This thesis presents a method for integrating heterogeneous gene/protein datasets at the functional level based on Gene Ontology term similarity. Often biologists want to integrate heterogeneous data sets obtain from different biological samples. A major challenge in this process is how to link the heterogeneous datasets. Currently, the most common approach is to link them through common reference database identifiers which tend to result in small number of matching identifiers. This is due to lack of standard accession schemes. Due to this problem, biologists may not recognize the underlying biological phenomena revealed by a combination of the data but by each data set individually. We discuss an approach for integrating heterogeneous datasets by computing the similarity among them based on the similarity of their GO annotations. Then we group the genes and/or proteins with similar annotations by applying a hierarchical clustering algorithm. The results demonstrate a more comprehensive understanding of the biological processes involved.

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Cold-water corals are an important component of deep-sea ecosystems as they establish structurally complex habitats that support benthic biodiversity. These communities face imminent threats from increasing anthropogenic influences in the deep sea. Following the 2010 Deepwater Horizon blowout, several spill-impacted coral communities were discovered in the deep Gulf of Mexico, and subsequent mesophotic regions, although the exact source and extent of this impact is still under investigation, as is the recovery potential of these organisms. At a minimum, impacted octocorals were exposed to flocculant material containing oil and dispersant components, and were visibly stressed. Here the impacts of oil and dispersant exposure are assessed for the octocoral genus Paramuricea. A de novo reference assembly was created to perform gene expression analyses from high-throughput sequencing data. Robust assessments of these data for P. biscaya colonies revealed the underlying expression-level effects resulting from in situ floc exposure. Short-term toxicity studies, exposing the cold-water octocorals Paramuricea type B3 and Callogorgia delta to various fractions and concentrations of oil, dispersant and oil/dispersant mixtures, were also conducted to determine overall toxicity and tease apart the various components of the synergistic exposure effects. Finally, alterations in Paramuricea B3 gene expression profiles were inspected to characterize genome-wide changes induced by each treatment and putative genes under differential regulation. The experimental results provide evidence for a relatively high toxicity of chemical dispersants as compared to oil additions alone, elucidating the implications of applying oil dispersants to future oil spills. My findings revealed signatures of cellular stress in floc-exposed corals associated with xenobiotic metabolism, immune and inflammatory responses as well as transcriptional suppression of vital cellular components like ribosomal proteins. The data also suggests poor recovery potential in our coral samples exposed to floc. In addition, promising biomarker candidates were identified from the differential expression data for use in future spill-impact monitoring. / Biology

Current sequencing technologies allows researchers unprecedented insight into our biology, and how these biological mechanisms can become distorted and lead to disease. These aberrant mechanisms can be brought about by many causes, but some occur as a result of genetic mutations or external factors through the epigenome. Here, we used our microfluidic technology to profile the epigenome and transcriptome to study such aberrant mechanisms in three different diseases and illnesses: breast cancer, chronic inflammation, and mental illness. We profiled the epigenome of breast tissue from healthy women with the BRCA1 mutation to understand how the mutation may facilitate eventual breast cancer. Epigenomic changes in breast cells suggest that cells in the basal compartment may differentiate into a different cell type, and perhaps become the source of breast cancer. Next, we compared the epigenome and genome of murine immune cells under low-grade inflammation and acute inflammation conditions. We found that low-grade inflammation preferentially utilizes different signaling pathways than in acute inflammation, and this may lead to a non-resolving state. Finally, we analyzed the effect of the maternal immune activation on unborn offspring, and how these changes could cause later mental illness. The insights we made into these diseases may lead to future therapies. / Doctor of Philosophy / Despite advances in medical and scientific research, there is still a dearth of information on how diseases affect the expression of our genes, such as breast cancer, chronic inflammation, and influenza. Mutation in the BRCA1 gene is probably the most well-known mutation that can lead to breast cancer. We know the overarching reason that mutation in BRCA1 can lead to cancer, as BRCA1 is responsible for repairing damage in the DNA, so mutations can compound and create cancerous cells. However, we do not know the exact mechanisms by which this actually happens. Another widespread problem is chronic inflammation, which can promote or lead to diseases such as diabetes, cancer, Alzheimer's, Rheumatoid arthritis, and heart disease. In addition, there are many causes of chronic inflammation that many people have experienced at some point in time, including stress, insomnia, being sedentary, poor eating habits, and obesity. Despite this, we still do not fully understand why chronic inflammation differs from normal inflammation, which is a healthy process, or why it does not resolve. There are also other connections that are surprising, and many are not aware of. If a pregnant woman gets the flu during her second trimester, her baby has much higher odds of developing schizophrenia later in its lifetime. Given the prevalence of the flu, there is a very real chance that an expecting mother will be infected during her pregnancy.

Fungi play important roles in various environments. Some of them infect plants and cause economically important diseases. However, many fungal pathogens cause similar symptoms or are even spread asymptomatically, making it difficult to identify them morphologically. Therefore, culture-independent, sequence-based diagnostic methods that can detect and identify fungi independently of the symptoms that they cause are desirable. Whole genome metagenomic sequencing has the potential to enable rapid diagnosis of plant diseases without culturing pathogens and designing pathogen-specific probes. In my study, the MinION nanopore sequencer, a portable single‐molecule sequencing platform developed by Oxford Nanopore Technologies, was employed to detect the fungus Calonectria pseudonaviculata (Cps), the causal agent of the devastating boxwood blight disease of the popular ornamental boxwood (Buxus spp.). Various DNA extraction methods and computational tools were compared. Detection was sensitive with an extremely low false positive rate for most methods. Therefore, metagenomic sequencing is a promising technology that could be implemented in routine diagnostics of fungal diseases. Other fungi may play important roles in the atmosphere because of their ice nucleation activity (INA). INA is the capacity of some particles to induce ice formation above the temperature that pure water freezes (-38°C). Importantly, INPs affect the ratio of ice crystals to liquid droplets in clouds, which in turn affects Earth's radiation balance and the intensity and frequency of precipitation. A few fungal species can produce ice nucleating particles (INPs) that cause ice formation at temperatures ≥ –10°C and they may be present in clouds. Two such fungal genera are Fusarium and Mortierella but little is known about their INPs and the genetic basis of their INA. In my study, F. avenaceum and M. alpina were examined in detail. INPs of both species were characterized and it was found that strains within both species varied in regards to the strength of INA. Whole genome sequencing and comparative genomic studies were then performed to identify putative INA genes. Differential expression analyses at different growth temperatures were also performed. INP properties of the two species shared similarities, both appearing to consist of secreted aggregates larger than 30 kDa. Low temperatures induced INA in both species. Lists of candidate INA genes were identified based on their presence in the strains with the strongest INA and/or induction of their expression at low temperatures and because they either encode secreted proteins or enzymes that produce other molecules known to have INA in other organisms. These genes can now be characterized further to help identify the fungal INA genes in both species. This can be expected to help increase our understanding of the role of fungal INA in the atmosphere. / Doctor of Philosophy / Fungi are important to life on Earth and play roles in the environments that surround us. On the one hand, fungi can make plants sick and some plant diseases may even cause economic losses to farmers. If the cause of a disease can be identified accurately in an early stage before symptoms develop, disease transmission may be prevented and plants may be protected from disease. However, it is a challenge to find out which fungus causes which disease since symptoms of different fungal diseases look very similar. Typically, we have to wait for plants to become very sick or we have to isolate the fungus that causes a disease to identity it, which may be time-consuming and not lead to precise identification. DNA sequencing technologies have the potential to lead to more sensitive, faster, and more accurate disease diagnosis and, therefore, may help prevent disease outbreaks. In my study, the MinION nanopore sequencer, a small portable device, was used to detect the fungus causing boxwood blight on boxwood. By loading the DNA of unhealthy boxwood on the device, the boxwood blight pathogen was identified within a very short time. Thus, this method is a promising diagnostic method that may be applied to detect other plant fungal diseases as well. On the other hand, fungi may affect Earth's climate by affecting how many water droplets in clouds are frozen, which in turn affects Earth's temperature and how often and how much it rains and snows. Fungi may affect the freezing of water droplets in clouds since some of them have ice nucleation activity (INA), which is the capacity to catalyze ice formation at a higher temperature than the temperature at which pure water freezes (-38°C), and they may be present in clouds. So far, INA has only been found in a few fungi, including the species Fusarium avenaceum and Mortierella alpina, but the mechanism of their INA is poorly understood. In my study, multiple F. avenaceum and M. alpina strains were examined in detail. Two approaches were used. First, strains in each species were compared with each other to find out how strong their INA is. Once it was found that they differed in their strength of INA, their genomes were sequenced and compared to find genes present in the most active strains and missing from the least active strains since it is these genes that may contribute to INA. It was also found that both fungal species had stronger INA when they were grown at lower temperatures. Therefore, the expression of their genes between higher and lower temperatures was compared to find the genes that were more highly expressed at lower temperatures since it is these genes that may cause INA. Based on previous studies, fungal INPs may either consist of secreted proteins or be the products of biosynthetic gene clusters. Therefore, the list of potential genes was reduced by looking for genes encoding either secreted proteins or biosynthetic gene clusters. The list of these potential INA genes will make it easier to identify the INA genes in F. avenaceum and M. alpina and determine the role of fungi in affecting the weather and climate on Earth.

The field of functional genomics aims to understand the complex relationship between genotype and phenotype by integrating genome-wide approaches, such as transcriptomics, proteomics, and metabolomics. Large-scale "-omics" research has been made widely possible by the advent of high-throughput techniques, such as next-generation sequencing and mass-spectrometry. The vast data generated from such studies provide a wealth of information on the biological dynamics underlying phenotypes. Though functional genomics approaches are used extensively in human disease research, their use also spans organisms as miniscule as mycoplasmas to as great as sperm whales. In particular, functional genomics is instrumental in agricultural advancements for the improvement of productivity and sustainability in crop and livestock production. Improvement in soybean production is especially imperative, as soybeans are a primary source of oil and protein for human and livestock consumption, respectively. The research presented here employs functional genomics approaches – transcriptomics and metabolomics – to discern the transcriptional regulation and metabolic events underlying two economically important agronomic traits in soybean: seed phytic acid content and Soybean mosaic virus resistance. At normal levels, seed phytic acid content inhibits mineral absorption in humans and livestock, acting as an antinutrient and contributing to phosphorus pollution; however, the development of low phytic acid soybeans has helped mitigate these issues, as their seeds increase nutrient bioavailability and reduce environmental impact. Despite these desirable qualities, low phytic acid soybeans exhibit poor seed performance, which negatively affects germination rates and yield and has prevented their large-scale commercial production. Thus, part of the focus of this research was investigating the effects of mutations conferring the low phytic acid phenotype on seed germination. Comparative studies between low and normal phytic acid soybean seeds were carried out and revealed distinct differences in metabolite profiles and in the transcriptional regulation of biological pathways that may be vital for successful seed germination. The final part of this research concerns Rsv3-mediated extreme resistance, a unique mode of resistance that is effective against the most virulent strains of Soybean mosaic virus. The molecular mechanisms governing this type of resistance are poorly characterized. Therefore, the research presented here attempts to elucidate the regulatory elements responsible for the induction of the Rsv3-mediated extreme resistance response. Utilizing a comparative transcriptomic time series approach on Soybean mosaic virus-inoculated Rsv3 (resistant) and rsv3 (susceptible) soybean lines, this final study provides gene candidates putatively functioning in the regulation of biological pathways demonstrated to be crucial for Rsv3-mediated resistance. / Doctor of Philosophy / Soybeans are a crop of great economic importance, being a primary source of oil and protein for human and livestock consumption, respectively. Increasing demand for soybean calls for improvement in its production. An emerging field that has had tremendous impact on this endeavor is the field of functional genomics. Functional genomics approaches generate large-scale biological data that can aid in discerning how specific processes are regulated and controlled in an organism. The research presented in this work utilizes functional genomics approaches to elucidate the biological mechanisms underlying two economically important traits in soybean: seed phytic acid content and Soybean mosaic virus resistance. Phytic acid is a compound found in soybean seeds that causes nutrient deficiencies and phosphorus pollution. Soybeans with reduced to phytic acid content have been developed to mitigate these problems; they have poor seed germination and emergence. The studies in this work employ functional genomics approaches to compare unique sets of low and normal phytic acid soybeans to help establish the relationship between seed phytic acid content and seed performance. These studies resulted in new and promising hypotheses for future studies on investigating the low phytic acid trait. The final focus of this work used a functional genomics approach to discern the molecular mechanisms underlying a unique mode of resistance to Soybean mosaic virus. The study identified genes in soybean that are potentially critical to resistance against Soybean mosaic virus.

La transcriptómica estudia el nivel de expresión de los genes en distintas condiciones experimentales para tratar de identificar los genes asociados a un fenotipo dado así como las relaciones de regulación entre distintos genes. Los datos ómicos se caracterizan por contener información de miles de variables en una muestra con pocas observaciones. Las tecnologías de alto rendimiento más comunes para medir el nivel de expresión de miles de genes simultáneamente son los microarrays y, más recientemente, la secuenciación de RNA (RNA-seq). Este trabajo de tesis versará sobre la evaluación, adaptación y desarrollo de modelos estadísticos para el análisis de datos de expresión génica, tanto si ha sido estimada mediante microarrays o bien con RNA-seq. El estudio se abordará con herramientas univariantes y multivariantes, así como con métodos tanto univariantes como multivariantes. / Tarazona Campos, S. (2014). Statistical methods for transcriptomics: From microarrays to RNA-seq [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48485 / Premios Extraordinarios de tesis doctorales

Thesis advisor: Marc-Jan Gubbels / Thesis advisor: Sarah McMenamin / Toxoplasma gondii, an obligate intracellular parasite, infects nearly one-third of the global population, causing the disease toxoplasmosis. Despite its significant health impact, the molecular mechanisms governing its lytic cycle and stress-induced adaptation remain incompletely understood. The unique asexual cell division mechanism, endodyogeny, used by T. gondii to expand its parasitic biomass in intermediate hosts, including humans, leads to severe pathological consequences through repeated rounds of the lytic cycle, resulting in acute toxoplasmosis. The parasite’s cell cycle is characterized by a prolonged G1 phase, with centrosome duplication marking the onset of the S phase, followed by a transient G2 phase and a near-simultaneous onset of mitosis and cytokinesis. These overlapping division processes, coupled with the challenges of synchronizing T. gondii, obscure the precise molecular mechanisms of its transcriptional programs. To address these challenges, we employed single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq), combined with advanced machine learning tools, to reveal ‘transition points’ in gene expression and chromatin accessibility that correspond to shifts in biological activity during the lytic cycle. RNA velocity and time-course clustering analyses uncovered a significant G1a transcriptional burst and identified specific AP2 family transcription factors (TFs) that peak during the C-to-G1a transition, likely driving this burst to regulate G1 progression. Further, we conducted an in-depth functional characterization of G1-specific TFs, focusing on AP2XII-8, which plays a critical role in activating a ribosome regulon to promote G1 progression. The study identified combinatorial binding motifs and suggested the existence of a large AP2XII-8 protein complex, involving other TFs and epigenetic factors, that reuglates the intricate processes of T. gondii cell cycle replication. Additionally, we examined stress-responsive AP2 TFs associated with enhanced virulence during in vitro evolution, providing insights into adaptive mechanisms that enable T. gondii to thrive under extracellular stress conditions. Collectively, these findings enhance our understanding of T. gondii’s complex regulatory networks, offering potential targets for therapeutic intervention against acute toxoplasmosis. This dissertation provides the time-resolved transcriptional and chromatin accessibility landscapes of T. gondii’s lytic cycle, resolves transcriptional programs to DNA motifs, and identifies key regulatory elements involved in its cell cycle progression and stress response. / Thesis (PhD) — Boston College, 2024. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

Big data and the revolution in sequencing technologies have transformed the way biomedical research is conducted. To unravel the underlying biological mechanisms of tumor development, treatment efficiency and to find new treatments for diseases such as cancer, it is necessary to use bioinformatic tools addressing the challenges posed by big data. This dissertation demonstrated how vast amounts of publicly available high-throughput sequencing data can be used to address open questions that relate to data-driven research. These include how genetic information can be used to assess therapeutic efficacy and drug repurposing, and how the analysis of tissue-specific transcriptional patterns can improve our understanding of the transcriptional repertoire of human genes. First study: This study investigates the prognostic and predictive value of TERT promoter mutations (TERTpm) and TERT expression in melanoma patients, particularly those undergoing immune checkpoint inhibition (ICI) therapy (anti-CTLA4 and anti-PD1/L1). Leveraging data from highly annotated melanoma cohorts, the study aims to evaluate how TERTpm and TERT expression influence tumor survival and immune response. Additionally, it seeks to address gaps in understanding the non-canonical roles of TERT in malignant melanoma by analyzing clinicopathological and demographic factors, as well as co-regulated gene expression, to provide deeper insights into its broader biological impact. Main findings first study: As comprehensive multivariate survival analyses were not available, the prognostic value of TERTpm and expression was tested in several melanoma ICI and non-ICI cohorts, including important clinical variables such as tumor mutational burden (TMB). However, the prognostic value for melanoma was not supported, as neither TERTpm nor TERT expression were associated with longer survival. As the proposed predictive value of TERTpm for anti-CTLA4 therapy was not statistically supported, we emphasize the inclusion of discussed biomarkers such as TMB in multivariate survival analysis. Incorporating immune signatures, TERT expression as a potential proxy for immune response was assessed. Although TERT expression was associated with elevated CD4+ T cells, its association with exhaustion markers suggests a dysfunctional T-cell response in TERT-high tumors. Defining phenotypic exhaustion in the CD4+ T-cells could be crucial to understanding missing immune responses in TERT-high tumors. TERT expression was increased in metastases arising from thinner primaries compared to metastases arising from thicker primaries. This raises the question of whether upregulation of TERT expression promotes early efficient metastasis, a function that may exist in addition to canonical telomerase activity. This was further supported by the enrichment of genes with upregulated TERT expression that are involved in extracellular matrix remodeling and thus would promote invasion of primary melanoma cells. Extending the non-canonical functions of TERT expression, its co-expression with DNA repair-genes, even across tumor types, hints toward a function of TERT in establishing genomic stability under stress in line with many previous studies. This could be useful in the context of chemotherapy and radiotherapy resistance of melanoma and also in other cancers such as glioblastoma, where in addition to TERTpm, TERT expression could also be measured to test for sensitivity to DNA damaging agents. This highlights the relevance of assessing TERT expression, besides the promoter mutation status. In summary, this study highlights the importance of across-cohort replication to re-evaluate potential biomarkers. While the extent of which TERT promoter mutations govern survival under anti-CTLA4 therapy was inconclusive, this study emphasizes the importance of a comprehensive multivariate analysis that accounts for confounding factors to identify robust biomarkers. Moreover, this data-driven analysis highlights the non-canonical functions of TERT expression, which are currently of great interest as it appears to contribute to early metastasis and the establishment of genomic stability. As our analysis revealed a potentially dysfunctional immune response in patients with high levels of TERT, it would be highly interesting to see whether the combination of currently tested TERT-based vaccines and immune checkpoint inhibition could achieve better results than ICI alone. Second study: This study aimed to identify potential drug candidates for tumors with DLST overexpression, which is linked to poor outcomes in triple-negative breast cancer and neuroblastoma and associated with the oxidative phosphorylation (OXPHOS) pathway. By integrating drug sensitivity data from over 250 drugs (GDSC project) and genomic data from over 800 cell lines (CCLE database), the research tested whether DLST amplification or elevated DLST mRNA levels make tumors more or less sensitive to OXPHOS inhibitors or other approved drugs, providing a foundation for targeted therapeutic strategies. Main results second study: Vulnerabilities of DLST-high tumors were identified for seven different drugs. Those drug candidates proposed could be subject to further rigorous tests using knock-out and knock-in experiments of cell lines, xenografts in animal models to evaluate their therapeutic potential for DLST-high tumors. DLST-activated cell lines were more sensitive to the BCL-2 inhibitor (obatoclax mesylate), a drug which has previously been shown to reduce OXPHOS in human leukemia stem cells. This was consistent with the hypothesis that some tumor cells may activate OXPHOS via DLST upregulation to ensure increased energy production. Several protein kinase inhibitors were identified, which hints toward a link between DLST and the extracellular signal-regulated kinases/mitogen-activated protein kinase (ERK/MAPK) signaling pathways. This was further supported by increased DLST expression in cell lines with driver mutations in KRAS and therefore serves as a starting point for understanding the role of ERK/MAPK inhibitors in DLST-activated cancer. I showed that using genomic information in conjunction with drug sensitivity data can provide drug candidates for drug repurposing. In a wider scope, these analyses could be transferred to analyses of other genes in association with drugs and hence, this study could serve as a prime example of how to approach questions of drug resistance in the presence of genetic changes. Third study: a browser-based application was developed to investigate tissue-specific transcript variability using deep-sequenced data from 927 human samples across 48 tissues. As the full picture of the human transcriptome is still incomplete, new non-canonical transcript variants and tissue-specificity may help to explain cellular mechanisms and may change the interpretation of disease-relevant mutations. We applied the webtool to the class of adhesion G protein-coupled receptors (aGPCRs), a class of receptors with a complex exon-intron structure. Main results third study: A vast transcript variety was identified by using deliberately relaxed parameters, with an average of 24 different transcript variants per all 33 aGPCR genes, where several of the priorly expressed variants had not yet been annotated. Therefore, future experimental planning should consider that the annotated aGPCR transcript variants may not be the dominant transcript variants. Adhesion GPCR transcript variants showed variable transcription starts and their complex exon-intron structures encoded for a flexible protein domain architecture of the N and C termini and the seven-helix transmembrane domain (7TMD). Of particular interest, we found that ADGRG7 has a transcript variant with an extra helix in the transmembrane domain. This was further supported by functional experiments using immunofluorescence studies and indirect cellular enzyme-linked immunosorbent assays, making it the first aGPCR with an eight-helix TMD. Tissue-specific expression patterns of transcript variants were observed, which may explain the phenotypic variation between tissues. This could also affect the assessment of disease-causing mutations as shown in the case of ADGRC1/CELSR1 where some transcript variants might not be affected by a specific mutation. Therefore querying other sets of genes in the application, where disease-causing mutations are described, may explain tissue-specific phenotypes. The development of the user-friendly browser-based application Splice-O-Mat, has demonstrated the feasibility of the analysis of tissue-specific transcriptomes. All accumulated data are presented in a browser-based application at: https://tools.hornlab.org/Splice-O-Mat/. Hence, this application serves as a starting point for in-depth analysis of genes, their splicing patterns and (alternative) promoter usage across human tissues. This dissertation highlights the importance of sequence analysis and bioinformatics in addressing clinically relevant questions in cancer, such as therapy efficacy and drug resistance. By leveraging publicly available data and large-scale analyses, it reduces biases from small datasets and uncovers key mechanistic insights. The development of a browser-based tool for tissue-specific splicing further advances understanding of protein diversity and genomic changes, emphasizing the critical role of big data in medical research.:Chapter I - Introduction 1 Big data in biomedicine 1 Challenges and potentials in data-driven biomedical research 4 Data-driven aspects of basic and translational cancer research 6 Clinical relevance of RNA and transcriptomics 8 Chapter II - Objectives 11 Chapter III - Publications 14 Publication 1: TERT expression is associated with metastasis from thin primaries, exhausted CD4+ T cells in melanoma and with DNA repair across cancer entities 14 Publication 2: Candidate drugs associated with sensitivity of cancer cell lines with DLST amplification or high mRNA levels 33 Publication 3: The repertoire and structure of adhesion GPCR transcript variants assembled from publicly available deep-sequenced human samples 42 Chapter IV - Summary 69 References 75 Supplementary Material 82 Supplementary material for “TERT expression is associated with metastasis from thin primaries, exhausted CD4+ T cells in melanoma and with DNA repair across cancer entities” 82 Supplementary material for “Candidate drugs associated with sensitivity of cancer cell lines with DLST amplification or high mRNA levels” 96 Supplementary material for “The repertoire and structure of adhesion GPCR transcript variants assembled from publicly available deep-sequenced human samples” 98 Spezifizierung des wissenschaftlichen Beitrags 108 Erklärung über die eigenständige Abfassung der Arbeit 111 Curriculum vitae 112 Publikationen und Präsentationen 114 Artikel 114 Präsentationen 115 Poster 115 Danksagungen 116