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Exposito-Alonso, M.

Publications and source records attributed to Exposito-Alonso, M..

26 records · Page 2Linked to original sources

Quantifying the scale of genetic diversity extinction in the Anthropocene

More species than ever before are at risk of extinction due to anthropogenic habitat loss and climate change. But even species that are not threatened have seen reductions in their populations and geographic ranges, likely impacting their genetic diversity. Although preserving genetic diversity is key to maintaining adaptability of species, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. By bridging theories of biodiversity and population genetics, we introduce a mathematical framework to understand the loss of naturally occurring DNA mutations within decreasing habitat within a species. Analysing genome-wide variation data of 10,095 geo-referenced individuals from 20 plant and animal species, we show that genome-wide diversity follows a power law with geographic area (the mutations-area relationship), which can predict genetic diversity loss in spatial computer simulations of local population extinctions. Given pre-21st century values of ecosystem transformations, we estimate that over 10% of genetic diversity may already be lost, surpassing the United Nations targets for genetic preservation. These estimated losses could rapidly accelerate with advancing climate change and habitat destruction, highlighting the need for forecasting tools that facilitate implementation of policies to protect genetic resources globally.

ecology↗

Small peptides modulate the immune function of the ion channel-like protein ACD6 in Arabidopsis thaliana

ACCELERATED CELL DEATH 6 (ACD6) mediates a trade-off between growth and defense in Arabidopsis thaliana. However, the precise biochemical mechanism by which ACD6 and related proteins in plants act remains enigmatic. Here, we identified two loci, MODULATOR OF HYPERACTIVE ACD6 1 (MHA1) and its paralog MHA1-LIKE (MHA1L), that code for [~]7 kDa proteins that differentially interact with specific ACD6 variants. MHA1L enhances accumulation of an ACD6 complex, thereby increasing activity of the ACD6 standard allele for regulating plant growth and defenses. ACD6 is a multipass transmembrane protein with intracellular ankyrin repeats that are structurally similar to those found in mammalian ion channels. Several lines of evidence link increased ACD6 activity to enhanced calcium influx, likely mediated by ACD6 itself and with MHA1L as a direct regulator of ACD6.

plant biology↗

Non-additive polygenic models improve predictions of fitness traits in three eukaryote model species

To describe a living organism it is often said that "the whole is greater than the sum of its parts". In genetics, we may also think that the effect of multiple mutations on an organism is greater than their additive individual effect, a phenomenon called epistasis or multiplicity. Despite the last decades discovery that many disease- and fitness-related traits are polygenic, or controlled by many genetic variants, it is still debated whether the effects of individual genes combine additively or not. Here we develop a flexible likelihood framework for genome-wide associations to fit complex traits such as fitness under both additive and non-additive polygenic architectures. Analyses of simulated datasets under different true additive, multiplicative, or other epistatic models, confirm that our method can identify global non-additive selection. Applying the model to experimental datasets of wild type lines of Arabidopsis thaliana, Drosophila melanogaster, and Saccharomyces cerevisiae, we find that fitness is often best explained with non-additive polygenic models. Instead, a multiplicative polygenic model appears to better explain fitness in some experimental environments. The statistical models presented here have the potential to improve prediction of phenotypes, such as disease susceptibility, over the standard methods for calculating polygenic scores which assume additivity.

evolutionary biology↗

Mutation bias shapes gene evolution in Arabidopsis thaliana

Classical evolutionary theory maintains that mutation rate variation between genes should be random with respect to fitness 1-4 and evolutionary optimization of genic mutation rates remains controversial 3,5. However, it has now become known that cytogenetic (DNA sequence + epigenomic) features influence local mutation probabilities 6, which is predicted by more recent theory to be a prerequisite for beneficial mutation rates between different classes of genes to readily evolve 7. To test this possibility, we used de novo mutations in Arabidopsis thaliana to create a high resolution predictive model of mutation rates as a function of cytogenetic features across the genome. As expected, mutation rates are significantly predicted by features such as GC content, histone modifications, and chromatin accessibility. Deeper analyses of predicted mutation rates reveal effects of introns and untranslated exon regions in distancing coding sequences from mutational hotspots at the start and end of transcribed regions in A. thaliana. Finally, predicted coding region mutation rates are significantly lower in genes where mutations are more likely to be deleterious, supported by numerous estimates of evolutionary and functional constraint. These findings contradict neutral expectations that mutation probabilities are independent of fitness consequences. Instead they are consistent with the evolution of lower mutation rates in functionally constrained loci due to cytogenetic features, with important implications for evolutionary biology8.

evolutionary biology↗

A map of climate change-driven natural selection in Arabidopsis thaliana

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 change1,2, however, do not typically take into account that natural selection can dramatically impact the genetic makeup of populations3. 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 level4. 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 Europe5, we forecast a wave of directional selection moving North, putting many native A thaliana populations at evolutionary risk.

evolutionary biology↗

Adaptive diversification of growth allometry in the plant Arabidopsis thaliana

Seed plants vary tremendously in size and morphology. However, variation and covariation between plant traits may at least in part be governed by universal biophysical laws and biological constants. Metabolic Scaling Theory (MST) posits that whole-organismal metabolism and growth rate are under stabilizing selection that minimizes the scaling of hydrodynamic resistance and maximizes the scaling of resource uptake. This constrains variation in physiological traits and in the rate of biomass accumulation, so that they can be expressed as mathematical functions of plant size with near constant allometric scaling exponents across species. However, observed variation in scaling exponents questions the evolutionary drivers and the universality of allometric equations. We have measured growth scaling and fitness traits of 451 Arabidopsis thaliana accessions with sequenced genomes. Variation among accessions around the scaling exponent predicted by MST correlated with relative growth rate, seed production and stress resistance. Genomic analyses indicate that growth allometry is affected by many genes associated with local climate and abiotic stress response. The gene with the strongest effect, PUB4, has molecular signatures of balancing selection, suggesting that intraspecific variation in growth scaling is maintained by opposing selection on the trade-off between seed production and abiotic stress resistance. Our findings support a core MST prediction and suggest that variation in allometry contributes to local adaptation to contrasting environments. Our results help reconcile past debates on the origin of allometric scaling in biology, and begin to link adaptive variation in allometric scaling to specific genes.\n\nSignificance statementAre there biological constants unifying phenotypic diversity across scales? Metabolic Scaling Theory (MST) predicts mathematical regularity and constancy in the allometric scaling of growth rate with body size across species. Here, we show that adaptation to climate in Arabidopsis thaliana is associated with local strains that substantially deviate from the values predicted by MST. This deviation can be linked to increased stress tolerance at the expense of seed production, and it occurs through selection on genes that are involved in abiotic stress response and that are geographically correlated with climatic conditions. This highlights the evolutionary role of allometric diversification and helps establish the physiological bases of plant adaptation to contrasting environments.

ecology↗

A rainfall-manipulation experiment with 517 Arabidopsis thaliana accessions

The gold standard for studying natural selection and adaptation in the wild is to quantify lifetime fitness of individuals from natural populations that have been grown together in a common garden, or that have been reciprocally transplanted. By combining fitness values with species traits and genome sequences, one can infer selection coefficients at the genetic level. Here we present a rainfall-manipulation experiment with 517 whole-genome sequenced natural accessions of the plant Arabidopsis thaliana spanning the global distribution of the species. The experiments were conducted in two field stations in contrasting climates, in the Mediterranean and in Central Europe, where we built rainout shelters and simulated high and low rainfall. Using custom image analysis we quantified fitness- and phenology-related traits for 23,154 pots, which contained about 14,500 plants growing independently, and over 310,000 plants growing in small populations (max. 30 plants). This large field experiment dataset, which associates fitness and ecologically-relevant traits with genomes, will provide an important resource to test eco-evolutionary genetic theories and to understand the potential evolutionary impacts of future climates on an important plant model species.

evolutionary biology↗

Genomic basis and evolutionary potential for extreme drought adaptation in Arabidopsis thaliana

Because earth is currently experiencing unprecedented climate change, it is important to predict how species will respond to it. However, geographically-explicit predictive studies frequently ignore that species are comprised of genetically diverse individuals that can vary in their degree of adaptation to extreme local environments; properties that will determine the species ability to withstand climate change. Because an increase in extreme drought events is expected to challenge plant communities with global warming, we carried out a greenhouse experiment to investigate which genetic variants predict surviving an extreme drought event and how those variants are distributed across Eurasian Arabidopsis thaliana individuals. Genetic variants conferring higher drought survival showed signatures of polygenic adaptation, and were more frequently found in Mediterranean and Scandinavian regions. Using geoenvironmental models, we predicted that Central European populations might lag behind in adaptation by the end of the 21st 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.\n\nOne-sentence summary\"Future genetic changes in A. thaliana populations can be forecast by combining climate change models with genomic predictions based on experimental phenotypic data.\"

evolutionary biology↗