historically attention has been focused on the process of transcriptional activation, we predict that RNA turnover pathways are equally important for gene expression regulation. This has been implied for selected protein-coding RNAs (mRNAs) but is virtually unexplored for non-protein-coding RNAs (ncRNAs). The intention of the EURECA proposal is to establish cutting-edge research to characterize mammalian nuclear RNA turnover; its factor utility, substrate specificity and regulatory capacity. We foresee that RNA turnover is at the core of gene expression regulation - forming intricate connection to RNA productive systems – thus, being centrally placed to determine RNA fate. EURECA seeks to dramatically improve our understanding of cellular decision processes impacting RNA levels and to establish models for how regulated RNA turnover helps control key biological processes. The realization that the number of ncRNA producing genes was previously grossly underestimated foretells that ncRNA regulation will impact on most aspects of cell biology. Consistently, aberrant ncRNA levels correlate with human disease phenotypes and RNA turnover complexes are linked to disease biology. Still, solid models for how ncRNA turnover regulate biological processes in higher eukaryotes are not available. Moreover, which ncRNAs retain function and which are merely transcriptional by-products remain a major challenge to sort out. The circumstances and kinetics of ncRNA turnover are therefore important to delineate as these will ultimately relate to the likelihood of molecular function. A fundamental challenge here is to also discern which protein complements of non-coding ribonucleoprotein particles (ncRNPs) are (in)compatible with function. Balancing single transcript/factor analysis with high-throughput methodology, EURECA will address these questions."

2 497 960 €

Start date: 2014-04-01, End date: 2019-03-31

Accounting for firms' heterogeneity in trade patterns is probably one of the key innovations of international trade that occurred during the last decade. The impact of initial papers such as Melitz (2003) and Bernard and Jensen (1999) is so large in the field that it is considered to have introduced a new paradigm. Apart from providing a convincing framework for a set of empirical facts, the main motivation of this literature was that there are new gains to be expected from trade liberalization. Those come from a selection process, raising aggregate productivity through the reallocation of output among heterogeneous firms. It initially seemed that the information requirements for trade policy evaluations had become much more demanding, in particular requiring detailed micro data. However, the recent work of Arkolakis et al. (2011) suggests that two aggregate ``sufficient statistics'' may be all that is needed to compute the welfare changes associated with trade liberalization. More, they show that those statistics are the same when evaluating welfare changes in representative firm models. The project has three parts. The first one starts by showing that the sufficient statistics approach relies crucially on a specific distributional assumption on heterogeneity, the Pareto distribution. When distributed non-Pareto, heterogeneity does matter, i.e. aggregate statistics are not sufficient to evaluate welfare changes and predict trade patterns. The second part of the project specifies which type of firm-level heterogeneity matters. It shows how to identify which sectors are characterized by ``productivity sorting'' and in which ones ``quality sorting'' is more relevant. Extending the analysis to multiple product firms, the third part shows that heterogeneity inside the firm also matters for welfare changes following trade shocks. It considers how the change in the product mix of the firm following trade liberalization alters the measured productivity of the firm.

1 119 040 €

Start date: 2012-11-01, End date: 2018-07-31