Uncovering Mosaic Tandem Repeats and Structural Variants with Long-Read Sequencing

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In this upcoming Bioinformatics and Computational Methods Shared Interest Group (SIG) Seminar, Dr. Fritz Sedlazeck will present on mosaic structural variants (SVs) and tandem repeat (TR) mutations, as well as introduce a new extension of Sniffles, an SV caller.

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Description

Dr. Fritz Sedlazeck will present his recent work in this upcoming Bioinformatics and Computational Methods Shared Interest Group (SIG) Seminar.

Mosaic variants, which arise post-zygotically, are increasingly recognized as important contributors to human disease, yet remain understudied, particularly within repetitive and structurally complex regions of the genome. In this talk, Fritz Sedlazeck will present their latest findings on mosaic structural variants (SVs) and tandem repeat (TR) mutations, uncovered through long-read sequencing of human tissues. They describe novel benchmarking and detection frameworks that enable high-resolution assessment of mosaic variation across variant types. In the second half, he will introduce a new extension of Sniffles, their widely used SV caller, enabling the discovery of cell type–specific SVs from bulk long-read data by leveraging coverage patterns and breakpoint sharing across tissues. These innovations push the boundaries of mosaic variant detection and open new avenues for linking somatic variation to tissue-specific biology and disease. 

Overview of Presentation:

  • Understand how long-read sequencing technologies enable the detection of complex and repetitive variants with high resolution.  
  • Learn about the biological significance and detection strategies for mosaic mutations, including those occurring in structural and tandem repeat regions.  
  • Gain insight into approaches for cell type deconvolution using bulk long-read sequencing data to identify cell type-specific structural variants.  
  • Explore the role of tandem repeat variation, particularly mosaic TR mutations, in genomic diversity and disease risk.