Suzanne de Bruijn

53 The impact of modern technologies on molecular diagnostics Missense, synonymous, indel and intronic variants Substitution variants located in the coding (exonic) or non-coding (intronic) regions of a gene are more difficult to interpret. Missense variants and small in-frame insertions or deletions (indels) lead to changes in amino acid composition. Several computational tools have been developed to aid in the assessment of deleterious consequences of the identified variants. Output scores provided by these tools are usually based on the evolutionary conservation of the altered nucleotide or amino acid residues, biochemical consequences of the amino acid change, or the location and context of the residue within the protein sequence e.g. in a domain with a specific function. Most widely applied tools are Combined Annotation-Dependent Depletion (CADD) 129 , Grantham 130 , MutationTaster 131 , phyloP 132 , PolyPhen-2 133 and Sorting Intolerant FromTolerant (SIFT). 134 Alternatively, synonymous, missense and (deep)-intronic variants can disrupt the normal splicing machinery and alter pre-mRNA processing. Variants can introduce or strengthen cryptic splice sites, disrupt canonical donor or acceptor splice sites or disrupt the (binding) motifs that are essential for correct splicing processes, such as exonic splicing enhancers or silencers. 101 This can lead to alternative splicing events, such as pseudo-exon inclusion, exon elongation or (partial) exon skipping. Potential splice-altering variants can be evaluated based on nucleotide conservation scores or by performing splicing assessments using predictive splicing algorithms, such as Human Splicing Finder 135 , SpliceSiteFinder‐like 136 , MaxEntSCan 137 , GeneSplicer 138 , NNSPLICE 139 and SpliceAI, a deep learning algorithm. 140 In vitro midi- or minigene splice assays can be performed to confirm the predicted alternative splicing events in HEK293T cells or, if transcript levels allow, aberrant splicing can be detected in RNA derived from (EBV- transformed) blood cells. 141 142 Onepitfall of splicesiteprediction tools is tissue-specific splicingof exons,whichprevents most current prediction tools from detecting cochlear or retina-specific splicing effects. Recently, Riepe et al. benchmarked different established and deep-learning tools on sets of variants in tissue-specific genes ABCA4 and MYBPC3 and observed that SpliceAI is the best performing splice prediction tool for both non-canonical splice site and deep- intronic variants in ABCA4 . 143 Moreover, Rowlands et al. compared seven machine and deep learning-based splice prediction tools and demonstrated that SpliceAI is superior in both sensitivity and specificity. 144 Regulatory variants Variants located in intergenic and intronic regions of the genome can exert their pathogenic effect through a variety of mechanisms. Variation can occur within characterized cis regulatory elements (CREs), such as promoters, enhancers, or