Project acronym 3D-REPAIR
Project Spatial organization of DNA repair within the nucleus
Researcher (PI) Evanthia Soutoglou
Host Institution (HI) THE UNIVERSITY OF SUSSEX
Country United Kingdom
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 ALZSYN
Project Imaging synaptic contributors to dementia
Researcher (PI) Tara Spires-Jones
Host Institution (HI) THE UNIVERSITY OF EDINBURGH
Country United Kingdom
Call Details Consolidator Grant (CoG), LS5, ERC-2015-CoG
Summary Alzheimer's disease, the most common cause of dementia in older people, is a devastating condition that is becoming a public health crisis as our population ages. Despite great progress recently in Alzheimer’s disease research, we have no disease modifying drugs and a decade with a 99.6% failure rate of clinical trials attempting to treat the disease. This project aims to develop relevant therapeutic targets to restore brain function in Alzheimer’s disease by integrating human and model studies of synapses. It is widely accepted in the field that alterations in amyloid beta initiate the disease process. However the cascade leading from changes in amyloid to widespread tau pathology and neurodegeneration remain unclear. Synapse loss is the strongest pathological correlate of dementia in Alzheimer’s, and mounting evidence suggests that synapse degeneration plays a key role in causing cognitive decline. Here I propose to test the hypothesis that the amyloid cascade begins at the synapse leading to tau pathology, synapse dysfunction and loss, and ultimately neural circuit collapse causing cognitive impairment. The team will use cutting-edge multiphoton and array tomography imaging techniques to test mechanisms downstream of amyloid beta at synapses, and determine whether intervening in the cascade allows recovery of synapse structure and function. Importantly, I will combine studies in robust models of familial Alzheimer’s disease with studies in postmortem human brain to confirm relevance of our mechanistic studies to human disease. Finally, human stem cell derived neurons will be used to test mechanisms and potential therapeutics in neurons expressing the human proteome. Together, these experiments are ground-breaking since they have the potential to further our understanding of how synapses are lost in Alzheimer’s disease and to identify targets for effective therapeutic intervention, which is a critical unmet need in today’s health care system.
Summary
Alzheimer's disease, the most common cause of dementia in older people, is a devastating condition that is becoming a public health crisis as our population ages. Despite great progress recently in Alzheimer’s disease research, we have no disease modifying drugs and a decade with a 99.6% failure rate of clinical trials attempting to treat the disease. This project aims to develop relevant therapeutic targets to restore brain function in Alzheimer’s disease by integrating human and model studies of synapses. It is widely accepted in the field that alterations in amyloid beta initiate the disease process. However the cascade leading from changes in amyloid to widespread tau pathology and neurodegeneration remain unclear. Synapse loss is the strongest pathological correlate of dementia in Alzheimer’s, and mounting evidence suggests that synapse degeneration plays a key role in causing cognitive decline. Here I propose to test the hypothesis that the amyloid cascade begins at the synapse leading to tau pathology, synapse dysfunction and loss, and ultimately neural circuit collapse causing cognitive impairment. The team will use cutting-edge multiphoton and array tomography imaging techniques to test mechanisms downstream of amyloid beta at synapses, and determine whether intervening in the cascade allows recovery of synapse structure and function. Importantly, I will combine studies in robust models of familial Alzheimer’s disease with studies in postmortem human brain to confirm relevance of our mechanistic studies to human disease. Finally, human stem cell derived neurons will be used to test mechanisms and potential therapeutics in neurons expressing the human proteome. Together, these experiments are ground-breaking since they have the potential to further our understanding of how synapses are lost in Alzheimer’s disease and to identify targets for effective therapeutic intervention, which is a critical unmet need in today’s health care system.
Max ERC Funding
2 000 000 €
Duration
Start date: 2016-11-01, End date: 2021-10-31
Project acronym BPI
Project Bayesian Peer Influence: Group Beliefs, Polarisation and Segregation
Researcher (PI) Gilat Levy
Host Institution (HI) LONDON SCHOOL OF ECONOMICS AND POLITICAL SCIENCE
Country United Kingdom
Call Details Consolidator Grant (CoG), SH1, ERC-2015-CoG
Summary "The objective of this research agenda is to provide a new framework to model and analyze dynamics of group beliefs, in order to study phenomena such as group polarization, segregation and inter-group discrimination. We introduce a simple new heuristic, the Bayesian Peer Influence heuristic (BPI), which is based on rational foundations and captures how individuals are influenced by others' beliefs. We will explore the theoretical properties of this heuristic, and apply the model to analyze the implications of belief dynamics on social interactions.
Understanding the formation and evolution of beliefs in groups is an important aspect of many economic applications, such as labour market discrimination. The beliefs that different groups of people have about members of other groups should be central to any theory or empirical investigation of this topic. At the same time, economic models of segregation and discrimination typically do not focus on the evolution and dynamics of group beliefs that allow for such phenomena. There is therefore a need for new tools of analysis for incorporating the dynamics of group beliefs; this is particularly important in order to understand the full implications of policy interventions which often intend to ""educate the public''. The BPI fills this gap in the literature by offering a tractable and natural heuristic for group communication.
Our aim is to study the theoretical properties of the BPI, as well as its applications to the dynamics of group behavior. Our plan is to: (i) Analyze rational learning from others’ beliefs and characterise the BPI. (ii) Use the BPI to account for cognitive biases in information processing. (iii) Use the BPI to analyze the diffusion of beliefs in social networks. (iv) Apply the BPI to understand the relation between belief polarization, segregation in education and labour market discrimination. (v) Apply the BPI to understand the relation between belief polarization and political outcomes."
Summary
"The objective of this research agenda is to provide a new framework to model and analyze dynamics of group beliefs, in order to study phenomena such as group polarization, segregation and inter-group discrimination. We introduce a simple new heuristic, the Bayesian Peer Influence heuristic (BPI), which is based on rational foundations and captures how individuals are influenced by others' beliefs. We will explore the theoretical properties of this heuristic, and apply the model to analyze the implications of belief dynamics on social interactions.
Understanding the formation and evolution of beliefs in groups is an important aspect of many economic applications, such as labour market discrimination. The beliefs that different groups of people have about members of other groups should be central to any theory or empirical investigation of this topic. At the same time, economic models of segregation and discrimination typically do not focus on the evolution and dynamics of group beliefs that allow for such phenomena. There is therefore a need for new tools of analysis for incorporating the dynamics of group beliefs; this is particularly important in order to understand the full implications of policy interventions which often intend to ""educate the public''. The BPI fills this gap in the literature by offering a tractable and natural heuristic for group communication.
Our aim is to study the theoretical properties of the BPI, as well as its applications to the dynamics of group behavior. Our plan is to: (i) Analyze rational learning from others’ beliefs and characterise the BPI. (ii) Use the BPI to account for cognitive biases in information processing. (iii) Use the BPI to analyze the diffusion of beliefs in social networks. (iv) Apply the BPI to understand the relation between belief polarization, segregation in education and labour market discrimination. (v) Apply the BPI to understand the relation between belief polarization and political outcomes."
Max ERC Funding
1 662 942 €
Duration
Start date: 2016-08-01, End date: 2022-01-31
Project acronym DEPP
Project Designing Effective Public Policies
Researcher (PI) Henrik Jacobsen Kleven
Host Institution (HI) LONDON SCHOOL OF ECONOMICS AND POLITICAL SCIENCE
Country United Kingdom
Call Details Consolidator Grant (CoG), SH1, ERC-2015-CoG
Summary This proposal outlines a number of projects in public economics, with links to other fields such as macro, real estate, labor, and gender economics. The projects evolve around several large administrative datasets from the UK and Denmark, and they advance approaches and methodologies that have recently been developed in public economics into new areas. There is a strong public policy focus running through the proposal, including tax policy, transfer policy, family policy, and indirectly monetary policy. The objective is to achieve a comprehensive understanding of how government interventions affect two key markets: the housing market and the labor market.
The project is divided into two themes. The first theme focuses on the housing market and is divided into three subprojects. The first project investigates the effects of mortgage interest rates on leverage and house prices, and it develops a new quasi-experimental method for estimating the elasticity of intertemporal substitution in consumption, a crucial parameter for many public policies. The second and third projects investigate housing market responses to different tax policies, focusing on how such responses are magnified by liquidity constraints and leverage.
The second theme focuses on the labor market and is divided into two subprojects. The first project studies secular changes in gender inequality and the underlying sources of those changes, focusing mainly on the effects of child rearing on gender inequality. The project explores the underlying mechanisms driving child-related inequality, including gender identity norms and family policies. The second project proposes a new way of estimating macro labor supply elasticities that integrates taxes and public expenditures, and it develops a theoretical framework to draw policy implications from those estimations.
Summary
This proposal outlines a number of projects in public economics, with links to other fields such as macro, real estate, labor, and gender economics. The projects evolve around several large administrative datasets from the UK and Denmark, and they advance approaches and methodologies that have recently been developed in public economics into new areas. There is a strong public policy focus running through the proposal, including tax policy, transfer policy, family policy, and indirectly monetary policy. The objective is to achieve a comprehensive understanding of how government interventions affect two key markets: the housing market and the labor market.
The project is divided into two themes. The first theme focuses on the housing market and is divided into three subprojects. The first project investigates the effects of mortgage interest rates on leverage and house prices, and it develops a new quasi-experimental method for estimating the elasticity of intertemporal substitution in consumption, a crucial parameter for many public policies. The second and third projects investigate housing market responses to different tax policies, focusing on how such responses are magnified by liquidity constraints and leverage.
The second theme focuses on the labor market and is divided into two subprojects. The first project studies secular changes in gender inequality and the underlying sources of those changes, focusing mainly on the effects of child rearing on gender inequality. The project explores the underlying mechanisms driving child-related inequality, including gender identity norms and family policies. The second project proposes a new way of estimating macro labor supply elasticities that integrates taxes and public expenditures, and it develops a theoretical framework to draw policy implications from those estimations.
Max ERC Funding
1 294 699 €
Duration
Start date: 2016-06-01, End date: 2021-05-31
Project acronym EDWEL
Project Empirical Demand and Welfare Analysis
Researcher (PI) Debopam Bhattacharya
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Country United Kingdom
Call Details Consolidator Grant (CoG), SH1, ERC-2015-CoG
Summary Measurement of consumer welfare is central to economic evaluations. It underlies calculation of price-indices, formulation of tax policies, and environmental and industrial regulation. But existing measurement methods rely on restrictive assumptions about consumer preferences, leading to potentially incorrect conclusions regarding policy-impacts. The proposed project aims to make fundamental contributions to empirical welfare analysis by developing nonparametric approaches, which would avoid such assumptions and thus produce reliable welfare estimates from micro-data. The emphasis will be on welfare-evaluation of price/quality changes in the under-researched but common real-life setting of discrete-choice, e.g., the impact of tuition subsidies for college entrants, fare-hikes for passengers and access to new channels for TV viewers. The project will cover (i) discrete choice with multinomial/ordered/non-exclusive alternatives, (ii) random coefficient choice-models, (iii) settings where one’s choice affects one’s peers’ utilities, and (iv) dynamic choice under uncertainty such as durable-purchase. Welfare analyses in situations (ii)-(iv) are previously unexplored problems and represent ambitious undertakings. Situation (i) has been analyzed only under strong, unsubstantiated assumptions, like quasilinear preferences and extreme valued errors. The key insight driving the project is that welfare calculations require less information than what is needed to identify underlying preference parameters. The project will also develop methods to overcome common data problems like interval-reporting and endogeneity of income. The theoretical results will be complemented by software codes in Stata/R which can be readily used by practitioners. Given the ubiquity of welfare analysis in economic applications and its use in non-academic settings such as merger-analysis, damage calculations, etc., the project is likely to have a substantial impact both in and beyond the academia.
Summary
Measurement of consumer welfare is central to economic evaluations. It underlies calculation of price-indices, formulation of tax policies, and environmental and industrial regulation. But existing measurement methods rely on restrictive assumptions about consumer preferences, leading to potentially incorrect conclusions regarding policy-impacts. The proposed project aims to make fundamental contributions to empirical welfare analysis by developing nonparametric approaches, which would avoid such assumptions and thus produce reliable welfare estimates from micro-data. The emphasis will be on welfare-evaluation of price/quality changes in the under-researched but common real-life setting of discrete-choice, e.g., the impact of tuition subsidies for college entrants, fare-hikes for passengers and access to new channels for TV viewers. The project will cover (i) discrete choice with multinomial/ordered/non-exclusive alternatives, (ii) random coefficient choice-models, (iii) settings where one’s choice affects one’s peers’ utilities, and (iv) dynamic choice under uncertainty such as durable-purchase. Welfare analyses in situations (ii)-(iv) are previously unexplored problems and represent ambitious undertakings. Situation (i) has been analyzed only under strong, unsubstantiated assumptions, like quasilinear preferences and extreme valued errors. The key insight driving the project is that welfare calculations require less information than what is needed to identify underlying preference parameters. The project will also develop methods to overcome common data problems like interval-reporting and endogeneity of income. The theoretical results will be complemented by software codes in Stata/R which can be readily used by practitioners. Given the ubiquity of welfare analysis in economic applications and its use in non-academic settings such as merger-analysis, damage calculations, etc., the project is likely to have a substantial impact both in and beyond the academia.
Max ERC Funding
1 426 418 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym Endogenous_Info
Project Financial Decision Making with Endogenous Information Acquisition
Researcher (PI) Marcin Kacperczyk
Host Institution (HI) IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
Country United Kingdom
Call Details Consolidator Grant (CoG), SH1, ERC-2015-CoG
Summary Are financial markets informationally efficient? Are some economic agents more informed than others? What is the impact of such heterogeneity on asset prices? These questions, of great economic significance, have permeated academic and business circles over the last few decades. Despite significant progress on the theoretical and empirical fronts relatively little is known about how information is endogenously acquired and processed in markets by agents with differential access to information and facing heterogeneous opportunities.
Using the novel setting of endogenous information acquisition with non-trivial heterogeneity the project has two goals: (A) to lay out micro foundations for informed trading in investment and corporate settings using the contexts of illegal insider trading and household finance; (B) to investigate macro implications of heterogeneous information for global economic phenomena such as income inequality, organizational design, and market power.
Summary
Are financial markets informationally efficient? Are some economic agents more informed than others? What is the impact of such heterogeneity on asset prices? These questions, of great economic significance, have permeated academic and business circles over the last few decades. Despite significant progress on the theoretical and empirical fronts relatively little is known about how information is endogenously acquired and processed in markets by agents with differential access to information and facing heterogeneous opportunities.
Using the novel setting of endogenous information acquisition with non-trivial heterogeneity the project has two goals: (A) to lay out micro foundations for informed trading in investment and corporate settings using the contexts of illegal insider trading and household finance; (B) to investigate macro implications of heterogeneous information for global economic phenomena such as income inequality, organizational design, and market power.
Max ERC Funding
1 588 959 €
Duration
Start date: 2016-06-01, End date: 2020-05-31
Project acronym Frontiers in Design
Project Frontiers in Mechanism Design: Methodology and Applications
Researcher (PI) Vasiliki Skreta
Host Institution (HI) UNIVERSITY COLLEGE LONDON
Country United Kingdom
Call Details Consolidator Grant (CoG), SH1, ERC-2015-CoG
Summary Mechanism design is the engineering side of economics. Research findings in this field have helped governments and practitioners worldwide design better institutions: auctions that are more profitable or efficient; labour markets that improve the match between employees and employers; and better ways to assign students to public schools. The cornerstone of mechanism design is the revelation principle, which provides a canonical class of mechanisms and turns the mechanism-selection problem (which a priori may appear unmanageable) to a constrained optimization problem. The standard mechanism design paradigm relies on three fundamental assumptions: 1. The designer of the institution—the principal—does not have any privileged information. 2. The principal chooses the mechanism and commits to it once and for all. 3. There is no interrelationship of the mechanism with outside markets. In addition, almost the entire mechanism design literature assumes that private information is unverifiable (soft). These assumptions often fail in today’s “big data” world: Firms (online retailers, insurance companies, banks) do have privileged—and often certifiable—information that may affect contractual terms they propose. Also, they interact repeatedly with the same agents and, as they learn about them, they attempt to change the terms by making personalized offers. Finally, often a mechanism—e.g. a government insurance program—interacts with private insurance markets. The proposed research aims at providing methods and foundations to design optimal mechanisms at precisely those highly relevant situations: 1. mechanism-design by an informed principal, 2. design of mechanisms and their transparency when the principal lacks commitment, 3. mechanism-design when an intervention interacts with markets. The latter part of the project aims to employ these cutting-edge tools to revisit the design of insurance markets.
Summary
Mechanism design is the engineering side of economics. Research findings in this field have helped governments and practitioners worldwide design better institutions: auctions that are more profitable or efficient; labour markets that improve the match between employees and employers; and better ways to assign students to public schools. The cornerstone of mechanism design is the revelation principle, which provides a canonical class of mechanisms and turns the mechanism-selection problem (which a priori may appear unmanageable) to a constrained optimization problem. The standard mechanism design paradigm relies on three fundamental assumptions: 1. The designer of the institution—the principal—does not have any privileged information. 2. The principal chooses the mechanism and commits to it once and for all. 3. There is no interrelationship of the mechanism with outside markets. In addition, almost the entire mechanism design literature assumes that private information is unverifiable (soft). These assumptions often fail in today’s “big data” world: Firms (online retailers, insurance companies, banks) do have privileged—and often certifiable—information that may affect contractual terms they propose. Also, they interact repeatedly with the same agents and, as they learn about them, they attempt to change the terms by making personalized offers. Finally, often a mechanism—e.g. a government insurance program—interacts with private insurance markets. The proposed research aims at providing methods and foundations to design optimal mechanisms at precisely those highly relevant situations: 1. mechanism-design by an informed principal, 2. design of mechanisms and their transparency when the principal lacks commitment, 3. mechanism-design when an intervention interacts with markets. The latter part of the project aims to employ these cutting-edge tools to revisit the design of insurance markets.
Max ERC Funding
1 644 774 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym HIGEN
Project ADVANCED STATISTICAL METHODS FOR HIGH-DIMENSIONAL GENETIC STUDIES
Researcher (PI) Jonathan Lawrence Marchini
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Country United Kingdom
Call Details Consolidator Grant (CoG), LS2, ERC-2013-CoG
Summary "Statistical methods play a central role in the field of modern genetics. New technologies are driving an explosion of high-dimensional datasets that will sustain a continuing need for new methods, theory and computationally efficient software. My proposal has two parts that will address the statistical challenges and creation of resources at the frontier of the science in this area. The methods development will be driven by, and applied to, several cutting-edge datasets in the fields of human disease genetics, population genetics and plant and animal breeding, guaranteeing impact on exciting scientific questions.
The first part concerns a wide circle of ideas around haplotype estimation, genotype imputation and analysis of sequencing data. The overarching aim is to provide a suite of methods that can estimate haplotypes and impute genotypes in a unified and computationally efficient manner. In addition, we will work to create a reference set of haplotypes from tens of thousands of European and worldwide samples that will form a central resource for human disease and population genetic studies.
The second part concerns the development of models for high-dimensional phenotypic data in genome-wide association studies. This is poorly developed area of human disease genetics with great potential for methods development and wide ranging applications."
Summary
"Statistical methods play a central role in the field of modern genetics. New technologies are driving an explosion of high-dimensional datasets that will sustain a continuing need for new methods, theory and computationally efficient software. My proposal has two parts that will address the statistical challenges and creation of resources at the frontier of the science in this area. The methods development will be driven by, and applied to, several cutting-edge datasets in the fields of human disease genetics, population genetics and plant and animal breeding, guaranteeing impact on exciting scientific questions.
The first part concerns a wide circle of ideas around haplotype estimation, genotype imputation and analysis of sequencing data. The overarching aim is to provide a suite of methods that can estimate haplotypes and impute genotypes in a unified and computationally efficient manner. In addition, we will work to create a reference set of haplotypes from tens of thousands of European and worldwide samples that will form a central resource for human disease and population genetic studies.
The second part concerns the development of models for high-dimensional phenotypic data in genome-wide association studies. This is poorly developed area of human disease genetics with great potential for methods development and wide ranging applications."
Max ERC Funding
1 627 906 €
Duration
Start date: 2014-06-01, End date: 2019-05-31
Project acronym ICLUb
Project Regulation of DNA interstrand crosslink repair by ubiquitin.
Researcher (PI) Helen Walden
Host Institution (HI) UNIVERSITY OF GLASGOW
Country United Kingdom
Call Details Consolidator Grant (CoG), LS1, ERC-2015-CoG
Summary The overall objective of this proposal is to understand, on an atomic level, the mechanism of activation and regulation of the Fanconi Anemia (FA) DNA repair pathway. Homozygous mutations in the FA pathway lead to Fanconi Anemia, a devastating childhood genome instability disorder, typified by bone marrow failure and a high predisposition to cancers. The FA pathway is required for the repair of DNA interstrand crosslinks (ICLs), the hallmark of many cancers and FA. ICL repair is poorly understood on a biophysical and mechanistic level. The FA pathway is regulated by ubiquitin, in a cycle of monoubiquitination and deubiquitination of FANCD2. Despite considerable advances in our understanding of the genetics of the pathway, there is strikingly little known on a mechanistic and chemical level concerning how the ubiquitin signal is assembled, recognised and disassembled. We will define, on an atomic level, the site-specific monoubiquitination and deubiquitination cycle of FANCD2 in its entirety. We will determine the mechanism of FANCD2 monoubiquitination, identify and characterise currently unknown readers of the monoubiquitin signal, define the role of the core complex in the modification of FANCD2, and the requirements for removal of the signal. To tackle this ambitious work we will determine the atomic level three-dimensional structure of key complexes in the modification cycle, and develop a novel method for producing large quantities of stably modified FANCD2. The results of our work will represent a major breakthrough in our knowledge and understanding of the regulation of a critical DNA repair process, will provide a model for understanding mechanisms of monoubiquitination, and will open up both therapeutic potential and new pathways for research into the cause and cure of FA, cancers, and aldehyde-induced liver or bone marrow failure.
Summary
The overall objective of this proposal is to understand, on an atomic level, the mechanism of activation and regulation of the Fanconi Anemia (FA) DNA repair pathway. Homozygous mutations in the FA pathway lead to Fanconi Anemia, a devastating childhood genome instability disorder, typified by bone marrow failure and a high predisposition to cancers. The FA pathway is required for the repair of DNA interstrand crosslinks (ICLs), the hallmark of many cancers and FA. ICL repair is poorly understood on a biophysical and mechanistic level. The FA pathway is regulated by ubiquitin, in a cycle of monoubiquitination and deubiquitination of FANCD2. Despite considerable advances in our understanding of the genetics of the pathway, there is strikingly little known on a mechanistic and chemical level concerning how the ubiquitin signal is assembled, recognised and disassembled. We will define, on an atomic level, the site-specific monoubiquitination and deubiquitination cycle of FANCD2 in its entirety. We will determine the mechanism of FANCD2 monoubiquitination, identify and characterise currently unknown readers of the monoubiquitin signal, define the role of the core complex in the modification of FANCD2, and the requirements for removal of the signal. To tackle this ambitious work we will determine the atomic level three-dimensional structure of key complexes in the modification cycle, and develop a novel method for producing large quantities of stably modified FANCD2. The results of our work will represent a major breakthrough in our knowledge and understanding of the regulation of a critical DNA repair process, will provide a model for understanding mechanisms of monoubiquitination, and will open up both therapeutic potential and new pathways for research into the cause and cure of FA, cancers, and aldehyde-induced liver or bone marrow failure.
Max ERC Funding
1 999 998 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym IdrSeq
Project Discovery and characterization of functional disordered regions and the genes involved in their regulation through next generation sequencing
Researcher (PI) Madanbabu Mohan
Host Institution (HI) UNITED KINGDOM RESEARCH AND INNOVATION
Country United Kingdom
Call Details Consolidator Grant (CoG), LS2, ERC-2015-CoG
Summary A large fraction of any eukaryotic genome (>40%) encodes protein segments that do not adopt a defined tertiary structure. These proteins or regions are called intrinsically disordered proteins/regions (IDPs/IDRs). IDRs are enriched in critical functions such as transcription and signaling, and have been linked with numerous diseases including neurodegeneration and cancer. In contrast to structured regions, the molecular principles behind the sequence-function relationship of IDRs remain poorly understood.
We propose to identify functional IDRs and discover genes that regulate their function using yeast as a cellular model. We will develop and apply a targeted, high-throughput approach called IdrSeq. This technology exploits next generation sequencing to simultaneously assay vast libraries of sequences (~millions) that code for IDRs by coupling IDR sequence (genotype) to a selectable function (phenotype) and identifying functional variants through a selection experiment.
Specifically, using IdrSeq, we aim to identify and characterize IDRs in a cellular context that can
(Aim 1) activate transcription, and discover genes that regulate IDR mediated transcription
(Aim 2) influence protein stability, and discover genes that regulate IDR mediated half-life
(Aim 3) form higher-order assemblies and discover genes that regulate assembly formation
The unique feature of this proposal is its integrative vision of synthetic & systems biology, structural biology, cell biology, genetics, experiments and computation to establish a discovery platform to study IDRs in a cellular context. Since IdrSeq is modular and scalable, it can be readily extended to investigate a broad range of IDR functions, and adapted to other organisms. Elucidating the principles of sequence-function-gene relationship of IDRs holds enormous potential for synthetic biology. The discovery of genes that regulate IDR function has direct implications for human health by revealing novel therapeutic targets.
Summary
A large fraction of any eukaryotic genome (>40%) encodes protein segments that do not adopt a defined tertiary structure. These proteins or regions are called intrinsically disordered proteins/regions (IDPs/IDRs). IDRs are enriched in critical functions such as transcription and signaling, and have been linked with numerous diseases including neurodegeneration and cancer. In contrast to structured regions, the molecular principles behind the sequence-function relationship of IDRs remain poorly understood.
We propose to identify functional IDRs and discover genes that regulate their function using yeast as a cellular model. We will develop and apply a targeted, high-throughput approach called IdrSeq. This technology exploits next generation sequencing to simultaneously assay vast libraries of sequences (~millions) that code for IDRs by coupling IDR sequence (genotype) to a selectable function (phenotype) and identifying functional variants through a selection experiment.
Specifically, using IdrSeq, we aim to identify and characterize IDRs in a cellular context that can
(Aim 1) activate transcription, and discover genes that regulate IDR mediated transcription
(Aim 2) influence protein stability, and discover genes that regulate IDR mediated half-life
(Aim 3) form higher-order assemblies and discover genes that regulate assembly formation
The unique feature of this proposal is its integrative vision of synthetic & systems biology, structural biology, cell biology, genetics, experiments and computation to establish a discovery platform to study IDRs in a cellular context. Since IdrSeq is modular and scalable, it can be readily extended to investigate a broad range of IDR functions, and adapted to other organisms. Elucidating the principles of sequence-function-gene relationship of IDRs holds enormous potential for synthetic biology. The discovery of genes that regulate IDR function has direct implications for human health by revealing novel therapeutic targets.
Max ERC Funding
1 998 126 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
