Day 1 :
- Track 1: Functional Genomics
Track 2: Transcriptional Profiling
Track 3: m-RNA Analysis
Track 4: Cancer Genomics
Track 5: Analysis of Non-coding RNA
Cleveland State University, USA
Title: A Genome-Wide Polyribosome Profiling Revealed a Post- Transcriptional Operon as an Endogenous Defense Against Inflammation
Time : 12:30-12:50
Dr. Barsanjit Mazumder has completed his PhD at the age of 28 years from Bose Institute, Jadavpur University, India and Postdoctoral Studies from Cleveland Clinic. He is now the Professor of Molecular Genetics, in the Center for Gene regulation in Health of Disease of the Department of Biological Science of Cleveland State University. He has been awarded several major grants from NIH and American Heart Association and published more than 35 papers in high visibility journals including Cell, Molecular Cell, Molecular & Cellular Biology, and Journal of Immunology etc and served as a reviewer of many funding organizations.
Emerging evidence suggests that the transcriptome does not always faithfully represent the proteome. Using Affymetrix Gene Chip analysis of the polyribosome-profiled mRNAs from the IFN-g activated monocytes/macrophages we have identified a cohort of mRNAs under translation control. These mRNAs encode different chemokines and their receptors. Our subsequent studies have identified these mRNAs as a member of a single posttranscriptional operon regulated by ribosomal protein L13adependent translational silencing. Release of L13a from 60S ribosomal subunit is required for this process and the silencing is mediated by the presence of GAIT (Gamma Activated Inhibitor of Translation) element in the 3ʼUTRs of the target mRNAs. To test the physiological consequence of this L13a-dependent translational silencing in macrophage we have created viable macrophagespecific L13a-knockout (KO) mice (L13aflox/floxLysMCre+). In these mice the termination of inflammation is severely compromised due to the uncontrolled synthesis of several inflammatory proteins e.g. chemokine and chemokine receptors. Upon LPS-induced endotoxemia, these animals displayed significantly reduced survival rates and symptoms of severe inflammation. Recently we have tested the relevance of this translational silencing in two other murine models of human disease caused by uncontrolled inflammation e.g. High-Fat diet-induced atherosclerosis and DSSinduced experimental colitis. Both of these studies revealed the essential role of L13a-dependent translational silencing as an endogenous defense against these diseases. Although no disease related SNPs have yet been reported in L13a gene however, we anticipate that manipulation of such pathways may offer novel therapeutic strategies against human inflammatory diseases.
Girish C Shukla is an Associate Professor of Biology. He received his B.S. in Chemistry from Delhi University and Ph.D. in Molecular Biology and Biochemistry from Brunel University, London, in 1997. He has been a faculty member of Cleveland State University since 2006.
Master transcriptional regulator Androgen Receptor (AR) remained a fascinating and an enigmatic molecule, particularly it causative role in Prostate cancer biology. Major impetus in PCa research is currently focused on the development of new generation of therapeutics to target AR expression, in castration-resistant stage of the disease. 920 amino acid coding AR gene encompasses over 180 kilobase (kb) of X-chromosome containing eight exons that produces a nearly 10.7 kb AR mRNA. The fully processed mature AR mRNA account for only 26% of total coding capacity and most of the transcript codes for noncoding regions that includes 5 and 3 UTRs. However, functional roles of UTRs in AR gene expression, principally its regulatory involvement in development of CRPC remained indefinable. Our research is focusing on understanding the functional roles of 6.8 kb long AR 3 UTR in AR gene expression and especially the molecular mechanism that revitalizes AR expression in CRPC. We have shown that a number of regulatory noncoding miRNAs play a critical 3 UTR targeting role in AR gene expression and has potential therapeutic implications. Here we show a synergistic approach of targeting AR expression mediated via its 3 UTR, using a miRNA cocktail combinatorial approach. In addition, we are investigating the potential functional association of 3 UTR in AR gene expression and implication in metastatic CRPC.
VTT Brasil, Brazil
Time : 14:10-14:30
Junio Cota has completed his Ph.D at the age of 27 years from University of Campinas, Brazil. He worked for three years (2010-2013) as a research associate at Brazilian Bioethanol Science and Technology Laboratory, and now he is a research scientist in Biotechnology at VTT Brasil, a Finnish Technical Research Center. He has published more than 17 papers in reputed journals and 5 chapters in international books. Furthermore he has been talked in some reputed international conferences.
The phosphatase and tensin homolog (PTEN) tumor suppressor gene is one of the most frequently mutated genes in endometrial cancer, mainly in the endometrioid (ENDO) subtype and less commonly in the serous subtype. The goal of the study was to explore the role of PTEN regulating miRs in the two histological types of endometrial cancer using TCGA data. We defined PTEN loss as one MAD less than the median value of the normalized PTEN data generated from reverse phase protein arrays (RPPA), with PTEN-loss samples consisting of 15% of all samples. The PTEN-loss samples are primarily ENDO subtype. PTEN loss is associated with a higher risk of disease progression in the ENDO subtype but a lower risk in the serous group (not significant likely due to the low number of events in the TCGA sample set). Of the 492 miRs with detectable expression levels, 231 are differentially expressed between the ENDO and serous subtypes. Five miRs show significant association with overall survival (OS) in the ENDO subtype and none in the serous subtype. Within the ENDO subtype, two miRs are significantly associated with OS in the high microsatellite instability (MSI-H) samples both of which are significantly correlated with PTEN protein levels. While the other three miRs are significantly associated with OS in MSI-stable (MSS) samples only one of the miRs is significantly correlated with PTEN protein expression. Further analysis will explore the relationship between miRs and functional PTEN with a focus on the different subtypes in endometrial cancer.
University of Florida, USA
Title: The coding potential of pseudomonas aeruginosa: Gene discovery across strains by computational comparative genomics and ribosome profiling
Time : 14:30-14:50
Luciano Brocchieri has completed his Ph.D. in theoretical population genetics from the University of Parma, Italy, and postdoctoral studies at Stanford University, Department of Mathematics. He was Senior Scientist at Stanford University, Department of Mathematics and he is now Assistant Professor at the University of Florida, Department of Medicine. Dr. Brocchieri research is focused on the analysis of the evolution of gene families and on the development of bioinformatics methods for the identification and analysis of gene sequences. Dr. Brocchieri is the author of several papers, reviews and commentaries published in international reputed scientific journals.
Pseudomonas aeruginosa is an opportunistic pathogen of growing relevance for hospitalized patients and in particular in the development of cystic fibrosis. Complete genome sequences of several strains of P. aeruginosa have been sequenced in an effort to identify the genetic basis of the differences in virulence observed among strains. Interpretations of the results of comparative genomics rely on accurate and comparable annotations of genomic features across strains. To compare as accurately as possible the coding potential of different P. aeruginosa strains, we used a hybrid approach combining computational and experimental analyses. Potential coding regions were identified in all strains combining the results of four popular computational gene prediction methods with evolutionary conservation analysis and our recently-developed approach for computational frame-analysis, based on the identification of sequence segments with statistically significant 3-base compositional periodicity indicative of the presence of codon structures. Furthermore, we experimentally identified on a transcriptomic scale coding regions actively undergoing translation in the reference strain P. aeruginosa PAO1, using the recently developed technique of ribosome profiling. This analysis was repeated in control growth and in coditions of oxidative stress, which is relevant to the infection of the cystic fibrotic lung. These analyses allowed us to identify several genes whose distribution across strains was not reflected by published annotations. By ribosome profiling in P. aeruginosa PAO1 we also identified genes that could not be predicted computationally and precisely defined the position of the start-of-translation of several genes. Furthermore, we characterized changes in patterns of translation related to oxidative stress. Our analyses significantly enhance our understanding of the coding potential of the different strains of P. aeruginosa and provide for the first time information on the regulation of translation in environmental conditions relevant to the interaction with the human host.
Associate Professor, Cincinnati Childrens Hospital Medical Center, USA
Title: Single-cell RNA-seq profiling identified molecular signatures and transcriptional networks regulating lung maturation
Time : 14:50-15:10
Yan Xu is presently an Associate Professor at Cincinnati Childrens Hospital Medical Center and the Bioinformatics Core Director of the Perinatal Institute. Dr. Xu was graduated from Shanghai Medical University in 1986. She completed her Ph.D from University of South Alabama in 1997 and postdoctoral training from University of Colorado in 2000. Dr. Xus research is focused on the identification of gene signatures, regulatory networks, and biological pathways controlling lung maturation and disease. She has published 57 peer reviewed papers and served as reviewer and editor for a number of reputed scientific journals.
Lung formation and function are orchestrated by a diversity of cell signaling and transcriptional interactions among progenitor cells that are accomplished at the level of individual cells that are integrated by paracrine interactions among the many cells that comprise the lung. In the present study, we used massive parallel DNA sequencing coupled with an unbiased analytic approach to identify molecular mRNA signatures in single cells isolated from the entire embryonic mouse lung at the saccular phase (E16.5) of morphogenesis. Through integrative bioinformatics and systems biology analysis of single-cell RNA-seq data, we identified major cell types in the fetal mouse lung. A diversity of epithelial, endothelial, smooth muscle, bone marrow derived, and fibroblastic cell types were classified by their RNA expression similarity within cell type groups. Unique cell-specific gene signatures, key regulators, bioprocesses and functional profiles associated with each cell type and across cell types, via paracrine signaling, were identified. Single-cell mRNA-Seq analysis revealed the spectrum of transcriptional heterogeneity present within closely related pulmonary progenitor cells. We developed a bioinformatics pipeline to analyze the complex and extensive single-cell RNA data. The data provide a rich information base facilitating the understanding of lung maturation at high resolution and identifying the genetic framework that regulates cell fates during lung maturation (Supported by R01HL105433, U01 HL122642).
University of Pennsylvania, USA
Time : 15:10-15:30
Kyoung-Jae Won has completed his Ph.D. University of Southampton, UK in 2006 and postdoctoral studies from University of Copenhagen, Denmark and University of California, San Diego. He is a research assistant professor of Genetics at the University of Pennsylvania. He has published more than 20 papers in reputed journals.
Rosiglitazone (rosi) is an insulin sensitizing drug that functions as a ligand for PPAR and remodels the transcriptome of mature adipocytes. However, the direct effects of rosi on genomic transcription have not been evaluated. Here, using global run-on followed by deep sequencing (GRO-seq), we demonstrate that rosi has dramatic effects on RNA transcription in mature adipocytes.
Tokyo University of Agriculture and Technology, Japan
Title: Construction of the big data processing environment and mathematical modeling for psychiatric diagnosis in a cloud computing system
Time : 15:30-15:50
Kazuo Ishii, Ph.D. is the Professor of Genome Science of the Graduate School of Agriculture of Tokyo University of Agriculture and Technology in Japan. After receiving the PhD degree from the Graduate School of Medicine of the University of Tokushima in 1995, he started professional career in genomic sciences. From 1997 to 2000, he participated in human genome sequencing project at the University of Tokyo and RIKEN Genomic Sciences Center. After that, he worked for SNPs discovery at Centre National de Genotypage, Evry, France. In 2003, he changed his specialty to bioinformatics, especially such as data analysis and data mining. He performed bioinformatics research at Osaka Medical Center for Cancer and Cardiovascular Diseases (2003-2005), Tokyo University of Science (2005-2009), and Northwestern University, Feinberg School of Medicine (2010). In 2011, he got the present job and he has dedicated to the Human Resource Development Program in Agricultural Genome Sciences in Tokyo University of Agriculture and Technology, funding supported from the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT).
A big data processing environment in the cloud computing system AWS (Amazon Web Services) was constructed to develop a psychiatric diagnosis system. And large-scale data analysis with genomic data, such as quantitative PCR, microarray and next generation sequencing technologies, was performed. The analysis system consisted of Hadoop, MapReduce, NoSQL, R and other open source software. To analyze multidimentional data, discrimination analysis, cluster analysis, machine learning, bayesian algorithm and other data mining methods were evaluated. Some explanatory variables with high sensitivity and specificity were able to selected with this system and construct of mathematical model using selected explanatory variables were achieved.In this speech, construct of data processing system and mathematical modeling will be introduced and discussed.
University of Las Palmas de Gran Canaria, Spain
Title: DNA Binding Sites for Transcriptional Activators and Expression and Activation of Resistance Genes
Time : 15:50-16:10
Maria M. Tavio MD completed her Ph.D. at the age of 27 years from University of Las Palmas de Gran Canaria and postdoctoral studies from The London Hospital Medical College, Queen Mary´s University of London, UK and the Faculty of Medicine of L´ Aquila University, Italy. She is titular professor at the University of Las Palmas de Gran Canaria. She has published more than 40 papers on quinolone and beta-lactam resistance including her article on QnrS1 protein characterization derived from her recent work at Harvard Medical School, USA. She also serves as assessor for national and European research projects on antimicrobial resistance.
The expression of a gene moves through many stages, each of which offers an opportunity for regulation. By far the most common type of regulation occurs at the first stage, when RNA is made. Genes that are regulated at this level are said to be transcriptionally regulated. Transcriptional regulation occurs primarily through proteins called transcriptional regulators, which usually bind to DNA, often with helix-turn-helix motifs. The techniques of comparative genomics have made it possible to identify repressor and activator genes in a wide of bacteria. These transcriptional regulatory proteins belong to a limited number of known families, although they regulate operons with very different functions and respond to different effectors. There are at least 15 different families of transcriptional regulators, some of them consist only of repressors, others consist only of activators, and some consist of both repressors and activators. Here several transcriptional activators belonging to the families AraC/XylS, LuxR, LysR and TetR, involved in the development of antibiotic resistance to beta-lactams and quinolones as well as their DNA binding sites are analyzed and compared. Likewise, we will show our recent findings on the role of transcriptional regulatory proteins in the expression of beta-lactam and quinolone resistance genes.