Le CD81 est une molécule de surface appartenant à la superfamille des tetraspanines. Son rôle pronostique a été précédemment étudié dans les pathologies lymphoïdes, dont le myélome multiple où son expression est associée à un pronostic péjoratif. A ce jour, ce marqueur n'a pas été étudié dans les leucémies aiguës myéloïdes (LAM). Nous avons étudié l'expression membranaire du CD81 sur les blastes de LAM au diagnostic, son association aux autres caractéristiques des LAM et sa potentielle influence sur la survie des patients sur une cohorte de 134 patients traités par chimiothérapie intensive.Le CD81 a été retrouvé chez 92 patients sur 134 (69%). Les patients exprimant ce marqueur avaient une leucocytose initiale plus élevée (p=0.02) et présentaient une cytogénétique intermédiaire ou défavorable (p<0.001). L'expression du CD81 avait un impact négatif sur la survie des patients (survie sans évènements (EFS), survie globale (OS), survie sans rechute (RFS)) en analyse uni- (p<0.001) et multivariées (p=0.003, 0.002 and <0.001 respectivement).De plus, le CD81 avait un impact négatif sur l'OS des patients avec une mutation de NPM1 (p=0.01) et chez les patients du groupe cytogénétique favorable (p=0.002) selon la classification ELN.Les anomalies du cycle cellulaire étant associées à la chimiorésistance, la croissance tumorale et l'agressivité de la pathologie, nous avons étudié l'expression du Ki67 sur les blastes de LAM au diagnostic. Ainsi, 10 prélèvements médullaires de patients avec une faible expression du CD81 par les blastes (moins de 20% de positivité) et 10 prélèvements avec une forte expression du marqueur ont été étudiés. Nous avons pu démontrer une expression significativement inférieure du Ki67 sur les blastes CD81 positifs par rapport aux blastes CD81 négatifs (p<0.001), suggérant ainsi un rôle potentiel du CD81 dans le contrôle du cycle cellulaire. De plus, nous nous sommes intéressés au rôle du CD81 dans la chimiorésistance et sur les différentes voies de signalisation cellulaire en étudiant le profil d'expression génique.En conclusion, le CD81 semble être un nouveau marqueur pronostique des LAM ainsi qu'une cible potentielle de traitement de ces pathologies. / CD81 is a cell surface protein which belongs to the tetraspanin family. While in multiple myeloma its expression on plasma cells is associated with worse prognosis, this has not yet been explored in acute myeloid leukemia (AML). We measured membrane expression of CD81 on AML cells at diagnosis, evaluated its association with AML characteristics and its influence on patient outcome after intensive chemotherapy in a cohort of 134 patients. CD81 was detected in 92/134 (69%) patients. Patients with AML expressing CD81 had elevated leukocyte count (p=0.02) and were more likely classified as intermediate or adverse-risk by cytogenetics (p<0.001). CD81 expression had a negative impact on survival (event-free [EFS], overall [OS] and relapse-free survival [RFS]) in univariate (p<0.001) and in multivariate analyses (p=0.003, 0.002 and <0.001, respectively). CD81 has a negative impact on OS in patients with NPM1 mutation (p=0.01) and in favorable risk patients by European Leukemia Net (ELN) classification (p=0.002).Since aberrations in cell cycle signaling can cause drug resistance, tumor growth and aggressiveness we measured Ki67 on primary blast cells from AML patients. We considered 10 bone marrow samples from AML patients with either weak CD81 expression (less than 20% of blast cells) or 10 bone marrow samples with strong CD81 expression on blasts. We found a significant lower ki67 expression on blast cells from CD81 positive patients compared with those from CD81 negative patients (p<0.001), indicating a potential role of CD81 in cell cycle control. Furthermore, we investigated the role of CD81 in chemotherapy resistance and investigated potentially implicated signaling pathways by gene expression profiling.In conclusion, the cell surface marker CD81 may be a new prognostic marker for diagnostic risk classification and a new potential therapeutic target for drug development in AML.

TITLE: Mutation and substitution rates in sexual and asexual forms: a clue to the persistence of sex in a model group of Cobitis? AUTOR: Jan Röslein DEPARTMENT: Ústav živočišné fyziologie a genetiky AVČR, v.v.i. SUPERVISOR: Mgr. Karel Janko, Ph.D. ABSTRACT: Subject of this thesis is to test several hypotheses about the evolution of asexual reproduction in model group of fish family Cobitis and its mutual competition among sexual and asexual forms, which touches one of the oldest unresolved issues of biology. Specifically, the work deals with the accumulation of non-synonymous mutations, which accelerated accumulation in the genome of clonal lineages theoretically leads to increased extinction compared with sexually reproducing populations (so-called. The theory of Muller's ratchet and Kondrashov's hatchet). This thesis is based on a normalized cDNA sequencing data from oocytes and liver tissue, which has served as a base matrix (generated based on non-normalized cDNA data) for transcriptome sequencing (RNAseq). Consequently, the RNAseq data have served as validation for acquired polymorphisms, detection of differential expression of allele- specific expression (ASE) hybrid biotypes. This diploma thesis balances among the edges of vast spectrum of hypotheses regarding the evolution of the genus hybrid...

Access to primary human corneal endothelial cells (HCEC) is limited and donor-derived differences between cultures exacerbate the issue of data reproducibility, whereas cell lines can provide sufficient numbers of homogenous cells for multiple experiments. An immortalized HCEC population was adapted to serum-free culture medium and repeated cloning was performed. Clonally grown cells were propagated under serum-free conditions and growth curves were recorded. Cells were characterized immunocytochemically for junctional proteins, collagens, Na,K-ATPase and HCEC-specific 9.3.E-antigen. Ultrastructure was monitored by scanning and transmission electron microscopy. Two clonal cell lines, HCEC-B4G12 and HCEC-H9C1, could be isolated and expanded, which differed morphologically: B4G12 cells were polygonal, strongly adherent and formed a strict monolayer, H9C1 cells were less adherent and formed floating spheres. The generation time of B4G12 cells was 62.26 ± 14.5 h and that of H9C1 cells 44.05 ± 5.05 h. Scanning electron microscopy revealed that B4G12 cells had a smooth cell surface, while H9C1 cells had numerous thin filopodia. Both cell lines expressed ZO-1 and occludin adequately, and little but well detectable amounts of connexin-43. Expression of HCEC-specific 9.3.E-antigen was found commensurately in both cell lines, while expression of Na,K-ATPase α1 was higher in H9C1 cells than in B4G12 cells. B4G12 cells expressed collagen IV abundantly and almost no collagen III, while H9C1 cells expressed both collagens at reasonable amounts. It is concluded that the clonal cell line B4G12 represents an ideal model of differentiated HCEC, while H9C1 may reflect features of developing or transitional HCEC. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

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Cytogenetic analysis of cells of chronic lymphocytic leukemia (CLL) is difficult because of their low proliferative activity. To obtain sufficient number of mitoses for performing chromosomal analysis a suitable stimulation of cell division is needed. Using DSP30/IL2 stimulated cultivation 391 CLL samples were investigated in 5 years' period. The cultivation was showed to have high success rate (96%; 375/391) with also high rate of detection of pathological clones by both karyotype and metaphase FISH analyses (in 84% of samples; 329/391). Almost in half of samples (44%; 171/391) other aberrations than recurrent FISH (i.e. 13q14 deletion, trisomy 12, TP53, ATM genes deletions) were found. Also high frequency of translocations (37%; 144/391), complex karyotypes (28%; 111/391) and clonal evolution, which was detected in one third of all samples (34% of samples with presence of more than two clones; 133/391) and like a new event in disease duration even more frequently (in 39% of samples repeatedly investigated after stimulated cultivation; 21/54), was revealed. The presence of translocations, complex karyotypes and clonal evolution was associated with progressive form of disease (P 0,000003, resp. P 0,0002 and P 0,05/P 0,04). In cases of the recurrent deletions the detailed analysis of metaphase...

Genealogy reconstruction is widely used in biology when relationships among entities are studied. Phylogenies, or evolutionary trees, show the differences between species. They are of profound importance because they help to obtain better understandings of evolutionary processes. Pedigrees, or family trees, on the other hand visualize the relatedness between individuals in a population. The reconstruction of pedigrees and the inference of parentage in general is now a cornerstone in molecular ecology. Applications include the direct infer- ence of gene flow, estimation of the effective population size and parameters describing the population’s mating behaviour such as rates of inbreeding. In the first part of this thesis, we construct genealogies of various types of cancer. Histopatho- logical classification of human tumors relies in part on the degree of differentiation of the tumor sample. To date, there is no objective systematic method to categorize tumor subtypes by maturation. We introduce a novel algorithm to rank tumor subtypes according to the dis- similarity of their gene expression from that of stem cells and fully differentiated tissue, and thereby construct a phylogenetic tree of cancer. We validate our methodology with expression data of leukemia and liposarcoma subtypes and then apply it to a broader group of sarcomas and of breast cancer subtypes. This ranking of tumor subtypes resulting from the application of our methodology allows the identification of genes correlated with differentiation and may help to identify novel therapeutic targets. Our algorithm represents the first phylogeny-based tool to analyze the differentiation status of human tumors. In contrast to asexually reproducing cancer cell populations, pedigrees of sexually reproduc- ing populations cannot be represented by phylogenetic trees. Pedigrees are directed acyclic graphs (DAGs) and therefore resemble more phylogenetic networks where reticulate events are indicated by vertices with two incoming arcs. We present a software package for pedigree reconstruction in natural populations using co-dominant genomic markers such as microsatel- lites and single nucleotide polymorphism (SNPs) in the second part of the thesis. If available, the algorithm makes use of prior information such as known relationships (sub-pedigrees) or the age and sex of individuals. Statistical confidence is estimated by Markov chain Monte Carlo (MCMC) sampling. The accuracy of the algorithm is demonstrated for simulated data as well as an empirical data set with known pedigree. The parentage inference is robust even in the presence of genotyping errors. We further demonstrate the accuracy of the algorithm on simulated clonal populations. We show that the joint estimation of parameters of inter- est such as the rate of self-fertilization or clonality is possible with high accuracy even with marker panels of moderate power. Classical methods can only assign a very limited number of statistically significant parentages in this case and would therefore fail. The method is implemented in a fast and easy to use open source software that scales to large datasets with many thousand individuals.:Abstract v Acknowledgments vii 1 Introduction 1 2 Cancer Phylogenies 7 2.1 Introduction..................................... 7 2.2 Background..................................... 9 2.2.1 PhylogeneticTrees............................. 9 2.2.2 Microarrays................................. 10 2.3 Methods....................................... 11 2.3.1 Datasetcompilation ............................ 11 2.3.2 Statistical Methods and Analysis..................... 13 2.3.3 Comparison of our methodology to other methods . . . . . . . . . . . 15 2.4 Results........................................ 16 2.4.1 Phylogenetic tree reconstruction method. . . . . . . . . . . . . . . . . 16 2.4.2 Comparison of tree reconstruction methods to other algorithms . . . . 28 2.4.3 Systematic analysis of methods and parameters . . . . . . . . . . . . . 30 2.5 Discussion...................................... 32 3 Wild Pedigrees 35 3.1 Introduction..................................... 35 3.2 The molecular ecologist’s tools of the trade ................... 36 3.2.1 3.2.2 3.2.3 3.2.1 Sibship inference and parental reconstruction . . . . . . . . . . . . . . 37 3.2.2 Parentage and paternity inference .................... 39 3.2.3 Multigenerational pedigree reconstruction . . . . . . . . . . . . . . . . 40 3.3 Background..................................... 40 3.3.1 Pedigrees .................................. 40 3.3.2 Genotypes.................................. 41 3.3.3 Mendelian segregation probability .................... 41 3.3.4 LOD Scores................................. 43 3.3.5 Genotyping Errors ............................. 43 3.3.6 IBD coefficients............................... 45 3.3.7 Bayesian MCMC.............................. 46 3.4 Methods....................................... 47 3.4.1 Likelihood Model.............................. 47 3.4.2 Efficient Likelihood Calculation...................... 49 3.4.3 Maximum Likelihood Pedigree ...................... 51 3.4.4 Full siblings................................. 52 3.4.5 Algorithm.................................. 53 3.4.6 Missing Values ............................... 56 3.4.7 Allelefrequencies.............................. 58 3.4.8 Rates of Self-fertilization.......................... 60 3.4.9 Rates of Clonality ............................. 60 3.5 Results........................................ 61 3.5.1 Real Microsatellite Data.......................... 61 3.5.2 Simulated Human Population....................... 62 3.5.3 SimulatedClonalPlantPopulation.................... 64 3.6 Discussion...................................... 71 4 Conclusions 77 A FRANz 79 A.1 Availability ..................................... 79 A.2 Input files...................................... 79 A.2.1 Maininputfile ............................... 79 A.2.2 Knownrelationships ............................ 80 A.2.3 Allele frequencies.............................. 81 A.2.4 Sampling locations............................. 82 A.3 Output files..................................... 83 A.4 Web 2.0 Interface.................................. 86 List of Figures 87 List of Tables 88 List Abbreviations 90 Bibliography 92 Curriculum Vitae I

Clonal haematopoiesis of indeterminate potential, or CHIP are a family of mutations present in the general population. CHIP-mutations are prevalent in the haematopoietic stem cells and in the more mature cell populations, T-lymphocytes, B-lymphocytes and myeloid cells (CD3+, CD19+ and CD33+ cells) in blood. By separating these cell populations using magnetic isolation, extracting DNA from the cell populations, and detecting the same mutation in all cell populations, one can prove the presence of CHIP-mutations in a hematopoietic stem cell. At least 50 ng good quality DNA is needed for the gene analysis to detect CHIP-mutations. The magnet separated cell population may be very small, so the DNA extraction method must be optimized to achieve enough DNA yield. The main purpose of the method development was to compare two storage methods before DNA-extractions, and then three different DNA-quantification methods after the DNA-extractions. After the best storage and quantification methods were identified, five samples of cryo-preserved viable cells were used to isolate cell populations using magnetic beads covered in specific antibodies and a magnetic field, and then quantified. Results of the study showed that the best way was to store the cells in ATL-buffer and Proteinase K. To quantify DNA, qPCR was the most accurate method, since the other methods showed incorrect results because of the low DNA concentrations. Magnet cell separation was partly successful. All except one of the DNA yields from the cell separation protocols reached the critical amount of DNA, but some yields were not pure yields of the sought-after cell population. In general, the method must be worked on more with further research.

High transduction rates of viral vectors in gene therapies (GT) and experimental hematopoiesis ensure a high frequency of gene delivery, although multiple integration events can occur in the same cell. Therefore, tracing of integration sites (IS) leads to mis-quantification of the true clonal spectrum and limits safety considerations in GT. Hence, we use correlations between repeated measurements of IS abundances to estimate their mutual similarity and identify clusters of co-occurring IS, for which we assume a clonal origin. We evaluate the performance, robustness and specificity of our methodology using clonal simulations. The reconstruction methods, implemented and provided as an R-package, are further applied to experimental clonal mixes and preclinical models of hematopoietic GT. Our results demonstrate that clonal reconstruction from IS data allows to overcome systematic biases in the clonal quantification as an essential prerequisite for the assessment of safety and long-term efficacy of GT involving integrative vectors.

High-throughput sequencing technologies are improving in quality, capacity, and costs, providing versatile applications in DNA and RNA research. For small genomes or fraction of larger genomes, DNA samples can be mixed and loaded together on the same sequencing track. This so-called multiplexing approach relies on a specific DNA tag, index, or barcode that is attached to the sequencing or amplification primer and hence accompanies every read. After sequencing, each sample read is identified on the basis of the respective barcode sequence. Alterations of DNA barcodes during synthesis, primer ligation, DNA amplification, or sequencing may lead to incorrect sample identification unless the error is revealed and corrected. This can be accomplished by implementing error correcting algorithms and codes. This barcoding strategy increases the total number of correctly identified samples, thus improving overall sequencing efficiency. Two popular sets of error-correcting codes are Hamming codes and codes based on the Levenshtein distance. Levenshtein-based codes operate only on words of known length. Since a DNA sequence with an embedded barcode is essentially one continuous long word, application of the classical Levenshtein algorithm is problematic. In this thesis we demonstrate the decreased error correction capability of Levenshtein-based codes in a DNA context and suggest an adaptation of Levenshtein-based codes that is proven of efficiently correcting nucleotide errors in DNA sequences. In our adaptation, we take any DNA context into account and impose more strict rules for the selection of barcode sets. In simulations we show the superior error correction capability of the new method compared to traditional Levenshtein and Hamming based codes in the presence of multiple errors. We present an adaptation of Levenshtein-based codes to DNA contexts capable of guaranteed correction of a pre-defined number of insertion, deletion, and substitution mutations. Our improved method is additionally capable of correcting on average more random mutations than traditional Levenshtein-based or Hamming codes. As part of this work we prepared software for the flexible generation of DNA codes based on our new approach. To adapt codes to specific experimental conditions, the user can customize sequence filtering, the number of correctable mutations and barcode length for highest performance. However, not every platform is susceptible to a large number of both indel and substitution errors. The Illumina “Sequencing by Synthesis” platform shows a very large number of substitution errors as well as a very specific shift of the read that results in inserted and deleted bases at the 5’-end and the 3’-end (which we call phaseshifts). We argue in this scenario that the application of Sequence-Levenshtein-based codes is not efficient because it aims for a category of errors that barely occurs on this platform, which reduces the code size needlessly. As a solution, we propose the “Phaseshift distance” that exclusively supports the correction of substitutions and phaseshifts. Additionally, we enable the correction of arbitrary combinations of substitution and phaseshift errors. Thus, we address the lopsided number of substitutions compared to phaseshifts on the Illumina platform. To compare codes based on the Phaseshift distance to Hamming Codes as well as codes based on the Sequence-Levenshtein distance, we simulated an experimental scenario based on the error pattern we identified on the Illumina platform. Furthermore, we generated a large number of different sets of DNA barcodes using the Phaseshift distance and compared codes of different lengths and error correction capabilities. We found that codes based on the Phaseshift distance can correct a number of errors comparable to codes based on the Sequence-Levenshtein distance while offering the number of DNA barcodes comparable to Hamming codes. Thus, codes based on the Phaseshift distance show a higher efficiency in the targeted scenario. In some cases (e.g., with PacBio SMRT in Continuous Long Read mode), the position of the barcode and DNA context is not well defined. Many reads start inside the genomic insert so that adjacent primers might be missed. The matter is further complicated by coincidental similarities between barcode sequences and reference DNA. Therefore, a robust strategy is required in order to detect barcoded reads and avoid a large number of false positives or negatives. For mass inference problems such as this one, false discovery rate (FDR) methods are powerful and balanced solutions. Since existing FDR methods cannot be applied to this particular problem, we present an adapted FDR method that is suitable for the detection of barcoded reads as well as suggest possible improvements.

L’objectif de cette thèse est de déterminer l’étendue de la variabilité épigénétique, plus particulièrement du polymorphisme de méthylation de l’ADN, non liée à la variabilité génétique dans les populations asexuées en milieu naturel. Cette évaluation nous a permis de mieux cerner l’importance que peuvent avoir les processus épigénétiques en écologie et en évolution. Le modèle biologique utilisé est l’hybride clonal du complexe gynogénétique Chrosomus eos-neogaeus. Malgré une homogénéité génétique, une importante variabilité phénotypique est observée entre les hybrides d’une même lignée clonale mais retrouvés dans des environnements différents. L’influence des processus épigénétiques apporte une explication sur ce paradoxe. L’épigénétique se définit comme une modification de l’expression des gènes sans changement de la séquence d’ADN. La diversité des phénotypes peut entre autre s’expliquer par des patrons de méthylation différentiels des gènes et/ou des allèles des gènes entre les hybrides génétiquement identiques. La diversité des lignées épiclonales peut quant à elle s’expliquer par la colonisation de plusieurs lignées épiclonales, s’établir en réponse à l’environnement ou de façon aléatoire. Plusieurs méthodes seront utilisées afin de survoler le génome des hybrides clonaux pour mettre en évidence le polymorphisme de méthylation de l’ADN à l’échelle de l’individu et entre les individus de différentes populations. / The aim of the thesis is to determine the extent of epigenetic variation, more specifically DNA methylation polymorphism, not linked to genetic variation in natural populations of an asexual vertebrate. This evaluation enables to better understand the importance that plays epigenetics processes in ecology and evolution. The biological model used is the clonal hybrid of the gynogenetic Chrosomus eos-neogaeus complex. Even in absence of genetic difference, an important phenotypic variability is observed among hybrids of the same clonal lineage living in different environments. Epigenetics, a modification of genes expression without a change at the DNA sequence, provides an explanation to this paradox. The diversity of phenotypes may be explained by differential methylation patterns of genes and/or alleles among genetically identical hybrids. The diversity of epiclonal lineages may be explained by the colonisation of many epiclonal lineages, established in response to the environment or stochastically. Many methods were used for screening the genome of clonal hybrids in order to highlight DNA methylation polymophism at the scale of an individual and among individuals of different populations.