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  1. Free, publicly-accessible full text available October 1, 2024
  2. Betancourt, Andrea (Ed.)
    Abstract Evolutionary processes driving physiological trait variation depend on the underlying genomic mechanisms. Evolution of these mechanisms depends on the genetic complexity (involving many genes) and how gene expression impacting the traits is converted to phenotype. Yet, genomic mechanisms that impact physiological traits are diverse and context dependent (e.g., vary by environment and tissues), making them difficult to discern. We examine the relationships between genotype, mRNA expression, and physiological traits to discern the genetic complexity and whether the gene expression affecting the physiological traits is primarily cis- or trans-acting. We use low-coverage whole genome sequencing and heart- or brain-specific mRNA expression to identify polymorphisms directly associated with physiological traits and expressed quantitative trait loci (eQTL) indirectly associated with variation in six temperature specific physiological traits (standard metabolic rate, thermal tolerance, and four substrate specific cardiac metabolic rates). Focusing on a select set of mRNAs belonging to co-expression modules that explain up to 82% of temperature specific traits, we identified hundreds of significant eQTL for mRNA whose expression affects physiological traits. Surprisingly, most eQTL (97.4% for heart and 96.7% for brain) were trans-acting. This could be due to higher effect size of trans- versus cis-acting eQTL for mRNAs that are central to co-expression modules. That is, we may have enhanced the identification of trans-acting factors by looking for single nucleotide polymorphisms associated with mRNAs in co-expression modules that broadly influence gene expression patterns. Overall, these data indicate that the genomic mechanism driving physiological variation across environments is driven by trans-acting heart- or brain-specific mRNA expression. 
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    Free, publicly-accessible full text available July 1, 2024
  3. Abstract Magnetic order in most materials occurs when magnetic ions with finite moments arrange in a particular pattern below the ordering temperature. Intriguingly, if the crystal electric field (CEF) effect results in a spin-singlet ground state, a magnetic order can still occur due to the exchange interactions between neighboring ions admixing the excited CEF levels. The magnetic excitations in such a state are spin excitons generally dispersionless in reciprocal space. Here we use neutron scattering to study stoichiometric Ni 2 Mo 3 O 8 , where Ni 2+ ions form a bipartite honeycomb lattice comprised of two triangular lattices, with ions subject to the tetrahedral and octahedral crystalline environment, respectively. We find that in both types of ions, the CEF excitations have nonmagnetic singlet ground states, yet the material has magnetic order. Furthermore, CEF spin excitons from the tetrahedral sites form a dispersive diffusive pattern around the Brillouin zone boundary, likely due to spin entanglement and geometric frustrations. 
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    Free, publicly-accessible full text available December 1, 2024
  4. Climate change risks like extreme temperatures and high variability in rainfall adversely affect livelihoods, particularly for farmers in Burkina Faso where the primary sector is agriculture. Decisions on whether to adapt to these risks depend on how farmers perceive each risk and the resources they have available. In this study, we examine how long-term changes in temperature and rainfall are perceived by farmers in Burkina Faso. We also compare the extent to which these perceptions align with actual recorded changes in temperature and rainfall for multiple periods between 1991 and 2014. We use a logistic regression model to analyze the role of resources, such as asset ownership and perceived standards of living, along with household size, age, and gender of the household head to explain differences in perception and ultimately the decision to adapt. Our results show that the vast majority of farmers in Burkina Faso perceive changes in temperature and rainfall; however, only about half of those individuals perceive changes in ways that align with recorded long-term trends in their local temperature or rainfall. The extent to which those perceptions align with recorded changes depends on the time frame selected. Older farmers and those with assets were less likely to perceive temperature and rainfall trends in ways that aligned with climate records; however, farmers' perceptions of temperature change aligning with records and their perceived standard of living were both associated with the decision to adapt. This misalignment of perceptions with records and resources has significant implications for efforts to inform and support climate risk mitigation and adaptation. 
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  5. Abstract Physiological trait variation underlies health, responses to global climate change, and ecological performance. Yet, most physiological traits are complex, and we have little understanding of the genes and genomic architectures that define their variation. To provide insight into the genetic architecture of physiological processes, we related physiological traits to heart and brain mRNA expression using a weighted gene co-expression network analysis. mRNA expression was used to explain variation in six physiological traits (whole animal metabolism (WAM), critical thermal maximum (CT max ), and four substrate specific cardiac metabolic rates (CaM)) under 12 °C and 28 °C acclimation conditions. Notably, the physiological trait variations among the three geographically close (within 15 km) and genetically similar F. heteroclitus populations are similar to those found among 77 aquatic species spanning 15–20° of latitude (~ 2,000 km). These large physiological trait variations among genetically similar individuals provide a powerful approach to determine the relationship between mRNA expression and heritable fitness related traits unconfounded by interspecific differences. Expression patterns explained up to 82% of metabolic trait variation and were enriched for multiple signaling pathways known to impact metabolic and thermal tolerance ( e.g. , AMPK, PPAR, mTOR, FoxO, and MAPK) but also contained several unexpected pathways ( e.g. , apoptosis, cellular senescence), suggesting that physiological trait variation is affected by many diverse genes. 
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  6. Abstract An evolutionary debate contrasts the importance of genetic convergence versus genetic redundancy. In genetic convergence, the same adaptive trait evolves because of similar genetic changes. In genetic redundancy, the adaptive trait evolves using different genetic combinations, and populations might not share the same genetic changes. Here we address this debate by examining single nucleotide polymorphisms (SNPs) associated with the rapid evolution of character displacement in Anolis carolinensis populations inhabiting replicate islands with and without a competitor species (1Spp and 2Spp islands, respectively). We identify 215-outliers SNPs that have improbably large FST values, low nucleotide variation, greater linkage than expected and that are enriched for genes underlying animal movement. The pattern of SNP divergence between 1Spp and 2Spp populations supports both genetic convergence and genetic redundancy for character displacement. In support of genetic convergence: all 215-outliers SNPs are shared among at least three of the five 2Spp island populations, and 23% of outlier SNPS are shared among all five 2Spp island populations. In contrast, in support of genetic redundancy: many outlier SNPs only have meaningful allele frequency differences between 1Spp and 2Spp islands on a few 2Spp islands. That is, on at least one of the 2Spp islands, 77% of outlier SNPs have allele frequencies more similar to those on 1Spp islands than to those on 2Spp islands. Focusing on genetic convergence is scientifically rigorous because it relies on replication. Yet, this focus distracts from the possibility that there are multiple, redundant genetic solutions that enhance the rate and stability of adaptive change. 
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  7. Abstract

    Negative correlations in the sequential evolution of interspike intervals (ISIs) are a signature of memory in neuronal spike-trains. They provide coding benefits including firing-rate stabilization, improved detectability of weak sensory signals, and enhanced transmission of information by improving signal-to-noise ratio. Primary electrosensory afferent spike-trains in weakly electric fish fall into two categories based on the pattern of ISI correlations: non-bursting units have negative correlations which remain negative but decay to zero with increasing lags (Type I ISI correlations), and bursting units have oscillatory (alternating sign) correlation which damp to zero with increasing lags (Type II ISI correlations). Here, we predict and match observed ISI correlations in these afferents using a stochastic dynamic threshold model. We determine the ISI correlation function as a function of an arbitrary discrete noise correlation function$${{\,\mathrm{\mathbf {R}}\,}}_k$$Rk, wherekis a multiple of the mean ISI. The function permits forward and inverse calculations of the correlation function. Both types of correlation functions can be generated by adding colored noise to the spike threshold with Type I correlations generated with slow noise and Type II correlations generated with fast noise. A first-order autoregressive (AR) process with a single parameter is sufficient to predict and accurately match both types of afferent ISI correlation functions, with the type being determined by the sign of the AR parameter. The predicted and experimentally observed correlations are in geometric progression. The theory predicts that the limiting sum of ISI correlations is$$-0.5$$-0.5yielding a perfect DC-block in the power spectrum of the spike train. Observed ISI correlations from afferents have a limiting sum that is slightly larger at$$-0.475 \pm 0.04$$-0.475±0.04($$\text {mean} \pm \text {s.d.}$$mean±s.d.). We conclude that the underlying process for generating ISIs may be a simple combination of low-order AR and moving average processes and discuss the results from the perspective of optimal coding.

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  8. ABSTRACT Physiology defines individual responses to global climate change and species distributions across environments. Physiological responses are driven by temperature on three time scales: acute, acclimatory and evolutionary. Acutely, passive temperature effects often dictate an expected 2-fold increase in metabolic processes for every 10°C change in temperature (Q10). Yet, these acute responses often are mitigated through acclimation within an individual or evolutionary adaptation within populations over time. Natural selection can influence both responses and often reduces interindividual variation towards an optimum. However, this interindividual physiological variation is not well characterized. Here, we quantified responses to a 16°C temperature difference in six physiological traits across nine thermally distinct Fundulus heteroclitus populations. These traits included whole-animal metabolism (WAM), critical thermal maximum (CTmax) and substrate-specific cardiac metabolism measured in approximately 350 individuals. These traits exhibited high variation among both individuals and populations. Thermal sensitivity (Q10) was determined, specifically as the acclimated Q10, in which individuals were both acclimated and assayed at each temperature. The interindividual variation in Q10 was unexpectedly large: ranging from 0.6 to 5.4 for WAM. Thus, with a 16°C difference, metabolic rates were unchanged in some individuals, while in others they were 15-fold higher. Furthermore, a significant portion of variation was related to habitat temperature. Warmer populations had a significantly lower Q10 for WAM and CTmax after acclimation. These data suggest that individual variation in thermal sensitivity reflects different physiological strategies to respond to temperature variation, providing many different adaptive responses to changing environments. 
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