Aging is associated with a systemic length-associated transcriptome imbalance

Abstract

Aging is among the most important risk factors for morbidity and mortality. To contribute toward a molecular understanding of aging, we analyzed age-resolved transcriptomic data from multiple studies. Here, we show that transcript length alone explains most transcriptional changes observed with aging in mice and humans. We present three lines of evidence supporting the biological importance of the uncovered transcriptome imbalance. First, in vertebrates the length association primarily displays a lower relative abundance of long transcripts in aging. Second, eight antiaging interventions of the Interventions Testing Program of the National Institute on Aging can counter this length association. Third, we find that in humans and mice the genes with the longest transcripts enrich for genes reported to extend lifespan, whereas those with the shortest transcripts enrich for genes reported to shorten lifespan. Our study opens fundamental questions on aging and the organization of transcriptomes.

Genome-wide RNA polymerase stalling shapes the transcriptome during aging

“…Previously, we reported the preferential loss of long gene mRNA expression in aged rodent liver and human hippocampus 29 , later also noted in fruit fly photoreceptors 30 and brain aging 31 , 32 . Therefore, we tested whether gene length is implicated in GLPT.…”

The Road Less Traveled: Uncovering the Convergence Toward Specific Pleiotropic Phenotypes in Aging

“…Recent research, including my own, has revealed that as an organism ages, its transcriptome changes in a manner that is informed by the lengths of transcript molecules. This relationship between transcript length and aging has been first observed by the lab of Jan Hoeijmakers 8 , and since then been described for C. elegans 9 , fruit flies 10 , killifish 11 , mice 8,9,[11][12][13] , rats 11 , and humans 8,11,14 . In most cases, the correlation between transcript length and age-dependent change is negative, although some tissues and cell types exhibit a positive correlation 11 .…”

“…Changes in the transcriptome during aging may affect all genes, but the most significant and reliable changes are observed in genes with the shortest and longest transcripts 8,11,13 . As I will demonstrate later in this manuscript, changes observed for the shortest transcripts may be an indirect consequence of changes in long transcripts.…”

The RNA-Seq data analysis shows how the ontogenesis defines aging

“…Currently, the RNA sequencing method has become one of the main ways to study the fundamental mechanisms of aging. In studies on age-related changes in the transcriptome, a decrease in its production during life was found ( Kang et al, 2022 ), as well as multidirectional changes in RNA production levels across individual gene groups ( Santra et al, 2019 ; Meyer and Schumacher, 2021 ; Stoeger et al, 2022 ). Summarizing the currently available data on age-associated reduction of gene expression, it can be argued that it contributes to the progressive reduction of cellular functions.…”

“…Summarizing the currently available data on age-associated reduction of gene expression, it can be argued that it contributes to the progressive reduction of cellular functions. Understanding the mechanisms that determine transcriptome aging is necessary to determine the underlying mechanisms of aging ( Stegeman and Weake, 2017 ; Lu et al, 2022 ; Stoeger et al, 2022 ). Based on our theoretical model, one of the main questions to test it is whether the level of RNA synthesis and related resources are redistributed between the functional groups of HG and IntG genes during ontogenesis.…”