Differential inclusion of NEB exons 143 and 144 provides insight into NEB-related myopathy variant interpretation and disease manifestation.

Biallelic pathogenic variants in the gene encoding nebulin (NEB) are a known cause of congenital myopathy. We present two brothers with congenital myopathy and compound heterozygous variants (NC_000002.12:g.151692086G>T; NM_001271208.2: c.2079C>A; p.(Cys693Ter) and NC_000002.12:g.151533439T>C; NM_001271208.2:c.21522+3A>G ) in NEB. Transcriptomic sequencing on affected individual muscle revealed that the extended splice variant c.21522+3A>G causes exon 144 skipping. Nebulin isoforms containing exon 144 are known to be mutually exclusive with isoforms containing exon 143, and these isoforms are differentially expressed during development and in adult skeletal muscles. Affected individuals MRI patterns of muscle involvement were compared to the known pattern of relative abundance of these two isoforms in muscle. We propose that the pattern of muscle involvement in these affected individuals better fits the distribution of exon 144-containing isoforms in muscle than with previously published MRI findings in NEB-related disease due to other variants. Our report introduces disease pathogenesis and manifestation as a result of alteration of isoform distributions in muscle.

A harmonized public resource of deeply sequenced diverse human genomes.

Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also show substantial added value from this data set compared with the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared with previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality-control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

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. The addition of CNV detection to exome analysis identified causal CNVs for 171 families (2.6%). The estimated sizes of CNVs ranged from 293 bp to 80 Mb. The causal CNVs consisted of 140 deletions, 15 duplications, 3 suspected complex structural variants (SVs), 3 insertions, and 10 complex SVs, the latter two groups being identified by orthogonal confirmation methods. To classify CNV variant pathogenicity, we used the 2020 American College of Medical Genetics and Genomics/ClinGen CNV interpretation standards and developed additional criteria to evaluate allelic and functional data as well as variants on the X chromosome to further advance the framework. We interpreted 151 CNVs as likely pathogenic/pathogenic and 20 CNVs as high-interest variants of uncertain significance. Calling CNVs from existing exome data increases the diagnostic yield for individuals undiagnosed after standard testing approaches, providing a higher-resolution alternative to arrays at a fraction of the cost of genome sequencing. Our improvements to the classification approach advances the systematic framework to assess the pathogenicity of CNVs.

The landscape of regional missense mutational intolerance quantified from 125,748 exomes.

Missense variants can have a range of functional impacts depending on factors such as the specific amino acid substitution and location within the gene. To interpret their deleteriousness, studies have sought to identify regions within genes that are specifically intolerant of missense variation 1-12 . Here, we leverage the patterns of rare missense variation in 125,748 individuals in the Genome Aggregation Database (gnomAD) 13 against a null mutational model to identify transcripts that display regional differences in missense constraint. Missense-depleted regions are enriched for ClinVar 14 pathogenic variants, de novo missense variants from individuals with neurodevelopmental disorders (NDDs) 15,16 , and complex trait heritability. Following ClinGen calibration recommendations for the ACMG/AMP guidelines, we establish that regions with less than 20% of their expected missense variation achieve moderate support for pathogenicity. We create a missense deleteriousness metric (MPC) that incorporates regional constraint and outperforms other deleteriousness scores at stratifying case and control de novo missense variation, with a strong enrichment in NDDs. These results provide additional tools to aid in missense variant interpretation.

Differential inclusion of NEB exons 143 and 144 provides insight into NEB-related myopathy variant interpretation and disease manifestation.

Biallelic pathogenic variants in the gene encoding nebulin (NEB) are a known cause of congenital myopathy. We present two individuals with congenital myopathy and compound heterozygous variants (NM_001271208.2: c.2079C>A; p.(Cys693Ter) and c.21522+3A>G ) in NEB. Transcriptomic sequencing on patient muscle revealed that the extended splice variant c.21522+3A>G causes exon 144 skipping. Nebulin isoforms containing exon 144 are known to be mutually exclusive with isoforms containing exon 143, and these isoforms are differentially expressed during development and in adult skeletal muscles. Patients MRIs were compared to the known pattern of relative abundance of these two isoforms in muscle. We propose that the pattern of muscle involvement in these patients better fits the distribution of exon 144-containing isoforms in muscle than with previously published MRI findings in NEB-related disease due to other variants. To our knowledge this is the first report hypothesizing disease pathogenesis through the alteration of isoform distributions in muscle.

Genome and RNA sequencing boost neuromuscular diagnoses to 62% from 34% with exome sequencing alone.

OBJECTIVE: Most families with heritable neuromuscular disorders do not receive a molecular diagnosis. Here we evaluate diagnostic utility of exome, genome, RNA sequencing, and protein studies and provide evidence-based recommendations for their integration into practice. METHODS: In total, 247 families with suspected monogenic neuromuscular disorders who remained without a genetic diagnosis after standard diagnostic investigations underwent research-led massively parallel sequencing: neuromuscular disorder gene panel, exome, genome, and/or RNA sequencing to identify causal variants. Protein and RNA studies were also deployed when required. RESULTS: Integration of exome sequencing and auxiliary genome, RNA and/or protein studies identified causal or likely causal variants in 62% (152 out of 247) of families. Exome sequencing alone informed 55% (83 out of 152) of diagnoses, with remaining diagnoses (45%; 69 out of 152) requiring genome sequencing, RNA and/or protein studies to identify variants and/or support pathogenicity. Arrestingly, novel disease genes accounted for <4% (6 out of 152) of diagnoses while 36.2% of solved families (55 out of 152) harbored at least one splice-altering or structural variant in a known neuromuscular disorder gene. We posit that contemporary neuromuscular disorder gene-panel sequencing could likely provide 66% (100 out of 152) of our diagnoses today. INTERPRETATION: Our results emphasize thorough clinical phenotyping to enable deep scrutiny of all rare genetic variation in phenotypically consistent genes. Post-exome auxiliary investigations extended our diagnostic yield by 81% overall (34-62%). We present a diagnostic algorithm that details deployment of genomic and auxiliary investigations to obtain these diagnoses today most effectively. We hope this provides a practical guide for clinicians as they gain greater access to clinical genome and transcriptome sequencing.

Recurrent de novo SPTLC2 variant causes childhood-onset amyotrophic lateral sclerosis (ALS) by excess sphingolipid synthesis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of the upper and lower motor neurons with varying ages of onset, progression and pathomechanisms. Monogenic childhood-onset ALS, although rare, forms an important subgroup of ALS. We recently reported specific SPTLC1 variants resulting in sphingolipid overproduction as a cause for juvenile ALS. Here, we report six patients from six independent families with a recurrent, de novo, heterozygous variant in SPTLC2 c.778G>A [p.Glu260Lys] manifesting with juvenile ALS. METHODS: Clinical examination of the patients along with ancillary and genetic testing, followed by biochemical investigation of patients' blood and fibroblasts, was performed. RESULTS: All patients presented with early-childhood-onset progressive weakness, with signs and symptoms of upper and lower motor neuron degeneration in multiple myotomes, without sensory neuropathy. These findings were supported on ancillary testing including nerve conduction studies and electromyography, muscle biopsies and muscle ultrasound studies. Biochemical investigations in plasma and fibroblasts showed elevated levels of ceramides and unrestrained de novo sphingolipid synthesis. Our studies indicate that SPTLC2 variant [c.778G>A, p.Glu260Lys] acts distinctly from hereditary sensory and autonomic neuropathy (HSAN)-causing SPTLC2 variants by causing excess canonical sphingolipid biosynthesis, similar to the recently reported SPTLC1 ALS associated pathogenic variants. Our studies also indicate that serine supplementation, which is a therapeutic in SPTLC1 and SPTCL2-associated HSAN, is expected to exacerbate the excess sphingolipid synthesis in serine palmitoyltransferase (SPT)-associated ALS. CONCLUSIONS: SPTLC2 is the second SPT-associated gene that underlies monogenic, juvenile ALS and further establishes alterations of sphingolipid metabolism in motor neuron disease pathogenesis. Our findings also have important therapeutic implications: serine supplementation must be avoided in SPT-associated ALS, as it is expected to drive pathogenesis further.

Biallelic CRELD1 variants cause a multisystem syndrome, including neurodevelopmental phenotypes, cardiac dysrhythmias, and frequent infections.

PURPOSE: We sought to delineate a multisystem disorder caused by recessive cysteine-rich with epidermal growth factor-like domains 1 (CRELD1) gene variants. METHODS: The impact of CRELD1 variants was characterized through an international collaboration utilizing next-generation DNA sequencing, gene knockdown, and protein overexpression in Xenopus tropicalis, and in vitro analysis of patient immune cells. RESULTS: Biallelic variants in CRELD1 were found in 18 participants from 14 families. Affected individuals displayed an array of phenotypes involving developmental delay, early-onset epilepsy, and hypotonia, with about half demonstrating cardiac arrhythmias and some experiencing recurrent infections. Most harbored a frameshift in trans with a missense allele, with 1 recurrent variant, p.(Cys192Tyr), identified in 10 families. X tropicalis tadpoles with creld1 knockdown displayed developmental defects along with increased susceptibility to induced seizures compared with controls. Additionally, human CRELD1 harboring missense variants from affected individuals had reduced protein function, indicated by a diminished ability to induce craniofacial defects when overexpressed in X tropicalis. Finally, baseline analyses of peripheral blood mononuclear cells showed similar proportions of immune cell subtypes in patients compared with healthy donors. CONCLUSION: This patient cohort, combined with experimental data, provide evidence of a multisystem clinical syndrome mediated by recessive variants in CRELD1.

A harmonized public resource of deeply sequenced diverse human genomes.

Underrepresented populations are often excluded from genomic studies due in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high quality set of 4,094 whole genomes from HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also demonstrate substantial added value from this dataset compared to the prior versions of the component resources, typically combined via liftover and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared to previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

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 GREGoR consortium. Each family's CNV data was analyzed using the seqr platform and candidate CNVs classified using the 2020 ACMG/ClinGen CNV interpretation standards. We developed additional evidence criteria to address situations not covered by the current standards. The addition of CNV calling to exome analysis identified causal CNVs for 173 families (2.6%). The estimated sizes of CNVs ranged from 293 bp to 80 Mb with estimates that 44% would not have been detected by standard chromosomal microarrays. The causal CNVs consisted of 141 deletions, 15 duplications, 4 suspected complex structural variants (SVs), 3 insertions and 10 complex SVs, the latter two groups being identified by orthogonal validation methods. We interpreted 153 CNVs as likely pathogenic/pathogenic and 20 CNVs as high interest variants of uncertain significance. Calling CNVs from existing exome data increases the diagnostic yield for individuals undiagnosed after standard testing approaches, providing a higher resolution alternative to arrays at a fraction of the cost of genome sequencing. Our improvements to the classification approach advances the systematic framework to assess the pathogenicity of CNVs.