• MeSH
• Caenorhabditis elegans genetics   MeSH
• Databases, Genetic utilization   MeSH
• Drosophila genetics   MeSH
• European Union MeSH
• Research Support as Topic MeSH
• Humans MeSH
• Muscular Dystrophies epidemiology   etiology   genetics   MeSH
• Research Design MeSH
• Check Tag
• Humans MeSH
• Publication type
• Congress MeSH
• Comparative Study MeSH
• Geographicals
• Czech Republic MeSH

One of the aims of high-throughput gene/protein profiling experiments is the identification of biological processes altered between two or more conditions. Pathway analysis is an umbrella term for a multitude of computational approaches used for this purpose. While in the beginning pathway analysis relied on enrichment-based approaches, a newer generation of methods is now available, exploiting pathway topologies in addition to gene/protein expression levels. However, little effort has been invested in their critical assessment with respect to their performance in different experimental setups. Here, we assessed the performance of seven representative methods identifying differentially expressed pathways between two groups of interest based on gene expression data with prior knowledge of pathway topologies: SPIA, PRS, CePa, TAPPA, TopologyGSA, Clipper and DEGraph. We performed a number of controlled experiments that investigated their sensitivity to sample and pathway size, threshold-based filtering of differentially expressed genes, ability to detect target pathways, ability to exploit the topological information and the sensitivity to different pre-processing strategies. We also verified type I error rates and described the influence of overexpression of single genes, gene sets and topological motifs of various sizes on the detection of a pathway as differentially expressed. The results of our experiments demonstrate a wide variability of the tested methods. We provide a set of recommendations for an informed selection of the proper method for a given data analysis task.

• MeSH
• Databases, Genetic MeSH
• Datasets as Topic MeSH
• Humans MeSH
• Metabolic Networks and Pathways * MeSH
• Gene Expression Profiling methods   MeSH
• High-Throughput Nucleotide Sequencing MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH

• MeSH
• Ceruloplasmin analysis   genetics   deficiency   MeSH
• Cystic Fibrosis diagnosis   MeSH
• Databases, Genetic * MeSH
• alpha 1-Antitrypsin Deficiency diagnosis   MeSH
• Child MeSH
• Glycerol Kinase analysis   genetics   deficiency   MeSH
• Hepatolenticular Degeneration diagnosis   MeSH
• Clinical Laboratory Techniques * methods   utilization   MeSH
• Humans MeSH
• Menkes Kinky Hair Syndrome diagnosis   MeSH
• DNA Mutational Analysis * MeSH
• Infant, Newborn MeSH
• Computer Simulation MeSH
• Reverse Transcriptase Polymerase Chain Reaction methods   utilization   MeSH
• Polymerase Chain Reaction * methods   utilization   MeSH
• Canavan Disease diagnosis   MeSH
• Metabolism, Inborn Errors * diagnosis   MeSH
• Congenital, Hereditary, and Neonatal Diseases and Abnormalities diagnosis   MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Infant, Newborn MeSH
• Publication type
• Lecture MeSH

BACKGROUND: The Clinical Genome Resource (ClinGen) is an international collaborative effort among scientists and clinicians, diagnostic and research laboratories, and the patient community. Using a standardized framework, ClinGen has established guidelines to classify gene-disease relationships as definitive, strong, moderate, and limited on the basis of available scientific and clinical evidence. When the genetic and functional evidence for a gene-disease relationship has conflicting interpretations or contradictory evidence, they can be disputed or refuted. OBJECTIVE: We assessed genes related to primary antibody deficiencies. METHODS: The ClinGen Antibody Deficiencies Gene Curation Expert Panel, using the ClinGen framework, classified genes related to primary antibody deficiency that primarily affect B-cell development and/or function, and that account for the largest proportion of inborn errors of immunity or primary immunodeficiencies. RESULTS: The expert panel curated a total of 65 genes associated with humoral immune defects to validate 74 gene-disease relationships. Of these, 40 were classified as definitive, 1 as strong, 16 as moderate, 15 as limited, and 2 as disputed. The curation process involved reviewing 490 patient records and 3546 associated human phenotype ontology entries. The 3 most frequently observed terms related to primary antibody deficiency were decreased circulating antibody level, pneumonia, and lymphadenopathy. CONCLUSIONS: These curations (publicly available at ClinicalGenome.org) represent the first effort to provide a comprehensive genetic and phenotypic revision of genetic disorders affecting humoral immunity, as reviewed and approved by experts in the field.

• MeSH
• Databases, Genetic MeSH
• Genetic Predisposition to Disease MeSH
• Humans MeSH
• Primary Immunodeficiency Diseases * genetics   MeSH
• Immunologic Deficiency Syndromes * genetics   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

Environmental sequencing has greatly expanded our knowledge of micro-eukaryotic diversity and ecology by revealing previously unknown lineages and their distribution. However, the value of these data is critically dependent on the quality of the reference databases used to assign an identity to environmental sequences. Existing databases contain errors and struggle to keep pace with rapidly changing eukaryotic taxonomy, the influx of novel diversity, and computational challenges related to assembling the high-quality alignments and trees needed for accurate characterization of lineage diversity. EukRef (eukref.org) is an ongoing community-driven initiative that addresses these challenges by bringing together taxonomists with expertise spanning the eukaryotic tree of life and microbial ecologists, who use environmental sequence data to develop reliable reference databases across the diversity of microbial eukaryotes. EukRef organizes and facilitates rigorous mining and annotation of sequence data by providing protocols, guidelines, and tools. The EukRef pipeline and tools allow users interested in a particular group of microbial eukaryotes to retrieve all sequences belonging to that group from International Nucleotide Sequence Database Collaboration (INSDC) (GenBank, the European Nucleotide Archive [ENA], or the DNA DataBank of Japan [DDBJ]), to place those sequences in a phylogenetic tree, and to curate taxonomic and environmental information for the group. We provide guidelines to facilitate the process and to standardize taxonomic annotations. The final outputs of this process are (1) a reference tree and alignment, (2) a reference sequence database, including taxonomic and environmental information, and (3) a list of putative chimeras and other artifactual sequences. These products will be useful for the broad community as they become publicly available (at eukref.org) and are shared with existing reference databases.

• MeSH
• Ciliophora genetics   MeSH
• Databases, Genetic MeSH
• Data Curation * MeSH
• Eukaryota classification   genetics   MeSH
• Phylogeny * MeSH
• Genetic Variation * MeSH
• RNA, Ribosomal genetics   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH

Dědičná nádorová onemocnění tvoří malou, ale klinicky významnou část onkologických onemocnění, v České republice se jedná ročně o několik tisíc osob. Identifikace kauzální mutace v nádorových predispozičních genech má u těchto nemocných zásadní prognostický a v některých případech i prediktivní význam. Mimo to je podmínkou cílené preventivní péče o asymptomatické nosiče mutací v rodinách se zvýšeným rizikem vzniku nádorového onemocnění. Do současné doby bylo charakterizováno více než 150 nádorových predispozičních genů. Mutace většiny z nich se vyskytují vzácně, s výraznou populační specifičností a jejich klinická interpretace je často obtížná. Diagnostiku raritních variant technicky zjednodušují postupy využívající sekvenování nové generace, které umožňují vyšetření rozsáhlých sad genů. Za účelem racionalizace diagnostiky hereditárních nádorových syndromů v České republice jsme navrhli sekvenační panel „CZECANCA“, který cílí na vyšetření 219 genů asociovaných s dědičnými nádorovými onemocněními. Panel obsahuje přes 50 klinicky významných genů vysokého a středního rizika, zbývající geny tvoří málo prozkoumané a kandidátní predispoziční geny, jejichž vrozené mutace mají nejasnou klinickou interpretaci. Společně s návrhem panelu byl optimalizován postup vlastního sekvenování a bioinformatického zpracování sekvenačních dat pro tvorbu jednotné databáze genotypů analyzovaných vzorků. Cílem projektu je nabídnout použití sekvenačního panelu včetně optimalizovaného postupu sekvenování nové generace diagnostickým laboratořím v České republice a zajistit sdílení genotypů a klinických údajů o vyšetřovaných pacientech ve společné databázi za účelem zlepšení možnosti klinické interpretace vzácných mutací u vysoce rizikových osob.

Individuals with hereditary cancer syndromes form a minor but clinically important subgroup of oncology patients, comprising several thousand cases in the Czech Republic annually. In these patients, the identification of pathogenic mutations in cancer susceptibility genes has an important predictive and, in some cases, prognostic value. It also enables rational preventive strategies in asymptomatic carriers from affected families. More than 150 cancer susceptibility genes have been described so far; however, mutations in most of them are very rare, occurring with substantial population variability, and hence their clinical interpretation is very complicated. Diagnostics of mutations in cancer susceptibility genes have benefited from the broad availability of next-generation sequencing analyses using targeted gene panels. In order to rationalize the diagnostics of hereditary cancer syndromes in the Czech Republic, we have prepared the sequence capture panel “CZECANCA”, targeting 219 cancer susceptibility genes. Besides more than 50 clinically important high- and moderate-penetrance susceptibility genes, the panel also targets less common candidate genes with uncertain clinical relevance. Alongside the panel design, we have optimized the analytical and bioinformatics pipeline, which will facilitate establishing a collective nationwide database of genotypes and clinical data from the analyzed individuals. The key objective of this project is to provide diagnostic laboratories in the Czech Republic with a reliable procedure and collective database improving the clinical utility of next-generation sequencing analyses in high-risk patients, which would help improve the interpretation of rare or population-specific variants in cancer susceptibility genes. Key words: genetic predisposition testing – hereditary cancer syndromes – high-throughput nucleotide sequencing – genetic information databases – panel sequencing – sequence capture – next-generation sequencing (NGS) This work was supported by Czech Ministry of Health grants No. NT14054, NV15-28830A, NV15--27695A and The League Against Cancer Prague. The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers. Submitted: 2. 10. 2015 Accepted: 13. 10. 2015

• Keywords
• sekvenování nové generace (NGS), cílené sekvenování, panelové sekvenování,
• MeSH
• Databases, Genetic * utilization   MeSH
• Neoplastic Syndromes, Hereditary * diagnosis   genetics   MeSH
• Genetic Predisposition to Disease MeSH
• Genetic Testing methods   MeSH
• Humans MeSH
• Sequence Analysis, DNA MeSH
• Information Dissemination MeSH
• Computational Biology MeSH
• High-Throughput Nucleotide Sequencing * MeSH
• Research Design MeSH
• Germ-Line Mutation MeSH
• Check Tag
• Humans MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH

• MeSH
• Genetics MeSH
• Genetics, Medical MeSH
• Genetics, Population MeSH

• Conspectus
• Obecná genetika. Obecná cytogenetika. Evoluce
• NML Fields
• genetika, lékařská genetika
• biologie
• NML Publication type
• učebnice vysokých škol

Accurate annotation of genomic variants in human diseases is essential to allow personalized medicine. Assessment of somatic and germline TP53 alterations has now reached the clinic and is required in several circumstances such as the identification of the most effective cancer therapy for patients with chronic lymphocytic leukemia (CLL). Here, we present Seshat, a Web service for annotating TP53 information derived from sequencing data. A flexible framework allows the use of standard file formats such as Mutation Annotation Format (MAF) or Variant Call Format (VCF), as well as common TXT files. Seshat performs accurate variant annotations using the Human Genome Variation Society (HGVS) nomenclature and the stable TP53 genomic reference provided by the Locus Reference Genomic (LRG). In addition, using the 2017 release of the UMD_TP53 database, Seshat provides multiple statistical information for each TP53 variant including database frequency, functional activity, or pathogenicity. The information is delivered in standardized output tables that minimize errors and facilitate comparison of mutational data across studies. Seshat is a beneficial tool to interpret the ever-growing TP53 sequencing data generated by multiple sequencing platforms and it is freely available via the TP53 Website, http://p53.fr or directly at http://vps338341.ovh.net/.

• MeSH
• Molecular Sequence Annotation MeSH
• Databases, Genetic * MeSH
• Genetic Variation genetics   MeSH
• Genomics trends   MeSH
• Internet MeSH
• Humans MeSH
• Mutation MeSH
• Tumor Suppressor Protein p53 genetics   MeSH
• Software * MeSH
• Computational Biology trends   MeSH
• High-Throughput Nucleotide Sequencing MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Objectives: Phosphoribosylpyrophosphate synthetase (PRPS1) superactivity is an X-linked disorder characterized by urate overproduction Online Mendelian Inheritance in Man (OMIM) gene reference 300661. This condition is thought to rarely affect women, and when it does, the clinical presentation is mild. We describe a 16-year-old African American female who developed progressive tophi, nephrolithiasis and acute kidney failure due to urate overproduction. Family history included a mother with tophaceous gout who developed end-stage kidney disease due to nephrolithiasis and an affected sister with polyarticular gout. The main aim of this study was to describe the clinical manifestations of PRPS1 superactivity in women. Methods: Whole exome sequencing was performed in affected females and their fathers. Results: Mutational analysis revealed a new c.520 G > A (p.G174R) mutation in the PRPS1 gene. The mutation resulted in decreased PRPS1 inhibition by ADP. Conclusion: Clinical findings in previously reported females with PRPS1 superactivity showed a high clinical penetrance of this disorder with a mean serum urate level of 8.5 (4.1) mg/dl [506 (247) μmol/l] and a high prevalence of gout. These findings indicate that all women in families with PRPS1 superactivity should be genetically screened for a mutation (for clinical management and genetic counselling). In addition, women with tophaceous gout, gout presenting in childhood, or a strong family history of severe gout should be considered for PRPS1 mutational analysis.

• MeSH
• Arthritis, Gouty etiology   genetics   MeSH
• Adult MeSH
• Genetic Diseases, X-Linked diagnosis   genetics   MeSH
• Humans MeSH
• Adolescent MeSH
• Molecular Structure MeSH
• Mutation MeSH
• Nephrolithiasis etiology   genetics   MeSH
• Purine-Pyrimidine Metabolism, Inborn Errors complications   diagnosis   genetics   MeSH
• Ribose-Phosphate Pyrophosphokinase genetics   metabolism   MeSH
• Pedigree MeSH
• Whole Genome Sequencing methods   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Case Reports MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH

• MeSH
• Genetics, Medical MeSH

• Conspectus
• Obecná genetika. Obecná cytogenetika. Evoluce
• NML Fields
• genetika, lékařská genetika