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De novo FOXP1 mutations have been associated with intellectual disability (ID), motor delay, autistic features and a wide spectrum of speech difficulties. C syndrome (Opitz C trigonocephaly syndrome) is a rare and genetically heterogeneous condition, characterized by trigonocephaly, craniofacial anomalies and ID. Several different chromosome deletions and and point mutations in distinct genes have been associated with the disease in patients originally diagnosed as Opitz C. By whole exome sequencing we identified a de novo splicing mutation in FOXP1 in a patient, initially diagnosed as C syndrome, who suffers from syndromic intellectual disability with trigonocephaly. The mutation (c.1428 + 1 G > A) promotes the skipping of exon 16, a frameshift and a premature STOP codon (p.Ala450GLyfs*13), as assessed by a minigene strategy. The patient reported here shares speech difficulties, intellectual disability and autistic features with other FOXP1 syndrome patients, and thus the diagnosis for this patient should be changed. Finally, since trigonocephaly has not been previously reported in FOXP1 syndrome, it remains to be proved whether it may be associated with the FOXP1 mutation. ; The authors thank the patient and his family for wholehearted collaboration. They are also grateful to M. Cozar for technical assistance, and to CNAG for exome sequencing within the "300 exomes to elucidate rare diseases" program. Funding was from Associació Síndrome Opitz C, Terrassa, Spain; Spanish Ministerio de Economía y Competitividad (SAF2014-56562-R; SAF2016-75948-R, FECYT, crowdfunding PRECIPITA); ISCIII Ministerio de Economía y Competitividad (PT13/0001/0044), Catalan Government (2014SGR932) and from CIBERER (U720).

Data de publicació electrònica: 09-04-2021 ; The area of the Spanish Pyrenees is particularly interesting for studying the demographic dynamics of European rural areas given its orography, the main traditional rural condition of its population and the reported higher patterns of consanguinity of the region. Previous genetic studies suggest a gradient of genetic continuity of the area in the West to East axis. However, it has been shown that micro-population substructure can be detected when considering high-quality NGS data and using spatial explicit methods. In this work, we have analyzed the genome of 30 individuals sequenced at 40× from five different valleys in the Spanish Eastern Pyrenees (SEP) separated by less than 140 km along a west to east axis. Using haplotype-based methods and spatial analyses, we have been able to detect micro-population substructure within SEP not seen in previous studies. Linkage disequilibrium and autozygosity analyses suggest that the SEP populations show diverse demographic histories. In agreement with these results, demographic modeling by means of ABC-DL identify heterogeneity in their effective population sizes despite of their close geographic proximity, and suggests that the population substructure within SEP could have appeared around 2500 years ago. Overall, these results suggest that each rural population of the Pyrenees could represent a unique entity. ; OL, IM, RT, JC, and SB acknowledge the support from Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa, CERCA Program/Generalitat de Catalunya, Spanish Ministry of Science and Innovation through the Instituto de Salud Carlos III, Generalitat de Catalunya through Departament de Salut and Departament d'Empresa i Coneixement, Co-financing with funds from the European Regional Development Fund by the Spanish Ministry of Science and Innovation corresponding to the Programa Operativo FEDER Plurirregional de España (POPE) 2014–2020 and by the Secretaria d'Universitats i Recerca, Departament d'Empresa i Coneixement of the Generalitat de Catalunya corresponding to the Programa Operatiu FEDER de Catalunya 2014–2020. OL gratefully acknowledges the financial support from Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness)—RYC-2013-14797, BFU2015-68759-P and PGC2018-098574-B-I00 and Generalitat de Catalunya (Government of Catalonia)—GRC 2017 SGR 937. IM gratefully acknowledges the financial support from the Government of Catalonia | Agència de Gestió d'Ajuts Universitaris i de Recerca (Agency for Management of University and Research Grants)—GRC 2014 SGR 615. MMA was supported by a FPU15/01251 from Ministerio de Ciencia, innovación y Universidades. PM and MMA acknowledge the financial support from Precipita-FECYT (FBG 309307 project). The samples analyzed in this study are part of a much larger sample whose collection was supported by the project CGL2011-27866 of the Ministerio de Ciencia y Tecnologia, the Fundació Moret i Marguí, and the invaluable collaboration of the Hospital San Bernabé (Berguedà), Fundació Sant Hospital (Alt Urgell), Hospital d'Olot i Comarcal (Garrotxa), Hospital de Campdevànol (Ripollès), and Hospital Comarcal (Pallars)

Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics. ; The Solve-RD project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 779257. Data were analysed using the RD‐Connect Genome‐Phenome Analysis Platform, which received funding from EU projects RD‐Connect, Solve-RD and EJP-RD (grant numbers FP7 305444, H2020 779257, H2020 825575), Instituto de Salud Carlos III (grant numbers PT13/0001/0044, PT17/0009/0019; Instituto Nacional de Bioinformática, INB) and ELIXIR Implementation Studies.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes. ; We acknowledge the support of the developers of PhenoTips, which was used in the past by RD-Connect and NeurOmics as the primary tool to collate phenotypic data. We would also like to thank the leaders and members of the Instituto Nacional de Bioinformática (INB) and ELIXIR for their support and collaboration throughout the years. RD-Connect (RD-Connect, an integrated platform connecting registries, biobanks, and clinical bioinformatics) received funding from the Seventh Framework (FP7) Programme of the European Union under grant agreement No 305444. Data were analyzed using the RD-Connect GPAP, which received funding from EU ...

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes. ; RD-Connect (RD-Connect, an integrated platform connecting registries, biobanks, and clinical bioinformatics) received funding from the Seventh Framework (FP7) Programme of the European Union under grant agreement No 305444. Data were analyzed using the RD-Connect GPAP, which received funding from EU projects Solve-RD, EJP-RD (grant numbers H2020 779257, H2020 825575), Instituto de Salud Carlos III (Grant numbers PT13/0001/0044, PT17/0009/0019; Instituto Nacional de Bioinformática, INB), ELIXIR-EXCELERATE (Grant number EU H2020 #676559) and ELIXIR Implementation Studies (Remote real-time visualization of human rare disease genomics ...