Biology subjects

Shapiro, A.

Publications and source records attributed to Shapiro, A..

10 recordsLinked to original sources

bioRxiv2026

Genomic offset is not predictive of recent demographic trends in Lycaeides butterflies

Genomic offset (GO) is increasingly used to predict population maladaptation risk under climate change, with larger offsets assumed to indicate greater vulnerability. Despite rapid adoption in conservation planning, it remains unclear how sensitive GO estimates are to key methodological choices, including SNP set composition, genotype-environment association (GEA) methods, and the specific GO metric used. Empirical validation against observed population dynamics also remains limited. Here, we evaluate the methodological robustness and predictive performance of GO using multidecadal demographic monitoring data from Lycaeides butterflies, a system with short generation times and high fecundity that may facilitate rapid adaptive responses. GO estimates were broadly consistent across SNP sets, regardless of composition or size, with climate-associated and randomly selected SNPs yielding largely concordant values. Consistency across GEA methods was moderate and depended on the SNP set used. In contrast, GO metrics differed substantially in the magnitude of maladaptation estimated, suggesting they capture distinct biological signals and should not be treated as interchangeable. Crucially, GO was a poor predictor of observed population trends, regardless of SNP set composition, GO metric, or GEA method, both at sites used to fit GEA models and when extrapolated to independent demographic sites. These findings suggest that, while GO provides a valuable conceptual framework for assessing potential maladaptation, its quantitative estimates and predictive power are sensitive to methodological choices and species-specific biological context. We therefore urge careful alignment of GO metric assumptions with conservation objectives, along with rigorous empirical validation, before GO estimates are used to inform management decisions.

evolutionary biology↗

bioRxiv2025

Temporal dynamics of color polymorphism and hybridization in Colias butterflies

Investigations into the genetic basis of color polymorphism have played a key role in our understanding of genetic architecture and the evolution of mating systems. Sulphur butterflies (Colias) have been models in this field, but also contain unsolved puzzles with respect to species boundaries and hybridization. We surveyed genomic variation across five years in a location where phenotypic intermediates between Colias eurytheme and C. eriphyle are observed, but ancestry variation of potential hybrids has not been quantified. Our results reveal individuals with hybrid ancestry roughly in proportion to the frequency of individuals of intermediate phenotype recorded in the wild. Individuals with hybrid ancestry were predominantly those with intermediate morphologies, but morphologically intermediate individuals were not always of hybrid origin, which raises alternative possibilities for the origin and maintenance of color variation in the system. Genomic regions differentiated between species are largely located on the Z chromosome, and we find more candidates on autosomes than in another Colias contact zone. The dynamics of hybridization in this system are highly variable through time, suggesting fertile avenues for future study into the maintenance of species boundaries in the face of temporally-variable, climatically influenced, and pervasive hybridization.

evolutionary biology↗

bioRxiv2025

Quiescence modulates age-related changes in the functional capacity of highly proliferative canine lung mesenchymal stromal cell populations

The functional capacity of highly proliferative cell populations changes with age. Here, we report that the proliferative capacity of canine lung mesenchymal stromal cells (LMSCs) declines with increasing age of the donor. However, other functional changes such as reduced autophagy, reduced migration/wound healing, increased production of reactive oxygen species, and increased senescence are not significantly altered with increasing age. Furthermore, transcriptomic profiling suggests minimal age-related changes. These data suggest that the reduced proliferative capacity of lung LMSCs isolated from aging donors may be associated with reversible cell cycle arrest (quiescence), rather than irreversible cell cycle arrest (senescence). Similar findings have been reported in other systems, including neural and muscle stem cells that are associated with low turnover-rate tissues.

developmental biology↗

bioRxiv2025

Temporal occupancy distributions reveal multifaceted and heterogeneous effects of climatic variation on montane butterflies

Climate change has substantially altered the phenology of many organisms, with profound implications for biodiversity and species interactions. However, phenological studies of insects have often focused on shifts over time, without explicitly examining how climate drives these changes. In addition, the metrics used to measure changes in phenology often capture only limited information about the flight period. In this study, we analyzed multidecadal observational and climate data using a hierarchical Bayesian framework to model the annual probability of occurrence distributions for 135 butterfly species across five montane sites along an elevational gradient. Our analysis used polynomial models that account for shifts in abundance and the timing and length of flight periods to investigate the effect of climate on butterfly phenology. We found that spring maximum and minimum temperatures, as well as winter precipitation, are important predictors of butterfly phenology. High winter precipitation delayed phenology at high-elevation sites where substantial snowfall occurs, while increased spring maximum temperatures generally advanced phenology across all elevations. Even modest increases in spring minimum temperatures caused substantial shift in phenology. We documented variability in the effect of climate on phenology across sites, among species within a site and among populations of the same species across different sites with variability among species within a site being especially pronounced. We also found that climate influences different aspects of the flight period differently (e.g., timing versus duration), underscoring the need to move beyond single metrics such as day of first flight. These findings highlight the importance of examining the entire flight period and considering the interplay of species-specific traits to improve predictions of how climate change impacts phenology. Such approaches might be essential for designing more targeted and effective conservation strategies in response to ongoing climate change.

ecology↗

bioRxiv2024

Longitudinal study of neurochemical, volumetric and behavioral changes in Q140 & BACHD mouse models of Huntingtons disease

Brain metabolites, detectable by magnetic resonance spectroscopy (MRS), have been examined as potential biomarkers in Huntingtons Disease (HD). In this study, the RQ140 and BACHD transgenic mouse models of HD were used to investigate the relative sensitivity of the metabolite profiling and the brain volumetry to characterize mouse HD. Magnetic resonance imaging (MRI) and 1H MRS data were acquired at 9.4 T from the transgenic mice and wild-type littermates every 3 months until death. Brain shrinkage was detectable in striatum of both mouse models at 12 months compared to littermates. In Q140 mice, increases in PCr and Gln occurred in striatum prior to cortex. Myo-inositol was significantly elevated in both regions from an early age. Lac, Ala and PE decreased in Q140 striatum. Tau increased in Q140 cortex. Metabolite changes in the BACHD cortex and striatum were minimal with a striatal decrease in Lac being most prominent, consistent with a dearth of ubiquitin and 1C2 positive aggregates detected in those regions. Binary logistical regression models generated from the Q140 metabolite data were able to predict the presence of disease in the BACHD striatal and previously published R6/2 metabolite data. Thus, neurochemical changes precede volume shrinkage and become potential biomarkers for HD mouse models Introduction

neuroscience↗

bioRxiv2020

An antiviral self-replicating molecular heterotroph

We report the synthesis of a molecular machine, fabricated from nucleic acids, which is capable of digesting viral RNA and utilizing it to assemble additional copies of itself inside living cells. The machines body plan combines several parts that build upon the target RNA, assembling an immobile, DNA:RNA 4-way junction, which contains a single gene encoding a hammerhead ribozyme (HHR). Full assembly of the machines body from its parts enables the subsequent elongation of the gene and transcription of HHR molecules, followed by HHR-mediated digestion of the target molecule. This digestion converts the target to a building block suitable for participation in the assembly of more copies of the machine, mimicking biological heterotrophy. In this work we describe the general design of a prototypical machine, characterize its activity cycle and kinetics, and show that it can be efficiently and safely delivered into live cells. As a proof of principle, we constructed a machine that targets the Autographa californica multicapsid nucleopolyhedrovirus (AcMNPV) GP64 gene, and show that it effectively suppresses viral propagation in a cell population, exhibiting predator/prey-like dynamics with the infecting virus. In addition, the machine significantly reduced viral infection, stress signaling, and innate immune activation inside virus-infected animals. This preliminary design could control the behavior of antisense therapies for a range of applications, particularly against dynamic targets such as viruses and cancer.

synthetic biology↗

bioRxiv2020

Forest condition in the Congo Basin for the assessment of ecosystem conservation status

Measuring forest degradation is important for understanding and designing measures to protect biodiversity and the capacity of forests to deliver ecosystem services. Conservation planning, particularly the prioritization of management interventions for forests, is often lacking spatial data on ecological condition, and it is often overlooked within decision-making processes. Existing methods for assessing forest degradation via proxies or binary measures (i.e. intact or not) cannot adequately consider the important variations of ecological condition. Direct methods to measure degradation (e.g. through remote sensing) require extensive training data, calibration and validation, and may be too sensitive to small-scale or short-term changes which may not be related to degradation. We developed a metric termed Forest Condition (FC) which aims to measure the degree of forest degradation, incorporating temporal history of forest change over a large spatial extent. We parameterized this metric based on estimated changes in above ground biomass in the context of forest fragmentation over time to estimate a continuous measure of forest degradation for Congo Basin countries. We estimate that just less than 70% of Congo Basin forests remain fully intact. FC was validated by direct remote sensing measurements from Landsat imagery for DRC. Results showed that FC was significantly positively correlated with forest canopy cover, gap area per hectare, and magnitude of temporal change in Normalized Burn Ratio. We tested the ability of FC to distinguish primary and secondary degradation and deforestation and found significant differences in gap area and spectral anomalies to validate our theoretical model. We used the IUCN Red List of Ecosystems criteria to demonstrate the value of applying forest degradation to assess the risk of ecosystem collapse. Based on this assessment, we found that without including FC in the assessment of biotic disruption, 12 ecosystems could not have a threat status assigned, and a further 9 ecosystems would have a lower threat status. Our overall assessment of ecosystems found approximately half of forest of Congo Basin ecosystem types which cover over 20% of all forest area are threatened including 4 ecosystems (<1% of total area) which are critically engendered. FC is a transferrable and scalable assessment to support forest monitoring, planning, and management.

ecology↗

bioRxiv2020

Only 40% of the world's forests are in good health

Many global environmental agendas, including halting biodiversity loss, reversing land degradation, and limiting climate change, depend upon retaining forests with high ecological integrity, yet the scale and degree of forest modification remains poorly quantified and mapped. By integrating data on observed and inferred human pressures and an index of lost connectivity, we generate the first globally-consistent, continuous index of forest condition as determined by degree of anthropogenic modification. Globally, only 17.4 million km2 of forest (40.5%) have high landscape level integrity (mostly found in Canada, Russia, the Amazon, Central Africa and New Guinea) and only 27% of this area is found in nationally-designated protected areas. Of the forest in protected areas, only 56% has high landscape level integrity. Ambitious policies that prioritize the retention of forest integrity, especially in the most intact areas, are now urgently needed alongside current efforts aimed at halting deforestation and restoring the integrity of forests globally.

ecology↗

bioRxiv2019

Subjective value then confidence in human ventromedial prefrontal cortex

Two fundamental goals of decision making are to select actions that maximize rewards while minimizing costs and to have strong confidence in the accuracy of a judgment. Neural signatures of these two forms of value: the subjective value (SV) of choice alternatives and the value of the judgment (confidence), have both been observed in ventromedial prefrontal cortex (vmPFC). However, the relationship between these dual value signals and their relative time courses are unknown. We recorded fMRI while 28 men and women performed a two-phase Ap-Av task with mixed-outcomes of monetary rewards paired with painful shock stimuli. Neural responses were measured during offer valuation (offer phase) and choice valuation (commit phase) and analyzed with respect to observed decision outcomes, model-estimated SV and confidence. During the offer phase, vmPFC tracked SV and decision outcomes, but it not confidence. During the commit phase, vmPFC tracked confidence, computed as the quadratic extension of SV, but it bore no significant relationship with the offer valuation itself, nor the decision. In fact, vmPFC responses from the commit phase were selective for confidence even for rejected offers, wherein confidence and SV were inversely related. Conversely, activation of the cognitive control network, including within lateral prefrontal cortex (lPFC) and dorsal anterior cingulate cortex (dACC) was associated with ambivalence, during both the offer and commit phases. Taken together, our results reveal complementary representations in vmPFC during value-based decision making that temporally dissociate such that offer valuation (SV) emerges before decision valuation (confidence).

neuroscience↗

bioRxiv2019

In utero estrogenic endocrine disruption alters the stroma to increase extracellular matrix density and mammary gland stiffness.

In utero endocrine disruption is linked to increased risk of breast cancer later in life. Despite numerous studies establishing this linkage, the long-term molecular changes that predispose mammary cells to carcinogenic transformation are unknown. Several lines of evidence indicate the stroma mediates endocrine disruption following early-life (or in utero) exposure. Herein, we utilized BPA as a model of estrogenic endocrine disruption to analyze the long-term consequences in the stroma. Using RNA-seq transcriptional profiling of adult primary fibroblasts isolated from female mice exposed to BPA in utero, we identified deregulated genes associated with the extracellular matrix. Specifically, multiple collagen genes had increased expression in exposed mice. In line with the transcriptional data, collagen deposition is increased in adult BPA-exposed mice. We further demonstrate in vitro that fibroblasts exposed to BPA in utero remodel a collagen matrix, thereby decreasing permeability of the collagen matrix. These alterations to the mammary gland resulted in increased gland stiffness in the adult mice. Our data connects early life endocrine disruption to breast density. Interestingly, increased collagen deposition and gland stiffness were not observed in the developing glands of younger mice, suggesting risk factors for breast cancer continue to develop throughout life following these exposures. Finally, we assessed whether in utero exposure to two other endocrine disruptors, BPS and DES, also increase breast stiffness in adult mice. While DES increased breast stiffness, BPS did not, suggesting this BPA alternative may in fact pose less breast cancer risk than its predecessor. As breast stiffness, extracellular matrix density, and collagen deposition have been directly linked to breast cancer risk, these data mechanistically link endocrine disruptor exposures and molecular alterations to increased disease susceptibility in the gland.

cancer biology↗