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Abstract
Short tandem repeats (STRs), or microsatellites, are highly mutable genomic elements that modulate gene regulations and are implicated in a range of human diseases. However, detecting mosaic STR mutations at single-cell resolution remains challenging due to both technical and biological complexities. To address this, we developed BayesMonSTR, a robust algorithm that enables accurate detection of mosaic STR mutations. Using this tool in single-cell analysis of human tissues, we reveal an accumulation of longer mosaic STR insertions and deletions (indels) in aging mitotic and post-mitotic cells. Strikingly, prefrontal cortex (PFC) neurons accumulate a higher burden of STR mutations than B cells or lung epithelium, with aged neurons exhibiting a particularly pronounced increase in longer STR deletions. These mutations are enriched at transcription start sites (TSSs) and active enhancers of highly expressed genes. Our work establishes a foundation for genome-wide, hypothesis-free discovery of disease-associated mosaic STR mutations and reveals a previously unexplored landscape of mosaic STR variation in development and aging.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
The primary focus of this revision was to enhance the clarity and conciseness of the manuscript. The main text has been significantly streamlined to improve its flow and focus, ensuring that the core arguments and findings are presented more directly. This was achieved by condensing detailed descriptions and removing redundant phrases, resulting in a more accessible narrative without compromising the scientific integrity of the work. In line with this effort to improve clarity and focus, the number of figures has been reduced. The figure set has been carefully curated to retain only the most essential data that directly support the main conclusions of the study. Supplementary figures are now referenced where appropriate to provide additional supporting data for the interested reader. Finally, this revision corrects several typographical and grammatical errors identified throughout the text. Addressing these minor errors polishes the manuscript and ensures that the scientific content is communicated with greater precision and professionalism.
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