Biology subjects

Villa, J.

Publications and source records attributed to Villa, J..

5 recordsLinked to original sources

bioRxiv2025

Egg colour mimicry in the common cuckoo results from coevolutionary alternation, not coevolutionary arms races

The exquisite eggshell mimicry found in many cuckoo-host systems has been the textbook example of a coevolutionary arms race1. In this system, cuckoos lay their eggs in their hosts nests leaving these foster parents to rear their young2. In defence, most of these hosts have evolved the ability to recognize cuckoo eggs. It is long-assumed that these interactions select for ever-improving eggshell mimicry in cuckoo host-races laying distinct eggs that specifically mimic their hosts eggshell, regardless of its particular colour3,4. We challenge this paradigm and demonstrate that coevolutionary arms races and egg colour mimicry are the exception to the rule. Here, using eggshell reflectance spectra from 39 host species and the specific cuckoo eggs found in their nests, we show that eggshell colour mimicry is very uncommon even among frequent hosts. Although cuckoo eggs display considerable variation in eggshell colour, their hosts eggshell colours occupy 6 times their colour volume. As a result, mimicry is only achieved for a small subset of the egg colour gamut. Furthermore, cuckoo host-races rarely lay eggs that match their hosts eggs better than those of other potential hosts or that are distinct from those laid by other cuckoo host-races. These patterns are inconsistent with the long-held assumption of coevolutionary arms races, but consistent with coevolutionary alternation that is defined by a process of continual host-switching. These findings open new avenues for research in a system that has long served as a model for studying coevolutionary processes.

evolutionary biology↗

bioRxiv2025

Harnessing artificial intelligence to automate environmental predictions

Predicting heterogeneous and non-linear processes remains a fundamental challenge in Earth sciences. Here, we present an artificial intelligence (AI)-guided framework that iteratively combines predictive modeling with targeted field sampling to rapidly improve environmental predictions. We demonstrate our workflow by predicting oxygen consumption, a key process of stream metabolism, across the contiguous United States (CONUS). Our approach consisted of 18 iterative loops of measurements and models, combining distributed participatory field sampling, lab analysis, automated machine learning (ML) predictions, and error and distinctiveness analyses to autonomously guide the next sampling at optimal site locations. Through our approach, we increased the predictive power of sediment oxygen consumption across CONUS by over fifteenfold between the first and last iteration. Relative to our last sampling iteration, our first sampling missed sites with high rates and underestimated median oxygen consumption rates by 68%. In addition to identifying areas of high oxygen consumption rates, iterations enabled refinement of laboratory and data handling methods, and engagement with a broad community of field researchers. We conclude that AI-guided iterative loops between targeted sampling and predictive modeling are a powerful and efficient approach for improving predictions of heterogeneous environmental processes.

ecology↗

bioRxiv2023

Separation-of-function mutants reveal the NF-κB-independent involvement of IκBα in the regulation of stem cell and oncogenic programs

We previously demonstrated that the NF-{kappa}B inhibitor I{kappa}B binds the chromatin together with PRC2 to regulate a subset of developmental- and stem cell-related genes. This alternative function has been elusive in both physiological and disease conditions because of the predominant role of I{kappa}B as a negative regulator of NF-{kappa}B. We here uniquely characterize specific residues of I{kappa}B that allow the generation of separation-of-function (SOF) mutants that are defective for either NF-{kappa}B-related (SOF{Delta}NF-{kappa}B) or chromatin-related (SOF{Delta}H2A,H4) activities. Expression of I{kappa}B SOF{Delta}NF-{kappa}B, but not SOF{Delta}H2A/H4, is sufficient to negatively regulate a specific stemness program in intestinal cells, thus rescuing the differentiation blockage imposed by I{kappa}B deficiency. In contrast, full I{kappa}B activity is required for regulating clonogenic/tumor-initiating activity of colorectal cancer cells. Our data indicate that SOF mutants represent an exclusive tool for studying I{kappa}B functions in physiology and disease, and identified I{kappa}B as a robust prognosis biomarker for human cancer.

cell biology↗

bioRxiv2022

Recording animal-view videos of the natural world

Plants, animals, and fungi display a rich tapestry of colors. Animals, in particular, use colors in dynamic displays performed in spatially complex environments. In such natural settings, light is reflected or refracted from objects with complex shapes that cast shadows and generate highlights. In addition, the illuminating light changes continuously as viewers and targets move through heterogeneous, continually fluctuating, light conditions. Although traditional spectrophotometric approaches for studying colors are objective and repeatable, they fail to document this complexity. Worse, they miss the temporal variation of color signals entirely. Here, we introduce hardware and software that provide ecologists and filmmakers the ability to accurately record animal-perceived colors in motion. Specifically, our Python codes transform photos or videos into perceivable units (quantum catches) for any animal of known photoreceptor sensitivity. We provide the plans, codes, and validation tests necessary for end-users to capture animal-view videos. This approach will allow ecologists to investigate how animals use colors in dynamic behavioral displays, the ways natural illumination alters perceived colors, and other questions that remained unaddressed until now due to a lack of suitable tools. Finally, our pipeline provides scientists and filmmakers with a new, empirically grounded approach for depicting the perceptual worlds of non-human animals.

animal behavior and cognition↗

bioRxiv2022

Consistent differences in eggshell phenotypes select for bluer eggs in an avian host-parasite system

Avian brood parasitism is a well-recognized model for studying coevolution. In this model, hosts adapt the ability to recognize and remove parasitic young to avoid the costs of rearing foreign offspring, while parasites counter-adapt phenotypes to evade detection. A classic example of host-parasite coevolutionary arms race is the great reed warbler and its parasite the common cuckoo (hereafter warbler and cuckoo, respectively). Recent work has found that cuckoo eggs are more likely to be accepted by warblers when those are bluer than their own eggs. Therefore, hosts would select for bluer cuckoo eggs; in turn, this provides directional selection for hosts eggs to remain bluer than cuckoo eggs. Here, we tested whether there were consistent differences in eggshell appearance between cuckoo and warbler eggs using a dataset which provides eggshell coloration of both warblers and cuckoos from the same nest. Despite being a textbook example of mimicry, we found that the cuckoos have significantly browner eggs than the warblers. These findings most likely suggest that this warbler-cuckoo system is experiencing negative frequency-dependent selection, as expected under red queen dynamics. Future research comparing warbler-cuckoo interactions over time would advance our understanding of the coevolution between avian brood parasites and their hosts.

evolutionary biology↗