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bioRxiv · 10.64898/2026.04.08.717017

Long-read analysis of tetrameric microsatellites with vmwhere supports GGAA repeat length-dependent chromatin state association in Ewing sarcoma

Peterson, S. K.·Massie, A. M.·Rubinsteyn, A.·Wang, J. R.·Davis, I. J.
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Abstract

Microsatellites are abundant genomic elements that contribute to genetic diversity and disease-associated regulatory variation. Although long-read sequencing enables accurate resolution of repetitive regions, computational methods for fully resolved microsatellite genotyping remain limited. Here, we introduce variant motif where (vmwhere), a computational framework for identifying, genotyping, decomposing, and visualizing complex tetrameric microsatellites from long-read sequencing data. Using simulated error-free reads, vmwhere accurately measures several genotyping metrics, including allele length, repeat length, maximum consecutive repeat length, and motif density. Applied to long-read whole-genome sequencing data, vmwhere identified sequence interruptions, motif-specific differences in repeat architecture, and ancestry-associated allele variation, including long repeat alleles that exceed short-read sequencing limitations. We applied vmwhere to GGAA microsatellites in Ewing sarcoma, an aggressive pediatric cancer driven by EWS-FLI1 fusion oncoprotein, which binds to microsatellites and remodels chromatin. Genome-wide integration of long-read-defined microsatellite architecture with chromatin accessibility and EWS-FLI1 binding revealed that GGAA repeat structure was associated with chromatin state, with longer consecutive repeat microsatellites exhibiting increased EWS-FLI1 binding and chromatin accessibility. Cell line-specific expansions and contractions of GGAA microsatellite repeat length were associated with gains and losses of chromatin accessibility. Further, we identified haplotype-specific chromatin states, with preferential binding and accessibility at longer alleles. Together, these results establish vmwhere as a scalable framework for resolving population-level microsatellite variation and linking repeat architecture to chromatin state. Repeat structure and length characteristics provides insights into genotype-function relationships at microsatellite repeats in cancer.

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Peterson, S. K., Massie, A. M., Rubinsteyn, A., Wang, J. R., Davis, I. J.. 2026-04-10. Long-read analysis of tetrameric microsatellites with vmwhere supports GGAA repeat length-dependent chromatin state association in Ewing sarcoma. https://doi.org/10.64898/2026.04.08.717017

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