ERC FUNDED PROJECTS

Homologous recombination (HR) is a conserved DNA double-strand breaks (DSB) repair pathway that uniquely uses an intact DNA molecule as a template. Genome-wide homology search is carried out by a nucleoprotein filament (NPF) assembled on the ssDNA flanking the DSB, and whose product is a “D-loop” joint molecule. Beyond accurate DSB repair, this capacity of HR to spatially associates homologous molecules is also harnessed for homolog pairing in meiosis. The goal of “3D-loop” is to tackle two long lasting conundrums: the fundamental homology search mechanism that achieves accurate and efficient identification of a single homologous donor in the vastness of the genome and nucleus, and how this mechanism is adapted for the purpose of homologs attachment in meiosis. I overcame the main hurdle to study these core steps of HR by developing a suite of proximity ligation-based methodologies and experimental systems to physically detect joint molecules in yeast cells. It revealed elaborate regulation controlling D-loop dynamics and a novel class of joint molecules. This proposal builds upon these methodologies and findings to first address basic properties of the homology sampling process by the NPF and the role of D-loop dynamics, with the long-term goal to establish a quantitative framework of homology search in mitotic cells (WP1). Second, the meiosis-specific regulation of homology search leading to homolog pairing likely integrates chromosomal-scale information. Genome re-synthesis and engineering approaches will be deployed to (i) achieve a quantitative and dynamic cartography of the cytological and molecular events of meiosis over a large chromosomal region, (ii) probe cis-acting regulations at the chromosomal scale, and (iii) revisit the molecular paradigm for crossover formation (WP2). We expect this project to shed light on the fundamental process of homology search and its involvement in the chromosome pairing phenomenon lying at the basis of sexual reproduction.

1 499 779 €

Start date: 2020-01-01, End date: 2024-12-31

Epigenetic inheritance entails transmission of phenotypic traits not encoded in the DNA sequence and, in the most extreme case, Transgenerational Epigenetic Inheritance (TEI) involves transmission of memory through multiple generations. Very little is known on the mechanisms governing TEI and this is the subject of the present proposal. By transiently enhancing long-range chromatin interactions, we recently established isogenic Drosophila epilines that carry stable alternative epialleles, defined by differential levels of the Polycomb-dependent H3K27me3 mark. Furthermore, we extended our paradigm to natural phenotypes. These are ideal systems to study the role of Polycomb group (PcG) proteins and other components in regulating nuclear organization and epigenetic inheritance of chromatin states. The present project conjugates genetics, epigenomics, imaging and molecular biology to reach three critical aims. Aim 1: Analysis of the molecular mechanisms regulating Polycomb-mediated TEI. We will identify the DNA, protein and RNA components that trigger and maintain transgenerational chromatin inheritance as well as their mechanisms of action. Aim 2: Role of 3D genome organization in the regulation of TEI. We will analyze the developmental dynamics of TEI-inducing long-range chromatin interactions, identify chromatin components mediating 3D chromatin contacts and characterize their function in the TEI process. Aim 3: Identification of a broader role of TEI during development. TEI might reflect a normal role of PcG components in the transmission of parental chromatin onto the next embryonic generation. We will explore this possibility by establishing other TEI paradigms and by relating TEI to the normal PcG function in these systems and in normal development. This research program will unravel the biological significance and the molecular underpinnings of TEI and lead the way towards establishing this area of research into a consolidated scientific discipline.

2 500 000 €

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

This project investigates the two-way relationship between spatio-temporal genome organization and coordinated gene regulation, through an approach at the interface between physics, computer science and biology. In the nucleus, preferred positions are observed from chromosomes to single genes, in relation to normal and pathological cellular states. Evidence indicates a complex spatio-temporal coupling between co-regulated genes: e.g. certain genes cluster spatially when responding to similar factors and transcriptional noise patterns suggest domain-wide mechanisms. Yet, no individual experiment allows probing transcriptional coordination in 4 dimensions (FISH, live locus tracking, Hi-C...). Interpreting such data also critically requires theory (stochastic processes, statistical physics…). A lack of appropriate experimental/analytical approaches is impairing our understanding of the 4D genome. Our proposal combines cutting-edge single-molecule imaging, signal-theory data analysis and physical modeling to study how genes coordinate in space and time in a single nucleus. Our objectives are to understand (a) competition/recycling of shared resources between genes within subnuclear compartments, (b) how enhancers communicate with genes domain-wide, and (c) the role of local conformational dynamics and supercoiling in gene co-regulation. Our organizing hypothesis is that, by acting on their microenvironment, genes shape their co-expression with other genes. Building upon my expertise, we will use dual-color MS2/PP7 RNA labeling to visualize for the first time transcription and motion of pairs of hormone-responsive genes in real time. With our innovative signal analysis tools, we will extract spatio-temporal signatures of underlying processes, which we will investigate with stochastic modeling and validate through experimental perturbations. We expect to uncover how the functional organization of the linear genome relates to its physical properties and dynamics in 4D.

1 499 750 €

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

"How are actions initiated by the human brain when there is no external sensory cue or other immediate imperative? How do subtle ongoing interactions within the brain and between the brain, body, and sensory context influence the spontaneous initiation of action? How should we approach the problem of trying to identify the neural events that cause spontaneous voluntary action? Much is understood about how the brain decides between competing alternatives, leading to different behavioral responses. But far less is known about how the brain decides ""when"" to perform an action, or ""whether"" to perform an action in the first place, especially in a context where there is no sensory cue to act such as during foraging. This project seeks to open a new chapter in the study of spontaneous voluntary action building on a novel hypothesis recently introduced by the applicant (Schurger et al, PNAS 2012) concerning the role of ongoing neural activity in action initiation. We introduce brain-behavior forecasting, the converse of movement-locked averaging, as an approach to identifying the neurodynamic states that commit the motor system to performing an action ""now"", and will apply it in the context of information foraging. Spontaneous action remains a profound mystery in the brain basis of behavior, in humans and other animals, and is also central to the problem of asynchronous intention-detection in brain-computer interfaces (BCIs). A BCI must not only interpret what the user intends, but also must detect ""when"" the user intends to act, and not respond otherwise. This remains the biggest challenge in the development of high-performance BCIs, whether invasive or non-invasive. This project will take a systematic and collaborative approach to the study of spontaneous self-initiated action, incorporating computational modeling, neuroimaging, and machine learning techniques towards a deeper understanding of voluntary behavior and the robust asynchronous detection of decisions-to-act."

1 338 130 €

Start date: 2015-10-01, End date: 2020-09-30