Bi-allelic SNAPC4 variants dysregulate global alternative splicing and lead to neuroregression and progressive spastic paraparesis.

The vast majority of human genes encode multiple isoforms through alternative splicing, and the temporal and spatial regulation of those isoforms is critical for organismal development and function. The spliceosome, which regulates and executes splicing reactions, is primarily composed of small nuclear ribonucleoproteins (snRNPs) that consist of small nuclear RNAs (snRNAs) and protein subunits. snRNA gene transcription is initiated by the snRNA-activating protein complex (SNAPc). Here, we report ten individuals, from eight families, with bi-allelic, deleterious SNAPC4 variants. SNAPC4 encoded one of the five SNAPc subunits that is critical for DNA binding. Most affected individuals presented with delayed motor development and developmental regression after the first year of life, followed by progressive spasticity that led to gait alterations, paraparesis, and oromotor dysfunction. Most individuals had cerebral, cerebellar, or basal ganglia volume loss by brain MRI. In the available cells from affected individuals, SNAPC4 abundance was decreased compared to unaffected controls, suggesting that the bi-allelic variants affect SNAPC4 accumulation. The depletion of SNAPC4 levels in HeLa cell lines via genomic editing led to decreased snRNA expression and global dysregulation of alternative splicing. Analysis of available fibroblasts from affected individuals showed decreased snRNA expression and global dysregulation of alternative splicing compared to unaffected cells. Altogether, these data suggest that these bi-allelic SNAPC4 variants result in loss of function and underlie the neuroregression and progressive spasticity in these affected individuals.

Commonalities across computational workflows for uncovering explanatory variants in undiagnosed cases.

PURPOSE: Genomic sequencing has become an increasingly powerful and relevant tool to be leveraged for the discovery of genetic aberrations underlying rare, Mendelian conditions. Although the computational tools incorporated into diagnostic workflows for this task are continually evolving and improving, we nevertheless sought to investigate commonalities across sequencing processing workflows to reveal consensus and standard practice tools and highlight exploratory analyses where technical and theoretical method improvements would be most impactful. METHODS: We collected details regarding the computational approaches used by a genetic testing laboratory and 11 clinical research sites in the United States participating in the Undiagnosed Diseases Network via meetings with bioinformaticians, online survey forms, and analyses of internal protocols. RESULTS: We found that tools for processing genomic sequencing data can be grouped into four distinct categories. Whereas well-established practices exist for initial variant calling and quality control steps, there is substantial divergence across sites in later stages for variant prioritization and multimodal data integration, demonstrating a diversity of approaches for solving the most mysterious undiagnosed cases. CONCLUSION: The largest differences across diagnostic workflows suggest that advances in structural variant detection, noncoding variant interpretation, and integration of additional biomedical data may be especially promising for solving chronically undiagnosed cases.

Explorations to improve the completeness of exome sequencing.

BACKGROUND: Exome sequencing has advanced to clinical practice and proven useful for obtaining molecular diagnoses in rare diseases. In approximately 75 % of cases, however, a clinical exome study does not produce a definitive molecular diagnosis. These residual cases comprise a new diagnostic challenge for the genetics community. The Undiagnosed Diseases Program of the National Institutes of Health routinely utilizes exome sequencing for refractory clinical cases. Our preliminary data suggest that disease-causing variants may be missed by current standard-of-care clinical exome analysis. Such false negatives reflect limitations in experimental design, technical performance, and data analysis. RESULTS: We present examples from our datasets to quantify the analytical performance associated with current practices, and explore strategies to improve the completeness of data analysis. In particular, we focus on patient ascertainment, exome capture, inclusion of intronic variants, and evaluation of medium-sized structural variants. CONCLUSIONS: The strategies we present may recover previously-missed, disease causing variants in second-pass exome analysis. Understanding the limitations of the current clinical exome search space provides a rational basis to improve methods for disease variant detection using genome-scale sequencing techniques.

Complex translocation disrupting TCF4 and altering TCF4 isoform expression segregates as mild autosomal dominant intellectual disability.

BACKGROUND: Mutations of TCF4, which encodes a basic helix-loop-helix transcription factor, cause Pitt-Hopkins syndrome (PTHS) via multiple genetic mechanisms. TCF4 is a complex locus expressing multiple transcripts by alternative splicing and use of multiple promoters. To address the relationship between mutation of these transcripts and phenotype, we report a three-generation family segregating mild intellectual disability with a chromosomal translocation disrupting TCF4. RESULTS: Using whole genome sequencing, we detected a complex unbalanced karyotype disrupting TCF4 (46,XY,del(14)(q23.3q23.3)del(18)(q21.2q21.2)del(18)(q21.2q21.2)inv(18)(q21.2q21.2)t(14;18)(q23.3;q21.2)(14pter®14q23.3::18q21.2®18q21.2::18q21.1®18qter;18pter®18q21.2::14q23.3®14qter). Subsequent transcriptome sequencing, qRT-PCR and nCounter analyses revealed that cultured skin fibroblasts and peripheral blood had normal expression of genes along chromosomes 14 or 18 and no marked changes in expression of genes other than TCF4. Affected individuals had 12-33 fold higher mRNA levels of TCF4 than did unaffected controls or individuals with PTHS. Although the derivative chromosome generated a PLEKHG3-TCF4 fusion transcript, the increased levels of TCF4 mRNA arose from transcript variants originating distal to the translocation breakpoint, not from the fusion transcript. CONCLUSIONS: Although validation in additional patients is required, our findings suggest that the dysmorphic features and severe intellectual disability characteristic of PTHS are partially rescued by overexpression of those short TCF4 transcripts encoding a nuclear localization signal, a transcription activation domain, and the basic helix-loop-helix domain.