Duplication and subfunctionalisation of the general transcription factor IIIA (gtf3a) gene in teleost genomes, with ovarian specific transcription of gtf3ab

Fish oogenesis is characterised by a massive growth of oocytes each reproductive season. This growth requires the stockpiling of certain molecules, such as ribosomal RNAs to assist the rapid ribosomal assembly and protein synthesis required to allow developmental processes in the newly formed embryo. Massive 5S rRNA expression in oocytes, facilitated by transcription factor 3A (Gtf3a), serves as marker of intersex condition in fish exposed to xenoestrogens. Our present work on Gtf3a gene evolution has been analysed in silico in teleost genomes and functionally in the case of the zebrafish Danio rerio. Synteny-analysis of fish genomes has allowed the identification of two gtf3a paralog genes, probably emerged from the teleost specific genome duplication event. Functional analyses demonstrated that gtf3ab has evolved as a gene specially transcribed in oocytes as observed in Danio rerio, and also in Oreochromis niloticus. Instead, gtf3aa was observed to be ubiquitously expressed. In addition, in zebrafish embryos gtf3aa transcription began with the activation of the zygotic genome (similar to 8 hpf), while gtf3ab transcription began only at the onset of oogenesis. Under exposure to 100 ng/L 17 beta-estradiol, fully feminised 61 dpf zebrafish showed transcription of ovarian gtf3ab, while masculinised (100 ng/L 17 alpha-methyltestosterone treated) zebrafish only transcribed gtf3aa. Sex related transcription of gtf3ab coincided with that of cyp19a1a being opposite to that of amh and dmrt1. Such sex dimorphic pattern of gtf3ab transcription was not observed earlier in larvae that had not yet shown any signs of gonad formation after 26 days of oestradiol exposure. Thus, gtf3ab transcription is a consequence of oocyte differentiation and not a direct result of estrogen exposure, and could constitute a useful marker of gonad feminisation and intersex condition.This work has been funded through research projects of MINECO (AGL2012-33477 and AGL2015-63936_R), Basque-Government (PhD fellowship to IRB, S-PE13UN101 & IT81013). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Random X Inactivation and Extensive Mosaicism in Human Placenta Revealed by Analysis of Allele-Specific Gene Expression along the X Chromosome

Imprinted inactivation of the paternal X chromosome in marsupials is the primordial mechanism of dosage compensation for X-linked genes between females and males in Therians. In Eutherian mammals, X chromosome inactivation (XCI) evolved into a random process in cells from the embryo proper, where either the maternal or paternal X can be inactivated. However, species like mouse and bovine maintained imprinted XCI exclusively in extraembryonic tissues. The existence of imprinted XCI in humans remains controversial, with studies based on the analyses of only one or two X-linked genes in different extraembryonic tissues. Here we readdress this issue in human term placenta by performing a robust analysis of allele-specific expression of 22 X-linked genes, including XIST, using 27 SNPs in transcribed regions. We show that XCI is random in human placenta, and that this organ is arranged in relatively large patches of cells with either maternal or paternal inactive X. In addition, this analysis indicated heterogeneous maintenance of gene silencing along the inactive X, which combined with the extensive mosaicism found in placenta, can explain the lack of agreement among previous studies. Our results illustrate the differences of XCI mechanism between humans and mice, and highlight the importance of addressing the issue of imprinted XCI in other species in order to understand the evolution of dosage compensation in placental mammals

In-silico identification of human genes submitted to allelic differential expression

Estudos recentes demonstraram que a variação de expressão alelo-específica é mais comum do que se imaginou, podendo chegar, em humanos, a 50% dos genes. Identificar os genes submetidos ao controle de expressão alelo-específica é muito importante para o entendimento de várias doenças, incluindo o câncer. A identificação dos alvos desse tipo de regulação diferencial é difícil, principalmente devido à dificuldade de se avaliar a expressão de cada alelo individualmente. Neste trabalho, abordamos este problema com uma estratégia de análise in-silico, fundamentada na integração de dados públicos do genoma humano, dados de expressão (como cDNAs, SAGE e MPSS) e dados sobre polimorfismos (SNPs). Desenvolvemos um banco de dados de polimorfismos de base única (Single-Nucleotide Polymorphism - SNPs) associados a etiquetas alternativas de SAGE (Serial Analysis of Gene Expression) e MPSS (massively parallel signature sequencing). SAGE e MPSS são técnicas desenvolvidas para análise da expressão de genes em larga escala. Ambas as técnicas têm como princípio a produção de pequenas seqüências marcadoras (etiquetas), adjacentes aos sítios de enzimas de restrição que estiverem mais próximo da cauda poli-A do RNA mensageiro. Tais etiquetas são seqüenciadas em grande escala e a quantidade de etiquetas é usada para medir a abundância relativa dos RNAs mensageiros correspondentes. A presença de SNPs nos sítios de restrição ou nas seqüências das etiquetas pode gerar etiquetas distintas para alelos do mesmo gene, que denominamos etiquetas alternativas. Neste trabalho, empregamos o banco de dados de etiquetas alternativas associadas a SNPs para identificar genes com expressão alélica diferencial. Usando esta estratégia, identificamos 812 genes com expressão monoalélica, Estudos anteriores comprovaram que, dentre os 812 genes identificados, cinco estão sujeitos ao fenômeno de imprinting genômico. Durante o decorrer deste estudo, trabalhos realizados por outros grupos apontaram outros 73 genes do nosso repertório como genes que apresentam variação no nível de expressão dos alelos em heterozigotos. Com objetivo de confirmar a expressão alélica diferencial dos nossos candidatos, selecionamos 29 genes para validação experimental. Para 12 destes genes não achamos indivíduos heterozigotos, impossibilitando a análise da expressão dos alelos. Dentre os outros 17 genes, três apresentaram expressão bialélica e 14 apresentaram expressão alélica diferencial nos indivíduos heterozigotos, sendo que 3 deles apresentaram expressão monoalélica. Estes resultados sugerem que nossa estratégia pode contribuir significativamente na identificação de genes com expressão alélica diferencial.Recent studies have shown that variation of allelic-specific gene expression is more common than previously thought, reaching up to 50% of human genes. To identify genes displaying differential expression among alleles it is important for the understanding of several diseases, including the cancer. Identification of genes submitted to allelic-specific differential expression is hard, mostly due to the difficulty in evaluating the expression levels of each allele independently. In this work, we developed an in-silico approach, based on the integration of public data about the human genome, gene expression data (such as cDNAs, SNPs, SAGE and MPSS) and data on polymorphisms (SNPs). We developed a database of Single Nucleotide Polymorphisms (SNPs) associated to alternative SAGE (Serial Analysis of Gene Expression) and MPSS (Massively Parallel Signature Sequencing) tags. SAGE and MPSS are genome-wide techniques developed for analysis of gene expression. Both techniques rely on the production of short marker sequences (known as tags), adjacent to restriction sites closer to the poly-A tail of messenger RNAs. Such tags are sequenced in a large scale and tag counts are used to measure the relative abundance of their corresponding transcripts. The presence of SNPs in the restriction sites or in the tag sequences might generate allelic-specific tags for the same gene, which we call alternative tags. In this work, we used the database of SNPs and associated alternative tags to identify genes submitted to allelic-specific differential gene expression. Using this approach, we identified 812 genes showing allelic-specific differential gene expression. Previous studies have shown that, among the 812 candidates, five genes are targets for genomic imprinting. While this study was being performed, work done by other groups suggested other 73 genes in our candidates list to have different expression levels for alleles in heterozygous. Aiming to verify whether variations in the expression levels of alleles existed among our candidate genes, we submitted 29 genes for experimental validation. For 12 genes, we couldnt find heterozygous individuals, thus rendering it impossible to ascertain whether the supposed expression variation was true. Among the other 17 genes analyzed, three genes presented bi-allelic expression and 14 genes have shown clear differential expression among alleles, three of the last ones displaying strict mono-allelic expression. These results suggest that our approach may contribute significantly to the identification of genes with allelic-specific differential expression

In-silico identification of human genes submitted to allelic differential expression

Estudos recentes demonstraram que a variação de expressão alelo-específica é mais comum do que se imaginou, podendo chegar, em humanos, a 50% dos genes. Identificar os genes submetidos ao controle de expressão alelo-específica é muito importante para o entendimento de várias doenças, incluindo o câncer. A identificação dos alvos desse tipo de regulação diferencial é difícil, principalmente devido à dificuldade de se avaliar a expressão de cada alelo individualmente. Neste trabalho, abordamos este problema com uma estratégia de análise in-silico, fundamentada na integração de dados públicos do genoma humano, dados de expressão (como cDNAs, SAGE e MPSS) e dados sobre polimorfismos (SNPs). Desenvolvemos um banco de dados de polimorfismos de base única (Single-Nucleotide Polymorphism - SNPs) associados a etiquetas alternativas de SAGE (Serial Analysis of Gene Expression) e MPSS (massively parallel signature sequencing). SAGE e MPSS são técnicas desenvolvidas para análise da expressão de genes em larga escala. Ambas as técnicas têm como princípio a produção de pequenas seqüências marcadoras (etiquetas), adjacentes aos sítios de enzimas de restrição que estiverem mais próximo da cauda poli-A do RNA mensageiro. Tais etiquetas são seqüenciadas em grande escala e a quantidade de etiquetas é usada para medir a abundância relativa dos RNAs mensageiros correspondentes. A presença de SNPs nos sítios de restrição ou nas seqüências das etiquetas pode gerar etiquetas distintas para alelos do mesmo gene, que denominamos etiquetas alternativas. Neste trabalho, empregamos o banco de dados de etiquetas alternativas associadas a SNPs para identificar genes com expressão alélica diferencial. Usando esta estratégia, identificamos 812 genes com expressão monoalélica, Estudos anteriores comprovaram que, dentre os 812 genes identificados, cinco estão sujeitos ao fenômeno de imprinting genômico. Durante o decorrer deste estudo, trabalhos realizados por outros grupos apontaram outros 73 genes do nosso repertório como genes que apresentam variação no nível de expressão dos alelos em heterozigotos. Com objetivo de confirmar a expressão alélica diferencial dos nossos candidatos, selecionamos 29 genes para validação experimental. Para 12 destes genes não achamos indivíduos heterozigotos, impossibilitando a análise da expressão dos alelos. Dentre os outros 17 genes, três apresentaram expressão bialélica e 14 apresentaram expressão alélica diferencial nos indivíduos heterozigotos, sendo que 3 deles apresentaram expressão monoalélica. Estes resultados sugerem que nossa estratégia pode contribuir significativamente na identificação de genes com expressão alélica diferencial.Recent studies have shown that variation of allelic-specific gene expression is more common than previously thought, reaching up to 50% of human genes. To identify genes displaying differential expression among alleles it is important for the understanding of several diseases, including the cancer. Identification of genes submitted to allelic-specific differential expression is hard, mostly due to the difficulty in evaluating the expression levels of each allele independently. In this work, we developed an in-silico approach, based on the integration of public data about the human genome, gene expression data (such as cDNAs, SNPs, SAGE and MPSS) and data on polymorphisms (SNPs). We developed a database of Single Nucleotide Polymorphisms (SNPs) associated to alternative SAGE (Serial Analysis of Gene Expression) and MPSS (Massively Parallel Signature Sequencing) tags. SAGE and MPSS are genome-wide techniques developed for analysis of gene expression. Both techniques rely on the production of short marker sequences (known as tags), adjacent to restriction sites closer to the poly-A tail of messenger RNAs. Such tags are sequenced in a large scale and tag counts are used to measure the relative abundance of their corresponding transcripts. The presence of SNPs in the restriction sites or in the tag sequences might generate allelic-specific tags for the same gene, which we call alternative tags. In this work, we used the database of SNPs and associated alternative tags to identify genes submitted to allelic-specific differential gene expression. Using this approach, we identified 812 genes showing allelic-specific differential gene expression. Previous studies have shown that, among the 812 candidates, five genes are targets for genomic imprinting. While this study was being performed, work done by other groups suggested other 73 genes in our candidates list to have different expression levels for alleles in heterozygous. Aiming to verify whether variations in the expression levels of alleles existed among our candidate genes, we submitted 29 genes for experimental validation. For 12 genes, we couldnt find heterozygous individuals, thus rendering it impossible to ascertain whether the supposed expression variation was true. Among the other 17 genes analyzed, three genes presented bi-allelic expression and 14 genes have shown clear differential expression among alleles, three of the last ones displaying strict mono-allelic expression. These results suggest that our approach may contribute significantly to the identification of genes with allelic-specific differential expression

The Expression of the Immunoproteasome Subunit PSMB9 Is Related to Distinct Molecular Subtypes of Uterine Leiomyosarcoma

Background: Uterine leiomyosarcoma (uLMS) are rare and malignant tumors that arise in the myometrium cells and whose diagnosis is based on histopathological features. Identifying diagnostic biomarkers for uLMS is a challenge due to molecular heterogeneity and the scarcity of samples. In vivo and in vitro models for uLMS are urgently needed. Knockout female mice for the catalytic subunit of the immunoproteasome PSMB9 (MIM:177045) develop spontaneous uLMS. This study aimed to analyze the role of PSMB9 in uLMS tumorigenesis and patient outcome. Methods: Molecular data from 3 non-related uLMS cohorts were integrated and analyzed by proteotranscriptomic using gene expression and protein abundance levels in 68 normal adjacent myometrium (MM), 66 uterine leiomyoma (LM), and 67 uLMS. Results: the immunoproteasome pathway is upregulated and the gene PMSB9 shows heterogeneous expression values in uLMS. Quartile group analysis showed no significant difference between groups high and low PSMB9 expression groups at 3-years overall survival (OS). Using CYBERSORTx analysis we observed 9 out of 17 samples in the high group clustering together due to high M2 macrophages and CD4 memory resting, and high CD8+/PSMB9 ratio was associated with better OS. The main pathway regulated in the high group is IFNγ and in the low is the ECM pathway dependent on the proto-oncogene SRC. Conclusion: these findings suggest 2 subtypes of uLMS (immune-related and ECM-related) with different candidate mechanisms of malignancy

siRNA database for SARS-CoV-2

This projects provides database of SARS-CoV-2 targets for siRNA approaches, aiming to speed the development of new target antivirals

The Human Cell Surfaceome of Breast Tumors

Introduction. Cell surface proteins are ideal targets for cancer therapy and diagnosis. We have identified a set of more than 3700 genes that code for transmembrane proteins believed to be at human cell surface. Methods. We used a high-throuput qPCR system for the analysis of 573 cell surface protein-coding genes in 12 primary breast tumors, 8 breast cell lines, and 21 normal human tissues including breast. To better understand the role of these genes in breast tumors, we used a series of bioinformatics strategies to integrates different type, of the datasets, such as KEGG, protein-protein interaction databases, ONCOMINE, and data from, literature. Results. We found that at least 77 genes are overexpressed in breast primary tumors while at least 2 of them have also a restricted expression pattern in normal tissues. We found common signaling pathways that may be regulated in breast tumors through the overexpression of these cell surface protein-coding genes. Furthermore, a comparison was made between the genes found in this report and other genes associated with features clinically relevant for breast tumorigenesis. Conclusions. The expression profiling generated in this study, together with an integrative bioinformatics analysis, allowed us to identify putative targets for breast tumors

In Silico Analysis and Immunohistochemical Characterization of NaPi2b Protein Expression in Ovarian Carcinoma With Monoclonal Antibody Mx35

Introduction: Ovarian adenocarcinoma is frequently detected at the late stage, when therapy efficacy is limited and death occurs in up to 50% of the cases. A potential novel treatment for this disease is a monoclonal antibody that recognizes phosphate transporter sodium-dependent phosphate transporter protein 2b (NaPi2b). Materials and Methods: To better understand the expression of this protein in different histologic types of ovarian carcinomas, we immunostained 50 tumor samples with anti-NaPi2b monoclonal antibody MX35 and, in parallel, we assessed the expression of the gene encoding NaPi2b (SCL34A2) by in silico analysis of microarray data. Results: Both approaches detected higher expression of NaPi2b (SCL34A2) in ovarian carcinoma than in normal tissue. Moreover, a comprehensive analysis indicates that SCL34A2 is the only gene of the several phosphate transporters genes whose expression differentiates normal from carcinoma samples, suggesting it might exert a major role in ovarian carcinomas. Immunohistochemical and mRNA expression data have also shown that 2 histologic subtypes of ovarian carcinoma express particularly high levels of NaPi2b: serous and clear cell adenocarcinomas. Serous adenocarcinomas are the most frequent, contrasting with clear cell carcinomas, rare, and with worse prognosis. Conclusion: This identification of subgroups of patients expressing NaPi2b may be important in selecting cohorts who most likely should be included in future clinical trials, as a recently generated humanized version of MX35 has been developed.FINEPFINEPRecepta Biopharma, BrazilRecepta Biopharma, Brazi

Expression analysis of stem cell-related genes reveal OCT4 as a predictor of poor clinical outcome in medulloblastoma

Aberrant expression of stem cell-related genes in tumors may confer more primitive and aggressive traits affecting clinical outcome. Here, we investigated expression and prognostic value of the neural stem cell marker CD133, as well as of the pluripotency genes LIN28 and OCT4 in 37 samples of pediatric medulloblastoma, the most common and challenging type of embryonal tumor. While most medulloblastoma samples expressed CD133 and LIN28, OCT4 expression was found to be more sporadic, with detectable levels occurring in 48% of tumors. Expression levels of OCT4, but not CD133 or LIN28, were significantly correlated with shorter survival (P <= 0.0001). Median survival time of patients with tumors hyperexpressing OCT4 and tumors displaying low/undetectable OCT4 expression were 6 and 153 months, respectively. More importantly, when patients were clinically stratified according to their risk of tumor recurrence, positive OCT4 expression in primary tumor specimens could discriminate patients classified as average risk but which further deceased within 5 years of diagnosis (median survival time of 28 months), a poor clinical outcome typical of high risk patients. Our findings reveal a previously unknown prognostic value for OCT4 expression status in medulloblastoma, which might be used as a further indicator of poor survival and aid postoperative treatment selection, with a particular potential benefit for clinically average risk patients.INCT-Celulas Tronco em Doencas Geneticas HumanasINCTCelulas Tronco em Doencas Geneticas HumanasFAPESPFAPESPCNPqCNPqCAPESCAPE