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One important question in aging research is how differences in genomics and transcriptomics determine the maximum lifespan in various species. Despite recent progress, much is still unclear on the topic, partly due to the lack of samples in nonmodel organisms and due to challenges in direct comparisons of transcriptomes from different species. The novel ranking‐based method that we employ here is used to analyze gene expression in the gray whale and compare its de novo assembled transcriptome with that of other long‐ and short‐lived mammals. Gray whales are among the top 1% longest‐lived mammals. Despite the extreme environment, or maybe due to a remarkable adaptation to its habitat (intermittent hypoxia, Arctic water, and high pressure), gray whales reach at least the age of 77 years. In this work, we show that long‐lived mammals share common gene expression patterns between themselves, including high expression of DNA maintenance and repair, ubiquitination, apoptosis, and immune responses. Additionally, the level of expression for gray whale orthologs of pro‐ and anti‐longevity genes found in model organisms is in support of their alleged role and direction in lifespan determination. Remarkably, among highly expressed pro‐longevity genes many are stress‐related, reflecting an adaptation to extreme environmental conditions. The conducted analysis suggests that the gray whale potentially possesses high resistance to cancer and stress, at least in part ensuring its longevity. This new transcriptome assembly also provides important resources to support the efforts of maintaining the endangered population of gray whales. [ABSTRACT FROM AUTHOR]

Caloric restriction ( CR), a reduction in calorie intake without malnutrition, retards aging in several animal models from worms to mammals. Developing CR mimetics, compounds that reproduce the longevity benefits of CR without its side effects, is of widespread interest. Here, we employed the Connectivity Map to identify drugs with overlapping gene expression profiles with CR. Eleven statistically significant compounds were predicted as CR mimetics using this bioinformatics approach. We then tested rapamycin, allantoin, trichostatin A, LY-294002 and geldanamycin in Caenorhabditis elegans. An increase in lifespan and healthspan was observed for all drugs except geldanamycin when fed to wild-type worms, but no lifespan effects were observed in eat-2 mutant worms, a genetic model of CR, suggesting that life-extending effects may be acting via CR-related mechanisms. We also treated daf-16 worms with rapamycin, allantoin or trichostatin A, and a lifespan extension was observed, suggesting that these drugs act via DAF-16-independent mechanisms, as would be expected from CR mimetics. Supporting this idea, an analysis of predictive targets of the drugs extending lifespan indicates various genes within CR and longevity networks. We also assessed the transcriptional profile of worms treated with either rapamycin or allantoin and found that both drugs use several specific pathways that do not overlap, indicating different modes of action for each compound. The current work validates the capabilities of this bioinformatic drug repositioning method in the context of longevity and reveals new putative CR mimetics that warrant further studies. [ABSTRACT FROM AUTHOR]

One of the important questions in aging research is how differences in transcriptomics are associated with the longevity of various species. Unfortunately, at the level of individual genes, the links between expression in different organs and maximum lifespan (MLS) are yet to be fully understood. Analyses are complicated further by the fact that MLS is highly associated with other confounding factors (metabolic rate, gestation period, body mass, etc.) and that linear models may be limiting. Using gene expression from 41 mammalian species, across five organs, we constructed gene-centric regression models associating gene expression with MLS and other species traits. Additionally, we used SHapley Additive exPlanations and Bayesian networks to investigate the non-linear nature of the interrelations between the genes predicted to be determinants of species MLS. Our results revealed that expression patterns correlate with MLS, some across organs, and others in an organ-specific manner. The combination of methods employed revealed gene signatures formed by only a few genes that are highly predictive towards MLS, which could be used to identify novel longevity regulator candidates in mammals. [ABSTRACT FROM AUTHOR]