Biology subjects

Lira-Noriega, A.

Publications and source records attributed to Lira-Noriega, A..

3 recordsLinked to original sources

bioRxiv2026

Genome-wide divergence in a desert plant in the Baja California Peninsula driven by glacial cycles and adaptation to different climatic conditions

The processes that generate distinct patterns of population subdivision (i.e., phylogeographic breaks) and facilitate local adaptations continue to be a focal point of evolutionary research. Here, we used whole-genome sequencing, demographic modeling, ecological niche modeling, and genotype-environment association analysis paired with outlier tests to understand patterns and drivers of diversification of the desert shrub Encelia farinosa in the Baja California Peninsula. We found that E. farinosa was represented by three moderately differentiated (0.027 < Fst < 0.068) genetically distinct groups, distributed across the North, Central and Southern regions of the Peninsula. Demographic analyses revealed fluctuations in the effective population sizes and two lineage divergence events, which coincided with the onset of recent glacial cycles. The ecological niche modeling recovered concordant southward shifts and decrease in the suitable habitat for all E. farinosa groups during the Last Glacial period. Analyses of associations between putative adaptive loci and environmental variables suggested that climate has been an important driver of adaptive genetic variation, with regional differentiation primarily associated with solar irradiation, temperature, and precipitation seasonality. We demonstrate that local adaptations in E. farinosa involve multiple genes associated with immune response, stress response, and morphological adaptations associated with arid climate such as leaf pubescence. Our findings indicate that current levels of differentiation and genetic variation in E. farinosa can be explained by the interplay of processes acting at multiple temporal scales, including isolation by distance, glaciation-mediated demographic processes, and recent natural selection shaping specific adaptations for each geographical group.

evolutionary biology↗

bioRxiv2025

Behavioral and phenotypic constraint belie deep genomic divergence and seasonal adaptation in a widespread desert lizard

Cryptic species offer opportunities to reveal the mechanisms that constrain phenotypic divergence during speciation. We integrated whole-genome sequencing, morphological, micro- and macro-climatic, and behavioral data to investigate divergence across a well- documented genetic break in the desert-adapted side-blotched lizard, Uta stansburiana, on the Baja California peninsula. Despite deep genomic differentiation, clades show remarkable similarity in morphology, habitat use, and thermal biology. Nearly all genetic differentiation (87%) is explained by isolation by distance and seasonal variation in precipitation, with almost no effect of temperature. Behavioral thermoregulation and changes in activity time accommodate strong macro- and micro-climatic differences, buffering against selection that would otherwise drive morphological and physiological divergence. In contrast, genomic signatures of selection and divergence in genes associated with the nervous system, sensory perception, and biomolecule metabolism indicate adaptation to differences in rainfall seasonality. The results show behavioral flexibility can constrain phenotypic divergence, yielding cryptic species-level genetic divergence despite strong eco-climatic disparities and selection pressures. More broadly, this study shows how rigorous statistical integration of multiple data types can disentangle competing eco- climatic drivers that can decouple phenotype from genotype during speciation. SignificanceUnderstanding why deep genetic divergence occurs without phenotypic differentiation is a longstanding challenge in evolutionary biology. By statistically integrating genomic, morphological, climatic, and behavioral data, we test the mechanisms controlling differentiation within a natural lizard system in a geo-climatically diverse setting. Results show that isolation by distance and adaptation to precipitation seasonality drive nearly all genomic differentiation. Behavioral adjustment to strong thermal variation buffers against selection pressure otherwise expected to cause divergence in morphology, thermal biology, and habitat use. This work demonstrates how rigorous integrative analyses can tease apart ecological and neutral factors controlling genomic divergence, providing rare insight into causal mechanisms driving speciation while constraining phenotypic divergence.

evolutionary biology↗

bioRxiv2020

American mammals susceptibility to dengue according to geographical, environmental and phylogenetic distances

Many human emergent and re-emergent diseases have a sylvatic cycle. Yet, little effort has been put into discovering and modeling the wild mammal reservoirs of dengue (DENV), particularly in the Americas. Here, we show a species-level susceptibility prediction to dengue of wild mammals in the Americas as a function of the three most important biodiversity dimensions (ecological, geographical, and phylogenetic spaces), using machine learning protocols. Model predictions showed that different species of bats would be highly susceptible to DENV infections, where susceptibility mostly depended on phylogenetic relationships among hosts and their environmental requirement. Mammal species predicted as highly susceptible coincide with sets of species that have been reported infected in field studies, but it also suggests other species that have not been previously considered or that have been captured in low numbers. Also, the environment (i.e., the distance between the species optima in bioclimatic dimensions) in combination with geographic and phylogenetic distance is highly relevant in predicting susceptibility to DENV in wild mammals. Our results agree with previous modeling efforts indicating that temperature is an important factor determining DENV transmission, and provide novel insights regarding other relevant factors and the importance of considering wild reservoirs. This modeling framework will aid in the identification of potential DENV reservoirs for future surveillance efforts.

ecology↗