Identification of microRNA activity by Targets' Reverse EXpression

Motivation: Non-coding microRNAs (miRNAs) act as regulators of global protein output. While their major effect is on protein levels of target genes, it has been proven that they also specifically impact on the messenger RNA level of targets. Prominent interest in miRNAs strongly motivates the need for increasing the options available to detect their cellular activity

Inference of Gene Regulation via miRNAs During ES Cell Differentiation Using MiRaGE Method

MicroRNA (miRNA) is a critical regulator of cell growth, differentiation, and development. To identify important miRNAs in a biological process, many bioinformatical tools have been developed. We have developed MiRaGE (MiRNA Ranking by Gene Expression) method to infer the regulation of gene expression by miRNAs from changes of gene expression profiles. The method does not require precedent array normalization. We applied the method to elucidate possibly important miRNAs during embryonic stem (ES) cell differentiation to neuronal cells and we infer that certain miRNAs, including miR-200 family, miR-429, miR-302 family, and miR-17-92 cluster members may be important to the maintenance of undifferentiated status in ES cells

MIRTFnet: Analysis of miRNA Regulated Transcription Factors

Several expression datasets of miRNA transfection experiments are available to analyze the regulatory mechanisms downstream of miRNA effects. The miRNA induced regulatory effects can be propagated via transcription factors (TFs). We propose the method MIRTFnet to identify miRNA controlled TFs as active regulators if their downstream target genes are differentially expressed

BayMiR: inferring evidence for endogenous miRNA-induced gene repression from mRNA expression profiles

BACKGROUND: Popular miRNA target prediction techniques use sequence features to determine the functional miRNA target sites. These techniques commonly ignore the cellular conditions in which miRNAs interact with their targets in vivo. Gene expression data are rich resources that can complement sequence features to take into account the context dependency of miRNAs. RESULTS: We introduce BayMiR, a new computational method, that predicts the functionality of potential miRNA target sites using the activity level of the miRNAs inferred from genome-wide mRNA expression profiles. We also found that mRNA expression variation can be used as another predictor of functional miRNA targets. We benchmarked BayMiR, the expression variation, Cometa, and the TargetScan “context scores” on two tasks: predicting independently validated miRNA targets and predicting the decrease in mRNA abundance in miRNA overexpression assays. BayMiR performed better than all other methods in both benchmarks and, surprisingly, the variation index performed better than Cometa and some individual determinants of the TargetScan context scores. Furthermore, BayMiR predicted miRNA target sets are more consistently annotated with GO and KEGG terms than similar sized random subsets of genes with conserved miRNA seed regions. BayMiR gives higher scores to target sites residing near the poly(A) tail which strongly favors mRNA degradation using poly(A) shortening. Our work also suggests that modeling multiplicative interactions among miRNAs is important to predict endogenous mRNA targets. CONCLUSIONS: We develop a new computational method for predicting the target mRNAs of miRNAs. BayMiR applies a large number of mRNA expression profiles and successfully identifies the mRNA targets and miRNA activities without using miRNA expression data. The BayMiR package is publicly available and can be readily applied to any mRNA expression data sets

Mecanismos epigenéticos e controle da expressão do gene HLA-G

Orientador: Maria da Graça BicalhoMonografia (Bacharelado) - Universidade Federal do Paraná. Setor de Ciências Biológicas. Curso de Graduação em Ciências BiológicasResumo : O gene HLA-G faz parte do Complexo Principal de Histocompatibilidade (MHC) e encontra-se no cromossomo 6, na posição 6p21.3. Ele apresenta uma distribuição tecidual restrita e possui funções relacionadas à supressão da resposta imune através da interação da proteína HLA-G com receptores inibitórios presentes nas células Natural Killer (NK) e linfócitos T. Um dos principais papéis atribuídos à HLA-G tem sido a indução da tolerância imunológica materna ao feto semi-alogênico no processo gestacional. Além disso, em situações patológicas tais como, células neoplásicas, transformadas ou infectadas por vírus, sua expressão tem sido considerada uma estratégia, ou mecanismo de escape ao sistema imune do hospedeiro. O controle da expressão de HLA-G ocorre via elementos em cis presentes em sua região promotora/reguladora quando interagem com fatores transcricionais e proteínas ativadoras/inibidoras de reguladores (elementos de ação trans) e acontece tanto em nível trascricional como traducional. Além disso, eventos epigenéticos podem ocorrer em ambos os níveis. Epigenética envolve o estudo de mudanças na expressão gênica sem que ocorram mudanças na sequência de DNA. Os principais eventos epigenéticos são: a metilação das citosinas (C) adjacentes às guaninas (G) na fita do DNA; modificações pós-traducionais da cauda das histonas e, controle da expressão do gene por associação do RNAm a microRNAs. O gene HLA-G está sujeito a todas essas formas de controle da expressão gênica de forma interativa. Neste trabalho ilustramos algumas influências dos eventos epigenéticos na expressão do HLA-G e, mostramos que variações nucleotídicas presentes nos alelos de HLA-G podem exercer grande influência no controle da sua expressão, quaisquer que sejam os mecanismos atuantes

Activity of microRNAs and transcription factors in Gene Regulatory Networks

In biological research, diverse high-throughput techniques enable the investigation of whole systems at the molecular level. The development of new methods and algorithms is necessary to analyze and interpret measurements of gene and protein expression and of interactions between genes and proteins. One of the challenges is the integrated analysis of gene expression and the associated regulation mechanisms. The two most important types of regulators, transcription factors (TFs) and microRNAs (miRNAs), often cooperate in complex networks at the transcriptional and post-transcriptional level and, thus, enable a combinatorial and highly complex regulation of cellular processes. For instance, TFs activate and inhibit the expression of other genes including other TFs whereas miRNAs can post-transcriptionally induce the degradation of transcribed RNA and impair the translation of mRNA into proteins. The identification of gene regulatory networks (GRNs) is mandatory in order to understand the underlying control mechanisms. The expression of regulators is itself regulated, i.e. activating or inhibiting regulators in varying conditions and perturbations. Thus, measurements of gene expression following targeted perturbations (knockouts or overexpressions) of these regulators are of particular importance. The prediction of the activity states of the regulators and the prediction of the target genes are first important steps towards the construction of GRNs. This thesis deals with these first bioinformatics steps to construct GRNs. Targets of TFs and miRNAs are determined as comprehensively and accurately as possible. The activity state of regulators is predicted for specific high-throughput data and specific contexts using appropriate statistical approaches. Moreover, (parts of) GRNs are inferred, which lead to explanations of given measurements. The thesis describes new approaches for these tasks together with accompanying evaluations and validations. This immediately defines the three main goals of the current thesis: 1. The development of a comprehensive database of regulator-target relation. Regulators and targets are retrieved from public repositories, extracted from the literature via text mining and collected into the miRSel database. In addition, relations can be predicted using various published methods. In order to determine the activity states of regulators (see 2.) and to infer GRNs (3.) comprehensive and accurate regulator-target relations are required. It could be shown that text mining enables the reliable extraction of miRNA, gene, and protein names as well as their relations from scientific free texts. Overall, the miRSel contains about three times more relations for the model organisms human, mouse, and rat as compared to state-of-the-art databases (e.g. TarBase, one of the currently most used resources for miRNA-target relations). 2. The prediction of activity states of regulators based on improved target sets. In order to investigate mechanisms of gene regulation, the experimental contexts have to be determined in which the respective regulators become active. A regulator is predicted as active based on appropriate statistical tests applied to the expression values of its set of target genes. For this task various gene set enrichment (GSE) methods have been proposed. Unfortunately, before an actual experiment it is unknown which genes are affected. The missing standard-of-truth so far has prevented the systematic assessment and evaluation of GSE tests. In contrast, the trigger of gene expression changes is of course known for experiments where a particular regulator has been directly perturbed (i.e. by knockout, transfection, or overexpression). Based on such datasets, we have systematically evaluated 12 current GSE tests. In our analysis ANOVA and the Wilcoxon test performed best. 3. The prediction of regulation cascades. Using gene expression measurements and given regulator-target relations (e.g. from the miRSel database) GRNs are derived. GSE tests are applied to determine TFs and miRNAs that change their activity as cellular response to an overexpressed miRNA. Gene regulatory networks can constructed iteratively. Our models show how miRNAs trigger gene expression changes: either directly or indirectly via cascades of miRNA-TF, miRNA-kinase-TF as well as TF-TF relations. In this thesis we focus on measurements which have been obtained after overexpression of miRNAs. Surprisingly, a number of cancer relevant miRNAs influence a common core of TFs which are involved in processes such as proliferation and apoptosis

Bioinformatics analysis of HPV associated host microRNA functions and identification of viral microRNA

Human papillomaviruses (HPVs) form a large family among double stranded DNA (dsDNA) viruses, some types of which are the major causes of cervical cancer. HPV 16 is widely distributed and the most common high-risk HPV type and approximately half of the cervical cancers are associated with HPV type 16. Of the three HPV 16 encoded oncogenes, the function of E5 in regulating viral replication and pathogenesis is less well understood than E6 and E7. The microRNAs (miRNAs) are important small noncoding RNA molecules that regulate wide range of cellular functions. Some dsDNA viruses, such as SV40 and human polyomaviruses, have functional viral miRNAs. The functional and molecular similarities among dsDNA viruses suggest that HPV could encode viral miRNAs, which have not been validated thus far. The aim of this thesis was to study the functions of the host miRNAs in HPV 16 oncogene induction and identify novel HPV encoded viral miRNAs. We utilized microarray technology to investigate the effect of E5 on host miRNAs and mRNAs expression in 0 96 hours after E5 induction in a cell line model. Among the differentially expressed cellular miRNAs, we further validated the expression of hsa-mir-146a, hsa-mir-203, and hsa-mir-324-5p and some of their target genes in a time series of 96 hours of E5 induction. Our results indicate that HPV E5 expression has an impact through complex regulatory patterns of gene expression in the host cells, and part of those genes is regulated by the E5 protein. Second, high throughput sequencing was used to identify virus-encoded miRNAs. We prepared small RNA sequencing libraries from ten HPV-associated cervical lesions, including cancer and two HPV-harboring cell lines. For more flexible analysis of the sequencing data we developed miRSeqNovel, an R based workflow for miRNA sequencing data analysis, and applied it to the sequencing data to predict putative viral miRNAs and discovered nine putative papillomavirus encoded miRNAs. Viral miRNA validation was performed for five candidates, four of which were successfully validated by qPCR from cervical tissue samples and cell lines: two were encoded by HPV 16, one by HPV 38, and one by HPV 68. The expression of two HPV 16 miRNAs was further supported by in situ hybridization, and colocalization with p16INK4A staining, a marker of cervical neoplasia. Prediction of cellular target genes of HPV 16 encoded miRNAs suggests that they may play a role in cell cycle, immune functions, cell adhesion and migration, development and cancer, which were also among the functions targeted by the E5 regulated host cell mRNA and miRNAs. Two putative viral target sites for the two validated HPV 16 miRNAs were mapped to the E5 gene, one in the E1 gene, two in the L1 gene, and one in the long control region (LCR).Ihmisen papilloomavirukset (HPV) muodostavat suuren heimon kaksijuosteisen DNA-virusten (dsDNA) joukossa, ja niistä jotkin virustyypit ovat kohdunkaulasyövän pääasiallisia aiheuttajia. HPV 16 on laajalle levinnyt ja yleisin suuren riskin HPV-tyyppi, joka aiheuttaa noin puolet kohdunkaulasyövistä. Kolmesta HPV 16:n koodittamasta onkogeenistä E5:n toiminta viruksen replikaation ja patogeneesin säätelyssä tunnetaan huonommin kuin E6:n ja E7:n. Mikro-RNA:t (miRNA) ovat pieniä ei-koodittaavia RNA-molekyylejä, joilla on tärkeä merkitys solun toimintojen säätelyssä. Jotkin dsDNA-virukset, kuten SV40 ja ihmisen polyoomavirukset, koodittavat omia toiminnallisia mikro-RNA:ita. HPV:n koodittamia mRNAita ei ole aiemmin validoitu, mutta dsDNA-virusten toiminnalliset ja molekulaariset samankaltaisuudet viittaavat siihen, että myös HPV voisi koodittaa omia mikro-RNA:ita. Väitöskirjan tavoitteena oli tutkia isäntäsolun mikro-RNA:iden toimintaa HPV 16 onkogeeni-induktiossa ja löytää uusia, HPV:n koodittamia miRNA:ita. Tutkimme sirutekniikan avulla E5:n vaikutusta isännän miRNA- ja mRNA-ekspressioon solulinjamallissa 0-96 tunnin kuluessa E5:n induktiosta. Eri tavoin ekpressoituneista miRNA tutkimme tarkemmin hsa-mir-146, hsa-mir-203 ja hsa-mir-324-5p sekä muutamien näiden kohdegeenien ekspressiota 96 tunnin aikasarjana E5 induktiosta. Tulokset osoittavat HPV E5 ekspression vaikuttavan isäntäsolun geenien ilmentymiseen monimutkaisen säätelymallin välityksellä ja E5-proteiinin myös säätelevän osaa näistä geeneistä. Next generation sekvensointia käytettiin tunnistamaan virusten koodaamia miRNA:ita. Joustavampaa miRNA sekvenssidatan analysointia varten kehitimme miRSeqNovel-nimisen R-pohjaisen työkalun ja käytimme sitä ennustamaan mahdollisia virusten koodaamia miRNA:ita. Löysimme yhdeksän mahdollisesti HPV:n koodaamaa miRNA:ta, joista viisi otettiin mukaan miRNAn validointiin. Neljä viidestä HPV:n koodaamasta miRNAsta pystyttiin validoimaan qPCR:n avulla kohdunkaulan kudosnäytteistä ja solulonjoista. Näistä kaksi miRNA:ta on HPV 16 koodaamaa ja yhdet HPV38 ja HPV68 koodaamia. Kahden HPV16 koodaaman miRNA:n ekspressiota osoitettiin myös in-situ-hybridisaatiossa kolokalisoituneena värjäyksessä kohdunkaulan neoplasiasta kertovan P16INK4a kanssa. HPV16 mikro-RNA:n kohdegeenien ennusteet viittaavat miRNA:iden mahdolliseen rooliin solusyklissä, immuunijärjestelmän toiminnoissa, soluadheesiossa ja migraatiossa, yksilönkehityksessä ja syövässä. Nämä kohteet löytyvät myös E5:n säätelemien mRNA:iden ja miRNA:iden kohteista. Kaksi HPV16 miRNA:n mahdollista kohdetta löytyvät viruksen E5-geenistä, yksi kohden E1 geenistä, kaksi L1 geenistä ja yksi pitkästä kontrollialueesta (LCR)

A systems biology approach to non-coding RNAs: the networks of cancer

A non-coding RNA is a functional RNA molecule that is not translated into a protein. This class of molecules is involved in many cellular processes and includes highly abundant and functionally important RNAs such as transfer RNA (tRNA), ribosomal RNA (rRNA), as well as small interfering RNAs (siRNAs), microRNAs (miRNAs), transcribed ultraconserved regions (T-UCRs) and others. First of all, we investigate the specificity for normal tissues of two selected non-coding RNAs: Transcribed UltraConserved Region and microRNAs. Second, we want to find whether these non-coding RNAs can be candidates as features for the selection of specific cancers, using statistical algorithms and bioinformatics tools. Third, we generate miRNA gene networks in normal and different cancer and leukemia. The term “ultraconserved” refer to genomic regions longer than 200 base pairs that are absolutely conserved (100% homology with no insertions or deletions) in human, mouse, and rat genomes. There are 481 T-UCRs. The reason for this extreme conservation remains a mystery; T-UCRs may play a functional role in the ontogeny and phylogeny of mammals and other vertebrates. Genome-wide profiling revealed that UCRs are frequently located on overlapping exons in genes involved in RNA processing and can be found in introns or at fragile sites and in cancer-associated genomic regions. We investigate the expression of T-UCRs in 374 normal samples from 46 different tissues, grouped by 16 systems. Moreover, we analyzed the specificity of T-UCRs in cancers. Tissue specific T-UCRs can differentiate cell types. We then examine the expression of T-UCRs in human embryonic stem cells, induced pluripotent stem cells, and a series of differentiated cell types (trophoblast, embryoid bodies at 7 and 14 days of differentiation, definitive endoderm, and spontaneous differentiated monolayers). One T-UCR in particular, uc.283 plus, is highly specific for embryonic and induced pluripotent stem cells, as confirmed by real time PCR (RT-PCR). MiRNAs are global regulators of protein output. Each miRNA has been studied for its single contribution to differential expression or to a compact predictive signature. Thus, we propose a study of miRNAs in cancer by applying a systems biology approach. We study miRNA profiles in 4419 human samples (3312 neoplastic, 1107 non-malignant), corresponding to 50 normal tissues (grouped by 17 systems) and 51 cancer types. We calculate tissue specificity and cancer type specificity, a small set of miRNAs were tissue-specific while many others were broadly expressed. Then we find whether non-coding RNAs can be candidates as features for the selection of specific cancers, using statistical algorithms and bioinformatics tools, as decision trees. Afterwards, we build miRNA gene networks by using our very large expression miRNA database. The complexity of our expression database enables us to perform a detailed analysis of coordinated miRNA activities. We also build specialized miRNA networks for different solid tumors and leukemias. Combining differential expression, genetic networks, DNA copy number alterations and other systems biology approaches we confirm or discovered miRNAs with comprehensive roles in cancer. We find that normal tissues are represented by single complete miRNA networks. Cancers instead show separate and unlinked miRNA sub-networks. miRNAs independent from the general transcriptional program were often known as cancer-related. We validate our results by in silico, in vitro and in vivo analysis. We demonstrate that the target genes of these uncoordinated miRNA involve in specific cancer-related pathways

Studio molecolare e funzionale della famiglia del miR-302 in cellule staminali e tumorali

MicroRNAs, also called miRNA or miR are short ribonucleic acid molecules of 19-24 nucleotides that play an important regulatory role in the expression of cellular proteins through post-transcriptional gene silencing. Despite their identification and description is relatively recent, the microRNAs are assigned tasks that involve almost all physiological and pathological cellular processes. Our research has focused on the study of a family of microRNAs, miR-302. Among more than 700 miRNA identified, the miR-302 seems to be more expressed in embryonic stem cells (-ES-) and is one of microRNAs with the highest specificity of expression. We performed a molecular study of miR-302 on expression profiles from human embryonic stem cells (hESCs) and hESC in differentiation in order to describe the correlation between the different expression profiles and the cell state. The hypothesis of CSC (Cancer Stem Cells) provides an explanation for the refractoriness to treatment and the latent ability of certain cancers. Our laboratory have been discovered a number of miRNAs that play a critical role in cancer and therefore our research focus on investigating the expression levels in normal tissues and tumor counterparts. We then examined the expression of mir-302 in samples of ductal carcinoma in situ and invasive carcinoma of the breast samples. In situ hybridization investigation has found that the MIR-302 is present in the infiltrating ductal carcinoma, but not in cells of normal tissue. In addition, primary tumors with lymph node metastasis have an excess of tumor cells expressing the mir-302. Based on this observation, we sought to understand the mechanisms that lead to the expression of the cluster. We observed that tumor cell lines of breast cancer treated in conditions of hypoxia express the miR-302b, while the counterpart in normoxia do not express it. According to the screening carried out on the tissues of patients the miR-302 bound to metastases and especially to the lower survival of the individual, the target validation of estrogen receptor ER-alpha in epithelial cell lines has led us to have several assumptions about the role that could have the expression of miR-302 on epithelial mesenchymal transition EMT and its counterpart, MET and the further role in metastasis. The choice of generating a mouse Knock in that express miR-302 marked by a reporter gene, ZsGreen, will lead to a series of in vivo studies for the coming years