Research topics

The topic that has always fascinated me is how organisms adapt to climate. I am particularly interested in experimental ecology and population genomics. On one hand, ecology looks for general patterns of species traits associated to climate. On the other hand, genetics provides insights on the molecular basis of ecologically relevant traits and sets the statistical framework to study the interplay of evolutionary forces: migration, drift, mutation, and selection. It is in the intersection of ecology x genetics x bioinformatics, where cool stuff happens!

The annual, cosmopolitan, and self-fertilizing plant Arabidopsis thaliana, from which 1001 genomes have been recently produced (1001 Genomes Consortium, 2016 CELL), is a formidable model system to understand how environmental selective forces shape species diversity. And it is my favorite model system. Below are short descriptions of my ongoing projects.

Evolution of a newly colonizing plant lineage


Exposito-Alonso &  Becker et al. (2017) The rate and effect of de novo mutations in a colonizing lineage of Arabidopsis thalianaPLOS Genetics, doi:

Scenarios of low complex evolutionary history can help to characterize and understand the essential processes of evolution. We have been able to sequence multiple individuals from a single North American Arabidopsis thaliana lineage, including historical DNA from herbarium speciments collected as far back as 1864. Leveraging this lineage, which likely was originated from a single colonization event from Eurasia, we directly quantified the speed at which diversity is generated by de novo mutations and learned about the equilibria with population size and natural selection. We discovered that the dynamics were dominated by multiple bottlenecks with sudden exponential growths. Although phenotype mapping is challenging due to high LD, we gathered evidences that some functional new mutations probably had an adaptive advantage.

Climate adaptation from standing variation

This project takes most of my time currently and involves high-throughput phenotype experiments in the greenhouse and in the field to study climatic adaptation from standing variation. I use world wide distributed accessions sequenced in the 1001 genomes project and measure several fitness traits using image processing tools. Combining it with whole-genome sequences, I aim to identify genetic variation associated with high performance under harsh climatic conditions such as drought. Also, based on population genetics models, I reconstruct population sizes, admixture of ancestral populations, and geographic spread of genetic diversity, and connect those with climatic adaptation events in the past.

1- Adaptation to simulated drought and forecast under climate change


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Exposito-Alonso et al. (2017) Genomic basis and evolutionary potential for extreme drought adaptation in Arabidopsis thaliana. Nature Ecology & Evolution, doi:

Because earth is currently experiencing a dramatic climate change, it is of critical interest to predict how species will respond to it. However, most predictive studies ignore that species comprise genetically diverse individuals. Thus, the chance of a species to withstand climate change will likely depend on how many subpopulations are already adapted to extreme environments. Because a major consequence of global warming will be an increase in extreme drought events, we first identified genetic variants in Arabidopsis thaliana that predict survival of such an event. Subsequently, we determined how these variants are distributed across the native range of the species. Genetic variants conferring higher drought survival showed signatures of polygenic adaptation, and were more frequently found in Mediterranean and Scandinavian regions. Using geo-environmental models, we predicted that Central European populations might lag behind in adaptation by the end of the 21 st century. Further analyses showed that a population decline could nevertheless be compensated by natural selection acting efficiently over standing variation or by migration of adapted individuals from populations at the margins of the species’ distribution. These findings highlight the importance of within-species genetic heterogeneity in facilitating an evolutionary response to a changing climate.

2- Natural selection under manipulated rainfall at Mediterranean and European field stations


Exposito-Alonso et al. (2017) A rainfall-manipulation experiment with 517 Arabidopsis thaliana accesions. bioRxiv

Exposito-Alonso et al. (2018) A map of climate driven-selection in Arabidopsis thalianabioRxiv

Through the lens of evolution, climate change is an agent of directional selection that forces populations to change and adapt, or face extinction. Current assessments of the risks associated with climate change, however, do not typically take into account that natural selection can dramatically impact the genetic makeup of populations. We made use of extensive genome information in Arabidopsis thaliana and measured how rainfall-manipulation affected the fitness of 517 natural lines grown in Spain and Germany. This allowed us to directly infer selection at the genetic level. Natural selection was particularly strong in the hot-dry Spanish location, killing 63% of lines and significantly changing the frequency of ~5% of all genome-wide variants. A significant proportion of this selection over variants could be predicted from climate (mis)match between experimental sites and the geographic areas of where variants are found (R2=29-52%). Field-validated predictions across the species range indicated that Mediterranean and Western Siberia populations — at the edges of the species’ environmental limits — currently experience the strongest climate-driven selection, and Central Europeans the weakest. With rapidly increasing droughts and rising temperatures in Europe, we forecast a wave of directional selection moving North, putting many native A. thaliana populations at evolutionary risk.


3- Genomics of rapid Evolution in Novel Environments GrENE-net

On fall 2017 we started evolution experiments in over 45 locations. For three years, we will monitor evolution in real time. For more information visit the web

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