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

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.