Combined bioinformatic and splicing analysis of likely benign intronic and synonymous variants reveals evidence for pathogenicity.

Purpose: Clinical variant analysis pipelines likely have poor sensitivity to the effects on splicing from variants beyond 10 to 20 bases of exon-intron boundaries. Here, we demonstrate the value of SpliceAI to inform curation of rare variants previously classified as benign/likely benign (B/LB) under current guidelines.

Methods: Exome sequencing data from 576 pediatric cancer patients enrolled in the Texas KidsCanSeq study were filtered for intronic or synonymous variants absent from population databases, predicted to alter splicing via SpliceAI (>0.

A first-generation genome-wide map of correlated DNA methylation demonstrates highly coordinated and tissue-independent clustering across regulatory regions.

Genome-wide DNA methylation studies have typically focused on quantitative assessments of CpG methylation at individual loci. Although methylation states at nearby CpG sites are known to be highly correlated, suggestive of an underlying coordinated regulatory network, the extent and consistency of inter-CpG methylation correlation across the genome, including variation between individuals, disease states, and tissues, remains unknown. Here, we leverage image conversion of correlation matrices to identify correlated methylation units (CMUs) across the genome, describe their variation across tissues, and annotate their regulatory potential using 35 public Illumina BeadChip datasets spanning more than 12,000 individuals and 26 different tissues.