Repetitive elements as a transcriptomic marker of aging: Evidence in multiple datasets and models

Abstract

Transcriptomic markers of aging can be useful for studying age-related processes and diseases. However, noncoding repetitive element (RE) transcripts, which may play an important role in aging, are commonly overlooked in transcriptome studies—and their potential as a transcriptomic marker of aging has not been evaluated. Here, we used multiple RNA-seq datasets generated from human samples and Caenorhabditis elegans and found that most RE transcripts (a) accumulate progressively with aging; (b) can be used to accurately predict age; and (c) may be a good marker of biological age. The strong RE/aging correlations we observed are consistent with growing evidence that RE transcripts contribute directly to aging and disease.