Full genome analysis of a young girl with deafness, dystonia, central hypomyelination, refractory seizure, and fluctuating liver function impairment revealed a heterozygous, de novo variant in the BCAP31 gene on chromosome X28q (NC_000023.11(BCAP31_v001):c.92G>A), mutations of which caused the X-linked recessive severe neurologic disorder DDCH (Deafness, Dystonia, and Cerebral Hypomyelination, OMIM#300475). Reverse transcription-PCR (RT-PCR) of the patient’s white blood cells showed the absence of wild-type BCAP31 mRNA but the presence of two novel BCAP31 mRNAs. The major alternatively-spliced mRNA is due to exon 2 skipping and the utilization of a new initiation site in exon 3 that leads to a frameshift and truncated transcript while the minor novel mRNA has a 110 nucleotide insertion to exon 2. Phasing studies showed that the de novo variant arose in the paternal X chromosome. X chromosome inactivation assay was done and confirmed that the patient’s maternal X chromosome was preferentially inactivated, providing evidence that the mutated BCAP31 gene was the predominantly expressed. According to the ACMG guideline, this variant is deemed “pathogenic” (PS2, PS3, PM2, PP3, PP4) and deleterious. This is the first reported female patient in BCAP31-related syndrome resulted from skewed X-inactivation and a de novo mutation in the active X chromosome.
Recently, we demonstrated that the qualitative American College of Medical Genetics and Genomics/ Association for Medical Pathology (ACMG/AMP) guidelines for evaluation of Mendelian disease gene variants are fundamentally compatible with a quantitative Bayesian formulation. Here, we show that the underlying ACMG/AMP “strength of evidence categories” can be abstracted into a point system. These points are proportional to Log(odds), are additive, and produce a system that recapitulates the Bayesian formulation of the ACMG/AMP guidelines. Strengths of this system are its simplicity and that the connection between point values and odds of pathogenicity allows empirical calibration of strength of evidence for individual data types. Weaknesses include that a narrow range of prior probabilities is locked in, and that the Bayesian nature of the system is inapparent. We conclude that a points-based system has useful attributes of user friendliness and can be useful so long as the underlying Bayesian principles are acknowledged.
This letter is a response to the commentary by Jonson & Do (Johnson and Do 2020) on our paper, entitled “A Vietnamese human genetic variation database” (Vinh et al. 2019). The commentators concerned about two issues: Firstly, the relation of Southeast Asian (SEA) and East Asian (EA) groups to African and European groups; Secondly, the history of migration and settlement in Southeast Asia. Our responses will clarify both concerns from the commentators.
It is possible to estimate the prior probability of pathogenicity for germline disease gene variants based on bioinformatic prediction of variant effect/s. However, routinely used approaches have likely led to the underestimation and underreporting of variants located outside donor and acceptor splice site motifs that affect mRNA processing. This review presents information about hereditary cancer gene germline variants, outside native splice sites, with experimentally validated splicing effects. We list 81 exonic variants that impact splicing regulatory elements in BRCA1, BRCA2, MLH1, MSH2, MSH6 and PMS2. We utilized a pre-existing large-scale BRCA1 functional dataset to map functional splicing regulatory elements, assess the relative performance of different tools to predict effects of 283 variants on such elements, and develop a generic workflow to prioritize variants that may impact splicing regulatory elements. We also describe rare examples of intronic variants that impact branchpoint sites and create pseudoexons. We discuss the challenges in predicting variant effect on branchpoint site usage and pseudoexonization, and suggest strategies to improve the bioinformatic prioritization of such variants for experimental validation. Importantly, our review highlights the importance of considering impact of variants outside donor and acceptor motifs on mRNA splicing and disease causation.