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.

Authors

Institutions

Publication Details

Journal
Nucleic Acids Research
Published
2025-08-16
DOI
https://doi.org/10.1093/nar/gkaf866
Citations
3
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
2.42

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Accurate detection of tandem repeats exposes ubiquitous reuse of biological sequences

Erik S. Wright, Shu‐Ting Cho
3 citations
Nucleic Acids Research
Genomics and Phylogenetic Studies
2.42
article

Accurate detection of tandem repeats exposes ubiquitous reuse of biological sequences

Erik S. Wright, Shu‐Ting Cho
article en
3 citations

Abstract

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.

Nucleic Acids ResearchVol. 53(17)
University of Pittsburgh (US), Evolutionary Genomics (United States) (US), Computational Diagnostics (United States) (US), Institut de Biologia Evolutiva (ES), Joint Institute for Computational Sciences (US)
National Institutes of Health, National Institute of Allergy and Infectious Diseases
Openalex Percentile: Top 10%
Genomics and Phylogenetic Studies
2.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.