Project acronym 100 Archaic Genomes
Project Genome sequences from extinct hominins
Researcher (PI) Svante PÄÄBO
Host Institution (HI) MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Call Details Advanced Grant (AdG), LS2, ERC-2015-AdG
Summary Neandertals and Denisovans, an Asian group distantly related to Neandertals, are the closest evolutionary relatives of present-day humans. They are thus of direct relevance for understanding the origin of modern humans and how modern humans differ from their closest relatives. We will generate genome-wide data from a large number of Neandertal and Denisovan individuals from across their geographical and temporal range as well as from other extinct hominin groups which we may discover. This will be possible by automating highly sensitive approaches to ancient DNA extraction and DNA libraries construction that we have developed so that they can be applied to many specimens from many sites in order to identify those that contain retrievable DNA. Whenever possible we will sequence whole genomes and in other cases use DNA capture methods to generate high-quality data from representative parts of the genome. This will allow us to study the population history of Neandertals and Denisovans, elucidate how many times and where these extinct hominins contributed genes to present-day people, and the extent to which modern humans and archaic groups contributed genetically to Neandertals and Denisovans. By retrieving DNA from specimens that go back to the Middle Pleistocene we will furthermore shed light on the early history and origins of Neandertals and Denisovans.
Summary
Neandertals and Denisovans, an Asian group distantly related to Neandertals, are the closest evolutionary relatives of present-day humans. They are thus of direct relevance for understanding the origin of modern humans and how modern humans differ from their closest relatives. We will generate genome-wide data from a large number of Neandertal and Denisovan individuals from across their geographical and temporal range as well as from other extinct hominin groups which we may discover. This will be possible by automating highly sensitive approaches to ancient DNA extraction and DNA libraries construction that we have developed so that they can be applied to many specimens from many sites in order to identify those that contain retrievable DNA. Whenever possible we will sequence whole genomes and in other cases use DNA capture methods to generate high-quality data from representative parts of the genome. This will allow us to study the population history of Neandertals and Denisovans, elucidate how many times and where these extinct hominins contributed genes to present-day people, and the extent to which modern humans and archaic groups contributed genetically to Neandertals and Denisovans. By retrieving DNA from specimens that go back to the Middle Pleistocene we will furthermore shed light on the early history and origins of Neandertals and Denisovans.
Max ERC Funding
2 350 000 €
Duration
Start date: 2016-11-01, End date: 2021-10-31
Project acronym 2-HIT
Project Genetic interaction networks: From C. elegans to human disease
Researcher (PI) Ben Lehner
Host Institution (HI) FUNDACIO CENTRE DE REGULACIO GENOMICA
Call Details Starting Grant (StG), LS2, ERC-2007-StG
Summary Most hereditary diseases in humans are genetically complex, resulting from combinations of mutations in multiple genes. However synthetic interactions between genes are very difficult to identify in population studies because of a lack of statistical power and we fundamentally do not understand how mutations interact to produce phenotypes. C. elegans is a unique animal in which genetic interactions can be rapidly identified in vivo using RNA interference, and we recently used this system to construct the first genetic interaction network for any animal, focused on signal transduction genes. The first objective of this proposal is to extend this work and map a comprehensive genetic interaction network for this model metazoan. This project will provide the first insights into the global properties of animal genetic interaction networks, and a comprehensive view of the functional relationships between genes in an animal. The second objective of the proposal is to use C. elegans to develop and validate experimentally integrated gene networks that connect genes to phenotypes and predict genetic interactions on a genome-wide scale. The methods that we develop and validate in C. elegans will then be applied to predict phenotypes and interactions for human genes. The final objective is to dissect the molecular mechanisms underlying genetic interactions, and to understand how these interactions evolve. The combined aim of these three objectives is to generate a framework for understanding and predicting how mutations interact to produce phenotypes, including in human disease.
Summary
Most hereditary diseases in humans are genetically complex, resulting from combinations of mutations in multiple genes. However synthetic interactions between genes are very difficult to identify in population studies because of a lack of statistical power and we fundamentally do not understand how mutations interact to produce phenotypes. C. elegans is a unique animal in which genetic interactions can be rapidly identified in vivo using RNA interference, and we recently used this system to construct the first genetic interaction network for any animal, focused on signal transduction genes. The first objective of this proposal is to extend this work and map a comprehensive genetic interaction network for this model metazoan. This project will provide the first insights into the global properties of animal genetic interaction networks, and a comprehensive view of the functional relationships between genes in an animal. The second objective of the proposal is to use C. elegans to develop and validate experimentally integrated gene networks that connect genes to phenotypes and predict genetic interactions on a genome-wide scale. The methods that we develop and validate in C. elegans will then be applied to predict phenotypes and interactions for human genes. The final objective is to dissect the molecular mechanisms underlying genetic interactions, and to understand how these interactions evolve. The combined aim of these three objectives is to generate a framework for understanding and predicting how mutations interact to produce phenotypes, including in human disease.
Max ERC Funding
1 100 000 €
Duration
Start date: 2008-09-01, End date: 2014-04-30
Project acronym 3D-In-Macro
Project Inequality in 3D – measurement and implications for macroeconomic theory
Researcher (PI) Andreas Fagereng
Host Institution (HI) STIFTELSEN HANDELSHOYSKOLEN BI
Call Details Starting Grant (StG), SH1, ERC-2019-STG
Summary This project will contribute toward a better understanding of inequality and its macroeconomic implications. We will study inequality and its dynamics along three dimensions: Consumption, Income and Wealth, “3D Inequality.” With novel microdata we can measure the entirety of the economy down to the single household along the 3 dimensions.
In macroeconomics, much theoretical progress has been made in understanding when distributions matter for aggregates. Newer heterogeneous agent models deliver strikingly different implications for monetary and fiscal policies than what the traditional representative agent models do, and also allow us to study the distributional implications of different policies across households. In principle, this class of models can incorporate the potentially rich interactions between inequality and the macroeconomy: on the one hand, inequality shapes macroeconomic aggregates; on the other hand, macroeconomic shocks and policies affect inequality. However, absent precise micro-level facts it is difficult to establish which of the potential mechanisms highlighted by these models are the most important in reality.
Our empirical efforts will be disciplined by these recent developments in modelling macroeconomic phenomena with microeconomic heterogeneity. Our overarching motivation is to quantify the type of micro heterogeneity that matters for macroeconomic theory and thereby inform the development of current and future macroeconomic models. The novel insights we aim to provide could lead to substantial improvements in both fiscal and monetary policy tools. Furthermore, a better understanding of the forces behind growing inequality will inform the current debate on this issue and provide important lessons to policy makers who see economic inequality as a problem in itself.
Summary
This project will contribute toward a better understanding of inequality and its macroeconomic implications. We will study inequality and its dynamics along three dimensions: Consumption, Income and Wealth, “3D Inequality.” With novel microdata we can measure the entirety of the economy down to the single household along the 3 dimensions.
In macroeconomics, much theoretical progress has been made in understanding when distributions matter for aggregates. Newer heterogeneous agent models deliver strikingly different implications for monetary and fiscal policies than what the traditional representative agent models do, and also allow us to study the distributional implications of different policies across households. In principle, this class of models can incorporate the potentially rich interactions between inequality and the macroeconomy: on the one hand, inequality shapes macroeconomic aggregates; on the other hand, macroeconomic shocks and policies affect inequality. However, absent precise micro-level facts it is difficult to establish which of the potential mechanisms highlighted by these models are the most important in reality.
Our empirical efforts will be disciplined by these recent developments in modelling macroeconomic phenomena with microeconomic heterogeneity. Our overarching motivation is to quantify the type of micro heterogeneity that matters for macroeconomic theory and thereby inform the development of current and future macroeconomic models. The novel insights we aim to provide could lead to substantial improvements in both fiscal and monetary policy tools. Furthermore, a better understanding of the forces behind growing inequality will inform the current debate on this issue and provide important lessons to policy makers who see economic inequality as a problem in itself.
Max ERC Funding
1 376 875 €
Duration
Start date: 2020-05-01, End date: 2025-04-30
Project acronym 3D-loop
Project Mechanism of homology search and the logic of homologous chromosome pairing in meiosis
Researcher (PI) Aurele PIAZZA
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Starting Grant (StG), LS2, ERC-2019-STG
Summary 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.
Summary
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.
Max ERC Funding
1 499 779 €
Duration
Start date: 2020-01-01, End date: 2024-12-31
Project acronym 3D-REPAIR
Project Spatial organization of DNA repair within the nucleus
Researcher (PI) Evanthia Soutoglou
Host Institution (HI) THE UNIVERSITY OF SUSSEX
Call Details Consolidator Grant (CoG), LS2, ERC-2015-CoG
Summary 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
Summary
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
Max ERC Funding
1 999 750 €
Duration
Start date: 2017-03-01, End date: 2022-02-28
Project acronym 3DEpi
Project Transgenerational epigenetic inheritance of chromatin states : the role of Polycomb and 3D chromosome architecture
Researcher (PI) Giacomo CAVALLI
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Advanced Grant (AdG), LS2, ERC-2017-ADG
Summary 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.
Summary
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.
Max ERC Funding
2 500 000 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym 4C
Project 4C technology: uncovering the multi-dimensional structure of the genome
Researcher (PI) Wouter Leonard De Laat
Host Institution (HI) KONINKLIJKE NEDERLANDSE AKADEMIE VAN WETENSCHAPPEN - KNAW
Call Details Starting Grant (StG), LS2, ERC-2007-StG
Summary The architecture of DNA in the cell nucleus is an emerging epigenetic key contributor to genome function. We recently developed 4C technology, a high-throughput technique that combines state-of-the-art 3C technology with tailored micro-arrays to uniquely allow for an unbiased genome-wide search for DNA loci that interact in the nuclear space. Based on 4C technology, we were the first to provide a comprehensive overview of long-range DNA contacts of selected loci. The data showed that active and inactive chromatin domains contact many distinct regions within and between chromosomes and genes switch long-range DNA contacts in relation to their expression status. 4C technology not only allows investigating the three-dimensional structure of DNA in the nucleus, it also accurately reconstructs at least 10 megabases of the one-dimensional chromosome sequence map around the target sequence. Changes in this physical map as a result of genomic rearrangements are therefore identified by 4C technology. We recently demonstrated that 4C detects deletions, balanced inversions and translocations in patient samples at a resolution (~7kb) that allowed immediate sequencing of the breakpoints. Excitingly, 4C technology therefore offers the first high-resolution genomic approach that can identify both balanced and unbalanced genomic rearrangements. 4C is expected to become an important tool in clinical diagnosis and prognosis. Key objectives of this proposal are: 1. Explore the functional significance of DNA folding in the nucleus by systematically applying 4C technology to differentially expressed gene loci. 2. Adapt 4C technology such that it allows for massive parallel analysis of DNA interactions between regulatory elements and gene promoters. This method would greatly facilitate the identification of functionally relevant DNA elements in the genome. 3. Develop 4C technology into a clinical diagnostic tool for the accurate detection of balanced and unbalanced rearrangements.
Summary
The architecture of DNA in the cell nucleus is an emerging epigenetic key contributor to genome function. We recently developed 4C technology, a high-throughput technique that combines state-of-the-art 3C technology with tailored micro-arrays to uniquely allow for an unbiased genome-wide search for DNA loci that interact in the nuclear space. Based on 4C technology, we were the first to provide a comprehensive overview of long-range DNA contacts of selected loci. The data showed that active and inactive chromatin domains contact many distinct regions within and between chromosomes and genes switch long-range DNA contacts in relation to their expression status. 4C technology not only allows investigating the three-dimensional structure of DNA in the nucleus, it also accurately reconstructs at least 10 megabases of the one-dimensional chromosome sequence map around the target sequence. Changes in this physical map as a result of genomic rearrangements are therefore identified by 4C technology. We recently demonstrated that 4C detects deletions, balanced inversions and translocations in patient samples at a resolution (~7kb) that allowed immediate sequencing of the breakpoints. Excitingly, 4C technology therefore offers the first high-resolution genomic approach that can identify both balanced and unbalanced genomic rearrangements. 4C is expected to become an important tool in clinical diagnosis and prognosis. Key objectives of this proposal are: 1. Explore the functional significance of DNA folding in the nucleus by systematically applying 4C technology to differentially expressed gene loci. 2. Adapt 4C technology such that it allows for massive parallel analysis of DNA interactions between regulatory elements and gene promoters. This method would greatly facilitate the identification of functionally relevant DNA elements in the genome. 3. Develop 4C technology into a clinical diagnostic tool for the accurate detection of balanced and unbalanced rearrangements.
Max ERC Funding
1 225 000 €
Duration
Start date: 2008-09-01, End date: 2013-08-31
Project acronym 4D-GenEx
Project Spatio-temporal Organization and Expression of the Genome
Researcher (PI) Antoine COULON
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Starting Grant (StG), LS2, ERC-2017-STG
Summary 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.
Summary
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.
Max ERC Funding
1 499 750 €
Duration
Start date: 2018-04-01, End date: 2023-03-31
Project acronym ABEP
Project Asset Bubbles and Economic Policy
Researcher (PI) Jaume Ventura Fontanet
Host Institution (HI) Centre de Recerca en Economia Internacional (CREI)
Call Details Advanced Grant (AdG), SH1, ERC-2009-AdG
Summary 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.
Summary
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.
Max ERC Funding
1 000 000 €
Duration
Start date: 2010-04-01, End date: 2015-03-31
Project acronym ABRSEIST
Project Antibiotic Resistance: Socio-Economic Determinants and the Role of Information and Salience in Treatment Choice
Researcher (PI) Hannes ULLRICH
Host Institution (HI) DEUTSCHES INSTITUT FUR WIRTSCHAFTSFORSCHUNG DIW (INSTITUT FUR KONJUNKTURFORSCHUNG) EV
Call Details Starting Grant (StG), SH1, ERC-2018-STG
Summary Antibiotics have contributed to a tremendous increase in human well-being, saving many millions of lives. However, antibiotics become obsolete the more they are used as selection pressure promotes the development of resistant bacteria. The World Health Organization has proclaimed antibiotic resistance as a major global threat to public health. Today, 700,000 deaths per year are due to untreatable infections. To win the battle against antibiotic resistance, new policies affecting the supply and demand of existing and new drugs must be designed. I propose new research to identify and evaluate feasible and effective demand-side policy interventions targeting the relevant decision makers: physicians and patients. ABRSEIST will make use of a broad econometric toolset to identify mechanisms linking antibiotic resistance and consumption exploiting a unique combination of physician-patient-level antibiotic resistance, treatment, and socio-economic data. Using machine learning methods adapted for causal inference, theory-driven structural econometric analysis, and randomization in the field it will provide rigorous evidence on effective intervention designs. This research will improve our understanding of how prescribing, resistance, and the effect of antibiotic use on resistance, are distributed in the general population which has important implications for the design of targeted interventions. It will then estimate a structural model of general practitioners’ acquisition and use of information under uncertainty about resistance in prescription choice, allowing counterfactual analysis of information-improving policies such as mandatory diagnostic testing. The large-scale and structural econometric analyses allow flexible identification of physician heterogeneity, which ABRSEIST will exploit to design and evaluate targeted, randomized information nudges in the field. The result will be improved rational use and a toolset applicable in contexts of antibiotic prescribing.
Summary
Antibiotics have contributed to a tremendous increase in human well-being, saving many millions of lives. However, antibiotics become obsolete the more they are used as selection pressure promotes the development of resistant bacteria. The World Health Organization has proclaimed antibiotic resistance as a major global threat to public health. Today, 700,000 deaths per year are due to untreatable infections. To win the battle against antibiotic resistance, new policies affecting the supply and demand of existing and new drugs must be designed. I propose new research to identify and evaluate feasible and effective demand-side policy interventions targeting the relevant decision makers: physicians and patients. ABRSEIST will make use of a broad econometric toolset to identify mechanisms linking antibiotic resistance and consumption exploiting a unique combination of physician-patient-level antibiotic resistance, treatment, and socio-economic data. Using machine learning methods adapted for causal inference, theory-driven structural econometric analysis, and randomization in the field it will provide rigorous evidence on effective intervention designs. This research will improve our understanding of how prescribing, resistance, and the effect of antibiotic use on resistance, are distributed in the general population which has important implications for the design of targeted interventions. It will then estimate a structural model of general practitioners’ acquisition and use of information under uncertainty about resistance in prescription choice, allowing counterfactual analysis of information-improving policies such as mandatory diagnostic testing. The large-scale and structural econometric analyses allow flexible identification of physician heterogeneity, which ABRSEIST will exploit to design and evaluate targeted, randomized information nudges in the field. The result will be improved rational use and a toolset applicable in contexts of antibiotic prescribing.
Max ERC Funding
1 498 920 €
Duration
Start date: 2019-01-01, End date: 2023-12-31