Robust molecular subgrouping and reference-free aneuploidy detection in medulloblastoma using low-depth whole genome bisulfite sequencing.
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Medulloblastoma comprises four principal molecular disease groups and their component subgroups, each with distinct molecular and clinical features. Group assignment is currently achieved diagnostically using Illumina DNA methylation microarray. Whole-genome sequencing (WGS) capacity is rapidly expanding in the clinical setting and the development of platform-independent, sequence-based assays of molecular group offers significant potential. Specifically, whole-genome bisulfite sequencing (WGBS) enables assessment of genome-wide methylation status at single-base resolution, however its routine application has been limited by high DNA input requirements, cost, and a lack of pipelines tailored to more rapidly-acquired and cost-effective low-depth (< 10x) sequencing data. We utilised WGBS data for 69 medulloblastomas, comprising 35 in-house low-depth (~ 10x) and 34 publicly available high-depth (~ 30x) samples, alongside cerebellar controls (n = 8), all with matched DNA methylation microarray data. We assessed quality (QC) and imputation approaches using low-pass WGBS data, assessed inter-platform correlation and identified molecular groups and subgroups by directly integrating matched/associated loci from WGBS sample data with the MNP classifier probeset. We further assessed and optimised reference-free aneuploidy detection using low-pass WGBS and assessed concordance with microarray-derived calls. We developed and optimised pipelines for processing, QC, and analysis of low-pass WGBS data, suitable for routine molecular subgrouping and reference-free aneuploidy assessment. We demonstrate that low-pass WGBS data can (i) be integrated into existing array-trained models with high assignment probabilities for both principal molecular groups (97% concordance) and molecular subgroups (94.2% concordance), and (ii) detect clinically relevant focal copy number changes, including SNCAIP, with greater sensitivity than microarray approaches. Low-pass WGBS performs equivalently to array-based methods at comparable cost. Finally, its ascertainment of the full methylome enables elucidation of additional biological complexity and inter-tumoural heterogeneity that has hitherto been inaccessible. These findings provide proof-of-concept for clinical adoption of low-pass WGBS, applied using standard WGS technology.