FunForGen

Individual variants in the DNA sequence (i.e. the linear sequence of the 4 DNA building blocks, the so-called bases) are called polymorphisms and can influence the function of genes and thus contribute to the clinical manifestation of diseases or influence their course and therapy. In addition, polymorphism patterns can be so characteristic for each individual that they also enable the forensic identification of perpetrators and victims on the basis of a DNA trace. The determination of polymorphisms is thus a tool for both forensics and clinical diagnostics. In recent years, DNA analysis has experienced a revolution through the development of high-throughput methods for DNA sequence determination (so-called "Next Generation Sequencing", NGS). In contrast to previous methods, they allow the simultaneous analysis of numerous different DNA sections, so that a very large amount of genetic information can be determined within a few days at relatively low cost. The evaluation of this complex data would be inconceivable without the simultaneous development of bioinformatics procedures that match the sequence information obtained with information available in databases, for example, and thus help to filter out characteristic features.

The university research focus "Functional and Forensic Genomics" aims to develop the necessary analytical expertise in this forward-looking field of application of DNA analytics. This technical goal is being pursued by means of four sub-projects that are important in forensic DNA analysis as well as in clinical diagnostics.

• Sequence determination of forensic STR loci, whose variants are currently distinguished solely on the basis of sequence length. Sequence determination will also detect additional, finer differences and thus improve the evaluation of previously problematic traces.
• Elucidation of patient-specific DNA sequence variants in certain genes that can influence the course and, in particular, the so far hardly predictable success of therapy in Parkinson's disease. The sequence variants found will then be functionally investigated in the laboratory (using molecular biological and electrophysiological methods).
• Elucidation of patient-specific DNA sequence variants in genes responsible for specific, rare hereditary metabolic diseases (acyl metabolic disorders). This should contribute to a better understanding of the diseases, which could result in improved diagnostics and possibly also improved therapies. Sequence variants found are then to be functionally investigated in the laboratory (using biochemical and molecular biological methods).
• Creation of bioinformatics tools for the targeted evaluation of the large amount of data. In particular, the automatic assignment of the sequence data to the investigated genes and the extraction and annotation of relevant sequence variants are to be implemented. Complementary, a prediction of possible molecular effects of the polymorphisms is to be made possible by means of database comparisons and molecular models.

Publications

Poethe, S.-S., Holtel, J., Biermann, Riemer, T., J.-P., Grabmüller, M., Madea, B., Thiele, R. & Jäger,   R. (2023) Cost-Effective Next Generation Sequencing-Based STR Typing with Improved Analysis of Minor, Degraded and Inhibitor-Containing DNA Samples. Int. J. Mol. Sci. 24, 3382.

Heß, S.A., Trapani, S., Boronat, M.d.M., Theunissen, G.M.G., Rolf, B. & Jäger, R. (2021) Ribosomal DNA as target for the assessment of DNA degradation of human and canine DNA. Legal Med. 48: 101819.

Schulke D. & Sass J.O. (2021) Frequent sequence variants of human glycine N-acyltransferase (GLYAT) and inborn errors of metabolism. Biochimie 183: 30-34.

Sass J.O., Behringer S., Fernando M., Cesaroni E., Cursio I., Volpini A. & Till C. (2020) D-Glycerate kinase deficiency in a neuropediatric patient. Brain Dev. 42: 226-230.

Tsortouktzidis D., Grundke K., Till C., Korwitz-Reichelt A. & Sass J.O. (2019) Acylpeptide hydrolase (APEH) sequence variants with potential impact on the metabolism of the antiepileptic drug valproic acid. Metab Brain Dis. 34: 1629-1634.

Heß, S.A., Biermann, J.-P., Grabmüller, M., Madea, B., Thiele, R. & Jäger, R. (2019) Evaluation of STR profiles of single telogen hairs using probabilistic methods. Forensic Sci Int: Genetics Suppl. 7: e454-e456.

Sass J.O., Kalkan Uçar S. & van Karnebeek C.D.M. (2018) From rodent heart to inborn errors of human metabolism. Mol Genet Metab. 123: 287-288.