A suite of automated sequence analyses reduces the number of candidate deleterious variants and reveals a difference between probands and unaffected siblings

A complete pedigree-based graph workflow for rare candidate variant analysis

Methods that use a linear genome reference for genome sequencing data analysis are reference-biased. In the field of clinical genetics for rare diseases, a resulting reduction in genotyping accuracy in some regions has likely prevented the resolution of some cases. Pangenome graphs embed population variation into a reference structure. Although pangenome graphs have helped to reduce reference mapping bias, further performance improvements are possible. We introduce VG-Pedigree, a pedigree-aware workflow based on the pangenome-mapping tool of Giraffe and the variant calling tool DeepTrio using a specially trained model for Giraffe-based alignments. We demonstrate mapping and variant calling improvements in both single-nucleotide variants (SNVs) and insertion and deletion (indel) variants over those produced by alignments created using BWA-MEM to a linear-reference and Giraffe mapping to a pangenome graph containing data from the 1000 Genomes Project. We have also adapted and upgraded deleterious-variant (DV) detecting methods and programs into a streamlined workflow. We used these workflows in combination to detect small lists of candidate DVs among 15 family quartets and quintets of the Undiagnosed Diseases Program (UDP). All candidate DVs that were previously diagnosed using the Mendelian models covered by the previously published methods were recapitulated by these workflows. The results of these experiments indicate that a slightly greater absolute count of DVs are detected in the proband population than in their matched unaffected siblings.

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.

Mutations in GET4 disrupt the transmembrane domain recognition complex pathway

The transmembrane domain recognition complex (TRC) targets cytoplasmic C-terminal tail-anchored (TA) proteins to their respective membranes in the endoplasmic reticulum (ER), Golgi, and mitochondria. It is composed of three proteins, GET4, BAG6, and GET5. We identified an individual with compound heterozygous missense variants (p.Arg122His, p.Ile279Met) in GET4 that reduced all three TRC proteins by 70% to 90% in his fibroblasts, suggesting a possible defect in TA protein targeting. He presented with global developmental delay, intellectual disabilities, seizures, facial dysmorphism, and delayed bone age. We found the TA protein, syntaxin 5, is poorly targeted to Golgi membranes compared to normal controls. Since GET4 regulates ER to Golgi transport, we hypothesized that such transport would be disrupted in his fibroblasts, and discovered that retrograde (but not anterograde) transport was significantly reduced. Despite reduction in the three TRC proteins, their mRNA levels were unchanged, suggesting increased degradation in patient fibroblasts. Treating fibroblasts with the FDA-approved proteasome inhibitor, bortezomib (10 nM), restored syntaxin 5 localization and nearly normalized the levels of all three TRC proteins. Our study identifies the first individual with GET4 mutations.

GGPS1 Mutations Cause Muscular Dystrophy/Hearing Loss/Ovarian Insufficiency Syndrome

OBJECTIVE

A hitherto undescribed phenotype of early onset muscular dystrophy associated with sensorineural hearing loss and primary ovarian insufficiency was initially identified in 2 siblings and in subsequent patients with a similar constellation of findings. The goal of this study was to understand the genetic and molecular etiology of this condition.

METHODS

We applied whole exome sequencing (WES) superimposed on shared haplotype regions to identify the initial biallelic variants in GGPS1 followed by GGPS1 Sanger sequencing or WES in 5 additional families with the same phenotype. Molecular modeling, biochemical analysis, laser membrane injury assay, and the generation of a Y259C knock-in mouse were done.

RESULTS

A total of 11 patients in 6 families carrying 5 different biallelic pathogenic variants in specific domains of GGPS1 were identified. GGPS1 encodes geranylgeranyl diphosphate synthase in the mevalonate/isoprenoid pathway, which catalyzes the synthesis of geranylgeranyl pyrophosphate, the lipid precursor of geranylgeranylated proteins including small guanosine triphosphatases. In addition to proximal weakness, all but one patient presented with congenital sensorineural hearing loss, and all postpubertal females had primary ovarian insufficiency. Muscle histology was dystrophic, with ultrastructural evidence of autophagic material and large mitochondria in the most severe cases. There was delayed membrane healing after laser injury in patient-derived myogenic cells, and a knock-in mouse of one of the mutations (Y259C) resulted in prenatal lethality.

INTERPRETATION

The identification of specific GGPS1 mutations defines the cause of a unique form of muscular dystrophy with hearing loss and ovarian insufficiency and points to a novel pathway for this clinical constellation. ANN NEUROL 2020;88:332-347.

The undiagnosed diseases program: Approach to diagnosis

Undiagnosed and rare conditions are collectively common and affect millions of people worldwide. The NIH Undiagnosed Diseases Program (UDP) strives to achieve both a comprehensive diagnosis and a better understanding of the mechanisms of disease for many of these individuals. Through the careful review of records, a well-orchestrated inpatient evaluation, genomic sequencing and testing, and with the use of emerging strategies such as matchmaking programs, the UDP succeeds nearly 30 percent of the time for these highly selective cases. Although the UDP process is built on a unique set of resources, case examples demonstrate steps genetic professionals can take, in both clinical and research settings, to arrive at a diagnosis for their most challenging cases.