DNA double helix is altered as it goes through an hourglass, representing the effects of aging on gene expression. Image credit: Olga Ibañez-Solé and Ainhoa Irastorza (CC BY 4.0)
The human body contains hundreds of different cell types which vary greatly in shape and size despite all sharing the same genetic material. This is because each cell switches on, or ‘expresses’, a unique set of genes that gives them a specific identity, such as becoming a nerve or a muscle cell.
Recent studies have shown that cells in some tissues tend to lose their identity with age, and activate some of the genes that define them less strongly. This results in seemingly identical cells expressing the same genes in a more variable way, a phenomenon commonly referred to as noise.
A technique called single-cell RNA sequencing is typically used to measure the activity of genes in individual cells, and has been used to study the role of noise in a wide range of aging tissues. However, the results of these studies have been analyzed using different computational methods, making it difficult to make comparisons between tissues and organisms. This has led to an ongoing debate about whether increased noise is a signature feature of aging, and if it is experienced throughout the body or restricted to certain cell types.
To overcome this, Ibáñez-Solé, Ascensión et al. developed two new computational tools for analyzing noise and changes in cell identity: these were then applied to seven unique sequencing datasets which had been collected from various tissues in humans and mice at different ages.
While there were some differences in the level of noise between young and old cells, these changes were not consistent across tissues and organisms. In contrast, other features associated with aging were consistently found in each of the sequencing datasets.
The role of noise in aging has been gaining increasingly more attention in the scientific literature. However, the findings of Ibáñez-Solé, Ascensión et al. suggest that this phenomenon is not a hallmark of the aging process, and that the field should focus on other factors that reduce the health of tissues and cells as organisms get older. The computational approach they developed could also be used to evaluate the role of noise in other contexts, such as certain diseases.
