Abstract
Detection of 3' PMS2 copy-number mutations that cause Lynch syndrome is difficult because of highly homologous pseudogenes. To improve the accuracy and efficiency of clinical screening for these mutations, we developed a new method to analyze standard capture-based, next-generation sequencing data to identify deletions and duplications in PMS2 exons 9 to 15. The approach captures sequences using PMS2 targets, maps sequences randomly among regions with equal mapping quality, counts reads aligned to homologous exons and introns, and flags read count ratios outside of empirically derived reference ranges. The method was trained on 1352 samples, including 8 known positives, and tested on 719 samples, including 17 known positives. Clinical implementation of the first version of this method detected new mutations in the training (N = 7) and test (N = 2) sets that had not been identified by our initial clinical testing pipeline. The described final method showed complete sensitivity in both sample sets and false-positive rates of 5% (training) and 7% (test), dramatically decreasing the number of cases needing additional mutation evaluation. This approach leveraged the differences between gene and pseudogene to distinguish between PMS2 and PMS2CL copy-number mutations. These methods enable efficient and sensitive Lynch syndrome screening for 3' PMS2 copy-number mutations and may be applied similarly to other genomic regions with highly homologous pseudogenes.