Gray whale transcriptome reveals longevity adaptations associated with DNA repair and ubiquitination

Abstract

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.

Alternative Animal Models of Aging Research

“…This gene plays a dual role in autophagy and DNA repair and is present in multiple copies in the genomes of the sperm whale, North Atlantic right whale, and bowhead whale (Tollis et al, 2019). Consistently, quantitative transcriptome analysis revealed up-regulation of genes for DNA repair and autophagy in the gray whale (Toren et al, 2020). Finally, analysis of coding sequence variation independently identified positive selection on DNA repair/cancer suppression genes (Tollis et al, 2019).…”

“…In summary, the insights gained from genomic cetacean studies suggest that molecular adaptations in DNA repair genes played a key role in the evolution of cancer resistance and longevity in these species. Crucial resource requirements for these and presumably future findings were the initial sequencing of the B. mysticetus genome (Seim et al, 2014;Keane et al, 2015) which was followed by sequencing of the minke whale (Balaenoptera acutorostrata; Yim et al, 2014;Park et al, 2015;Malde et al, 2017), the gray whale (Eschrichtius robustus; Moskalev et al, 2017;Toren et al, 2020), the humpback whale (Megaptera novaeangliae; Tollis et al, 2019) and the largest mammal, the blue whale (Balaenoptera musculus; Árnason et al, 2018). As with other animals that cannot be kept for obvious reasons, a key challenge for the future is to identify experimental approaches that can be used to verify hypotheses derived from such comparative studies with regard to transferability to humans.…”

Footprints in the Sand: Deep Taxonomic Comparisons in Vertebrate Genomics to Unveil the Genetic Programs of Human Longevity

“…This comparative genomic approach has proven to be a powerful and efficient tool to refine genetic signals of complex phenotypic traits, ranging from echolocation ( Parker et al, 2013 ) to vitamin synthesis ( Hiller et al, 2012 ). As an additional approach, transcriptomes of diverse species have been generated in order to understand changes in gene expression in organisms with varied lifespans (e.g., Seim et al, 2014 ; Toren et al, 2020 ; Kulaga et al, 2021 ). While providing in depth analysis about differential regulation of gene expression, the results of these methods are centered on particular tissues, ages, and genetic contexts, which will introduce confounding variables into multispecies comparisons.…”

Machine Learning Analysis of Longevity-Associated Gene Expression Landscapes in Mammals

“…Recent studies demonstrated that differences in gene expression between long- and short-living mammals exist [ 7 , 8 , 9 , 10 ]. In particular, some of the longest-lived mammals display enhanced expression of genes related to DNA maintenance and repair, ubiquitination, immune responses, apoptosis, and autophagy [ 11 ]. The overexpression of DNA repair genes is also confirmed by cross-species cell culture profiling [ 12 ].…”

“…For at least 33 mammalian species the expression of immune response genes in the liver, kidney, and brain shows positive correlations with MLS [ 9 ]. There is also clear evidence of pro-longevity transcriptomic adaptations in long-living species such as bats [ 13 ], naked mole rats [ 8 , 14 ], and whales [ 7 , 11 ].…”