Doctor of Philosophy (PhD) / Gene expression is known to be regulated at the level of transcription. Recently, however, there has been a growing realisation of the importance of gene regulation at the post-transcriptional level, namely at the level of pre-mRNA processing (5’ capping, splicing and polyadenylation), nuclear export, mRNA localisation and translation. Erythroid krüppel-like factor (Eklf) is the founding member of the Krüppel-like factor (Klf) family of transcription factors and plays an important role in erythropoiesis. In addition to its nuclear presence, Eklf was recently found to localise to the cytoplasm and this observation prompted us to examine whether this protein has a role as an RNA-binding protein, in addition to its well-characterised DNA-binding function. In this thesis we demonstrate that Eklf displays RNA-binding activity in an in vitro and in vivo context through the use of its classical zinc finger (ZF) domains. Furthermore, using two independent in vitro assays, we show that Eklf has a preference for A and U RNA homoribopolymers. These results represent the first description of RNA-binding by a member of the Klf family. We developed a dominant negative mutant of Eklf by expressing its ZF region in murine erythroleukaemia (MEL) cells. We used this to investigate the importance of this protein in haematopoietic lineage decisions by examining its effect on the multipotent K562 cell line. We provide evidence that Eklf appears to be critical not only for the promotion of erythropoiesis, but also for the inhibition of megakaryopoiesis.

abstract: Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. To validate these approaches in a disease-specific context, we built a schizophreniaspecific network based on the inferred associations and performed a comprehensive prioritization of human genes with respect to the disease. These results are expected to be validated empirically, but computational validation using known targets are very positive. / Dissertation/Thesis / Ph.D. Computer Science 2011

abstract: Threshold logic has been studied by at least two independent group of researchers. One group of researchers studied threshold logic with the intention of building threshold logic circuits. The earliest research to this end was done in the 1960's. The major work at that time focused on studying mathematical properties of threshold logic as no efficient circuit implementations of threshold logic were available. Recently many post-CMOS (Complimentary Metal Oxide Semiconductor) technologies that implement threshold logic have been proposed along with efficient CMOS implementations. This has renewed the effort to develop efficient threshold logic design automation techniques. This work contributes to this ongoing effort. Another group studying threshold logic did so, because the building block of neural networks - the Perceptron, is identical to the threshold element implementing a threshold function. Neural networks are used for various purposes as data classifiers. This work contributes tangentially to this field by proposing new methods and techniques to study and analyze functions implemented by a Perceptron After completion of the Human Genome Project, it has become evident that most biological phenomenon is not caused by the action of single genes, but due to the complex interaction involving a system of genes. In recent times, the `systems approach' for the study of gene systems is gaining popularity. Many different theories from mathematics and computer science has been used for this purpose. Among the systems approaches, the Boolean logic gene model has emerged as the current most popular discrete gene model. This work proposes a new gene model based on threshold logic functions (which are a subset of Boolean logic functions). The biological relevance and utility of this model is argued illustrated by using it to model different in-vivo as well as in-silico gene systems. / Dissertation/Thesis / Ph.D. Computer Science 2012

Next-Generation Sequencing (NGS) technologies have been evolving at an unparalleled pace. The ability to generate millions of base pairs of data in a short time and at lower cost than previously has led to a dramatic expansion of technologies within the field. This dissertation discusses the development and validation of new methods for assessing genomic variation, dynamic changes in gene expression, high-accuracy sequencing, and analysis of recombination events. By reducing the cost of analyzing many samples for genetic divergence by genotyping the same region of the genome in multiple samples, researchers can pursue investigations on a larger scale. Next-RAD (Nextera fragmentation with Restriction-Associated Digestion) allows analysis of a uniform subset of loci between organisms for comparison of populations by genetic differences with reduced burdens of cost and data analysis. This method was applied to the Anopheles darlingi mosquito to identify three distinct species that were thought to be a uniform population. The lowering cost of large-scale sequencing investigations allows for massively parallel analysis of genomic function in a single assay. Regulation of gene expression in response to stress is a complex process which can only be understood by analyzing many pathways in tandem. A novel method is described which quantifies on a genome-wide scale the expression of millions of randomer tags driven by associated transcriptional enhancers. This method provides novel data in the form of high-resolution analysis of gene regulation. Aside from generating novel data types, another force behind development of new technologies is to improve data quality. One limitation of NGS is the inherent error rate. PELE-Seq (Paired End Low Error Sequencing) was developed to address this problem, by employing completely overlapping paired-end reads as well as a dual barcoding strategy to eliminate incorrect sequences resulting from final library amplification. This new tool improves data quality dramatically. Finally, the rapid expansion of tools necessitates the identification of new applications for these technologies. To this end, 10x Genomics Linked-Read sequencing was employed to identify recombination events in multiple species. The haplotype-resolved nature of the data generated from such assays has many promising applications.

abstract: A novel clustered regularly interspaced short palindromic repeats/CRISPR-associated (CRISPR/Cas) tool for simultaneous gene editing and regulation was designed and tested. This study used the CRISPR-associated protein 9 (Cas9) endonuclease in complex with a 14-nucleotide (nt) guide RNA (gRNA) to repress a gene of interest using the Krüppel associated box (KRAB) domain, while also performing a separate gene modification using a 20-nt gRNA targeted to a reporter vector. DNA Ligase IV (LIGIV) was chosen as the target for gene repression, given its role in nonhomologous end joining, a common DNA repair process that competes with the more precise homology-directed repair (HDR). To test for gene editing, a 20-nt gRNA was designed to target a disrupted enhanced green fluorescent protein (EGFP) gene present in a reporter vector. After the gRNA introduced a double-stranded break, cells attempted to repair the cut site via HDR using a DNA template within the reporter vector. In the event of successful gene editing, the EGFP sequence was restored to a functional state and green fluorescence was detectable by flow cytometry. To achieve gene repression, a 14-nt gRNA was designed to target LIGIV. The gRNA included a com protein recruitment domain, which recruited a Com-KRAB fusion protein to facilitate gene repression via chromatin modification of LIGIV. Quantitative polymerase chain reaction was used to quantify repression. This study expanded upon earlier advancements, offering a novel and versatile approach to genetic modification and transcriptional regulation using CRISPR/Cas9. The overall results show that both gene editing and repression were occurring, thereby providing support for a novel CRISPR/Cas system capable of simultaneous gene modification and regulation. Such a system may enhance the genome engineering capabilities of researchers, benefit disease research, and improve the precision with which gene editing is performed. / Dissertation/Thesis / Masters Thesis Molecular and Cellular Biology 2018

No description available.

The discovery of the non-coding RNA (ncRNA) has been primarily focused on the genomes of eukaryotes and pathogenic bacteria. In vibrios, all that is known up to now regarding ncRNAs involves V. cholerae N16961 e V. campbellii ATCC BAA-1116. In this study, ncRNA candidate genes were identified in the genomes of V. campbellii ATCC BAA-1116, V. alginolyticus 40B, V. communis 1DA3 e V. mimicus VM573. V. alginolyticus 40B and V. campbellii ATCC BAA-1116 are abundant in brazilian corals, whereas V. mimicus VM573 is a toxic strain (carrying the Vibrio pathogenicity island) atypical to this species. In order to identify the ncRNAs in silico, the tools Infernal and Rfam database were used. Perl programs were developed in the present work. The Infernal tool and the Rfam database are based on the Covariance Model (CM), a special case of Stochastic Context Free Grammars (SCFG). Up to 38 ncRNAs were identified per species. They were classified into seven classes according to their regulatory function and/or structural (1. riboswitches, 2. modulators of protein activity, 3. RNA's antisensus of trans action, 4. RNA's antisensus of cis action, 5. ribonucleoproteins, 6. regulation by transcription termination and 7. unknown classification). The most abundant group was the riboswitch, whereas the less abundant group was the ribonucleoprotein. This work demonstrated that the ncRNAs show a great diversity in functional classes, possibly associated with the regulation of different cellular processes in vibrios, including regulation of pathogenicity. / A descoberta de RNA não-codificante (ncRNA) tem focado principalmente nos genomas de eucariontes e de bactérias patogênicas. Em vibrios, o que se conhece até o momento sobre ncRNAs envolve V. cholerae N16961 e V. campbellii ATCC BAA-1116. Neste estudo, são identificados genes candidatos de ncRNAs no genoma de V. campbellii ATCC BAA-1116, V. alginolyticus 40B, V. communis 1DA3 e V. mimicus VM573. V. alginolyticus 40B e V. campbellii ATCC BAA-1116 são abundantes em corais brasileiros, enquanto que V. mimicus VM573 é uma linhagem toxigênica (CT e TCP positiva) atípica desta espécie. Para identificar os ncRNAs através de análise in silico foram utilizadas ferramentas já disponíveis (Infernal e a base de dados Rfam) e programas em Perl desenvolvidos no presente trabalho. A ferramenta Infernal e a base de dados Rfam são baseados em modelo de covariância (CM), um caso especial de gramáticas estocásticas livres de contexto (SCFG). Foram identificados até 38 ncRNAs por espécie, os quais foram classificados em sete classes de acordo com sua função regulatória e /ou estrutural (riboswitches, moduladores da atividade de proteínas, RNAs antisenso de ação trans, RNAs antisenso de ação cis, ribonucleoproteinas, regulação por término de transcrição e classificação desconhecida). O grupo mais abundante foi o riboswitch, enquanto que o grupo menos abundante foi o ribonucleoproteina. Este trabalho demonstrou que os ncRNAs apresentam uma ampla diversidade de classes funcionais, estando possivelmente associados com a regulação de diferentes processos celulares em vibrio, incluindo a regulação da patogenicidade.

Orientador: Robson Francisco Carvalho / Resumo: A caquexia associada ao câncer é uma síndrome caracterizada pela grave perda de tecido musculo esquelético; que se estima que afeta mais de 50% de todos os pacientes com câncer e resulta em menor qualidade de vida devido a fadiga, fraqueza, redução da função imune, resistência à insulina e baixa tolerância e resposta à quimioterapia. Notavelmente, 20% das mortes relacionadas ao câncer são diretamente causadas pela caquexia. A principal limitação de que atualmente não há terapia direcionada, é o uso de abordagens tradicionais que não tratam a complexidade em sistemas biológicos, caracterizada por interações não-lineares de redes de regulação genética (GRN, do inglês Gene Regulatory Networks). Por esse motivo, ainda é necessária uma identificação dos componentes da GRN e uma compreensão quantitativa de sua integração temporal no controle das respostas celulares. Adquirir tal conhecimento é fundamental para capturar detalhes mecanicistas essenciais para direcionar estratégias terapêuticas para uma doença complexa, como a caquexia do câncer. Neste trabalho, examinamos a expressão genética do músculo esquelético em dois abordagens metodológicos diferentes: usando dados de expressão de genes estáticos e dinâmicos. Estruturamos nosso trabalho da seguinte maneira: o Capítulo 1 apresenta uma caracterização quantitativa das vias de sinalização e uma reconstrução de GRN no tecido musculo esquelético em ratos portadores de carcinoma de pulmão de Lewis (LLC, do inglês Lewis lung carcinoma... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Cancer cachexia is a syndrome characterized by the severe skeletal muscle wasting tissue; that affects more than 50% of all cancer patients and results in lower quality of life due to compromised fatigue, weakness, decreased immune function, insulin resistance and poor tolerance and response to radio and chemotherapy. Remarkably, approximately 20% of cancer-related deaths are estimated to be directly caused by cachexia. There is currently no effective targeted therapy and the main limitation lays on the traditional approaches that not deal with the inherent complexity, characterized by non-linear interactions, of gene regulatory networks (GRN). Thus, a clear identification of the components of gene regulation, and a quantitative understanding of their temporal integration to control cellular responses is fundamental for capture essential mechanistic details that will ultimately enable the development of direct therapeutic strategies for the treatment of cancer cachexia. Here, we examine genome-wide gene expression of muscle wasting under two different frameworks, using static and dynamic gene expression data. We structure this approach as follow: Chapter 1 presents a quantitative characterization of the signaling pathways and a GRN reconstruction of muscle wasting in Lewis Lung Carcinoma (LLC) tumor-bearing mice by integrating static mRNAs and microRNAs expression profiles. The results show that LLC mice reduced body weight in 20% and presented muscle and fat tissue wasting a... (Complete abstract click electronic access below) / Doutor

Nesta tese, mostramos que o modelo estocástico binário para expressão gênica, por um gene auto-regulado, possui solução completa. A solução dependente do tempo é escrita via expansão em termos das funções de Heun confluentes. Apresentamos um exemplo de dinâmica estocástica desse gene. Para tal, desenvolvemos uma relação de recorrência entre derivadas arbitrárias das funções de Heun confluentes. Mostramos também que o regime estacionário deste modelo possui simetria de Lie SO(2, 1) tipo Lorentz. Esta simetria é análoga à simetria do momento angular, porém com um sinal errado. O invariante desta álgebra define a meia-vida relativa do regime dinâmico do gene. O equivalente do momento angular azimutal é uma medida indireta do nível de atividade do gene. Os operadores levantamento e abaixamento conectam diferentes processos estocásticos de expressão proteínica. As flutuações destes processos estocásticos são classificadas em termos das relações entre os etiquetadores de um elemento da representação da álgebra. No arcabouço da teoria dos grupos, o modelo estocástico para um gene externamente regulado aparece como um caso particular do modelo para um gene auto-regulado. Mostramos, por fim, uma comparação entre estas duas estratégias de regulação. Demonstramos que um gene auto-regulado pode expressar proteínas em regimes sub Poisson, Poisson ou super Poisson. Por seu turno, o gene externamente regulado somente expressa proteínas em regimes Poisson ou super Poisson. Portanto, num processo estocástico, a auto-regulação mostra-se como uma forma de controle mais precisa. Também mostramos que a dinâmica de genes auto-regulados possui meia-vida mais curta que a de genes externamente regulados. Ou seja, a auto-regulação permite respostas mais rápidas à perturbações externas. / In this thesis we show that the stochastic binary model to protein synthesis by na auto-regulated gene is completely solvable. The time-dependent solution is written in terms of the confluent Heun functions. We present an example of probability dynamics to this gene. To get that, we developed a recurrence relation between arbitrary derivatives of the confluent Heun functions. We also show the existence of a Lorentz-like Lie symmetry SO(2, 1). This is an analogous to the angular momentum symmetry but presenting one wrong sign in its preserved form. This invariant defines the relative half-life of the dynamical regime of the gene. The equivalent of the azimuth angular momentum measures indirectly the activity level of the gene. The ladder operators connect distinct stochastic processes of protein synthesis. The fluctuations of these processes are classified in terms of the relation between labeling numbers of a representation of the algebra. In the group theory formalism, the stochastic model to an externally regulated gene is a particular case of the model to an auto-regulated gene. We compare these two gene regulation strategies, and show that the auto-regulated gene can synthesize proteins into the super Poisson, Poisson, and sub Poisson fluctuating regimes. The externally regulated gene only presents the super Poisson and Poisson regimes. Therefore, the auto-regulation is responsible for a more precise control of gene expression. We also show that the dynamics of the auto-regulated genes has a shorter half-life. Thus, the auto-regulation permits faster responses of the system to external perturbation.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2017-02-14T12:46:20Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_Danielli Batista Bezerra Cajueiro.pdf: 1520169 bytes, checksum: 01f947c81a685b7a391d5c6dbfcf83bd (MD5) / Made available in DSpace on 2017-02-14T12:46:20Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_Danielli Batista Bezerra Cajueiro.pdf: 1520169 bytes, checksum: 01f947c81a685b7a391d5c6dbfcf83bd (MD5) Previous issue date: 2015-06-12 / CAPES / As fontes de nitrogênio do meio são classificadas como preferenciais e nãopreferenciais, de maneira que as primeiras inibem a expressão dos genes responsáveis pela metabolização das segundas por um mecanismo chamado de Repressão Catabólica do Nitrogênio (Nitrogen Catabolic Repression - NCR). No presente estudo avaliamos o padrão de regulação dos genes do metabolismo central do nitrogênio na levedura Dekkera bruxellensis. Foram definidos quatro grupos de fontes de nitrogênio baseados no crescimento celular. Em seguida, o padrão de expressão dos genes do metabolismo central do nitrogênio mostrou que fenilalanina, embora do grupo quatro, é o maior indutor das permeases Gap1p e Put4p, resultando em sua elevada taxa de consumo. Já a histidina, indutora da permease Put4p, promove maior indução dos genes que codificam as enzimas de assimilação de amônia. Quando o mecanismo NCR é inibido pela presença de metionina sulfoximina no meio, ocorre a desrrepressão dos genes que codificam as permeases. E finalmente, os resultados mostram que nitrato, definido no grupo dois induz o mecanismo de sinalização intracelular de regulação gênica semelhante ao que se observa quando as células estão no estado de privação de nitrogênio no meio. Isto complementa os estudos anteriores nos quais mostramos que a assimilação de nitrato altera o estado fisiológico da célula para respiração mesmo na presença de alta concentração de glicose no meio. / The nitrogen sources in the medium are classified as preferential or non-preferrential, so that the first inhibit expression of genes responsible for metabolism of the latter by a mechanism called Nitrogen Catabolic Repression (NCR). In the present study we evaluated the pattern of gene regulation of the central nitrogen metabolism in yeast Dekkera bruxellensis. It was defined four groups of nitrogen sources based on cell growth. Then, the expression pattern of the central nitrogen metabolism genes showed that phenylalanine, though belonging to group four, is the biggest inducer of genes of permeases Gap1p Put4p, resulting in its high consumption rate. Moreover, histidine induces the gene encoding permease Put4p and promoted the highest induction of the genes encoding the enzymes of ammonia assimilation. When the NCR mechanism was inhibited by the presence of methionine sulfoximine in the medium there was derepression of the genes encoding for permeases. Finally, the results showed that nitrate, defined in the group two, induced the intracellular signaling pathway gene regulation similar to that seen when cells are in a state of nitrogen deprivation in the middle. This complements our previous studies that showed that the nitrate assimilation alter the physiological state of the cell to respiration even in presence of high glucose concentration in medium.