Project acronym 2SEXES_1GENOME
Project Sex-specific genetic effects on fitness and human disease
Researcher (PI) Edward Hugh Morrow
Host Institution (HI) THE UNIVERSITY OF SUSSEX
Call Details Starting Grant (StG), LS8, ERC-2011-StG_20101109
Summary Darwin’s theory of natural selection rests on the principle that fitness variation in natural populations has a heritable component, on which selection acts, thereby leading to evolutionary change. A fundamental and so far unresolved question for the field of evolutionary biology is to identify the genetic loci responsible for this fitness variation, thereby coming closer to an understanding of how variation is maintained in the face of continual selection. One important complicating factor in the search for fitness related genes however is the existence of separate sexes – theoretical expectations and empirical data both suggest that sexually antagonistic genes are common. The phrase “two sexes, one genome” nicely sums up the problem; selection may favour alleles in one sex, even if they have detrimental effects on the fitness of the opposite sex, since it is their net effect across both sexes that determine the likelihood that alleles persist in a population. This theoretical framework raises an interesting, and so far entirely unexplored issue: that in one sex the functional performance of some alleles is predicted to be compromised and this effect may account for some common human diseases and conditions which show genotype-sex interactions. I propose to explore the genetic basis of sex-specific fitness in a model organism in both laboratory and natural conditions and to test whether those genes identified as having sexually antagonistic effects can help explain the incidence of human diseases that display sexual dimorphism in prevalence, age of onset or severity. This multidisciplinary project directly addresses some fundamental unresolved questions in evolutionary biology: the genetic basis and maintenance of fitness variation; the evolution of sexual dimorphism; and aims to provide novel insights into the genetic basis of some common human diseases.
Summary
Darwin’s theory of natural selection rests on the principle that fitness variation in natural populations has a heritable component, on which selection acts, thereby leading to evolutionary change. A fundamental and so far unresolved question for the field of evolutionary biology is to identify the genetic loci responsible for this fitness variation, thereby coming closer to an understanding of how variation is maintained in the face of continual selection. One important complicating factor in the search for fitness related genes however is the existence of separate sexes – theoretical expectations and empirical data both suggest that sexually antagonistic genes are common. The phrase “two sexes, one genome” nicely sums up the problem; selection may favour alleles in one sex, even if they have detrimental effects on the fitness of the opposite sex, since it is their net effect across both sexes that determine the likelihood that alleles persist in a population. This theoretical framework raises an interesting, and so far entirely unexplored issue: that in one sex the functional performance of some alleles is predicted to be compromised and this effect may account for some common human diseases and conditions which show genotype-sex interactions. I propose to explore the genetic basis of sex-specific fitness in a model organism in both laboratory and natural conditions and to test whether those genes identified as having sexually antagonistic effects can help explain the incidence of human diseases that display sexual dimorphism in prevalence, age of onset or severity. This multidisciplinary project directly addresses some fundamental unresolved questions in evolutionary biology: the genetic basis and maintenance of fitness variation; the evolution of sexual dimorphism; and aims to provide novel insights into the genetic basis of some common human diseases.
Max ERC Funding
1 500 000 €
Duration
Start date: 2012-01-01, End date: 2016-12-31
Project acronym 321
Project from Cubic To Linear complexity in computational electromagnetics
Researcher (PI) Francesco Paolo ANDRIULLI
Host Institution (HI) POLITECNICO DI TORINO
Call Details Consolidator Grant (CoG), PE7, ERC-2016-COG
Summary Computational Electromagnetics (CEM) is the scientific field at the origin of all new modeling and simulation tools required by the constantly arising design challenges of emerging and future technologies in applied electromagnetics. As in many other technological fields, however, the trend in all emerging technologies in electromagnetic engineering is going towards miniaturized, higher density and multi-scale scenarios. Computationally speaking this translates in the steep increase of the number of degrees of freedom. Given that the design cost (the cost of a multi-right-hand side problem dominated by matrix inversion) can scale as badly as cubically with these degrees of freedom, this fact, as pointed out by many, will sensibly compromise the practical impact of CEM on future and emerging technologies.
For this reason, the CEM scientific community has been looking for years for a FFT-like paradigm shift: a dynamic fast direct solver providing a design cost that would scale only linearly with the degrees of freedom. Such a fast solver is considered today a Holy Grail of the discipline.
The Grand Challenge of 321 will be to tackle this Holy Grail in Computational Electromagnetics by investigating a dynamic Fast Direct Solver for Maxwell Problems that would run in a linear-instead-of-cubic complexity for an arbitrary number and configuration of degrees of freedom.
The failure of all previous attempts will be overcome by a game-changing transformation of the CEM classical problem that will leverage on a recent breakthrough of the PI. Starting from this, the project will investigate an entire new paradigm for impacting algorithms to achieve this grand challenge.
The impact of the FFT’s quadratic-to-linear paradigm shift shows how computational complexity reductions can be groundbreaking on applications. The cubic-to-linear paradigm shift, which the 321 project will aim for, will have such a rupturing impact on electromagnetic science and technology.
Summary
Computational Electromagnetics (CEM) is the scientific field at the origin of all new modeling and simulation tools required by the constantly arising design challenges of emerging and future technologies in applied electromagnetics. As in many other technological fields, however, the trend in all emerging technologies in electromagnetic engineering is going towards miniaturized, higher density and multi-scale scenarios. Computationally speaking this translates in the steep increase of the number of degrees of freedom. Given that the design cost (the cost of a multi-right-hand side problem dominated by matrix inversion) can scale as badly as cubically with these degrees of freedom, this fact, as pointed out by many, will sensibly compromise the practical impact of CEM on future and emerging technologies.
For this reason, the CEM scientific community has been looking for years for a FFT-like paradigm shift: a dynamic fast direct solver providing a design cost that would scale only linearly with the degrees of freedom. Such a fast solver is considered today a Holy Grail of the discipline.
The Grand Challenge of 321 will be to tackle this Holy Grail in Computational Electromagnetics by investigating a dynamic Fast Direct Solver for Maxwell Problems that would run in a linear-instead-of-cubic complexity for an arbitrary number and configuration of degrees of freedom.
The failure of all previous attempts will be overcome by a game-changing transformation of the CEM classical problem that will leverage on a recent breakthrough of the PI. Starting from this, the project will investigate an entire new paradigm for impacting algorithms to achieve this grand challenge.
The impact of the FFT’s quadratic-to-linear paradigm shift shows how computational complexity reductions can be groundbreaking on applications. The cubic-to-linear paradigm shift, which the 321 project will aim for, will have such a rupturing impact on electromagnetic science and technology.
Max ERC Funding
2 000 000 €
Duration
Start date: 2017-09-01, End date: 2022-08-31
Project acronym 4D-EEG
Project 4D-EEG: A new tool to investigate the spatial and temporal activity patterns in the brain
Researcher (PI) Franciscus C.T. Van Der Helm
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Call Details Advanced Grant (AdG), PE7, ERC-2011-ADG_20110209
Summary Our first goal is to develop a new tool to determine brain activity with a high temporal (< 1 msec) and spatial (about 2 mm) resolution with the focus on motor control. High density EEG (up to 256 electrodes) will be used for EEG source localization. Advanced force-controlled robot manipulators will be used to impose continuous force perturbations to the joints. Advanced closed-loop system identification algorithms will identify the dynamic EEG response of multiple brain areas to the perturbation, leading to a functional interpretation of EEG. The propagation of the signal in time and 3D space through the cortex can be monitored: 4D-EEG. Preliminary experiments with EEG localization have shown that the continuous force perturbations resulted in a better signal-to-noise ratio and coherence than the current method using transient perturbations..
4D-EEG will be a direct measure of the neural activity in the brain with an excellent temporal response and easy to use in combination with motor control tasks. The new 4D-EEG method is expected to provide a breakthrough in comparison to functional MRI (fMRI) when elucidating the meaning of cortical map plasticity in motor learning.
Our second goal is to generate and validate new hypotheses about the longitudinal relationship between motor learning and cortical map plasticity by clinically using 4D-EEG in an intensive, repeated measurement design in patients suffering from a stroke. The application of 4D-EEG combined with haptic robots will allow us to discover how dynamics in cortical map plasticity are related with upper limb recovery after stroke in terms of neural repair and using behavioral compensation strategies while performing a meaningful motor tasks.. The non-invasive 4D-EEG technique combined with haptic robots will open the window about what and how patients (re)learn when showing motor recovery after stroke in order to allow us to develop more effective patient-tailored therapies in neuro-rehabilitation.
Summary
Our first goal is to develop a new tool to determine brain activity with a high temporal (< 1 msec) and spatial (about 2 mm) resolution with the focus on motor control. High density EEG (up to 256 electrodes) will be used for EEG source localization. Advanced force-controlled robot manipulators will be used to impose continuous force perturbations to the joints. Advanced closed-loop system identification algorithms will identify the dynamic EEG response of multiple brain areas to the perturbation, leading to a functional interpretation of EEG. The propagation of the signal in time and 3D space through the cortex can be monitored: 4D-EEG. Preliminary experiments with EEG localization have shown that the continuous force perturbations resulted in a better signal-to-noise ratio and coherence than the current method using transient perturbations..
4D-EEG will be a direct measure of the neural activity in the brain with an excellent temporal response and easy to use in combination with motor control tasks. The new 4D-EEG method is expected to provide a breakthrough in comparison to functional MRI (fMRI) when elucidating the meaning of cortical map plasticity in motor learning.
Our second goal is to generate and validate new hypotheses about the longitudinal relationship between motor learning and cortical map plasticity by clinically using 4D-EEG in an intensive, repeated measurement design in patients suffering from a stroke. The application of 4D-EEG combined with haptic robots will allow us to discover how dynamics in cortical map plasticity are related with upper limb recovery after stroke in terms of neural repair and using behavioral compensation strategies while performing a meaningful motor tasks.. The non-invasive 4D-EEG technique combined with haptic robots will open the window about what and how patients (re)learn when showing motor recovery after stroke in order to allow us to develop more effective patient-tailored therapies in neuro-rehabilitation.
Max ERC Funding
3 477 202 €
Duration
Start date: 2012-06-01, End date: 2017-05-31
Project acronym A-DATADRIVE-B
Project Advanced Data-Driven Black-box modelling
Researcher (PI) Johan Adelia K Suykens
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Advanced Grant (AdG), PE7, ERC-2011-ADG_20110209
Summary Making accurate predictions is a crucial factor in many systems (such as in modelling energy consumption, power load forecasting, traffic networks, process industry, environmental modelling, biomedicine, brain-machine interfaces) for cost savings, efficiency, health, safety and organizational purposes. In this proposal we aim at realizing a new generation of more advanced black-box modelling techniques for estimating predictive models from measured data. We will study different optimization modelling frameworks in order to obtain improved black-box modelling approaches. This will be done by specifying models through constrained optimization problems by studying different candidate core models (parametric models, support vector machines and kernel methods) together with additional sets of constraints and regularization mechanisms. Different candidate mathematical frameworks will be considered with models that possess primal and (Lagrange) dual model representations, functional analysis in reproducing kernel Hilbert spaces, operator splitting and optimization in Banach spaces. Several aspects that are relevant to black-box models will be studied including incorporation of prior knowledge, structured dynamical systems, tensorial data representations, interpretability and sparsity, and general purpose optimization algorithms. The methods should be suitable for handling larger data sets and high dimensional input spaces. The final goal is also to realize a next generation software tool (including symbolic generation of models and handling different supervised and unsupervised learning tasks, static and dynamic systems) that can be generically applied to data from different application areas. The proposal A-DATADRIVE-B aims at getting end-users connected to the more advanced methods through a user-friendly data-driven black-box modelling tool. The methods and tool will be tested in connection to several real-life applications.
Summary
Making accurate predictions is a crucial factor in many systems (such as in modelling energy consumption, power load forecasting, traffic networks, process industry, environmental modelling, biomedicine, brain-machine interfaces) for cost savings, efficiency, health, safety and organizational purposes. In this proposal we aim at realizing a new generation of more advanced black-box modelling techniques for estimating predictive models from measured data. We will study different optimization modelling frameworks in order to obtain improved black-box modelling approaches. This will be done by specifying models through constrained optimization problems by studying different candidate core models (parametric models, support vector machines and kernel methods) together with additional sets of constraints and regularization mechanisms. Different candidate mathematical frameworks will be considered with models that possess primal and (Lagrange) dual model representations, functional analysis in reproducing kernel Hilbert spaces, operator splitting and optimization in Banach spaces. Several aspects that are relevant to black-box models will be studied including incorporation of prior knowledge, structured dynamical systems, tensorial data representations, interpretability and sparsity, and general purpose optimization algorithms. The methods should be suitable for handling larger data sets and high dimensional input spaces. The final goal is also to realize a next generation software tool (including symbolic generation of models and handling different supervised and unsupervised learning tasks, static and dynamic systems) that can be generically applied to data from different application areas. The proposal A-DATADRIVE-B aims at getting end-users connected to the more advanced methods through a user-friendly data-driven black-box modelling tool. The methods and tool will be tested in connection to several real-life applications.
Max ERC Funding
2 485 800 €
Duration
Start date: 2012-04-01, End date: 2017-03-31
Project acronym AAATSI
Project Advanced Antenna Architecture for THZ Sensing Instruments
Researcher (PI) Andrea Neto
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Call Details Starting Grant (StG), PE7, ERC-2011-StG_20101014
Summary The Tera-Hertz portion of the spectrum presents unique potentials for advanced applications. Currently the THz spectrum is revealing the mechanisms at the origin of our universe and provides the means to monitor the health of our planet via satellite based sensing of critical gases. Potentially time domain sensing of the THz spectrum will be the ideal tool for a vast variety of medical and security applications.
Presently, systems in the THz regime are extremely expensive and consequently the THz spectrum is still the domain of only niche (expensive) scientific applications. The main problems are the lack of power and sensitivity. The wide unused THz spectral bandwidth is, herself, the only widely available resource that in the future can compensate for these problems. But, so far, when scientists try to really use the bandwidth, they run into an insurmountable physical limit: antenna dispersion. Antenna dispersion modifies the signal’s spectrum in a wavelength dependent manner in all types of radiation, but is particularly deleterious to THz signals because the spectrum is too wide and with foreseeable technology it cannot be digitized.
The goal of this proposal is to introduce break-through antenna technology that will eliminate the dispersion bottle neck and revolutionize Time Domain sensing and Spectroscopic Space Science. Achieving these goals the project will pole vault THz imaging technology into the 21-th century and develop critically important enabling technologies which will satisfy the electrical engineering needs of the next 30 years and in the long run will enable multi Tera-bit wireless communications.
In order to achieve these goals, I will first build upon two major breakthrough radiation mechanisms that I pioneered: Leaky Lenses and Connected Arrays. Eventually, ultra wide band imaging arrays constituted by thousands of components will be designed on the bases of the new theoretical findings and demonstrated.
Summary
The Tera-Hertz portion of the spectrum presents unique potentials for advanced applications. Currently the THz spectrum is revealing the mechanisms at the origin of our universe and provides the means to monitor the health of our planet via satellite based sensing of critical gases. Potentially time domain sensing of the THz spectrum will be the ideal tool for a vast variety of medical and security applications.
Presently, systems in the THz regime are extremely expensive and consequently the THz spectrum is still the domain of only niche (expensive) scientific applications. The main problems are the lack of power and sensitivity. The wide unused THz spectral bandwidth is, herself, the only widely available resource that in the future can compensate for these problems. But, so far, when scientists try to really use the bandwidth, they run into an insurmountable physical limit: antenna dispersion. Antenna dispersion modifies the signal’s spectrum in a wavelength dependent manner in all types of radiation, but is particularly deleterious to THz signals because the spectrum is too wide and with foreseeable technology it cannot be digitized.
The goal of this proposal is to introduce break-through antenna technology that will eliminate the dispersion bottle neck and revolutionize Time Domain sensing and Spectroscopic Space Science. Achieving these goals the project will pole vault THz imaging technology into the 21-th century and develop critically important enabling technologies which will satisfy the electrical engineering needs of the next 30 years and in the long run will enable multi Tera-bit wireless communications.
In order to achieve these goals, I will first build upon two major breakthrough radiation mechanisms that I pioneered: Leaky Lenses and Connected Arrays. Eventually, ultra wide band imaging arrays constituted by thousands of components will be designed on the bases of the new theoretical findings and demonstrated.
Max ERC Funding
1 499 487 €
Duration
Start date: 2011-11-01, End date: 2017-10-31
Project acronym ABYSS
Project ABYSS - Assessment of bacterial life and matter cycling in deep-sea surface sediments
Researcher (PI) Antje Boetius
Host Institution (HI) ALFRED-WEGENER-INSTITUT HELMHOLTZ-ZENTRUM FUR POLAR- UND MEERESFORSCHUNG
Call Details Advanced Grant (AdG), LS8, ERC-2011-ADG_20110310
Summary The deep-sea floor hosts a distinct microbial biome covering 67% of the Earth’s surface, characterized by cold temperatures, permanent darkness, high pressure and food limitation. The surface sediments are dominated by bacteria, with on average a billion cells per ml. Benthic bacteria are highly relevant to the Earth’s element cycles as they remineralize most of the organic matter sinking from the productive surface ocean, and return nutrients, thereby promoting ocean primary production. What passes the bacterial filter is a relevant sink for carbon on geological time scales, influencing global oxygen and carbon budgets, and fueling the deep subsurface biosphere. Despite the relevance of deep-sea sediment bacteria to climate, geochemical cycles and ecology of the seafloor, their genetic and functional diversity, niche differentiation and biological interactions remain unknown. Our preliminary work in a global survey of deep-sea sediments enables us now to target specific genes for the quantification of abyssal bacteria. We can trace isotope-labeled elements into communities and single cells, and analyze the molecular alteration of organic matter during microbial degradation, all in context with environmental dynamics recorded at the only long-term deep-sea ecosystem observatory in the Arctic that we maintain. I propose to bridge biogeochemistry, ecology, microbiology and marine biology to develop a systematic understanding of abyssal sediment bacterial community distribution, diversity, function and interactions, by combining in situ flux studies and different visualization techniques with a wide range of molecular tools. Substantial progress is expected in understanding I) identity and function of the dominant types of indigenous benthic bacteria, II) dynamics in bacterial activity and diversity caused by variations in particle flux, III) interactions with different types and ages of organic matter, and other biological factors.
Summary
The deep-sea floor hosts a distinct microbial biome covering 67% of the Earth’s surface, characterized by cold temperatures, permanent darkness, high pressure and food limitation. The surface sediments are dominated by bacteria, with on average a billion cells per ml. Benthic bacteria are highly relevant to the Earth’s element cycles as they remineralize most of the organic matter sinking from the productive surface ocean, and return nutrients, thereby promoting ocean primary production. What passes the bacterial filter is a relevant sink for carbon on geological time scales, influencing global oxygen and carbon budgets, and fueling the deep subsurface biosphere. Despite the relevance of deep-sea sediment bacteria to climate, geochemical cycles and ecology of the seafloor, their genetic and functional diversity, niche differentiation and biological interactions remain unknown. Our preliminary work in a global survey of deep-sea sediments enables us now to target specific genes for the quantification of abyssal bacteria. We can trace isotope-labeled elements into communities and single cells, and analyze the molecular alteration of organic matter during microbial degradation, all in context with environmental dynamics recorded at the only long-term deep-sea ecosystem observatory in the Arctic that we maintain. I propose to bridge biogeochemistry, ecology, microbiology and marine biology to develop a systematic understanding of abyssal sediment bacterial community distribution, diversity, function and interactions, by combining in situ flux studies and different visualization techniques with a wide range of molecular tools. Substantial progress is expected in understanding I) identity and function of the dominant types of indigenous benthic bacteria, II) dynamics in bacterial activity and diversity caused by variations in particle flux, III) interactions with different types and ages of organic matter, and other biological factors.
Max ERC Funding
3 375 693 €
Duration
Start date: 2012-06-01, End date: 2018-05-31
Project acronym ACrossWire
Project A Cross-Correlated Approach to Engineering Nitride Nanowires
Researcher (PI) Hannah Jane JOYCE
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Call Details Starting Grant (StG), PE7, ERC-2016-STG
Summary Nanowires based on group III–nitride semiconductors exhibit outstanding potential for emerging applications in energy-efficient lighting, optoelectronics and solar energy harvesting. Nitride nanowires, tailored at the nanoscale, should overcome many of the challenges facing conventional planar nitride materials, and also add extraordinary new functionality to these materials. However, progress towards III–nitride nanowire devices has been hampered by the challenges in quantifying nanowire electrical properties using conventional contact-based measurements. Without reliable electrical transport data, it is extremely difficult to optimise nanowire growth and device design. This project aims to overcome this problem through an unconventional approach: advanced contact-free electrical measurements. Contact-free measurements, growth studies, and device studies will be cross-correlated to provide unprecedented insight into the growth mechanisms that govern nanowire electronic properties and ultimately dictate device performance. A key contact-free technique at the heart of this proposal is ultrafast terahertz conductivity spectroscopy: an advanced technique ideal for probing nanowire electrical properties. We will develop new methods to enable the full suite of contact-free (including terahertz, photoluminescence and cathodoluminescence measurements) and contact-based measurements to be performed with high spatial resolution on the same nanowires. This will provide accurate, comprehensive and cross-correlated feedback to guide growth studies and expedite the targeted development of nanowires with specified functionality. We will apply this powerful approach to tailor nanowires as photoelectrodes for solar photoelectrochemical water splitting. This is an application for which nitride nanowires have outstanding, yet unfulfilled, potential. This project will thus harness the true potential of nitride nanowires and bring them to the forefront of 21st century technology.
Summary
Nanowires based on group III–nitride semiconductors exhibit outstanding potential for emerging applications in energy-efficient lighting, optoelectronics and solar energy harvesting. Nitride nanowires, tailored at the nanoscale, should overcome many of the challenges facing conventional planar nitride materials, and also add extraordinary new functionality to these materials. However, progress towards III–nitride nanowire devices has been hampered by the challenges in quantifying nanowire electrical properties using conventional contact-based measurements. Without reliable electrical transport data, it is extremely difficult to optimise nanowire growth and device design. This project aims to overcome this problem through an unconventional approach: advanced contact-free electrical measurements. Contact-free measurements, growth studies, and device studies will be cross-correlated to provide unprecedented insight into the growth mechanisms that govern nanowire electronic properties and ultimately dictate device performance. A key contact-free technique at the heart of this proposal is ultrafast terahertz conductivity spectroscopy: an advanced technique ideal for probing nanowire electrical properties. We will develop new methods to enable the full suite of contact-free (including terahertz, photoluminescence and cathodoluminescence measurements) and contact-based measurements to be performed with high spatial resolution on the same nanowires. This will provide accurate, comprehensive and cross-correlated feedback to guide growth studies and expedite the targeted development of nanowires with specified functionality. We will apply this powerful approach to tailor nanowires as photoelectrodes for solar photoelectrochemical water splitting. This is an application for which nitride nanowires have outstanding, yet unfulfilled, potential. This project will thus harness the true potential of nitride nanowires and bring them to the forefront of 21st century technology.
Max ERC Funding
1 499 195 €
Duration
Start date: 2017-04-01, End date: 2022-03-31
Project acronym ADaPTIVE
Project Analysing Diversity with a Phenomic approach: Trends in Vertebrate Evolution
Researcher (PI) Anjali Goswami
Host Institution (HI) NATURAL HISTORY MUSEUM
Call Details Starting Grant (StG), LS8, ERC-2014-STG
Summary What processes shape vertebrate diversity through deep time? Approaches to this question can focus on many different factors, from life history and ecology to large-scale environmental change and extinction. To date, the majority of studies on the evolution of vertebrate diversity have focused on relatively simple metrics, specifically taxon counts or univariate measures, such as body size. However, multivariate morphological data provides a more complete picture of evolutionary and palaeoecological change. Morphological data can also bridge deep-time palaeobiological analyses with studies of the genetic and developmental factors that shape variation and must also influence large-scale patterns of evolutionary change. Thus, accurately reconstructing the patterns and processes underlying evolution requires an approach that can fully represent an organism’s phenome, the sum total of their observable traits.
Recent advances in imaging and data analysis allow large-scale study of phenomic evolution. In this project, I propose to quantitatively analyse the deep-time evolutionary diversity of tetrapods (amphibians, reptiles, birds, and mammals). Specifically, I will apply and extend new imaging, morphometric, and analytical tools to construct a multivariate phenomic dataset for living and extinct tetrapods from 3-D scans. I will use these data to rigorously compare extinction selectivity, timing, pace, and shape of adaptive radiations, and ecomorphological response to large-scale climatic shifts across all tetrapod clades. To do so, I will quantify morphological diversity (disparity) and rates of evolution spanning over 300 million years of tetrapod history. I will further analyse the evolution of phenotypic integration by quantifying not just the traits themselves, but changes in the relationships among traits, which reflect the genetic, developmental, and functional interactions that shape variation, the raw material for natural selection.
Summary
What processes shape vertebrate diversity through deep time? Approaches to this question can focus on many different factors, from life history and ecology to large-scale environmental change and extinction. To date, the majority of studies on the evolution of vertebrate diversity have focused on relatively simple metrics, specifically taxon counts or univariate measures, such as body size. However, multivariate morphological data provides a more complete picture of evolutionary and palaeoecological change. Morphological data can also bridge deep-time palaeobiological analyses with studies of the genetic and developmental factors that shape variation and must also influence large-scale patterns of evolutionary change. Thus, accurately reconstructing the patterns and processes underlying evolution requires an approach that can fully represent an organism’s phenome, the sum total of their observable traits.
Recent advances in imaging and data analysis allow large-scale study of phenomic evolution. In this project, I propose to quantitatively analyse the deep-time evolutionary diversity of tetrapods (amphibians, reptiles, birds, and mammals). Specifically, I will apply and extend new imaging, morphometric, and analytical tools to construct a multivariate phenomic dataset for living and extinct tetrapods from 3-D scans. I will use these data to rigorously compare extinction selectivity, timing, pace, and shape of adaptive radiations, and ecomorphological response to large-scale climatic shifts across all tetrapod clades. To do so, I will quantify morphological diversity (disparity) and rates of evolution spanning over 300 million years of tetrapod history. I will further analyse the evolution of phenotypic integration by quantifying not just the traits themselves, but changes in the relationships among traits, which reflect the genetic, developmental, and functional interactions that shape variation, the raw material for natural selection.
Max ERC Funding
1 482 818 €
Duration
Start date: 2015-06-01, End date: 2020-05-31
Project acronym AdaptoSCOPE
Project Using cis-regulatory mutations to highlight polygenic adaptation in natural plant systems
Researcher (PI) Juliette de Meaux
Host Institution (HI) UNIVERSITAET ZU KOELN
Call Details Consolidator Grant (CoG), LS8, ERC-2014-CoG
Summary 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.
Summary
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.
Max ERC Funding
1 683 120 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
Project acronym AGNOSTIC
Project Actively Enhanced Cognition based Framework for Design of Complex Systems
Researcher (PI) Björn Ottersten
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Call Details Advanced Grant (AdG), PE7, ERC-2016-ADG
Summary Parameterized mathematical models have been central to the understanding and design of communication, networking, and radar systems. However, they often lack the ability to model intricate interactions innate in complex systems. On the other hand, data-driven approaches do not need explicit mathematical models for data generation and have a wider applicability at the cost of flexibility. These approaches need labelled data, representing all the facets of the system interaction with the environment. With the aforementioned systems becoming increasingly complex with intricate interactions and operating in dynamic environments, the number of system configurations can be rather large leading to paucity of labelled data. Thus there are emerging networks of systems of critical importance whose cognition is not effectively covered by traditional approaches. AGNOSTIC uses the process of exploration through system probing and exploitation of observed data in an iterative manner drawing upon traditional model-based approaches and data-driven discriminative learning to enhance functionality, performance, and robustness through the notion of active cognition. AGNOSTIC clearly departs from a passive assimilation of data and aims to formalize the exploitation/exploration framework in dynamic environments. The development of this framework in three applications areas is central to AGNOSTIC. The project aims to provide active cognition in radar to learn the environment and other active systems to ensure situational awareness and coexistence; to apply active probing in radio access networks to infer network behaviour towards spectrum sharing and self-configuration; and to learn and adapt to user demand for content distribution in caching networks, drastically improving network efficiency. Although these cognitive systems interact with the environment in very different ways, sufficient abstraction allows cross-fertilization of insights and approaches motivating their joint treatment.
Summary
Parameterized mathematical models have been central to the understanding and design of communication, networking, and radar systems. However, they often lack the ability to model intricate interactions innate in complex systems. On the other hand, data-driven approaches do not need explicit mathematical models for data generation and have a wider applicability at the cost of flexibility. These approaches need labelled data, representing all the facets of the system interaction with the environment. With the aforementioned systems becoming increasingly complex with intricate interactions and operating in dynamic environments, the number of system configurations can be rather large leading to paucity of labelled data. Thus there are emerging networks of systems of critical importance whose cognition is not effectively covered by traditional approaches. AGNOSTIC uses the process of exploration through system probing and exploitation of observed data in an iterative manner drawing upon traditional model-based approaches and data-driven discriminative learning to enhance functionality, performance, and robustness through the notion of active cognition. AGNOSTIC clearly departs from a passive assimilation of data and aims to formalize the exploitation/exploration framework in dynamic environments. The development of this framework in three applications areas is central to AGNOSTIC. The project aims to provide active cognition in radar to learn the environment and other active systems to ensure situational awareness and coexistence; to apply active probing in radio access networks to infer network behaviour towards spectrum sharing and self-configuration; and to learn and adapt to user demand for content distribution in caching networks, drastically improving network efficiency. Although these cognitive systems interact with the environment in very different ways, sufficient abstraction allows cross-fertilization of insights and approaches motivating their joint treatment.
Max ERC Funding
2 499 595 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
