RT Journal Article
SR Electronic
T1 Detecting tandem repeat expansions in cohorts sequenced with short-read sequencing data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 157792
DO 10.1101/157792
A1 Rick M Tankard
A1 Mark F Bennett
A1 Peter Degorski
A1 Martin B Delatycki
A1 Paul J Lockhart
A1 Melanie Bahlo
YR 2018
UL http://biorxiv.org/content/early/2018/07/25/157792.abstract
AB Repeat expansions cause over 30, predominantly neurogenetic, inherited disorders. These can present with overlapping clinical phenotypes, making molecular diagnosis challenging. Single gene or small panel PCR-based methods are employed to identify the precise genetic cause, but can be slow and costly, and often yield no result. Genomic analysis via whole exome and whole genome sequencing (WES and WGS) is being increasingly performed to diagnose genetic disorders. However, until recently analysis protocols could not identify repeat expansions in these datasets.A new method, called exSTRa (expanded Short Tandem Repeat algorithm) for the identification of repeat expansions using either WES or WGS was developed and performance of exSTRa was assessed in a simulation study. In addition, four retrospective cohorts of individuals with eleven different known repeat expansion disorders were analysed with the new method. Results were assessed by comparing to known disease status. Performance was also compared to three other analysis methods (ExpansionHunter, STRetch and TREDPARSE), which were developed specifically for WGS data. Expansions in the STR loci assessed were successfully identified in WES and WGS datasets by all four methods, with high specificity and sensitivity, excepting the FRAXA STR where expansions were unlikely to be detected. Overall exSTRa demonstrated more robust/superior performance for WES data in comparison to the other three methods. exSTRa can be applied to existing WES or WGS data to identify likely repeat expansions and can be used to investigate any STR of interest, by specifying location and repeat motif. We demonstrate that methods such as exSTRa can be effectively utilized as a screening tool to interrogate WES data generated with PCR-based library preparations and WGS data generated using either PCR-based or PCR-free library protocols, for repeat expansions which can then be followed up with specific diagnostic tests. exSTRa is available via GitHub (https://github.com/bahlolab/exSTRa).