REEV: review, evaluate and explain variants.

In the era of high throughput sequencing, special software is required for the clinical evaluation of genetic variants. We developed REEV (Review, Evaluate and Explain Variants), a user-friendly platform for clinicians and researchers in the field of rare disease genetics. Supporting data was aggregated from public data sources.

Validation of 3 Computer-Aided Facial Phenotyping Tools (DeepGestalt, GestaltMatcher, and D-Score): Comparative Diagnostic Accuracy Study.

Background: While characteristic facial features provide important clues for finding the correct diagnosis in genetic syndromes, valid assessment can be challenging. The next-generation phenotyping algorithm DeepGestalt analyzes patient images and provides syndrome suggestions. GestaltMatcher matches patient images with similar facial features.

GestaltMatcher facilitates rare disease matching using facial phenotype descriptors.

Many monogenic disorders cause a characteristic facial morphology. Artificial intelligence can support physicians in recognizing these patterns by associating facial phenotypes with the underlying syndrome through training on thousands of patient photographs. However, this 'supervised' approach means that diagnoses are only possible if the disorder was part of the training set.

GLI3 variants causing isolated polysyndactyly are not restricted to the protein's C-terminal third.

Loss of function variants of GLI3 are associated with a variety of forms of polysyndactyly: Pallister-Hall syndrome (PHS), Greig-Cephalopolysyndactyly syndrome (GCPS), and isolated polysyndactyly (IPD). Variants affecting the N-terminal and C-terminal thirds of the GLI3 protein have been associated with GCPS, those within the central third with PHS. Cases of IPD have been attributed to variants affecting the C-terminal third of the GLI3 protein.

Complete lung agenesis caused by complex genomic rearrangements with neo-TAD formation at the SHH locus.

During human organogenesis, lung development is a timely and tightly regulated developmental process under the control of a large number of signaling molecules. Understanding how genetic variants can disturb normal lung development causing different lung malformations is a major goal for dissecting molecular mechanisms during embryogenesis. Here, through exome sequencing (ES), array CGH, genome sequencing (GS) and Hi-C, we aimed at elucidating the molecular basis of bilateral isolated lung agenesis in three fetuses born to a non-consanguineous family.

Efficiency of Computer-Aided Facial Phenotyping (DeepGestalt) in Individuals With and Without a Genetic Syndrome: Diagnostic Accuracy Study.

Background: Collectively, an estimated 5% of the population have a genetic disease. Many of them feature characteristics that can be detected by facial phenotyping. Face2Gene CLINIC is an online app for facial phenotyping of patients with genetic syndromes.

Variable pulmonary manifestations in Chitayat syndrome: Six additional affected individuals.

Hand hyperphalangism leading to shortened index fingers with ulnar deviation, hallux valgus, mild facial dysmorphism and respiratory compromise requiring assisted ventilation are the key features of Chitayat syndrome. This condition results from the recurrent heterozygous missense variant NM_006494.2:c.

Hi-C Identifies Complex Genomic Rearrangements and TAD-Shuffling in Developmental Diseases.

Genome-wide analysis methods, such as array comparative genomic hybridization (CGH) and whole-genome sequencing (WGS), have greatly advanced the identification of structural variants (SVs) in the human genome. However, even with standard high-throughput sequencing techniques, complex rearrangements with multiple breakpoints are often difficult to resolve, and predicting their effects on gene expression and phenotype remains a challenge. Here, we address these problems by using high-throughput chromosome conformation capture (Hi-C) generated from cultured cells of nine individuals with developmental disorders (DDs).