Algae are a group of highly diverse photosynthetic organisms found in variety of habitats. As the primary energy base in ecosystems, knowledge of the diversity and presence of certain algal lineages is paramount to our understanding of the trophic state of aquatic habitats. In recent years, the state of Florida has seen an increase of both marine and freshwater algal blooms. Similarly, filamentous algae have begun outcompeting vascular macrophytes throughout many of Florida’s springs as nutrient enrichment from anthropogenic sources increases. Traditionally, the Florida algal spring communities have been assessed using classic morphological methods, which may underrepresent the true biodiversity present. Therefore, the goal of this study was to conduct a more complete diversity assessment implementing next-generation sequencing techniques (NGS) with morphological analyses and culturing methods. While morphological methods identified a wide variety of algal taxa, belonging to 4 phyla (Bacillariophyta, Charophyta, Chlorophyta, and Cyanobacteria), next-generation sequencing techniques provided greater detail of the diatom community. This is particularly important as many diatom taxa are used as indicators of water quality. We noted discrepancies between these two methods, highlighting how NGS techniques may complement the use of morphological analyses when analyzing algal diversity in this system. Culturing methods also revealed the presence of two taxa new to science (Nodosilinea fontisand Brasilonema variegatus), indicating these springs may represent a potential source of novel cyanobacteria. Taken together, this study showcases Florida springs are rich in algal diversity and a combination of methods is required for more complete biodiversity assessments. Future studies implementing such methods will aid in the preservation and conservation of these ecosystems.

With the recent adoption of the Next Generation Science Standards in Oregon, there is a great need for teachers to be trained to effectively implement the three dimensions of the Next Generation Science Standards (NGSS) in their teaching. Time and location are the largest constraining factors that affect teacher participation in professional development trainings. To address this constraint, Tryon Creek State Park offered a NGSS professional development training opportunity for teachers that was integrated within a field trip that they took their students on. Before the field trip, teachers were introduced to the NGSS through a set of NGSS pre-field trip materials which informed them about the NGSS and how aspects of it would be integrated into their students' field trip. Teachers accompanied their students on a two-hour long field trip at Tryon Creek State Park where teachers observed nature guides model NGSS-aligned activities for the students. My research aimed to answer the following question: How will an informal science education program at Tryon Creek State Park affect K-2 teachers' awareness of the Next Generation Science Standards? Outcomes were measured through a pre/post retrospective survey and follow-up interviews. On the survey teachers reported little awareness of the three dimensions of the NGSS and very few of the teachers increased their understanding after the treatment. On the other hand, most had a high level of awareness and confidence in teaching factual information supporting the NGSS prior to treatment, resulting in a ceiling effect. Interviews suggested that few teachers read the materials sent in advance of the field trip, but teachers who did read the materials indicated increases in understanding of the NGSS. During the field trip several of the nature guides were effective in modeling science and engineering practices. These findings suggest that this method of professional development is promising, but needs further refinement.

This study examined the impact of an inquiry based Next Generation Science Standard aligned science unit on elementary students' understanding and application of the eight Science and Engineering Practices and their relation in building student problem solving skills. The study involved 44 second grade students and three participating classroom teachers. The treatment consisted of a school district developed Second Grade Earth Science unit: What is happening to our playground? that was taught at the beginning of the school year. Quantitative results from a Likert type scale pre and post survey and from student content knowledge assessments showed growth in student belief of their own abilities in the science classroom. Qualitative data gathered from student observations and interviews performed at the conclusion of the Earth Science unit further show gains in student understanding and attitudes. This study adds to the existing literature on the importance of standard aligned, inquiry based science curriculum that provides time for students to engage in science practices.

La leucémie myéloïde chronique (LMC) est un syndrome myéloprolifératif rare traité par des inhibiteurs de tyrosine kinase, tel que l’imatinib. Malgré son efficacité, la résistance au traitement est un problème récurrent. Des variants génétiques responsables d’une altération de la mort cellulaire programmée (apoptose) pourraient notamment expliquer l’hétérogénéité de la réponse au traitement entre les patients. Dans un premier temps, l’objectif était de rechercher des variants candidats. Pour cela un panel de 45 gènes impliqués dans l’apoptose a été étudié par séquençage nouvelle génération chez 24 patients atteints de LMC, 12 répondeurs et 12 résistants au traitement par imatinib. A l’aide d’outils informatiques, 473 polymorphismes ont été détectés. Le nombre de patients étudiés étant limité, de nouvelles méthodes statistiques ont dû être développées pour analyser les résultats obtenus. Tout d’abord, les fréquences de survenue des variants chez les patients résistants et répondeurs ont été comparées aux fréquences observées dans la population générale et visualisées par une approche de statistiques descriptives. Cette stratégie a permis de réduire la liste à 95 polymorphismes pouvant être impliqués dans la résistance au traitement. Par la suite, les gènes ont été classés selon leur enrichissement en allèles variants. Au final, trois gènes candidats ont été choisis et séquencés chez 103 patients. Cette méthodologie, automatisée grâce à un algorithme informatique, a permis de mettre en évidence, un variant non synonyme dans le gène BCL RAMBO, retrouvé plus fréquemment chez les patients résistants de manière significative. Dans un second temps, l’objectif était de caractériser le rôle de ce variant dans la réponse à l’imatinib à l’aide de lignées cellulaires modifiées par la technologie CRISPR-Cas9. Des cellules n’exprimant plus la protéine ont été obtenues et ont permis de mettre en évidence le rôle majeur de la protéine BCL RAMBO dans l’inhibition de l’apoptose. Des lignées cellulaires portant le variant candidat ont également été créées à l’aide d’une nouvelle technique utilisant CRISPR-Cas9 : l’exon entier contenant le nucléotide d’intérêt a été remplacé par un exon modifié. La modification d’un acide aminé induite par le variant a été associé à une perte de la sensibilité au traitement par imatinib dans ces lignées, comme suggéré après séquençage des patients. Ces données indiquent que BCL-RAMBO, facteur anti-apoptotique dans une lignée modèle de LMC, pourrait devenir une nouvelle cible thérapeutique afin de surmonter la résistance à l’imatinib / Chronic myeloid leukemia (CML) is a rare myeloproliferative syndrome treated by tyrosine kinase inhibitors, such as imatinib. Despite its efficacy, resistance to treatment is a persistent clinical issue. Notably, genetic variants causing alterations in apoptosis may explain heterogeneity of imatinib sensitivity between patients. First, the goal was to look for candidate variants. For that purpose, a panel of 45 apoptotic genes was assessed by next-generation sequencing on 24 CML patients, 12 sensitive and 12 resistant to imatinib treatment. Using informatics tools, 473 polymorphisms were detected. As the number of sequenced samples was limited, novel statistical methods had to be developed to interpret the results. The variant frequency in resistant and sensitive patients was compared to variant frequency in the general population and visualized using descriptive statistics. This strategy allowed to obtain a restricted list of 95 polymorphisms that might be involved in resistance to the treatment. Then, genes were ranked according to variant allele enrichment. At the end, three candidate genes were chosen and sequenced for 103 CML patients. This methodology, automated using a computer algorithm, permitted to highlight a nonsynonymous variant in the BCL RAMBO gene, significantly found more often in resistant patients. Second, the objective was to characterize the role of this variant in response to imatinib using model cell lines modified by CRISPR-Cas9 technology. BCL-RAMBO knock-out cells were obtained and allowed to demonstrate the major role of BCL-RAMBO protein in apoptosis inhibition. Additionally, cell lines carrying the variant were created using a new CRISPR-Cas9 mediated technique: the whole exon carrying the nucleotide of interest was replaced with a variant exon. The amino acid change induced by the identified polymorphism was associated with a loss of sensitivity to imatinib treatment in these cell lines as suggested after patient sequencing. These data indicate that BCL-RAMBO, anti apoptotic factor in a CML cell line, could become a novel therapeutic target to overcome drug inefficacy for a subset of resistant patients.

La caractérisation exaustive des variations de l'ADN peut aider à progresser dans de nombreux champs liés à la génomique du cancer. Le séquençage nouvelle génération (NGS en anglais pour Next Generation Sequencing) est actuellement la technique la plus efficace pour déterminer une séquence ADN, du aux faibles coûts et durées des expériences comparé à la méthode de séquençage traditionnelle de Sanger. Cependant, la détection de mutations à partir de données NGS reste encore un problème difficile, en particulier pour les mutations somatiques présentes en très faible abondance comme lorsque l'on essaye d'identifier des mutations sous-clonales d'une tumeur, des mutations dérivées de la tumeur dans l'ADN circulant libre, ou des mutations somatiques dans des tissus normaux. La difficulté principale est de précisement distinguer les vraies mutations des artefacts de séquençage du au fait qu'ils atteignent des niveaux similaires. Dans cette thèse nous avons étudié la nature systématique des erreurs dans les données NGS afin de proposer des méthodologies efficaces capables d'identifier des mutations potentiellement en faible abondance. Dans un premier chapitre, nous decrivons needlestack, un nouvel outil d'appel de variants basé sur la modélisation des erreurs systématiques sur plusieurs échantillons pour extraire des mutations candidates. Dans un deuxième chapitre, nous proposons deux méthodes de filtrage des variants basées sur des résumés statistiques et sur de l'apprentissage automatique, dans le but de d'améliorer la précision de la détection des mutations par l'identification des erreurs non-systématiques. Finalement, dans un dernier chapitre nous appliquons ces approches pour développer des biomarqueurs de détection précoce du cancer en utilisant l'ADN circulant tumoral / Comprehensive characterization of DNA variations can help to progress in multiple cancer genomics fields. Next Generation Sequencing (NGS) is currently the most efficient technique to determine a DNA sequence, due to low experiment cost and time compared to the traditional Sanger sequencing. Nevertheless, detection of mutations from NGS data is still a difficult problem, in particular for somatic mutations present in very low abundance like when trying to identify tumor subclonal mutations, tumor-derived mutations in cell free DNA, or somatic mutations from histological normal tissue. The main difficulty is to precisely distinguish between true mutations from sequencing artifacts as they reach similar levels. In this thesis we have studied the systematic nature of errors in NGS data to propose efficient methodologies in order to accurately identify mutations potentially in low proportion. In a first chapter, we describe needlestack, a new variant caller based on the modelling of systematic errors across multiple samples to extract candidate mutations. In a second chapter, we propose two post-calling variant filtering methods based on new summary statistics and on machine learning, with the aim of boosting the precision of mutation detection through the identification of non-systematic errors. Finally, in a last chapter we apply these approaches to develop cancer early detection biomarkers using circulating tumor DNA

Les leucémies aiguës myéloïdes (LAM) du sujet âgé sont les plus fréquentes des leucémies aiguës. Bien que de physiopathologie hétérogène, elles partagent un pronostic défavorable. L’azacitidine est devenue un des traitements de référence pour les patients jugés inéligibles pour une chimiothérapie intensive mais les critères de sélection des patients entre ces deux approches sont controversés. L’identification de biomarqueur prédictif de réponse à l’azacitidine doit permettre de rationnaliser ce choix thérapeutique. Les facteurs pronostiques classiques d’une cohorte de 334 patients atteints de LAM manquent de précision pour guider la meilleure stratégie pour un patient donné. A partir du séquençage de 224 patients traités par azacitidine, nous montrons un impact défavorable des mutations de TP53 sur la survie globale, quel que soit leur caractérisation fonctionnelle. Le séquençage des exomes de 49 patients selon leur réponse à l’azacitidine (26 répondeurs et 23 non répondeurs), suivi du re-séquençage ciblé de 4 polymorphismes chez 175 patients a montré un impact positif du polymorphisme rs7622799 de MECOM sur la survie globale sous azacitidine. / Elderly patients with acute myeloid leukemias (AML) represent the most frequent acute leukemias. Although they differ in their pathophysiology, they all share an adverse prognosis. Azacitidine has become one of the reference low-intensity frontline therapy for patients deemed unfit for intensive chemotherapy. Patients selection between these 2 options remains controversial. Predictive biomarkers of response to azacitidine should allowed to rationalize this decision making. Classical prognosis factors of a cohort of 334 newly diagnosed AML lack of precision to determine the optimum strategy for any individual patient. By sequencing of a 224-patients series of azacitidine-treated AML patients, we demonstrate an adverse impact of TP53 mutation on overall survival, irrespective of the functional characterization of p53 mutants. Exome sequencing of 49 patients with extreme phenotype as defined by their response under azacitidine (26 responders versus 23 non-responders), followed by targeted sequencing of 4 common polymorphisms in a validation set of 175 patients, showed a positif impact of MECOM rs7622799 on overall survival.

Orientador: Semíramis Guimarães Ferraz Viana / Resumo: Giardia duodenalis é um dos principais agentes etiológicos de diarreia infecciosa, sobretudo em crianças em idade pré-escolar que vivem em comunidades de baixa renda. Estudos da diversidade genética de G. duodenalis ampliaram o conhecimento da epidemiologia nas infecções humanas, entretanto um dos temas mais interessantes e menos conhecidos é a possível interação de Giardia com o microbioma do hospedeiro e com patógenos concomitantes. No presente estudo, avaliou-se a composição e a diversidade da comunidade bacteriana de crianças saudáveis e crianças com diarreia, parasitadas por Giardia e outros protozoários intestinais. Os isolados de Giardia obtidos nessa população foram caracterizados geneticamente. Amostras de fezes foram obtidas de 181 crianças de 0 a 6 anos de idade, das quais 156 crianças hígidas atendidas em centros de educação infantil e 25 crianças com diarreia atendidas no PS Infantil Municipal. Cada amostra de fezes foi processada para o exame microscópico e submetida à extração de DNA a ser empregado em duas etapas distintas: (1) amplificação e sequenciamento Sanger para a caracterização genética de Giardia e o diagnóstico de Blastocystis sp, Dientamoeba fragilis, Enterocytozoon bieneusi e Cryptosporidium spp. e (2) amplificação do gene 16s RNA ribossomal e sequenciamento de nova geração (plataforma Illumina MiSeq) para a caracterização da microbiota intestinal. Giardia (36,5%) e Blastocystis (41,7%) foram os parasitas mais prevalentes. A caracterização genética... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Giardia duodenalis is one of the major etiological agents of infectious diarrhea, especially in preschool children living in low-income settings. Studies focused on genetic diversity of G. duodenalis have provided insights for a better understanding of epidemiology in human infections. However, one of the most interesting and least known issues is the possible interplay between Giardia and the host microbiome and concomitant pathogens. In this work, we evaluated the diversity and composition of bacterial community of healthy children and children presenting with diarrhea infected by Giardia and/or other intestinal protozoa. In addition, Giardia isolates infecting this population were genotyping. A total of 181 stool samples from children aged 0 to 6 years old (156 from daycare children and 25 from diarrheic children attending in an emergence pediatric center) were tested by microscopic examination and submitted to DNA extraction for the following steps: (1) conventional PCR/sequencing for Giardia genotyping and the diagnosis of Blastocystis sp, Dientamoeba fragilis, Enterocytozoon bieneusi and Cryptosporidium spp and (2) next-generation sequencing (Illumina MiSeq) based analysis of intestinal microbiota. Giardia (36.5%) and Blastocystis (41.7%) were the most prevalent parasites. Analysis of Giardia sequences retrieved from 61 isolates revealed infections by assemblages A (31%), B (69%) and mixed infections A+B (3%). Metagenomic analyzes revealed similarity of bacterial microb... (Complete abstract click electronic access below) / Doutor

The Brigham Young University (BYU) Radio Astronomy Systems group, in collaboration with the National Radio Astronomy Observatory (NRAO), the Center for Astrophysics at West Virginia University (WVU), and the Green Bank Observatory (GBO) have developed, and commissioned, a broadband real-time digital back end processing system for a 38-element phased array feed (PAF) with 150 MHz of instantaneous bandwidth. This system is capable of producing coarse and fine channel correlations, and implements a real-time beamformer that forms 7 simultaneous dual-polarized beams. This thesis outlines the hardware and software development for the digital back end and presents on-telescope commissioning results. This system has been measured to provide an unprecedented low Tsys/η noise level of 28 K and can perform maps of galactic hydrogen observations in a fraction of the time of a conventional single horn feed. The National Radio Astronomy Observatory (NRAO) has recently announced the concept and development of the next generation Very Large Array (ngVLA), a large interferometric array consisting of 300 radio telescopes and longest baseline (distance between a pair of antennas) of 300 km. Large interferometric arrays have been shown to attenuate radio frequency interference (RFI) because it is decorrelated as it propagates across long baselines. This is not always sufficient, especially with dense core array geometries and with the ever-increasing amount of strong RFI sources. Conventional RFI projection-based mitigation techniques have performed poorly on large interferometers because of covariance matrix estimation error due to decorrelation when identifying interference subspace parameters. This thesis presents an algorithm that overcomes the challenge of decorrelation by applying subspace projection via subarray processing (SP-SAP). Each subarray is designed to have a set of elements with high mutual correlation in the interferer for better estimation of subspace parameters. In simulation, compared to the former approach of applying subspace projection on the full array, SP-SAP improves mitigation of the RFI on the order of 9 dB. A signal of interest is shown then to be observable through the RFI in a full synthetic image.

Obsessive-compulsive disorder (OCD) and the spectrum of associated conditions, affect 2-4% of the population worldwide. Although heritability studies in OCD have shown a 3 - 12 times increased risk for first degree relatives, the identification of the underlying risk-conferring genetic variation using classic genetic association studies has proven to be difficult. The possibility of a larger contribution of rare genetic variants to the risk of psychiatric disorder has been suggested by several successful studies. We expect that a spectrum of risk allele frequencies exists, which includes not only common variation but also a substantial amount of rare genetic variants that contribute to OCD. This thesis is aimed at identifying and functionally characterizing rare genetic variation in the OCD spectrum. Identified statistically significant variants were scrutinized for changes related to synaptic function using high content screening and subsequent functional analyses. Identifying the genetic profile of rare variants found in the OCD spectrum cohort combined with the functional impact that these variants have has provided insight into the etiology of the OCD spectrum. With these approaches a foundation can be laid for the development of a predictive model of the OCD spectrum.

The chimpanzee is humankind’s closest living relative and the two species diverged ~6 million years ago. Comparative studies of the human and chimpanzee genomes and transcriptomes are of great interest to understand the molecular mechanisms of speciation and the development of species-specific traits. The aim of this thesis is to characterize differences between the two species with regard to their genome sequences and the resulting transcript profiles. The first two papers focus on indel divergence and in particular, indels causing premature termination codons (PTCs) in 8% of the chimpanzee genes. The density of PTC genes is correlated with both the distance to the telomere and the indel divergence. Many PTC genes have several associated transcripts and since not all are affected by the PTC we propose that PTCs may affect the pattern of expressed isoforms. In the third paper, we investigate the transcriptome divergence in cerebellum, heart and liver, using high-density exon arrays. The results show that gene expression differs more between tissues than between species. Approximately 15% of the genes are differentially expressed between species, and half of the genes show different splicing patterns. We identify 28 cassette exons which are only included in one of the species, often in a tissue-specific manner. In the fourth paper, we use massive parallel sequencing to study the chimpanzee transcriptome in frontal cortex and liver. We estimate gene expression and search for novel transcribed regions (TRs). The majority of TRs are located close to genes and possibly extend the annotations. A subset of TRs are not found in the human genome. The brain transcriptome differs substantially from that of the liver and we identify a subset of genes enriched with TRs in frontal cortex. In conclusion, this thesis provides evidence of extensive genomic and transcriptomic variability between human and chimpanzee. The findings provide a basis for further studies of the underlying differences affecting phenotypic divergence between human and chimpanzee.