M. Exposito-Alonso

This study shows that gene editing can relax selection constraints on plant traits by altering genetic correlations between flowering time and water use efficiency in Arabidopsis thaliana.

This study shows that ecological trade-offs between dispersal, competition, and stress tolerance shape the geographic distribution of Arabidopsis thaliana in Europe.

The paper uses historical A. thaliana genomes and genetic knowledge to show a decrease in stomatal density over time linked to climate change.

This paper develops a deep learning model that predicts plant species distributions using remote sensing, citizen science, and deep learning, enabling high-resolution biodiversity monitoring.

This paper validates pool-sequencing for tracking rapid plant population evolution and introduces tools to accelerate population genetic analysis.

This study automates the GLO-Roots platform with robotics and image analysis to examine natural variation in Arabidopsis root system architecture over time, revealing complex traits correlated with climate variables.

The paper revisits Haldane's Dilemma by analyzing substitution load and selective deaths in Arabidopsis thaliana, finding a higher proportion of selective deaths than previously thought.

This study examines phenotypic variation in Arabidopsis thaliana along latitudinal and center-margins gradients, finding both patterns of differentiation in stress tolerance and colonization ability.

The paper introduces a mathematical framework to estimate genetic diversity loss due to habitat reduction and shows that over 10% of genetic diversity may already be lost globally.

The paper identifies two small proteins, MHA1 and MHA1L, that modulate ACD6 activity in Arabidopsis thaliana, affecting growth and defense trade-offs through calcium influx regulation.

The paper develops a non-additive polygenic model to predict fitness traits in three eukaryote species and finds non-additive models better explain fitness in some cases.

The paper shows that mutation rates in Arabidopsis thaliana are influenced by cytogenetic features and are lower in genes with deleterious mutations, contradicting neutral expectations.

The paper assesses climate change-driven natural selection in Arabidopsis thaliana by analyzing fitness impacts of rainfall manipulation across different geographic regions.

The paper shows that Arabidopsis thaliana accessions exhibit variation in growth allometry linked to climate adaptation, with PUB4 gene under balancing selection affecting trade-offs between stress resistance and seed production.

The paper predicts future genetic changes in A. thaliana populations by integrating climate change models with genomic data from experimental drought survival experiments.