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Hibernation is a fascinating adaptation to food-scarce winters, characterized by significant physiological and behavioral changes, including fasting, inactivity, and insulin resistance. While hibernation is critical for the survival of many species, hibernation-related traits are often considered pathological in humans. Hibernation has been studied from a genomic perspective, especially with respect to transcription across multiple tissues. These studies have identified the differential activity of signaling pathways related to metabolism, tissue protection, and other mechanisms likely underlying hibernation phenotypes. Bears, in particular, are an interesting model for physiological and genomic studies of hibernation due to their large size and unique mode of hibernation compared to other small mammalian hibernators. Investigating the intricate molecular mechanisms underlying bear hibernation may therefore provide insight into fundamental biological processes with potential translational implications for human health, particularly with respect to metabolic disorders such as type II diabetes. This review focuses on recent advances and outstanding questions related to the exploration of bear hibernation from a genomic perspective. 

Salinity gradients act as strong environmental barriers that limit the distribution of aquatic organisms. Changes in gene expression associated with transitions between freshwater and saltwater environments can provide insights into organismal responses to variation in salinity. We used RNA-sequencing (RNA-seq) to investigate genome-wide variation in gene expression between a hypersaline population and a freshwater population of the livebearing fish speciesLimia perugiae(Poeciliidae). Our analyses of gill gene expression revealed potential molecular mechanisms underlying salinity tolerance in this species, including the enrichment of genes involved in ion transport, maintenance of chemical homeostasis, and cell signaling in the hypersaline population. We also found differences in gene expression patterns associated with cell-cycle and protein-folding processes between the hypersaline and freshwaterL.perugiae. Bidirectional freshwater-saltwater transitions have occurred repeatedly during the diversification of fishes, allowing for broad-scale examination of repeatable patterns in evolution. Therefore, we compared transcriptomic variation inL.perugiaewith other teleosts that have made freshwater-saltwater transitions to test for convergence in gene expression. Among the four distantly related population pairs from high- and low-salinity environments that we included in our analysis, we found only ten shared differentially expressed genes, indicating little evidence for convergence. However, we found that differentially expressed genes shared among three or more lineages were functionally enriched for ion transport and immune functioning. Overall, our results—in conjunction with other recent studies—suggest that different genes are involved in salinity transitions across disparate lineages of teleost fishes. 

Regulating transcription allows organisms to respond to their environment, both within a single generation (plasticity) and across generations (adaptation). We examined transcriptional differences in gill tissues of fishes in thePoecilia mexicanaspecies complex (family Poeciliidae), which have colonized toxic springs rich in hydrogen sulfide (H₂S) in southern Mexico. There are gene expression differences between sulfidic and non-sulfidic populations, yet regulatory mechanisms mediating this gene expression variation remain poorly studied. We combined capped-small RNA sequencing (csRNA-seq), which captures actively transcribed (i.e. nascent) transcripts, and messenger RNA sequencing (mRNA-seq) to examine how variation in transcription, enhancer activity, and associated transcription factor binding sites may facilitate adaptation to extreme environments. csRNA-seq revealed thousands of differentially initiated transcripts between sulfidic and non-sulfidic populations, many of which are involved in H₂S detoxification and response. Analyses of transcription factor binding sites in promoter and putative enhancer csRNA-seq peaks identified a suite of transcription factors likely involved in regulating H₂S-specific shifts in gene expression, including several key transcription factors known to respond to hypoxia. Our findings uncover a complex interplay of regulatory processes that reflect the divergence of extremophile populations ofP. mexicanafrom their non-sulfidic ancestors and suggest shared responses among evolutionarily independent lineages. 

Abstract Adaptation to extreme environments often involves the evolution of dramatic physiological changes. To better understand how organisms evolve these complex phenotypic changes, the repeatability and predictability of evolution, and possible constraints on adapting to an extreme environment, it is important to understand how adaptive variation has evolved. Poeciliid fishes represent a particularly fruitful study system for investigations of adaptation to extreme environments due to their repeated colonization of toxic hydrogen sulfide–rich springs across multiple species within the clade. Previous investigations have highlighted changes in the physiology and gene expression in specific species that are thought to facilitate adaptation to hydrogen sulfide–rich springs. However, the presence of adaptive nucleotide variation in coding and regulatory regions and the degree to which convergent evolution has shaped the genomic regions underpinning sulfide tolerance across taxa are unknown. By sampling across seven independent lineages in which nonsulfidic lineages have colonized and adapted to sulfide springs, we reveal signatures of shared evolutionary rate shifts across the genome. We found evidence of genes, promoters, and putative enhancer regions associated with both increased and decreased convergent evolutionary rate shifts in hydrogen sulfide–adapted lineages. Our analysis highlights convergent evolutionary rate shifts in sulfidic lineages associated with the modulation of endogenous hydrogen sulfide production and hydrogen sulfide detoxification. We also found that regions with shifted evolutionary rates in sulfide spring fishes more often exhibited convergent shifts in either the coding region or the regulatory sequence of a given gene, rather than both. 

Hibernation is a highly seasonal physiological adaptation that allows brown bears (Ursus arctos) to survive extended periods of low food availability. Similarly, daily or circadian rhythms conserve energy by coordinating body processes to optimally match the environmental light/dark cycle. Brown bears express circadian rhythms in vivo and their cells do invitro throughout the year, suggesting that these rhythms may play important roles during periods of negative energy balance. Here, we use time-series analysis of RNA sequencing data and timed measurements of ATP production in adipose-derived fibroblasts from active and hibernation seasons under two temperature conditions to confirm that rhythmicity was present. Culture temperature matching that of hibernation body temperature (34°C) resulted in a delay of daily peak ATP production in comparison with active season body temperatures (37°C). The timing of peaks of mitochondrial gene transcription was altered as were the amplitudes of transcripts coding for enzymes of the electron transport chain. Additionally, we observed changes in mean expression and timing of key metabolic genes such as SIRT1 and AMPK which are linked to the circadian system and energy balance. The amplitudes of several circadian gene transcripts were also reduced. These results reveal a link between energy conservation and a functioning circadian system in hibernation 

Repetitive elements (REs) are integral to the composition, structure, and function of eukaryotic genomes, yet remain understudied in most taxonomic groups. We investigated REs across 601 insect species and report wide variation in RE dynamics across groups. Analysis of associations between REs and protein-coding genes revealed dynamic evolution at the interface between REs and coding regions across insects, including notably elevated RE–gene associations in lineages with abundant long interspersed nuclear elements (LINEs). We leveraged this large, empirical data set to quantify impacts of long-read technology on RE detection and investigate fundamental challenges to RE annotation in diverse groups. In long-read assemblies, we detected ∼36% more REs than short-read assemblies, with long terminal repeats (LTRs) showing 162% increased detection, whereas DNA transposons and LINEs showed less respective technology-related bias. In most insect lineages, 25%–85% of repetitive sequences were “unclassified” following automated annotation, compared with only ∼13% inDrosophilaspecies. Although the diversity of available insect genomes has rapidly expanded, we show the rate of community contributions to RE databases has not kept pace, preventing efficient annotation and high-resolution study of REs in most groups. We highlight the tremendous opportunity and need for the biodiversity genomics field to embrace REs and suggest collective steps for making progress toward this goal. 

Objectives Complex physiological adaptations often involve the coordination of molecular responses across multiple tissues. Establishing transcriptomic resources for non-traditional model organisms with phenotypes of interest can provide a foundation for understanding the genomic basis of these phenotypes, and the degree to which these resemble, or contrast, those of traditional model organisms. Here, we present a one-of-a-kind gene expression dataset generated from multiple tissues of two hibernating brown bears (Ursus arctos). Data description This dataset is comprised of 26 samples collected from 13 tissues of two hibernating brown bears. These samples were collected opportunistically and are typically not possible to attain, resulting in a highly unique and valuable gene expression dataset. In combination with previously published datasets, this new transcriptomic resource will facilitate detailed investigation of hibernation physiology in bears, and the potential to translate aspects of this biology to treat human disease. 

Abstract ObjectivesComplex physiological adaptations often involve the coordination of molecular responses across multiple tissues. Establishing transcriptomic resources for non-traditional model organisms with phenotypes of interest can provide a foundation for understanding the genomic basis of these phenotypes, and the degree to which these resemble, or contrast, those of traditional model organisms. Here, we present a one-of-a-kind gene expression dataset generated from multiple tissues of two hibernating brown bears (Ursus arctos). Data descriptionThis dataset is comprised of 26 samples collected from 13 tissues of two hibernating brown bears. These samples were collected opportunistically and are typically not possible to attain, resulting in a highly unique and valuable gene expression dataset. In combination with previously published datasets, this new transcriptomic resource will facilitate detailed investigation of hibernation physiology in bears, and the potential to translate aspects of this biology to treat human disease. 

Hibernation in bears involves a suite of metabolical and physiological changes, including the onset of insulin resistance, that are driven in part by sweeping changes in gene expression in multiple tissues. Feeding bears glucose during hibernation partially restores active season physiological phenotypes, including partial resensitization to insulin, but the molecular mechanisms underlying this transition remain poorly understood. Here, we analyze tissue-level gene expression in adipose, liver, and muscle to identify genes that respond to midhibernation glucose feeding and thus potentially drive postfeeding metabolical and physiological shifts. We show that midhibernation feeding stimulates differential expression in all analyzed tissues of hibernating bears and that a subset of these genes responds specifically by shifting expression toward levels typical of the active season. Inferences of upstream regulatory molecules potentially driving these postfeeding responses implicate peroxisome proliferator-activated receptor gamma (PPARG) and other known regulators of insulin sensitivity, providing new insight into high-level regulatory mechanisms involved in shifting metabolic phenotypes between hibernation and active states.