An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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.

Revealing the mechanisms underlying the reversible physiology of hibernation could have applications to both human and animal health as hibernation is often associated with disease-like states. The present study uses RNA-sequencing to reveal the tissue and seasonal transcriptional changes occurring in grizzly bears (Ursus arctos horribilis). Comparing hibernation to other seasons, bear adipose has a greater number of differentially expressed genes than liver and skeletal muscle. During hyperphagia, adipose has more than 900 differentially expressed genes compared to active season. Hibernation is characterized by reduced expression of genes associated with insulin signaling, muscle protein degradation, and urea production, and increased expression within muscle protein anabolic pathways. Across all three tissues we find a subset of shared differentially expressed genes, some of which are uncharacterized, that together may reflect a common regulatory mechanism. The identified gene families could be useful for developing novel therapeutics to treat human and animal diseases.