1,039 research outputs found

    Graduate Catalog of Studies, 2023-2024

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    Graduate Catalog of Studies, 2023-2024

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    On the robustness of Bayesian phylogenetic gene tree estimation

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    Comparative genomics of recent adaptation in Candida pathogens

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    [eng] Fungal infections pose a serious health threat, affecting >1,000 million people and causing ~1.5 million deaths each year. The problem is growing due to insufficient diagnostic and therapeutic options, increased number of susceptible patients, expansion of pathogens partly linked to climate change and the rise of antifungal drug resistance. Among other fungal pathogens, Candida species are a major cause of severe hospital-acquired infections, with high mortality in immunocompromised patients. Various Candida pathogens constitute a public health issue, which require further efforts to develop new drugs, optimize currently available treatments and improve diagnostics. Given the high dynamism of Candida genomes, a promising strategy to improve current therapies and diagnostics is to understand the evolutionary mechanisms of adaptation to antifungal drugs and to the human host. Previous work using in vitro evolution, population genomics, selection inferences and Genome Wide Association Studies (GWAS) have partially clarified such recent adaptation, but various open questions remain. In the three research articles that conform this PhD thesis we addressed some of these gaps from the perspective of comparative genomics. First, we addressed methodological issues regarding the analysis of Candida genomes. Studying recent adaptation in these pathogens requires adequate bioinformatic tools for variant calling, filtering and functional annotation. Among other reasons, current methods are suboptimal due to limited accuracy to identify structural variants from short read sequencing data. In addition, there is a need for easy-to-use, reproducible variant calling pipelines. To address these gaps we developed the “personalized Structural Variation detection” pipeline (perSVade), a framework to call, filter and annotate several variant types, including structural variants, directly from reads. PerSVade enables accurate identification of structural variants in any species of interest, such as Candida pathogens. In addition, our tool automatically predicts the structural variant calling accuracy on simulated genomes, which informs about the reliability of the calling process. Furthermore, perSVade can be used to analyze single nucleotide polymorphisms and copy number-variants, so that it facilitates multi-variant, reproducible genomic studies. This tool will likely boost variant analyses in Candida pathogens and beyond. Second, we addressed open questions about recent adaptation in Candida, using perSVade for variant identification. On the one hand, we investigated the evolutionary mechanisms of drug resistance in Candida glabrata. For this, we used a large-scale in vitro evolution experiment to study adaptation to two commonly-used antifungals: fluconazole and anidulafungin. Our results show rapid adaptation to one or both drugs, with moderate fitness costs and through few mutations in a narrow set of genes. In addition, we characterize a novel role of ERG3 mutations in cross-resistance towards fluconazole in anidulafungin-adapted strains. These findings illuminate the mutational paths leading to drug resistance and cross-resistance in Candida pathogens. On the other hand, we reanalyzed ~2,000 public genomes and phenotypes to understand the signs of recent selection and drug resistance in six major Candida species: C. auris, C. glabrata, C. albicans, C. tropicalis, C. parapsilosis and C. orthopsilosis. We found hundreds of genes under recent selection, suggesting that clinical adaptation is diverse and complex. These involve species-specific but also convergently affected processes, such as cell adhesion, which could underlie conserved adaptive mechanisms. In addition, using GWAS we predicted known drivers of antifungal resistance alongside potentially novel players. Furthermore, our analyses reveal an important role of generally-overlooked structural variants, and suggest an unexpected involvement of (para)sexual recombination in the spread of resistance. Taken together, our findings provide novel insights on how Candida pathogens adapt to human-related environments and suggest candidate genes that deserve future attention. In summary, the results of this thesis improve our knowledge about the mechanisms of recent adaptation in Candida pathogens, which may enable improved therapeutic and diagnostic applications.[cat] Les infeccions fúngiques representen una greu amenaça per a la salut, afectant a més de 1.000 milions de persones i causant aproximadament 1,5 milions de morts cada any. El problema està augmentant a causa d’unes opcions terapèutiques i diagnòstiques insuficients, l'increment del nombre de pacients susceptibles, l'expansió dels patògens parcialment vinculada al canvi climàtic i l'augment de la resistència als fàrmacs antifúngics. D’entre diversos fongs patògens, els llevats del gènere Candida són una causa important d'infeccions nosocomials, amb una alta mortalitat en pacients immunodeprimits. Diverses espècies de Candida constitueixen un problema de salut pública, cosa que requereix més esforços per a desenvolupar nous medicaments, optimitzar els tractaments disponibles i millorar els diagnòstics. Tenint en compte el dinamisme genòmic d’aquests patògens, una estratègia prometedora per millorar les teràpies i diagnòstics actuals és comprendre els mecanismes evolutius d'adaptació als fàrmacs antifúngics i a l’hoste humà. Treballs anteriors utilitzant l'evolució in vitro, la genòmica de poblacions, les inferències de selecció i els estudis d'associació de genoma complet (GWAS, per les sigles en anglès) han aclarit parcialment aquesta adaptació recent, però encara hi ha diverses preguntes obertes. En els tres articles que conformen aquesta tesi doctoral, hem abordat algunes d'aquestes preguntes des de la perspectiva de la genòmica comparativa. En primer lloc, hem abordat qüestions metodològiques relatives a l'anàlisi dels genomes de les espècies Candida. L'estudi de l'adaptació recent en aquests patògens requereix eines bioinformàtiques adequades per a la detecció, filtratge i anotació funcional de variants genètiques. Entre altres raons, els mètodes actuals són subòptims a causa de la limitada precisió per identificar variants estructurals a partir de dades de seqüenciació amb lectures curtes. A més, hi ha una necessitat d’eines computacionals per a la detecció de variants que siguin senzilles d'utilitzar i reproduibles. Per abordar aquestes mancances, hem desenvolupat el mètode bioinformàtic "personalized Structural Variation detection" (perSVade), una eina que permet la detecció, filtratge i anotació de diversos tipus de variants, incloent-hi les variants estructurals, directament des de les lectures. PerSVade permet la identificació precisa de les variants estructurals en qualsevol espècie d'interès, com ara els patògens Candida. A més, la nostra eina prediu automàticament la precisió de la detecció d’aquestes variants en genomes simulats, la qual cosa informa sobre la fiabilitat del procés. Finalment, perSVade es pot utilitzar per analitzar altres tipus de variants, com els polimorfismes de nucleòtid únic o els canvis en el nombre de còpies, facilitant així estudis genòmics integrals i reproduibles. Aquesta eina probablement impulsarà les anàlisis genòmiques en els patògens Candida i també en altres espècies. En segon lloc, hem abordat algunes de les preguntes obertes sobre l'adaptació recent en els llevats Candida, utilitzant perSVade per a la identificació de variants. D'una banda, hem investigat els mecanismes evolutius de resistència als fàrmacs antifúngics en Candida glabrata. Per a això, hem utilitzat un experiment d'evolució in vitro a gran escala per estudiar l'adaptació a dos antifúngics comuns: el fluconazol i l’anidulafungina. Els nostres resultats mostren una adaptació ràpida a un o ambdós fàrmacs, amb un cost per al creixement moderat i a través de poques mutacions en un nombre reduït de gens. A més, hem caracteritzat un paper nou de les mutacions en ERG3 en la resistència creuada al fluconazol en soques adaptades a anidulafungina. Aquests descobriments aclareixen els processos mutacionals que condueixen a la resistència als fàrmacs i a la resistència creuada en els patògens Candida. D'altra banda, hem re-analitzat aproximadament 2.000 genomes i fenotips disponibles en repositoris públics per a comprendre els senyals genòmics de selecció recent i de resistència a fàrmacs antifúngics, en sis espècies rellevants de Candida: C. auris, C. glabrata, C. albicans, C. tropicalis, C. parapsilosis i C. orthopsilosis. Hem trobat centenars de gens sota selecció recent, suggerint que l'adaptació clínica és diversa i complexa. Aquests gens estan relacionats amb funcions específiques de cada espècie, però també trobem processos alterats de manera similar en diferents patògens, com per exemple l’adhesió cel·lular, cosa que indica fenòmens d’adaptació conservats. A part, utilitzant GWAS hem predit mecanismes esperats de resistència a antifúngics i també possibles nous factors. A més, les nostres anàlisis revelen un paper important de les variants estructurals, generalment poc estudiades, i suggereixen una implicació inesperada de la recombinació (para)sexual en la propagació de la resistència. En conjunt, els nostres descobriments proporcionen noves perspectives sobre com els patògens Candida s'adapten als entorns humans, i suggereixen gens candidats que mereixen investigacions futures. En resum, els resultats d’aquesta tesi milloren el nostre coneixement sobre els mecanismes d'adaptació recent en els patògens Candida, cosa que pot permetre el disseny de noves teràpies i diagnòstics

    Molecular signals of arms race evolution between RNA viruses and their hosts

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    Viruses are intracellular parasites that hijack their hosts’ cellular machinery to replicate themselves. This creates an evolutionary “arms race” between hosts and viruses, where the former develop mechanisms to restrict viral infection and the latter evolve ways to circumvent these molecular barriers. In this thesis, I explore examples of this virus-host molecular interplay, focusing on events in the evolutionary histories of both viruses and hosts. The thesis begins by examining how recombination, the exchange of genetic material between related viruses, expands the genomic diversity of the Sarbecovirus subgenus, which includes SARS-CoV responsible for the 2002 SARS epidemic and SARS-CoV-2 responsible for the COVID-19 pandemic. On the host side, I examine the evolutionary interaction between RNA viruses and two interferon-stimulated genes expressed in hosts. First, I show how the 2′-5′-oligoadenylate synthetase 1 (OAS1) gene of horseshoe bats (Rhinolophoidea), the reservoir host of sarbecoviruses, lost its anti-coronaviral activity at the base of this bat superfamily. By reconstructing the Rhinolophoidea common ancestor OAS1 protein, I first validate the loss of antiviral function and highlight the implications of this event in the virus-host association between sarbecoviruses and horseshoe bat hosts. Second, I focus on the evolution of the human butyrophilin subfamily 3 member A3 (BTN3A3) gene which restricts infection by avian influenza A viruses (IAV). The evolutionary analysis reveals that BTN3A3’s anti-IAV function was gained within the primates and that specific amino acid substitutions need to be acquired in IAVs’ NP protein to evade the human BTN3A3 activity. Gain of BTN3A3-evasion-conferring substitutions correlate with all major human IAV pandemics and epidemics, making these NP residues key markers for IAV transmissibility potential to humans. In the final part of the thesis, I present a novel approach for evaluating dinucleotide compositional biases in virus genomes. An application of my metric on the Flaviviridae virus family uncovers how ancestral host shifts of these viruses correlate with adaptive shifts in their genomes’ dinucleotide representation. Collectively, the contents of this thesis extend our understanding of how viruses interact with their hosts along their intertangled evolution and provide insights into virus host switching and pandemic preparedness

    Statistical methods for gene selection and genetic association studies

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    This dissertation includes five Chapters. A brief description of each chapter is organized as follows. In Chapter One, we propose a signed bipartite genotype and phenotype network (GPN) by linking phenotypes and genotypes based on the statistical associations. It provides a new insight to investigate the genetic architecture among multiple correlated phenotypes and explore where phenotypes might be related at a higher level of cellular and organismal organization. We show that multiple phenotypes association studies by considering the proposed network are improved by incorporating the genetic information into the phenotype clustering. In Chapter Two, we first illustrate the proposed GPN to GWAS summary statistics. Then, we assess contributions to constructing a well-defined GPN with a clear representation of genetic associations by comparing the network properties with a random network, including connectivity, centrality, and community structure. The network topology annotations based on the sparse representations of GPN can be used to understand the disease heritability for the highly correlated phenotypes. In applications of phenome-wide association studies, the proposed GPN can identify more significant pairs of genetic variant and phenotype categories. In Chapter Three, a powerful and computationally efficient gene-based association test is proposed, aggregating information from different gene-based association tests and also incorporating expression quantitative trait locus information. We show that the proposed method controls the type I error rates very well and has higher power in the simulation studies and can identify more significant genes in the real data analyses. In Chapter Four, we develop six statistical selection methods based on the penalized regression for inferring target genes of a transcription factor (TF). In this study, the proposed selection methods combine statistics, machine learning , and convex optimization approach, which have great efficacy in identifying the true target genes. The methods will fill the gap of lacking the appropriate methods for predicting target genes of a TF, and are instrumental for validating experimental results yielding from ChIP-seq and DAP-seq, and conversely, selection and annotation of TFs based on their target genes. In Chapter Five, we propose a gene selection approach by capturing gene-level signals in network-based regression into case-control association studies with DNA sequence data or DNA methylation data, inspired by the popular gene-based association tests using a weighted combination of genetic variants to capture the combined effect of individual genetic variants within a gene. We show that the proposed gene selection approach have higher true positive rates than using traditional dimension reduction techniques in the simulation studies and select potentially rheumatoid arthritis related genes that are missed by existing methods

    ACARORUM CATALOGUS IX. Acariformes, Acaridida, Schizoglyphoidea (Schizoglyphidae), Histiostomatoidea (Histiostomatidae, Guanolichidae), Canestrinioidea (Canestriniidae, Chetochelacaridae, Lophonotacaridae, Heterocoptidae), Hemisarcoptoidea (Chaetodactylidae, Hyadesiidae, Algophagidae, Hemisarcoptidae, Carpoglyphidae, Winterschmidtiidae)

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    The 9th volume of the series Acarorum Catalogus contains lists of mites of 13 families, 225 genera and 1268 species of the superfamilies Schizoglyphoidea, Histiostomatoidea, Canestrinioidea and Hemisarcoptoidea. Most of these mites live on insects or other animals (as parasites, phoretic or commensals), some inhabit rotten plant material, dung or fungi. Mites of the families Chetochelacaridae and Lophonotacaridae are specialised to live with Myriapods (Diplopoda). The peculiar aquatic or intertidal mites of the families Hyadesidae and Algophagidae are also included.Publishe

    Rescue of Missplicing by CRISPR/SpCas9-Based Genome Editing Approaches Targeting Deep-Intronic Variants in ABCA4

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    CRISPR/Cas-vermittelte Genom-Editierung stellt eine vielversprechende Technologie dar, mit der sich die meisten bekannten krankheitsverursachenden Mutationen, einschließlich tief-intronischer Varianten, korrigieren lassen. Pathogene tief-intronische Varianten stellen einen erheblichen Teil der krankheitsverursachenden Mutationen im Mutationsspektrum des ABCA4-Gens dar. Die molekularen Mechanismen, durch welche sie wirken, sind mit fehlerhaften pre-mRNA-Spleißprozessen verbunden, die schließlich zu fehlgespleißten ABCA4-Transkripten führen. Die isolierte ABCA4 c.5197-557G>T tief-intronische Variante führt zur Retention einer 188-bp intronischen Sequenz im reifen mRNA-Transkript. Durch die Etablierung von drei Standard-CRISPR/SpCas9-basierten Ansätzen und der neuartigen Enhanced-Deletion-SpCas9-Strategie konnte der Spleißdefekt, der durch die isolierte c.5197-557G>T verursacht wird, im Minigen-Assay in HEK293T-Zellen sowie in heterozygoten c.5197-557G>T-Zapfen-Photorezeptor-Vorläuferzellen erfolgreich korrigiert werden. Darüber hinaus wurde der neuartige Enhanced-Deletion-SpCas9-Ansatz in einem Minigen-Assay in HEK293T-Zellen zur Rettung von Fehlspleißen aufgrund der geclusterten tief-intronischen Varianten (c.5196+1013G>A, c.5196+1056G>A, c.5196+1134C>G, c.5196+1137G>A und c.5196+1216C>A) im Intron 30 von ABCA4 in ersten Experimenten angewendet. Insgesamt konnte in dieser Arbeit zum ersten Mal gezeigt werden, dass Spleißdefekte in ABCA4, welche durch tief-intronische Varianten verursacht werden, durch die Anwendung von Genom-Editierungs-Ansätzen erfolgreich behoben werden können. Darüber hinaus wurde ein neuartiges und vielversprechendes Editierungs-Tool (Enhanced-Deletion-SpCas9) etabliert und für die Rettung von isolierten und geclusterten tief-intronischen-Varianten optimiert.Genome editing mediated by CRISPR/Cas molecules represent a promising technology applicable to the correction of most of the known disease-causing mutations, including pathogenic deep-intronic variants. Pathogenic deep-intronic variants represent a good portion of the disease causing mutations in the mutational spectrum of the ABCA4 gene. The molecular mechanisms through which they act is associated with faulty pre-mRNA splicing processes, eventually leading to abberant ABCA4 transcripts. The isolated ABCA4 c.5197-557G>T deep-intronic variants results in the retention of a 188-bp intronic sequence in the mature mRNA transcript. By establishing three standard CRISPR/SpCas9-based approaches and the novel Enhanced-Deletion SpCas9 approach, the splicing defect due to the isolated c.5197-557G>T was sucessufully corrected in minigene assay in HEK293T cells, as well as in heterozygous c.5197-557G>T cone photoreceptor precursor cells. Furthermore, the novel Enhanced-Deletion-SpCas9 approach was preliminarly applied in minigene assay in HEK293T cells for the rescue of missplicing due to the clustered deep-intronic variants (c.5196+1013G>A, c.5196+1056G>A, c.5196+1134C>G, c.5196+1137G>A and c.5196+1216C>A) in intron 30 of ABCA4. On the whole, this thesis showed for the first time the successull rescue of ABCA4-related splicing defects by implementing genome editing approaches. In addition, a novel and highly promising editing tool (Enhanced-Deletion-SpCas9) was established and optimized for the rescue of isolated and clustered deep-intronic variants
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