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Peter Durairaj, R. R.

Publications and source records attributed to Peter Durairaj, R. R..

2 recordsLinked to original sources

Targeted sequencing of expanded tandem repeats: Identifying interruptions and errors

Expanded repeat disorders remain without a disease modifying treatment. Some of the most important modifiers of disease severity include inherited repeat size, their somatic mosaicism, and whether they contain interruptions. Targeted sequencing approaches are becoming the gold standard on how these parameters are measured despite repeats being notoriously challenging to sequence. Here we developed CHARLIE (Comprehensive High-throughput Analysis of Repeat Length, Interruptions and Expansions) to identify and position interruptions within expanded repeats. We used samples from Huntingtons disease and myotonic dystrophy type 1 sequenced with Illumina MiSeq and PacBios Single-Molecule Real-Time Sequencing. We validated the pipeline against previous methods for identifying germline-inherited interruptions. One challenge that can potentially mask the identification of true interruptions and sequence variation is the accuracy of sequencing platforms, which, when applied to expanded repeats, is largely unknown. Our results suggest that each sequencing platform produces a distinct error profile and we show that PCR-free library preparation for SMRT sequencing improves sequencing accuracy. CHARLIE, therefore, provides a method that can help differentiate between trivial sequencing errors and those interruptions that modify disease presentation, which can be inherited or somatic in origin.

bioinformatics↗

SCIA: A fast and widely applicable pipeline for measuring expanded repeat instability

The expansion of short tandem repeats is a feature of over 60 different human diseases. Ongoing somatic instability throughout a patients lifetime can influence disease progression and has emerged as a therapeutic target. Understanding its mechanism is essential for the identification of both drug targets and therapeutic interventions. A major obstacle towards this translational goal has been to measure changes in repeat size distribution given that these are complex datasets. To address this, here we provide a new analysis method, and accompanying software, that generates delta plots, extracts the instability frequency from targeted long-read sequencing data, the bias towards expansion or contraction, and the average size of the changes. It further provides statistical analysis for comparison between treatments. We show its applicability to non-dividing cells, and in vivo datasets. Moreover, we have developed a streamlined experimental design for dividing cells, Single Clone-based Instability Assay (SCIA), that saves weeks in assessing the effect of a gene knockout on repeat instability and is ideal for an initial screen. We have validated the approach using FAN1, PMS1, and MLH1 knockouts. Using SCIA, we find that although FAN1 knockout clones showed increased frequency of expansions, the size of the expansions were smaller. This highlights the wealth of information that can be extracted and the potential for novel insights into the mechanism of repeat instability.

neuroscience↗