Publication

Spatial areas of genotype probability: Predicting the spatial distribution of adaptive genetic variants under future climatic conditions

Abstract

In a context of rapid global change, one of the key components for the survival of species is their genetic evolutionary potential for adaptation. Many methods have been developed to identify genetic variants underpinning adaptation to climate, but few tools were made available to integrate this knowledge into conservation management. We present here the SPatial Areas of Genotype probability (SPAG), a method to transpose the results of genotype-environment association studies into an evolutionary potential spatial prediction framework. We define a univariate model predicting the spatial distribution of a single-locus adaptive genotype and three multivariate models allowing the integration of several adaptive loci in a composite genotype. Unlike existing methods, SPAGs provide (a) a flexible approach to combine loci under different types of intergenic relationships and (b) a cross-validation framework to assess the pertinence of evolutionary potential predictions. SPAGs can be integrated with climate change projections to forecast the future spatial distribution of genotypes. The analysis of the mismatch between current and future SPAGs ("genomic offset") makes it possible to identify vulnerable populations potentially lacking the adaptive genotypes necessary for future survival. We tested the SPAG approach on a simulated population and applied it to characterize the evolutionary potential of 161 Moroccan goats to bioclimatic conditions. We identified seven regions of the Moroccan goat genome strongly associated with the precipitation seasonality and used the SPAG approach to predict the evolutionary potential. We then forecasted the shift in SPAGs under a strong climate change scenario and uncovered the goat populations likely to be threatened in future conditions. The SPAG methodology is an efficient and flexible tool to characterize the evolutionary potential across a landscape and to transpose evolutionary information into conservation frameworks.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Related concepts (41)
Climate change
In common usage, climate change describes global warming—the ongoing increase in global average temperature—and its effects on Earth's climate system. Climate change in a broader sense also includes previous long-term changes to Earth's climate. The current rise in global average temperature is more rapid than previous changes, and is primarily caused by humans burning fossil fuels. Fossil fuel use, deforestation, and some agricultural and industrial practices increase greenhouse gases, notably carbon dioxide and methane.
Adaptation
In biology, adaptation has three related meanings. Firstly, it is the dynamic evolutionary process of natural selection that fits organisms to their environment, enhancing their evolutionary fitness. Secondly, it is a state reached by the population during that process. Thirdly, it is a phenotypic trait or adaptive trait, with a functional role in each individual organism, that is maintained and has evolved through natural selection. Historically, adaptation has been described from the time of the ancient Greek philosophers such as Empedocles and Aristotle.
Evolvability
Evolvability is defined as the capacity of a system for adaptive evolution. Evolvability is the ability of a population of organisms to not merely generate genetic diversity, but to generate adaptive genetic diversity, and thereby evolve through natural selection. In order for a biological organism to evolve by natural selection, there must be a certain minimum probability that new, heritable variants are beneficial. Random mutations, unless they occur in DNA sequences with no function, are expected to be mostly detrimental.
Show more
Related publications (50)

Influence of future climate scenarios on the sizing of Building-Integrated Photovoltaics (BIPV) installations. Case study of a new research-center building in Switzerland

Sergi Aguacil Moreno

This paper analyzes the findings obtained when applying a multi-criteria performance-based method for sizing a BIPV installation considering different weather files, representing historical data (TMY; typical meteorological year) and prospective data (thre ...
2023

Environment-dependent epistasis increases phenotypic diversity in gene regulatory networks

Florence Gauye, Florian Baier

Mutations to gene regulatory networks can be maladaptive or a source of evolutionary novelty. Epistasis con-founds our understanding of how mutations affect the expression patterns of gene regulatory networks, a chal-lenge exacerbated by the dependence of ...
AMER ASSOC ADVANCEMENT SCIENCE2023

Clean air policies are key for successfully mitigating Arctic warming

Julia Schmale, Luca Pozzoli

A tighter integration of modeling frameworks for climate and air quality is urgently needed to assess the impacts of clean air policies on future Arctic and global climate. We combined a new model emulator and comprehensive emissions scenarios for air poll ...
2022
Show more
Related MOOCs (10)
Traitements et Applications en Télédétection
Ce cours s’adresse aux étudiants et professionnels qui ont recours aux données de télédétection pour la réalisation de projets d’aménagement, de construction, de gestion de l’environnement, de transpo
Geographical Information Systems 1
Organisé en deux parties, ce cours présente les bases théoriques et pratiques des systèmes d’information géographique, ne nécessitant pas de connaissances préalables en informatique. En suivant cette
Geographical Information Systems 1
Organisé en deux parties, ce cours présente les bases théoriques et pratiques des systèmes d’information géographique, ne nécessitant pas de connaissances préalables en informatique. En suivant cette
Show more

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.