Resumen de Highly accurate variant detection for identification of tumor mutations and mosaic variants
The rapid development of high-throughput sequencing technologies pushed forward the fields of medical genomics and precision medicine, creating many new applications for diagnostics and clinical studies that require high quality data and highly accurate analysis methods (Shendure et al., 2017; Pfeiffer et al., 2018). Distinguishing errors from real variants in Next Generation Sequencing data is a challenge when systematic errors, random sequencing errors, germline variants or somatic variants at very low allele frequency are present in the same data (Li, 2014). In the first part of this thesis, we developed a genotype callability filter (ABB) able to identify systematic variant calling errors that were not found by state-of-the art methods. This tool cleans false positive calls from somatic and germline variant callsets, as well as detects false gene-disease associations in case-control studies. Secondly, we developed a set of novel methods able to distinguish and correct sequencing and PCR errors with the use of molecular barcodes, permitting us to build error rate models for the detection of somatic mutations at extremely low allele frequencies. We demonstrated the applicability of our methods for liquid biopsy and monitoring of cancer treatment response in a longitudinal study of the circulating-tumor DNA (ctDNA) kinetics in 20 head and neck squamous cell carcinoma patients during radiochemotherapy (RCTX). As final part of this thesis, we characterized mosaic mutations in a multi-tissue, multi-individual study using a cohort of thousands of samples from hundreds of healthy individuals (Ardlie et al., 2015). The high number of embryonic mosaic mutations we observed in coding regions implies novel hypotheses and diagnostic procedures for investigating genetic causes of disease and cancer predisposition.
Ardlie KG, Deluca DS, Segre A V., Sullivan TJ, Young TR, Gelfand ET, Trowbridge CA, Maller JB, Tukiainen T, Lek M, Ward LD, Kheradpour P, et al. 2015. The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans. Science (80- ) 348:648–660.
Li H. 2014. Toward better understanding of artifacts in variant calling from high-coverage samples. Bioinformatics 1–9.
Pfeiffer F, Gröber C, Blank M, Händler K, Beyer M, Schultze JL, Mayer G. 2018. Systematic evaluation of error rates and causes in short samples in next-generation sequencing. Sci Rep 8:10950.
Shendure J, Balasubramanian S, Church GM, Gilbert W, Rogers J, Schloss JA, Waterston RH. 2017. DNA sequencing at 40: past, present and future. Nature 550:345–353.
