The 37 Italian patient-parents trios and German patients underwent whole-exome sequencing (WES). Exome library capture and enrichment was performed with BGI kit (BGI Genomics, n = 104) or the NimbleGen SeqCap EZ (Roche, n = 7) and sequenced as paired-end reads with an Illumina system. As previously described,23 sequencing reads were processed to obtain annotated variant calls and retain for downstream analyses only variants located in coding exons or canonical splice-site junctions. Guidelines for sequence variant interpretation of the American College of Medical Genetics (ACMG)24 were followed for clinical classification of variants in established epilepsy genes by using the online platform Varsome (https://varsome.com/).
We calculated the mean rate of de novo variants (DNVs) in the main variant classes (missense, nonsense, splicing affecting, frame-shift, in-frame indels and synonymous single nucleotide variants) and used for comparison data from a large control cohort of 1911 trios previously published.25 Although we did not formally account for differences in variant discovery workflows,25 they have similarities in both enrichment methods and bioinformatic pipelines.
To select candidate FE genes, we used the following criteria: (i) the DNV has allele count ≤1 across control samples in the genome aggregation database (gnomAD) data set v2.1.1 including counts on 60146 chromosomes; (ii) the DNV has CADD Phred score (v1.4) ≥ 15; (iii) the gene is expressed in brain according to the Human Protein Atlas and Human Allen Brain Atlas databases; (iv) the encoded protein is important for brain development and function based on NCBI Entrez Gene Summary and UniprotKB databases as well as bibliographic research; and (v) the gene is intolerant to variation according to gnomAD v2.1.1 measures for genetic constraints (missense Z score > 3 and/or pLI > 0.9) or already associated with epileptic seizures in humans.
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