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RNA (Ribonuceic Acid) sequencing technology is a powerful technology used to give re- searchers essential information about the functionality of genes. The transcriptomic study and downstream analysis highlight the functioning of the genes associated with a specific biological process/treatment. In practice, differentially expressed genes associated with a particular treatment or genotype are subjected to downstream analysis to find some critical set of genes. This critical set of genes/ genes pathways infers the effect of the treatment in a cell or tissue. This disserta- tion describes the multiple stages framework of finding these critical sets of genes using different analysis methodologies and inference algorithms. RNA sequencing technology helps to find the differentially expressed genes associated with the treatments and genotypes. The preliminary step of RNA-seq analysis consists of extracting the mRNA(messenger RNA) followed by mRNA libraries’ preparation and sequencing using the Illumina HiSeq 2000 platform. The later stage analysis starts with mapping the RNA sequencing data (obtained from the previous step) to the genome annotations and counting each annotated gene’s reads to produce the gene expression data. The second step involves using the statistical method such as linear model fit, clustering, and probabilistic graphical modeling to analyze genes and gene networks’ role in treatment responses. In this dissertation, an R software package is developed that compiles all the RNA sequencing steps and the downstream analysis using the R software and Linux environment. Inference methodology based on loopy belief propagation is conducted on the gene networks to infer the differential expression of the gene in the further step. The loopy belief propagation algorithm uses a computational modeling framework that takes the gene expression data and the transcriptional Factor interacting with the genes. The inference method starts with constructing a gene-Transcriptional Factor network. The construction of the network uses an undirected proba- bilistic graphical modeling approach. Later the belief message is propagated across all the nodes of the graphs. The analysis and inference methods explained in the dissertation were applied to the Arabidopsis plant with two different genotypes subjected to two different stress treatments. The results for the analysis and inference methods are reported in the dissertation.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第23572号 / 医博第4786号 / 新制||医||1054(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 妹尾 浩, 教授 武藤 学, 教授 小川 誠司 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Single-cell RNA-sequencing (scRNA-seq) technology enables researchers to investigate a genome at the cellular level with unprecedented resolution. An organism consists of a heterogeneous collection of cell types, each of which plays a distinct role in various biological processes. Hence, the first step of scRNA-seq data analysis often is to distinguish cell types so that they can be investigated separately. Researchers have recently developed several automated cell type annotation tools based on supervised machine learning algorithms, requiring neither biological knowledge nor subjective human decisions. Dropout is a crucial characteristic of scRNA-seq data which is widely utilized in differential expression analysis but not by existing cell annotation methods. We present scAnnotate, a cell annotation tool that fully utilizes dropout information. We model every gene’s marginal distribution using a mixture model, which describes both the dropout proportion and the distribution of the non-dropout expression levels. Then, using an ensemble machine learning approach, we combine the mixture models of all genes into a single model for cell-type annotation. This combining approach can avoid estimating numerous parameters in the high-dimensional joint distribution of all genes. Using fourteen real scRNA-seq datasets, we demonstrate that scAnnotate is competitive against nine existing annotation methods, and that it accurately annotates cells when training and test data are (1) similar, (2) cross-platform, and (3) cross-species. Of the cells that are incorrectly annotated by scAnnotate, we find that a majority are different from those of other methods. / Graduate / 2023-07-27

No description available.

Yes / Functional genomics research can give us valuable insights into bacterial gene function. RNA Sequencing (RNA-seq) can generate information on transcript abundance in bacteria following abiotic stress treatments. In this study, we used the RNA-seq technique to study the transcriptomes of the opportunistic nosocomial pathogen Pseudomonas aeruginosa PAO1 following heat shock. Samples were grown at both the human body temperature (37 C) and an arbitrarily-selected temperature of 46 C. In this work using RNA-seq, we identified 133 genes that are differentially expressed at 46 C compared to the human body temperature. Our work identifies some key P. aeruginosa PAO1 genes whose products have importance in both environmental adaptation as well as in vivo infection in febrile hosts. More importantly, our transcriptomic results show that many genes are only expressed when subjected to heat shock. Because the RNA-seq can generate high throughput gene expression profiles, our work reveals many unanticipated genes with further work to be done exploring such genes products. / University of Malaya High Impact Research (HIR) UM-MOHE HIR Grants (UM.C/625/1/HIR/MOHE/CHAN/14/1, No. H-50001-A000027; UM.C/625/1/HIR/MOHE/CHAN/01, No. A000001-50001); PPP Grant (PG081-2015B)

Yes / Maintenance of skeletal muscle mass and function is critical to health and wellbeing throughout the lifespan. However, disuse through reduced physical activity (e.g., sedentarism), immobilisation, bed rest or microgravity has significant adverse effects on skeletal muscle health. Conversely, resistance exercise training (RET) induces positive muscle mass and strength adaptations. Several studies have employed microarray technology to understand the transcriptional basis of muscle atrophy and hypertrophy after disuse and RET, respectively, to devise fully effective therapeutic interventions. More recently, rapidly falling costs have seen RNA-sequencing (RNA-seq) increasingly applied in exploring muscle adaptations to RET and disuse. The aim of this review is to summarise the transcriptional responses to RET or disuse measured via RNA-seq in young and older adults. We also highlight analytical considerations to maximise the utility of RNA-seq in the context of skeletal muscle research. The limited number of muscle transcriptional signatures obtained thus far with RNA-seq are generally consistent with those obtained with microarrays. However, RNA-seq may provide additional molecular insight, particularly when combined with data-driven approaches such as correlation network analyses. In this context, it is essential to consider the most appropriate study design parameters as well as bioinformatic and statistical approaches. This will facilitate the use of RNA-seq to better understand the transcriptional regulators of skeletal muscle plasticity in response to increased or decreased use.

Aedes aegypti is the primary vector for dengue, zika, chikungunya, and yellow fever viruses. Disease transmission through this mosquito places over 40% of the world's population at risk of contracting one or more of these pathogens. Current control strategies such as insecticide application have failed or carry additional burdens, such as off-target toxicity to mammals and birds. Our lab proposes utilizing a conserved arthropod hormone pathway, juvenile hormone (JH), related to growth and reproduction to curb these vector populations and reduce disease transmission. Additionally, JH is nontoxic to birds and mammals; it requires incredibly high doses to have lethal effects. We hypothesize that JH-responsive genes expressed early in the adult are responsible for her reproductive capacity and by manipulating the signaling downstream of the receptor, we will be able to decrease the female's fecundity and limit vector populations. Via bioinformatics screening of RNA-sequencing data using the New Tuxedo pipeline, we identified 47 potential transcription factor candidates. With the use of in vitro culturing of the mosquito's reproductive tissues in the presence of a translation inhibitor, we identified two early JH responsive gene candidates, FoxA and zinc finger 519, p-value <0.05. The functional characterization of these two remains to be seen, however, in Drosophila melanogaster, they both have roles in chromatin remodeling and require protein partners to carry out long range interactions. / Master of Science in Life Sciences / The mosquito, Aedes aegypti, is responsible for the spread of a myriad of viruses such as dengue, zika, and chikungunya. Currently, these infections have no vaccine or treatment available and transmission rates continue to steeply rise in response to the spread of breeding grounds. Popular insecticides carry detriments such as off-species toxicity and continuous application to treatment areas. Our lab proposes an alternative to these chemical insecticides by manipulating a developmental pathway in the mosquito. The Juvenile Hormone pathway is conserved in arthropods, responsible for growth and reproduction, and the hormone is nontoxic to mammals. Through the combination of bioinformatics and genomics studies, we have identified two JH-responsive gene candidates that are potential regulators of this pathway.

Clostridium perfringens is a Gram-positive (Gr+) anaerobic pathogen that was found to contain Type IV pilus (T4P) system genes within the genomes of all its sequenced strains. T4P are widely used in Gram-negative organisms for aggregation, biofilm formation, adherence, and DNA uptake. Because few examples of T4P-utilizing Gram-positive bacteria are studied to date, we wanted to characterize the T4P system in this Gr+ bacterium. To understand the regulation of T4P genes and therefore better understand their expression, we employed the highly powerful next-generation sequencing tool RNA-seq in a variety of conditions. RNA-seq uncovered previously unknown regulatory mechanisms surrounding T4P genes as well as provided transcriptional information for most of the genes in the C. perfringens strain 13 genome. We also utilized reporter gene assays to look at post-transcriptional regulation of T4P promoters. The wealth of RNA-seq data acted as a jumping-off point for many smaller projects involving transcriptional regulators that may influence T4P expression. We investigated a novel small RNA in close proximity to the major T4P operon, as well as two little-characterized transcriptional regulators that function in the same conditions as T4P genes. RNA-seq also provided data to develop a method for protein purification from C. perfringens without induction. / Master of Science

Les longs ARN non codants (lncRNAs) sont définis comme des transcrits de plus de 200nt et n'ayant pas de potentiel codant. Des études récentes ont démontré que les lncRNAs pouvaient être impliqués dans la régulation de la transcription, de la traduction, de la différenciation cellulaire, de l'expression génique, du cycle cellulaire et des modifications de la chromatine. De plus, il a été montré un impact fonctionnel de certains lncRNAs dans le processus de cancérogenèse mais nos connaissances actuelles sur ces molécules dans le cancer, et plus particulièrement dans la leucémie, restent extrêmement limitées. Au cours de cette étude, nous avons analysé l'expression des lncRNAs par RNA-sequencing sur 40 patients atteints de leucémie aiguë myéloblastique (LAM) à caryotype normal. Parmi les 11065 lncRNAs exprimés dans nos échantillons, nous avons identifié une signature de lncRNAs associée à la mutation de NPM1. Afin de mettre en évidence les fonctions putatives des lncRNAs sélectionnés, nous avons utilisé un algorithme de prédiction d'interaction protéine/ARN. De manière intéressante, plus de la moitié des lncRNAs présentent des sites d'interactions potentiels à SUZ12, une sous unité du complexe PRC2 (Polycomb repressive complex 2), connu pour être recruté par des lncRNAs pour la régulation épigénétique de gènes cibles. Par RNA immunoprécipitation (RIP) de SUZ12, nous avons pu démontrer que le lncRNA XLOC_087120 interagissait avec SUZ12. De plus, son expression est anti-corrélée avec celle des gènes voisins codants des histones, suggérant un rôle dans la régulation négative des histones par ce lncRNA. L'impact de la dérégulation de XLOC_087120 sur les histones a été confirmé par des expériences de surexpression et d'inhibition de ce lncRNA dans des lignées de LAM. De plus, même si la mutation NPM1 ne semble pas affecter directement l'expression de ce lncRNA, des expériences d'infection de la forme mutée de NPM1 dans une lignée LAM ont montré que NPM1 pourrait réguler la localisation nucléaire/cytoplasmique de XLOC_087120 et moduler sa fonction de répresseur. En conclusion, ces données suggèrent que les lncRNAs sont des facteurs clés dans la pathogenèse des LAMs. / Long noncoding RNAs (lncRNAs) are defined as RNA transcripts that are larger than 200 nt but do not appear to have protein- coding potential. Recent studies have demonstrated that lncRNAs regulate many processes such as transcription, translation, cellular differentiation, gene expression regulation, cell cycle regulation, and chromatin modification. Cumulative evidence points towards an important role of lncRNAs in cancer initiation, development, and progression. However, our overall knowledge of lncRNAs in cancer, including leukemia, remains extremely limited. In this study, we investigated lncRNA expression by RNA-sequencing in 40 acute myeloid leukemia (AML) patients with normal karyotype. Among 11065 lncRNA expressed in our samples, we identified specific lncRNA signature associated with the presence of NPM1 mutation. To go further into the putative function of these lncRNAs, we used catRAPID Omics algorithm to predict potential protein partners. Interestingly, the majority of the selected lncRNAs contains putative SUZ12 binding sites, a PRC2 (Polycomb Repressive Complex 2) component known to be linked to lncRNAs and to epigenetically regulates target genes. By using SUZ12 RNA Immunoprecipitation, we identify one lncRNA named XLOC_087120 linked to SUZ12. XLOC_087120 is located in a region enriched in histone genes. Pearson correlation showed a significative anti-correlation between XLOC_087120 and histone neighboring coding gene expression suggesting a role of this lncRNA in the regulation of histone genes. The impact on histone genes expression was confirmed by overexpression and inhibition of XLOC_087120 in AML cell lines. Overexpression of NPM1 mutant in an AML cell line showed that NPM1 modulates the nuclear/cytoplasmic localization of XLOC_087120 and consequently its repressive function. Altogether, these data suggest that lncRNAs should be considered as key players in the pathogenesis of acute myeloid leukemias.