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Molecular signatures of healthy ageing in long-lived rodents
Secondary Supervisor(s): Dr Hannah Bridgewater (Warwick)
University of Registration: Coventry University
BBSRC Research Themes: Integrated Understanding of Health (Ageing)
Project Outline
Ageing, the progressive decline of function with age, is almost ubiquitous in the animal kingdom. Our understanding of the causes of ageing stems to a large extent from studies on short-lived model organisms, such as worms, mice, humans and fruit flies. However, more recently, ageing researchers have begun to appreciate the value of investigating long-lived organisms that show very limited symptoms of senescence, such as the naked mole-rat (NMR), which may allow us to find ways of improving healthy ageing in humans. In fact, maximum lifespan (MLS) varies greatly within rodents, from 4 years in mice and rats to over 10 years in several south American species, such as nutria, chinchilla and guinea pig. Therefore, although the extremely long-lived NMRs (MLS > 30 years) offer invaluable insight into ageing diseases, a holistic view into the broad variation in lifespan within rodents is important for discovering more general molecular signatures of longevity in mammals.
Objective
This research aims to investigate the fundamental genomic and transcriptomic signatures of longevity in rodents to gain insights into improving healthy ageing in humans.
Approach
Genomics: All available, high quality rodent genome assemblies (currently 45, NCBI, accessed October 2024) will be comparatively analysed in a phylogenetic context. These evolutionary analyses will include gene family size evolution, domain rearrangements, evolutionary rate analysis and the investigation of selection patterns. All genomic signatures will be correlated to maximum lifespans of rodent lineages to identify the most informative molecular traits for investigating genomic footprints of healthy ageing in rodents.
Transcriptomics: In parallel, novel tissue- and age-specific transcriptomes will be generated for three mole-rat species with varying MLS: NMR (> 30 years), Damaraland mole-rat (DMR, 15 years) and blind mole-rat (BMR, 21 years), provided by Prof Sumbera, University of South Bohemia (Czech Republic). These will be created for liver, skin and skeletal muscle tissues from different aged individuals and supplemented with similar, published data sets of other rodent species. Various transcriptomic traits will be investigated in relation to absolute and relative age, i.e. individual age in relation to species-specific MLS. These traits will include age- and species-specific variation in gene expression, co-expression network structure, expression noise and alternative splicing.
Machine Learning: Deep neural networks will be developed that can reliably predict the age of an individual or MLS of a species based on genomic features and/or expression profile. This tool will then be employed to identify the most informative genomic and transcriptomic traits in making these predictions of age.
Genetic testing: Thus, identified genomic traits that are strongly related to longevity in long-lived rodents will be functionally tested in mouse and human cell lines, led by Dr Hannah Bridgewater at University of Warwick. Depending on the genetic target a gene-editing/regulating experiment will be designed and performed. For example, if the rodents with a longer MLS show a decrease in the lead gene, then siRNA is likely to be successful; If the gene is more highly activated then CRISPRa would be the preferred methodology.
Expected Outcomes
With this study we expect to identify universal genomic footprints of longevity, both within and outside of protein coding regions. Specifically, we expect to find these molecular signatures within pathways that are integral to the canonical hallmarks of ageing, such as nutrient sensing, mitochondrial activity, DNA repair, cell-cycle, and transcriptional regulation, as well as, so-far unappreciated molecular mechanisms. The implications of this research are far-reaching, opening up new avenues of research into revealing the secrets to healthy ageing in humans.
Key References
Sahm, et al. Aging 10.12 (2018): 3938.
Harrison, et al. GenBioEvo 13.6 (2021): evab093.
