917 resultados para RNA-seq data
Resumo:
Cryptococcus neoformans is a pathogenic basidiomycetous yeast responsible for more than 600,000 deaths each year. It occurs as two serotypes (A and D) representing two varieties (i.e. grubii and neoformans, respectively). Here, we sequenced the genome and performed an RNA-Seq-based analysis of the C. neoformans var. grubii transcriptome structure. We determined the chromosomal locations, analyzed the sequence/structural features of the centromeres, and identified origins of replication. The genome was annotated based on automated and manual curation. More than 40,000 introns populating more than 99% of the expressed genes were identified. Although most of these introns are located in the coding DNA sequences (CDS), over 2,000 introns in the untranslated regions (UTRs) were also identified. Poly(A)-containing reads were employed to locate the polyadenylation sites of more than 80% of the genes. Examination of the sequences around these sites revealed a new poly(A)-site-associated motif (AUGHAH). In addition, 1,197 miscRNAs were identified. These miscRNAs can be spliced and/or polyadenylated, but do not appear to have obvious coding capacities. Finally, this genome sequence enabled a comparative analysis of strain H99 variants obtained after laboratory passage. The spectrum of mutations identified provides insights into the genetics underlying the micro-evolution of a laboratory strain, and identifies mutations involved in stress responses, mating efficiency, and virulence.
Resumo:
Current measures of global gene expression analyses, such as correlation and mutual information-based approaches, largely depend on the degree of association between mRNA levels and to a lesser extent on variability. I develop and implement a new approach, called the Ratiometric method, which is based on the coefficient of variation of the expression ratio of two genes, relying more on variation than previous methods. The advantage of such modus operandi is the ability to detect possible gene pair interactions regardless of the degree of expression dispersion across the sample group. Gene pairs with low expression dispersion, i.e., their absolute expressions remain constant across the sample group, are systematically missed by correlation and mutual information analyses. The superiority of the Ratiometric method in finding these gene pair interactions is demonstrated in a data set of RNA-seq B-cell samples from the 1000 Genomes Project Consortium. The Ratiometric method renders a more comprehensive recovery of KEGG pathways and GO-terms.
Resumo:
Extensive departures from balanced gene dose in aneuploids are highly deleterious. However, we know very little about the relationship between gene copy number and expression in aneuploid cells. We determined copy number and transcript abundance (expression) genome-wide in Drosophila S2 cells by DNA-Seq and RNA-Seq. We found that S2 cells are aneuploid for >43 Mb of the genome, primarily in the range of one to five copies, and show a male genotype ( approximately two X chromosomes and four sets of autosomes, or 2X;4A). Both X chromosomes and autosomes showed expression dosage compensation. X chromosome expression was elevated in a fixed-fold manner regardless of actual gene dose. In engineering terms, the system "anticipates" the perturbation caused by X dose, rather than responding to an error caused by the perturbation. This feed-forward regulation resulted in precise dosage compensation only when X dose was half of the autosome dose. Insufficient compensation occurred at lower X chromosome dose and excessive expression occurred at higher doses. RNAi knockdown of the Male Specific Lethal complex abolished feed-forward regulation. Both autosome and X chromosome genes show Male Specific Lethal-independent compensation that fits a first order dose-response curve. Our data indicate that expression dosage compensation dampens the effect of altered DNA copy number genome-wide. For the X chromosome, compensation includes fixed and dose-dependent components.
Resumo:
Cryptococcus neoformans is a pathogenic basidiomycetous yeast responsible for more than 600,000 deaths each year. It occurs as two serotypes (A and D) representing two varieties (i.e. grubii and neoformans, respectively). Here, we sequenced the genome and performed an RNA-Seq-based analysis of the C. neoformans var. grubii transcriptome structure. We determined the chromosomal locations, analyzed the sequence/structural features of the centromeres, and identified origins of replication. The genome was annotated based on automated and manual curation. More than 40,000 introns populating more than 99% of the expressed genes were identified. Although most of these introns are located in the coding DNA sequences (CDS), over 2,000 introns in the untranslated regions (UTRs) were also identified. Poly(A)-containing reads were employed to locate the polyadenylation sites of more than 80% of the genes. Examination of the sequences around these sites revealed a new poly(A)-site-associated motif (AUGHAH). In addition, 1,197 miscRNAs were identified. These miscRNAs can be spliced and/or polyadenylated, but do not appear to have obvious coding capacities. Finally, this genome sequence enabled a comparative analysis of strain H99 variants obtained after laboratory passage. The spectrum of mutations identified provides insights into the genetics underlying the micro-evolution of a laboratory strain, and identifies mutations involved in stress responses, mating efficiency, and virulence.
Resumo:
Transcriptional regulation has been studied intensively in recent decades. One important aspect of this regulation is the interaction between regulatory proteins, such as transcription factors (TF) and nucleosomes, and the genome. Different high-throughput techniques have been invented to map these interactions genome-wide, including ChIP-based methods (ChIP-chip, ChIP-seq, etc.), nuclease digestion methods (DNase-seq, MNase-seq, etc.), and others. However, a single experimental technique often only provides partial and noisy information about the whole picture of protein-DNA interactions. Therefore, the overarching goal of this dissertation is to provide computational developments for jointly modeling different experimental datasets to achieve a holistic inference on the protein-DNA interaction landscape.
We first present a computational framework that can incorporate the protein binding information in MNase-seq data into a thermodynamic model of protein-DNA interaction. We use a correlation-based objective function to model the MNase-seq data and a Markov chain Monte Carlo method to maximize the function. Our results show that the inferred protein-DNA interaction landscape is concordant with the MNase-seq data and provides a mechanistic explanation for the experimentally collected MNase-seq fragments. Our framework is flexible and can easily incorporate other data sources. To demonstrate this flexibility, we use prior distributions to integrate experimentally measured protein concentrations.
We also study the ability of DNase-seq data to position nucleosomes. Traditionally, DNase-seq has only been widely used to identify DNase hypersensitive sites, which tend to be open chromatin regulatory regions devoid of nucleosomes. We reveal for the first time that DNase-seq datasets also contain substantial information about nucleosome translational positioning, and that existing DNase-seq data can be used to infer nucleosome positions with high accuracy. We develop a Bayes-factor-based nucleosome scoring method to position nucleosomes using DNase-seq data. Our approach utilizes several effective strategies to extract nucleosome positioning signals from the noisy DNase-seq data, including jointly modeling data points across the nucleosome body and explicitly modeling the quadratic and oscillatory DNase I digestion pattern on nucleosomes. We show that our DNase-seq-based nucleosome map is highly consistent with previous high-resolution maps. We also show that the oscillatory DNase I digestion pattern is useful in revealing the nucleosome rotational context around TF binding sites.
Finally, we present a state-space model (SSM) for jointly modeling different kinds of genomic data to provide an accurate view of the protein-DNA interaction landscape. We also provide an efficient expectation-maximization algorithm to learn model parameters from data. We first show in simulation studies that the SSM can effectively recover underlying true protein binding configurations. We then apply the SSM to model real genomic data (both DNase-seq and MNase-seq data). Through incrementally increasing the types of genomic data in the SSM, we show that different data types can contribute complementary information for the inference of protein binding landscape and that the most accurate inference comes from modeling all available datasets.
This dissertation provides a foundation for future research by taking a step toward the genome-wide inference of protein-DNA interaction landscape through data integration.
Resumo:
Despite the ecological importance of copepods, few Next Generation Sequencing studies (NGS) have been performed on small crustaceans, and a standard method for RNA extraction is lacking. In this study, we compared three commonly-used methods: TRIzol®, Aurum Total RNA Mini Kit and Qiagen RNeasy Micro Kit, in combination with preservation reagents TRIzol® or RNAlater®, to obtain high-quality and quantity of RNA from copepods for NGS. Total RNA was extracted from the copepods Calanus helgolandicus, Centropages typicus and Temora stylifera and its quantity and quality were evaluated using NanoDrop, agarose gel electrophoresis and Agilent Bioanalyzer. Our results demonstrate that preservation of copepods in RNAlater® and extraction with Qiagen RNeasy Micro Kit were the optimal isolation method for high-quality and quantity of RNA for NGS studies of C. helgolandicus. Intriguingly, C. helgolandicus 28S rRNA is formed by two subunits that separate after heat-denaturation and migrate along with 18S rRNA. This unique property of protostome RNA has never been reported in copepods. Overall, our comparative study on RNA extraction protocols will help increase gene expression studies on copepods using high-throughput applications, such as RNA-Seq and microarrays.
Resumo:
Genetic risk factors for chronic kidney disease (CKD) are being identified through international collaborations. By comparison, epigenetic risk factors for CKD have only recently been considered using population-based approaches. DNA methylation is a major epigenetic modification that is associated with complex diseases, so we investigated methylome-wide loci for association with CKD. A total of 485,577 unique features were evaluated in 255 individuals with CKD (cases) and 152 individuals without evidence of renal disease (controls). Following stringent quality control, raw data were quantile normalized and β values calculated to reflect the methylation status at each site. The difference in methylation status was evaluated between cases and controls with resultant P values adjusted for multiple testing. Genes with significantly increased and decreased levels of DNA methylation were considered for biological relevance by functional enrichment analysis using KEGG pathways in Partek Genomics Suite. Twenty-three genes, where more than one CpG per loci was identified with Padjusted < 10−8, demonstrated significant methylation changes associated with CKD and additional support for these associated loci was sought from published literature. Strong biological candidates for CKD that showed statistically significant differential methylation include CUX1, ELMO1, FKBP5, INHBA-AS1, PTPRN2, and PRKAG2 genes; several genes are differentially methylated in kidney tissue and RNA-seq supports a functional role for differential methylation in ELMO1 and PRKAG2 genes. This study reports the largest, most comprehensive, genome-wide quantitative evaluation of DNA methylation for association with CKD. Evidence confirming methylation sites influence development of CKD would stimulate research to identify epigenetic therapies that might be clinically useful for CKD.
Resumo:
Patterns of glycosylation are important in cancer, but the molecular mechanisms that drive changes are often poorly understood. The androgen receptor drives prostate cancer (PCa) development and progression to lethal metastatic castration-resistant disease. Here we used RNA-Seq coupled with bioinformatic analyses of androgen-receptor (AR) binding sites and clinical PCa expression array data to identify ST6GalNAc1 as a direct and rapidly activated target gene of the AR in PCa cells. ST6GalNAc1 encodes a sialytransferase that catalyses formation of the cancer-associated sialyl-Tn antigen (sTn), which we find is also induced by androgen exposure. Androgens induce expression of a novel splice variant of the ST6GalNAc1 protein in PCa cells. This splice variant encodes a shorter protein isoform that is still fully functional as a sialyltransferase and able to induce expression of the sTn-antigen. Surprisingly, given its high expression in tumours, stable expression of ST6GalNAc1 in PCa cells reduced formation of stable tumours in mice, reduced cell adhesion and induced a switch towards a more mesenchymal-like cell phenotype in vitro. ST6GalNAc1 has a dynamic expression pattern in clinical datasets, beingsignificantly up-regulated in primary prostate carcinoma but relatively down-regulated in established metastatic tissue. ST6GalNAc1 is frequently upregulated concurrently with another important glycosylation enzyme GCNT1 previously associated with prostate cancer progression and implicated in Sialyl Lewis X antigen synthesis. Together our data establishes an androgen-dependent mechanism for sTn antigen expression in PCa, and are consistent with a general role for the androgen receptor in driving important coordinate changes to the glycoproteome during PCa progression.
Resumo:
The global aim of this thesis was to evaluate and assess the effects of a pesticide (dimethoate) and a metal (nickel), as model chemicals, within different organization levels, starting at the detoxification pathways (enzymatic biomarkers) and energy costs associated (energy content quantification, energy consumption and CEA) along with the physiological alterations at the individual and population level (mortality), leading to a metabolomic analysis (using liquid 1H-NMR) and finally a gene expression analysis (transcriptome and RT-qPCR analysis). To better understand potential variations in response to stressors, abiotic factors were also assessed in terrestrial isopods such as temperature, soil moisture and UV radiation. The evaluation performed using biochemical biomarkers and energy related parameters showed that increases in temperature might negatively affect the organisms by generating oxidative stress. It also showed that this species is acclimated to environments with low soil moisture, and that in high moisture scenarios there was a short gap between the optimal and adverse conditions that led to increased mortality. As for UV-R, doses nowadays present have shown to induce significant negative impact on these organisms. The long-term exposure to dimethoate showed that besides the neurotoxicity resulting from acetylcholinesterase inhibition, this stressor also caused oxidative stress. This effect was observed for both concentrations used (recommended field dose application and a below EC50 value) and that its combination with different temperatures (20ºC and 25ºC) showed different response patterns. It was also observed that dimethoate’s degradation rate in soils was higher in the presence of isopods. In a similar study performed with nickel, oxidative stress was also observed. But, in the case of this stressor exposure, organisms showed a strategy where the energetic costs necessary for detoxification (biomarkers) seemed to be compensated by positive alterations in the energy related parameters. In this work we presented for the first time a metabolomic profile of terrestrial isopods exposed to stressors (dimethoate and niquel), since until the moment only a previous study was performed on a metabolomic evaluation in nonexposed isopods. In the first part of the study we identify 24 new metabolites that had not been described previously. On the second part of the study a metabolomic profile variation of abstract non-exposed organism throughout the exposure was presented and finally the metabolomic profile of organisms exposed to dimethoate and nickel. The exposure to nickel suggested alteration in growth, moult, haemocyanin and glutathione synthesis, energy pathways and in osmoregulation. As for the exposure to dimethoate alterations in osmoregulation, energy pathways, moult and neurotransmission were also suggested. In this work it was also presented the first full body transcriptome of a terrestrial isopod from the species Porcellionides pruinosus, which will complement the scarce information available for this group of organisms. This transcriptome also served as base for a RNA-Seq and a RT-qPCR analysis. The results of the RNA-Seq analysis performed in organisms exposed to nickel showed that this stressor negatively impacted at the genetic and epigenetic levels, in the trafficking, storage and elimination of metals, generates oxidative stress, inducing neurotoxicity and also affecting reproduction. These results were confirmed through RT-qPCR. As for the impact of dimethoate on these organisms it was only accessed through RT-qPCR and showed oxidative stress, an impact in neurotransmission, in epigenetic markers, DNA repair and cell cycle impairment. This study allowed the design of an Adverse Outcome Pathway draft that can be used further on for legislative purposes.
Resumo:
RESUMO: Actualmente, a única possibilidade de cura para doentes com adenocarcinoma do pâncreas (PDAC) é a ressecção cirúrgica, no início deste estudo, perguntamo-nos se os predictores clínico-patológicos clássicos de prognostico poderiam ser validados em uma grande cohort de doentes com cancro do pâncreas ressecável e se outros predictores clínicos poderiam ter um papel na decisão de que doentes beneficiariam de ressecção cirúrgica. No capítulo 2, observamos que até 30% dos doentes morrem no primeiro ano após a ressecção cirúrgica, pelo que o nosso objectivo foi determinar factores pré-operatórios que se correlacionam com mortalidade precoce após ressecação cirúrgica com recurso a um instrumento estatisticamente validado, o Charlson-Age Comorbidity Index (CACI), determinamos que um CACI score superior a 4 foi preditivo de internamentos prolongados (p <0,001), complicações pós-operatórias (p = 0,042), e mortalidade em 1 ano pós- ressecção cirúrgica (p <0,001). Um CACI superior a 6 triplicou a mortalidade no primeiro ano pós-cirurgia e estes doentes têm menos de 50% de probabilidade de estarem vivos um ano após a cirurgia. No capítulo 3, o nosso objectivo foi identificar uma proteína de superfície que se correlacionasse estatisticamente com o prognostico de doentes com adenocarcinoma do pâncreas e permitisse a distinção de subgrupos de doentes de acordo com as suas diferenças moleculares, perguntamo-nos ainda se essa proteína poderia ser um marcador de células-estaminais. No nosso trabalho anterior observamos que as células tumorais na circulação sanguínea apresentavam genes com características bifenotípica epitelial e mesenquimal, enriquecimento para genes de células estaminais (ALDH1A1 / ALDH1A2 e KLF4), e uma super-expressão de genes da matriz extracelular (colagénios, SPARC, e DCN) normalmente identificados no estroma de PDAC. Após a avaliação dos tumores primários com RNA-ISH, muitos dos genes identificados, foram encontrados co-localizando em uma sub-população de células na região basal dos ductos pancreáticos malignos. Além disso, observamos que estas células expressam o marcador SV2A neuroendócrino, e o marcador de células estaminais ALDH1A1/2. Em comparação com tumores negativos para SV2, os doentes com tumores SV2 positivos apresentaram níveis mais baixos de CA 19-9 (69% vs. 52%, p = 0,012), tumores maiores (> 4 cm, 23% vs. 10%, p = 0,0430), menor invasão de gânglios linfáticos (69% vs. 86%, p = 0,005) e tumores mais diferenciados (69% vs. 57%, p = 0,047). A presença de SV2A foi associada com uma sobrevida livre de doença mais longa (HR: 0,49 p = 0,009) bem como melhor sobrevida global (HR: 0,54 p = 0,018). Em conjunto, esta informação aponta para dois subtipos diferentes de adenocarcinoma do pâncreas, e estes subtipos co-relacionam estatisticamente com o prognostico de doentes, sendo este subgrupo definido pela presença do clone celular SV2A / ALDH1A1/2 positivo com características neuroendócrinas. No Capítulo 4, a expressão de SV2A no cancro do pâncreas foi validado em linhas celulares primárias. Demonstramos a heterogeneidade do adenocarcinoma do pâncreas de acordo com características clonais neuroendócrinas. Ao comparar as linhas celulares expressando SV2 com linhas celulares negativas, verificamos que as linhas celulares SV2+ eram mais diferenciadas, diferindo de linhas celulares SV2 negativas no que respeita a mutação KRAS, proliferação e a resposta à quimioterapia. No capítulo 5, perguntamo-nos se o clone celular SV2 positivo poderia explicar a resistência a quimioterapia observada em doentes. Observamos um aumento absoluto de clones celulares expressando SV2A, em múltiplas linhas de evidência - doentes, linhas de células primárias e xenotransplantes. Embora, tenhamos sido capazes de demonstrar que o adenocarcinoma do pâncreas é uma doença heterogénea, consideramos que a caracterização genética destes clones celulares expressando SV2A é de elevada importância. Pretendemos colmatar esta limitação com as seguintes estratégias: Após o tratamento com quimioterapia neoadjuvante na nossa coorte, realizamos microdissecação a laser das amostras primarias em parafina, de forma a analisar mutações genéticas observadas no adenocarcinoma pancreático; em segundo lugar, pretendemos determinar consequências de knockdown da expressão de SV2A em nossas linhas celulares seguindo-se o tratamento com gemicitabina para determinação do papel funcional de SV2A; finalmente, uma vez que os nossos esforços anteriores com um promotor - repórter e SmartFlare ™ falharam, o próximo passo será realizar RNA-ISH PrimeFlow™ seguido de FACS e RNA-seq para caracterização deste clone celular. Em conjunto, conseguimos provar com várias linhas de evidência, que o adenocarcinoma pancreático é uma doença heterogénea, definido por um clone de células que expressam SV2A, com características neuroendócrinas. A presença deste clone no tecido de doentes correlaciona-se estatisticamente com o prognostico da doença, incluindo sobrevida livre de doença e sobrevida global. Juntamente com padrões de proliferação e co-expressão de ALDH1A1/2, este clone parece apresentar um comportamento de células estaminais e está associado a resistência a quimioterapia, uma vez que a sua expressão aumenta após agressão química, quer em doentes, quer em linhas de células primárias.----------------------------- ABSTRACT: Currently, the only chance of cure for patients with pancreatic adenocarcinoma is surgical resection, at the beginning of my thesis studies, we asked if the classical clinicopathologic predictors of outcome could be validated in a large cohort of patients with early stage pancreatic cancer and if other clinical predictors could have a role on deciding which patients would benefit from surgery. In chapter 2, we found that up to 30% of patients die within the first year after curative intent surgery for pancreatic adenocarcinoma. We aimed at determining pre-operative factors that would correlate with early mortality following resection for pancreatic cancer using a statistically validated tool, the Charlson-Age Comorbidity Index (CACI). We found that a CACI score greater than 4 was predictive of increased length of stay (p<0.001), post-operative complications (p=0.042), and mortality within 1-year of pancreatic resection (p<0.001). A CACI score of 6 or greater increased 3-fold the odds of death within the first year. Patients with a high CACI score have less than 50% likelihood of being alive 1 year after surgery. In chapter 3 we aimed at identifying a surface protein that correlates with patient’s outcome and distinguishes sub-groups of patients according to their molecular differences and if this protein could be a cancer stem cell marker. The most abundant class of circulating tumor cells identified in our previous work was found to have biphenotypic features of epithelial to mesenchymal transition, enrichment for stem-cell associated genes (ALDH1A1/ALDH1A2 and KLF4), and an overexpression of extracellular matrix genes (Collagens, SPARC, and DCN) normally found in the stromal microenvironment of PDAC primary tumors. Upon evaluation of matched primary tumors with RNA-ISH, many of the genes identified were found to co-localize in a sub-population of cells at the basal region of malignant pancreatic ducts. In addition, these cells expressed the neuroendocrine marker SV2A, and the stem cell marker ALDH1A1/2. Compared to SV2 negative tumors, patients with SV2 positive tumors were more likely to present with lower CA 19-9 (69% vs. 52%, p = 0.012), bigger tumors (size > 4 cm, 23% vs. 10%, p= 0.0430), less nodal involvement (69% vs. 86%, p = 0.005) and lower histologic grade (69% vs. 57%, p = 0.047). The presence of SV2A expressing cells was associated with an improved disease free survival (HR: 0.49 p=0.009) and overall survival (HR: 0.54 p=0.018) and correlated linearly with ALDH1A2. Together, this information points to two different sub-types of pancreatic adenocarcinoma, and these sub-types correlated with patients’ outcome and were defined by the presence of a SV2A/ ALDH1A1/2 expressing clone with neuroendocrine features. In Chapter 4, SV2A expression in cancer was validated in primary cell lines. We were able to demonstrate pancreatic adenocarcinoma heterogeneity according to neuroendocrine clonal features. When comparing SV2 expressing cell lines with SV2 negative cell lines, we found that SV2+ cell lines were more differentiated and differ from SV2 negative cell lines regarding KRAS mutation, proliferation and response to chemotherapy. In Chapter 5 we aimed at determining if this SV2 positive clone could explain chemoresistance observed in patients. We found an absolute increase in SV2A expressing cells, with multiple lines of evidence, in patients, primary cell lines and xenografts. Although, we have been able to show evidence that pancreatic adenocarcinoma is a heterogeneous disease, our findings warrant further investigation. To further characterize SV2A expressing clones after treatment with neoadjuvant chemotherapy in our cohort, we have performed laser capture microdissection of the paraffin embedded tissue in this study and will analyze the tissue for known genetic mutations in pancreatic adenocarcinoma; secondly, we want to know what will happen after knocking down SV2A expression in our cell lines followed by treatment with gemcitabine to determine if SV2A is functionally important; finally, since our previous efforts with a promoter – reporter and SmartFlare™ have failed, we will utilize a novel PrimeFlow™ RNA-ISH assay followed by FACS and RNA sequencing to further characterize this cellular clone. Overall our data proves, with multiple lines of evidence, that pancreatic adenocarcinoma is a heterogeneous disease, defined by a clone of SV2A expressing cells, with neuroendocrine features. The presence of this clone in patients’ tissue correlates with patient’s disease free survival and overall survival. Together with patterns of proliferation and ALDH1A1/2 co-expression, this clone seems to present a stem-cell-like behavior and is associated with chemoresistance, since it increases after chemotherapy, both in patients and primary cell lines.
Resumo:
La méthode ChIP-seq est une technologie combinant la technique de chromatine immunoprecipitation avec le séquençage haut-débit et permettant l’analyse in vivo des facteurs de transcription à grande échelle. Le traitement des grandes quantités de données ainsi générées nécessite des moyens informatiques performants et de nombreux outils ont vu le jour récemment. Reste cependant que cette multiplication des logiciels réalisant chacun une étape de l’analyse engendre des problèmes de compatibilité et complique les analyses. Il existe ainsi un besoin important pour une suite de logiciels performante et flexible permettant l’identification des motifs. Nous proposons ici un ensemble complet d’analyse de données ChIP-seq disponible librement dans R et composé de trois modules PICS, rGADEM et MotIV. A travers l’analyse de quatre jeux de données des facteurs de transcription CTCF, STAT1, FOXA1 et ER nous avons démontré l’efficacité de notre ensemble d’analyse et mis en avant les fonctionnalités novatrices de celui-ci, notamment concernant le traitement des résultats par MotIV conduisant à la découverte de motifs non détectés par les autres algorithmes.
Resumo:
Phosphorylation of the coronavirus nucleoprotein (N protein) has been predicted to play a role in RNA binding. To investigate this hypothesis, we examined the kinetics of RNA binding between nonphosphorylated and phosphorylated infectious bronchitis virus N protein with nonviral and viral RNA by surface plasmon resonance (Biacore). Mass spectroscopic analysis of N protein identified phosphorylation sites that were proximal to RNA binding domains. Kinetic analysis, by surface plasmon resonance, indicated that nonphospborylated N protein bound with the same affinity to viral RNA as phosphorylated N protein. However, phosphorylated N protein bound to viral RNA with a higher binding affinity than nonviral RNA, suggesting that phosphorylation of N protein determined the recognition of virus RNA. The data also indicated that a known N protein binding site (involved in transcriptional regulation) consisting of a conserved core sequence present near the 5' end of the genome (in the leader sequence) functioned by promoting high association rates of N protein binding. Further analysis of the leader sequence indicated that the core element was not the only binding site for N protein and that other regions functioned to promote high-affinity binding.
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)