Trio RNA sequencing in a cohort of medically complex children

A systematic assessment of the impact of rare canonical splice site variants on splicing using functional and in silico methods

Canonical splice site variants (CSSVs) are often presumed to cause loss-of-function (LoF) and are assigned very strong evidence of pathogenicity (according to American College of Medical Genetics/Association for Molecular Pathology criterion PVS1). The exact nature and predictability of splicing effects of unselected rare CSSVs in blood-expressed genes are poorly understood. We identified 168 rare CSSVs in blood-expressed genes in 112 individuals using genome sequencing, and studied their impact on splicing using RNA sequencing (RNA-seq). There was no evidence of a frameshift, nor of reduced expression consistent with nonsense-mediated decay, for 25.6% of CSSVs: 17.9% had wildtype splicing only and normal junction depths, 3.6% resulted in cryptic splice site usage and in-frame insertions or deletions, 3.6% resulted in full exon skipping (in frame), and 0.6% resulted in full intron inclusion (in frame). Blind to these RNA-seq data, we attempted to predict the precise impact of CSSVs by applying in silico tools and the ClinGen Sequence Variant Interpretation Working Group 2018 guidelines for applying PVS1 criterion. The predicted impact on splicing using (1) SpliceAI, (2) MaxEntScan, and (3) AutoPVS1, an automatic classification tool for PVS1 interpretation of null variants that utilizes Ensembl Variant Effect Predictor and MaxEntScan, was concordant with RNA-seq analyses for 65%, 63%, and 61% of CSSVs, respectively. In summary, approximately one in four rare CSSVs did not show evidence for LoF based on analysis of RNA-seq data. Predictions from in silico methods were often discordant with findings from RNA-seq. More caution may be warranted in applying PVS1-level evidence to CSSVs in the absence of functional data.

Further evidence supporting the role of GTDC1 in glycine metabolism and neurodevelopmental disorders

Copy number variants (CNVs) represent the genetic cause of about 15-20% of neurodevelopmental disorders (NDDs). We identified a ~67 kb de novo intragenic deletion on chromosome 2q22.3 in a female individual showing a developmental encephalopathy characterised by epilepsy, severe intellectual disability, speech delay, microcephaly, and thin corpus callosum with facial dysmorphisms. The microdeletion involved exons 5-6 of GTDC1, encoding a putative glycosyltransferase, whose expression is particularly enriched in the nervous system. In a previous study, a balanced de novo translocation encompassing GTDC1 was reported in a male child with global developmental delay and delayed speech and language development. Based on these premises, we explored the transcriptomic profile of our proband to evaluate the functional consequences of the novel GTDC1 de novo intragenic deletion in relation to the observed neurodevelopmental phenotype. RNA-seq on the proband's lymphoblastoid cell line (LCL) showed expression changes of glycine/serine and cytokine/chemokine signalling pathways, which are related to neurodevelopment and epileptogenesis. Subsequent analysis by ELISA (enzyme-linked immunosorbent assay) and HPLC (high-performance liquid chromatography) revealed increased levels of glycine in the proband's LCL and serum compared to matched controls. Given that an increased level of glycine has been observed in the plasma samples of individuals with Rett syndrome, a condition sharing epilepsy, microcephaly, and intellectual disability with our proband, we proposed that the GTDC1 downregulation is implicated in neurodevelopmental impairment by altering glycine metabolism. Furthermore, our findings expanded the phenotypic spectrum of the novel GTDC1-related condition, including microcephaly and epilepsy among relevant clinical features.

Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders

BACKGROUND

In the process of finding the causative variant of rare diseases, accurate assessment and prioritization of genetic variants is essential. Previous variant prioritization tools mainly depend on the in-silico prediction of the pathogenicity of variants, which results in low sensitivity and difficulty in interpreting the prioritization result. In this study, we propose an explainable algorithm for variant prioritization, named 3ASC, with higher sensitivity and ability to annotate evidence used for prioritization. 3ASC annotates each variant with the 28 criteria defined by the ACMG/AMP genome interpretation guidelines and features related to the clinical interpretation of the variants. The system can explain the result based on annotated evidence and feature contributions.

RESULTS

We trained various machine learning algorithms using in-house patient data. The performance of variant ranking was assessed using the recall rate of identifying causative variants in the top-ranked variants. The best practice model was a random forest classifier that showed top 1 recall of 85.6% and top 3 recall of 94.4%. The 3ASC annotates the ACMG/AMP criteria for each genetic variant of a patient so that clinical geneticists can interpret the result as in the CAGI6 SickKids challenge. In the challenge, 3ASC identified causal genes for 10 out of 14 patient cases, with evidence of decreased gene expression for 6 cases. Among them, two genes (HDAC8 and CASK) had decreased gene expression profiles confirmed by transcriptome data.

CONCLUSIONS

3ASC can prioritize genetic variants with higher sensitivity compared to previous methods by integrating various features related to clinical interpretation, including features related to false positive risk such as quality control and disease inheritance pattern. The system allows interpretation of each variant based on the ACMG/AMP criteria and feature contribution assessed using explainable AI techniques.

Estimating the proportion of nonsense variants undergoing the newly described phenomenon of manufactured splice rescue

A recent report described a nonsense variant simultaneously creating a donor splice site, resulting in a truncated but functional protein. To explore the generalizability of this unique mechanism, we annotated >115,000 nonsense variants using SpliceAI. Between 0.61% (donor gain delta score >0.8, for high precision) and 2.57% (>0.2, for high sensitivity) of nonsense variants were predicted to create new donor splice sites at or upstream of the stop codon. These variants were less likely than other nonsense variants in the same genes to be classified as pathogenic/likely pathogenic in ClinVar (p < 0.001). Up to 1 in 175 nonsense variants were predicted to result in small in-frame deletions and loss-of-function evasion through this "manufactured splice rescue" mechanism. We urge caution when interpreting nonsense variants where manufactured splice rescue is a strong possibility and correlation with phenotype is challenging, as will often be the case with secondary findings and newborn genomic screening programs.

Decoding complex inherited phenotypes in rare disorders: the DECIPHERD initiative for rare undiagnosed diseases in Chile

Rare diseases affect millions of people worldwide, and most have a genetic etiology. The incorporation of next-generation sequencing into clinical settings, particularly exome and genome sequencing, has resulted in an unprecedented improvement in diagnosis and discovery in the past decade. Nevertheless, these tools are unavailable in many countries, increasing health care gaps between high- and low-and-middle-income countries and prolonging the "diagnostic odyssey" for patients. To advance genomic diagnoses in a setting of limited genomic resources, we developed DECIPHERD, an undiagnosed diseases program in Chile. DECIPHERD was implemented in two phases: training and local development. The training phase relied on international collaboration with Baylor College of Medicine, and the local development was structured as a hybrid model, where clinical and bioinformatics analysis were performed in-house and sequencing outsourced abroad, due to lack of high-throughput equipment in Chile. We describe the implementation process and findings of the first 103 patients. They had heterogeneous phenotypes, including congenital anomalies, intellectual disabilities and/or immune system dysfunction. Patients underwent clinical exome or research exome sequencing, as solo cases or with parents using a trio design. We identified pathogenic, likely pathogenic or variants of unknown significance in genes related to the patients´ phenotypes in 47 (45.6%) of them. Half were de novo informative variants, and half of the identified variants have not been previously reported in public databases. DECIPHERD ended the diagnostic odyssey for many participants. This hybrid strategy may be useful for settings of similarly limited genomic resources and lead to discoveries in understudied populations.

Rare de novo gain-of-function missense variants in DOT1L are associated with developmental delay and congenital anomalies

Misregulation of histone lysine methylation is associated with several human cancers and with human developmental disorders. DOT1L is an evolutionarily conserved gene encoding a lysine methyltransferase (KMT) that methylates histone 3 lysine-79 (H3K79) and was not previously associated with a Mendelian disease in OMIM. We have identified nine unrelated individuals with seven different de novo heterozygous missense variants in DOT1L through the Undiagnosed Disease Network (UDN), the SickKids Complex Care genomics project, and GeneMatcher. All probands had some degree of global developmental delay/intellectual disability, and most had one or more major congenital anomalies. To assess the pathogenicity of the DOT1L variants, functional studies were performed in Drosophila and human cells. The fruit fly DOT1L ortholog, grappa, is expressed in most cells including neurons in the central nervous system. The identified DOT1L variants behave as gain-of-function alleles in flies and lead to increased H3K79 methylation levels in flies and human cells. Our results show that human DOT1L and fly grappa are required for proper development and that de novo heterozygous variants in DOT1L are associated with a Mendelian disease.