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. 2020 Apr 24;12(1):36.
doi: 10.1186/s13073-020-00737-2.

Clinical impact of splicing in neurodevelopmental disorders

Stephan J Sanders  1 , Grace B Schwartz  2 , Kyle Kai-How Farh  3
Affiliations

Clinical impact of splicing in neurodevelopmental disorders

Stephan J Sanders et al. Genome Med. .

Abstract

Clinical exome sequencing is frequently used to identify gene-disrupting variants in individuals with neurodevelopmental disorders. While splice-disrupting variants are known to contribute to these disorders, clinical interpretation of cryptic splice variants outside of the canonical splice site has been challenging. Here, we discuss papers that improve such detection.

Keywords: Antisense oligonucleotide; Autism spectrum disorder; Canonical splice site; Clinical exome sequencing; Cryptic splice site; Developmental delay; Gene splicing; Isoform; Polypyrimidine tract; SpliceAI.

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Conflict of interest statement

K.K.F. was employed by Illumina at the time of writing this commentary. The following patents related to SpliceAI have been filed: Deep Learning-Based Splice Site Classification, Deep Learning-Based Aberrant Splicing Detection, and Aberrant Splicing Detection Using Convolutional Neural Networks (CNNS). The remaining authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Overview of the splicing region. a The spliceosome attaches to pre-mRNA as it is transcribed from DNA, removing introns and leaving an exon junction complex upstream. The mature mRNA can migrate out of the nucleus for translation. b Motifs of the polypyrimidine tract, acceptor, and donor, calculated from all protein-coding exons. c Odds ratios of observed and expected variant frequencies around the splice site based on ExAC exome sequencing data in Zhang et al. [4]. Lord et al. [3] use the same ExAC data to calculate the mutability-adjusted proportion of singletons (MAPS) across splicing regions, which is higher at nucleotides intolerant of variation. Jaganathan et al. [5] developed SpliceAI, a neural network for predicting the impact of variants on splicing across the genome; the number of potential variants with a Δ score ≥ 0.1 is shown across splicing regions. Abbreviations: TSS, transcription start site; UTR, untranslated region; A, acceptor; D, donor; Pol II, polymerase II; Ter, termination codon; Poly(A), polyadenylation
See this image and copyright information in PMC

References

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