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ANGI

Financiado

Adaptive significance of Non Genetic Inheritance

Our ability to predict adaptation and the response of populations to selection is limited. Solving this issue is a fundamental challenge of evolutionary ecology with implications for applied sciences such as conservation, and agro... ver más

28/02/2022

CNRS

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2022-02-28

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

ERC-CoG-2015: ERC Consolidator Grant

I+D

Cerrada hace 9 años

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2 Participantes

CNRS

2.00M€ | Lider

TECNICA FORESTAL MECANIZADA

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Últimas noticias

29-11-2024: IDAE En las últimas 48 horas el Organismo IDAE ha otorgado 4 concesiones

29-11-2024: ECE En las últimas 48 horas el Organismo ECE ha otorgado 2 concesiones

29-11-2024: CMVAMADRID En las últimas 48 horas el Organismo CMVAMADRID ha otorgado 37 concesiones

Duración del proyecto: 72 meses Fecha Inicio: 2016-02-24
Fecha Fin: 2022-02-28

Presupuesto del proyecto 2M€

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

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