As of summer 2019 I’ll be joining the Carnegie Department of Plant Biology based in Stanford. Go the lab website for updates:


I am a Postdoc working on Statistical Evolutionary Genetics with Prof. Rasmus Nielsen at the University of California Berkeley. Previously, I did my PhD in Evolutionary Genomics and Plant Adaptation with Prof. Detlef Weigel at the Max Planck Institute for Developmental Biology in Germany (Oct 2014 – Oct2018), a MSc in Quantitative Genetics and Genome Analysis at the University of Edinburgh (Sep 2013 – Sep 2014) and a BSc in Biology at the Universities of Alicante and Sevilla (Sep 2008 – Jul 2013). 

My work revolves around climate change adaptation and evolutionary rates of the plant Arabidopsis thaliana



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If you need a PDF, drop me an e-mail or search Sci-Hub in Google.


10. Exposito-Alonso, M. (2018). On climate change and genetic evolution in Arabidopsis thaliana. Max Planck Institute for Developmental Bioloy & Universität Tübingen, Ph.D. Thesis.

9. Exposito-Alonso, M., Burbano, H. A., Bossdorf, O., Nielsen, R., Weigel, D. (2018) A map of climate driven-selection in Arabidopsis thaliana. bioRxiv,


8. Exposito-Alonso, M., Rodríguez, R.G., Barragán, C., Capovilla, G., Chae, E., Devos, J., Dogan, E.S., Friedemann, C., Gross, C., Lang, P., Lundberg, D., Middendorf, V., Kageyama, J., Karasov, T., Kersten, S., Petersen, S., Rabbani, L., Regalado, J., Reinelt, L., Rowan, B., Seymour, D.K., Symeonidi, E., Schwab, R., Tran, D.T.N., Venkataramani, K., Van de Weyer, A.-L., Vasseur, F., Wang, G., Wedegärtner, R., Weiss, F., Wu, R., Xi, W., Zaidem, M., Zhu, W., García-Arenal, F., Burbano, H.A., Bossdorf, O., Weigel, D., (2017) A rainfall-manipulation experiment with 517 Arabidopsis thaliana accessions. bioRxiv,

7. Exposito-Alonso, M., Brennan, A., Alonso-Blanco, C., Picó, F.X., (2018). Spatio-temporal variation in fitness responses to contrasting environments in Arabidopsis thalianaEvolution, (in press)

6. Vasseur, F., Exposito-Alonso, M., Ayala-Garay, O., Wang, G., Enquist, B.J., Violle, C., Ville, D., Weigel, D., (2018). Scaling irregularities explained by local adaptation in Arabidopsis thaliana. Proceedings of the National Academy of Sciences, | (2018) bioRxiv,

5. Exposito-Alonso, M.*, Becker, C.*, Schuenemann, V.J., Reitter, E., Setzer, C., Slovak, R., Brachi, B., Hagmann, J., Grimm, D.G., Jiahui, C., Busch, W., Bergelson, J., Ness, R.W., Krause, J., Burbano, H.A., Weigel, D., (2018). The rate and effect of new mutations in a colonizing plant lineage. PLOS Genetics, | (2016) bioRxiv, | Cover:

4. Exposito-Alonso, M., Vasseur, F., Ding, W., Wang, G., Burbano, H.A., Weigel, D., (2018). Genomic basis and evolutionary potential for extreme drought adaptation in Arabidopsis thaliana. Nature Ecology & Evolution 2, 352–358. | (2017) bioRxiv,

3. Lee, C.-R., Svardal, H., Farlow, A., Exposito-Alonso, M., Ding, W., Novikova, P., Alonso-Blanco, C., Weigel, D., Nordborg, M., (2017). On the post-glacial spread of human commensal Arabidopsis thaliana. Nature Communications. 8, 14458.

2. Iakovidis, M., Teixeira, P.J.P.L., Exposito-Alonso, M., Cowper, M.G., Law, T.F., Liu, Q., Vu, M.C., Dang, T.M., Corwin, J.A., Weigel, D., Dangl, J.L., Grant, S.R., (2016). Effector-triggered immune response in Arabidopsis thaliana is a quantitative trait. Genetics 204, 337–353.

1. 1001 Genomes Consortium§, (2016). 1,135 Genomes reveal the global pattern of polymorphism in Arabidopsis thaliana. Cell 166, 481–491.  §Personal contributions: manuscript writing, Fig. 6A, Fig. 6C, and initial analyses of Fig. 4A.


Corrigenda of typos and thinkos



10/2014 – 10/2018 PhD program Evolutionary biology, Developmental biology, Genetics and Ecology (EDGE).
Max Planck Institute for Developmental Biology
Tübingen (Germany)

9/2013 – 9/2014 MSc in Quantitative Genetics and Genome Analysis – specialization Evolutionary Genetics
University of Edinburgh (UK)

9/2008 – 7/2013 BSc in Biology
University of Alicante and University of Seville (Spain)

Talks & Conferences

7/2019 Joint Congress SSE & ASN. (invited symposium talk)
Providence, RI (USA)

5/2018 EvE seminars. (invited talk)
Tübingen (Germany)

3/2018 DIKO seminars. (invited talk)
Tübingen (Germany)

8/2018 II Joint Congress of the European Society for Evolutionary Biology, the American Society of Naturalists, the Society for the Study of Evolution and the Society of Systematic Biologists.  ESEB & SSE & ASN & SSB 2018. (symposium #64 organizer)
Montpellier (France)

01/2018 1st Genomic Basis of Climate Adaptation Symposium. (talk)
Senckenberg Biodiversity and Climate Research Centre.

Frankfurt (Germany)

11/2017 University of California Davis – Center for Population Biology (CPB). (invited talk)
University of California Davis (US)

11/2017 XV Bay Area Population Genomics Meeting  BAPG.
Stanford (US)

10/2017 Center for Theoretical Evolutionary Genomics CTEG. 
University of California Berkeley (US)

8/2017 XVIst congress of the European Society of Evolutionary Biology. ESEB 2017. (poster, see it here!)
Groningen (Netherlands)

9/2016 46th Annual meeting of the Ecological Society of Germany, Austria and Switzerland. Gfö 2016. (invited talk)
Marburg (Germany)

6-7/2016 “California talk tour”. Hosting labs:
Graham Coop, Annie Schmitt, Jeff Ross-Ibarra. UC Davis, California (US)
Dmitry Petrov, Stanford, Palo Alto, California (US)
Daniel Koenig, UC Riverside, Riverside, California (US)

6/2016 Congress of the Society for the Study of Evolution SSE2015. (talk)
Austin, Texas (US)

8/2015 XVth Congress of the European Society for Evolutionary Biology ESEB2015(talk)
Lausanne (Switzerland)

6/2015 Congress of the Society for Molecular Biology and Evolution SMBE 2015. (talk)
Vienna (Austria)

7/2015 International Conference on Arabidopsis Research ICAR 2015. (poster co-author)
Paris (France)

5/2015 Quantitative Genomics 2015. QG2015 (organizer)
London (UK)

5/2014 Quantitative Genomics 2014 QG2014. “Arabidopsis thaliana in North America: a natural mutation accumulation line since the 19th century colonization”. (talk)
London (UK)


2017 EMBO ST fellowship
European Molecular Biology Organization

2015 Best Academic record of the Faculty of Biology at University of Sevilla
Its Excellency City Council of Sevilla (Spain)

2014 Royal Cavalry of Sevilla award for the best academic rank of the Natural Sciences Faculty at University of Sevilla
Real Maestranza de Caballería de Sevilla (Spain)

2013 Best Academic Rank award.
University of Sevilla (Spain)

2013 “la Caixa” Postgraduate International Grant .
“la Caixa” Foundation

2013 Scholarship for Erasmus Mundus Masters Programme in Evolutionary Biology (MEME) (declined).
European Commission (EACEA)

2012 Collaboration Research Scholarship .
Ministry of Education – Spanish Government

2011 Research Scholarship (JAE Intro) .
Spanish National Research Council (CSIC)

2008-2013 Annual Tuition Fee Scholarship for Honour Marks in the Bachelor’s degree (5 consecutive years).
University of Alicante and University of Sevilla (Spain)

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:

By following the evolution of populations that are initially genetically homogeneous, much can be learned about core biological principles. For example, it allows for detailed studies of the rate of emergence of de novo mutations and their change in frequency due to drift and selection. Unfortunately, in multicellular organisms with generation times of months or years, it is difficult to set up and carry out such experiments over many generations. An alternative is provided by “natural evolution experiments” that started from colonizations or invasions of new habitats by selfing lineages. With limited or missing gene flow from other lineages, new mutations and their effects can be easily detected. North America has been colonized in historic times by the plant Arabidopsis thaliana, and although multiple intercrossing lineages are found today, many of the individuals belong to a single lineage, HPG1. To determine in this lineage the rate of substitutions-the subset of mutations that survived natural selection and drift-, we have sequenced genomes from plants collected between 1863 and 2006. We identified 73 modern and 27 herbarium specimens that belonged to HPG1. Using the estimated substitution rate, we infer that the last common HPG1 ancestor lived in the early 17th century, when it was most likely introduced by chance from Europe. Mutations in coding regions are depleted in frequency compared to those in other portions of the genome, consistent with purifying selection. Nevertheless, a handful of mutations is found at high frequency in present-day populations. We link these to detectable phenotypic variance in traits of known ecological importance, life history and growth, which could reflect their adaptive value. Our work showcases how, by applying genomics methods to a combination of modern and historic samples from colonizing lineages, we can directly study new mutations and their potential evolutionary relevance.

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


Screen Shot 2017-03-18 at 12.32.41.png

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 rainfall-manipulated field experiments in Mediterranean and European 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