METHODS: Studying breast cancer, we established genome-scale DNA methylation profiles of prospectively collected buffy coat samples (n = 702) from a case-control study nested within the EPIC-Heidelberg cohort using reduced representation bisulphite sequencing (RRBS).

RESULTS: We observed cancer-specific DNA methylation events in buffy coat samples. Increased DNA methylation in genomic regions associated with SURF6 and REXO1/CTB31O20.3 was linked to the length of time to diagnosis in the prospectively collected buffy coat DNA from individuals who subsequently developed breast cancer. Using machine learning methods, we piloted a DNA methylation-based classifier that predicted case-control status in a held-out validation set with 76.5% accuracy, in some cases up to 15 years before clinical diagnosis of the disease.

FINDINGS: Here, we systematically enhanced the draft genome of S. haematobium using a single-molecule and long-range DNA-sequencing approach. We achieved a major improvement in the accuracy and contiguity of the genome assembly, making it superior or comparable to assemblies for other schistosome species. We transferred curated gene models to this assembly and, using enhanced gene annotation pipelines, inferred a gene set with as many or more complete gene models as those of other well-studied schistosomes. Using conserved, single-copy orthologs, we assessed the phylogenetic position of S. haematobium in relation to other parasitic flatworms for which draft genomes were available.