Male proband with intractable seizures and a de novo start-codon-disrupting variant in GLUL.

Bi-allelic variants in GLUL, encoding glutamine synthetase and responsible for the conversion of glutamate to glutamine, are associated with a severe recessive disease due to glutamine deficiency. A dominant disease mechanism was recently reported in nine females, all with a de novo single-nucleotide variant within the start codon or the 5' UTR of GLUL that truncates 17 amino acids of the protein product, including its critical N-terminal degron sequence. This truncation results in a disorder of abnormal glutamine synthetase stability and manifests as a phenotype of severe developmental and epileptic encephalopathy.

Diagnosing missed cases of spinal muscular atrophy in genome, exome, and panel sequencing data sets.

Purpose: We set out to develop a publicly available tool that could accurately diagnose spinal muscular atrophy (SMA) in exome, genome, or panel sequencing data sets aligned to a GRCh37, GRCh38, or T2T reference genome.

Methods: The SMA Finder algorithm detects the most common genetic causes of SMA by evaluating reads that overlap the c.840 position of the SMN1 and SMN2 paralogs.

Exome copy number variant detection, analysis, and classification in a large cohort of families with undiagnosed rare genetic disease.

Copy number variants (CNVs) are significant contributors to the pathogenicity of rare genetic diseases and, with new innovative methods, can now reliably be identified from exome sequencing. Challenges still remain in accurate classification of CNV pathogenicity. CNV calling using GATK-gCNV was performed on exomes from a cohort of 6,633 families (15,759 individuals) with heterogeneous phenotypes and variable prior genetic testing collected at the Broad Institute Center for Mendelian Genomics of the Genomics Research to Elucidate the Genetics of Rare Diseases consortium and analyzed using the seqr platform.

Advanced variant classification framework reduces the false positive rate of predicted loss-of-function variants in population sequencing data.

Predicted loss of function (pLoF) variants are often highly deleterious and play an important role in disease biology, but many pLoF variants may not result in loss of function (LoF). Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines' PVS1 criterion.