Transcript capture and ultradeep long-read RNA sequencing (CAPLRseq) to diagnose HNPCC/Lynch syndrome.

Abstract

Whereas most human genes encode multiple mRNA isoforms with distinct function, clinical workflows for assessing this heterogeneity are not readily available. This is a substantial shortcoming, considering that up to 25% of disease-causing gene variants are suspected of disrupting mRNA splicing or mRNA abundance. Long-read sequencing can readily portray mRNA isoform diversity, but its sensitivity is relatively low due to insufficient transcriptome penetration. We developed and applied capture-based target enrichment from patient RNA samples combined with Oxford Nanopore long-read sequencing for the analysis of 123 hereditary cancer transcripts (capture and ultradeep long-read RNA sequencing (CAPLRseq)). Validating CAPLRseq, we confirmed 17 cases of hereditary non-polyposis colorectal cancer/Lynch syndrome based on the demonstration of splicing defects and loss of allele expression of mismatch repair genes <i>MLH1</i>, <i>PMS2</i>, <i>MSH2</i> and <i>MSH6</i>. Using CAPLRseq, we reclassified two variants of uncertain significance in <i>MSH6</i> and <i>PMS2</i> as either likely pathogenic or benign. Our data show that CAPLRseq is an automatable and adaptable workflow for effective transcriptome-based identification of disease variants in a clinical diagnostic setting.