Accurate detection of tandem repeats exposes ubiquitous reuse of biological sequences.

Tandem repetition is one of the major processes underlying genome evolution and phenotypic diversification. While newly formed tandem repeats are often easy to identify, it is more challenging to detect repeat copies as they diverge over evolutionary timescales. Existing programs for finding tandem repeats return markedly different results, and it is unclear which predictions are more correct and how much room remains for improvement. Here, we introduce DetectRepeats, a new method that uses empirical information about structural repeats to improve the accuracy of repeat detection. We show that DetectRepeats advances the state-of-the-art by finding highly divergent repeats with relatively few false positive detections. We apply DetectRepeats to genomes across the tree of life to discover an enrichment of detectable tandem repeats within different genes, genome regions, and taxa. Furthermore, we use phylogenetic reconciliation to determine that some tandem repeats continue to evolve through intra-repeat unit replacement. In this manner, tandem repeats serve as a renewable genetic resource offering a bountiful source of alternative genetic material. Our work unlocks the confident detection of ancient tandem repeats, opening a doorway to future discoveries. DetectRepeats is part of the DECIPHER package for the R programming language and available via Bioconductor.