As the field of next-generation sequencing (NGS) matures and the technology grows more advanced, it is becoming an increasingly strong tool for solving various biological problems. Harvesting and analysing the full genomic sequence of an individual and comparing it to a reference genome can unravel information about detrimental mutations, in particular ones that give rise to diseases such as cancer. At the Rudbeck Laboratory, Uppsala University, a fully automatic software pipeline for somatic mutational analysis of cancer patient sequence data is in development. This will increase the efficiency and accuracy of a process which today consists of several discrete computation steps. In turn, this will reduce the time to result and facilitate the process of making a diagnosis and delegate the optimal treatment for the patient. However, the genomic data of an individual is very sensitive and private, which demands that great security precautions are taken. Moreover, as more and more data are produced storage space is becoming increasingly valuable, which requires that data are handled and stored as efficiently as possible. In this project, I developed a Python pipeline for automatic compression and encryption of NGS alignment data, which aims to ensure full privacy protection of patient data while maintaining high computational and storage efficiency. The pipeline uses a state-of-the-art real-time compression algorithm combined with an Advanced Encryption Standard cipher. It offers security that meets rigorous modern standards, and performance which at least matches that of existing solutions. The system is made to be easily integrated in the somatic mutation analysis pipeline. This way, the data generated during the analysis, which are too large to be kept in operational memory, can safely be stored to disk.

On average, 5-10% of all cancers occur in patients with hereditary tumors, who may have mutations in tens to hundreds of tumor predisposition genes. The phenotypes in mutation carriers overlap, and parallel analyses with sequencing panels is the method of choice in diagnostics. In our laboratory, we designed a universal panel and a targeted panel for a specific cancer, which allowed us to identify genetic alterations in patients with ovarian cancer, breast cancer, melanoma, and other cancers in the Czech Republic. The results of next generation sequencing (NGS) analyses show that the most frequent genetic alteration in ovarian cancers patients in the Czech Republic are hereditary mutations in BRCA1 (in 24% of unselected patients) and in malignant melanoma patients CDKN2A (in 2% of high risk patients). The presence of hereditary alterations is a clinically significant phenomenon affecting the prognosis and treatment of the disease. However, the interpretation of NGS findings is complicated by the presence of variants of unknown significance (VUS). We participate in the interpretation of VUS in the main predisposing genes BRCA1 and BRCA2 within the international consortium ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles). Our and international results of the most...

Familial adenomatous polyposis (FAP) is a condition caused by germline mutations in tumor suppressor gene APC, inherited in autosomal dominant manner. Patients with FAP develop hundreds to thousands of adenomatous colorectal polyps with extremely high risk of malignant reversal into adenocarcinoma of colon and/or rectum. The aim of this thesis is to re-analyze a cohort of highly suspected FAP probands from years 1993-2004 whose diagnosis previously failed to be confirmed by at that time commonly used methods of molecular diagnostics. Next generation sequencing on MiSeq and NextSeq platforms (Illumina®) was performed on 78 samples of probands' DNA, isolated from peripheral blood, using gene panel CZECANCA version 1.2 (Czech Cancer Panel for Clinical Application). The panel enables sequencing of exons and exon-intron junctions of 226 genes linked to hereditary cancer predispositions, newly also including the diagnostically important promoter 1B region of APC. Pathogenic variant in the APC gene was detected in 18 % of re-analyzed probands, 11 % of probands carry pathogenic variants in other genes associated with colorectal polyps. Additional 13 % of probands are carriers of a variants of unknown clinical significance. NGS gene panel CZECANCA enabled diagnosis confirmation or re-evaluation of 22 FAP...

Human noroviruses are a major cause of acute gastroenteritis worldwide and can betransmitted through consumption of contaminated raw food. Shellfish like oysters can becontaminated by human sewage during production and accumulate multiple Norovirus strainsin low concentrations. Here we developed a simplified and cost effective targetedmetagenomic approach by sequencing PCR amplicons with next generation sequencing(NGS) of the capsid (VP1) viral gene. New design of reverse primers using the codehopstrategy and direct addition of illumina adapter with one step RT-PCR and sequencing onnano chip reduced hand on time and cost of the analysis. A mix of faecal samples and oystersamples associated with outbreaks were used to evaluate the ability and limitations in theidentification of strains from Norovirus genogroup I (GI) and genogroup II (GII). Withsamples containing only one genotype the method was able to identify all strains. Usingartificially mixed samples the method was able to identify almost all strains except a few GIIat low concentrations. Oyster samples showed more limitations for the method and it waswere only able to identify the strain in some of the samples but did find multiple GI strains inmore than one sample. Despite some limitations, the simplified method for VP1-targetedmetagenomics is a sensitive approach allowing the study of norovirus diversity incontaminated oysters and the identification of norovirus strains implicated in outbreaks. Thisat a lower cost and hands on time compared to published methods.

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Affinity ligands are important molecules used in affinity chromatography for purification of significant substances from complex mixtures. To find affinity ligands specific to important target molecules could be a challenging process. Cytiva uses the powerful phage display technique to find new promising affinity ligands. The phage display technique is a method run in several enrichment cycles. When developing new affinity ligands, a protein scaffold library with a diversity of up to 1010-1011 different protein scaffold variants is run through the enrichment cycles.  The result from the phage display rounds is screened for target molecule binding followed by sequencing, usually with one of the conventional screening methods ELISA or Biacore followed by Sanger sequencing. However, the throughput of these analyses are unfortunately very low, often with only a few hundred screened clones. Therefore, Next Generation Sequencing or NGS, has become an increasingly popular screening method for phage display libraries which generates millions of sequences from each phage display round. This creates a need for a robust data analysis pipeline to be able to interpret the large amounts of data.  In this project, a pipeline for analysis of NGS data of phage displayed libraries has been developed at Cytiva. Cytiva uses NGS as one of their screening methods of phage displayed protein libraries because of the high throughput compared to the conventional screening methods. The purpose is to find new affinity ligands for purification of essential substances used in drugs.  The pipeline has been created using the object-oriented programming language R and consists of several analyses covering the most important steps to be able to find promising results from the NGS data. With the developed pipeline the user can analyze the data on both DNA and protein sequence level and per position residue breakdown, as well as filter the data based on specific amino acids and positions. This gives a robust and thorough analysis which can lead to promising results that can be used in the development of novel affinity ligands for future purification products.

Epigenetic modifications, such as DNA methylation and histone modifications, play important roles in gene expression and regulation, and are highly involved in cellular processes such as stem cell pluripotency/differentiation and tumorigenesis. Chromatin immunoprecipitation (ChIP) is the technique of choice for examining in vivo DNA-protein interactions and has been a great tool for studying epigenetic mechanisms. However, conventional ChIP assays require millions of cells for tests and are not practical for examination of samples from lab animals and patients. Automated microfluidic chips offer the advantage to handle small sample sizes and facilitate rapid reaction. They also eliminate cumbersome manual handling. In this report, I will talk about three different projects that utilized microfluidic immunoprecipitation followed by next genereation sequencing technologies to enable low input and high through epigenomics profiling. First, I examined RNA polymerase II transcriptional regulation with microfluidic chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) assays. Second, I probed the temporal dynamics in the DNA methylome during cancer development using a transgenic mouse model with microfluidic methylated DNA immunoprecipitation followed by next generation sequencing (MeDIP-seq) assays. Third, I explored negative enrichment of circulating tumor cells (CTCs) followed by microfluidic ChIP-seq technology for studying temporal dynamic histone modification (H3K4me3) of patient-derived tumor xenograft on an immunodeficient mouse model during the course of cancer metastasis. In the first study, I adapted microfluidic ChIP-seq devices to achieve ultrahigh sensitivity to study Pol2 transcriptional regulation from scarce cell samples. I dramatically increased the assay sensitivity to an unprecedented level (~50 K cells for pol2 ChIP-seq). Importantly, this is three orders of magnitude more sensitive than the prevailing pol2 ChIP-seq assays. I showed that MNase digestion provided better ChIP-seq signal than sonication, and two-steps fixation with MNase digestion provided the best ChIP-seq quality followed by one-step fixation with MNase digestion, and lastly, no fixation with MNase digestion. In the second study, I probed dynamic epigenomic changes during tumorigenesis using mice often require profiling epigenomes using a tiny quantity of tissue samples. Conventional epigenomic tests do not support such analysis due to the large amount of materials required by these assays. In this study, I developed an ultrasensitive microfluidics-based methylated DNA immunoprecipitation followed by next-generation sequencing (MeDIP-seq) technology for profiling methylomes using as little as 0.5 ng DNA (or ~100 cells) with 1.5 h on-chip process for immunoprecipitation. This technology enabled me to examine genome-wide DNA methylation in a C3(1)/SV40 T-antigen transgenic mouse model during different stages of mammary cancer development. Using this data, I identified differentially methylated regions and their associated genes in different periods of cancer development. Interestingly, the results showed that methylomic features are dynamic and change with tumor developmental stage. In the last study, I developed a negative enrichment of CTCs followed by ultrasensitive microfluidic ChIP-seq technology for profiling histone modification (H3K4Me3) of CTCs to resolve the technical challenges associated with CTC isolation and difficulties related with tools for profiling whole genome histone modification on tiny cell samples. / Ph. D.

Identification of recurrent mutations through next-generation sequencing (NGS) has given us a deeper understanding of the molecular mechanisms involved in chronic lymphocytic leukemia (CLL) development and progression and provided novel means for risk assessment in this clinically heterogeneous disease. In paper I, we screened a population-based cohort of CLL patients (n=364) for TP53, NOTCH1, SF3B1, BIRC3 and MYD88 mutations using Sanger sequencing, and confirmed the negative prognostic impact of TP53, SF3B1 or NOTCH1 aberrations, though at lower frequencies compared to previous studies. In paper II, we assessed the feasibility of targeted NGS using a gene panel including 9 CLL-related genes in a large patient cohort (n=188). We could validate 93% (144/155) of mutations with Sanger sequencing; the remaining were at the detection limit of the latter technique, and technical replication showed a high concordance (77/82 mutations, 94%). In paper III, we performed a longitudinal study of CLL patients (n=41) relapsing after fludarabine, cyclophosphamide and rituximab (FCR) therapy using whole-exome sequencing. In addition to known poor-prognostic mutations (NOTCH1, TP53, ATM, SF3B1, BIRC3, and NFKBIE), we detected mutations in a ribosomal gene, RPS15, in almost 20% of cases (8/41). In extended patient series, RPS15-mutant cases had a poor survival similar to patients with NOTCH1, SF3B1, or 11q aberrations. In vitro studies revealed that RPS15mut cases displayed reduced p53 stabilization compared to cases wildtype for RPS15. In paper IV, we performed RNA-sequencing in CLL patients (n=50) assigned to 3 clinically and biologically distinct subsets carrying stereotyped B-cell receptors (i.e. subsets #1, #2 and #4) and revealed unique gene expression profiles for each subset. Analysis of SF3B1-mutated versus wildtype subset #2 patients revealed a large number of splice variants (n=187) in genes involved in chromatin remodeling and ribosome biogenesis. Taken together, this thesis confirms the prognostic impact of recurrent mutations and provides data supporting implementation of targeted NGS in clinical routine practice. Moreover, we provide evidence for the involvement of novel players, such as RPS15, in disease progression and present transcriptome data highlighting the potential of global approaches for the identification of molecular mechanisms contributing to CLL development within prognostically relevant subgroups.

Characterising and understanding factors that affect the rate of molecular evolution in proteins has played a major part in the development of evolutionary theory. The early analyses of amino acid substitutions stimulated the development of the neutral theory of molecular evolution, which later evolved into the nearly neutral theory. More recent work has lead to a better understanding of the role selection plays at the molecular level, but there is still limited understanding of how higher levels of protein organisation affect the way natural selection acts. The investigation of this question is the central aim of this thesis, which is addressed via the analysis of selective pressures in secondary protein structures in insects, mammals and fungi. The analyses for the first two groups were conducted using publically available datasets. To conduct the analyses in fungi, genome sequence data from the fungal genus Microbotryum (sequenced in our laboratory) was assembled and annotated, resulting in the development of a number of bioinformatics tools which are described here. The fungal, insect and mammalian datasets were interrogated with regard to a number of structural features, such as protein secondary structure, position of a site with regard to adaptively evolving sites, hydropathy and solvent-accessibility. These features were correlated with the signals of positive and purifying selection detected using phylogenetic maximum likelihood and Bayesian approaches. I conclude that all of the factors examined can have an effect on the rate of molecular evolution. In particular, disordered and hydrophilic regions of the protein are found to experience fewer physiochemical constraints and contain a higher proportion of adaptively evolving sites. It is also revealed that positively selected residues are ‘clustered’ together spatially, and these trends persist in the three taxa. Finally, I show that this variation in adaptive evolution is a result of both selective events and physiochemical constraint.

Chronic Lymphocytic Leukemia (CLL) is a type of cancer that affects the B cells of the immune system causing problems in the process of producing antibodies. It can be sorted into mutated and unmutated CLL based on the percentage of somatic mutations in the Immunoglobulin Heavy chain Variable region (IgHV). The B cells of healthy individuals can be sorted into three groups; CD27dull memory B cells (MBCs), CD27bright MBCs and naïve B cells. The hypothesis for the project was that the unmutated CLL subset originates from CD27dull MBCs and the mutated CLL subset originates from CD27bright MBCs. RNA-sequencing data from healthy individuals were acquired from a collaboration partner in Rome and CLL-patients were collected from public datasets available online. Several bioinformatic tools were used to analyze the data. First, the quality of the data files was checked, then adapter sequence from the sequencing process and low-quality bases were removed (trimming). Good quality of the files was confirmed after the trimming. Secondly, these files were mapped against the human reference genome (GRCh38/hg38) for alignment, then the resulted data was used to check for genes that showed differential expression between the different groups. Results were analyzed and visualized using Venn diagrams, Principal Component Analysis (PCA) and heatmap plots and random forest. A list of 85 genes was generated based on the different comparisons and was used in one PCA plot that showed clear separation between the different groups. The SWAP70 gene was analyzed for single nucleotide polymorphisms (SNPs). The study concluded five genes that could be used as biomarkers for CLL and the diagnosis of its subtypes where some of them were discussed in previous studies. Also, the mutated CLL subset showed a similar behavior to the healthy individuals and this could validate the original hypothesis and justifies the better disease prognosis for this subtype.