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.

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.

The brown bear (Ursus arctos) is the second largest and most widespread extant terrestrial carnivore on Earth and has recently emerged as a medical model for human metabolic diseases. Here, we report a fully phased chromosome-level assembly of a male North American brown bear built by combining Pacific Biosciences (PacBio) HiFi data and publicly available Hi-C data. The final genome size is 2.47 Gigabases (Gb) with a scaffold and contig N50 length of 70.08 and 43.94 Megabases (Mb), respectively. Benchmarking Universal Single-Copy Ortholog (BUSCO) analysis revealed that 94.5% of single copy orthologs from Mammalia were present in the genome (the highest of any ursid genome to date). Repetitive elements accounted for 44.48% of the genome and a total of 20,480 protein coding genes were identified. Based on whole genome alignment to the polar bear, the brown bear is highly syntenic with the polar bear, and our phylogenetic analysis of 7,246 single-copy orthologs supports the currently proposed species tree for Ursidae. This highly contiguous genome assembly will support future research on both the evolutionary history of the bear family and the physiological mechanisms behind hibernation, the latter of which has broad medical implications.

Understanding how metabolic reprogramming happens in cells will aid the progress in the treatment of a variety of metabolic disorders. Brown bears undergo seasonal shifts in insulin sensitivity, including reversible insulin resistance in hibernation. We performed RNA-sequencing on brown bear adipocytes and proteomics on serum to identify changes possibly responsible for reversible insulin resistance. We observed dramatic transcriptional changes, which depended on both the cell and serum season of origin. Despite large changes in adipocyte gene expression, only changes in eight circulating proteins were identified as related to the seasonal shifts in insulin sensitivity, including some that have not previously been associated with glucose homeostasis. The identified serum proteins may be sufficient for shifting hibernation adipocytes to an active-like state.