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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. 

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. 

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).

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 Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals 1 . These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample. 

Abstract The short arms of the human acrocentric chromosomes 13, 14, 15, 21 and 22 (SAACs) share large homologous regions, including ribosomal DNA repeats and extended segmental duplications 1,2 . Although the resolution of these regions in the first complete assembly of a human genome—the Telomere-to-Telomere Consortium’s CHM13 assembly (T2T-CHM13)—provided a model of their homology 3 , it remained unclear whether these patterns were ancestral or maintained by ongoing recombination exchange. Here we show that acrocentric chromosomes contain pseudo-homologous regions (PHRs) indicative of recombination between non-homologous sequences. Utilizing an all-to-all comparison of the human pangenome from the Human Pangenome Reference Consortium 4 (HPRC), we find that contigs from all of the SAACs form a community. A variation graph 5 constructed from centromere-spanning acrocentric contigs indicates the presence of regions in which most contigs appear nearly identical between heterologous acrocentric chromosomes in T2T-CHM13. Except on chromosome 15, we observe faster decay of linkage disequilibrium in the pseudo-homologous regions than in the corresponding short and long arms, indicating higher rates of recombination 6,7 . The pseudo-homologous regions include sequences that have previously been shown to lie at the breakpoint of Robertsonian translocations 8 , and their arrangement is compatible with crossover in inverted duplications on chromosomes 13, 14 and 21. The ubiquity of signals of recombination between heterologous acrocentric chromosomes seen in the HPRC draft pangenome suggests that these shared sequences form the basis for recurrent Robertsonian translocations, providing sequence and population-based confirmation of hypotheses first developed from cytogenetic studies 50 years ago 9 .