Combined genomic and phenotypic classification of inherited and acquired genetic disease with long-read sequencing

Current long read sequencing (LRS) platforms allow the simultaneous detection of both genetic variation and epigenetic modification, yet in most cases only genetic variation is utilised. Here we demonstrate the additional potential utility of methylation-based cell type deconvolution and outlier detection, using LRS data from two different platforms. This approach could reliably estimate the proportions of the most abundant cellular constituents of human blood and peripheral blood mononuclear cells, using either primary samples or synthetic mixtures of data from purified cells. Using samples from patients with a hematological malignancy (B cell chronic lymphocytic leukemia) or immunodeficiency (X-linked agammaglobulinemia), LRS resolved both the disease-associated variant and primary cellular phenotype in a single assay. The LRS approach yielded similar cell proportion estimates to orthogonal scRNAseq data generated on the same samples. LRS-derived methylation data therefore represents an incidental source of phenotypic data, with potential future utility in genomic discovery in population-scale biobanks, and in the investigation of inherited and acquired genetic disease.