A fisiopatologia das síndromes de falência da medula óssea (FMO) está relacionada a mecanismos adquiridos de destruição das células-tronco hematopoeiticas na medula ou a defeitos constitucionais em genes fundamentais para o reparo do DNA e manutenção dos telômeros. A anemia aplástica (AA), o protótipo das doenças de FMO, pode ter etiologia adquirida ou constitucional. A avaliação genética de pacientes com AA adquirida tem como objetivo a detecção de mutações somáticas que possam ser usadas como marcadores de resposta ao tratamento imunossupressor. Diferentemente, em pacientes com AA constitucional, a avaliação genética é fundamental para detecção de mutações etiológicas na doença do paciente, sendo essencial para o tratamento e seleção de doadores de medula óssea. Contudo, o papel das mutações constitucionais na fisiopatologia e modulação imunológica da AA adquirida ainda não é conhecido. Neste estudo, nós sequenciamos pacientes com AA de duas coortes independentes utilizando diferentes painéis de sequenciamento de genes alvos. A primeira coorte, composta por 13 pacientes com AA adquirida, foi sequenciada utilizando um painel com 165 genes relacionados à FMO, neoplasias hematológicas, reparo de DNA, manutenção dos telômeros e vias de resposta imune. A segunda coorte, composta por 59 pacientes investigados para doença constitucional, foi sequenciada com um painel de sequenciamento comercial com 49 genes relacionados à FMO hereditária. Foram identificadas alterações potencialmente patogênicas em três dos cinco pacientes com AA adquirida que não responderam à imunossupressão: dois pacientes com variantes em TERT e um com uma variante em DHX36. Não foram identificadas variantes funcionalmente relevantes nos pacientes que responderam ao tratamento imunossupressor. Em contraste, foram identificadas variantes potencialmente patogênicas em RTEL1 em 8 pacientes com AA constitucional. Variantes em RTEL1 foram associadas tanto ao encurtamento telomérico quanto à erosão excessiva do 3\' overhang, independentemente do comprimento dos telômeros. Desse modo, apenas a medida do comprimento dos telômeros não foi suficiente para identificar todos ospacientes com disfunções teloméricas. As plataformas de sequenciamento de nova geração diminuíram o custo e o tempo para a avaliação genética dos pacientes com FMO. Em nosso estudo, os pacientes com AA adquirida não apresentaram um padrão genético associado à sua resposta ao tratamento com imunossupressores, no entanto, o sequenciamento da coorte com suspeita de AA constitucional foi capaz de identificar o defeito genético associado à doença do paciente em 40% dos casos. O uso de dados clínicos, investigação familiar, análises in silico e testes funcionais foram essenciais para uma correta interpretação da patogenicidade de novas variantes identificadas por sequenciamento de nova geração. / The pathophysiology of bone marrow failure (BMF) can be immune, as in acquired aplastic anemia (AA), or constitutional, due to germline mutations in genes critical for DNA repair and telomere maintenance. The genetic screening of patients with constitutional AA is performed to detect germline mutations that are etiologic in patients\' disease. That is critical for treatment decisions and to identify a donor for a bone marrow transplant. In acquired AA, the genetic screening has been used to detect somatic mutations that can predict patients\' outcomes after treatment, as the role of germline mutations in this disease is yet not clear. To investigate the role of germline variants in AA, we screened two independent cohorts with two different targeting sequencing panels; a first cohort composed by 13 patients with acquired AA that was screened using a panel with 165 genes related to BMF, hematologic malignancies, DNA repair, telomere maintenance, and immune response pathways. A second cohort composed of 59 patients suspected to have a constitutional disease screened by a commercial Inherited Bone Marrow Failure Sequencing panel. In our first cohort, while patients without functional relevant germline variants responded to immunosuppression treatment (n=8), three out of 5 nonresponder patients were identified with variants in telomere biology genes. We found patients carrying TERT and DHX36 variants. In our constitutional AA cohort, we identified 8 patients carrying variants in the RTEL1 gene, a helicase critical to telomere maintenance. RTEL1 variants associated with both patients\' overall telomere shortening and single-stranded 3\' overhang erosion independent of telomere length. Also, 3\' overhang erosion was associated with patients\' predisposition to clonal evolution. In this context, the variants identified in the helicases genes DHX36 and RTEL1 were both associated with patients\' normal telomere length and poor outcomes. Also, telomere length measurement alone was insufficient to identify all primary telomere defects. The platforms of next-generation sequencing decreased the cost and time for the genetic screening of patients with BMF. In our study, acquired AA patients did not display a clear genetic pattern associated with their immunosuppressive treatment response. In contrast, the sequencing of the cohort selected based on their suspicion to have an inherited diseaseidentified a molecular defect that might be pathogenic in up to 40% of patients, including the RTEL1 variants. Pathogenicity assessment of genetic variants requires a combination of clinical, in silico, and functional data required to avoid misinterpretation of common variants.

Thesis advisor: Gabor T. Marth / During the last few years, numerous new sequencing technologies have emerged that require tools that can process large amounts of read data quickly and accurately. Regardless of the downstream methods used, reference-guided aligners are at the heart of all next-generation analysis studies. I have developed a general reference-guided aligner, MOSAIK, to support all current sequencing technologies (Roche 454, Illumina, Applied Biosystems SOLiD, Helicos, and Sanger capillary). The calibrated alignment qualities calculated by MOSAIK allow the user to fine-tune the alignment accuracy for a given study. MOSAIK is a highly configurable and easy-to-use suite of alignment tools that is used in hundreds of labs worldwide. MOSAIK is an integral part of our genetic variant discovery pipeline. From SNP and short-INDEL discovery to structural variation discovery, alignment accuracy is an essential requirement and enables our downstream analyses to provide accurate calls. In this thesis, I present three major studies that were formative during the development of MOSAIK and our analysis pipeline. In addition, I present a novel algorithm that identifies mobile element insertions (non-LTR retrotransposons) in the human genome using split-read alignments in MOSAIK. This algorithm has a low false discovery rate (4.4 %) and enabled our group to be the first to determine the number of mobile elements that differentially occur between any two individuals. / Thesis (PhD) — Boston College, 2010. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

Dezoito galinhas de uma população experimental utilizada em um cruzamento recíproco entre as linhagens de frangos de corte (TT) e de postura (CC) foram sequenciadas pela tecnologia de nova geração na plataforma Illumina com uma cobertura média de 10X. A descoberta de variantes genéticas foi realizada em uma região de locos de característica quantitativa (Quantitative Trait Locus, QTL), associado anteriormente com peso e percentagem de gordura abdominal no cromossomo 3 da galinha (GGA3), entre os marcadores microssatélites LEI0161 e ADL0371 (33,595,706-42,632,651 pb). O programa SAMtools foi utilizado na identificação de 136.054 SNPs únicos e 15.496 INDELs únicas nos 18 animais sequenciados e após a filtragem das mutações, 92.518 SNPs únicos e 9.298 INDELs únicas foram mantidas. Uma lista de 77 genes foi analisada buscando genes relacionados ao metabolismo de lipídios. Variantes localizadas na região codificante (386 SNPs e 15 INDELs) foram identificadas e associadas com vias metabólicas importantes. Variantes nos genes LOC771163, EGLN1, GNPAT, FAM120B, THBS2 e GGPS1 foram identificadas e podem ser responsáveis pela associação do QTL com a deposição de gordura na carcaça em galinhas. / Eighteen chickens from a parental generation used in a reciprocal cross with broiler and layer lines were sequenced by new generation technology with an average of 10-fold coverage. The DNA sequencing was performed by Illumina next generation platform. The genetic variants discovery was performed in a quantitative trait loci (QTL) region which was previously associated with abdominal fat weight and percentage in chicken chromosome 3 (GGA3) between the microsatellite markers LEI0161 and ADL0371 (33,595,706-42,632,651 bp). SAMtools software was used to detect 136,054 unique SNPs and 15,496 unique INDELs for the 18 chickens, and after quality filtration 92,518 unique SNPs and 9,298 unique INDELs were retained. One list of 77 genes was analised and genes related to lipid metabolism were searched. Variants located in coding region (386 SNPs and 15 INDELs) were identified and associated with important metabolic pathways. Loss of functional variants in the genes LOC771163, EGLN1, GNPAT, FAM120B, THBS2 and GGPS1 may be responsible for the QTL associated with fat deposition in chicken.

A produção brasileira de carne de frango tem uma grande importância econômica no mundo todo devido principalmente aos avanços do melhoramento genético. O surgimento de novas tecnologias de sequenciamento (sequenciamento de nova geração) tem se tornado uma ferramenta poderosa, pois por meio da identificação de SNPs (polimorfismo de nucleotídeo único) e INDELs (deleções/inserções) possibilita a adição de novas informações ao melhoramento genético. A deposição de músculo, em especial o músculo de peito, é uma das características que mais merecem destaque por causa da sua importância nutricional e econômica. Sendo assim o objetivo deste trabalho foi ressequenciar o genoma de 18 aves de duas linhagens distintas experimentais e identificar SNPs e INDELs em uma região de QTL no cromossomo 2 da galinha associado anteriormente com deposição de músculo do peito, além de caracterizar variantes potencialemente funcionais e propor mutações candidatas para estudos futuros. Para isso, dezoito galinhas de duas diferentes linhagens experimentais (corte e postura), ambas desenvolvidas pela Embrapa Suíno e Aves, foram sequenciadas pela plataforma de nova geração da Illumina. SNPs e INDELs foram identificados por meio de ferramentas de bioinformática em uma região de QTL no cromossomo 2 da galinha (105.848.755-112.648.761 pb) que foi previamente associada com deposição de músculo de peito. O sequenciamento dos 18 animais gerou em torno 2,7 bilhões de reads e após a filtragem por qualidade foram mantidas 77% das reads. Em seguida, as reads foram alinhadas ao genoma referência (Gallus_gallus-4.0, NCBI) pela ferramenta Bowtie2 e gerou em média 10,6X de cobertura de sequenciamento na região-alvo. , Foram identificados 722.832 SNPs e 63.727 INDELs para os 18 animais por meio do programa SAMtools, e após uma filtragem rigorosa, foram mantidos 77% dos SNPs (n=558.767) e 60% das INDELs (n=38.402). Com base nas variantes únicas para os 18 animais (85.765 SNPs e 7.824 INDELs) foi realizada a anotação funcional por meio da ferramenta ANNOVAR. Dentre os SNPs não sinônimos (n=153) e stopgain (n=3), 15 foram classificados como deletérios. Um dos SNPs deletérios que já foi depositado em banco de dados foi identificado no gene RB1CC1, que tem sua função relacionada ao desenvolvimento do músculo de peito. Utilizando a ferramenta DAVID foi possível analisar 37 genes relacionados aos SNPs não sinônimos, stopgain, INDELs frameshift e não frameshift. Dentre estes genes, três (DTNA, RB1CC1 e C-MOS) foram selecionados por terem suas funções relacionadas ao desenvolvimento muscular e suas mutações foram analisadas. Sendo assim, futuros estudos podem ser realizados nestes genes candidatos e nas mutações identificadas, por meio de análises de associação e validação em populações comerciais, permitindo assim uma melhor explicação o efeito do QTL estudado. / The Brazilian chicken meat production has a great economic importance in worldwide mainly due to advances in breeding. The emergence of new techniques of sequencing (nextgeneration sequencing) becomes a powerful tool because through identification of SNPs (single nucleotide polymorphism) and INDELs (deletions/insertions) allows the addition of new information for genetic improvement. The muscle deposition, particularly the breast muscle, is one of the features that are most noteworthy because of its nutritional and economic importance. Therefore the aim of this study was to perform the genome resequencing of 18 chicken from two distinct experimental lines and identify SNPs and INDELs in a QTL region on chromosome 2 previously associated with breast muscle, and characterize the variants to identify potentially function ones and propose candidate mutations for future studies. To achieve these objectives, eighteen chickens of two different experimental lines (broiler and layer), both developed by Embrapa Swine and Poultry were sequenced by Illumina next-generation platform. SNPs and INDELs were identified by bioinformatic tools in a QTL region on chicken chromosome 2 (105,848,755-112,648,761 bp) which was previously associated with breast muscle deposition. Sequencing of the eighteen animals generated around 2.7 billion of reads, and 77% of the reads were retained after filtering. The reads were aligned against the chicken genome reference (Gallus_gallus-4.0, NCBI) by Bowtie2 tool resulting in a 10.6X coverage across the target region. Using SAMtools, 722,832 SNPs and 63,727 INDELs were identified in the all individuals, and after a stringent filtration, 77% of SNPs (n=558,767) and 60% of INDELs (n=38,402) were maintained. Based on unique variants for all the animal (85,765 SNPs and 7,828 INDELs) were performed the functional annotation by ANNOVAR tool. Among the non-synonymous SNPs (n=153) and stopgain (n=3), fifteen were predicted like a deleterious mutation. One of deleterious SNPs has already deposited in public database, and it was identified in RB1CC1 gene, which function is related to breast muscle development. Using the DAVID tool was possible to analyze the 37 genes related to the non-synonymous SNPs, stopgain, frameshift and non-frameshift INDELs. Among these genes, three (DTNA, RB1CC1 and C-MOS) were selected due their functions related to muscle development and their mutations were analyzed. Therefore, further association studies can be performed with these candidate genes and their mutations, and also validation in commercial populations, allowing a better explanation of QTL effects.

Bakgrund: Donationsprocessen är en del av intensivvården som ställer stora krav på de närstående, som förutom att ha drabbats av plötslig förlust, också har ett beslut om donation att ta ställning till. Intensivvårdssjuksköterskor har en stor roll i denna process men upplever ofta det svårt att veta hur de ska bemöta de närstående på ett bra sätt. Syfte: Att identifiera och sammanställa hur närstående till potentiella organdonatorer upplever transitionerna de genomgår under donationsprocessen. Metod: Studien utfördes som en litteraturöversikt med kvalitativ design. En deskriptiv innehållsanalys utfördes av 17 stycken studier som baserats på intervjuer med närstående kring deras upplevelser av donationsprocessen. Resultat: De närståendes transitioner sammanfattades i tre huvudkategorier: från liv till död, insikt och acceptans och från död till liv. Beskrivningarna av deras upplevelser kretsade i huvudsak kring bemötande från vården, samtyckesprocessen och förståelse för situationen. De flesta upplevde ett gott empatiskt bemötande men många hade svåt att ta till sig och förstå information kring framför allt hjändödsbegreppet. Att ta ett beslut om samtycke till donation upplevdes för vissa som en tröst då det gav förlusten en mening, medan andra upplevde det som ett omöjligt och fruktansvärt beslut att ta. Slutsats: Viktiga områden för näståendes upplevelser under donationsprocessen var bemötandet, det emotionella stödet, informationen och beslutsfattandet. Kunskapen om närståendes upplevelser är relevant för intensivvården och intensivvårdssjuksköterskan för att vården skall kunna ge den omvårdnad som behövs under processen. / Background: The process of organ- and tissue donation is a part of the critical care that puts a lot of pressure on the next of kin who as well as being victims of a sudden loss, need to make a decision about donation. Intensive care nurses play a major role within this process and often experience it difficult to know how to respond to the next of kin in a good way. Aim: To identify and compile how next of kin to potential organ donors experience the transitions they go through during the donation process. Method: This study has been conducted as a review of previous literature and with a qualitative design. A descriptive content analysis was performed of 17 studies which were based on interviews with next of kin and their experiences with the donation process. Results: The next of kin transitions were compiled into three main categories: from life to death, insight and acceptance and from death to life. The description of their experiences through these transitions mainly focused on reception from hospital staff, the decision-making process and their perception of the situation. The reception in the majority of the cases was considered good and empathetic. A number of them had a difficult time understanding the information given to them, in particular about the meaning of brain death. Some of the next of kin did experience making the decision about donation as a comfort that gave them a deeper meaning to their loss, while others experienced it as an impossible and dreadful decision to make. Conclusion: Important aspects recognized by the next of kin during the donation process were; the personal treatment, the emotional support, the received information and the decision-making. The knowledge surrounding experiences of the next of kin, is relevant to the intensive care and the intensive care nurse, to reassure that they provide the care needed during the process.

Ce travail est focalisé sur le problème de la construction autonome du modèle 3D d'un objet inconnu en utilisant un robot humanoïde. Plus particulièrement, nous considérons un HRP-2 guidé par la vision au sein d'un environnement connu qui peut contenir des obstacles. Notre méthode considère les informations visuelles disponibles, les contraintes sur le corps du robot ainsi que le modèle de l'environnement dans le but de générer des postures adéquates et les mouvements nécessaires autour de l'objet. Le problème de sélection de vue ("Next-Best-View") est abordé en se basant sur un générateur de postures qui calcule une configuration par la résolution d'un problème d'optimisation. Une première solution est une approche locale où un algorithme de rendu original à été conçu afin d'être inclut directement dans le générateur de postures. Une deuxième solution augmente la robustesse aux minimums locaux en décomposant le problème en 2 étapes: (i) trouver la pose du capteur tout en satisfaisant un ensemble de contraintes réduit, et (ii) calculer la configuration complète du robot avec le générateur de posture. La première étape repose sur des méthodes d'optimisation globale et locale (BOBYQA) afin de converger vers des points de vue pertinents dans des espaces de configuration admissibles non convexes. Notre approche est testée en conditions réelles par le biais d'une architecture cohérente qui inclus différents composants logiciels spécifique à l'usage d'un humanoïde. Ces expériences intègrent des travaux de recherche en cours en planification de mouvements, contrôle de mouvements et traitement d'image, qui pourront permettre de construire de façon autonome le modèle 3D d'un objet. / This work addresses the problem of autonomously constructing the 3D model of an unknown object using a humanoid robot.More specifically, we consider a HRP-2 evolving in a known environment, which is possibly cluttered, guided by vision.Our method considers the visual information available, the constraints on the robot body, and the model of the environment in order to generate pertinent postures and the necessary motions around the object.Our two solutions to the Next-Best-View problem are based on a specific posture generator, where a posture is computed by solving an optimization problem.The first solution is a local approach to the problem where an original rendering algorithm is specifically designed in order to be directly included in the posture generator. The rendering algorithm can display complex 3D shapes while taking into account self-occlusions.The second solution seeks more global solutions by decoupling the problem in two steps: (i) find the best sensor pose while satisfying a reduced set of constraints on the humanoid, and (ii) generate a whole-body posture with the posture generator.The first step relies on global sampling and BOBYQA, a derivative-free optimization method, to converge toward pertinent viewpoints in non-convex feasible configuration spaces.Our approach is tested in real conditions by using a coherent architecture that includes various complex software components that consider the specificities of the humanoid robot. This experiment integrates on-going works addressing the tasks of motion planning, motion control, and visual processing, to allow the completion of the 3D object reconstruction in future works.

For over two decades, the study of genetics has been making significant progress towards understanding the causes of common disease. Across a wide range of complex disorders there have been hundreds of associated loci identified, largely driven by common genetic variation. Now, with the advent of next-generation sequencing technology, we are able to interrogate rare and low frequency variation in a high throughput manner for the first time. This provides an exciting opportunity to investigate the role of rarer variation in complex disease risk on a genome-wide scale, potentially o↵ering novel insights into the biological mechanisms underlying disease pathogenesis. In this thesis I will assess the potential of this technology to further our understanding of the genetics of complex disease, using inflammatory bowel disease (IBD) as an example. After first reviewing the history of genetic studies into IBD, I will describe the analytical challenges that can occur when using sequencing to perform case-control association testing at scale, and the methods that can be used to overcome these. I then test for novel IBD associations in a low coverage whole genome sequencing dataset, and uncover a significant burden of rare, damaging missense variation in the gene NOD2, as well as a more general burden of such variation amongst known inflammatory bowel disease risk genes. Through imputation into both new and existing genotyped cohorts, I also describe the discovery of 26 novel IBD-associated loci, including a low frequency missense variant in ADCY7 that approximately doubles the risk of ulcerative colitis. I resolve biological associations underlying several of these novel associations, including a number of signals associated with monocyte-specific changes in integrin gene expression following immune stimulation. These results reveal important insights into the genetic architecture of inflammatory bowel disease, and suggest that a combination of continued array-based genome- wide association studies, imputed using substantial new reference panels, and large scale deep sequencing projects will be required in order to fully understand the genetic basis of complex diseases like IBD.

"Recently, sequencing technologies have generated massive and heterogeneous data sets. However, interpretation of these data sets is a major barrier to understand genomic heterogeneity in complex diseases. In this dissertation, we develop a Bayesian statistical method for single nucleotide level analysis and a global optimization method for gene expression level analysis to characterize genomic heterogeneity in mixed samples. The detection of rare single nucleotide variants (SNVs) is important for understanding genetic heterogeneity using next-generation sequencing (NGS) data. Various computational algorithms have been proposed to detect variants at the single nucleotide level in mixed samples. Yet, the noise inherent in the biological processes involved in NGS technology necessitates the development of statistically accurate methods to identify true rare variants. At the single nucleotide level, we propose a Bayesian probabilistic model and a variational expectation maximization (EM) algorithm to estimate non-reference allele frequency (NRAF) and identify SNVs in heterogeneous cell populations. We demonstrate that our variational EM algorithm has comparable sensitivity and specificity compared with a Markov Chain Monte Carlo (MCMC) sampling inference algorithm, and is more computationally efficient on tests of relatively low coverage (27x and 298x) data. Furthermore, we show that our model with a variational EM inference algorithm has higher specificity than many state-of-the-art algorithms. In an analysis of a directed evolution longitudinal yeast data set, we are able to identify a time-series trend in non-reference allele frequency and detect novel variants that have not yet been reported. Our model also detects the emergence of a beneficial variant earlier than was previously shown, and a pair of concomitant variants. Characterization of heterogeneity in gene expression data is a critical challenge for personalized treatment and drug resistance due to intra-tumor heterogeneity. Mixed membership factorization has become popular for analyzing data sets that have within-sample heterogeneity. In recent years, several algorithms have been developed for mixed membership matrix factorization, but they only guarantee estimates from a local optimum. At the gene expression level, we derive a global optimization (GOP) algorithm that provides a guaranteed epsilon-global optimum for a sparse mixed membership matrix factorization problem for molecular subtype classification. We test the algorithm on simulated data and find the algorithm always bounds the global optimum across random initializations and explores multiple modes efficiently. The GOP algorithm is well-suited for parallel computations in the key optimization steps. "

Next-Generation Sequencing has opened the doors to nearly limitless amounts of genomic data, but the clinical utility of this data is not yet clear. From examining at sequencing data of known familial cancer genes in hereditary cancer patients, the NCGENES study found a clear molecular diagnosis in about 5% of patients and an uncertain molecular result in about 15% of patients. The remaining 80% of hereditary cancer patients received a negative result for the screening of known cancer genes. These latter patients were followed up by whole exome sequencing analysis, and the data was used to perform a research sweep to potentially identify mutation(s) in gene(s) that have yet to be clearly associated with their phenotype. Hereditary breast cancer has a relatively well-established set of susceptibility genes, yet a large percentage of the molecular etiology is still unknown. There are many genes that are good candidates for breast cancer genes based on their protein's function, but they may not actually contribute to breast cancer susceptibility. The ClinGen consortium is aiming to establish the clinical validity of gene-disease associations so that clinicians and patients can better interpret and utilize sequencing results. Six breast cancer susceptibility genes were evaluated using the ClinGen clinical validity framework with the goal of both evaluating the genes already on hereditary breast cancer panels and evaluating genes not yet widely tested to determine if there is enough evidence to support their role in disease to warrant widespread testing. These genes have varying levels of evidence supporting their role in breast cancer susceptibility. The variants in each of the six genes were compared between a cancer patient cohort and a non-cancer patient cohort enrolled in the NCGENES whole exome sequencing study. One likely pathogenic variant and several variants of unknown significance were identified in various genes, and the burden of variants in cancer cases versus controls was evaluated, although the controls were not matched to the cancer cohort in any way. Research sweeps were performed for patients with VUSs to ensure that there were no other mutations in genes that would better fit the phenotype. This thesis presents a method for evaluating gene-disease associations and for utilizing whole exome sequencing data to pinpoint a molecular diagnosis in hereditary breast cancer patients. Overall, it was found that the ClinGen method of evaluating clinical validity of gene-disease associations could be helpful when determining if variants are pathogenic or benign. A new gene, RINT1, was found to have enough evidence to be moderately associated with hereditary breast cancer and it was subsequently added to the diagnostic list so that all cancer patients will now be screened for RINT1 variants. In addition, it was found that two of the genes currently on the diagnostic list, RAD51C and RAD51D, have "disputed" evidence with respect to breast cancer susceptibility. Interestingly, they have much more evidence for an association with ovarian cancer, so if variants are found in these genes, the patient's phenotype should be considered when evaluating them. It was also shown that PALB2, an established breast cancer susceptibility gene, indeed is definitively associated with breast cancer, and the NCGENES cancer patients have more truncating variants than the controls, further validating the clinical validity assertion. Finally, an ovarian cancer patient with two interesting variants, one in SLX4 and one in GEN1, were evaluated. Studies showed that knocking out both of these genes' pathways was highly destructive to the cell. A VUS was found in each of these genes, and it was hypothesized that perhaps these two variants together may be sufficient to contribute to this patient's cancer susceptibility.

The repeated emergence of drug resistance in Plasmodium falciparum underscores the importance of understanding the genetic architecture of current resistance pathways, as well as any associated fitness costs. Why resistance emerges in particular regions of the world has been linked to particular genetic backgrounds that better tolerate resistance-associated polymorphisms; this is likely to play a key role in driving the epidemiology of drug resistance, however is infrequently studied at a large scale in a laboratory setting. The first results chapter establishes a barcoding approach for P. falciparum with the aim of tracking parasite growth in vitro. The strategy used was adapted for P. falciparum by using a pseudogene (PfRh3) as a safe harbour to insert unique molecular barcodes. These libraries of barcoded P. falciparum vectors were also used as a readout of transfection efficiency. The second chapter establishes a proof of principle for phenotyping by barcode sequencing, using a panel of barcoded parasites generated in different genetic backgrounds that comprise sufficient genetic diversity to pilot the method. These were grown in the presence and absence of antimalarial compounds, and growth phenotypes were measured in parallel using BarSeq. The third results chapter studies the contribution of mutations in Pfkelch13, a molecular marker of artemisinin resistance, to parasite fitness. Combining CRISPR/Cas9-based genome editing and high throughput sequencing, the impact of Pfkelch13 alleles on fitness in the context of particular strain backgrounds is revealed. In particular, the impact of genetic background in the emergence and spread of drug-resistant lineages (referred to as KEL1) in Southeast Asia carrying a Y580 Pfkelch13 allele. Overall, given the current pace of genome sequencing of pathogenic organisms such as P. falciparum, it will be important to increase the scale of experimental genetics, in order to tackle in real-time natural variation that might be under constant selection from drugs, thus anticipating the emergence of drug resistance in changing parasite populations. Through this work, tools were developed to facilitate parallel phenotyping by measuring in vitro growth using high-throughput sequencing. The work also develops novel approaches to address the importance of genetic background and a potential role for positive epistasis in a lineage responsible for the recent outbreak of drug-resistant malaria in Southeast Asia.