Východiska: Hereditární nádorové syndromy tvoří významnou podskupinu zhoubných nádorových onemocnění způsobených patogenními variantami v některém z mnoha známých nádorových predispozičních genů. Diagnostika nádorové predispozice je založena na genetickém testování pomocí sekvenování nové generace. To umožňuje analýzu mnoha genů najednou, nicméně zároveň se zvyšuje počet identifikovaných variant. Správná klasifikace nalezených variant je zásadní pro klinickou interpretaci výsledků genetického testování. Cíl: Cílem práce je shrnutí pravidel pro klasifikaci identifikovaných variant v rámci jednotlivých pracovišť a představení procesu tvorby společné klasifikace. Sdílení nalezených genetických variant a tvorba jejich konsenzuální klasifikace v rámci národních laboratorně diagnostických komunit probíhá v ČR v rámci konzorcia Czech Cancer Panel for Clinical Application (CZECANCA) sdružujícího výzkumné a diagnostické onkogenetické laboratoře. Tvorba konsenzu pro klasifikaci variant probíhá podle definovaného protokolu. Sdílení výsledků a konsenzuální klasifikace zrychluje a zpřesňuje vydávání výsledků genetického testování, harmonizuje výsledky mezi laboratořemi a přispívá tak ke zkvalitnění péče o jedince ve vysokém riziku vzniku nádorových onemocnění a jejich příbuzné.
Background: Hereditary cancer syndromes are an important subset of malignant cancers caused by pathogenic variants in one of many known cancer predisposition genes. Diagnosis of cancer predisposition is based on genetic testing using next-generation sequencing. This allows many genes to be analysed at once, increasing the number of variants identified. The correct classification of the variants found is essential for the clinical interpretation of genetic test results. Purpose: The aim of this study is to summarise the rules for classifying identified variants within individual laboratories and to present the process for creating a common classification. In the Czech Republic, the sharing of identified genetic variants and the development of their consensus classification among national laboratory diagnostic communities is carried out within the Czech Cancer Panel for Clinical Application (CZECANCA) consortium of scientific and diagnostic oncogenetic laboratories. Consensus for variant classification follows a defined protocol. Sharing the results and consensus classification accelerates and refines the release of genetic test results, harmonises results between laboratories and thus contributes to improving the care of individuals at high risk of cancer and their relatives.
- Keywords
- CZECANCA,
- MeSH
- Neoplastic Syndromes, Hereditary * diagnosis genetics classification MeSH
- Genetic Predisposition to Disease genetics prevention & control MeSH
- Genetic Testing methods MeSH
- Classification MeSH
- Consensus * MeSH
- Humans MeSH
- Neoplasms genetics classification MeSH
- High-Throughput Nucleotide Sequencing methods MeSH
- Germ-Line Mutation genetics MeSH
- Check Tag
- Humans MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
- Geographicals
- Czech Republic MeSH
OBJECTIVES: Schizophrenia is a severe psychiatric disease affecting about 1% of the general population. The relative contribution of genetic factors has been estimated to be up to 80%. The mode of inheritance is complex, non-Mendelian, and in most cases involving the combined action of large numbers of genes. METHODS: This review summarises recent efforts to identify genetic variants associated with schizophrenia detected, e.g., through genome-wide association studies, studies on copy-number variants or next-generation sequencing. RESULTS: A large, new body of evidence on genetics of schizophrenia has accumulated over recent years. Many new robustly associated genetic loci have been detected. Furthermore, there is consensus that at least a dozen microdeletions and microduplications contribute to the disease. Genetic overlap between schizophrenia, other psychiatric disorders, and neurodevelopmental syndromes raised new questions regarding the current classification of psychiatric and neurodevelopmental diseases. CONCLUSIONS: Future studies will address especially the functional characterisation of genetic variants. This will hopefully open the doors to our understanding of the pathophysiology of schizophrenia and other related diseases. Complementary, integrated systems biology approaches to genomics, transcriptomics, proteomics and metabolomics may also play crucial roles in enabling a precision medicine approach to the treatment of individual patients.
- MeSH
- Consensus * MeSH
- Humans MeSH
- Schizophrenia genetics MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
MOTIVATION: Satellite DNA makes up significant portion of many eukaryotic genomes, yet it is relatively poorly characterized even in extensively sequenced species. This is, in part, due to methodological limitations of traditional methods of satellite repeat analysis, which are based on multiple alignments of monomer sequences. Therefore, we employed an alternative, alignment-free, approach utilizing k-mer frequency statistics, which is in principle more suitable for analyzing large sets of satellite repeat data, including sequence reads from next generation sequencing technologies. RESULTS: k-mer frequency spectra were determined for two sets of rice centromeric satellite CentO sequences, including 454 reads from ChIP-sequencing of CENH3-bound DNA (7.6 Mb) and the whole genome Sanger sequencing reads (5.8 Mb). k-mer frequencies were used to identify the most conserved sequence regions and to reconstruct consensus sequences of complete monomers. Reconstructed consensus sequences as well as the assessment of overall divergence of k-mer spectra revealed high similarity of the two datasets, suggesting that CentO sequences associated with functional centromeres (CENH3-bound) do not significantly differ from the total population of CentO, which includes both centromeric and pericentromeric repeat arrays. On the other hand, considerable differences were revealed when these methods were used for comparison of CentO populations between individual chromosomes of the rice genome assembly, demonstrating preferential sequence homogenization of the clusters within the same chromosome. k-mer frequencies were also successfully used to identify and characterize smRNAs derived from CentO repeats.
- MeSH
- Centromere genetics MeSH
- Chromosomes, Plant genetics MeSH
- DNA, Plant genetics MeSH
- Conserved Sequence genetics MeSH
- Molecular Sequence Data MeSH
- Oryza genetics MeSH
- DNA, Satellite genetics MeSH
- Base Sequence MeSH
- Sequence Analysis, DNA methods 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
