ERC FUNDED PROJECTS

The goal of this project is to demonstrate that novel aspects of the molecular basis of Darwinian adaptation can be discovered if the polygenic basis of adaptation is taken into account. This project will use the genome-wide distribution of cis-regulatory variants to discover the molecular pathways that are optimized during adaptation via accumulation of small effect mutations. Current approaches include scans for outlier genes with strong population genetics signatures of selection, or large effect QTL associating with fitness. They can only reveal a small subset of the molecular changes recruited along adaptive paths. Here, instead, the distribution of small effect mutations will be used to make inferences on the targets of polygenic adaptation across divergent populations in each of the two closely related species, A. thaliana and A. lyrata. These species are both found at diverse latitudes and show sign of local adaptation to climatic differences. Mutations affecting cis-regulation will be identified in leaves of plants exposed to various temperature regimes triggering phenotypic responses of adaptive relevance. Their distribution in clusters of functionally connected genes will be quantified. The phylogeographic differences in the distribution of the mutations will be used to disentangle neutral from adaptive clusters of functionally connected genes in each of the two species. This project will identify the molecular pathways subjected collectively to natural selection and provide a completely novel view on adaptive landscapes. It will further examine whether local adaptation occurs by convergent evolution of molecular systems in plants. This approach has the potential to find broad applications in ecology and agriculture.

1 683 120 €

Start date: 2015-09-01, End date: 2020-08-31

Applied electrochemistry plays a key role in many technologies, such as batteries, fuel cells, supercapacitors or solar cells. It is therefore at the core of many research programs all over the world. Yet, fundamental electrochemical investigations remain scarce. In particular, electrochemistry is among the fields for which the gap between theory and experiment is the largest. From the computational point of view, there is no molecular dynamics (MD) software devoted to the simulation of electrochemical systems while other fields such as biochemistry (GROMACS) or material science (LAMMPS) have dedicated tools. This is due to the difficulty of accounting for complex effects arising from (i) the degree of metallicity of the electrode (i.e. from semimetals to perfect conductors), (ii) the mutual polarization occurring at the electrode/electrolyte interface and (iii) the redox reactivity through explicit electron transfers. Current understanding therefore relies on standard theories that derive from an inaccurate molecular-scale picture. My objective is to fill this gap by introducing a whole set of new methods for simulating electrochemical systems. They will be provided to the computational electrochemistry community as a cutting-edge MD software adapted to supercomputers. First applications will aim at the discovery of new electrolytes for energy storage. Here I will focus on (1) ‘‘water-in-salts’’ to understand why these revolutionary liquids enable much higher voltage than conventional solutions (2) redox reactions inside a nanoporous electrode to support the development of future capacitive energy storage devices. These selected applications are timely and rely on collaborations with leading experimental partners. The results are expected to shed an unprecedented light on the importance of polarization effects on the structure and the reactivity of electrode/electrolyte interfaces, establishing MD as a prominent tool for solving complex electrochemistry problems.

1 588 769 €

Start date: 2018-04-01, End date: 2023-03-31

Our ability to predict adaptation and the response of populations to selection is limited. Solving this issue is a fundamental challenge of evolutionary ecology with implications for applied sciences such as conservation, and agronomy. Non genetic inheritance (NGI; e.g., ecological niche transmission) is suspected to play a foremost role in adaptive evolution but such hypothesis remains untested. Using quantitative genetics in wild plant populations, experimental evolution, and epigenetics, we will assess the role of NGI in the adaptive response to selection of plant populations. The ANGI project will follow the subsequent research program: (1) Using long-term survey data, we will measure natural selection in wild populations of Antirrhinum majus within its heterogeneous array of micro-habitats. We will calculate the fitness gain provided by multiple traits and stem elongation to plants growing in bushes where they compete for light. Stem elongation is known to depend on epigenetic variation. (2) Using a statistical approach that we developed, we will estimate the quantitative genetic and non genetic heritability of traits. (3) We will identify phenotypic changes caused by fitness that are based on genetic variation and NGI and assess their respective roles in adaptive evolution. (4) In controlled conditions, we will artificially select for increased stem elongation in clonal lineages, thereby excluding DNA variation. We will quantify the non genetic response to selection and test for a quantitative epigenetic signature of selection. (5) We will build on our results to generate an inclusive theory of genetic and non genetic natural selection. ANGI builds on a confirmed expertise in selection experiments, quantitative genetics and NGI. In addition, the availability of survey data provides a solid foundation for the achievement of this project. Our ambition is to shed light on original mechanisms underlying adaptation that are an alternative to genetic selection.

1 999 970 €

Start date: 2016-03-01, End date: 2021-02-28

Cognition improves an animal’s ability to tune its responses to environmental conditions. In group living animals, communication works to form a collective cognition that expands the group’s abilities beyond those of individuals. Despite much research, to date, there is little understanding of how collective cognition emerges within biological ensembles. A major obstacle towards such an understanding is the rarity of comprehensive multi-scale empirical data of these complex systems. We have demonstrated cooperative load transport by ants to be an ideal system to study the emergence of cognition. Similar to other complex cognitive systems, the ants employ high levels of emergence to achieve efficient problem solving over a large range of scenarios. Unique to this system, is its extreme amenability to experimental measurement and manipulation where internal conflicts map to forces, abstract decision making is reflected in direction changes, and future planning manifested in pheromone trails. This allows for an unprecedentedly detailed, multi-scale empirical description of the moment-to-moment unfolding of sophisticated cognitive processes. This proposal is aimed at materializing this potential to the full. We will examine the ants’ problem solving capabilities under a variety of environmental challenges. We will expose the underpinning rules on the different organizational scales, the flow of information between them, and their relative contributions to collective performance. This will allow for empirical comparisons between the ‘group’ and the ‘sum of its parts’ from which we will quantify the level of emergence in this system. Using the language of information, we will map the boundaries of this group’s collective cognition and relate them to the range of habitable environmental niches. Moreover, we will generalize these insights to formulate a new paradigm of emergence in biological groups opening new horizons in the study of cognitive processes in general.

2 000 000 €

Start date: 2018-06-01, End date: 2023-05-31