Gene Expression

Transcriptional signatures of ageing

We performed a meta-analysis of gene expression changes with age using microarray and RNA-Seq data across different tissues from mice, rats, and humans. Our results identify genes and processes consistently over- or under expressed with age and reveal previously unknown transcriptional changes with age, as further described elsewhere.

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Cellular senescence signatures

Cellular senescence, the irreversible cessation of cell division of normally proliferating cells, has been associated with ageing and age-related diseases like cancer. We performed a meta-analysis of microarray studies of senescence in human cells to identify cellular senescence signature genes, as described elsewhere. These signatures have been integrated into our CellAge database.

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Common transcriptional signatures of caloric restriction

Caloric restriction (CR), a reduction in calorie intake without malnutrition, retards age-related degeneration and extends lifespan in several organisms. We performed a meta-analysis of CR microarray studies in mammals to obtain a comprehensive picture of CR-induced changes. The common signatures of CR identified reveal genes and processes robustly altered due to CR, as described elsewhere.

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Whole Transcriptome Sequencing Reveals Dynamic RNA Changes in the Aging Rat Brain

Using RNA-seq to sequence the cerebral cortex transcriptome in young, middle aged and old rats, thirty-nine protein-coding genes were identified as differentially expressed (DE) with age.

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Tau Index of Gene Tissue Specificity

Using gene expression data, we calculated the tau index for human each gene and transcript, providing a measure of how specifically expressed each gene is in human tissues.

Full dataset and details are available.

A Web Portal of Age-Related Changes

We are developing a web portal that will integrate molecular, cellular and physiological age-related data. Our goal is to integrate various types of age-related changes, including changes ascertained by high-throughput technologies like microarrays. Although GenAge is a powerful resource for understanding the genetic basis of ageing, it does not typically include genes differently expressed between young and old tissues. In this project we want to incorporate microarray data. In a sense we aim to create an expO equivalent for ageing research based on current efforts such as Gene Expression Omnibus (GEO), ArrayExpress and Gene Aging Nexus (GAN), as well as published studies. Including physiological and tissue-level changes, like hormonal alterations, is also in our plans as we aim to create a repository of alterations with age.

By integrative age-related changes at various biological levels, our goal is not merely to describe those changes but primarily to help understand the mechanisms driving ageing changes and how they are translated into pathology. In other words, discriminate causes from effects of ageing in an attempt to interpret the origins of human ageing. We anticipate that this new resource will be valuable for researchers to relate age-related changes at different biological levels as well as develop quantitative models of ageing to obtain new insights, the so-called "systems biology paradigm".

This project is still in its initial stages and is considered work-in-progress. We anticipate to have a working portal later in 2009. If you wish to share your data with us or collaborate/contribute to this project, please contact us. This project is funded by the Biotechnology and Biological Sciences Research Council (BBSRC).


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