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Purpose Proper interpretation of genomic variants is critical to successful medical decision making based on genetic testing results. A fundamental prerequisite to accurate variant interpretation is the clear understanding of the clinical validity of gene–disease relationships. The Clinical Genome Resource (ClinGen) has developed a semiquantitative framework to assign clinical validity to gene–disease relationships. Methods The ClinGen Hearing Loss Gene Curation Expert Panel (HL GCEP) uses this framework to perform evidence-based curations of genes present on testing panels from 17 clinical laboratories in the Genetic Testing Registry. The HL GCEP curated and reviewed 142 genes and 164 gene–disease pairs, including 105 nonsyndromic and 59 syndromic forms of hearing loss. Results The final outcome included 82 Definitive (50%), 12 Strong (7%), 25 Moderate (15%), 32 Limited (20%), 10 Disputed (6%), and 3 Refuted (2%) classifications. The summary of each curation is date stamped with the HL GCEP approval, is live, and will be kept up-to-date on the ClinGen website ( https://search.clinicalgenome.org/kb/gene-validity ). Conclusion This gene curation approach serves to optimize the clinical sensitivity of genetic testing while reducing the rate of uncertain or ambiguous test results caused by the interrogation of genes with insufficient evidence of a disease link.

Background As the availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including secondary findings. Methods We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. Results For 36/65 gene-disease pairs, loss of function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using the CardiacG2P dataset as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. Conclusions Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is a pre-requisite for scalable genomic testing.

Background Vascular anomalies caused by somatic (postzygotic) variants are clinically and genetically heterogeneous diseases with overlapping or distinct entities. The genetic knowledge in this field is rapidly growing, and genetic testing is now part of the diagnostic workup alongside the clinical, radiological and histopathological data. Nonetheless, access to genetic testing is still limited, and there is significant heterogeneity across the approaches used by the diagnostic laboratories, with direct consequences on test sensitivity and accuracy. The clinical utility of genetic testing is expected to increase progressively with improved theragnostics, which will be based on information about the efficacy and safety of the emerging drugs and future molecules. The aim of this study was to make recommendations for optimising and guiding the diagnostic genetic testing for somatic variants in patients with vascular malformations. Results Physicians and lab specialists from 11 multidisciplinary European centres for vascular anomalies reviewed the genes identified to date as being involved in non-hereditary vascular malformations, evaluated gene–disease associations, and made recommendations about the technical aspects for identification of low-level mosaicism and variant interpretation. A core list of 24 genes were selected based on the current practices in the participating laboratories, the ISSVA classification and the literature. In total 45 gene–phenotype associations were evaluated: 16 were considered definitive, 16 strong, 3 moderate, 7 limited and 3 with no evidence. Conclusions This work provides a detailed evidence-based view of the gene–disease associations in the field of vascular malformations caused by somatic variants. Knowing both the gene–phenotype relationships and the strength of the associations greatly help laboratories in data interpretation and eventually in the clinical diagnosis. This study reflects the state of knowledge as of mid-2023 and will be regularly updated on the VASCERN-VASCA website (VASCERN-VASCA, https://vascern.eu/groupe/vascular-anomalies/ ).

Genetically determined disorders are highly heterogenous in clinical presentation and underlying molecular mechanism. The evidence underpinning these conditions in the peer-reviewed literature requires robust critical evaluation for diagnostic use. Here, we present a structured curation process for Gene2Phenotype (G2P). This draws on multiple lines of clinical, bioinformatic and functional evidence. The process utilises and extends existing terminologies, allows for precise definition of the molecular basis of disease, and confidence levels to be attributed to a given gene-disease assertion. In-depth disease curation using this process will prove useful in applications including in diagnostics, research and development of targeted therapeutics. G2P: www.ebi.ac.uk/gene2phenotype .

Progressive myoclonic epilepsy is a group of neurodegenerative diseases with complex clinical and genetic heterogeneity, which is associated with spontaneous or action-induced myoclonus and progressive neurodegeneration. Since 2020, 4 families with progressive myoclonic epilepsy-11 [OMIM#618876] have been reported with a very limited spectrum of SEMA6B pathogenic variants. In our study, whole-exome sequencing was used in a proband from a nonconsanguineous Chinese family presenting with growth retardation and recurrent atonic seizures. A deletion mutation (c.1960_1978del, p.Leu654Argfs*25) in the last exon of SEMA6B was detected, which is a de novo variant and pathogenic. The new genetic evidence we reported here strengthened the gene-disease relationship, and the gene curation level between SEMA6B and progressive myoclonic epilepsy-11 became “strong” following the ClinGen SOP. Therefore, the results of this study broaden the mutation spectrum of SEMA6B in different ethnic groups and strengthen the gene-disease relationship between SEMA6B and progressive myoclonic epilepsy-11.

Background Cranio-lenticulo-sutural dysplasia (CLSD) is a rare dysmorphic syndrome characterized by skeletal dysmorphism, late-closing fontanels, and cataracts. CLSD is caused by mutations in the SEC23A gene (OMIM# 607812) and can be inherited in either an autosomal dominant or autosomal recessive pattern. To date, only four mutations have been reported to cause CLSD. This study aims to identify the disease-causing variants in a large cohort of congenital cataract patients, to expand the genotypic and phenotypic spectrum of CLSD, and to confirm the association between SEC23A and autosomal recessive CLSD (ARCLSD). Methods We collected detailed medical records and performed comprehensive ocular examinations and whole-exome sequencing (WES) on 115 patients with congenital cataracts. After suspecting that a patient may have CLSD based on the sequencing results, we proceeded to conduct transmission electron microscopy (TEM) on the cultured skin fibroblasts. The clinical validity of the reported gene-disease relationships for the gene and the disease was evaluated using the ClinGen gene curation framework. Results Two novel compound heterozygous variants (c.710A > C p.Asp237Ala, c.1946T > C p.Leu649Pro) of the SEC23A gene, classified as variant of uncertain significance, were identified in the proband with skeletal, cardiac, ocular, and hearing defects. The observation of typical distended endoplasmic reticulum cisternae further supported the diagnosis of CLSD. Application of the ClinGen gene curation framework confirmed the association between SEC23A and ARCLSD. Conclusion This study expands the genotypic and phenotypic spectrum of CLSD, proposes TEM as a supplemental diagnostic method, and indicates that congenital cataracts are a typical sign of ARCLSD.

Genetic diversity found in crop wild relatives is critical to preserve and utilize for crop improvement to achieve sustainable food production amid climate change and increased demand. We genetically characterized a large collection of 1,041 Aegilops accessions distributed among 23 different species using more than 45K single nucleotide polymorphisms identified by genotyping-by-sequencing. The Wheat Genetics Resource Center (WGRC) Aegilops germplasm collection was curated through the identification of misclassified and redundant accessions. There were 49 misclassified and 28 sets of redundant accessions within the four diploid species. The curated germplasm sets now have improved utility for genetic studies and wheat improvement. We constructed a phylogenetic tree and principal component analysis cluster for all Aegilops species together, giving one of the most comprehensive views of Aegilops . The Sitopsis section and the U genome Aegilops clade were further scrutinized with in-depth population analysis. The genetic relatedness among the pair of Aegilops species provided strong evidence for the species evolution, speciation, and diversification. We inferred genome symbols for two species Ae . neglecta and Ae . columnaris based on the sequence read mapping and the presence of segregating loci on the pertinent genomes as well as genetic clustering. The high genetic diversity observed among Aegilops species indicated that the genus could play an even greater role in providing the critical need for untapped genetic diversity for future wheat breeding and improvement. To fully characterize these Aegilops species, there is an urgent need to generate reference assemblies for these wild wheats, especially for the polyploid Aegilops .

Background A very limited spectrum of ASCC1 pathogenic variants had been reported in six (mostly consanguineous) families with spinal muscular atrophy with congenital bone fractures 2 [OMIM #616867] since 2016. Methods A proband from a non‐consanguineous Chinese family presented with neonatal severe hypotonia, respiratory distress, muscle weakness, and atrophy, as well as congenital bone fractures was performed by exome sequencing. Results A compound heterozygosity of a nonsense (c.932C>G,p.Ser311Ter) and an exon 5 deletion in ASCC1 segregating with phenotypes was detected, both variants are novel and pathogenic. Since ASCC1 is a relatively new disease gene, we performed the gene curation by ClinGen SOP. The existing evidence is sufficient to support a \"Definitive\" level of disease‐gene relationship. Conclusion This case report expended the mutation spectrum of ASCC1 and support the notion that this novel disease also occurs in outbreed populations and this is a rare disease but may still be underdiagnosed due to its perinatal lethal outcomes. Spinal muscular atrophy with congenital bone fractures 2.

Background Automated gene-calling is still an error-prone process, particularly for the highly plastic genomes of fungal species. Improvement through quality control and manual curation of gene models is a time-consuming process that requires skilled biologists and is only marginally performed. The wealth of available fungal genomes has not yet been exploited by an automated method that applies quality control of gene models in order to obtain more accurate genome annotations. Results We provide a novel method named alignment-based fungal gene prediction (ABFGP) that is particularly suitable for plastic genomes like those of fungi. It can assess gene models on a gene-by-gene basis making use of informant gene loci. Its performance was benchmarked on 6,965 gene models confirmed by full-length unigenes from ten different fungi. 79.4% of all gene models were correctly predicted by ABFGP. It improves the output of ab initio gene prediction software due to a higher sensitivity and precision for all gene model components. Applicability of the method was shown by revisiting the annotations of six different fungi, using gene loci from up to 29 fungal genomes as informants. Between 7,231 and 8,337 genes were assessed by ABFGP and for each genome between 1,724 and 3,505 gene model revisions were proposed. The reliability of the proposed gene models is assessed by an a posteriori introspection procedure of each intron and exon in the multiple gene model alignment. The total number and type of proposed gene model revisions in the six fungal genomes is correlated to the quality of the genome assembly, and to sequencing strategies used in the sequencing centre, highlighting different types of errors in different annotation pipelines. The ABFGP method is particularly successful in discovering sequence errors and/or disruptive mutations causing truncated and erroneous gene models. Conclusions The ABFGP method is an accurate and fully automated quality control method for fungal gene catalogues that can be easily implemented into existing annotation pipelines. With the exponential release of new genomes, the ABFGP method will help decreasing the number of gene models that require additional manual curation.

Over the past decade, biology has undergone a data revolution in how researchers collect data and the amount of data being collected. An emerging challenge that has received limited attention in biology is managing, working with, and providing access to data under continual active collection. Regularly updated data present unique challenges in quality assurance and control, data publication, archiving, and reproducibility. We developed a workflow for a long-term ecological study that addresses many of the challenges associated with managing this type of data. We do this by leveraging existing tools to 1) perform quality assurance and control; 2) import, restructure, version, and archive data; 3) rapidly publish new data in ways that ensure appropriate credit to all contributors; and 4) automate most steps in the data pipeline to reduce the time and effort required by researchers. The workflow leverages tools from software development, including version control and continuous integration, to create a modern data management system that automates the pipeline.