Rare diseases represent a heterogeneous group of more than ~7000 different diseases, affecting 3,5-5,9% of the global population. Most rare diseases are genetic, but causal genes are known only in some of them. Many patients with rare diseases remain without a diagnosis, which is crucial for genetic counseling, prevention, and treatment. With the development of new methods of genome analysis, decreasing cost of sequencing, and increasing knowledge of the human genome, a new concept for identifying disease-causing genes was established. It is based on comparing the patient's genetic variability with the genetic variability of the general population. This dissertation describes next-generation sequencing technologies (NGS), bioinformatic analysis of acquired data and their applications in the elucidation of molecular underpinnings of rare genetic diseases. These procedures have led to the identification and characterization of causal genes and gene mutations in autosomal dominant tubulointerstitial kidney disease (SEC61A1, MUC1), autosomal dominant neuronal ceroid lipofuscinosis (CLN6, DNAJC5), neurodegenerative disease of unknown etiology (VPS15), Acadian variant of Fanconi syndrome (NDUFAF6) and spinal muscular atrophy (SMN1). The application of novel genome analysis techniques increased the...
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:434248 |
| Date | January 2020 |
| Creators | Přistoupilová, Anna |
| Contributors | Kmoch, Stanislav, Sedláček, Zdeněk, Pačes, Jan |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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