Integrative Analysis of Longitudinal Metabolomics Data from a Personal Multi-Omics Profile
Stanberry, Larissa; Mias, George I.; Haynes, Winston; Higdon, Roger; Snyder, Michael; Kolker, Eugene
2013-01-01
The integrative personal omics profile (iPOP) is a pioneering study that combines genomics, transcriptomics, proteomics, metabolomics and autoantibody profiles from a single individual over a 14-month period. The observation period includes two episodes of viral infection: a human rhinovirus and a respiratory syncytial virus. The profile studies give an informative snapshot into the biological functioning of an organism. We hypothesize that pathway expression levels are associated with disease status. To test this hypothesis, we use biological pathways to integrate metabolomics and proteomics iPOP data. The approach computes the pathways’ differential expression levels at each time point, while taking into account the pathway structure and the longitudinal design. The resulting pathway levels show strong association with the disease status. Further, we identify temporal patterns in metabolite expression levels. The changes in metabolite expression levels also appear to be consistent with the disease status. The results of the integrative analysis suggest that changes in biological pathways may be used to predict and monitor the disease. The iPOP experimental design, data acquisition and analysis issues are discussed within the broader context of personal profiling. PMID:24958148
Bastarrachea, Raúl A.; Gallegos-Cabriales, Esther C.; Nava-González, Edna J.; Haack, Karin; Voruganti, V. Saroja; Charlesworth, Jac; Laviada-Molina, Hugo A.; Veloz-Garza, Rosa A.; Cardenas-Villarreal, Velia Margarita; Valdovinos-Chavez, Salvador B.; Gomez-Aguilar, Patricia; Meléndez, Guillermo; López-Alvarenga, Juan Carlos; Göring, Harald H. H.; Cole, Shelley A.; Blangero, John; Comuzzie, Anthony G.; Kent, Jack W.
2012-01-01
Whole-transcriptome expression profiling provides novel phenotypes for analysis of complex traits. Gene expression measurements reflect quantitative variation in transcript-specific messenger RNA levels and represent phenotypes lying close to the action of genes. Understanding the genetic basis of gene expression will provide insight into the processes that connect genotype to clinically significant traits representing a central tenet of system biology. Synchronous in vivo expression profiles of lymphocytes, muscle, and subcutaneous fat were obtained from healthy Mexican men. Most genes were expressed at detectable levels in multiple tissues, and RNA levels were correlated between tissue types. A subset of transcripts with high reliability of expression across tissues (estimated by intraclass correlation coefficients) was enriched for cis-regulated genes, suggesting that proximal sequence variants may influence expression similarly in different cellular environments. This integrative global gene expression profiling approach is proving extremely useful for identifying genes and pathways that contribute to complex clinical traits. Clearly, the coincidence of clinical trait quantitative trait loci and expression quantitative trait loci can help in the prioritization of positional candidate genes. Such data will be crucial for the formal integration of positional and transcriptomic information characterized as genetical genomics. PMID:22797999
Bourdon-Lacombe, Julie A; Moffat, Ivy D; Deveau, Michelle; Husain, Mainul; Auerbach, Scott; Krewski, Daniel; Thomas, Russell S; Bushel, Pierre R; Williams, Andrew; Yauk, Carole L
2015-07-01
Toxicogenomics promises to be an important part of future human health risk assessment of environmental chemicals. The application of gene expression profiles (e.g., for hazard identification, chemical prioritization, chemical grouping, mode of action discovery, and quantitative analysis of response) is growing in the literature, but their use in formal risk assessment by regulatory agencies is relatively infrequent. Although additional validations for specific applications are required, gene expression data can be of immediate use for increasing confidence in chemical evaluations. We believe that a primary reason for the current lack of integration is the limited practical guidance available for risk assessment specialists with limited experience in genomics. The present manuscript provides basic information on gene expression profiling, along with guidance on evaluating the quality of genomic experiments and data, and interpretation of results presented in the form of heat maps, pathway analyses and other common approaches. Moreover, potential ways to integrate information from gene expression experiments into current risk assessment are presented using published studies as examples. The primary objective of this work is to facilitate integration of gene expression data into human health risk assessments of environmental chemicals. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.
Amar, David; Hait, Tom; Izraeli, Shai; Shamir, Ron
2015-09-18
Genome-wide expression profiling has revolutionized biomedical research; vast amounts of expression data from numerous studies of many diseases are now available. Making the best use of this resource in order to better understand disease processes and treatment remains an open challenge. In particular, disease biomarkers detected in case-control studies suffer from low reliability and are only weakly reproducible. Here, we present a systematic integrative analysis methodology to overcome these shortcomings. We assembled and manually curated more than 14,000 expression profiles spanning 48 diseases and 18 expression platforms. We show that when studying a particular disease, judicious utilization of profiles from other diseases and information on disease hierarchy improves classification quality, avoids overoptimistic evaluation of that quality, and enhances disease-specific biomarker discovery. This approach yielded specific biomarkers for 24 of the analyzed diseases. We demonstrate how to combine these biomarkers with large-scale interaction, mutation and drug target data, forming a highly valuable disease summary that suggests novel directions in disease understanding and drug repurposing. Our analysis also estimates the number of samples required to reach a desired level of biomarker stability. This methodology can greatly improve the exploitation of the mountain of expression profiles for better disease analysis. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Cross-platform method for identifying candidate network biomarkers for prostate cancer.
Jin, G; Zhou, X; Cui, K; Zhang, X-S; Chen, L; Wong, S T C
2009-11-01
Discovering biomarkers using mass spectrometry (MS) and microarray expression profiles is a promising strategy in molecular diagnosis. Here, the authors proposed a new pipeline for biomarker discovery that integrates disease information for proteins and genes, expression profiles in both genomic and proteomic levels, and protein-protein interactions (PPIs) to discover high confidence network biomarkers. Using this pipeline, a total of 474 molecules (genes and proteins) related to prostate cancer were identified and a prostate-cancer-related network (PCRN) was derived from the integrative information. Thus, a set of candidate network biomarkers were identified from multiple expression profiles composed by eight microarray datasets and one proteomics dataset. The network biomarkers with PPIs can accurately distinguish the prostate patients from the normal ones, which potentially provide more reliable hits of biomarker candidates than conventional biomarker discovery methods.
Jung, Seung-Hyun; Shin, Seung-Hun; Yim, Seon-Hee; Choi, Hye-Sun; Lee, Sug-Hyung; Chung, Yeun-Jun
2009-07-31
Recently, microarray-based comparative genomic hybridization (array-CGH) has emerged as a very efficient technology with higher resolution for the genome-wide identification of copy number alterations (CNA). Although CNAs are thought to affect gene expression, there is no platform currently available for the integrated CNA-expression analysis. To achieve high-resolution copy number analysis integrated with expression profiles, we established human 30k oligoarray-based genome-wide copy number analysis system and explored the applicability of this system for integrated genome and transcriptome analysis using MDA-MB-231 cell line. We compared the CNAs detected by the oligoarray with those detected by the 3k BAC array for validation. The oligoarray identified the single copy difference more accurately and sensitively than the BAC array. Seventeen CNAs detected by both platforms in MDA-MB-231 such as gains of 5p15.33-13.1, 8q11.22-8q21.13, 17p11.2, and losses of 1p32.3, 8p23.3-8p11.21, and 9p21 were consistently identified in previous studies on breast cancer. There were 122 other small CNAs (mean size 1.79 mb) that were detected by oligoarray only, not by BAC-array. We performed genomic qPCR targeting 7 CNA regions, detected by oligoarray only, and one non-CNA region to validate the oligoarray CNA detection. All qPCR results were consistent with the oligoarray-CGH results. When we explored the possibility of combined interpretation of both DNA copy number and RNA expression profiles, mean DNA copy number and RNA expression levels showed a significant correlation. In conclusion, this 30k oligoarray-CGH system can be a reasonable choice for analyzing whole genome CNAs and RNA expression profiles at a lower cost.
Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko
2016-06-01
Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.
Microarray profiling of chemical-induced effects is being increasingly used in medium and high-throughput formats. In this study, we describe computational methods to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), ...
Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang
2018-06-15
Investigating the potential biological function of differential changed genes through integrating multiple omics data including miRNA and mRNA expression profiles, is always hot topic. However, how to evaluate the repression effect on target genes integrating miRNA and mRNA expression profiles are not fully solved. In this study, we provide an analyzing method by integrating both miRNAs and mRNAs expression data simultaneously. Difference analysis was adopted based on the repression score, then significantly repressed mRNAs were screened out by DEGseq. Pathway analysis for the significantly repressed mRNAs shows that multiple pathways such as MAPK signaling pathway, TGF-beta signaling pathway and so on, may correlated to the colorectal cancer(CRC). Focusing on the MAPK signaling pathway, a miRNA-mRNA network that centering the cell fate genes was constructed. Finally, the miRNA-mRNAs that potentially important in the CRC carcinogenesis were screened out and scored by impact index. Copyright © 2018 Elsevier B.V. All rights reserved.
Zhang, Lei; Ma, Shiyun; Wang, Huailiang; Su, Hang; Su, Ke; Li, Longjie
2017-11-15
The purpose of our study was to identify new pathogenic genes used for exploring the pathogenesis of rheumatoid arthritis (RA). To screen pathogenic genes of RA, an integrated analysis was performed by using the microarray datasets in RA derived from the Gene Expression Omnibus (GEO) database. The functional annotation and potential pathways of differentially expressed genes (DEGs) were further discovered by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Afterwards, the integrated analysis of DNA methylation and gene expression profiling was used to screen crucial genes. In addition, we used RT-PCR and MSP to verify the expression levels and methylation status of these crucial genes in 20 synovial biopsy samples obtained from 10 RA model mice and 10 normal mice. BCL11B, CCDC88C, FCRLA and APOL6 were both up-regulated and hypomethylated in RA according to integrated analysis, RT-PCR and MSP verification. Four crucial genes (BCL11B, CCDC88C, FCRLA and APOL6) identified and analyzed in this study might be closely connected with the pathogenesis of RA. Copyright © 2017. Published by Elsevier B.V.
NASA Astrophysics Data System (ADS)
Suzuki, Kunihiro
2009-04-01
Ion implantation profiles are expressed by the Pearson function with first, second, third, and fourth moment parameters of Rp, ΔRp, γ, and β. We derived an analytical model for these profile moments by solving a Lindhard-Scharf-Schiott (LSS) integration equation using perturbation approximation. This analytical model reproduces Monte Carlo data that were well calibrated to reproduce a vast experimental database. The extended LSS theory is vital for instantaneously predicting ion implantation profiles with any combination of incident ions and substrate atoms including their energy dependence.
Rani, Lata; Mathur, Nitin; Gupta, Ritu; Gogia, Ajay; Kaur, Gurvinder; Dhanjal, Jaspreet Kaur; Sundar, Durai; Kumar, Lalit; Sharma, Atul
2017-01-01
In chronic lymphocytic leukemia (CLL), epigenomic and genomic studies have expanded the existing knowledge about the disease biology and led to the identification of potential biomarkers relevant for implementation of personalized medicine. In this study, an attempt has been made to examine and integrate the global DNA methylation changes with gene expression profile and their impact on clinical outcome in early stage CLL patients. The integration of DNA methylation profile ( n = 14) with the gene expression profile ( n = 21) revealed 142 genes as hypermethylated-downregulated and; 62 genes as hypomethylated-upregulated in early stage CLL patients compared to CD19+ B-cells from healthy individuals. The mRNA expression levels of 17 genes identified to be differentially methylated and/or differentially expressed was further examined in early stage CLL patients ( n = 93) by quantitative real time PCR (RQ-PCR). Significant differences were observed in the mRNA expression of MEIS1 , PMEPA1 , SOX7 , SPRY1 , CDK6 , TBX2 , and SPRY2 genes in CLL cells as compared to B-cells from healthy individuals. The analysis in the IGHV mutation based categories (Unmutated = 39, Mutated = 54) revealed significantly higher mRNA expression of CRY1 and PAX9 genes in the IGHV unmutated subgroup ( p < 0.001). The relative risk of treatment initiation was significantly higher among patients with high expression of CRY1 (RR = 1.91, p = 0.005) or PAX9 (RR = 1.87, p = 0.001). High expression of CRY1 (HR: 3.53, p < 0.001) or PAX9 (HR: 3.14, p < 0.001) gene was significantly associated with shorter time to first treatment. The high expression of PAX9 gene (HR: 3.29, 95% CI 1.172-9.272, p = 0.016) was also predictive of shorter overall survival in CLL. The DNA methylation changes associated with mRNA expression of CRY1 and PAX9 genes allow risk stratification of early stage CLL patients. This comprehensive analysis supports the concept that the epigenetic changes along with the altered expression of genes have the potential to predict clinical outcome in early stage CLL patients.
An Integrated Approach for RNA-seq Data Normalization.
Yang, Shengping; Mercante, Donald E; Zhang, Kun; Fang, Zhide
2016-01-01
DNA copy number alteration is common in many cancers. Studies have shown that insertion or deletion of DNA sequences can directly alter gene expression, and significant correlation exists between DNA copy number and gene expression. Data normalization is a critical step in the analysis of gene expression generated by RNA-seq technology. Successful normalization reduces/removes unwanted nonbiological variations in the data, while keeping meaningful information intact. However, as far as we know, no attempt has been made to adjust for the variation due to DNA copy number changes in RNA-seq data normalization. In this article, we propose an integrated approach for RNA-seq data normalization. Comparisons show that the proposed normalization can improve power for downstream differentially expressed gene detection and generate more biologically meaningful results in gene profiling. In addition, our findings show that due to the effects of copy number changes, some housekeeping genes are not always suitable internal controls for studying gene expression. Using information from DNA copy number, integrated approach is successful in reducing noises due to both biological and nonbiological causes in RNA-seq data, thus increasing the accuracy of gene profiling.
Lee, Mikyung; Kim, Yangseok
2009-12-16
Genomic alterations frequently occur in many cancer patients and play important mechanistic roles in the pathogenesis of cancer. Furthermore, they can modify the expression level of genes due to altered copy number in the corresponding region of the chromosome. An accumulating body of evidence supports the possibility that strong genome-wide correlation exists between DNA content and gene expression. Therefore, more comprehensive analysis is needed to quantify the relationship between genomic alteration and gene expression. A well-designed bioinformatics tool is essential to perform this kind of integrative analysis. A few programs have already been introduced for integrative analysis. However, there are many limitations in their performance of comprehensive integrated analysis using published software because of limitations in implemented algorithms and visualization modules. To address this issue, we have implemented the Java-based program CHESS to allow integrative analysis of two experimental data sets: genomic alteration and genome-wide expression profile. CHESS is composed of a genomic alteration analysis module and an integrative analysis module. The genomic alteration analysis module detects genomic alteration by applying a threshold based method or SW-ARRAY algorithm and investigates whether the detected alteration is phenotype specific or not. On the other hand, the integrative analysis module measures the genomic alteration's influence on gene expression. It is divided into two separate parts. The first part calculates overall correlation between comparative genomic hybridization ratio and gene expression level by applying following three statistical methods: simple linear regression, Spearman rank correlation and Pearson's correlation. In the second part, CHESS detects the genes that are differentially expressed according to the genomic alteration pattern with three alternative statistical approaches: Student's t-test, Fisher's exact test and Chi square test. By successive operations of two modules, users can clarify how gene expression levels are affected by the phenotype specific genomic alterations. As CHESS was developed in both Java application and web environments, it can be run on a web browser or a local machine. It also supports all experimental platforms if a properly formatted text file is provided to include the chromosomal position of probes and their gene identifiers. CHESS is a user-friendly tool for investigating disease specific genomic alterations and quantitative relationships between those genomic alterations and genome-wide gene expression profiling.
MethHC: a database of DNA methylation and gene expression in human cancer.
Huang, Wei-Yun; Hsu, Sheng-Da; Huang, Hsi-Yuan; Sun, Yi-Ming; Chou, Chih-Hung; Weng, Shun-Long; Huang, Hsien-Da
2015-01-01
We present MethHC (http://MethHC.mbc.nctu.edu.tw), a database comprising a systematic integration of a large collection of DNA methylation data and mRNA/microRNA expression profiles in human cancer. DNA methylation is an important epigenetic regulator of gene transcription, and genes with high levels of DNA methylation in their promoter regions are transcriptionally silent. Increasing numbers of DNA methylation and mRNA/microRNA expression profiles are being published in different public repositories. These data can help researchers to identify epigenetic patterns that are important for carcinogenesis. MethHC integrates data such as DNA methylation, mRNA expression, DNA methylation of microRNA gene and microRNA expression to identify correlations between DNA methylation and mRNA/microRNA expression from TCGA (The Cancer Genome Atlas), which includes 18 human cancers in more than 6000 samples, 6548 microarrays and 12 567 RNA sequencing data. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Zhang, Wenli; Muck-Hausl, Martin; Wang, Jichang; Sun, Chuanbo; Gebbing, Maren; Miskey, Csaba; Ivics, Zoltan; Izsvak, Zsuzsanna; Ehrhardt, Anja
2013-01-01
We recently developed adenovirus/transposase hybrid-vectors utilizing the previously described hyperactive Sleeping Beauty (SB) transposase HSB5 for somatic integration and we could show stabilized transgene expression in mice and a canine model for hemophilia B. However, the safety profile of these hybrid-vectors with respect to vector dose and genotoxicity remains to be investigated. Herein, we evaluated this hybrid-vector system in C57Bl/6 mice with escalating vector dose settings. We found that in all mice which received the hyperactive SB transposase, transgene expression levels were stabilized in a dose-dependent manner and that the highest vector dose was accompanied by fatalities in mice. To analyze potential genotoxic side-effects due to somatic integration into host chromosomes, we performed a genome-wide integration site analysis using linker-mediated PCR (LM-PCR) and linear amplification-mediated PCR (LAM-PCR). Analysis of genomic DNA samples obtained from HSB5 treated female and male mice revealed a total of 1327 unique transposition events. Overall the chromosomal distribution pattern was close-to-random and we observed a random integration profile with respect to integration into gene and non-gene areas. Notably, when using the LM-PCR protocol, 27 extra-chromosomal integration events were identified, most likely caused by transposon excision and subsequent transposition into the delivered adenoviral vector genome. In total, this study provides a careful evaluation of the safety profile of adenovirus/Sleeping Beauty transposase hybrid-vectors. The obtained information will be useful when designing future preclinical studies utilizing hybrid-vectors in small and large animal models. PMID:24124483
Liu, Yuesheng; Ji, Yuqiang; Li, Min; Wang, Min; Yi, Xiaoqing; Yin, Chunyan; Wang, Sisi; Zhang, Meizhen; Zhao, Zhao; Xiao, Yanfeng
2018-06-08
Long noncoding RNAs (lncRNAs) have an important role in adipose tissue function and energy metabolism homeostasis, and abnormalities may lead to obesity. To investigate whether lncRNAs are involved in childhood obesity, we investigated the differential expression profile of lncRNAs in obese children compared with non-obese children. A total number of 1268 differentially expressed lncRNAs and 1085 differentially expressed mRNAs were identified. Gene Ontology (GO) and pathway analysis revealed that these lncRNAs were involved in varied biological processes, including the inflammatory response, lipid metabolic process, osteoclast differentiation and fatty acid metabolism. In addition, the lncRNA-mRNA co-expression network and the protein-protein interaction (PPI) network were constructed to identify hub regulatory lncRNAs and genes based on the microarray expression profiles. This study for the first time identifies an expression profile of differentially expressed lncRNAs in obese children and indicated hub lncRNA RP11-20G13.3 attenuated adipogenesis of preadipocytes, which is conducive to the search for new diagnostic and therapeutic strategies of childhood obesity.
Huang, Lei; Zhao, Shuangping; Frasor, Jonna M.; Dai, Yang
2011-01-01
Approximately half of estrogen receptor (ER) positive breast tumors will fail to respond to endocrine therapy. Here we used an integrative bioinformatics approach to analyze three gene expression profiling data sets from breast tumors in an attempt to uncover underlying mechanisms contributing to the development of resistance and potential therapeutic strategies to counteract these mechanisms. Genes that are differentially expressed in tamoxifen resistant vs. sensitive breast tumors were identified from three different publically available microarray datasets. These differentially expressed (DE) genes were analyzed using gene function and gene set enrichment and examined in intrinsic subtypes of breast tumors. The Connectivity Map analysis was utilized to link gene expression profiles of tamoxifen resistant tumors to small molecules and validation studies were carried out in a tamoxifen resistant cell line. Despite little overlap in genes that are differentially expressed in tamoxifen resistant vs. sensitive tumors, a high degree of functional similarity was observed among the three datasets. Tamoxifen resistant tumors displayed enriched expression of genes related to cell cycle and proliferation, as well as elevated activity of E2F transcription factors, and were highly correlated with a Luminal intrinsic subtype. A number of small molecules, including phenothiazines, were found that induced a gene signature in breast cancer cell lines opposite to that found in tamoxifen resistant vs. sensitive tumors and the ability of phenothiazines to down-regulate cyclin E2 and inhibit proliferation of tamoxifen resistant breast cancer cells was validated. Our findings demonstrate that an integrated bioinformatics approach to analyze gene expression profiles from multiple breast tumor datasets can identify important biological pathways and potentially novel therapeutic options for tamoxifen-resistant breast cancers. PMID:21789246
High throughput gene expression profiling: a molecular approach to integrative physiology
Liang, Mingyu; Cowley, Allen W; Greene, Andrew S
2004-01-01
Integrative physiology emphasizes the importance of understanding multiple pathways with overlapping, complementary, or opposing effects and their interactions in the context of intact organisms. The DNA microarray technology, the most commonly used method for high-throughput gene expression profiling, has been touted as an integrative tool that provides insights into regulatory pathways. However, the physiology community has been slow in acceptance of these techniques because of early failure in generating useful data and the lack of a cohesive theoretical framework in which experiments can be analysed. With recent advances in both technology and analysis, we propose a concept of multidimensional integration of physiology that incorporates data generated by DNA microarray and other functional, genomic, and proteomic approaches to achieve a truly integrative understanding of physiology. Analysis of several studies performed in simpler organisms or in mammalian model animals supports the feasibility of such multidimensional integration and demonstrates the power of DNA microarray as an indispensable molecular tool for such integration. Evaluation of DNA microarray techniques indicates that these techniques, despite limitations, have advanced to a point where the question-driven profiling research has become a feasible complement to the conventional, hypothesis-driven research. With a keen sense of homeostasis, global regulation, and quantitative analysis, integrative physiologists are uniquely positioned to apply these techniques to enhance the understanding of complex physiological functions. PMID:14678487
Shvedova, Anna A.; Yanamala, Naveena; Kisin, Elena R.; Khailullin, Timur O.; Birch, M. Eileen; Fatkhutdinova, Liliya M.
2016-01-01
Background As the application of carbon nanotubes (CNT) in consumer products continues to rise, studies have expanded to determine the associated risks of exposure on human and environmental health. In particular, several lines of evidence indicate that exposure to multi-walled carbon nanotubes (MWCNT) could pose a carcinogenic risk similar to asbestos fibers. However, to date the potential markers of MWCNT exposure are not yet explored in humans. Methods In the present study, global mRNA and ncRNA expression profiles in the blood of exposed workers, having direct contact with MWCNT aerosol for at least 6 months (n = 8), were compared with expression profiles of non-exposed (n = 7) workers (e.g., professional and/or technical staff) from the same manufacturing facility. Results Significant changes in the ncRNA and mRNA expression profiles were observed between exposed and non-exposed worker groups. An integrative analysis of ncRNA-mRNA correlations was performed to identify target genes, functional relationships, and regulatory networks in MWCNT-exposed workers. The coordinated changes in ncRNA and mRNA expression profiles revealed a set of miRNAs and their target genes with roles in cell cycle regulation/progression/control, apoptosis and proliferation. Further, the identified pathways and signaling networks also revealed MWCNT potential to trigger pulmonary and cardiovascular effects as well as carcinogenic outcomes in humans, similar to those previously described in rodents exposed to MWCNTs. Conclusion This study is the first to investigate aberrant changes in mRNA and ncRNA expression profiles in the blood of humans exposed to MWCNT. The significant changes in several miRNAs and mRNAs expression as well as their regulatory networks are important for getting molecular insights into the MWCNT-induced toxicity and pathogenesis in humans. Further large-scale prospective studies are necessary to validate the potential applicability of such changes in mRNAs and miRNAs as prognostic markers of MWCNT exposures in humans. PMID:26930275
Network-Induced Classification Kernels for Gene Expression Profile Analysis
Dror, Gideon; Shamir, Ron
2012-01-01
Abstract Computational classification of gene expression profiles into distinct disease phenotypes has been highly successful to date. Still, robustness, accuracy, and biological interpretation of the results have been limited, and it was suggested that use of protein interaction information jointly with the expression profiles can improve the results. Here, we study three aspects of this problem. First, we show that interactions are indeed relevant by showing that co-expressed genes tend to be closer in the network of interactions. Second, we show that the improved performance of one extant method utilizing expression and interactions is not really due to the biological information in the network, while in another method this is not the case. Finally, we develop a new kernel method—called NICK—that integrates network and expression data for SVM classification, and demonstrate that overall it achieves better results than extant methods while running two orders of magnitude faster. PMID:22697242
Activity-based protein profiling for biochemical pathway discovery in cancer
Nomura, Daniel K.; Dix, Melissa M.; Cravatt, Benjamin F.
2011-01-01
Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment. PMID:20703252
Ge, Fei; Cao, Fenglin; Li, Haitao; Wang, Ping; Xu, Mengyuan; Song, Peng; Li, Xiaoxia; Wang, Shuye; Li, Jinmei; Han, Xueying; Zhao, Yanhong; Su, Yanhua; Li, Yinghua; Fan, Shengjin; Li, Limin; Zhou, Jin
2016-01-01
The pathogenesis of therapy-induced differentiation syndrome (DS) in patients with acute promyelocytic leukemia (APL) remains unclear. In this study, mRNA and microRNA (miRNA) expression profiling of peripheral blood APL cells from patients complicated with vs. without DS were integratively analyzed to explore the mechanisms underlying arsenic trioxide treatment-associated DS. By integrating the differentially expressed data with the data of differentially expressed microRNAs and their computationally predicted target genes, as well as the data of transcription factors and differentially expressed target microRNAs obtained from a literature search, a DS-related genetic regulatory network was constructed. Then using an EAGLE algorithm in clusterViz, the network was subdivided into 10 modules. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database the modules were annotated functionally, and three functionally active modules were recognized. The further in-depth analyses on the annotated functions of the three modules and the expression and roles of the related genes revealed that proliferation, differentiation, apoptosis and infiltration capability of APL cells might play important roles in the DS pathogenesis. The results could improve our understanding of DS pathogenesis from a more overall perspective, and could provide new clues for future research. PMID:27634874
BioVLAB-MMIA: a cloud environment for microRNA and mRNA integrated analysis (MMIA) on Amazon EC2.
Lee, Hyungro; Yang, Youngik; Chae, Heejoon; Nam, Seungyoon; Choi, Donghoon; Tangchaisin, Patanachai; Herath, Chathura; Marru, Suresh; Nephew, Kenneth P; Kim, Sun
2012-09-01
MicroRNAs, by regulating the expression of hundreds of target genes, play critical roles in developmental biology and the etiology of numerous diseases, including cancer. As a vast amount of microRNA expression profile data are now publicly available, the integration of microRNA expression data sets with gene expression profiles is a key research problem in life science research. However, the ability to conduct genome-wide microRNA-mRNA (gene) integration currently requires sophisticated, high-end informatics tools, significant expertise in bioinformatics and computer science to carry out the complex integration analysis. In addition, increased computing infrastructure capabilities are essential in order to accommodate large data sets. In this study, we have extended the BioVLAB cloud workbench to develop an environment for the integrated analysis of microRNA and mRNA expression data, named BioVLAB-MMIA. The workbench facilitates computations on the Amazon EC2 and S3 resources orchestrated by the XBaya Workflow Suite. The advantages of BioVLAB-MMIA over the web-based MMIA system include: 1) readily expanded as new computational tools become available; 2) easily modifiable by re-configuring graphic icons in the workflow; 3) on-demand cloud computing resources can be used on an "as needed" basis; 4) distributed orchestration supports complex and long running workflows asynchronously. We believe that BioVLAB-MMIA will be an easy-to-use computing environment for researchers who plan to perform genome-wide microRNA-mRNA (gene) integrated analysis tasks.
Pei, Haixia; Ma, Nan; Chen, Jiwei; Zheng, Yi; Tian, Ji; Li, Jing; Zhang, Shuai; Fei, Zhangjun; Gao, Junping
2013-01-01
MicroRNAs play an important role in plant development and plant responses to various biotic and abiotic stimuli. As one of the most important ornamental crops, rose (Rosa hybrida) possesses several specific morphological and physiological features, including recurrent flowering, highly divergent flower shapes, colors and volatiles. Ethylene plays an important role in regulating petal cell expansion during rose flower opening. Here, we report the population and expression profiles of miRNAs in rose petals during flower opening and in response to ethylene based on high throughput sequencing. We identified a total of 33 conserved miRNAs, as well as 47 putative novel miRNAs were identified from rose petals. The conserved and novel targets to those miRNAs were predicted using the rose floral transcriptome database. Expression profiling revealed that expression of 28 known (84.8% of known miRNAs) and 39 novel (83.0% of novel miRNAs) miRNAs was substantially changed in rose petals during the earlier opening period. We also found that 28 known and 22 novel miRNAs showed expression changes in response to ethylene treatment. Furthermore, we performed integrative analysis of expression profiles of miRNAs and their targets. We found that ethylene-caused expression changes of five miRNAs (miR156, miR164, miR166, miR5139 and rhy-miRC1) were inversely correlated to those of their seven target genes. These results indicate that these miRNA/target modules might be regulated by ethylene and were involved in ethylene-regulated petal growth. PMID:23696879
Transposon integration enhances expression of stress response genes.
Feng, Gang; Leem, Young-Eun; Levin, Henry L
2013-01-01
Transposable elements possess specific patterns of integration. The biological impact of these integration profiles is not well understood. Tf1, a long-terminal repeat retrotransposon in Schizosaccharomyces pombe, integrates into promoters with a preference for the promoters of stress response genes. To determine the biological significance of Tf1 integration, we took advantage of saturated maps of insertion activity and studied how integration at hot spots affected the expression of the adjacent genes. Our study revealed that Tf1 integration did not reduce gene expression. Importantly, the insertions activated the expression of 6 of 32 genes tested. We found that Tf1 increased gene expression by inserting enhancer activity. Interestingly, the enhancer activity of Tf1 could be limited by Abp1, a host surveillance factor that sequesters transposon sequences into structures containing histone deacetylases. We found the Tf1 promoter was activated by heat treatment and, remarkably, only genes that themselves were induced by heat could be activated by Tf1 integration, suggesting a synergy of Tf1 enhancer sequence with the stress response elements of target promoters. We propose that the integration preference of Tf1 for the promoters of stress response genes and the ability of Tf1 to enhance the expression of these genes co-evolved to promote the survival of cells under stress.
Transposon integration enhances expression of stress response genes
Feng, Gang; Leem, Young-Eun; Levin, Henry L.
2013-01-01
Transposable elements possess specific patterns of integration. The biological impact of these integration profiles is not well understood. Tf1, a long-terminal repeat retrotransposon in Schizosaccharomyces pombe, integrates into promoters with a preference for the promoters of stress response genes. To determine the biological significance of Tf1 integration, we took advantage of saturated maps of insertion activity and studied how integration at hot spots affected the expression of the adjacent genes. Our study revealed that Tf1 integration did not reduce gene expression. Importantly, the insertions activated the expression of 6 of 32 genes tested. We found that Tf1 increased gene expression by inserting enhancer activity. Interestingly, the enhancer activity of Tf1 could be limited by Abp1, a host surveillance factor that sequesters transposon sequences into structures containing histone deacetylases. We found the Tf1 promoter was activated by heat treatment and, remarkably, only genes that themselves were induced by heat could be activated by Tf1 integration, suggesting a synergy of Tf1 enhancer sequence with the stress response elements of target promoters. We propose that the integration preference of Tf1 for the promoters of stress response genes and the ability of Tf1 to enhance the expression of these genes co-evolved to promote the survival of cells under stress. PMID:23193295
Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang
2017-08-23
Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.
Barat, Ana; Ruskin, Heather J; Byrne, Annette T; Prehn, Jochen H M
2015-11-23
Recently, considerable attention has been paid to gene expression-based classifications of colorectal cancers (CRC) and their association with patient prognosis. In addition to changes in gene expression, abnormal DNA-methylation is known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Large-scale technologies, such as methylation microarray assays and specific sequencing of methylated DNA, have been used to determine whole genome profiles of CpG island methylation in tissue samples. In this article, publicly available microarray-based gene expression and methylation data sets are used to characterize expression subtypes with respect to locus-specific methylation. A major objective was to determine whether integration of these data types improves previously characterized subtypes, or provides evidence for additional subtypes. We used unsupervised clustering techniques to determine methylation-based subgroups, which are subsequently annotated with three published expression-based classifications, comprising from three to six subtypes. Our results showed that, while methylation profiles provide a further basis for segregation of certain (Inflammatory and Goblet-like) finer-grained expression-based subtypes, they also suggest that other finer-grained subtypes are not distinctive and can be considered as a single subtype.
Barat, Ana; Ruskin, Heather J.; Byrne, Annette T.; Prehn, Jochen H. M.
2015-01-01
Recently, considerable attention has been paid to gene expression-based classifications of colorectal cancers (CRC) and their association with patient prognosis. In addition to changes in gene expression, abnormal DNA-methylation is known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Large-scale technologies, such as methylation microarray assays and specific sequencing of methylated DNA, have been used to determine whole genome profiles of CpG island methylation in tissue samples. In this article, publicly available microarray-based gene expression and methylation data sets are used to characterize expression subtypes with respect to locus-specific methylation. A major objective was to determine whether integration of these data types improves previously characterized subtypes, or provides evidence for additional subtypes. We used unsupervised clustering techniques to determine methylation-based subgroups, which are subsequently annotated with three published expression-based classifications, comprising from three to six subtypes. Our results showed that, while methylation profiles provide a further basis for segregation of certain (Inflammatory and Goblet-like) finer-grained expression-based subtypes, they also suggest that other finer-grained subtypes are not distinctive and can be considered as a single subtype. PMID:27600244
Faraji, Farhoud; Hu, Ying; Wu, Gang; Goldberger, Natalie E.; Walker, Renard C.; Zhang, Jinghui; Hunter, Kent W.
2014-01-01
Metastasis is the result of stochastic genomic and epigenetic events leading to gene expression profiles that drive tumor dissemination. Here we exploit the principle that metastatic propensity is modified by the genetic background to generate prognostic gene expression signatures that illuminate regulators of metastasis. We also identify multiple microRNAs whose germline variation is causally linked to tumor progression and metastasis. We employ network analysis of global gene expression profiles in tumors derived from a panel of recombinant inbred mice to identify a network of co-expressed genes centered on Cnot2 that predicts metastasis-free survival. Modulating Cnot2 expression changes tumor cell metastatic potential in vivo, supporting a functional role for Cnot2 in metastasis. Small RNA sequencing of the same tumor set revealed a negative correlation between expression of the Mir216/217 cluster and tumor progression. Expression quantitative trait locus analysis (eQTL) identified cis-eQTLs at the Mir216/217 locus, indicating that differences in expression may be inherited. Ectopic expression of Mir216/217 in tumor cells suppressed metastasis in vivo. Finally, small RNA sequencing and mRNA expression profiling data were integrated to reveal that miR-3470a/b target a high proportion of network transcripts. In vivo analysis of Mir3470a/b demonstrated that both promote metastasis. Moreover, Mir3470b is a likely regulator of the Cnot2 network as its overexpression down-regulated expression of network hub genes and enhanced metastasis in vivo, phenocopying Cnot2 knockdown. The resulting data from this strategy identify Cnot2 as a novel regulator of metastasis and demonstrate the power of our systems-level approach in identifying modifiers of metastasis. PMID:24322557
Cancer survival classification using integrated data sets and intermediate information.
Kim, Shinuk; Park, Taesung; Kon, Mark
2014-09-01
Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a machine learning (ML) approach to integrate different data sets, and developed a novel method based on feature selection with Cox proportional hazard regression model (FSCOX) to improve the prediction of cancer survival time. FSCOX provides us with intermediate survival information, which is usually discarded when separating survival into 2 groups (short- and long-term), and allows us to perform survival analysis. We used an ML-based protocol for feature selection, integrating information from miRNA and mRNA expression profiles at the feature level. To predict survival phenotypes, we used the following classifiers, first, existing ML methods, support vector machine (SVM) and random forest (RF), second, a new median-based classifier using FSCOX (FSCOX_median), and third, an SVM classifier using FSCOX (FSCOX_SVM). We compared these methods using 3 types of cancer tissue data sets: (i) miRNA expression, (ii) mRNA expression, and (iii) combined miRNA and mRNA expression. The latter data set included features selected either from the combined miRNA/mRNA profile or independently from miRNAs and mRNAs profiles (IFS). In the ovarian data set, the accuracy of survival classification using the combined miRNA/mRNA profiles with IFS was 75% using RF, 86.36% using SVM, 84.09% using FSCOX_median, and 88.64% using FSCOX_SVM with a balanced 22 short-term and 22 long-term survivor data set. These accuracies are higher than those using miRNA alone (70.45%, RF; 75%, SVM; 75%, FSCOX_median; and 75%, FSCOX_SVM) or mRNA alone (65.91%, RF; 63.64%, SVM; 72.73%, FSCOX_median; and 70.45%, FSCOX_SVM). Similarly in the glioblastoma multiforme data, the accuracy of miRNA/mRNA using IFS was 75.51% (RF), 87.76% (SVM) 85.71% (FSCOX_median), 85.71% (FSCOX_SVM). These results are higher than the results of using miRNA expression and mRNA expression alone. In addition we predict 16 hsa-miR-23b and hsa-miR-27b target genes in ovarian cancer data sets, obtained by SVM-based feature selection through integration of sequence information and gene expression profiles. Among the approaches used, the integrated miRNA and mRNA data set yielded better results than the individual data sets. The best performance was achieved using the FSCOX_SVM method with independent feature selection, which uses intermediate survival information between short-term and long-term survival time and the combination of the 2 different data sets. The results obtained using the combined data set suggest that there are some strong interactions between miRNA and mRNA features that are not detectable in the individual analyses. Copyright © 2014 Elsevier B.V. All rights reserved.
Huang, Shi-Ming; Zhao, Xia; Zhao, Xue-Mei; Wang, Xiao-Ying; Li, Shan-Shan; Zhu, Yu-Hui
2014-01-01
Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection.
Huang, Shi-Ming; Zhao, Xia; Zhao, Xue-Mei; Wang, Xiao-Ying; Li, Shan-Shan; Zhu, Yu-Hui
2014-01-01
Objectives: Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. Methods: MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. Results: A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. Conclusions: We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection. PMID:25664019
Breast cancer: integrating the patient with her genome.
Angrist, Misha
2005-01-01
Increasingly, gene expression data are becoming the currency of the realm in assessing disease prognosis. This has been especially evident in cancer, particularly those malignancies for which tumor samples are fairly accessible and understanding prognostic factors has clear implications for treatment decisions. Recently, Pittman et al. demonstrated substantially increased accuracy of personalized disease outcome prediction in breast cancer by integrating gene-expression profile data with traditional clinical risk factors in a set of 158 breast cancer patients.
Bisognin, Andrea; Sales, Gabriele; Coppe, Alessandro; Bortoluzzi, Stefania; Romualdi, Chiara
2012-01-01
MAGIA2 (http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA2 performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA2 tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target. PMID:22618880
Li, Zibo; Heng, Jianfu; Yan, Jinhua; Guo, Xinwu; Tang, Lili; Chen, Ming; Peng, Limin; Wu, Yepeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Wang, Jun
2016-11-01
Gene-specific methylation and expression have shown biological and clinical importance for breast cancer diagnosis and prognosis. Integrated analysis of gene methylation and gene expression may identify genes associated with biology mechanism and clinical outcome of breast cancer and aid in clinical management. Using high-throughput microfluidic quantitative PCR, we analyzed the expression profiles of 48 candidate genes in 96 Chinese breast cancer patients and investigated their correlation with gene methylation and associations with breast cancer clinical parameters. Breast cancer-specific gene expression alternation was found in 25 genes with significant expression difference between paired tumor and normal tissues. A total of 9 genes (CCND2, EGFR, GSTP1, PGR, PTGS2, RECK, SOX17, TNFRSF10D, and WIF1) showed significant negative correlation between methylation and gene expression, which were validated in the TCGA database. Total 23 genes (ACADL, APC, BRCA2, CADM1, CAV1, CCND2, CST6, EGFR, ESR2, GSTP1, ICAM5, NPY, PGR, PTGS2, RECK, RUNX3, SFRP1, SOX17, SYK, TGFBR2, TNFRSF10D, WIF1, and WRN) annotated with potential TFBSs in the promoter regions showed negative correlation between methylation and expression. In logistics regression analysis, 31 of the 48 genes showed improved performance in disease prediction with combination of methylation and expression coefficient. Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.
Montague, Elizabeth; Stanberry, Larissa; Higdon, Roger; Janko, Imre; Lee, Elaine; Anderson, Nathaniel; Choiniere, John; Stewart, Elizabeth; Yandl, Gregory; Broomall, William; Kolker, Natali
2014-01-01
Abstract Multi-omics data-driven scientific discovery crucially rests on high-throughput technologies and data sharing. Currently, data are scattered across single omics repositories, stored in varying raw and processed formats, and are often accompanied by limited or no metadata. The Multi-Omics Profiling Expression Database (MOPED, http://moped.proteinspire.org) version 2.5 is a freely accessible multi-omics expression database. Continual improvement and expansion of MOPED is driven by feedback from the Life Sciences Community. In order to meet the emergent need for an integrated multi-omics data resource, MOPED 2.5 now includes gene relative expression data in addition to protein absolute and relative expression data from over 250 large-scale experiments. To facilitate accurate integration of experiments and increase reproducibility, MOPED provides extensive metadata through the Data-Enabled Life Sciences Alliance (DELSA Global, http://delsaglobal.org) metadata checklist. MOPED 2.5 has greatly increased the number of proteomics absolute and relative expression records to over 500,000, in addition to adding more than four million transcriptomics relative expression records. MOPED has an intuitive user interface with tabs for querying different types of omics expression data and new tools for data visualization. Summary information including expression data, pathway mappings, and direct connection between proteins and genes can be viewed on Protein and Gene Details pages. These connections in MOPED provide a context for multi-omics expression data exploration. Researchers are encouraged to submit omics data which will be consistently processed into expression summaries. MOPED as a multi-omics data resource is a pivotal public database, interdisciplinary knowledge resource, and platform for multi-omics understanding. PMID:24910945
Martini, Paolo; Risso, Davide; Sales, Gabriele; Romualdi, Chiara; Lanfranchi, Gerolamo; Cagnin, Stefano
2011-04-11
In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focused on the identification of significant differentially expressed genes. Later, researchers moved toward the systematic integration of gene expression profiles with additional biological information, such as chromosomal location, ontological annotations or sequence features. The analysis of gene expression linked to physical location of genes on chromosomes allows the identification of transcriptionally imbalanced regions, while, Gene Set Analysis focuses on the detection of coordinated changes in transcriptional levels among sets of biologically related genes. In this field, meta-analysis offers the possibility to compare different studies, addressing the same biological question to fully exploit public gene expression datasets. We describe STEPath, a method that starts from gene expression profiles and integrates the analysis of imbalanced region as an a priori step before performing gene set analysis. The application of STEPath in individual studies produced gene set scores weighted by chromosomal activation. As a final step, we propose a way to compare these scores across different studies (meta-analysis) on related biological issues. One complication with meta-analysis is batch effects, which occur because molecular measurements are affected by laboratory conditions, reagent lots and personnel differences. Major problems occur when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. We evaluated the power of combining chromosome mapping and gene set enrichment analysis, performing the analysis on a dataset of leukaemia (example of individual study) and on a dataset of skeletal muscle diseases (meta-analysis approach). In leukaemia, we identified the Hox gene set, a gene set closely related to the pathology that other algorithms of gene set analysis do not identify, while the meta-analysis approach on muscular disease discriminates between related pathologies and correlates similar ones from different studies. STEPath is a new method that integrates gene expression profiles, genomic co-expressed regions and the information about the biological function of genes. The usage of the STEPath-computed gene set scores overcomes batch effects in the meta-analysis approaches allowing the direct comparison of different pathologies and different studies on a gene set activation level.
Bumm, Klaus; Zheng, Mingzhong; Bailey, Clyde; Zhan, Fenghuang; Chiriva-Internati, M; Eddlemon, Paul; Terry, Julian; Barlogie, Bart; Shaughnessy, John D
2002-02-01
Clinical GeneOrganizer (CGO) is a novel windows-based archiving, organization and data mining software for the integration of gene expression profiling in clinical medicine. The program implements various user-friendly tools and extracts data for further statistical analysis. This software was written for Affymetrix GeneChip *.txt files, but can also be used for any other microarray-derived data. The MS-SQL server version acts as a data mart and links microarray data with clinical parameters of any other existing database and therefore represents a valuable tool for combining gene expression analysis and clinical disease characteristics.
Fujibuchi, Wataru; Anderson, John S. J.; Landsman, David
2001-01-01
Consensus pattern and matrix-based searches designed to predict cis-acting transcriptional regulatory sequences have historically been subject to large numbers of false positives. We sought to decrease false positives by incorporating expression profile data into a consensus pattern-based search method. We have systematically analyzed the expression phenotypes of over 6000 yeast genes, across 121 expression profile experiments, and correlated them with the distribution of 14 known regulatory elements over sequences upstream of the genes. Our method is based on a metric we term probabilistic element assessment (PEA), which is a ranking of potential sites based on sequence similarity in the upstream regions of genes with similar expression phenotypes. For eight of the 14 known elements that we examined, our method had a much higher selectivity than a naïve consensus pattern search. Based on our analysis, we have developed a web-based tool called PROSPECT, which allows consensus pattern-based searching of gene clusters obtained from microarray data. PMID:11574681
Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles
NASA Technical Reports Server (NTRS)
Eichler, Gabriel S.; Huang, Sui; Ingber, Donald E.
2003-01-01
Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/ge/gedihome.html Supplementary information: http://www.chip.org/ge/gedihome.html.
Vrahatis, Aristidis G; Dimitrakopoulos, Georgios N; Tsakalidis, Athanasios K; Bezerianos, Anastasios
2015-01-01
In the road for network medicine the newly emerged systems-level subpathway-based analysis methods offer new disease genes, drug targets and network-based biomarkers. In parallel, paired miRNA/mRNA expression data enable simultaneously monitoring of the micronome effect upon the signaling pathways. Towards this orientation, we present a methodological pipeline for the identification of differentially expressed subpathways along with their miRNA regulators by using KEGG signaling pathway maps, miRNA-target interactions and expression profiles from paired miRNA/mRNA experiments. Our pipeline offered new biological insights on a real application of paired miRNA/mRNA expression profiles with respect to the dynamic changes from colostrum to mature milk whey; several literature supported genes and miRNAs were recontextualized through miRNA-mediated differentially expressed subpathways.
Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H.; Lau, Ching C.; Behl, Sanjiv; Man, Tsz-Kwong
2007-01-01
With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License. PMID:19936083
Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H; Lau, Ching C; Behl, Sanjiv; Man, Tsz-Kwong
2007-10-06
With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License.
Loftus, Stacie K.; Baxter, Laura L.; Cronin, Julia C.; Fufa, Temesgen D.; Pavan, William J.
2017-01-01
Summary Hypoxia and HIF1α signaling direct tissue-specific gene responses regulating tumor progression, invasion and metastasis. By integrating HIF1α knockdown and hypoxia-induced gene expression changes, this study identifies a melanocyte-specific, HIF1α-dependent/hypoxia-responsive gene expression signature. Integration of these gene expression changes with HIF1α ChIP-Seq analysis identifies 81 HIF1α direct target genes in melanocytes. The expression levels for ten of the HIF1α direct targets – GAPDH, PKM, PPAT, DARS, DTWD1, SEH1L, ZNF292, RLF, AGTRAP, and GPC6 – are significantly correlated with reduced time of Disease Free Status (DFS) in melanoma by logistic regression (P-value =0.0013) and ROC curve analysis (AUC= 0.826, P-value<0.0001). This HIF1α-regulated profile defines a melanocyte-specific response under hypoxia, and demonstrates the role of HIF1α as an invasive cell state gatekeeper in regulating cellular metabolism, chromatin and transcriptional regulation, vascularization and invasion. PMID:28168807
Lu, Chenqi; Liu, Xiaoqin; Wang, Lin; Jiang, Ning; Yu, Jun; Zhao, Xiaobo; Hu, Hairong; Zheng, Saihua; Li, Xuelian; Wang, Guiying
2017-01-10
Due to genetic heterogeneity and variable diagnostic criteria, genetic studies of polycystic ovary syndrome are particularly challenging. Furthermore, lack of sufficiently large cohorts limits the identification of susceptibility genes contributing to polycystic ovary syndrome. Here, we carried out a systematic search of studies deposited in the Gene Expression Omnibus database through August 31, 2016. The present analyses included studies with: 1) patients with polycystic ovary syndrome and normal controls, 2) gene expression profiling of messenger RNA, and 3) sufficient data for our analysis. Ultimately, a total of 9 studies with 13 datasets met the inclusion criteria and were performed for the subsequent integrated analyses. Through comprehensive analyses, there were 13 genetic factors overlapped in all datasets and identified as significant specific genes for polycystic ovary syndrome. After quality control assessment, there were six datasets remained. Further gene ontology enrichment and pathway analyses suggested that differentially expressed genes mainly enriched in oocyte pathways. These findings provide potential molecular markers for diagnosis and prognosis of polycystic ovary syndrome, and need in-depth studies on the exact function and mechanism in polycystic ovary syndrome.
Zhao, Chen; Mao, Jinghe; Ai, Junmei; Shenwu, Ming; Shi, Tieliu; Zhang, Daqing; Wang, Xiaonan; Wang, Yunliang; Deng, Youping
2013-01-01
Insulin resistance is a key element in the pathogenesis of type 2 diabetes mellitus. Plasma free fatty acids were assumed to mediate the insulin resistance, while the relationship between lipid and glucose disposal remains to be demonstrated across liver, skeletal muscle and blood. We profiled both lipidomics and gene expression of 144 total peripheral blood samples, 84 from patients with T2D and 60 from healthy controls. Then, factor and partial least squares models were used to perform a combined analysis of lipidomics and gene expression profiles to uncover the bioprocesses that are associated with lipidomic profiles in type 2 diabetes. According to factor analysis of the lipidomic profile, several species of lipids were found to be correlated with different phenotypes, including diabetes-related C23:2CE, C23:3CE, C23:4CE, ePE36:4, ePE36:5, ePE36:6; race-related (African-American) PI36:1; and sex-related PE34:1 and LPC18:2. The major variance of gene expression profile was not caused by known factors and no significant difference can be directly derived from differential gene expression profile. However, the combination of lipidomic and gene expression analyses allows us to reveal the correlation between the altered lipid profile with significantly enriched pathways, such as one carbon pool by folate, arachidonic acid metabolism, insulin signaling pathway, amino sugar and nucleotide sugar metabolism, propanoate metabolism, and starch and sucrose metabolism. The genes in these pathways showed a good capability to classify diabetes samples. Combined analysis of gene expression and lipidomic profiling reveals type 2 diabetes-associated lipid species and enriched biological pathways in peripheral blood, while gene expression profile does not show direct correlation. Our findings provide a new clue to better understand the mechanism of disordered lipid metabolism in association with type 2 diabetes.
MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype.
Blenkiron, Cherie; Goldstein, Leonard D; Thorne, Natalie P; Spiteri, Inmaculada; Chin, Suet-Feung; Dunning, Mark J; Barbosa-Morais, Nuno L; Teschendorff, Andrew E; Green, Andrew R; Ellis, Ian O; Tavaré, Simon; Caldas, Carlos; Miska, Eric A
2007-01-01
MicroRNAs (miRNAs), a class of short non-coding RNAs found in many plants and animals, often act post-transcriptionally to inhibit gene expression. Here we report the analysis of miRNA expression in 93 primary human breast tumors, using a bead-based flow cytometric miRNA expression profiling method. Of 309 human miRNAs assayed, we identify 133 miRNAs expressed in human breast and breast tumors. We used mRNA expression profiling to classify the breast tumors as luminal A, luminal B, basal-like, HER2+ and normal-like. A number of miRNAs are differentially expressed between these molecular tumor subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumor subtypes in an independent data set. In some cases, changes in miRNA expression correlate with genomic loss or gain; in others, changes in miRNA expression are likely due to changes in primary transcription and or miRNA biogenesis. Finally, the expression of DICER1 and AGO2 is correlated with tumor subtype and may explain some of the changes in miRNA expression observed. This study represents the first integrated analysis of miRNA expression, mRNA expression and genomic changes in human breast cancer and may serve as a basis for functional studies of the role of miRNAs in the etiology of breast cancer. Furthermore, we demonstrate that bead-based flow cytometric miRNA expression profiling might be a suitable platform to classify breast cancer into prognostic molecular subtypes.
Clinical value of integrated-signature miRNAs in esophageal cancer.
Zhang, Heng-Chao; Tang, Kai-Fu
2017-08-01
MicroRNAs (miRNAs) are crucial regulators of gene expression in tumorigenesis and are of great interest to researchers, but miRNA profiles are often inconsistent between studies. The aim of this study was to confirm candidate miRNA biomarkers for esophageal cancer from integrated-miRNA expression profiling data and TCGA (The Cancer Genome Atlas) data in tissues. Here, we identify five significant miRNAs by a comprehensive analysis in esophageal cancer, and two of them (hsa-miR-100-5p and hsa-miR-133b) show better prognoses with significant difference for both 3-year and 5-year survival. Additionally, they participate in esophageal cancer occurrence and development according to KEGG and Panther enrichment analyses. Therefore, these five miRNAs may serve as miRNA biomarkers in esophageal cancer. Analysis of differential expression for target genes of these miRNAs may also provide new therapeutic alternatives in esophageal cancer. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.
In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer.
Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi
2013-10-04
Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC. Copyright © 2013 Elsevier Inc. All rights reserved.
Advancing the use of noncoding RNA in regulatory toxicology: Report of an ECETOC workshop.
Aigner, Achim; Buesen, Roland; Gant, Tim; Gooderham, Nigel; Greim, Helmut; Hackermüller, Jörg; Hubesch, Bruno; Laffont, Madeleine; Marczylo, Emma; Meister, Gunter; Petrick, Jay S; Rasoulpour, Reza J; Sauer, Ursula G; Schmidt, Kerstin; Seitz, Hervé; Slack, Frank; Sukata, Tokuo; van der Vies, Saskia M; Verhaert, Jan; Witwer, Kenneth W; Poole, Alan
2016-12-01
The European Centre for the Ecotoxicology and Toxicology of Chemicals (ECETOC) organised a workshop to discuss the state-of-the-art research on noncoding RNAs (ncRNAs) as biomarkers in regulatory toxicology and as analytical and therapeutic agents. There was agreement that ncRNA expression profiling data requires careful evaluation to determine the utility of specific ncRNAs as biomarkers. To advance the use of ncRNA in regulatory toxicology, the following research priorities were identified: (1) Conduct comprehensive literature reviews to identify possibly suitable ncRNAs and areas of toxicology where ncRNA expression profiling could address prevailing scientific deficiencies. (2) Develop consensus on how to conduct ncRNA expression profiling in a toxicological context. (3) Conduct experimental projects, including, e.g., rat (90-day) oral toxicity studies, to evaluate the toxicological relevance of the expression profiles of selected ncRNAs. Thereby, physiological ncRNA expression profiles should be established, including the biological variability of healthy individuals. To substantiate the relevance of key ncRNAs for cell homeostasis or pathogenesis, molecular events should be dose-dependently linked with substance-induced apical effects. Applying a holistic approach, knowledge on ncRNAs, 'omics and epigenetics technologies should be integrated into adverse outcome pathways to improve the understanding of the functional roles of ncRNAs within a regulatory context. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.
Kaufmann, Kerstin B.; Brendel, Christian; Suerth, Julia D.; Mueller-Kuller, Uta; Chen-Wichmann, Linping; Schwäble, Joachim; Pahujani, Shweta; Kunkel, Hana; Schambach, Axel; Baum, Christopher; Grez, Manuel
2013-01-01
Comparative integrome analysis has revealed that the most neutral integration pattern among retroviruses is attributed to alpharetroviruses. We chose X-linked chronic granulomatous disease (X-CGD) as model to evaluate the potential of self-inactivating (SIN) alpharetroviral vectors for gene therapy of monogenic diseases. Therefore, we combined the alpharetroviral vector backbone with the elongation factor-1α short promoter, both considered to possess a low genotoxic profile, to drive transgene (gp91phox) expression. Following efficient transduction transgene expression was sustained and provided functional correction of the CGD phenotype in a cell line model at low vector copy number. Further analysis in a murine X-CGD transplantation model revealed gene-marking of bone marrow cells and oxidase positive granulocytes in peripheral blood. Transduction of human X-CGD CD34+ cells provided functional correction up to wild-type levels and long-term expression upon transplantation into a humanized mouse model. In contrast to lentiviral vectors, no aberrantly spliced transcripts containing cellular exons fused to alpharetroviral sequences were found in transduced cells, implying that the safety profile of alpharetroviral vectors may extend beyond their neutral integration profile. Taken together, this highlights the potential of this SIN alpharetroviral system as a platform for new candidate vectors for future gene therapy of hematopoietic disorders. PMID:23207695
Meissner, Tobias; Seckinger, Anja; Rème, Thierry; Hielscher, Thomas; Möhler, Thomas; Neben, Kai; Goldschmidt, Hartmut; Klein, Bernard; Hose, Dirk
2011-12-01
Multiple myeloma is an incurable malignant plasma cell disease characterized by survival ranging from several months to more than 15 years. Assessment of risk and underlying molecular heterogeneity can be excellently done by gene expression profiling (GEP), but its way into clinical routine is hampered by the lack of an appropriate reporting tool and the integration with other prognostic factors into a single "meta" risk stratification. The GEP-report (GEP-R) was built as an open-source software developed in R for gene expression reporting in clinical practice using Affymetrix microarrays. GEP-R processes new samples by applying a documentation-by-value strategy to the raw data to be able to assign thresholds and grouping algorithms defined on a reference cohort of 262 patients with multiple myeloma. Furthermore, we integrated expression-based and conventional prognostic factors within one risk stratification (HM-metascore). The GEP-R comprises (i) quality control, (ii) sample identity control, (iii) biologic classification, (iv) risk stratification, and (v) assessment of target genes. The resulting HM-metascore is defined as the sum over the weighted factors gene expression-based risk-assessment (UAMS-, IFM-score), proliferation, International Staging System (ISS) stage, t(4;14), and expression of prognostic target genes (AURKA, IGF1R) for which clinical grade inhibitors exist. The HM-score delineates three significantly different groups of 13.1%, 72.1%, and 14.7% of patients with a 6-year survival rate of 89.3%, 60.6%, and 18.6%, respectively. GEP reporting allows prospective assessment of risk and target gene expression and integration of current prognostic factors in clinical routine, being customizable about novel parameters or other cancer entities. ©2011 AACR.
Gong, Bin-Sheng; Zhang, Qing-Pu; Zhang, Guang-Mei; Zhang, Shao-Jun; Zhang, Wei; Lv, Hong-Chao; Zhang, Fan; Lv, Sa-Li; Li, Chuan-Xing; Rao, Shao-Qi; Li, Xia
2007-01-01
Gene expression profiles and single-nucleotide polymorphism (SNP) profiles are modern data for genetic analysis. It is possible to use the two types of information to analyze the relationships among genes by some genetical genomics approaches. In this study, gene expression profiles were used as expression traits. And relationships among the genes, which were co-linked to a common SNP(s), were identified by integrating the two types of information. Further research on the co-expressions among the co-linked genes was carried out after the gene-SNP relationships were established using the Haseman-Elston sib-pair regression. The results showed that the co-expressions among the co-linked genes were significantly higher if the number of connections between the genes and a SNP(s) was more than six. Then, the genes were interconnected via one or more SNP co-linkers to construct a gene-SNP intermixed network. The genes sharing more SNPs tended to have a stronger correlation. Finally, a gene-gene network was constructed with their intensities of relationships (the number of SNP co-linkers shared) as the weights for the edges. PMID:18466544
KOK-SIN, TEOW; MOKHTAR, NORFILZA MOHD; HASSAN, NUR ZARINA ALI; SAGAP, ISMAIL; ROSE, ISA MOHAMED; HARUN, ROSLAN; JAMAL, RAHMAN
2015-01-01
Apart from genetic mutations, epigenetic alteration is a common phenomenon that contributes to neoplastic transformation in colorectal cancer. Transcriptional silencing of tumor-suppressor genes without changes in the DNA sequence is explained by the existence of promoter hypermethylation. To test this hypothesis, we integrated the epigenome and transcriptome data from a similar set of colorectal tissue samples. Methylation profiling was performed using the Illumina InfiniumHumanMethylation27 BeadChip on 55 paired cancer and adjacent normal epithelial cells. Fifteen of the 55 paired tissues were used for gene expression profiling using the Affymetrix GeneChip Human Gene 1.0 ST array. Validation was carried out on 150 colorectal tissues using the methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) technique. PCA and supervised hierarchical clustering in the two microarray datasets showed good separation between cancer and normal samples. Significant genes from the two analyses were obtained based on a ≥2-fold change and a false discovery rate (FDR) P-value of <0.05. We identified 1,081 differentially hypermethylated CpG sites and 36 hypomethylated CpG sites. We also found 709 upregulated and 699 downregulated genes from the gene expression profiling. A comparison of the two datasets revealed 32 overlapping genes with 27 being hypermethylated with downregulated expression and 4 hypermethylated with upregulated expression. One gene was found to be hypomethylated and downregulated. The most enriched molecular pathway identified was cell adhesion molecules that involved 4 overlapped genes, JAM2, NCAM1, ITGA8 and CNTN1. In the present study, we successfully identified a group of genes that showed methylation and gene expression changes in well-defined colorectal cancer tissues with high purity. The integrated analysis gives additional insight regarding the regulation of colorectal cancer-associated genes and their underlying mechanisms that contribute to colorectal carcinogenesis. PMID:25997610
Yoo, Seungyeul; Takikawa, Sachiko; Geraghty, Patrick; Argmann, Carmen; Campbell, Joshua; Lin, Luan; Huang, Tao; Tu, Zhidong; Foronjy, Robert F; Feronjy, Robert; Spira, Avrum; Schadt, Eric E; Powell, Charles A; Zhu, Jun
2015-01-01
Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a 'causal' role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology.
Integration of biological networks and gene expression data using Cytoscape
Cline, Melissa S; Smoot, Michael; Cerami, Ethan; Kuchinsky, Allan; Landys, Nerius; Workman, Chris; Christmas, Rowan; Avila-Campilo, Iliana; Creech, Michael; Gross, Benjamin; Hanspers, Kristina; Isserlin, Ruth; Kelley, Ryan; Killcoyne, Sarah; Lotia, Samad; Maere, Steven; Morris, John; Ono, Keiichiro; Pavlovic, Vuk; Pico, Alexander R; Vailaya, Aditya; Wang, Peng-Liang; Adler, Annette; Conklin, Bruce R; Hood, Leroy; Kuiper, Martin; Sander, Chris; Schmulevich, Ilya; Schwikowski, Benno; Warner, Guy J; Ideker, Trey; Bader, Gary D
2013-01-01
Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape. PMID:17947979
Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T.
2016-01-01
Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan–Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. PMID:26507857
Van Laere, Steven J; Ueno, Naoto T; Finetti, Pascal; Vermeulen, Peter; Lucci, Anthony; Robertson, Fredika M; Marsan, Melike; Iwamoto, Takayuki; Krishnamurthy, Savitri; Masuda, Hiroko; van Dam, Peter; Woodward, Wendy A; Viens, Patrice; Cristofanilli, Massimo; Birnbaum, Daniel; Dirix, Luc; Reuben, James M; Bertucci, François
2013-09-01
Inflammatory breast cancer (IBC) is a poorly characterized form of breast cancer. So far, the results of expression profiling in IBC are inconclusive due to various reasons including limited sample size. Here, we present the integration of three Affymetrix expression datasets collected through the World IBC Consortium allowing us to interrogate the molecular profile of IBC using the largest series of IBC samples ever reported. Affymetrix profiles (HGU133-series) from 137 patients with IBC and 252 patients with non-IBC (nIBC) were analyzed using unsupervised and supervised techniques. Samples were classified according to the molecular subtypes using the PAM50-algorithm. Regression models were used to delineate IBC-specific and molecular subtype-independent changes in gene expression, pathway, and transcription factor activation. Four robust IBC-sample clusters were identified, associated with the different molecular subtypes (P<0.001), all of which were identified in IBC with a similar prevalence as in nIBC, except for the luminal A subtype (19% vs. 42%; P<0.001) and the HER2-enriched subtype (22% vs. 9%; P<0.001). Supervised analysis identified and validated an IBC-specific, molecular subtype-independent 79-gene signature, which held independent prognostic value in a series of 871 nIBCs. Functional analysis revealed attenuated TGF-β signaling in IBC. We show that IBC is transcriptionally heterogeneous and that all molecular subtypes described in nIBC are detectable in IBC, albeit with a different frequency. The molecular profile of IBC, bearing molecular traits of aggressive breast tumor biology, shows attenuation of TGF-β signaling, potentially explaining the metastatic potential of IBC tumor cells in an unexpected manner. ©2013 AACR.
Li, Wen-Xing; Dai, Shao-Xing; Liu, Jia-Qian; Wang, Qian; Li, Gong-Hua; Huang, Jing-Fei
2016-01-01
Alzheimer's disease (AD) and schizophrenia (SZ) are both accompanied by impaired learning and memory functions. This study aims to explore the expression profiles of learning or memory genes between AD and SZ. We downloaded 10 AD and 10 SZ datasets from GEO-NCBI for integrated analysis. These datasets were processed using RMA algorithm and a global renormalization for all studies. Then Empirical Bayes algorithm was used to find the differentially expressed genes between patients and controls. The results showed that most of the differentially expressed genes were related to AD whereas the gene expression profile was little affected in the SZ. Furthermore, in the aspects of the number of differentially expressed genes, the fold change and the brain region, there was a great difference in the expression of learning or memory related genes between AD and SZ. In AD, the CALB1, GABRA5, and TAC1 were significantly downregulated in whole brain, frontal lobe, temporal lobe, and hippocampus. However, in SZ, only two genes CRHBP and CX3CR1 were downregulated in hippocampus, and other brain regions were not affected. The effect of these genes on learning or memory impairment has been widely studied. It was suggested that these genes may play a crucial role in AD or SZ pathogenesis. The different gene expression patterns between AD and SZ on learning and memory functions in different brain regions revealed in our study may help to understand the different mechanism between two diseases.
Haberman, Rebecca P; Colantuoni, Carlo; Koh, Ming Teng; Gallagher, Michela
2013-01-01
Aging is often associated with cognitive decline, but many elderly individuals maintain a high level of function throughout life. Here we studied outbred rats, which also exhibit individual differences across a spectrum of outcomes that includes both preserved and impaired spatial memory. Previous work in this model identified the CA3 subfield of the hippocampus as a region critically affected by age and integral to differing cognitive outcomes. Earlier microarray profiling revealed distinct gene expression profiles in the CA3 region, under basal conditions, for aged rats with intact memory and those with impairment. Because prominent age-related deficits within the CA3 occur during neural encoding of new information, here we used microarray analysis to gain a broad perspective of the aged CA3 transcriptome under activated conditions. Behaviorally-induced CA3 expression profiles differentiated aged rats with intact memory from those with impaired memory. In the activated profile, we observed substantial numbers of genes (greater than 1000) exhibiting increased expression in aged unimpaired rats relative to aged impaired, including many involved in synaptic plasticity and memory mechanisms. This unimpaired aged profile also overlapped significantly with a learning induced gene profile previously acquired in young adults. Alongside the increased transcripts common to both young learning and aged rats with preserved memory, many transcripts behaviorally-activated in the current study had previously been identified as repressed in the aged unimpaired phenotype in basal expression. A further distinct feature of the activated profile of aged rats with intact memory is the increased expression of an ensemble of genes involved in inhibitory synapse function, which could control the phenotype of neural hyperexcitability found in the CA3 region of aged impaired rats. These data support the conclusion that aged subjects with preserved memory recruit adaptive mechanisms to retain tight control over excitability under both basal and activated conditions.
Uncovering Hidden Layers of Cell Cycle Regulation through Integrative Multi-omic Analysis
Aviner, Ranen; Shenoy, Anjana; Elroy-Stein, Orna; Geiger, Tamar
2015-01-01
Studying the complex relationship between transcription, translation and protein degradation is essential to our understanding of biological processes in health and disease. The limited correlations observed between mRNA and protein abundance suggest pervasive regulation of post-transcriptional steps and support the importance of profiling mRNA levels in parallel to protein synthesis and degradation rates. In this work, we applied an integrative multi-omic approach to study gene expression along the mammalian cell cycle through side-by-side analysis of mRNA, translation and protein levels. Our analysis sheds new light on the significant contribution of both protein synthesis and degradation to the variance in protein expression. Furthermore, we find that translation regulation plays an important role at S-phase, while progression through mitosis is predominantly controlled by changes in either mRNA levels or protein stability. Specific molecular functions are found to be co-regulated and share similar patterns of mRNA, translation and protein expression along the cell cycle. Notably, these include genes and entire pathways not previously implicated in cell cycle progression, demonstrating the potential of this approach to identify novel regulatory mechanisms beyond those revealed by traditional expression profiling. Through this three-level analysis, we characterize different mechanisms of gene expression, discover new cycling gene products and highlight the importance and utility of combining datasets generated using different techniques that monitor distinct steps of gene expression. PMID:26439921
Zhou, Xiang; Michal, Jennifer J; Jiang, Zhihua; Liu, Bang
2017-11-01
Porcine respiratory and reproductive syndrome (PRRS), caused by PRRS virus (PRRSV), is one of the most serious infectious diseases in the swine industry worldwide. Indigenous Chinese Tongcheng (TC) pigs reportedly show strong resistance to PRRSV infection. The miRNA expression profiles of porcine alveolar macrophages (PAMs) of control TC pigs and those infected with PRRSV in vivo were analyzed by high-throughput sequencing to explore changes induced by infection. A total of 182 known miRNAs including 101 miRNA-5p and 81 miRNA-3p were identified with 23 up-regulated differentially expressed miRNAs (DEmiRNAs) and 25 down-regulated DEmiRNAs. Gene Ontology analysis showed that predicted target genes for the DEmiRNAs were enriched in immune response, transcription regulation, and cell death. The integrative analysis of mRNA and miRNA expression revealed that down-regulated methylation-related genes (DNMT1 and DNMT3b) were targeted by five up-regulated DEmiRNAs. Furthermore, 35 pairs of miRNAs (70 miRNAs) were co-expressed after PRRSV infection and six pairs were co-expressed differently. Our results describe miRNA expression profiles of TC pigs in response to PRRSV infection and lay a strong foundation for developing novel therapies to control PRRS in pigs.
NASA Technical Reports Server (NTRS)
Manning, Robert M.; Vyhnalek, Brian E.
2015-01-01
The values of the key atmospheric propagation parameters Ct2, Cq2, and Ctq are highly dependent upon the vertical height within the atmosphere thus making it necessary to specify profiles of these values along the atmospheric propagation path. The remote sensing method suggested and described in this work makes use of a rapidly integrating microwave profiling radiometer to capture profiles of temperature and humidity through the atmosphere. The integration times of currently available profiling radiometers are such that they are approaching the temporal intervals over which one can possibly make meaningful assessments of these key atmospheric parameters. Since these parameters are fundamental to all propagation conditions, they can be used to obtain Cn2 profiles for any frequency, including those for an optical propagation path. In this case the important performance parameters of the prevailing isoplanatic angle and Greenwood frequency can be obtained. The integration times are such that Kolmogorov turbulence theory and the Taylor frozen-flow hypothesis must be transcended. Appropriate modifications to these classical approaches are derived from first principles and an expression for the structure functions are obtained. The theory is then applied to an experimental scenario and shows very good results.
Integrating multi-omic features exploiting Chromosome Conformation Capture data.
Merelli, Ivan; Tordini, Fabio; Drocco, Maurizio; Aldinucci, Marco; Liò, Pietro; Milanesi, Luciano
2015-01-01
The representation, integration, and interpretation of omic data is a complex task, in particular considering the huge amount of information that is daily produced in molecular biology laboratories all around the world. The reason is that sequencing data regarding expression profiles, methylation patterns, and chromatin domains is difficult to harmonize in a systems biology view, since genome browsers only allow coordinate-based representations, discarding functional clusters created by the spatial conformation of the DNA in the nucleus. In this context, recent progresses in high throughput molecular biology techniques and bioinformatics have provided insights into chromatin interactions on a larger scale and offer a formidable support for the interpretation of multi-omic data. In particular, a novel sequencing technique called Chromosome Conformation Capture allows the analysis of the chromosome organization in the cell's natural state. While performed genome wide, this technique is usually called Hi-C. Inspired by service applications such as Google Maps, we developed NuChart, an R package that integrates Hi-C data to describe the chromosomal neighborhood starting from the information about gene positions, with the possibility of mapping on the achieved graphs genomic features such as methylation patterns and histone modifications, along with expression profiles. In this paper we show the importance of the NuChart application for the integration of multi-omic data in a systems biology fashion, with particular interest in cytogenetic applications of these techniques. Moreover, we demonstrate how the integration of multi-omic data can provide useful information in understanding why genes are in certain specific positions inside the nucleus and how epigenetic patterns correlate with their expression.
Lotus Base: An integrated information portal for the model legume Lotus japonicus
Mun, Terry; Bachmann, Asger; Gupta, Vikas; Stougaard, Jens; Andersen, Stig U.
2016-01-01
Lotus japonicus is a well-characterized model legume widely used in the study of plant-microbe interactions. However, datasets from various Lotus studies are poorly integrated and lack interoperability. We recognize the need for a comprehensive repository that allows comprehensive and dynamic exploration of Lotus genomic and transcriptomic data. Equally important are user-friendly in-browser tools designed for data visualization and interpretation. Here, we present Lotus Base, which opens to the research community a large, established LORE1 insertion mutant population containing an excess of 120,000 lines, and serves the end-user tightly integrated data from Lotus, such as the reference genome, annotated proteins, and expression profiling data. We report the integration of expression data from the L. japonicus gene expression atlas project, and the development of tools to cluster and export such data, allowing users to construct, visualize, and annotate co-expression gene networks. Lotus Base takes advantage of modern advances in browser technology to deliver powerful data interpretation for biologists. Its modular construction and publicly available application programming interface enable developers to tap into the wealth of integrated Lotus data. Lotus Base is freely accessible at: https://lotus.au.dk. PMID:28008948
Language and affective facial expression in children with perinatal stroke.
Lai, Philip T; Reilly, Judy S
2015-08-01
Children with perinatal stroke (PS) provide a unique opportunity to understand developing brain-behavior relations. Previous research has noted distinctive differences in behavioral sequelae between children with PS and adults with acquired stroke: children fare better, presumably due to the plasticity of the developing brain for adaptive reorganization. Whereas we are beginning to understand language development, we know little about another communicative domain, emotional expression. The current study investigates the use and integration of language and facial expression during an interview. As anticipated, the language performance of the five and six year old PS group is comparable to their typically developing (TD) peers, however, their affective profiles are distinctive: those with right hemisphere injury are less expressive with respect to affective language and affective facial expression than either those with left hemisphere injury or TD group. The two distinctive profiles for language and emotional expression in these children suggest gradients of neuroplasticity in the developing brain. Copyright © 2015 Elsevier Inc. All rights reserved.
The protein expression landscape of mitosis and meiosis in diploid budding yeast.
Becker, Emmanuelle; Com, Emmanuelle; Lavigne, Régis; Guilleux, Marie-Hélène; Evrard, Bertrand; Pineau, Charles; Primig, Michael
2017-03-06
Saccharomyces cerevisiae is an established model organism for the molecular analysis of fundamental biological processes. The genomes of numerous strains have been sequenced, and the transcriptome and proteome ofmajor phases during the haploid and diploid yeast life cycle have been determined. However, much less is known about dynamic changes of the proteome when cells switch from mitotic growth to meiotic development. We report a quantitative protein profiling analysis of yeast cell division and differentiation based on mass spectrometry. Information about protein levels was integrated with strand-specific tiling array expression data. We identified a total of 2366 proteins in at least one condition, including 175 proteins showing a statistically significant>5-fold change across the sample set, and 136 proteins detectable in sporulating but not respiring cells. We correlate protein expression patterns with biological processes and molecular function by Gene Ontology term enrichment, chemoprofiling, transcription interference and the formation of double stranded RNAs by overlapping sense/antisense transcripts. Our work provides initial quantitative insight into protein expression in diploid respiring and differentiating yeast cells. Critically, it associates developmentally regulated induction of antisense long noncoding RNAs and double stranded RNAs with fluctuating protein concentrations during growth and development. This integrated genomics analysis helps better understand how the transcriptome and the proteome correlate in diploid yeast cells undergoing mitotic growth in the presence of acetate (respiration) versus meiotic differentiation (Meiosis I and II). The study (i) provides quantitative expression data for 2366 proteins and their cognate mRNAs in at least one sample, (ii) shows strongly fluctuating protein levels during growth and differentiation for 175 cases, and (iii) identifies 136 proteins absent in mitotic but present in meiotic yeast cells. We have integrated protein profiling data using mass spectrometry with tiling array RNA profiling data and information on double-stranded RNAs (dsRNAs) by overlapping sense/antisense transcripts from an RNA-Sequencing experiment. This work therefore provides quantitative insight into protein expression during cell division and development and associates changing protein levels with developmental stage specific induction of antisense transcripts and the formation of dsRNAs. Copyright © 2017 Elsevier B.V. All rights reserved.
miRNA and mRNA Expression Profiles Reveal Insight into Chitosan-Mediated Regulation of Plant Growth.
Zhang, Xiaoqian; Li, Kecheng; Xing, Ronge; Liu, Song; Chen, Xiaolin; Yang, Haoyue; Li, Pengcheng
2018-04-18
Chitosan has been numerously studied as a plant growth regulator and stress tolerance inducer. To investigate the roles of chitosan as bioregulator on plant and unravel its possible metabolic responses mechanisms, we simultaneously investigated mRNAs and microRNAs (miRNAs) expression profiles of wheat seedlings in response to chitosan heptamer. We found 400 chitosan-responsive differentially expressed genes, including 268 up-regulated and 132 down-regulated mRNAs, many of which were related to photosynthesis, primary carbon and nitrogen metabolism, defense responses, and transcription factors. Moreover, miRNAs also participate in chitosan-mediated regulation on plant growth. We identified 87 known and 21 novel miRNAs, among which 56 miRNAs were induced or repressed by chitosan heptamer, such as miRNA156, miRNA159a, miRNA164, miRNA171a, miRNA319, and miRNA1127. The integrative analysis of miRNA and mRNA expression profiles in this case provides fundamental information for further investigation of regulation mechanisms of chitosan on plant growth and will facilitate its application in agriculture.
Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T
2017-10-01
Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.
Wang, Jinglu; Qu, Susu; Wang, Weixiao; Guo, Liyuan; Zhang, Kunlin; Chang, Suhua; Wang, Jing
2016-11-01
Numbers of gene expression profiling studies of bipolar disorder have been published. Besides different array chips and tissues, variety of the data processes in different cohorts aggravated the inconsistency of results of these genome-wide gene expression profiling studies. By searching the gene expression databases, we obtained six data sets for prefrontal cortex (PFC) of bipolar disorder with raw data and combinable platforms. We used standardized pre-processing and quality control procedures to analyze each data set separately and then combined them into a large gene expression matrix with 101 bipolar disorder subjects and 106 controls. A standard linear mixed-effects model was used to calculate the differentially expressed genes (DEGs). Multiple levels of sensitivity analyses and cross validation with genetic data were conducted. Functional and network analyses were carried out on basis of the DEGs. In the result, we identified 198 unique differentially expressed genes in the PFC of bipolar disorder and control. Among them, 115 DEGs were robust to at least three leave-one-out tests or different pre-processing methods; 51 DEGs were validated with genetic association signals. Pathway enrichment analysis showed these DEGs were related with regulation of neurological system, cell death and apoptosis, and several basic binding processes. Protein-protein interaction network further identified one key hub gene. We have contributed the most comprehensive integrated analysis of bipolar disorder expression profiling studies in PFC to date. The DEGs, especially those with multiple validations, may denote a common signature of bipolar disorder and contribute to the pathogenesis of disease. Copyright © 2016 Elsevier Ltd. All rights reserved.
Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis.
Liu, Mingyuan; Hou, Xiaojun; Zhang, Ping; Hao, Yong; Yang, Yiting; Wu, Xiongfeng; Zhu, Desheng; Guan, Yangtai
2013-05-01
Multiple sclerosis (MS) is the most prevalent demyelinating disease and the principal cause of neurological disability in young adults. Recent microarray gene expression profiling studies have identified several genetic variants contributing to the complex pathogenesis of MS, however, expressional and functional studies are still required to further understand its molecular mechanism. The present study aimed to analyze the molecular mechanism of MS using microarray analysis combined with bioinformatics techniques. We downloaded the gene expression profile of MS from Gene Expression Omnibus (GEO) and analysed the microarray data using the differentially coexpressed genes (DCGs) and links package in R and Database for Annotation, Visualization and Integrated Discovery. The regulatory impact factor (RIF) algorithm was used to measure the impact factor of transcription factor. A total of 1,297 DCGs between MS patients and healthy controls were identified. Functional annotation indicated that these DCGs were associated with immune and neurological functions. Furthermore, the RIF result suggested that IKZF1, BACH1, CEBPB, EGR1, FOS may play central regulatory roles in controlling gene expression in the pathogenesis of MS. Our findings confirm the presence of multiple molecular alterations in MS and indicate the possibility for identifying prognostic factors associated with MS pathogenesis.
Hung, Fei-Hung; Chiu, Hung-Wen
2015-01-01
Gene expression profiles differ in different diseases. Even if diseases are at the same stage, such diseases exhibit different gene expressions, not to mention the different subtypes at a single lesion site. Distinguishing different disease subtypes at a single lesion site is difficult. In early cases, subtypes were initially distinguished by doctors. Subsequently, further differences were found through pathological experiments. For example, a brain tumor can be classified according to its origin, its cell-type origin, or the tumor site. Because of the advancements in bioinformatics and the techniques for accumulating gene expressions, researchers can use gene expression data to classify disease subtypes. Because the operation of a biopathway is closely related to the disease mechanism, the application of gene expression profiles for clustering disease subtypes is insufficient. In this study, we collected gene expression data of healthy and four myelodysplastic syndrome subtypes and applied a method that integrated protein-protein interaction and gene expression data to identify different patterns of disease subtypes. We hope it is efficient for the classification of disease subtypes in adventure.
NASA Technical Reports Server (NTRS)
Varanasi, P.; Cess, R. D.; Bangaru, B. R. P.
1974-01-01
Measurements of the absolute intensity and integrated band absorption have been performed for the nu sub 9 fundamental band of ethane. The intensity is found to be about 34 per sq cm per atm at STP, and this is significantly higher than previous estimates. It is shown that a Gaussian profile provides an empirical representation of the apparent spectral absorption coefficient. Employing this empirical profile, a simple expression is derived for the integrated band absorption, which is in excellent agreement with experimental values. The band model is then employed to investigate the possible role of ethane as a source of thermal infrared opacity within the atmospheres of Jupiter and Saturn, and to interpret qualitatively observed brightness temperatures for Saturn.
In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pandi, Narayanan Sathiya, E-mail: sathiyapandi@gmail.com; Suganya, Sivagurunathan; Rajendran, Suriliyandi
Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However,more » the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC.« less
Zacapala-Gómez, Ana E; Navarro-Tito, Napoleón; Alarcón-Romero, Luz Del C; Ortuño-Pineda, Carlos; Illades-Aguiar, Berenice; Castañeda-Saucedo, Eduardo; Ortiz-Ortiz, Julio; Garibay-Cerdenares, Olga L; Jiménez-López, Marco A; Mendoza-Catalán, Miguel A
2018-03-27
Cervical cancer (CC) is the fourth cause of mortality by neoplasia in women worldwide. The use of immunomarkers is an alternative tool to complement currently used algorithms for detection of cancer, and to improve selection of therapeutic schemes. Aberrant expression of Ezrin and E-cadherin play an important role in tumor invasion. In this study we analyzed Ezrin and E-cadherin expression in liquid-based cervical cytology samples, and evaluated their potential use as prognostic immunomarkers. Immunocytochemical staining of Ezrin and E-cadherin was performed in cervical samples of 125 patients. The cytological or histological diagnostic was performed by Papanicolaou staining or H&E staining, respectively. HPV genotyping was determined using INNO-LIPA Genotyping Extra kit and the HPV physical status by in situ hybridization. Ezrin expression in HaCaT, HeLa and SiHa cell lines was determined by immunocytochemistry, immunofluorescence and Western blot. High Ezrin expression was observed in cervical cancer samples (70%), samples with multiple infection by HR-HPV (43%), and samples with integrated viral genome (47%). High Ezrin expression was associated with degree of SIL, viral genotype and physical status. In contrast, low E-cadherin expression was found in cervical cancer samples (95%), samples with multiple infection by HR-HPV/LR-HPV (87%) and integrated viral genome (72%). Low E-cadherin expression was associated with degree of SIL and viral genotype. Interestingly, Ezrin nuclear staining was associated with degree of SIL and viral genotype. High Ezrin expression, high percent of nuclear Ezrin and low E-cadherin expression behaved as risk factors for progression to HSIL and cervical cancer. Ezrin and E-cadherin expression profile in cervical cytology samples could be a potential prognostic marker, useful for identifying cervical lesions with a high-risk of progression to cervical cancer.
Feng, Ling; Wang, Ru; Lian, Meng; Ma, Hongzhi; He, Ning; Liu, Honggang; Wang, Haizhou; Fang, Jugao
2016-01-01
Long non-coding RNA (lncRNA) plays an important role in tumorigenesis. However, the expression pattern and function of lncRNAs in laryngeal squamous cell carcinoma (LSCC) are still unclear. To investigate the aberrantly expressed lncRNAs and mRNAs in advanced LSCC, we screened lncRNA and mRNA expression profiles in 9 pairs of primary Stage IVA LSCC tissues and adjacent non-neoplastic tissues by lncRNA and mRNA integrated microarrays. Gene Ontology and pathway analysis were performed to find out the significant function and pathway of the differentially expressed mRNAs, gene-gene functional interaction network and ceRNA network were constructed to select core mRNAs, and lncRNA-mRNA expression correlation network was built to identify the interactions between lncRNA and mRNA. qRT-PCR was performed to further validate the expressions of selected lncRNAs and mRNAs in advanced LSCC. We found 1459 differentially expressed lncRNAs and 2381 differentially expressed mRNAs, including 846 up-regulated lncRNAs and 613 down-regulated lncRNAs, 1542 up-regulated mRNAs and 839 down-regulated mRNAs. The mRNAs ITGB1, HIF1A, and DDIT4 were selected as core mRNAs, which are mainly involved in biological processes, such as matrix organization, cell cycle, adhesion, and metabolic pathway. LncRNA-mRNA expression correlation network showed LncRNA NR_027340, MIR31HG were positively correlated with ITGB1, HIF1A respectively. LncRNA SOX2-OT was negatively correlated with DDIT4. qRT-PCR further validated the expression of these lncRNAs and mRNAs. The work provides convincing evidence that the identified lncRNAs and mRNAs are potential biomarkers in advanced LSCC for further future studies.
A transcriptome-based examination of blood group expression
Noh, S.-J.; Lee, Y.T.; Byrnes, C.; Miller, J.L.
2011-01-01
Over the last two decades, red cell biologists witnessed a vast expansion of genetic-based information pertaining to blood group antigens and their carrier molecules. Genetic progress has led to a better comprehension of the associated antigens. To assist with studies concerning the integrated regulation and function of blood groups, transcript levels for each of the 36 associated genes were studied. Profiles using mRNA from directly sampled reticulocytes and cultured primary erythroblasts are summarized in this report. Transcriptome profiles suggest a highly regulated pattern of blood group gene expression during erythroid differentiation and ontogeny. Approximately one-third of the blood group carrier genes are transcribed in an erythroid-specific fashion. Low-level and indistinct expression was noted for most of the carbohydrate-associated genes. Methods are now being developed to further explore and manipulate expression of the blood group genes at all stages of human erythropoiesis. PMID:20685146
A regulatory toolbox of MiniPromoters to drive selective expression in the brain.
Portales-Casamar, Elodie; Swanson, Douglas J; Liu, Li; de Leeuw, Charles N; Banks, Kathleen G; Ho Sui, Shannan J; Fulton, Debra L; Ali, Johar; Amirabbasi, Mahsa; Arenillas, David J; Babyak, Nazar; Black, Sonia F; Bonaguro, Russell J; Brauer, Erich; Candido, Tara R; Castellarin, Mauro; Chen, Jing; Chen, Ying; Cheng, Jason C Y; Chopra, Vik; Docking, T Roderick; Dreolini, Lisa; D'Souza, Cletus A; Flynn, Erin K; Glenn, Randy; Hatakka, Kristi; Hearty, Taryn G; Imanian, Behzad; Jiang, Steven; Khorasan-zadeh, Shadi; Komljenovic, Ivana; Laprise, Stéphanie; Liao, Nancy Y; Lim, Jonathan S; Lithwick, Stuart; Liu, Flora; Liu, Jun; Lu, Meifen; McConechy, Melissa; McLeod, Andrea J; Milisavljevic, Marko; Mis, Jacek; O'Connor, Katie; Palma, Betty; Palmquist, Diana L; Schmouth, Jean-François; Swanson, Magdalena I; Tam, Bonny; Ticoll, Amy; Turner, Jenna L; Varhol, Richard; Vermeulen, Jenny; Watkins, Russell F; Wilson, Gary; Wong, Bibiana K Y; Wong, Siaw H; Wong, Tony Y T; Yang, George S; Ypsilanti, Athena R; Jones, Steven J M; Holt, Robert A; Goldowitz, Daniel; Wasserman, Wyeth W; Simpson, Elizabeth M
2010-09-21
The Pleiades Promoter Project integrates genomewide bioinformatics with large-scale knockin mouse production and histological examination of expression patterns to develop MiniPromoters and related tools designed to study and treat the brain by directed gene expression. Genes with brain expression patterns of interest are subjected to bioinformatic analysis to delineate candidate regulatory regions, which are then incorporated into a panel of compact human MiniPromoters to drive expression to brain regions and cell types of interest. Using single-copy, homologous-recombination "knockins" in embryonic stem cells, each MiniPromoter reporter is integrated immediately 5' of the Hprt locus in the mouse genome. MiniPromoter expression profiles are characterized in differentiation assays of the transgenic cells or in mouse brains following transgenic mouse production. Histological examination of adult brains, eyes, and spinal cords for reporter gene activity is coupled to costaining with cell-type-specific markers to define expression. The publicly available Pleiades MiniPromoter Project is a key resource to facilitate research on brain development and therapies.
Smith, Ryan C.; King, Jonas G.; Tao, Dingyin; Zeleznik, Oana A.; Brando, Clara; Thallinger, Gerhard G.; Dinglasan, Rhoel R.
2016-01-01
The innate immune response is highly conserved across all eukaryotes and has been studied in great detail in several model organisms. Hemocytes, the primary immune cell population in mosquitoes, are important components of the mosquito innate immune response, yet critical aspects of their biology have remained uncharacterized. Using a novel method of enrichment, we isolated phagocytic granulocytes and quantified their proteomes by mass spectrometry. The data demonstrate that phagocytosis, blood-feeding, and Plasmodium falciparum infection promote dramatic shifts in the proteomic profiles of An. gambiae granulocyte populations. Of interest, large numbers of immune proteins were induced in response to blood feeding alone, suggesting that granulocytes have an integral role in priming the mosquito immune system for pathogen challenge. In addition, we identify several granulocyte proteins with putative roles as membrane receptors, cell signaling, or immune components that when silenced, have either positive or negative effects on malaria parasite survival. Integrating existing hemocyte transcriptional profiles, we also compare differences in hemocyte transcript and protein expression to provide new insight into hemocyte gene regulation and discuss the potential that post-transcriptional regulation may be an important component of hemocyte gene expression. These data represent a significant advancement in mosquito hemocyte biology, providing the first comprehensive proteomic profiling of mosquito phagocytic granulocytes during homeostasis blood-feeding, and pathogen challenge. Together, these findings extend current knowledge to further illustrate the importance of hemocytes in shaping mosquito innate immunity and their principal role in defining malaria parasite survival in the mosquito host. PMID:27624304
Yoo, Seungyeul; Takikawa, Sachiko; Geraghty, Patrick; Argmann, Carmen; Campbell, Joshua; Lin, Luan; Huang, Tao; Tu, Zhidong; Feronjy, Robert; Spira, Avrum; Schadt, Eric E.; Powell, Charles A.; Zhu, Jun
2015-01-01
Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a ‘causal’ role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology. PMID:25569234
Integrated molecular portrait of non-small cell lung cancers
2013-01-01
Background Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC. Methods Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC. Results At DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of ~800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944. Conclusions Integrated molecular characterization of AC and SCC helped identify clinically relevant markers and potential drivers, which are recurrent and stable changes at DNA level that have functional implications at RNA level and have strong association with histological subtypes. PMID:24299561
Irigoyen, Antonio; Jimenez-Luna, Cristina; Benavides, Manuel; Caba, Octavio; Gallego, Javier; Ortuño, Francisco Manuel; Guillen-Ponce, Carmen; Rojas, Ignacio; Aranda, Enrique; Torres, Carolina; Prados, Jose
2018-01-01
Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.
Ohyanagi, Hajime; Takano, Tomoyuki; Terashima, Shin; Kobayashi, Masaaki; Kanno, Maasa; Morimoto, Kyoko; Kanegae, Hiromi; Sasaki, Yohei; Saito, Misa; Asano, Satomi; Ozaki, Soichi; Kudo, Toru; Yokoyama, Koji; Aya, Koichiro; Suwabe, Keita; Suzuki, Go; Aoki, Koh; Kubo, Yasutaka; Watanabe, Masao; Matsuoka, Makoto; Yano, Kentaro
2015-01-01
Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources. PMID:25505034
Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T
2016-01-04
Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan-Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Camps, Jordi; Nguyen, Quang Tri; Padilla-Nash, Hesed M.; Knutsen, Turid; McNeil, Nicole E.; Wangsa, Danny; Hummon, Amanda B.; Grade, Marian; Ried, Thomas; Difilippantonio, Michael J.
2016-01-01
To evaluate the mechanisms and consequences of chromosomal aberrations in colorectal cancer (CRC), we used a combination of spectral karyotyping, array comparative genomic hybridization (aCGH), and array-based global gene expression profiling on 31 primary carcinomas and 15 established cell lines. Importantly, aCGH showed that the genomic profiles of primary tumors are recapitulated in the cell lines. We revealed a preponderance of chromosome breakpoints at sites of copy number variants (CNVs) in the CRC cell lines, a novel mechanism of DNA breakage in cancer. The integration of gene expression and aCGH led to the identification of 157 genes localized within high-level copy number changes whose transcriptional deregulation was significantly affected across all of the samples, thereby suggesting that these genes play a functional role in CRC. Genomic amplification at 8q24 was the most recurrent event and led to the overexpression of MYC and FAM84B. Copy number dependent gene expression resulted in deregulation of known cancer genes such as APC, FGFR2, and ERBB2. The identification of only 36 genes whose localization near a breakpoint could account for their observed deregulated expression demonstrates that the major mechanism for transcriptional deregulation in CRC is genomic copy number changes resulting from chromosomal aberrations. PMID:19691111
Xiao, Han; Radovich, Cheryll; Welty, Nicholas; Hsu, Jason; Li, Dongmei; Meulia, Tea; van der Knaap, Esther
2009-01-01
Background Universally accepted landmark stages are necessary to highlight key events in plant reproductive development and to facilitate comparisons among species. Domestication and selection of tomato resulted in many varieties that differ in fruit shape and size. This diversity is useful to unravel underlying molecular and developmental mechanisms that control organ morphology and patterning. The tomato fruit shape gene SUN controls fruit elongation. The most dramatic effect of SUN on fruit shape occurs after pollination and fertilization although a detailed investigation into the timing of the fruit shape change as well as gene expression profiles during critical developmental stages has not been conducted. Results We provide a description of floral and fruit development in a red-fruited closely related wild relative of tomato, Solanum pimpinellifolium accession LA1589. We use established and propose new floral and fruit landmarks to present a framework for tomato developmental studies. In addition, gene expression profiles of three key stages in floral and fruit development are presented, namely floral buds 10 days before anthesis (floral landmark 7), anthesis-stage flowers (floral landmark 10 and fruit landmark 1), and 5 days post anthesis fruit (fruit landmark 3). To demonstrate the utility of the landmarks, we characterize the tomato shape gene SUN in fruit development. SUN controls fruit shape predominantly after fertilization and its effect reaches a maximum at 8 days post-anthesis coinciding with fruit landmark 4 representing the globular embryo stage of seed development. The expression profiles of the NILs that differ at sun show that only 34 genes were differentially expressed and most of them at a less than 2-fold difference. Conclusion The landmarks for flower and fruit development in tomato were outlined and integrated with the effect of SUN on fruit shape. Although we did not identify many genes differentially expressed in the NILs that differ at the sun locus, higher or lower transcript levels for many genes involved in phytohormone biosynthesis or signaling as well as organ identity and patterning of tomato fruit were found between developmental time points. PMID:19422692
Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella
2018-01-01
Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723
RAS oncogene-mediated deregulation of the transcriptome: from molecular signature to function.
Schäfer, Reinhold; Sers, Christine
2011-01-01
Transcriptome analysis of cancer cells has developed into a standard procedure to elucidate multiple features of the malignant process and to link gene expression to clinical properties. Gene expression profiling based on microarrays provides essentially correlative information and needs to be transferred to the functional level in order to understand the activity and contribution of individual genes or sets of genes as elements of the gene signature. To date, there exist significant gaps in the functional understanding of gene expression profiles. Moreover, the processes that drive the profound transcriptional alterations that characterize cancer cells remain mainly elusive. We have used pathway-restricted gene expression profiles derived from RAS oncogene-transformed cells and from RAS-expressing cancer cells to identify regulators downstream of the MAPK pathway.We describe the role of epigenetic regulation exemplified by the control of several immune genes in generic cell lines and colorectal cancer cells, particularly the functional interaction between signaling and DNA methylation. Moreover, we assess the role of the architectural transcription factor high mobility AT-hook 2 (HMGA2) as a regulator of the RAS-responsive transcriptome in ovarian epithelial cells. Finally, we describe an integrated approach combining pathway interference in colorectal cancer cells, gene expression profiling and computational analysis of regulatory elements of deregulated target genes. This strategy resulted in the identification of Y-box binding protein 1 (YBX1) as a regulator of MAPK-dependent proliferation and gene expression. The implications for a therapeutic application of HMGA2 gene silencing and the role of YBX1 as a prognostic factor are discussed.
Høgslund, Niels; Radutoiu, Simona; Krusell, Lene; Voroshilova, Vera; Hannah, Matthew A.; Goffard, Nicolas; Sanchez, Diego H.; Lippold, Felix; Ott, Thomas; Sato, Shusei; Tabata, Satoshi; Liboriussen, Poul; Lohmann, Gitte V.; Schauser, Leif; Weiller, Georg F.; Udvardi, Michael K.; Stougaard, Jens
2009-01-01
Genetic analyses of plant symbiotic mutants has led to the identification of key genes involved in Rhizobium-legume communication as well as in development and function of nitrogen fixing root nodules. However, the impact of these genes in coordinating the transcriptional programs of nodule development has only been studied in limited and isolated studies. Here, we present an integrated genome-wide analysis of transcriptome landscapes in Lotus japonicus wild-type and symbiotic mutant plants. Encompassing five different organs, five stages of the sequentially developed determinate Lotus root nodules, and eight mutants impaired at different stages of the symbiotic interaction, our data set integrates an unprecedented combination of organ- or tissue-specific profiles with mutant transcript profiles. In total, 38 different conditions sampled under the same well-defined growth regimes were included. This comprehensive analysis unravelled new and unexpected patterns of transcriptional regulation during symbiosis and organ development. Contrary to expectations, none of the previously characterized nodulins were among the 37 genes specifically expressed in nodules. Another surprise was the extensive transcriptional response in whole root compared to the susceptible root zone where the cellular response is most pronounced. A large number of transcripts predicted to encode transcriptional regulators, receptors and proteins involved in signal transduction, as well as many genes with unknown function, were found to be regulated during nodule organogenesis and rhizobial infection. Combining wild type and mutant profiles of these transcripts demonstrates the activation of a complex genetic program that delineates symbiotic nitrogen fixation. The complete data set was organized into an indexed expression directory that is accessible from a resource database, and here we present selected examples of biological questions that can be addressed with this comprehensive and powerful gene expression data set. PMID:19662091
Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells
Pelleri, Maria Chiara; Cattani, Chiara; Vitale, Lorenza; Antonaros, Francesca; Strippoli, Pierluigi; Locatelli, Chiara; Cocchi, Guido; Piovesan, Allison; Caracausi, Maria
2018-01-01
Down syndrome (DS) is due to the presence of an extra full or partial chromosome 21 (Hsa21). The identification of genes contributing to DS pathogenesis could be the key to any rational therapy of the associated intellectual disability. We aim at generating quantitative transcriptome maps in DS integrating all gene expression profile datasets available for any cell type or tissue, to obtain a complete model of the transcriptome in terms of both expression values for each gene and segmental trend of gene expression along each chromosome. We used the TRAM (Transcriptome Mapper) software for this meta-analysis, comparing transcript expression levels and profiles between DS and normal brain, lymphoblastoid cell lines, blood cells, fibroblasts, thymus and induced pluripotent stem cells, respectively. TRAM combined, normalized, and integrated datasets from different sources and across diverse experimental platforms. The main output was a linear expression value that may be used as a reference for each of up to 37,181 mapped transcripts analyzed, related to both known genes and expression sequence tag (EST) clusters. An independent example in vitro validation of fibroblast transcriptome map data was performed through “Real-Time” reverse transcription polymerase chain reaction showing an excellent correlation coefficient (r = 0.93, p < 0.0001) with data obtained in silico. The availability of linear expression values for each gene allowed the testing of the gene dosage hypothesis of the expected 3:2 DS/normal ratio for Hsa21 as well as other human genes in DS, in addition to listing genes differentially expressed with statistical significance. Although a fraction of Hsa21 genes escapes dosage effects, Hsa21 genes are selectively over-expressed in DS samples compared to genes from other chromosomes, reflecting a decisive role in the pathogenesis of the syndrome. Finally, the analysis of chromosomal segments reveals a high prevalence of Hsa21 over-expressed segments over the other genomic regions, suggesting, in particular, a specific region on Hsa21 that appears to be frequently over-expressed (21q22). Our complete datasets are released as a new framework to investigate transcription in DS for individual genes as well as chromosomal segments in different cell types and tissues. PMID:29740474
Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma
Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang
2017-01-01
Objective This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Methods Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Results Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification (P=0.009) or deletion (P=0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly (P=1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Conclusion Chromosomal CNVs may contribute to their transcript expression in cervical cancer. PMID:29312578
Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma.
Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang
2017-12-12
This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification ( P =0.009) or deletion ( P =0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly ( P =1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Chromosomal CNVs may contribute to their transcript expression in cervical cancer.
Weigt, S Samuel; Wang, Xiaoyan; Palchevskiy, Vyacheslav; Patel, Naman; Derhovanessian, Ariss; Shino, Michael Y; Sayah, David M; Lynch, Joseph P; Saggar, Rajan; Ross, David J; Kubak, Bernie M; Ardehali, Abbas; Palmer, Scott; Husain, Shahid; Belperio, John A
2018-06-01
Aspergillus colonization after lung transplant is associated with an increased risk of chronic lung allograft dysfunction (CLAD). We hypothesized that gene expression during Aspergillus colonization could provide clues to CLAD pathogenesis. We examined transcriptional profiles in 3- or 6-month surveillance bronchoalveolar lavage fluid cell pellets from recipients with Aspergillus fumigatus colonization (n = 12) and without colonization (n = 10). Among the Aspergillus colonized, we also explored profiles in those who developed CLAD (n = 6) or remained CLAD-free (n = 6). Transcription profiles were assayed with the HG-U133 Plus 2.0 microarray (Affymetrix). Differential gene expression was based on an absolute fold difference of 2.0 or greater and unadjusted P value less than 0.05. We used NIH Database for Annotation, Visualization and Integrated Discovery for functional analyses, with false discovery rates less than 5% considered significant. Aspergillus colonization was associated with differential expression of 489 probe sets, representing 404 unique genes. "Defense response" genes and genes in the "cytokine-cytokine receptor" Kyoto Encyclopedia of Genes and Genomes pathway were notably enriched in this list. Among Aspergillus colonized patients, CLAD development was associated with differential expression of 69 probe sets, representing 64 unique genes. This list was enriched for genes involved in "immune response" and "response to wounding", among others. Notably, both chitinase 3-like-1 and chitotriosidase were associated with progression to CLAD. Aspergillus colonization is associated with gene expression profiles related to defense responses including cytokine signaling. Epithelial wounding, as well as the innate immune response to chitin that is present in the fungal cell wall, may be key in the link between Aspergillus colonization and CLAD.
Wang, Hongyang; Owens, James D; Shih, Joanna H; Li, Ming-Chung; Bonner, Robert F; Mushinski, J Frederic
2006-04-27
Gene expression profiling by microarray analysis of cells enriched by laser capture microdissection (LCM) faces several technical challenges. Frozen sections yield higher quality RNA than paraffin-imbedded sections, but even with frozen sections, the staining methods used for histological identification of cells of interest could still damage the mRNA in the cells. To study the contribution of staining methods to degradation of results from gene expression profiling of LCM samples, we subjected pellets of the mouse plasma cell tumor cell line TEPC 1165 to direct RNA extraction and to parallel frozen sectioning for LCM and subsequent RNA extraction. We used microarray hybridization analysis to compare gene expression profiles of RNA from cell pellets with gene expression profiles of RNA from frozen sections that had been stained with hematoxylin and eosin (H&E), Nissl Stain (NS), and for immunofluorescence (IF) as well as with the plasma cell-revealing methyl green pyronin (MGP) stain. All RNAs were amplified with two rounds of T7-based in vitro transcription and analyzed by two-color expression analysis on 10-K cDNA microarrays. The MGP-stained samples showed the least introduction of mRNA loss, followed by H&E and immunofluorescence. Nissl staining was significantly more detrimental to gene expression profiles, presumably owing to an aqueous step in which RNA may have been damaged by endogenous or exogenous RNAases. RNA damage can occur during the staining steps preparatory to laser capture microdissection, with the consequence of loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts.
Wang, Hongyang; Owens, James D; Shih, Joanna H; Li, Ming-Chung; Bonner, Robert F; Mushinski, J Frederic
2006-01-01
Background Gene expression profiling by microarray analysis of cells enriched by laser capture microdissection (LCM) faces several technical challenges. Frozen sections yield higher quality RNA than paraffin-imbedded sections, but even with frozen sections, the staining methods used for histological identification of cells of interest could still damage the mRNA in the cells. To study the contribution of staining methods to degradation of results from gene expression profiling of LCM samples, we subjected pellets of the mouse plasma cell tumor cell line TEPC 1165 to direct RNA extraction and to parallel frozen sectioning for LCM and subsequent RNA extraction. We used microarray hybridization analysis to compare gene expression profiles of RNA from cell pellets with gene expression profiles of RNA from frozen sections that had been stained with hematoxylin and eosin (H&E), Nissl Stain (NS), and for immunofluorescence (IF) as well as with the plasma cell-revealing methyl green pyronin (MGP) stain. All RNAs were amplified with two rounds of T7-based in vitro transcription and analyzed by two-color expression analysis on 10-K cDNA microarrays. Results The MGP-stained samples showed the least introduction of mRNA loss, followed by H&E and immunofluorescence. Nissl staining was significantly more detrimental to gene expression profiles, presumably owing to an aqueous step in which RNA may have been damaged by endogenous or exogenous RNAases. Conclusion RNA damage can occur during the staining steps preparatory to laser capture microdissection, with the consequence of loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts. PMID:16643667
Nikolian, Vahagn C; Dekker, Simone E; Bambakidis, Ted; Higgins, Gerald A; Dennahy, Isabel S; Georgoff, Patrick E; Williams, Aaron M; Andjelkovic, Anuska V; Alam, Hasan B
2018-01-01
Combined traumatic brain injury and hemorrhagic shock are highly lethal. Following injuries, the integrity of the blood-brain barrier can be impaired, contributing to secondary brain insults. The status of the blood-brain barrier represents a potential factor impacting long-term neurologic outcomes in combined injuries. Treatment strategies involving plasma-based resuscitation and valproic acid therapy have shown efficacy in this setting. We hypothesize that a component of this beneficial effect is related to blood-brain barrier preservation. Following controlled traumatic brain injury, hemorrhagic shock, various resuscitation and treatment strategies were evaluated for their association with blood-brain barrier integrity. Analysis of gene expression profiles was performed using Porcine Gene ST 1.1 microarray. Pathway analysis was completed using network analysis tools (Gene Ontology, Ingenuity Pathway Analysis, and Parametric Gene Set Enrichment Analysis). Female Yorkshire swine were subjected to controlled traumatic brain injury and 2 hours of hemorrhagic shock (40% blood volume, mean arterial pressure 30-35 mmHg). Subjects were resuscitated with 1) normal saline, 2) fresh frozen plasma, 3) hetastarch, 4) fresh frozen plasma + valproic acid, or 5) hetastarch + valproic acid (n = 5 per group). After 6 hours of observation, brains were harvested for evaluation. Immunofluoroscopic evaluation of the traumatic brain injury site revealed significantly increased expression of tight-junction associated proteins (zona occludin-1, claudin-5) following combination therapy (fresh frozen plasma + valproic acid and hetastarch + valproic acid). The extracellular matrix protein laminin was found to have significantly improved expression with combination therapies. Pathway analysis indicated that valproic acid significantly modulated pathways involved in endothelial barrier function and cell signaling. Resuscitation with fresh frozen plasma results in improved expression of proteins essential for blood-brain barrier integrity. The addition of valproic acid provides significant improvement to these protein expression profiles. This is likely secondary to activation of key pathways related to endothelial functions.
Caracciolo, Daniele; Agnelli, Luca; Neri, Antonino; Walker, Brian A.; Morgan, Gareth J.; Cannataro, Mario
2015-01-01
Multiple Myeloma (MM) is a malignancy characterized by the hyperdiploid (HD-MM) and the non-hyperdiploid (nHD-MM) subtypes. To shed light within the molecular architecture of these subtypes, we used a novel integromics approach. By annotated MM patient mRNA/microRNA (miRNA) datasets, we investigated mRNAs and miRNAs profiles with relation to changes in transcriptional regulators expression. We found that HD-MM displays specific gene and miRNA expression profiles, involving the Signal Transducer and Activator of Transcription (STAT)3 pathway as well as the Transforming Growth Factor–beta (TGFβ) and the transcription regulator Nuclear Protein-1 (NUPR1). Our data define specific molecular features of HD-MM that may translate in the identification of novel relevant druggable targets. PMID:26056083
GTA: a game theoretic approach to identifying cancer subnetwork markers.
Farahmand, S; Goliaei, S; Ansari-Pour, N; Razaghi-Moghadam, Z
2016-03-01
The identification of genetic markers (e.g. genes, pathways and subnetworks) for cancer has been one of the most challenging research areas in recent years. A subset of these studies attempt to analyze genome-wide expression profiles to identify markers with high reliability and reusability across independent whole-transcriptome microarray datasets. Therefore, the functional relationships of genes are integrated with their expression data. However, for a more accurate representation of the functional relationships among genes, utilization of the protein-protein interaction network (PPIN) seems to be necessary. Herein, a novel game theoretic approach (GTA) is proposed for the identification of cancer subnetwork markers by integrating genome-wide expression profiles and PPIN. The GTA method was applied to three distinct whole-transcriptome breast cancer datasets to identify the subnetwork markers associated with metastasis. To evaluate the performance of our approach, the identified subnetwork markers were compared with gene-based, pathway-based and network-based markers. We show that GTA is not only capable of identifying robust metastatic markers, it also provides a higher classification performance. In addition, based on these GTA-based subnetworks, we identified a new bonafide candidate gene for breast cancer susceptibility.
Harris, R. Alan; Wang, Ting; Coarfa, Cristian; Nagarajan, Raman P.; Hong, Chibo; Downey, Sara L.; Johnson, Brett E.; Fouse, Shaun D.; Delaney, Allen; Zhao, Yongjun; Olshen, Adam; Ballinger, Tracy; Zhou, Xin; Forsberg, Kevin J.; Gu, Junchen; Echipare, Lorigail; O’Geen, Henriette; Lister, Ryan; Pelizzola, Mattia; Xi, Yuanxin; Epstein, Charles B.; Bernstein, Bradley E.; Hawkins, R. David; Ren, Bing; Chung, Wen-Yu; Gu, Hongcang; Bock, Christoph; Gnirke, Andreas; Zhang, Michael Q.; Haussler, David; Ecker, Joseph; Li, Wei; Farnham, Peggy J.; Waterland, Robert A.; Meissner, Alexander; Marra, Marco A.; Hirst, Martin; Milosavljevic, Aleksandar; Costello, Joseph F.
2010-01-01
Sequencing-based DNA methylation profiling methods are comprehensive and, as accuracy and affordability improve, will increasingly supplant microarrays for genome-scale analyses. Here, four sequencing-based methodologies were applied to biological replicates of human embryonic stem cells to compare their CpG coverage genome-wide and in transposons, resolution, cost, concordance and its relationship with CpG density and genomic context. The two bisulfite methods reached concordance of 82% for CpG methylation levels and 99% for non-CpG cytosine methylation levels. Using binary methylation calls, two enrichment methods were 99% concordant, while regions assessed by all four methods were 97% concordant. To achieve comprehensive methylome coverage while reducing cost, an approach integrating two complementary methods was examined. The integrative methylome profile along with histone methylation, RNA, and SNP profiles derived from the sequence reads allowed genome-wide assessment of allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression. PMID:20852635
Impact of Ischemia and Procurement Conditions on Gene Expression in Renal Cell Carcinoma
Liu, Nick W.; Sanford, Thomas; Srinivasan, Ramaprasad; Liu, Jack L.; Khurana, Kiranpreet; Aprelikova, Olga; Valero, Vladimir; Bechert, Charles; Worrell, Robert; Pinto, Peter A.; Yang, Youfeng; Merino, Maria; Linehan, W. Marston; Bratslavsky, Gennady
2013-01-01
Purpose Previous studies have shown that ischemia alters gene expression in normal and malignant tissues. There are no studies that evaluated effects of ischemia in renal tumors. This study examines the impact of ischemia and tissue procurement conditions on RNA integrity and gene expression in renal cell carcinoma. Experimental Design Ten renal tumors were resected without renal hilar clamping from 10 patients with renal clear cell carcinoma. Immediately after tumor resection, a piece of tumor was snap frozen. Remaining tumor samples were stored at 4C, 22C and 37C and frozen at 5, 30, 60, 120, and 240 minutes. Histopathologic evaluation was performed on all tissue samples, and only those with greater than 80% tumor were selected for further analysis. RNA integrity was confirmed by electropherograms and quantitated using RIN index. Altered gene expression was assessed by paired, two-sample t-test between the zero time point and aliquots from various conditions obtained from the same tumor. Results One hundred and forty microarrays were performed. Some RNA degradation was observed 240 mins after resection at 37C. The expression of over 4,000 genes was significantly altered by ischemia times or storage conditions. The greatest gene expression changes were observed with longer ischemia time and warmer tissue procurement conditions. Conclusion RNA from kidney cancer remains intact for up to 4 hours post surgical resection regardless of storage conditions. Despite excellent RNA preservation, time after resection and procurement conditions significantly influence gene expression profiles. Meticulous attention to pre-acquisition variables is of paramount importance for accurate tumor profiling. PMID:23136194
Gorini, Giorgio; Nunez, Yury O.; Mayfield, R. Dayne
2013-01-01
The molecular mechanisms underlying alcohol dependence involve different neurochemical systems and are brain region-dependent. Chronic Intermittent Ethanol (CIE) procedure, combined with a Two-Bottle Choice voluntary drinking paradigm, represents one of the best available animal models for alcohol dependence and relapse drinking. MicroRNAs, master regulators of the cellular transcriptome and proteome, can regulate their targets in a cooperative, combinatorial fashion, ensuring fine tuning and control over a large number of cellular functions. We analyzed cortex and midbrain microRNA expression levels using an integrative approach to combine and relate data to previous protein profiling from the same CIE-subjected samples, and examined the significance of the data in terms of relative contribution to alcohol consumption and dependence. MicroRNA levels were significantly altered in CIE-exposed dependent mice compared with their non-dependent controls. More importantly, our integrative analysis identified modules of coexpressed microRNAs that were highly correlated with CIE effects and predicted target genes encoding differentially expressed proteins. Coexpressed CIE-relevant proteins, in turn, were often negatively correlated with specific microRNA modules. Our results provide evidence that microRNA-orchestrated translational imbalances are driving the behavioral transition from alcohol consumption to dependence. This study represents the first attempt to combine ex vivo microRNA and protein expression on a global scale from the same mammalian brain samples. The integrative systems approach used here will improve our understanding of brain adaptive changes in response to drug abuse and suggests the potential therapeutic use of microRNAs as tools to prevent or compensate multiple neuroadaptations underlying addictive behavior. PMID:24358208
mirEX: a platform for comparative exploration of plant pri-miRNA expression data.
Bielewicz, Dawid; Dolata, Jakub; Zielezinski, Andrzej; Alaba, Sylwia; Szarzynska, Bogna; Szczesniak, Michal W; Jarmolowski, Artur; Szweykowska-Kulinska, Zofia; Karlowski, Wojciech M
2012-01-01
mirEX is a comprehensive platform for comparative analysis of primary microRNA expression data. RT-qPCR-based gene expression profiles are stored in a universal and expandable database scheme and wrapped by an intuitive user-friendly interface. A new way of accessing gene expression data in mirEX includes a simple mouse operated querying system and dynamic graphs for data mining analyses. In contrast to other publicly available databases, the mirEX interface allows a simultaneous comparison of expression levels between various microRNA genes in diverse organs and developmental stages. Currently, mirEX integrates information about the expression profile of 190 Arabidopsis thaliana pri-miRNAs in seven different developmental stages: seeds, seedlings and various organs of mature plants. Additionally, by providing RNA structural models, publicly available deep sequencing results, experimental procedure details and careful selection of auxiliary data in the form of web links, mirEX can function as a one-stop solution for Arabidopsis microRNA information. A web-based mirEX interface can be accessed at http://bioinfo.amu.edu.pl/mirex.
Dittmar, W James; McIver, Lauren; Michalak, Pawel; Garner, Harold R; Valdez, Gregorio
2014-07-01
The wealth of publicly available gene expression and genomic data provides unique opportunities for computational inference to discover groups of genes that function to control specific cellular processes. Such genes are likely to have co-evolved and be expressed in the same tissues and cells. Unfortunately, the expertise and computational resources required to compare tens of genomes and gene expression data sets make this type of analysis difficult for the average end-user. Here, we describe the implementation of a web server that predicts genes involved in affecting specific cellular processes together with a gene of interest. We termed the server 'EvoCor', to denote that it detects functional relationships among genes through evolutionary analysis and gene expression correlation. This web server integrates profiles of sequence divergence derived by a Hidden Markov Model (HMM) and tissue-wide gene expression patterns to determine putative functional linkages between pairs of genes. This server is easy to use and freely available at http://pilot-hmm.vbi.vt.edu/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Evans, Tyler G.; Hofmann, Gretchen E.
2012-01-01
Anthropogenic stressors, such as climate change, are driving fundamental shifts in the abiotic characteristics of marine ecosystems. As the environmental aspects of our world's oceans deviate from evolved norms, of major concern is whether extant marine species possess the capacity to cope with such rapid change. In what many scientists consider the post-genomic era, tools that exploit the availability of DNA sequence information are being increasingly recognized as relevant to questions surrounding ocean change and marine conservation. In this review, we highlight the application of high-throughput gene-expression profiling, primarily transcriptomics, to the field of marine conservation physiology. Through the use of case studies, we illustrate how gene expression can be used to standardize metrics of sub-lethal stress, track organism condition in natural environments and bypass phylogenetic barriers that hinder the application of other physiological techniques to conservation. When coupled with fine-scale monitoring of environmental variables, gene-expression profiling provides a powerful approach to conservation capable of informing diverse issues related to ocean change, from coral bleaching to the spread of invasive species. Integrating novel approaches capable of improving existing conservation strategies, including gene-expression profiling, will be critical to ensuring the ecological and economic health of the global ocean. PMID:22566679
Zheng, Chao; Zhao, Lei; Wang, Yu; Shen, Jiazhi; Zhang, Yinfei; Jia, Sisi; Li, Yusheng; Ding, Zhaotang
2015-01-01
Tea [Camellia sinensis (L) O. Kuntze, Theaceae] is one of the most popular non-alcoholic beverages worldwide. Cold stress is one of the most severe abiotic stresses that limit tea plants’ growth, survival and geographical distribution. However, the genetic regulatory network and signaling pathways involved in cold stress responses in tea plants remain unearthed. Using RNA-Seq, DGE and sRNA-Seq technologies, we performed an integrative analysis of miRNA and mRNA expression profiling and their regulatory network of tea plants under chilling (4℃) and freezing (-5℃) stress. Differentially expressed (DE) miRNA and mRNA profiles were obtained based on fold change analysis, miRNAs and target mRNAs were found to show both coherent and incoherent relationships in the regulatory network. Furthermore, we compared several key pathways (e.g., ‘Photosynthesis’), GO terms (e.g., ‘response to karrikin’) and transcriptional factors (TFs, e.g., DREB1b/CBF1) which were identified as involved in the early chilling and/or freezing response of tea plants. Intriguingly, we found that karrikins, a new group of plant growth regulators, and β-primeverosidase (BPR), a key enzyme functionally relevant with the formation of tea aroma might play an important role in both early chilling and freezing response of tea plants. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-Seq and sRNA-Seq analysis. This is the first study to simultaneously profile the expression patterns of both miRNAs and mRNAs on a genome-wide scale to elucidate the molecular mechanisms of early responses of tea plants to cold stress. In addition to gaining a deeper insight into the cold resistant characteristics of tea plants, we provide a good case study to analyse mRNA/miRNA expression and profiling of non-model plant species using next-generation sequencing technology. PMID:25901577
Zheng, Chao; Zhao, Lei; Wang, Yu; Shen, Jiazhi; Zhang, Yinfei; Jia, Sisi; Li, Yusheng; Ding, Zhaotang
2015-01-01
Tea [Camellia sinensis (L) O. Kuntze, Theaceae] is one of the most popular non-alcoholic beverages worldwide. Cold stress is one of the most severe abiotic stresses that limit tea plants' growth, survival and geographical distribution. However, the genetic regulatory network and signaling pathways involved in cold stress responses in tea plants remain unearthed. Using RNA-Seq, DGE and sRNA-Seq technologies, we performed an integrative analysis of miRNA and mRNA expression profiling and their regulatory network of tea plants under chilling (4℃) and freezing (-5℃) stress. Differentially expressed (DE) miRNA and mRNA profiles were obtained based on fold change analysis, miRNAs and target mRNAs were found to show both coherent and incoherent relationships in the regulatory network. Furthermore, we compared several key pathways (e.g., 'Photosynthesis'), GO terms (e.g., 'response to karrikin') and transcriptional factors (TFs, e.g., DREB1b/CBF1) which were identified as involved in the early chilling and/or freezing response of tea plants. Intriguingly, we found that karrikins, a new group of plant growth regulators, and β-primeverosidase (BPR), a key enzyme functionally relevant with the formation of tea aroma might play an important role in both early chilling and freezing response of tea plants. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-Seq and sRNA-Seq analysis. This is the first study to simultaneously profile the expression patterns of both miRNAs and mRNAs on a genome-wide scale to elucidate the molecular mechanisms of early responses of tea plants to cold stress. In addition to gaining a deeper insight into the cold resistant characteristics of tea plants, we provide a good case study to analyse mRNA/miRNA expression and profiling of non-model plant species using next-generation sequencing technology.
Building gene expression profile classifiers with a simple and efficient rejection option in R.
Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Hafeezurrehman, Hafeez
2011-01-01
The collection of gene expression profiles from DNA microarrays and their analysis with pattern recognition algorithms is a powerful technology applied to several biological problems. Common pattern recognition systems classify samples assigning them to a set of known classes. However, in a clinical diagnostics setup, novel and unknown classes (new pathologies) may appear and one must be able to reject those samples that do not fit the trained model. The problem of implementing a rejection option in a multi-class classifier has not been widely addressed in the statistical literature. Gene expression profiles represent a critical case study since they suffer from the curse of dimensionality problem that negatively reflects on the reliability of both traditional rejection models and also more recent approaches such as one-class classifiers. This paper presents a set of empirical decision rules that can be used to implement a rejection option in a set of multi-class classifiers widely used for the analysis of gene expression profiles. In particular, we focus on the classifiers implemented in the R Language and Environment for Statistical Computing (R for short in the remaining of this paper). The main contribution of the proposed rules is their simplicity, which enables an easy integration with available data analysis environments. Since in the definition of a rejection model tuning of the involved parameters is often a complex and delicate task, in this paper we exploit an evolutionary strategy to automate this process. This allows the final user to maximize the rejection accuracy with minimum manual intervention. This paper shows how the use of simple decision rules can be used to help the use of complex machine learning algorithms in real experimental setups. The proposed approach is almost completely automated and therefore a good candidate for being integrated in data analysis flows in labs where the machine learning expertise required to tune traditional classifiers might not be available.
Sunkel, Benjamin; Wu, Dayong; Chen, Zhong; Wang, Chiou-Miin; Liu, Xiangtao; Ye, Zhenqing; Horning, Aaron M; Liu, Joseph; Mahalingam, Devalingam; Lopez-Nicora, Horacio; Lin, Chun-Lin; Goodfellow, Paul J; Clinton, Steven K; Jin, Victor X; Chen, Chun-Liang; Huang, Tim H-M; Wang, Qianben
2016-05-19
Identifying prostate cancer-driving transcription factors (TFs) in addition to the androgen receptor promises to improve our ability to effectively diagnose and treat this disease. We employed an integrative genomics analysis of master TFs CREB1 and FoxA1 in androgen-dependent prostate cancer (ADPC) and castration-resistant prostate cancer (CRPC) cell lines, primary prostate cancer tissues and circulating tumor cells (CTCs) to investigate their role in defining prostate cancer gene expression profiles. Combining genome-wide binding site and gene expression profiles we define CREB1 as a critical driver of pro-survival, cell cycle and metabolic transcription programs. We show that CREB1 and FoxA1 co-localize and mutually influence each other's binding to define disease-driving transcription profiles associated with advanced prostate cancer. Gene expression analysis in human prostate cancer samples found that CREB1/FoxA1 target gene panels predict prostate cancer recurrence. Finally, we showed that this signaling pathway is sensitive to compounds that inhibit the transcription co-regulatory factor MED1. These findings not only reveal a novel, global transcriptional co-regulatory function of CREB1 and FoxA1, but also suggest CREB1/FoxA1 signaling is a targetable driver of prostate cancer progression and serves as a biomarker of poor clinical outcomes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
2008-05-12
The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less
Cruz-Rodriguez, Nataly; Combita, Alba L; Enciso, Leonardo J; Raney, Lauren F; Pinzon, Paula L; Lozano, Olga C; Campos, Alba M; Peñaloza, Niyireth; Solano, Julio; Herrera, Maria V; Zabaleta, Jovanny; Quijano, Sandra
2017-02-28
Survival of adults with B-Acute Lymphoblastic Leukemia requires accurate risk stratification of patients in order to provide the appropriate therapy. Contemporary techniques, using clinical and cytogenetic variables are incomplete for prognosis prediction. To improve the classification of adult patients diagnosed with B-ALL into prognosis groups, two strategies were examined and combined: the expression of the ID1/ID3/IGJ gene signature by RT-PCR and the immunophenotypic profile of 19 markers proposed in the EuroFlow protocol by Flow Cytometry in bone marrow samples. Both techniques were correlated to stratify patients into prognostic groups. An inverse relationship between survival and expression of the three-genes signature was observed and an immunophenotypic profile associated with clinical outcome was identified. Markers CD10 and CD20 were correlated with simultaneous overexpression of ID1, ID3 and IGJ. Patients with simultaneous expression of the poor prognosis gene signature and overexpression of CD10 or CD20, had worse Event Free Survival and Overall Survival than patients who had either the poor prognosis gene expression signature or only CD20 or CD10 overexpressed. By utilizing the combined evaluation of these two immunophenotypic markers along with the poor prognosis gene expression signature, the risk stratification can be significantly strengthened. Further studies including a large number of patients are needed to confirm these findings.
Endothelial effects of emission source particles: acute toxic response gene expression profiles.
Nadadur, Srikanth S; Haykal-Coates, Najwa; Mudipalli, Anuradha; Costa, Daniel L
2009-02-01
Air pollution epidemiology has established a strong association between exposure to ambient particulate matter (PM) and cardiovascular outcomes. Experimental studies in both humans and laboratory animals support varied biological mechanisms including endothelial dysfunction as potentially a central step to the elicitation of cardiovascular events. We therefore hypothesized that relevant early molecular alterations on endothelial cells should be assessable in vitro upon acute exposure to PM components previously shown to be involved in health outcomes. Using a model emission PM, residual oil fly ash and one of its predominant constituents (vanadium-V), we focused on the development of gene expression profiles to fingerprint that particle and its constituents to explore potential biomarkers for PM-induced endothelial dysfunction. Here we present differential gene expression and transcription factor activation profiles in human vascular endothelial cells exposed to a non-cytotoxic dose of fly ash or V following semi-global gene expression profiling of approximately 8000 genes. Both fly ash and it's prime constituent, V, induced alterations in genes involved in passive and active transport of solutes across the membrane; voltage-dependent ion pumps; induction of extracellular matrix proteins and adhesion molecules; and activation of numerous kinases involved in signal transduction pathways. These preliminary data suggest that cardiovascular effects associated with exposure to PM may be mediated by perturbations in endothelial cell permeability, membrane integrity; and ultimately endothelial dysfunction.
Kong, SW; Shimizu-Motohashi, Y; Campbell, MG; Lee, IH; Collins, CD; Brewster, SJ; Holm, IA; Rappaport, L
2013-01-01
Autism spectrum disorder (ASD) is one of the most prevalent neurodevelopmental disorders with high heritability, yet a majority of genetic contribution to pathophysiology is not known. Siblings of individuals with ASD are at increased risk for ASD and autistic traits, but the genetic contribution for simplex families is estimated to be less when compared to multiplex families. To explore the genomic (dis-) similarity between proband and unaffected sibling in simplex families, we used genome-wide gene expression profiles of blood from 20 proband-unaffected sibling pairs and 18 unrelated control individuals. The global gene expression profiles of unaffected siblings were more similar to those from probands as they shared genetic and environmental background. One hundred eighty nine genes were significantly differentially expressed between proband-sib pairs (nominal p-value < 0.01) after controlling for age, sex, and family effects. Probands and siblings were distinguished into two groups by cluster analysis with these genes. Overall, unaffected siblings were equally distant from the centroid of probands and from that of unrelated controls with the differentially expressed genes. Interestingly, 5 of 20 siblings had gene expression profiles that were more similar to unrelated controls than to their matched probands. In summary, we found a set of genes that distinguished probands from the unaffected siblings, and a subgroup of unaffected siblings who were more similar to probands. The pathways that characterized probands compared to siblings using peripheral blood gene expression profiles were the up-regulation of ribosomal, spliceosomal, and mitochondrial pathways, and the down-regulation of neuroreceptor-ligand, immune response and calcium signaling pathways. Further integrative study with structural genetic variations such as de novo mutations, rare variants, and copy number variations would clarify whether these transcriptomic changes are structural or environmental in origin. PMID:23625158
Effects of surface roughness and absorption on light propagation in graded-profile waveguides
DOE Office of Scientific and Technical Information (OSTI.GOV)
Danilenko, S S; Osovitskii, A N
2011-06-30
This paper examines the effects of surface roughness and absorption on laser light propagation in graded-profile waveguiding structures. We derive analytical expressions for the scattering and absorption coefficients of guided waves and analyse these coefficients in relation to parameters of the waveguiding structure and the roughness of its boundary. A new approach is proposed to measuring roughness parameters of precision dielectric surfaces. Experimental evidence is presented which supports the main conclusions of the theory. (integraled-optical waweguides)
Yin, Ji-Yuan; Guo, Chao-Qun; Wang, Zi; Yu, Mei-Ling; Gao, Shuai; Bukhari, Syed M; Tang, Li-Jie; Xu, Yi-Gang; Li, Yi-Jing
2016-11-01
Using two-step plasmid integration in the presence of 5-fluorouracil (5-FU), we developed a stable and markerless Lactobacillus casei strain for vaccine antigen expression. The upp of L. casei, which encodes uracil phosphoribosyltransferase (UPRTase), was used as a counterselection marker. We employed the Δupp isogenic mutant, which is resistant to 5-FU, as host and a temperature-sensitive suicide plasmid bearing upp expression cassette as counterselectable integration vector. Extrachromosomal expression of UPRTase complemented the mutated chromosomal upp allele and restored sensitivity to 5-FU. The resultant genotype can either be wild type or recombinant. The efficacy of the system was demonstrated by insertion and expression of porcine rotavirus (PRV) VP4. To improve VP4 expression, we analyzed L. casei transcriptional profiles and selected the constitutive highly expressed enolase gene (eno). The VP4 inserted after the eno termination codon were screened in the presence of 5-FU. Using genomic PCR amplification, we confirmed that VP4 was successfully integrated and stably inherited for at least 50 generations. Western blot demonstrated that VP4 was steadily expressed in medium with different carbohydrates. RT-qPCR and ELISA analysis showed that VP4 expression from the chromosomal location was similar to that achieved by a plasmid expression system. Applying the recombinant strain to immunize BALB/c mice via oral administration revealed that the VP4-expressing L. casei could induce both specific local and systemic humoral immune responses in mice. Overall, the improved gene replacement system represents an efficient method for chromosome recombination in L. casei and provides a safe tool for vaccine production.
A regulatory toolbox of MiniPromoters to drive selective expression in the brain
Portales-Casamar, Elodie; Swanson, Douglas J.; Liu, Li; de Leeuw, Charles N.; Banks, Kathleen G.; Ho Sui, Shannan J.; Fulton, Debra L.; Ali, Johar; Amirabbasi, Mahsa; Arenillas, David J.; Babyak, Nazar; Black, Sonia F.; Bonaguro, Russell J.; Brauer, Erich; Candido, Tara R.; Castellarin, Mauro; Chen, Jing; Chen, Ying; Cheng, Jason C. Y.; Chopra, Vik; Docking, T. Roderick; Dreolini, Lisa; D'Souza, Cletus A.; Flynn, Erin K.; Glenn, Randy; Hatakka, Kristi; Hearty, Taryn G.; Imanian, Behzad; Jiang, Steven; Khorasan-zadeh, Shadi; Komljenovic, Ivana; Laprise, Stéphanie; Liao, Nancy Y.; Lim, Jonathan S.; Lithwick, Stuart; Liu, Flora; Liu, Jun; Lu, Meifen; McConechy, Melissa; McLeod, Andrea J.; Milisavljevic, Marko; Mis, Jacek; O'Connor, Katie; Palma, Betty; Palmquist, Diana L.; Schmouth, Jean-François; Swanson, Magdalena I.; Tam, Bonny; Ticoll, Amy; Turner, Jenna L.; Varhol, Richard; Vermeulen, Jenny; Watkins, Russell F.; Wilson, Gary; Wong, Bibiana K. Y.; Wong, Siaw H.; Wong, Tony Y. T.; Yang, George S.; Ypsilanti, Athena R.; Jones, Steven J. M.; Holt, Robert A.; Goldowitz, Daniel; Wasserman, Wyeth W.; Simpson, Elizabeth M.
2010-01-01
The Pleiades Promoter Project integrates genomewide bioinformatics with large-scale knockin mouse production and histological examination of expression patterns to develop MiniPromoters and related tools designed to study and treat the brain by directed gene expression. Genes with brain expression patterns of interest are subjected to bioinformatic analysis to delineate candidate regulatory regions, which are then incorporated into a panel of compact human MiniPromoters to drive expression to brain regions and cell types of interest. Using single-copy, homologous-recombination “knockins” in embryonic stem cells, each MiniPromoter reporter is integrated immediately 5′ of the Hprt locus in the mouse genome. MiniPromoter expression profiles are characterized in differentiation assays of the transgenic cells or in mouse brains following transgenic mouse production. Histological examination of adult brains, eyes, and spinal cords for reporter gene activity is coupled to costaining with cell-type–specific markers to define expression. The publicly available Pleiades MiniPromoter Project is a key resource to facilitate research on brain development and therapies. PMID:20807748
Asgari, Yazdan; Khosravi, Pegah; Zabihinpour, Zahra; Habibi, Mahnaz
2018-02-19
Genome-scale metabolic models have provided valuable resources for exploring changes in metabolism under normal and cancer conditions. However, metabolism itself is strongly linked to gene expression, so integration of gene expression data into metabolic models might improve the detection of genes involved in the control of tumor progression. Herein, we considered gene expression data as extra constraints to enhance the predictive powers of metabolic models. We reconstructed genome-scale metabolic models for lung and prostate, under normal and cancer conditions to detect the major genes associated with critical subsystems during tumor development. Furthermore, we utilized gene expression data in combination with an information theory-based approach to reconstruct co-expression networks of the human lung and prostate in both cohorts. Our results revealed 19 genes as candidate biomarkers for lung and prostate cancer cells. This study also revealed that the development of a complementary approach (integration of gene expression and metabolic profiles) could lead to proposing novel biomarkers and suggesting renovated cancer treatment strategies which have not been possible to detect using either of the methods alone.
Profiling Religious Fundamentalism's Associations with Vocational Interests
ERIC Educational Resources Information Center
Warlick, Craig A.; Ingram, Paul B.; Multon, Karen D.; Vuyk, M. Alexandra
2017-01-01
Religion is a shaping force in the world today, increasingly expressed and integral to the flow and function of the workplace. The relationship between religious identity and work function is clearly present. However, no lines of research have explored how religion explains the variations in vocational interest, despite speculation that it does…
Using in vitro models for expression profiling studies on ethanol and drugs of abuse.
Thibault, Christelle; Hassan, Sajida; Miles, Michael
2005-03-01
The use of expression profiling with microarrays offers great potential for studying the mechanisms of action of drugs of abuse. Studies with the intact nervous system seem likely to be most relevant to understanding the mechanisms of drug abuse-related behaviours. However, the use of expression profiling with in vitro culture models offers significant advantages for identifying details of cellular signalling actions and toxicity for drugs of abuse. This study discusses general issues of the use of microarrays and cell culture models for studies on drugs of abuse. Specific results from existing studies are also discussed, providing clear examples of relevance for in vitro studies on ethanol, nicotine, opiates, cannabinoids and hallucinogens such as LSD. In addition to providing details on signalling mechanisms relevant to the neurobiology of drugs of abuse, microarray studies on a variety of cell culture systems have also provided important information on mechanisms of cellular/organ toxicity with drugs of abuse. Efforts to integrate genomic studies on drugs of abuse with both in vivo and in vitro models offer the potential for novel mechanistic rigor and physiological relevance.
Angelastro, James M.; Klimaschewski, Lars; Tang, Song; Vitolo, Ottavio V.; Weissman, Tamily A.; Donlin, Laura T.; Shelanski, Michael L.; Greene, Lloyd A.
2000-01-01
Neurotrophic factors such as nerve growth factor (NGF) promote a wide variety of responses in neurons, including differentiation, survival, plasticity, and repair. Such actions often require changes in gene expression. To identify the regulated genes and thereby to more fully understand the NGF mechanism, we carried out serial analysis of gene expression (SAGE) profiling of transcripts derived from rat PC12 cells before and after NGF-promoted neuronal differentiation. Multiple criteria supported the reliability of the profile. Approximately 157,000 SAGE tags were analyzed, representing at least 21,000 unique transcripts. Of these, nearly 800 were regulated by 6-fold or more in response to NGF. Approximately 150 of the regulated transcripts have been matched to named genes, the majority of which were not previously known to be NGF-responsive. Functional categorization of the regulated genes provides insight into the complex, integrated mechanism by which NGF promotes its multiple actions. It is anticipated that as genomic sequence information accrues the data derived here will continue to provide information about neurotrophic factor mechanisms. PMID:10984536
Ohyanagi, Hajime; Takano, Tomoyuki; Terashima, Shin; Kobayashi, Masaaki; Kanno, Maasa; Morimoto, Kyoko; Kanegae, Hiromi; Sasaki, Yohei; Saito, Misa; Asano, Satomi; Ozaki, Soichi; Kudo, Toru; Yokoyama, Koji; Aya, Koichiro; Suwabe, Keita; Suzuki, Go; Aoki, Koh; Kubo, Yasutaka; Watanabe, Masao; Matsuoka, Makoto; Yano, Kentaro
2015-01-01
Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.
Cytoscape: a software environment for integrated models of biomolecular interaction networks.
Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey
2003-11-01
Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
DeSantis, Michael C; DeCenzo, Shawn H; Li, Je-Luen; Wang, Y M
2010-03-29
Standard deviation measurements of intensity profiles of stationary single fluorescent molecules are useful for studying axial localization, molecular orientation, and a fluorescence imaging system's spatial resolution. Here we report on the analysis of the precision of standard deviation measurements of intensity profiles of single fluorescent molecules imaged using an EMCCD camera.We have developed an analytical expression for the standard deviation measurement error of a single image which is a function of the total number of detected photons, the background photon noise, and the camera pixel size. The theoretical results agree well with the experimental, simulation, and numerical integration results. Using this expression, we show that single-molecule standard deviation measurements offer nanometer precision for a large range of experimental parameters.
Ye, Bingyuan; Wang, Ruihua; Wang, Jianbo
2016-01-01
Raphanobrassica is an allopolyploid species derived from inter-generic hybridization that combines the R genome from R. sativus and the C genome from B. oleracea var. alboglabra. In the present study, we used a high-throughput sequencing method to identify the mRNA and miRNA profiles in Raphanobrassica and its parents. A total of 33,561 mRNAs and 283 miRNAs were detected, 9,209 mRNAs and 134 miRNAs were differentially expressed respectively, 7,633 mRNAs and 39 miRNAs showed ELD expression, 5,219 mRNAs and 57 miRNAs were non-additively expressed in Raphanobrassica. Remarkably, differentially expressed genes (DEGs) were up-regulated and maternal bias was detected in Raphanobrassica. In addition, a miRNA-mRNA interaction network was constructed based on reverse regulated miRNA-mRNAs, which included 75 miRNAs and 178 mRNAs, 31 miRNAs were non-additively expressed target by 13 miRNAs. The related target genes were significantly enriched in the GO term ‘metabolic processes’. Non-additive related target genes regulation is involved in a range of biological pathways, like providing a driving force for variation and adaption in this allopolyploid. The integrative analysis of mRNA and miRNA profiling provides more information to elucidate gene expression mechanism and may supply a comprehensive and corresponding method to study genetic and transcription variation of allopolyploid. PMID:27874043
Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis
Yang, Fang; Wang, Yumei
2018-01-01
Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis. PMID:29805480
Ota, Satoshi; Taimatsu, Kiyohito; Yanagi, Kanoko; Namiki, Tomohiro; Ohga, Rie; Higashijima, Shin-Ichi; Kawahara, Atsuo
2016-10-11
The CRISPR/Cas9 complex, which is composed of a guide RNA (gRNA) and the Cas9 nuclease, is useful for carrying out genome modifications in various organisms. Recently, the CRISPR/Cas9-mediated locus-specific integration of a reporter, which contains the Mbait sequence targeted using Mbait-gRNA, the hsp70 promoter and the eGFP gene, has allowed the visualization of the target gene expression. However, it has not been ascertained whether the reporter integrations at both targeted alleles cause loss-of-function phenotypes in zebrafish. In this study, we have inserted the Mbait-hs-eGFP reporter into the pax2a gene because the disruption of pax2a causes the loss of the midbrain-hindbrain boundary (MHB) in zebrafish. In the heterozygous Tg[pax2a-hs:eGFP] embryos, MHB formed normally and the eGFP expression recapitulated the endogenous pax2a expression, including the MHB. We observed the loss of the MHB in homozygous Tg[pax2a-hs:eGFP] embryos. Furthermore, we succeeded in integrating the Mbait-hs-eGFP reporter into an uncharacterized gene epdr1. The eGFP expression in heterozygous Tg[epdr1-hs:eGFP] embryos overlapped the epdr1 expression, whereas the distribution of eGFP-positive cells was disorganized in the MHB of homozygous Tg[epdr1-hs:eGFP] embryos. We propose that the locus-specific integration of the Mbait-hs-eGFP reporter is a powerful method to investigate both gene expression profiles and loss-of-function phenotypes.
Ota, Satoshi; Taimatsu, Kiyohito; Yanagi, Kanoko; Namiki, Tomohiro; Ohga, Rie; Higashijima, Shin-ichi; Kawahara, Atsuo
2016-01-01
The CRISPR/Cas9 complex, which is composed of a guide RNA (gRNA) and the Cas9 nuclease, is useful for carrying out genome modifications in various organisms. Recently, the CRISPR/Cas9-mediated locus-specific integration of a reporter, which contains the Mbait sequence targeted using Mbait-gRNA, the hsp70 promoter and the eGFP gene, has allowed the visualization of the target gene expression. However, it has not been ascertained whether the reporter integrations at both targeted alleles cause loss-of-function phenotypes in zebrafish. In this study, we have inserted the Mbait-hs-eGFP reporter into the pax2a gene because the disruption of pax2a causes the loss of the midbrain-hindbrain boundary (MHB) in zebrafish. In the heterozygous Tg[pax2a-hs:eGFP] embryos, MHB formed normally and the eGFP expression recapitulated the endogenous pax2a expression, including the MHB. We observed the loss of the MHB in homozygous Tg[pax2a-hs:eGFP] embryos. Furthermore, we succeeded in integrating the Mbait-hs-eGFP reporter into an uncharacterized gene epdr1. The eGFP expression in heterozygous Tg[epdr1-hs:eGFP] embryos overlapped the epdr1 expression, whereas the distribution of eGFP-positive cells was disorganized in the MHB of homozygous Tg[epdr1-hs:eGFP] embryos. We propose that the locus-specific integration of the Mbait-hs-eGFP reporter is a powerful method to investigate both gene expression profiles and loss-of-function phenotypes. PMID:27725766
Dense module enumeration in biological networks
NASA Astrophysics Data System (ADS)
Tsuda, Koji; Georgii, Elisabeth
2009-12-01
Analysis of large networks is a central topic in various research fields including biology, sociology, and web mining. Detection of dense modules (a.k.a. clusters) is an important step to analyze the networks. Though numerous methods have been proposed to this aim, they often lack mathematical rigorousness. Namely, there is no guarantee that all dense modules are detected. Here, we present a novel reverse-search-based method for enumerating all dense modules. Furthermore, constraints from additional data sources such as gene expression profiles or customer profiles can be integrated, so that we can systematically detect dense modules with interesting profiles. We report successful applications in human protein interaction network analyses.
Logotheti, Marianthi; Papadodima, Olga; Venizelos, Nikolaos; Chatziioannou, Aristotelis; Kolisis, Fragiskos
2013-01-01
Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%–5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO datasets. PMID:23554570
Organogenic nodule development in hop (Humulus lupulus L.): Transcript and metabolic responses
Fortes, Ana M; Santos, Filipa; Choi, Young H; Silva, Marta S; Figueiredo, Andreia; Sousa, Lisete; Pessoa, Fernando; Santos, Bartolomeu A; Sebastiana, Mónica; Palme, Klaus; Malhó, Rui; Verpoorte, Rob; Pais, Maria S
2008-01-01
Background Hop (Humulus lupulus L.) is an economically important plant forming organogenic nodules which can be used for genetic transformation and micropropagation. We are interested in the mechanisms underlying reprogramming of cells through stress and hormone treatments. Results An integrated molecular and metabolomic approach was used to investigate global gene expression and metabolic responses during development of hop's organogenic nodules. Transcript profiling using a 3,324-cDNA clone array revealed differential regulation of 133 unigenes, classified into 11 functional categories. Several pathways seem to be determinant in organogenic nodule formation, namely defense and stress response, sugar and lipid metabolism, synthesis of secondary metabolites and hormone signaling. Metabolic profiling using 1H NMR spectroscopy associated to two-dimensional techniques showed the importance of metabolites related to oxidative stress response, lipid and sugar metabolism and secondary metabolism in organogenic nodule formation. Conclusion The expression profile of genes pivotal for energy metabolism, together with metabolites profile, suggested that these morphogenic structures gain energy through a heterotrophic, transport-dependent and sugar-degrading anaerobic metabolism. Polyamines and auxins are likely to be involved in the regulation of expression of many genes related to organogenic nodule formation. These results represent substantial progress toward a better understanding of this complex developmental program and reveal novel information regarding morphogenesis in plants. PMID:18823540
Atmospheric constituent density profiles from full disk solar occultation experiments
NASA Technical Reports Server (NTRS)
Lumpe, J. D.; Chang, C. S.; Strickland, D. J.
1991-01-01
Mathematical methods are described which permit the derivation of the number of density profiles of atmospheric constituents from solar occultation measurements. The algorithm is first applied to measurements corresponding to an arbitrary solar-intensity distribution to calculate the normalized absorption profile. The application of Fourier transform to the integral equation yields a precise expression for the corresponding number density, and the solution is employed with the data given in the form of Laguerre polynomials. The algorithm is employed to calculate the results for the case of uniform distribution of solar intensity, and the results demonstrate the convergence properties of the method. The algorithm can be used to effectively model representative model-density profiles with constant and altitude-dependent scale heights.
Reiman, Mario; Laan, Maris; Rull, Kristiina; Sõber, Siim
2017-08-01
RNA degradation is a ubiquitous process that occurs in living and dead cells, as well as during handling and storage of extracted RNA. Reduced RNA quality caused by degradation is an established source of uncertainty for all RNA-based gene expression quantification techniques. RNA sequencing is an increasingly preferred method for transcriptome analyses, and dependence of its results on input RNA integrity is of significant practical importance. This study aimed to characterize the effects of varying input RNA integrity [estimated as RNA integrity number (RIN)] on transcript level estimates and delineate the characteristic differences between transcripts that differ in degradation rate. The study used ribodepleted total RNA sequencing data from a real-life clinically collected set ( n = 32) of human solid tissue (placenta) samples. RIN-dependent alterations in gene expression profiles were quantified by using DESeq2 software. Our results indicate that small differences in RNA integrity affect gene expression quantification by introducing a moderate and pervasive bias in expression level estimates that significantly affected 8.1% of studied genes. The rapidly degrading transcript pool was enriched in pseudogenes, short noncoding RNAs, and transcripts with extended 3' untranslated regions. Typical slowly degrading transcripts (median length, 2389 nt) represented protein coding genes with 4-10 exons and high guanine-cytosine content.-Reiman, M., Laan, M., Rull, K., Sõber, S. Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples. © FASEB.
Implementing a conceptual model of physical and chemical soil profile evolution
NASA Astrophysics Data System (ADS)
Kirkby, Mike
2017-04-01
When soil profile composition is generalised in terms of the proportion, p, of bedrock remaining (= 1 - depletion ratio), then other soil processes can also be expressed in terms of p, and 'soil depth' described by the integral of (1-p) down to bedrock. Soil profile evolution is expressed as the advance of a sigmoidal weathering front into the critical zone under the action of upward ionic diffusion of weathering products; downward advection of solutes in percolating waters, with loss of (cleanish) water as evapotranspiration and (solute-laden) water as a lateral sub-surface flow increment; and mechanical denudation increment at the surface. Each component responds to the degree of weathering. Percolation is limited by precipitation, evapotranspiration demand and the degree of weathering at each level in the profile which diverts subsurface flow. Mechanical removal rates are considered to broadly increase as weathering proceeds, as grain size and dilation angle decreases. The implication of these assumptions can be examined for steady state profiles, for which observed relationships between mechanical and chemical denudation rates; and between chemical denudation and critical zone depth are reproduced. For non-steady state evolution, these relationships break down, but provide a basis for linking critical zone with hillslope/ landform evolution.
USDA-ARS?s Scientific Manuscript database
Superficial scald is a chilling-related storage disorder of apple caused by the death of peel epidermal and hypodermal cells and associated discoloration. It is controlled using postharvest antioxidant (diphenylamine; DPA) and ethylene action inhibitor (1-methylcyclopropene; 1-MCP), and/or controlle...
Gandhi, Deepa; Tarale, Prashant; Naoghare, Pravin K; Bafana, Amit; Kannan, Krishnamurthi; Sivanesan, Saravanadevi
2016-01-01
Endosulfan, an organochlorine pesticide, is known to induce multiple disorders/abnormalities including neuro-degenerative disorders in many animal species. However, the molecular mechanism of endosulfan induced neuronal alterations is still not well understood. In the present study, the effect of sub-lethal concentration of endosulfan (3 μM) on human neuroblastoma cells (SH-SY5Y) was investigated using genomic and proteomic approaches. Microarray and 2D-PAGE followed by MALDI-TOF-MS analysis revealed differential expression of 831 transcripts and 16 proteins in exposed cells. A gene ontology enrichment analysis revealed that the differentially expressed genes and proteins were involved in variety of cellular events such as neuronal developmental pathway, immune response, cell differentiation, apoptosis, transmission of nerve impulse, axonogenesis, etc. The present study attempted to explore the possible molecular mechanism of endosulfan induced neuronal alterations in SH-SY5Y cells using an integrated genomic and proteomic approach. Based on the gene and protein profile possible mechanisms underlying endosulfan neurotoxicity were predicted. Copyright © 2015 Elsevier B.V. All rights reserved.
Vertical and Lateral Electron Content in the Martian Ionosphere
NASA Astrophysics Data System (ADS)
Paetzold, M. P.; Peter, K.; Bird, M. K.; Häusler, B.; Tellmann, S.
2016-12-01
The radio-science experiment MaRS (Mars Express Radio Science) on the Mars Express spacecraft sounds the neutral atmosphere and ionosphere of Mars since 2004. Approximately 800 vertical profiles of the ionospheric electron density have been acquired until today. The vertical electron content (TEC) is easily computed from the vertical electron density profile by integrating along the altitude. The TEC is typically a fraction of a TEC unit (1E16 m^-2) and depends on the solar zenith angle. The magnitude of the TEC is however fully dominated by the electron density contained in the main layer M2. The contributions by the M1 layer below M2 or the topside is marginal. MaRS is using two radio frequencies for the sounding of the ionosphere. The directly observed differential Doppler from the two received frequencies is a measure of the lateral electron content that means along the ray path and perpendicular to the vertical electron density profile. Combining both the vertical electron density profile, the vertical TEC and the directly observed lateral TEC describes the lateral electron density distribution in the ionosphere.
Unravelling the neurophysiological basis of aggression in a fish model
2010-01-01
Background Aggression is a near-universal behaviour with substantial influence on and implications for human and animal social systems. The neurophysiological basis of aggression is, however, poorly understood in all species and approaches adopted to study this complex behaviour have often been oversimplified. We applied targeted expression profiling on 40 genes, spanning eight neurological pathways and in four distinct regions of the brain, in combination with behavioural observations and pharmacological manipulations, to screen for regulatory pathways of aggression in the zebrafish (Danio rerio), an animal model in which social rank and aggressiveness tightly correlate. Results Substantial differences occurred in gene expression profiles between dominant and subordinate males associated with phenotypic differences in aggressiveness and, for the chosen gene set, they occurred mainly in the hypothalamus and telencephalon. The patterns of differentially-expressed genes implied multifactorial control of aggression in zebrafish, including the hypothalamo-neurohypophysial-system, serotonin, somatostatin, dopamine, hypothalamo-pituitary-interrenal, hypothalamo-pituitary-gonadal and histamine pathways, and the latter is a novel finding outside mammals. Pharmacological manipulations of various nodes within the hypothalamo-neurohypophysial-system and serotonin pathways supported their functional involvement. We also observed differences in expression profiles in the brains of dominant versus subordinate females that suggested sex-conserved control of aggression. For example, in the HNS pathway, the gene encoding arginine vasotocin (AVT), previously believed specific to male behaviours, was amongst those genes most associated with aggression, and AVT inhibited dominant female aggression, as in males. However, sex-specific differences in the expression profiles also occurred, including differences in aggression-associated tryptophan hydroxylases and estrogen receptors. Conclusions Thus, through an integrated approach, combining gene expression profiling, behavioural analyses, and pharmacological manipulations, we identified candidate genes and pathways that appear to play significant roles in regulating aggression in fish. Many of these are novel for non-mammalian systems. We further present a validated system for advancing our understanding of the mechanistic underpinnings of complex behaviours using a fish model. PMID:20846403
NASA Astrophysics Data System (ADS)
Zhang, Ye; Wu, Honglu; Ramesh, Govindarajan; Rohde, Larry; Story, Michael; Mangala, Lingegowda
2012-07-01
EFFECTS OF SIMULATED MICROGRAVITY ON THE EXPRESSION PROFILE OF MICRORNA IN HUMAN LYMPHOBLASTOID CELLS Lingegowda S. Mangala1,2, Ye Zhang1,3, Zhenhua He2, Kamal Emami1, Govindarajan T. Ramesh4, Michael Story 5, Larry H. Rohde2, and Honglu Wu1 1 NASA Johnson Space Center, Houston, Texas, USA 2 University of Houston Clear Lake, Houston, Texas, USA 3 Wyle Integrated Science and Engineering Group, Houston, Texas, USA 4 Norfolk State University, Norfolk, VA, USA 5 University of Texas, Southwestern Medical Center, Dallas, Texas, USA This study explores the changes in expression of microRNA (miRNA) and related genes under simulated microgravity conditions. In comparison to static 1g, microgravity has been shown to alter global gene expression patterns and protein levels in cultured cells or animals. miRNA has recently emerged as an important regulator of gene expression, possibly regulating as many as one-third of all human genes. However, very little is known about the effect of altered gravity on miRNA expression. To test the hypothesis that the miRNA expression profile would be altered in zero gravity resulting in altered regulation of gene expression leading to metabolic or functional changes in cells, we cultured TK6 human lymphoblastoid cells in a High Aspect Ratio Vessel (HARV; bioreactor) for 72 h either in the rotating condition to model microgravity in space or in the static condition as a control. Expression of several miRNA was changed significantly in the simulated microgravity condition including miR-150, miR-34a, miR-423-5p, miR-22 and miR-141, miR-618 and miR-222. To confirm whether this altered miRNA expression correlates with gene expression and functional changes of the cells, we performed DNA microarray and validated the related genes using q-RT PCR. Network and pathway analysis of gene and miRNA expression profiles indicates that the regulation of cell communication and catalytic activities, as well as pathways involved in immune response_IL-15 signaling and NGF mediated NF-kB activation were significantly altered under the simulated microgravity condition.
Prediction of epigenetically regulated genes in breast cancer cell lines.
Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen; Nautiyal, Shivani; Flaucher, Diane; Carlton, Victoria E H; Moorhead, Martin; Lu, Yontao; Gray, Joe W; Faham, Malek; Spellman, Paul; Parvin, Bahram
2010-06-04
Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profiles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profiles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fixed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically significant negative correlation between methylation profiles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identified 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.
Chacon, Diego; Beck, Dominik; Perera, Dilmi; Wong, Jason W H; Pimanda, John E
2014-01-01
The BloodChIP database (http://www.med.unsw.edu.au/CRCWeb.nsf/page/BloodChIP) supports exploration and visualization of combinatorial transcription factor (TF) binding at a particular locus in human CD34-positive and other normal and leukaemic cells or retrieval of target gene sets for user-defined combinations of TFs across one or more cell types. Increasing numbers of genome-wide TF binding profiles are being added to public repositories, and this trend is likely to continue. For the power of these data sets to be fully harnessed by experimental scientists, there is a need for these data to be placed in context and easily accessible for downstream applications. To this end, we have built a user-friendly database that has at its core the genome-wide binding profiles of seven key haematopoietic TFs in human stem/progenitor cells. These binding profiles are compared with binding profiles in normal differentiated and leukaemic cells. We have integrated these TF binding profiles with chromatin marks and expression data in normal and leukaemic cell fractions. All queries can be exported into external sites to construct TF-gene and protein-protein networks and to evaluate the association of genes with cellular processes and tissue expression.
The E2F3—Oncomir 1 axis is activated in Wilms Tumor
Kort, Eric J.; Farber, Leslie; Tretiakova, Maria; Petillo, David; Furge, Kyle A.; Yang, Ximing J.; Cornelius, Albert; Teh, Bin T.
2008-01-01
Oncomir-1 is an oncogenic cluster of microRNAs located on chromosome 13. Previous in vitro studies demonstrated that it is transcriptionally regulated by the transcription factor E2F3. In this report we combine expression profiling of both messenger RNA (mRNA) and micro RNAs (miRNA) in Wilms tumor (WT) samples to provide the first evidence that the E2F3—Oncomir 1 axis, previously identified in cell culture, is deregulated in primary human tumors. Analysis of RNA expression signatures demonstrated that an E2F3 gene signature was activated in all Wilms tumor samples analyzed, in contrast to other kidney tumors. This finding was validated by immunohistochemistry (IHC) on the protein level. Expression of E2F3 was lowest in early stage tumors, and highest in metastatic tissue. Expression profiling of miRNAs in WT showed that expression of each measured member of the Oncomir-1 family was highest in WT relative to other kidney tumor subtypes. Quantitative polymerase chain reaction (PCR) confirmed that these microRNAs were overexpressed in Wilms tumor relative to normal kidney tissue. These results suggest that the E2F3—Oncomir-1 axis is activated in Wilms tumor. Our study also demonstrates the utility of integrated genomics combining gene signature analysis with miRNA expression profiling to identify protein-miRNA interactions that are perturbed in disease states. PMID:18519660
OP17MICRORNA PROFILING USING SMALL RNA-SEQ IN PAEDIATRIC LOW GRADE GLIOMAS
Jeyapalan, Jennie N.; Jones, Tania A.; Tatevossian, Ruth G.; Qaddoumi, Ibrahim; Ellison, David W.; Sheer, Denise
2014-01-01
INTRODUCTION: MicroRNAs regulate gene expression by targeting mRNAs for translational repression or degradation at the post-transcriptional level. In paediatric low-grade gliomas a few key genetic mutations have been identified, including BRAF fusions, FGFR1 duplications and MYB rearrangements. Our aim in the current study is to profile aberrant microRNA expression in paediatric low-grade gliomas and determine the role of epigenetic changes in the aetiology and behaviour of these tumours. METHOD: MicroRNA profiling of tumour samples (6 pilocytic, 2 diffuse, 2 pilomyxoid astrocytomas) and normal brain controls (4 adult normal brain samples and a primary glial progenitor cell-line) was performed using small RNA sequencing. Bioinformatic analysis included sequence alignment, analysis of the number of reads (CPM, counts per million) and differential expression. RESULTS: Sequence alignment identified 695 microRNAs, whose expression was compared in tumours v. normal brain. PCA and hierarchical clustering showed separate groups for tumours and normal brain. Computational analysis identified approximately 400 differentially expressed microRNAs in the tumours compared to matched location controls. Our findings will then be validated and integrated with extensive genetic and epigenetic information we have previously obtained for the full tumour cohort. CONCLUSION: We have identified microRNAs that are differentially expressed in paediatric low-grade gliomas. As microRNAs are known to target genes involved in the initiation and progression of cancer, they provide critical information on tumour pathogenesis and are an important class of biomarkers.
Green, Michael R; Aya-Bonilla, Carlos; Gandhi, Maher K; Lea, Rod A; Wellwood, Jeremy; Wood, Peter; Marlton, Paula; Griffiths, Lyn R
2011-05-01
Recent developments in genomic technologies have resulted in increased understanding of pathogenic mechanisms and emphasized the importance of central survival pathways. Here, we use a novel bioinformatic based integrative genomic profiling approach to elucidate conserved mechanisms of lymphomagenesis in the three commonest non-Hodgkin's lymphoma (NHL) entities: diffuse large B-cell lymphoma, follicular lymphoma, and B-cell chronic lymphocytic leukemia. By integrating genome-wide DNA copy number analysis and transcriptome profiling of tumor cohorts, we identified genetic lesions present in each entity and highlighted their likely target genes. This revealed a significant enrichment of components of both the apoptosis pathway and the mitogen activated protein kinase pathway, including amplification of the MAP3K12 locus in all three entities, within the set of genes targeted by genetic alterations in these diseases. Furthermore, amplification of 12p13.33 was identified in all three entities and found to target the FOXM1 oncogene. Amplification of FOXM1 was subsequently found to be associated with an increased MYC oncogenic signaling signature, and siRNA-mediated knock-down of FOXM1 resulted in decreased MYC expression and induced G2 arrest. Together, these findings underscore genetic alteration of the MAPK and apoptosis pathways, and genetic amplification of FOXM1 as conserved mechanisms of lymphomagenesis in common NHL entities. Integrative genomic profiling identifies common central survival mechanisms and highlights them as attractive targets for directed therapy. 2011 Wiley-Liss, Inc.
Platform for combined analysis of functional and biomolecular phenotypes of the same cell.
Kelbauskas, L; Ashili, S; Zeng, J; Rezaie, A; Lee, K; Derkach, D; Ueberroth, B; Gao, W; Paulson, T; Wang, H; Tian, Y; Smith, D; Reid, B; Meldrum, Deirdre R
2017-03-16
Functional and molecular cell-to-cell variability is pivotal at the cellular, tissue and whole-organism levels. Yet, the ultimate goal of directly correlating the function of the individual cell with its biomolecular profile remains elusive. We present a platform for integrated analysis of functional and transcriptional phenotypes in the same single cells. We investigated changes in the cellular respiration and gene expression diversity resulting from adaptation to repeated episodes of acute hypoxia in a premalignant progression model. We find differential, progression stage-specific alterations in phenotypic heterogeneity and identify cells with aberrant phenotypes. To our knowledge, this study is the first demonstration of an integrated approach to elucidate how heterogeneity at the transcriptional level manifests in the physiologic profile of individual cells in the context of disease progression.
Farshidfar, Farshad; Zheng, Siyuan; Gingras, Marie-Claude; Newton, Yulia; Shih, Juliann; Robertson, A Gordon; Hinoue, Toshinori; Hoadley, Katherine A; Gibb, Ewan A; Roszik, Jason; Covington, Kyle R; Wu, Chia-Chin; Shinbrot, Eve; Stransky, Nicolas; Hegde, Apurva; Yang, Ju Dong; Reznik, Ed; Sadeghi, Sara; Pedamallu, Chandra Sekhar; Ojesina, Akinyemi I; Hess, Julian M; Auman, J Todd; Rhie, Suhn K; Bowlby, Reanne; Borad, Mitesh J; Zhu, Andrew X; Stuart, Josh M; Sander, Chris; Akbani, Rehan; Cherniack, Andrew D; Deshpande, Vikram; Mounajjed, Taofic; Foo, Wai Chin; Torbenson, Michael S; Kleiner, David E; Laird, Peter W; Wheeler, David A; McRee, Autumn J; Bathe, Oliver F; Andersen, Jesper B; Bardeesy, Nabeel; Roberts, Lewis R; Kwong, Lawrence N
2017-03-14
Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahepatic CCA cases and propose a molecular classification scheme. We identified an IDH mutant-enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Applications of lentiviral vectors in molecular imaging.
Chatterjee, Sushmita; De, Abhijit
2014-06-01
Molecular imaging provides the ability of simultaneous visual and quantitative estimation of long term gene expression directly from living organisms. To reveal the kinetics of gene expression by imaging method, often sustained expression of the transgene is required. Lentiviral vectors have been extensively used over last fifteen years for delivery of a transgene in a wide variety of cell types. Lentiviral vectors have the well known advantages such as sustained transgene delivery through stable integration into the host genome, the capability of infecting non-dividing and dividing cells, broad tissue tropism, a reasonably large carrying capacity for delivering therapeutic and reporter gene combinations. Additionally, they do not express viral proteins during transduction, have a potentially safe integration site profile, and a relatively easy system for vector manipulation and infective viral particle production. As a result, lentiviral vector mediated therapeutic and imaging reporter gene delivery to various target organs holds promise for the future treatment. In this review, we have conducted a brief survey of important lentiviral vector developments in diverse biomedical fields including reproductive biology.
Kogelman, Lisette J A; Zhernakova, Daria V; Westra, Harm-Jan; Cirera, Susanna; Fredholm, Merete; Franke, Lude; Kadarmideen, Haja N
2015-10-20
Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach. Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data. Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate < 0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we detected several obesity candidate genes, for example, ENPP1, CTSL, and ABHD12B. To our knowledge, this is the first study to perform an integrated genomics and transcriptomics (eQTL) study using, and modeling, genomic and subcutaneous adipose tissue RNA sequencing data on obesity in a porcine model. We detected several pathways and potential causal genes for obesity. Further validation and investigation may reveal their exact function and association with obesity.
Cenik, Can; Cenik, Elif Sarinay; Byeon, Gun W.; Grubert, Fabian; Candille, Sophie I.; Spacek, Damek; Alsallakh, Bilal; Tilgner, Hagen; Araya, Carlos L.; Tang, Hua; Ricci, Emiliano; Snyder, Michael P.
2015-01-01
Elucidating the consequences of genetic differences between humans is essential for understanding phenotypic diversity and personalized medicine. Although variation in RNA levels, transcription factor binding, and chromatin have been explored, little is known about global variation in translation and its genetic determinants. We used ribosome profiling, RNA sequencing, and mass spectrometry to perform an integrated analysis in lymphoblastoid cell lines from a diverse group of individuals. We find significant differences in RNA, translation, and protein levels suggesting diverse mechanisms of personalized gene expression control. Combined analysis of RNA expression and ribosome occupancy improves the identification of individual protein level differences. Finally, we identify genetic differences that specifically modulate ribosome occupancy—many of these differences lie close to start codons and upstream ORFs. Our results reveal a new level of gene expression variation among humans and indicate that genetic variants can cause changes in protein levels through effects on translation. PMID:26297486
Torres-Oliva, Montserrat; Schneider, Julia; Wiegleb, Gordon
2018-01-01
Drosophila melanogaster head development represents a valuable process to study the developmental control of various organs, such as the antennae, the dorsal ocelli and the compound eyes from a common precursor, the eye-antennal imaginal disc. While the gene regulatory network underlying compound eye development has been extensively studied, the key transcription factors regulating the formation of other head structures from the same imaginal disc are largely unknown. We obtained the developmental transcriptome of the eye-antennal discs covering late patterning processes at the late 2nd larval instar stage to the onset and progression of differentiation at the end of larval development. We revealed the expression profiles of all genes expressed during eye-antennal disc development and we determined temporally co-expressed genes by hierarchical clustering. Since co-expressed genes may be regulated by common transcriptional regulators, we combined our transcriptome dataset with publicly available ChIP-seq data to identify central transcription factors that co-regulate genes during head development. Besides the identification of already known and well-described transcription factors, we show that the transcription factor Hunchback (Hb) regulates a significant number of genes that are expressed during late differentiation stages. We confirm that hb is expressed in two polyploid subperineurial glia cells (carpet cells) and a thorough functional analysis shows that loss of Hb function results in a loss of carpet cells in the eye-antennal disc. Additionally, we provide for the first time functional data indicating that carpet cells are an integral part of the blood-brain barrier. Eventually, we combined our expression data with a de novo Hb motif search to reveal stage specific putative target genes of which we find a significant number indeed expressed in carpet cells. PMID:29360820
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sung, Hye Youn; Choi, Eun Nam; Ahn Jo, Sangmee
2011-11-04
Highlights: Black-Right-Pointing-Pointer Genome-wide DNA methylation pattern in Alzheimer's disease model cell line. Black-Right-Pointing-Pointer Integrated analysis of CpG methylation and mRNA expression profiles. Black-Right-Pointing-Pointer Identify three Swedish mutant target genes; CTIF, NXT2 and DDR2 gene. Black-Right-Pointing-Pointer The effect of Swedish mutation on alteration of DNA methylation and gene expression. -- Abstract: The Swedish mutation of amyloid precursor protein (APP-sw) has been reported to dramatically increase beta amyloid production through aberrant cleavage at the beta secretase site, causing early-onset Alzheimer's disease (AD). DNA methylation has been reported to be associated with AD pathogenesis, but the underlying molecular mechanism of APP-sw-mediated epigenetic alterationsmore » in AD pathogenesis remains largely unknown. We analyzed genome-wide interplay between promoter CpG DNA methylation and gene expression in an APP-sw-expressing AD model cell line. To identify genes whose expression was regulated by DNA methylation status, we performed integrated analysis of CpG methylation and mRNA expression profiles, and identified three target genes of the APP-sw mutant; hypomethylated CTIF (CBP80/CBP20-dependent translation initiation factor) and NXT2 (nuclear exporting factor 2), and hypermethylated DDR2 (discoidin domain receptor 2). Treatment with the demethylating agent 5-aza-2 Prime -deoxycytidine restored mRNA expression of these three genes, implying methylation-dependent transcriptional regulation. The profound alteration in the methylation status was detected at the -435, -295, and -271 CpG sites of CTIF, and at the -505 to -341 region in the promoter of DDR2. In the promoter region of NXT2, only one CpG site located at -432 was differentially unmethylated in APP-sw cells. Thus, we demonstrated the effect of the APP-sw mutation on alteration of DNA methylation and subsequent gene expression. This epigenetic regulatory mechanism may contribute to the pathogenesis of AD.« less
Wang, Guofu; Bi, Lechang; Wang, Gaofeng; Huang, Feilai; Lu, Mingjing; Zhu, Kai
2018-06-01
Objectives Expression profile of GSE57691 was analyzed to identify the similarities and differences between aortic occlusive disease and abdominal aortic aneurysm. Methods The expression profile of GSE57691 was downloaded from Gene Expression Omnibus database, including 20 small abdominal aortic aneurysm samples, 29 large abdominal aortic aneurysm samples, 9 aortic occlusive disease samples, and 10 control samples. Using the limma package in R, the differentially expressed genes were screened. Followed by enrichment analysis was performed for the differentially expressed genes using database for annotation, visualization, and integrated discovery online tool. Based on string online tool and Cytoscape software, protein-protein interaction network and module analyses were carried out. Moreover, integrated TF platform database and Cytoscape software were used for constructing transcriptional regulatory networks. Results As a result, 1757, 354, and 396 differentially expressed genes separately were identified in aortic occlusive disease, large abdominal aortic aneurysm, and small abdominal aortic aneurysm samples. UBB was significantly enriched in proteolysis related pathways with a high degree in three groups. SPARCL1 was another gene shared by these groups and regulated by NFIA, which had a high degree in transcriptional regulatory network. ACTB, a significant upregulated gene in abdominal aortic aneurysm samples, could be regulated by CLIC4, which was significantly enriched in cell motions. ACLY and NFIB were separately identified in aortic occlusive disease and small abdominal aortic aneurysm samples, and separately enriched in lipid metabolism and negative regulation of cell proliferation. Conclusions The downregulated UBB, NFIA, and SPARCL1 might play key roles in both aortic occlusive disease and abdominal aortic aneurysm, while the upregulated ACTB might only involve in abdominal aortic aneurysm. ACLY and NFIB were specifically involved in aortic occlusive disease and small abdominal aortic aneurysm separately.
Defining the gene expression signature of rhabdomyosarcoma by meta-analysis
Romualdi, Chiara; De Pittà, Cristiano; Tombolan, Lucia; Bortoluzzi, Stefania; Sartori, Francesca; Rosolen, Angelo; Lanfranchi, Gerolamo
2006-01-01
Background Rhabdomyosarcoma is a highly malignant soft tissue sarcoma in childhood and arises as a consequence of regulatory disruption of the growth and differentiation pathways of myogenic precursor cells. The pathogenic pathways involved in this tumor are mostly unknown and therefore a better characterization of RMS gene expression profile would represent a considerable advance. The availability of publicly available gene expression datasets have opened up new challenges especially for the integration of data generated by different research groups and different array platforms with the purpose of obtaining new insights on the biological process investigated. Results In this work we performed a meta-analysis on four microarray and two SAGE datasets of gene expression data on RMS in order to evaluate the degree of agreement of the biological results obtained by these different studies and to identify common regulatory pathways that could be responsible of tumor growth. Regulatory pathways and biological processes significantly enriched has been investigated and a list of differentially meta-profiles have been identified as possible candidate of aggressiveness of RMS. Conclusion Our results point to a general down regulation of the energy production pathways, suggesting a hypoxic physiology for RMS cells. This result agrees with the high malignancy of RMS and with its resistance to most of the therapeutic treatments. In this context, different isoforms of the ANT gene have been consistently identified for the first time as differentially expressed in RMS. This gene is involved in anti-apoptotic processes when cells grow in low oxygen conditions. These new insights in the biological processes responsible of RMS growth and development demonstrate the effective advantage of the use of integrated analysis of gene expression studies. PMID:17090319
Mozduri, Z; Bakhtiarizadeh, M R; Salehi, A
2018-06-01
Negative energy balance (NEB) is an altered metabolic state in modern high-yielding dairy cows. This metabolic state occurs in the early postpartum period when energy demands for milk production and maintenance exceed that of energy intake. Negative energy balance or poor adaptation to this metabolic state has important effects on the liver and can lead to metabolic disorders and reduced fertility. The roles of regulatory factors, including transcription factors (TFs) and micro RNAs (miRNAs) have often been separately studied for evaluating of NEB. However, adaptive response to NEB is controlled by complex gene networks and still not fully understood. In this study, we aimed to discover the integrated gene regulatory networks involved in NEB development in liver tissue. We downloaded data sets including mRNA and miRNA expression profiles related to three and four cows with severe and moderate NEB, respectively. Our method integrated two independent types of information: module inference network by TFs, miRNAs and mRNA expression profiles (RNA-seq data) and computational target predictions. In total, 176 modules were predicted by using gene expression data and 64 miRNAs and 63 TFs were assigned to these modules. By using our integrated computational approach, we identified 13 TF-module and 19 miRNA-module interactions. Most of these modules were associated with liver metabolic processes as well as immune and stress responses, which might play crucial roles in NEB development. Literature survey results also showed that several regulators and gene targets have already been characterized as important factors in liver metabolic processes. These results provided novel insights into regulatory mechanisms at the TF and miRNA levels during NEB. In addition, the method described in this study seems to be applicable to construct integrated regulatory networks for different diseases or disorders.
Guo, Michael; Liu, Zun; Willen, Jessie; Shaw, Cameron P; Richard, Daniel; Jagoda, Evelyn; Doxey, Andrew C; Hirschhorn, Joel; Capellini, Terence D
2017-12-05
GWAS have identified hundreds of height-associated loci. However, determining causal mechanisms is challenging, especially since height-relevant tissues (e.g. growth plates) are difficult to study. To uncover mechanisms by which height GWAS variants function, we performed epigenetic profiling of murine femoral growth plates. The profiled open chromatin regions recapitulate known chondrocyte and skeletal biology, are enriched at height GWAS loci, particularly near differentially expressed growth plate genes, and enriched for binding motifs of transcription factors with roles in chondrocyte biology. At specific loci, our analyses identified compelling mechanisms for GWAS variants. For example, at CHSY1 , we identified a candidate causal variant (rs9920291) overlapping an open chromatin region. Reporter assays demonstrated that rs9920291 shows allelic regulatory activity, and CRISPR/Cas9 targeting of human chondrocytes demonstrates that the region regulates CHSY1 expression. Thus, integrating biologically relevant epigenetic information (here, from growth plates) with genetic association results can identify biological mechanisms important for human growth.
Zhang, Wenli; Solanki, Manish; Müther, Nadine; Ebel, Melanie; Wang, Jichang; Sun, Chuanbo; Izsvak, Zsuzsanna; Ehrhardt, Anja
2013-01-01
Recombinant adeno-associated viral (AAV) vectors have been shown to be one of the most promising vectors for therapeutic gene delivery because they can induce efficient and long-term transduction in non-dividing cells with negligible side-effects. However, as AAV vectors mostly remain episomal, vector genomes and transgene expression are lost in dividing cells. Therefore, to stably transduce cells, we developed a novel AAV/transposase hybrid-vector. To facilitate SB-mediated transposition from the rAAV genome, we established a system in which one AAV vector contains the transposon with the gene of interest and the second vector delivers the hyperactive Sleeping Beauty (SB) transposase SB100X. Human cells were infected with the AAV-transposon vector and the transposase was provided in trans either by transient and stable plasmid transfection or by AAV vector transduction. We found that groups which received the hyperactive transposase SB100X showed significantly increased colony forming numbers indicating enhanced integration efficiencies. Furthermore, we found that transgene copy numbers in transduced cells were dose-dependent and that predominantly SB transposase-mediated transposition contributed to stabilization of the transgene. Based on a plasmid rescue strategy and a linear-amplification mediated PCR (LAM-PCR) protocol we analysed the SB100X-mediated integration profile after transposition from the AAV vector. A total of 1840 integration events were identified which revealed a close to random integration profile. In summary, we show for the first time that AAV vectors can serve as template for SB transposase mediated somatic integration. We developed the first prototype of this hybrid-vector system which with further improvements may be explored for treatment of diseases which originate from rapidly dividing cells. PMID:24116154
Casara, Silvia; Sales, Gabriele; Lanfranchi, Gerolamo; Celotti, Lucia; Mognato, Maddalena
2012-01-01
Background Ionizing radiation (IR) can be extremely harmful for human cells since an improper DNA-damage response (DDR) to IR can contribute to carcinogenesis initiation. Perturbations in DDR pathway can originate from alteration in the functionality of the microRNA-mediated gene regulation, being microRNAs (miRNAs) small noncoding RNA that act as post-transcriptional regulators of gene expression. In this study we gained insight into the role of miRNAs in the regulation of DDR to IR under microgravity, a condition of weightlessness experienced by astronauts during space missions, which could have a synergistic action on cells, increasing the risk of radiation exposure. Methodology/Principal Findings We analyzed miRNA expression profile of human peripheral blood lymphocytes (PBL) incubated for 4 and 24 h in normal gravity (1 g) and in modeled microgravity (MMG) during the repair time after irradiation with 0.2 and 2Gy of γ-rays. Our results show that MMG alters miRNA expression signature of irradiated PBL by decreasing the number of radio-responsive miRNAs. Moreover, let-7i*, miR-7, miR-7-1*, miR-27a, miR-144, miR-200a, miR-598, miR-650 are deregulated by the combined action of radiation and MMG. Integrated analyses of miRNA and mRNA expression profiles, carried out on PBL of the same donors, identified significant miRNA-mRNA anti-correlations of DDR pathway. Gene Ontology analysis reports that the biological category of “Response to DNA damage” is enriched when PBL are incubated in 1 g but not in MMG. Moreover, some anti-correlated genes of p53-pathway show a different expression level between 1 g and MMG. Functional validation assays using luciferase reporter constructs confirmed miRNA-mRNA interactions derived from target prediction analyses. Conclusions/Significance On the whole, by integrating the transcriptome and microRNome, we provide evidence that modeled microgravity can affects the DNA-damage response to IR in human PBL. PMID:22347458
Gottschalk, Laura B.; Vecchio-Pagan, Briana; Sharma, Neeraj; Han, Sangwoo T.; Franca, Arianna; Wohler, Elizabeth S.; Batista, Denise A.S.; Goff, Loyal A.; Cutting, Garry R.
2016-01-01
Background Analysis of the functional consequences and treatment response of rare CFTR variants is challenging due to the limited availability of primary airways cells. Methods A Flp recombination target (FRT) site for stable expression of CFTR was incorporated into an immortalized CF bronchial epithelial cell line (CFBE41o−). CFTR cDNA was integrated into the FRT site. Expression was evaluated by western blotting and confocal microscopy and function measured by short circuit current. RNA sequencing was used to compare the transcriptional profile of the resulting CF8Flp cell line to primary cells and tissues. Results Functional CFTR was expressed from integrated cDNA at the FRT site of the CF8Flp cell line at levels comparable to that seen in native airway cells. CF8Flp cells expressing WT-CFTR have a stable transcriptome comparable to that of primary cultured airway epithelial cells, including genes that play key roles in CFTR pathways. Conclusion CF8Flp cells provide a viable substitute for primary CF airway cells for the analysis of CFTR variants in a native context. PMID:26694805
Integration Site and Clonal Expansion in Human Chronic Retroviral Infection and Gene Therapy
Niederer, Heather A.; Bangham, Charles R. M.
2014-01-01
Retroviral vectors have been successfully used therapeutically to restore expression of genes in a range of single-gene diseases, including several primary immunodeficiency disorders. Although clinical trials have shown remarkable results, there have also been a number of severe adverse events involving malignant outgrowth of a transformed clonal population. This clonal expansion is influenced by the integration site profile of the viral integrase, the transgene expressed, and the effect of the viral promoters on the neighbouring host genome. Infection with the pathogenic human retrovirus HTLV-1 also causes clonal expansion of cells containing an integrated HTLV-1 provirus. Although the majority of HTLV-1-infected people remain asymptomatic, up to 5% develop an aggressive T cell malignancy. In this review we discuss recent findings on the role of the genomic integration site in determining the clonality and the potential for malignant transformation of cells carrying integrated HTLV-1 or gene therapy vectors, and how these results have contributed to the understanding of HTLV-1 pathogenesis and to improvements in gene therapy vector safety. PMID:25365582
USDA-ARS?s Scientific Manuscript database
The plant hormones regulate many physiological processes including apple fruit ripening by integrating diverse developmental cues and environmental signals. In addition to the well-characterized role of ethylene, jasmonic acid (JA) and its derivatives have also been suggested to play an important ro...
Cross-Platform Toxicogenomics for the Prediction of Non-Genotoxic Hepatocarcinogenesis in Rat
Metzger, Ute; Templin, Markus F.; Plummer, Simon; Ellinger-Ziegelbauer, Heidrun; Zell, Andreas
2014-01-01
In the area of omics profiling in toxicology, i.e. toxicogenomics, characteristic molecular profiles have previously been incorporated into prediction models for early assessment of a carcinogenic potential and mechanism-based classification of compounds. Traditionally, the biomarker signatures used for model construction were derived from individual high-throughput techniques, such as microarrays designed for monitoring global mRNA expression. In this study, we built predictive models by integrating omics data across complementary microarray platforms and introduced new concepts for modeling of pathway alterations and molecular interactions between multiple biological layers. We trained and evaluated diverse machine learning-based models, differing in the incorporated features and learning algorithms on a cross-omics dataset encompassing mRNA, miRNA, and protein expression profiles obtained from rat liver samples treated with a heterogeneous set of substances. Most of these compounds could be unambiguously classified as genotoxic carcinogens, non-genotoxic carcinogens, or non-hepatocarcinogens based on evidence from published studies. Since mixed characteristics were reported for the compounds Cyproterone acetate, Thioacetamide, and Wy-14643, we reclassified these compounds as either genotoxic or non-genotoxic carcinogens based on their molecular profiles. Evaluating our toxicogenomics models in a repeated external cross-validation procedure, we demonstrated that the prediction accuracy of our models could be increased by joining the biomarker signatures across multiple biological layers and by adding complex features derived from cross-platform integration of the omics data. Furthermore, we found that adding these features resulted in a better separation of the compound classes and a more confident reclassification of the three undefined compounds as non-genotoxic carcinogens. PMID:24830643
Integrative Analysis Reveals Relationships of Genetic and Epigenetic Alterations in Osteosarcoma
Skårn, Magne; Namløs, Heidi M.; Barragan-Polania, Ana H.; Cleton-Jansen, Anne-Marie; Serra, Massimo; Liestøl, Knut; Hogendoorn, Pancras C. W.; Hovig, Eivind; Myklebost, Ola; Meza-Zepeda, Leonardo A.
2012-01-01
Background Osteosarcomas are the most common non-haematological primary malignant tumours of bone, and all conventional osteosarcomas are high-grade tumours showing complex genomic aberrations. We have integrated genome-wide genetic and epigenetic profiles from the EuroBoNeT panel of 19 human osteosarcoma cell lines based on microarray technologies. Principal Findings The cell lines showed complex patterns of DNA copy number changes, where genomic copy number gains were significantly associated with gene-rich regions and losses with gene-poor regions. By integrating the datasets, 350 genes were identified as having two types of aberrations (gain/over-expression, hypo-methylation/over-expression, loss/under-expression or hyper-methylation/under-expression) using a recurrence threshold of 6/19 (>30%) cell lines. The genes showed in general alterations in either DNA copy number or DNA methylation, both within individual samples and across the sample panel. These 350 genes are involved in embryonic skeletal system development and morphogenesis, as well as remodelling of extracellular matrix. The aberrations of three selected genes, CXCL5, DLX5 and RUNX2, were validated in five cell lines and five tumour samples using PCR techniques. Several genes were hyper-methylated and under-expressed compared to normal osteoblasts, and expression could be reactivated by demethylation using 5-Aza-2′-deoxycytidine treatment for four genes tested; AKAP12, CXCL5, EFEMP1 and IL11RA. Globally, there was as expected a significant positive association between gain and over-expression, loss and under-expression as well as hyper-methylation and under-expression, but gain was also associated with hyper-methylation and under-expression, suggesting that hyper-methylation may oppose the effects of increased copy number for detrimental genes. Conclusions Integrative analysis of genome-wide genetic and epigenetic alterations identified dependencies and relationships between DNA copy number, DNA methylation and mRNA expression in osteosarcomas, contributing to better understanding of osteosarcoma biology. PMID:23144859
Integrated MicroRNA and mRNA Signatures Associated with Survival in Triple Negative Breast Cancer
Lovat, Francesca; Carasi, Stefania; Pulvirenti, Alfredo; Ferro, Alfredo; Alder, Hansjuerg; He, Gang; Vecchione, Andrea; Croce, Carlo M.; Shapiro, Charles L.; Huebner, Kay
2013-01-01
Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways. Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis. PMID:23405235
Integrated microRNA and mRNA signatures associated with survival in triple negative breast cancer.
Cascione, Luciano; Gasparini, Pierluigi; Lovat, Francesca; Carasi, Stefania; Pulvirenti, Alfredo; Ferro, Alfredo; Alder, Hansjuerg; He, Gang; Vecchione, Andrea; Croce, Carlo M; Shapiro, Charles L; Huebner, Kay
2013-01-01
Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways.Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis.
Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B; Almon, Richard R; DuBois, Debra C; Jusko, William J; Hoffman, Eric P
2004-01-01
Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp).
Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B.; Almon, Richard R.; DuBois, Debra C.; Jusko, William J.; Hoffman, Eric P.
2004-01-01
Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp). PMID:14681485
Gene-metabolite profile integration to understand the cause of spaceflight induced immunodeficiency.
Chakraborty, Nabarun; Cheema, Amrita; Gautam, Aarti; Donohue, Duncan; Hoke, Allison; Conley, Carolynn; Jett, Marti; Hammamieh, Rasha
2018-01-01
Spaceflight presents a spectrum of stresses very different from those associated with terrestrial conditions. Our previous study (BMC Genom. 15 : 659, 2014) integrated the expressions of mRNAs, microRNAs, and proteins and results indicated that microgravity induces an immunosuppressive state that can facilitate opportunistic pathogenic attack. However, the existing data are not sufficient for elucidating the molecular drivers of the given immunosuppressed state. To meet this knowledge gap, we focused on the metabolite profile of spaceflown human cells. Independent studies have attributed cellular energy deficiency as a major cause of compromised immunity of the host, and metabolites that are closely associated with energy production could be a robust signature of atypical energy fluctuation. Our protocol involved inoculation of human endothelial cells in cell culture modules in spaceflight and on the ground concurrently. Ten days later, the cells in space and on the ground were exposed to lipopolysaccharide (LPS), a ubiquitous membrane endotoxin of Gram-negative bacteria. Nucleic acids, proteins, and metabolites were collected 4 and 8 h post-LPS exposure. Untargeted profiling of metabolites was followed by targeted identification of amino acids and knowledge integration with gene expression profiles. Consistent with the past reports associating microgravity with increased energy expenditure, we identified several markers linked to energy deficiency, including various amino acids such as tryptophan, creatinine, dopamine, and glycine, and cofactors such as lactate and pyruvate. The present study revealed a molecular architecture linking energy metabolism and immunodeficiency in microgravity. The energy-deficient condition potentially cascaded into dysregulation of protein metabolism and impairment of host immunity. This project is limited by a small sample size. Although a strict statistical screening was carefully implemented, the present results further emphasize the need for additional studies with larger sample sizes. Validating this hypothesis using an in vivo model is essential to extend the knowledge towards identifying markers of diagnostic and therapeutic value.
Tatro, Erick T; Scott, Erick R; Nguyen, Timothy B; Salaria, Shahid; Banerjee, Sugato; Moore, David J; Masliah, Eliezer; Achim, Cristian L; Everall, Ian P
2010-04-26
HIV infection disturbs the central nervous system (CNS) through inflammation and glial activation. Evidence suggests roles for microRNA (miRNA) in host defense and neuronal homeostasis, though little is known about miRNAs' role in HIV CNS infection. MiRNAs are non-coding RNAs that regulate gene translation through post-transcriptional mechanisms. Messenger-RNA profiling alone is insufficient to elucidate the dynamic dance of molecular expression of the genome. We sought to clarify RNA alterations in the frontal cortex (FC) of HIV-infected individuals and those concurrently infected and diagnosed with major depressive disorder (MDD). This report is the first published study of large-scale miRNA profiling from human HIV-infected FC. The goals of this study were to: 1. Identify changes in miRNA expression that occurred in the frontal cortex (FC) of HIV individuals, 2. Determine whether miRNA expression profiles of the FC could differentiate HIV from HIV/MDD, and 3. Adapt a method to meaningfully integrate gene expression data and miRNA expression data in clinical samples. We isolated RNA from the FC (n = 3) of three separate groups (uninfected controls, HIV, and HIV/MDD) and then pooled the RNA within each group for use in large-scale miRNA profiling. RNA from HIV and HIV/MDD patients (n = 4 per group) were also used for non-pooled mRNA analysis on Affymetrix U133 Plus 2.0 arrays. We then utilized a method for integrating the two datasets in a Target Bias Analysis. We found miRNAs of three types: A) Those with many dysregulated mRNA targets of less stringent statistical significance, B) Fewer dysregulated target-genes of highly stringent statistical significance, and C) unclear bias. In HIV/MDD, more miRNAs were downregulated than in HIV alone. Specific miRNA families at targeted chromosomal loci were dysregulated. The dysregulated miRNAs clustered on Chromosomes 14, 17, 19, and X. A small subset of dysregulated genes had many 3' untranslated region (3'UTR) target-sites for dysregulated miRNAs. We provide evidence that certain miRNAs serve as key elements in gene regulatory networks in HIV-infected FC and may be implicated in neurobehavioral disorder. Finally, our data indicates that some genes may serve as hubs of miRNA activity.
Bexfield, C.E.; McBride, J.H.; Pugin, Andre J.M.; Ravat, D.; Biswas, S.; Nelson, W.J.; Larson, T.H.; Sargent, S.L.; Fillerup, M.A.; Tingey, B.E.; Wald, L.; Northcott, M.L.; South, J.V.; Okure, M.S.; Chandler, M.R.
2006-01-01
Shallow high-resolution seismic reflection surveys have traditionally been restricted to either compressional (P) or horizontally polarized shear (SH) waves in order to produce 2-D images of subsurface structure. The northernmost Mississippi embayment and coincident New Madrid seismic zone (NMSZ) provide an ideal laboratory to study the experimental use of integrating P- and SH-wave seismic profiles, integrated, where practicable, with micro-gravity data. In this area, the relation between "deeper" deformation of Paleozoic bedrock associated with the formation of the Reelfoot rift and NMSZ seismicity and "shallower" deformation of overlying sediments has remained elusive, but could be revealed using integrated P- and SH-wave reflection. Surface expressions of deformation are almost non-existent in this region, which makes seismic reflection surveying the only means of detecting structures that are possibly pertinent to seismic hazard assessment. Since P- and SH-waves respond differently to the rock and fluid properties and travel at dissimilar speeds, the resulting seismic profiles provide complementary views of the subsurface based on different levels of resolution and imaging capability. P-wave profiles acquired in southwestern Illinois and western Kentucky (USA) detect faulting of deep, Paleozoic bedrock and Cretaceous reflectors while coincident SH-wave surveys show that this deformation propagates higher into overlying Tertiary and Quaternary strata. Forward modeling of micro-gravity data acquired along one of the seismic profiles further supports an interpretation of faulting of bedrock and Cretaceous strata. The integration of the two seismic and the micro-gravity methods therefore increases the scope for investigating the relation between the older and younger deformation in an area of critical seismic hazard. ?? 2006 Elsevier B.V. All rights reserved.
Risk stratification in myelodysplastic syndromes: is there a role for gene expression profiling?
Zeidan, Amer M; Prebet, Thomas; Saad Aldin, Ehab; Gore, Steven David
2014-04-01
Evaluation of: Pellagatti A, Benner A, Mills KI et al. Identification of gene expression-based prognostic markers in the hematopoietic stem cells of patients with myelodysplastic syndromes. J. Clin. Oncol. 31(28), 3557-3564 (2013). Patients with myelodysplastic syndromes (MDS) exhibit wide heterogeneity in clinical outcomes making accurate risk-stratification an integral part of the risk-adaptive management paradigm. Current prognostic schemes for MDS rely on clinicopathological parameters. Despite the increasing knowledge of the genetic landscape of MDS and the prognostic impact of many newly discovered molecular aberrations, none to date has been incorporated formally into the major risk models. Efforts are ongoing to use data generated from genome-wide high-throughput techniques to improve the 'individualized' outcome prediction for patients. We here discuss an important paper in which gene expression profiling (GEP) technology was applied to marrow CD34(+) cells from 125 MDS patients to generate and validate a standardized GEP-based prognostic signature.
Characterizing mutation-expression network relationships in multiple cancers.
Ghazanfar, Shila; Yang, Jean Yee Hwa
2016-08-01
Data made available through large cancer consortia like The Cancer Genome Atlas make for a rich source of information to be studied across and between cancers. In recent years, network approaches have been applied to such data in uncovering the complex interrelationships between mutational and expression profiles, but lack direct testing for expression changes via mutation. In this pan-cancer study we analyze mutation and gene expression information in an integrative manner by considering the networks generated by testing for differences in expression in direct association with specific mutations. We relate our findings among the 19 cancers examined to identify commonalities and differences as well as their characteristics. Using somatic mutation and gene expression information across 19 cancers, we generated mutation-expression networks per cancer. On evaluation we found that our generated networks were significantly enriched for known cancer-related genes, such as skin cutaneous melanoma (p<0.01 using Network of Cancer Genes 4.0). Our framework identified that while different cancers contained commonly mutated genes, there was little concordance between associated gene expression changes among cancers. Comparison between cancers showed a greater overlap of network nodes for cancers with higher overall non-silent mutation load, compared to those with a lower overall non-silent mutation load. This study offers a framework that explores network information through co-analysis of somatic mutations and gene expression profiles. Our pan-cancer application of this approach suggests that while mutations are frequently common among cancer types, the impact they have on the surrounding networks via gene expression changes varies. Despite this finding, there are some cancers for which mutation-associated network behaviour appears to be similar: suggesting a potential framework for uncovering related cancers for which similar therapeutic strategies may be applicable. Our framework for understanding relationships among cancers has been integrated into an interactive R Shiny application, PAn Cancer Mutation Expression Networks (PACMEN), containing dynamic and static network visualization of the mutation-expression networks. PACMEN also features tools for further examination of network topology characteristics among cancers. Copyright © 2016 Elsevier Ltd. All rights reserved.
Integrative Analysis of Cancer Diagnosis Studies with Composite Penalization
Liu, Jin; Huang, Jian; Ma, Shuangge
2013-01-01
Summary In cancer diagnosis studies, high-throughput gene profiling has been extensively conducted, searching for genes whose expressions may serve as markers. Data generated from such studies have the “large d, small n” feature, with the number of genes profiled much larger than the sample size. Penalization has been extensively adopted for simultaneous estimation and marker selection. Because of small sample sizes, markers identified from the analysis of single datasets can be unsatisfactory. A cost-effective remedy is to conduct integrative analysis of multiple heterogeneous datasets. In this article, we investigate composite penalization methods for estimation and marker selection in integrative analysis. The proposed methods use the minimax concave penalty (MCP) as the outer penalty. Under the homogeneity model, the ridge penalty is adopted as the inner penalty. Under the heterogeneity model, the Lasso penalty and MCP are adopted as the inner penalty. Effective computational algorithms based on coordinate descent are developed. Numerical studies, including simulation and analysis of practical cancer datasets, show satisfactory performance of the proposed methods. PMID:24578589
GDA, a web-based tool for Genomics and Drugs integrated analysis.
Caroli, Jimmy; Sorrentino, Giovanni; Forcato, Mattia; Del Sal, Giannino; Bicciato, Silvio
2018-05-25
Several major screenings of genetic profiling and drug testing in cancer cell lines proved that the integration of genomic portraits and compound activities is effective in discovering new genetic markers of drug sensitivity and clinically relevant anticancer compounds. Despite most genetic and drug response data are publicly available, the availability of user-friendly tools for their integrative analysis remains limited, thus hampering an effective exploitation of this information. Here, we present GDA, a web-based tool for Genomics and Drugs integrated Analysis that combines drug response data for >50 800 compounds with mutations and gene expression profiles across 73 cancer cell lines. Genomic and pharmacological data are integrated through a modular architecture that allows users to identify compounds active towards cancer cell lines bearing a specific genomic background and, conversely, the mutational or transcriptional status of cells responding or not-responding to a specific compound. Results are presented through intuitive graphical representations and supplemented with information obtained from public repositories. As both personalized targeted therapies and drug-repurposing are gaining increasing attention, GDA represents a resource to formulate hypotheses on the interplay between genomic traits and drug response in cancer. GDA is freely available at http://gda.unimore.it/.
Wang, Yang; Chen, Zhi-Hao; Yin, Chun; Ma, Jian-Hua; Li, Di-Jie; Zhao, Fan; Sun, Yu-Long; Hu, Li-Fang; Shang, Peng; Qian, Ai-Rong
2015-01-01
The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has recently been applied in life science research. In this study a specially designed superconducting magnet with a large gradient high magnetic field (LG-HMF), which can provide three apparent gravity levels (μ-g, 1-g, and 2-g), was used to simulate a space-like gravity environment. Osteocyte, as the most important mechanosensor in bone, takes a pivotal position in mediating the mechano-induced bone remodeling. In this study, the effects of LG-HMF on gene expression profiling of osteocyte-like cell line MLO-Y4 were investigated by Affymetrix DNA microarray. LG-HMF affected osteocyte gene expression profiling. Differentially expressed genes (DEGs) and data mining were further analyzed by using bioinfomatic tools, such as DAVID, iReport. 12 energy metabolism related genes (PFKL, AK4, ALDOC, COX7A1, STC1, ADM, CA9, CA12, P4HA1, APLN, GPR35 and GPR84) were further confirmed by real-time PCR. An integrated gene interaction network of 12 DEGs was constructed. Bio-data mining showed that genes involved in glucose metabolic process and apoptosis changed notablly. Our results demostrated that LG-HMF affected the expression of energy metabolism related genes in osteocyte. The identification of sensitive genes to special environments may provide some potential targets for preventing and treating bone loss or osteoporosis. PMID:25635858
Wang, Yang; Chen, Zhi-Hao; Yin, Chun; Ma, Jian-Hua; Li, Di-Jie; Zhao, Fan; Sun, Yu-Long; Hu, Li-Fang; Shang, Peng; Qian, Ai-Rong
2015-01-01
The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has recently been applied in life science research. In this study a specially designed superconducting magnet with a large gradient high magnetic field (LG-HMF), which can provide three apparent gravity levels (μ-g, 1-g, and 2-g), was used to simulate a space-like gravity environment. Osteocyte, as the most important mechanosensor in bone, takes a pivotal position in mediating the mechano-induced bone remodeling. In this study, the effects of LG-HMF on gene expression profiling of osteocyte-like cell line MLO-Y4 were investigated by Affymetrix DNA microarray. LG-HMF affected osteocyte gene expression profiling. Differentially expressed genes (DEGs) and data mining were further analyzed by using bioinfomatic tools, such as DAVID, iReport. 12 energy metabolism related genes (PFKL, AK4, ALDOC, COX7A1, STC1, ADM, CA9, CA12, P4HA1, APLN, GPR35 and GPR84) were further confirmed by real-time PCR. An integrated gene interaction network of 12 DEGs was constructed. Bio-data mining showed that genes involved in glucose metabolic process and apoptosis changed notablly. Our results demostrated that LG-HMF affected the expression of energy metabolism related genes in osteocyte. The identification of sensitive genes to special environments may provide some potential targets for preventing and treating bone loss or osteoporosis.
Raherison, Elie S M; Giguère, Isabelle; Caron, Sébastien; Lamara, Mebarek; MacKay, John J
2015-07-01
Transcript profiling has shown the molecular bases of several biological processes in plants but few studies have developed an understanding of overall transcriptome variation. We investigated transcriptome structure in white spruce (Picea glauca), aiming to delineate its modular organization and associated functional and evolutionary attributes. Microarray analyses were used to: identify and functionally characterize groups of co-expressed genes; investigate expressional and functional diversity of vascular tissue preferential genes which were conserved among Picea species, and identify expression networks underlying wood formation. We classified 22 857 genes as variable (79%; 22 coexpression groups) or invariant (21%) by profiling across several vegetative tissues. Modular organization and complex transcriptome restructuring among vascular tissue preferential genes was revealed by their assignment to coexpression groups with partially overlapping profiles and partially distinct functions. Integrated analyses of tissue-based and temporally variable profiles identified secondary xylem gene networks, showed their remodelling over a growing season and identified PgNAC-7 (no apical meristerm (NAM), Arabidopsis transcription activation factor (ATAF) and cup-shaped cotyledon (CUC) transcription factor 007 in Picea glauca) as a major hub gene specific to earlywood formation. Reference profiling identified comprehensive, statistically robust coexpressed groups, revealing that modular organization underpins the evolutionary conservation of the transcriptome structure. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.
Li, Zheng; Srivastava, Shireesh; Yang, Xuerui; Mittal, Sheenu; Norton, Paul; Resau, James; Haab, Brian; Chan, Christina
2007-01-01
Background Free fatty acids (FFA) and tumor necrosis factor alpha (TNF-α) have been implicated in the pathogenesis of many obesity-related metabolic disorders. When human hepatoblastoma cells (HepG2) were exposed to different types of FFA and TNF-α, saturated fatty acid was found to be cytotoxic and its toxicity was exacerbated by TNF-α. In order to identify the processes associated with the toxicity of saturated FFA and TNF-α, the metabolic and gene expression profiles were measured to characterize the cellular states. A computational model was developed to integrate these disparate data to reveal the underlying pathways and mechanisms involved in saturated fatty acid toxicity. Results A hierarchical framework consisting of three stages was developed to identify the processes and genes that regulate the toxicity. First, discriminant analysis identified that fatty acid oxidation and intracellular triglyceride accumulation were the most relevant in differentiating the cytotoxic phenotype. Second, gene set enrichment analysis (GSEA) was applied to the cDNA microarray data to identify the transcriptionally altered pathways and processes. Finally, the genes and gene sets that regulate the metabolic responses identified in step 1 were identified by integrating the expression of the enriched gene sets and the metabolic profiles with a multi-block partial least squares (MBPLS) regression model. Conclusion The hierarchical approach suggested potential mechanisms involved in mediating the cytotoxic and cytoprotective pathways, as well as identified novel targets, such as NADH dehydrogenases, aldehyde dehydrogenases 1A1 (ALDH1A1) and endothelial membrane protein 3 (EMP3) as modulator of the toxic phenotypes. These predictions, as well as, some specific targets that were suggested by the analysis were experimentally validated. PMID:17498300
Profiles of metabolites and gene expression in rats with chemically induced hepatic necrosis.
Heijne, Wilbert H M; Lamers, Robert-Jan A N; van Bladeren, Peter J; Groten, John P; van Nesselrooij, Joop H J; van Ommen, Ben
2005-01-01
This study investigated whether integrated analysis of transcriptomics and metabolomics data increased the sensitivity of detection and provided new insight in the mechanisms of hepatotoxicity. Metabolite levels in plasma or urine were analyzed in relation to changes in hepatic gene expression in rats that received bromobenzene to induce acute hepatic centrilobular necrosis. Bromobenzene-induced lesions were only observed after treatment with the highest of 3 dose levels. Multivariate statistical analysis showed that metabolite profiles of blood plasma were largely different from controls when the rats were treated with bromobenzene, also at doses that did not elicit histopathological changes. Changes in levels of genes and metabolites were related to the degree of necrosis, providing putative novel markers of hepatotoxicity. Levels of endogenous metabolites like alanine, lactate, tyrosine and dimethylglycine differed in plasma from treated and control rats. The metabolite profiles of urine were found to be reflective of the exposure levels. This integrated analysis of hepatic transcriptomics and plasma metabolomics was able to more sensitively detect changes related to hepatotoxicity and discover novel markers. The relation between gene expression and metabolite levels was explored and additional insight in the role of various biological pathways in bromobenzene-induced hepatic necrosis was obtained, including the involvement of apoptosis and changes in glycolysis and amino acid metabolism. The complete Table 2 is available as a supplemental file online at http://taylorandfrancis.metapress.com/openurlasp?genre=journal&issn=0192-6233. To access the file, click on the issue link for 33(4), then select this article. A download option appears at the bottom of this abstract. In order to access the full article online, you must either have an individual subscription or a member subscription accessed through www.toxpath.org.
Platform for combined analysis of functional and biomolecular phenotypes of the same cell
Kelbauskas, L.; Ashili, S.; Zeng, J.; Rezaie, A.; Lee, K.; Derkach, D.; Ueberroth, B.; Gao, W.; Paulson, T.; Wang, H.; Tian, Y.; Smith, D.; Reid, B.; Meldrum, Deirdre R.
2017-01-01
Functional and molecular cell-to-cell variability is pivotal at the cellular, tissue and whole-organism levels. Yet, the ultimate goal of directly correlating the function of the individual cell with its biomolecular profile remains elusive. We present a platform for integrated analysis of functional and transcriptional phenotypes in the same single cells. We investigated changes in the cellular respiration and gene expression diversity resulting from adaptation to repeated episodes of acute hypoxia in a premalignant progression model. We find differential, progression stage-specific alterations in phenotypic heterogeneity and identify cells with aberrant phenotypes. To our knowledge, this study is the first demonstration of an integrated approach to elucidate how heterogeneity at the transcriptional level manifests in the physiologic profile of individual cells in the context of disease progression. PMID:28300162
Xue, Linlin; Xie, Li; Song, Xingguo; Song, Xianrang
2018-04-17
Platelets have emerged as key players in tumorigenesis and tumor progression. Tumor-educated platelet (TEP) RNA profile has the potential to diagnose non-small-cell lung cancer (NSCLC). The objective of this study was to identify potential TEP RNA biomarkers for the diagnosis of NSCLC and to explore the mechanisms in alternations of TEP RNA profile. The RNA-seq datasets GSE68086 and GSE89843 were downloaded from Gene Expression Omnibus DataSets (GEO DataSets). Then, the functional enrichment of the differentially expressed mRNAs was analyzed by the Database for Annotation Visualization and Integrated Discovery (DAVID). The miRNAs which regulated the differential mRNAs and the target mRNAs of miRNAs were identified by miRanda and miRDB. Then, the miRNA-mRNA regulatory network was visualized via Cytoscape software. Twenty consistently altered mRNAs (2 up-regulated and 18 down-regulated) were identified from the two GSE datasets, and they were significantly enriched in several biological processes, including transport and establishment of localization. Twenty identical miRNAs were found between exosomal miRNA-seq dataset and 229 miRNAs that regulated 20 consistently differential mRNAs in platelets. We also analyzed 13 spliceosomal mRNAs and their miRNA predictions; there were 27 common miRNAs between 206 differential exosomal miRNAs and 338 miRNAs that regulated 13 distinct spliceosomal mRNAs. This study identified 20 potential TEP RNA biomarkers in NSCLC for diagnosis by integrated bioinformatical analysis, and alternations in TEP RNA profile may be related to the post-transcriptional regulation and the splicing metabolisms of spliceosome. © 2018 Wiley Periodicals, Inc.
Host-Microbe Interactions in the Neonatal Intestine: Role of Human Milk Oligosaccharides123
Donovan, Sharon M.; Wang, Mei; Li, Min; Friedberg, Iddo; Schwartz, Scott L.; Chapkin, Robert S.
2012-01-01
The infant intestinal microbiota is shaped by genetics and environment, including the route of delivery and early dietary intake. Data from germ-free rodents and piglets support a critical role for the microbiota in regulating gastrointestinal and immune development. Human milk oligosaccharides (HMO) both directly and indirectly influence intestinal development by regulating cell proliferation, acting as prebiotics for beneficial bacteria and modulating immune development. We have shown that the gut microbiota, the microbial metatranscriptome, and metabolome differ between porcine milk–fed and formula-fed (FF) piglets. Our goal is to define how early nutrition, specifically HMO, shapes host-microbe interactions in breast-fed (BF) and FF human infants. We an established noninvasive method that uses stool samples containing intact sloughed epithelial cells to quantify intestinal gene expression profiles in human infants. We hypothesized that a systems biology approach, combining i) HMO composition of the mother’s milk with the infant’s gut gene expression and fecal bacterial composition, ii) gene expression, and iii short-chain fatty acid profiles would identify important mechanistic pathways affecting intestinal development of BF and FF infants in the first few months of life. HMO composition was analyzed by HLPC Chip/time-of-flight MS and 3 HMO clusters were identified using principle component analysis. Initial findings indicated that both host epithelial cell mRNA expression and the microbial phylogenetic profiles provided strong feature sets that distinctly classified the BF and FF infants. Ongoing analyses are designed to integrate the host transcriptome, bacterial phylogenetic profiles, and functional metagenomic data using multivariate statistical analyses. PMID:22585924
Integrative functional genomics of salt acclimatization in the model legume Lotus japonicus.
Sanchez, Diego H; Lippold, Felix; Redestig, Henning; Hannah, Matthew A; Erban, Alexander; Krämer, Ute; Kopka, Joachim; Udvardi, Michael K
2008-03-01
The model legume Lotus japonicus was subjected to non-lethal long-term salinity and profiled at the ionomic, transcriptomic and metabolomic levels. Two experimental designs with various stress doses were tested: a gradual step acclimatization and an initial acclimatization approach. Ionomic profiling by inductively coupled plasma/atomic emission spectrometry (ICP-AES) revealed salt stress-induced reductions in potassium, phosphorus, sulphur, zinc and molybdenum. Microarray profiling using the Lotus Genechip allowed the identification of 912 probesets that were differentially expressed under the acclimatization regimes. Gas chromatography/mass spectrometry-based metabolite profiling identified 147 differentially accumulated soluble metabolites, indicating a change in metabolic phenotype upon salt acclimatization. Metabolic changes were characterized by a general increase in the steady-state levels of many amino acids, sugars and polyols, with a concurrent decrease in most organic acids. Transcript and metabolite changes exhibited a stress dose-dependent response within the range of NaCl concentrations used, although threshold and plateau behaviours were also observed. The combined observations suggest a successive and increasingly global requirement for the reprogramming of gene expression and metabolic pathways to maintain ionic and osmotic homeostasis. A simple qualitative model is proposed to explain the systems behaviour of plants during salt acclimatization.
oPOSSUM: identification of over-represented transcription factor binding sites in co-expressed genes
Ho Sui, Shannan J.; Mortimer, James R.; Arenillas, David J.; Brumm, Jochen; Walsh, Christopher J.; Kennedy, Brian P.; Wasserman, Wyeth W.
2005-01-01
Targeted transcript profiling studies can identify sets of co-expressed genes; however, identification of the underlying functional mechanism(s) is a significant challenge. Established methods for the analysis of gene annotations, particularly those based on the Gene Ontology, can identify functional linkages between genes. Similar methods for the identification of over-represented transcription factor binding sites (TFBSs) have been successful in yeast, but extension to human genomics has largely proved ineffective. Creation of a system for the efficient identification of common regulatory mechanisms in a subset of co-expressed human genes promises to break a roadblock in functional genomics research. We have developed an integrated system that searches for evidence of co-regulation by one or more transcription factors (TFs). oPOSSUM combines a pre-computed database of conserved TFBSs in human and mouse promoters with statistical methods for identification of sites over-represented in a set of co-expressed genes. The algorithm successfully identified mediating TFs in control sets of tissue-specific genes and in sets of co-expressed genes from three transcript profiling studies. Simulation studies indicate that oPOSSUM produces few false positives using empirically defined thresholds and can tolerate up to 50% noise in a set of co-expressed genes. PMID:15933209
Toward a Model-Based Approach for Flight System Fault Protection
NASA Technical Reports Server (NTRS)
Day, John; Meakin, Peter; Murray, Alex
2012-01-01
Use SysML/UML to describe the physical structure of the system This part of the model would be shared with other teams - FS Systems Engineering, Planning & Execution, V&V, Operations, etc., in an integrated model-based engineering environment Use the UML Profile mechanism, defining Stereotypes to precisely express the concepts of the FP domain This extends the UML/SysML languages to contain our FP concepts Use UML/SysML, along with our profile, to capture FP concepts and relationships in the model Generate typical FP engineering products (the FMECA, Fault Tree, MRD, V&V Matrices)
Molecular profiles to biology and pathways: a systems biology approach.
Van Laere, Steven; Dirix, Luc; Vermeulen, Peter
2016-06-16
Interpreting molecular profiles in a biological context requires specialized analysis strategies. Initially, lists of relevant genes were screened to identify enriched concepts associated with pathways or specific molecular processes. However, the shortcoming of interpreting gene lists by using predefined sets of genes has resulted in the development of novel methods that heavily rely on network-based concepts. These algorithms have the advantage that they allow a more holistic view of the signaling properties of the condition under study as well as that they are suitable for integrating different data types like gene expression, gene mutation, and even histological parameters.
Bornhauser, Beat; Gombert, Michael; Kratsch, Christina; Stütz, Adrian M.; Sultan, Marc; Tchinda, Joelle; Worth, Catherine L.; Amstislavskiy, Vyacheslav; Badarinarayan, Nandini; Baruchel, André; Bartram, Thies; Basso, Giuseppe; Canpolat, Cengiz; Cario, Gunnar; Cavé, Hélène; Dakaj, Dardane; Delorenzi, Mauro; Dobay, Maria Pamela; Eckert, Cornelia; Ellinghaus, Eva; Eugster, Sabrina; Frismantas, Viktoras; Ginzel, Sebastian; Haas, Oskar A.; Heidenreich, Olaf; Hemmrich-Stanisak, Georg; Hezaveh, Kebria; Höll, Jessica I.; Hornhardt, Sabine; Husemann, Peter; Kachroo, Priyadarshini; Kratz, Christian P.; te Kronnie, Geertruy; Marovca, Blerim; Niggli, Felix; McHardy, Alice C.; Moorman, Anthony V.; Panzer-Grümayer, Renate; Petersen, Britt S.; Raeder, Benjamin; Ralser, Meryem; Rosenstiel, Philip; Schäfer, Daniel; Schrappe, Martin; Schreiber, Stefan; Schütte, Moritz; Stade, Björn; Thiele, Ralf; von der Weid, Nicolas; Vora, Ajay; Zaliova, Marketa; Zhang, Langhui; Zichner, Thomas; Zimmermann, Martin; Lehrach, Hans; Borkhardt, Arndt; Bourquin, Jean-Pierre; Franke, Andre; Korbel, Jan O.; Stanulla, Martin; Yaspo, Marie-Laure
2015-01-01
TCF3-HLF-fusion positive acute lymphoblastic leukemia (ALL) is currently incurable. Employing an integrated approach, we uncovered distinct mutation, gene expression, and drug response profiles in TCF3-HLF-positive and treatment-responsive TCF3-PBX1-positive ALL. Recurrent intragenic deletions of PAX5 or VPREB1 were identified in constellation with TCF3-HLF. Moreover somatic mutations in the non-translocated allele of TCF3 and a reduction of PAX5 gene dosage in TCF3-HLF ALL suggest cooperation within a restricted genetic context. The enrichment for stem cell and myeloid features in the TCF3-HLF signature may reflect reprogramming by TCF3-HLF of a lymphoid-committed cell of origin towards a hybrid, drug-resistant hematopoietic state. Drug response profiling of matched patient-derived xenografts revealed a distinct profile for TCF3-HLF ALL with resistance to conventional chemotherapeutics, but sensitivity towards glucocorticoids, anthracyclines and agents in clinical development. Striking on-target sensitivity was achieved with the BCL2-specific inhibitor venetoclax (ABT-199). This integrated approach thus provides alternative treatment options for this deadly disease. PMID:26214592
The impact of exposure by water to a model androgen, 17β-trenbolone (TRB), was assessed in fathead minnows using an integrated molecular approach. This included classical measures of endocrine exposure such as impacts on testosterone (T), 17β-estradiol (E2), and vitellogenin (VTG...
USDA-ARS?s Scientific Manuscript database
Age at puberty (AP) in gilts is a moderately heritable trait (h2 = 0.37) and the earliest indicator of sow reproductive longevity. Therefore, quantifying the pleiotropic sources that influence both AP and reproductive longevity is important in understanding the differences in sow fertility. In this ...
Buravkova, Ludmila B; Rudimov, Eugene G; Andreeva, Elena R; Grigoriev, Anatoly I
2018-03-01
Microgravity is a principal risk factor hampering human cardiovascular regulation during space flights. Endothelial dysfunction associated with the impaired integrity and uniformity of the monolayer represents a potential trigger for vascular damage. We characterized the expression profile of the multi-step cascade of adhesion molecules (ICAM-1, VCAM-1, E-selectin, VE-cadherin) in umbilical cord endothelial cells (ECs) after 24 h of exposure to simulated microgravity (SMG), pro-inflammatory cytokine TNF-α, and the combination of the two. Random Positioning Machine (RPM)-mediated SMG was used to mimic microgravity effects. SMG stimulated the expression of E-selectin, which is known to be involved in slowing leukocyte rolling. Primary ECs displayed heterogeneity with respect to the proportion of ICAM-1-positive cells. ECs were divided into two groups: pre-activated ECs displaying high proportion of ICAM-1 + -cells (ECs-1) (greater than 50%) and non-activated ECs with low proportion of ICAM-1 + -cells (ECs-2) (less than 25%). Only non-activated ECs-2 responded to SMG by elevating gene transcription and increasing ICAM-1 and VE-cadherin expression. This effect was enhanced after cumulative SMG-TNF-α exposure. ECs-1 displayed an unexpected decrease in number of E-selectin- and ICAM-1-positive ECs and pronounced up-regulation of VCAM1 upon activation of inflammation, which was partially abolished by SMG. Thus, non-activated ECs-2 are quite resistant to the impacts of microgravity and even exhibited an elevation of the VE-cadherin gene and protein expression, thus improving the integrity of the endothelial monolayer. Pre-activation of ECs with inflammatory stimuli may disturb the EC adhesion profile, attenuating its barrier function. These alterations may be among the mechanisms underlying cardiovascular dysregulation in real microgravity conditions. © 2017 Wiley Periodicals, Inc.
Shchetynsky, Klementy; Diaz-Gallo, Lina-Marcella; Folkersen, Lasse; Hensvold, Aase Haj; Catrina, Anca Irinel; Berg, Louise; Klareskog, Lars; Padyukov, Leonid
2017-02-02
Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of "connector" genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA.
Computer program for calculation of real gas turbulent boundary layers with variable edge entropy
NASA Technical Reports Server (NTRS)
Boney, L. R.
1974-01-01
A user's manual for a computer program which calculates real gas turbulent boundary layers with variable edge entropy on a blunt cone or flat plate at zero angle of attack is presented. An integral method is used. The method includes the effect of real gas in thermodynamic equilibrium and variable edge entropy. A modified Crocco enthalpy velocity relationship is used for the enthalpy profiles and an empirical correlation of the N-power law profile is used for the velocity profile. The skin-friction-coefficient expressions of Spalding and Chi and Van Driest are used in the solution of the momentum equation and in the heat-transfer predictions that use several modified forms of Reynolds analogy.
Song, Minyan; He, Yanghua; Zhou, Huangkai; Zhang, Yi; Li, Xizhi; Yu, Ying
2016-07-14
Subclinical mastitis is a widely spread disease of lactating cows. Its major pathogen is Staphylococcus aureus (S. aureus). In this study, we performed genome-wide integrative analysis of DNA methylation and transcriptional expression to identify candidate genes and pathways relevant to bovine S. aureus subclinical mastitis. The genome-scale DNA methylation profiles of peripheral blood lymphocytes in cows with S. aureus subclinical mastitis (SA group) and healthy controls (CK) were generated by methylated DNA immunoprecipitation combined with microarrays. We identified 1078 differentially methylated genes in SA cows compared with the controls. By integrating DNA methylation and transcriptome data, 58 differentially methylated genes were shared with differently expressed genes, in which 20.7% distinctly hypermethylated genes showed down-regulated expression in SA versus CK, whereas 14.3% dramatically hypomethylated genes showed up-regulated expression. Integrated pathway analysis suggested that these genes were related to inflammation, ErbB signalling pathway and mismatch repair. Further functional analysis revealed that three genes, NRG1, MST1 and NAT9, were strongly correlated with the progression of S. aureus subclinical mastitis and could be used as powerful biomarkers for the improvement of bovine mastitis resistance. Our studies lay the groundwork for epigenetic modification and mechanistic studies on susceptibility of bovine mastitis.
Song, Minyan; He, Yanghua; Zhou, Huangkai; Zhang, Yi; Li, Xizhi; Yu, Ying
2016-01-01
Subclinical mastitis is a widely spread disease of lactating cows. Its major pathogen is Staphylococcus aureus (S. aureus). In this study, we performed genome-wide integrative analysis of DNA methylation and transcriptional expression to identify candidate genes and pathways relevant to bovine S. aureus subclinical mastitis. The genome-scale DNA methylation profiles of peripheral blood lymphocytes in cows with S. aureus subclinical mastitis (SA group) and healthy controls (CK) were generated by methylated DNA immunoprecipitation combined with microarrays. We identified 1078 differentially methylated genes in SA cows compared with the controls. By integrating DNA methylation and transcriptome data, 58 differentially methylated genes were shared with differently expressed genes, in which 20.7% distinctly hypermethylated genes showed down-regulated expression in SA versus CK, whereas 14.3% dramatically hypomethylated genes showed up-regulated expression. Integrated pathway analysis suggested that these genes were related to inflammation, ErbB signalling pathway and mismatch repair. Further functional analysis revealed that three genes, NRG1, MST1 and NAT9, were strongly correlated with the progression of S. aureus subclinical mastitis and could be used as powerful biomarkers for the improvement of bovine mastitis resistance. Our studies lay the groundwork for epigenetic modification and mechanistic studies on susceptibility of bovine mastitis. PMID:27411928
van der Lugt, Benthe; Rusli, Fenni; Lute, Carolien; Lamprakis, Andreas; Salazar, Ethel; Boekschoten, Mark V; Hooiveld, Guido J; Müller, Michael; Vervoort, Jacques; Kersten, Sander; Belzer, Clara; Kok, Dieuwertje E G; Steegenga, Wilma T
2018-05-16
The aging process is associated with diminished colonic health. In this study, we applied an integrative approach to reveal potential interactions between determinants of colonic health in aging C57BL/6J mice. Analysis of gut microbiota composition revealed an enrichment of various potential pathobionts, including Desulfovibrio spp . , and a decline of the health-promoting Akkermansia spp . and Lactobacillus spp. during aging. Intraluminal concentrations of various metabolites varied between ages and we found evidence for an increased gut permeability at higher age. Colonic gene expression analysis suggested that during the early phase of aging (between 6 and 12 months), expression of genes involved in epithelial-to-mesenchymal transition and (re)organization of the extracellular matrix were increased. Differential expression of these genes was strongly correlated with Bifidobacterium spp. During the later phase of aging (between 12 and 28 months), gene expression profiles pointed towards a diminished antimicrobial defense and were correlated with an uncultured Gastranaerophilales spp. This study demonstrates that aging is associated with pronounced changes in gut microbiota composition and colonic gene expression. Furthermore, the strong correlations between specific bacterial genera and host gene expression may imply that orchestrated interactions take place in the vicinity of the colonic wall and potentially mediate colonic health during aging.
Yang, Lingjian; Ainali, Chrysanthi; Tsoka, Sophia; Papageorgiou, Lazaros G
2014-12-05
Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outcome. Traditional approaches where expression of genes were treated independently suffer from low prediction accuracy and difficulty of biological interpretation. Current research efforts focus on integrating information on protein interactions through biochemical pathway datasets with expression profiles to propose pathway-based classifiers that can enhance disease diagnosis and prognosis. As most of the pathway activity inference methods in literature are either unsupervised or applied on two-class datasets, there is good scope to address such limitations by proposing novel methodologies. A supervised multiclass pathway activity inference method using optimisation techniques is reported. For each pathway expression dataset, patterns of its constituent genes are summarised into one composite feature, termed pathway activity, and a novel mathematical programming model is proposed to infer this feature as a weighted linear summation of expression of its constituent genes. Gene weights are determined by the optimisation model, in a way that the resulting pathway activity has the optimal discriminative power with regards to disease phenotypes. Classification is then performed on the resulting low-dimensional pathway activity profile. The model was evaluated through a variety of published gene expression profiles that cover different types of disease. We show that not only does it improve classification accuracy, but it can also perform well in multiclass disease datasets, a limitation of other approaches from the literature. Desirable features of the model include the ability to control the maximum number of genes that may participate in determining pathway activity, which may be pre-specified by the user. Overall, this work highlights the potential of building pathway-based multi-phenotype classifiers for accurate disease diagnosis and prognosis problems.
Uehara, Yuriko; Oda, Katsutoshi; Ikeda, Yuji; Koso, Takahiro; Tsuji, Shingo; Yamamoto, Shogo; Asada, Kayo; Sone, Kenbun; Kurikawa, Reiko; Makii, Chinami; Hagiwara, Otoe; Tanikawa, Michihiro; Maeda, Daichi; Hasegawa, Kosei; Nakagawa, Shunsuke; Wada-Hiraike, Osamu; Kawana, Kei; Fukayama, Masashi; Fujiwara, Keiichi; Yano, Tetsu; Osuga, Yutaka; Fujii, Tomoyuki; Aburatani, Hiroyuki
2015-01-01
Ovarian clear cell carcinoma (CCC) is generally associated with chemoresistance and poor clinical outcome, even with early diagnosis; whereas high-grade serous carcinomas (SCs) and endometrioid carcinomas (ECs) are commonly chemosensitive at advanced stages. Although an integrated genomic analysis of SC has been performed, conclusive views on copy number and expression profiles for CCC are still limited. In this study, we performed single nucleotide polymorphism analysis with 57 epithelial ovarian cancers (31 CCCs, 14 SCs, and 12 ECs) and microarray expression analysis with 55 cancers (25 CCCs, 16 SCs, and 14 ECs). We then evaluated PIK3CA mutations and ARID1A expression in CCCs. SNP array analysis classified 13% of CCCs into a cluster with high frequency and focal range of copy number alterations (CNAs), significantly lower than for SCs (93%, P < 0.01) and ECs (50%, P = 0.017). The ratio of whole-arm to all CNAs was higher in CCCs (46.9%) than SCs (21.7%; P < 0.0001). SCs with loss of heterozygosity (LOH) of BRCA1 (85%) also had LOH of NF1 and TP53, and LOH of BRCA2 (62%) coexisted with LOH of RB1 and TP53. Microarray analysis classified CCCs into three clusters. One cluster (CCC-2, n = 10) showed more favorable prognosis than the CCC-1 and CCC-3 clusters (P = 0.041). Coexistent alterations of PIK3CA and ARID1A were more common in CCC-1 and CCC-3 (7/11, 64%) than in CCC-2 (0/10, 0%; P < 0.01). Being in cluster CCC-2 was an independent favorable prognostic factor in CCC. In conclusion, CCC was characterized by a high ratio of whole-arm CNAs; whereas CNAs in SC were mainly focal, but preferentially caused LOH of well-known tumor suppressor genes. As such, expression profiles might be useful for sub-classification of CCC, and might provide useful information on prognosis. PMID:26043110
Chadwick, Jessica A; Bhattacharya, Sayak; Lowe, Jeovanna; Weisleder, Noah; Rafael-Fortney, Jill A
2017-02-01
Angiotensin-converting enzyme inhibitors (ACEi) and mineralocorticoid receptor (MR) antagonists are FDA-approved drugs that inhibit the renin-angiotensin-aldosterone system (RAAS) and are used to treat heart failure. Combined treatment with the ACEi lisinopril and the nonspecific MR antagonist spironolactone surprisingly improves skeletal muscle, in addition to heart function and pathology in a Duchenne muscular dystrophy (DMD) mouse model. We recently demonstrated that MR is present in all limb and respiratory muscles and functions as a steroid hormone receptor in differentiated normal human skeletal muscle fibers. The goals of the current study were to begin to define cellular and molecular mechanisms mediating the skeletal muscle efficacy of RAAS inhibitor treatment. We also compared molecular changes resulting from RAAS inhibition with those resulting from the current DMD standard-of-care glucocorticoid treatment. Direct assessment of muscle membrane integrity demonstrated improvement in dystrophic mice treated with lisinopril and spironolactone compared with untreated mice. Short-term treatments of dystrophic mice with specific and nonspecific MR antagonists combined with lisinopril led to overlapping gene-expression profiles with beneficial regulation of metabolic processes and decreased inflammatory gene expression. Glucocorticoids increased apoptotic, proteolytic, and chemokine gene expression that was not changed by RAAS inhibitors in dystrophic mice. Microarray data identified potential genes that may underlie RAAS inhibitor treatment efficacy and the side effects of glucocorticoids. Direct effects of RAAS inhibitors on membrane integrity also contribute to improved pathology of dystrophic muscles. Together, these data will inform clinical development of MR antagonists for treating skeletal muscles in DMD. Copyright © 2017 the American Physiological Society.
Intragraft Molecular Pathways Associated with Tolerance Induction in Renal Transplantation.
Gallon, Lorenzo; Mathew, James M; Bontha, Sai Vineela; Dumur, Catherine I; Dalal, Pranav; Nadimpalli, Lakshmi; Maluf, Daniel G; Shetty, Aneesha A; Ildstad, Suzanne T; Leventhal, Joseph R; Mas, Valeria R
2018-02-01
The modern immunosuppression regimen has greatly improved short-term allograft outcomes but not long-term allograft survival. Complications associated with immunosuppression, specifically nephrotoxicity and infection risk, significantly affect graft and patient survival. Inducing and understanding pathways underlying clinical tolerance after transplantation are, therefore, necessary. We previously showed full donor chimerism and immunosuppression withdrawal in highly mismatched allograft recipients using a bioengineered stem cell product (FCRx). Here, we evaluated the gene expression and microRNA expression profiles in renal biopsy samples from tolerance-induced FCRx recipients, paired donor organs before implant, and subjects under standard immunosuppression (SIS) without rejection and with acute rejection. Unlike allograft samples showing acute rejection, samples from FCRx recipients did not show upregulation of T cell- and B cell-mediated rejection pathways. Gene expression pathways differed slightly between FCRx samples and the paired preimplantation donor organ samples, but most of the functional gene networks overlapped. Notably, compared with SIS samples, FCRx samples showed upregulation of genes involved in pathways, like B cell receptor signaling. Additionally, prediction analysis showed inhibition of proinflammatory regulators and activation of anti-inflammatory pathways in FCRx samples. Furthermore, integrative analyses (microRNA and gene expression profiling from the same biopsy sample) identified the induction of regulators with demonstrated roles in the downregulation of inflammatory pathways and maintenance of tissue homeostasis in tolerance-induced FCRx samples compared with SIS samples. This pilot study highlights the utility of molecular intragraft evaluation of pathways related to FCRx-induced tolerance and the use of integrative analyses for identifying upstream regulators of the affected downstream molecular pathways. Copyright © 2018 by the American Society of Nephrology.
Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan
2018-04-01
Association rule mining is an important technique for identifying interesting relationships between gene pairs in a biological data set. Earlier methods basically work for a single biological data set, and, in maximum cases, a single minimum support cutoff can be applied globally, i.e., across all genesets/itemsets. To overcome this limitation, in this paper, we propose dynamic threshold-based FP-growth rule mining algorithm that integrates gene expression, methylation and protein-protein interaction profiles based on weighted shortest distance to find the novel associations among different pairs of genes in multi-view data sets. For this purpose, we introduce three new thresholds, namely, Distance-based Variable/Dynamic Supports (DVS), Distance-based Variable Confidences (DVC), and Distance-based Variable Lifts (DVL) for each rule by integrating co-expression, co-methylation, and protein-protein interactions existed in the multi-omics data set. We develop the proposed algorithm utilizing these three novel multiple threshold measures. In the proposed algorithm, the values of , , and are computed for each rule separately, and subsequently it is verified whether the support, confidence, and lift of each evolved rule are greater than or equal to the corresponding individual , , and values, respectively, or not. If all these three conditions for a rule are found to be true, the rule is treated as a resultant rule. One of the major advantages of the proposed method compared with other related state-of-the-art methods is that it considers both the quantitative and interactive significance among all pairwise genes belonging to each rule. Moreover, the proposed method generates fewer rules, takes less running time, and provides greater biological significance for the resultant top-ranking rules compared to previous methods.
The interaction and integration of auxin signaling components.
Hayashi, Ken-ichiro
2012-06-01
IAA, a naturally occurring auxin, is a simple signaling molecule that regulates many diverse steps of plant development. Auxin essentially coordinates plant development through transcriptional regulation. Auxin binds to TIR1/AFB nuclear receptors, which are F-box subunits of the SCF ubiquitin ligase complex. The auxin signal is then modulated by the quantitative and qualitative responses of the Aux/IAA repressors and the auxin response factor (ARF) transcription factors. The specificity of the auxin-regulated gene expression profile is defined by several factors, such as the expression of these regulatory proteins, their post-transcriptional regulation, their stability and the affinity between these regulatory proteins. Auxin-binding protein 1 (ABP1) is a candidate protein for an auxin receptor that is implicated in non-transcriptional auxin signaling. ABP1 also affects TIR1/AFB-mediated auxin-responsive gene expression, implying that both the ABP1 and TIR1/AFB signaling machineries coordinately control auxin-mediated physiological events. Systematic approaches using the comprehensive mapping of the expression and interaction of signaling modules and computational modeling would be valuable for integrating our knowledge of auxin signals and responses.
A novel approach for data integration and disease subtyping
Tagett, Rebecca; Diaz, Diana
2017-01-01
Advances in high-throughput technologies allow for measurements of many types of omics data, yet the meaningful integration of several different data types remains a significant challenge. Another important and difficult problem is the discovery of molecular disease subtypes characterized by relevant clinical differences, such as survival. Here we present a novel approach, called perturbation clustering for data integration and disease subtyping (PINS), which is able to address both challenges. The framework has been validated on thousands of cancer samples, using gene expression, DNA methylation, noncoding microRNA, and copy number variation data available from the Gene Expression Omnibus, the Broad Institute, The Cancer Genome Atlas (TCGA), and the European Genome-Phenome Archive. This simultaneous subtyping approach accurately identifies known cancer subtypes and novel subgroups of patients with significantly different survival profiles. The results were obtained from genome-scale molecular data without any other type of prior knowledge. The approach is sufficiently general to replace existing unsupervised clustering approaches outside the scope of bio-medical research, with the additional ability to integrate multiple types of data. PMID:29066617
Li, Gengyun; Deng, Ying; Geng, Yupeng; Zhou, Chengchuan; Wang, Yuguo; Zhang, Wenju; Song, Zhiping; Gao, Lexuan; Yang, Ji
2017-01-01
Phenotypic plasticity is crucial for plants to survive in changing environments. Discovering microRNAs, identifying their targets and further inferring microRNA functions in mediating plastic developmental responses to environmental changes have been a critical strategy for understanding the underlying molecular mechanisms of phenotypic plasticity. In this study, the dynamic expression patterns of microRNAs under contrasting hydrological habitats in the amphibious species Alternanthera philoxeroides were identified by time course expression profiling using high-throughput sequencing technology. A total of 128 known and 18 novel microRNAs were found to be differentially expressed under contrasting hydrological habitats. The microRNA:mRNA pairs potentially associated with plastic internode elongation were identified by integrative analysis of microRNA and mRNA expression profiles, and were validated by qRT-PCR and 5′ RLM-RACE. The results showed that both the universal microRNAs conserved across different plants and the unique microRNAs novelly identified in A. philoxeroides were involved in the responses to varied water regimes. The results also showed that most of the differentially expressed microRNAs were transiently up-/down-regulated at certain time points during the treatments. The fine-scale temporal changes in microRNA expression highlighted the importance of time-series sampling in identifying stress-responsive microRNAs and analyzing their role in stress response/tolerance. PMID:29259617
Gene expression profile analysis of rat cerebellum under acute alcohol intoxication.
Zhang, Yu; Wei, Guangkuan; Wang, Yuehong; Jing, Ling; Zhao, Qingjie
2015-02-25
Acute alcohol intoxication, a common disease causing damage to the central nervous system (CNS) has been primarily studied on the aspects of alcohol addiction and chronic alcohol exposure. The understanding of gene expression change in the CNS during acute alcohol intoxication is still lacking. We established a model for acute alcohol intoxication in SD rats by oral gavage. A rat cDNA microarray was used to profile mRNA expression in the cerebella of alcohol-intoxicated rats (experimental group) and saline-treated rats (control group). A total of 251 differentially expressed genes were identified in response to acute alcohol intoxication, in which 208 of them were up-regulated and 43 were down-regulated. Gene ontology (GO) term enrichment analysis and pathway analysis revealed that the genes involved in the biological processes of immune response and endothelial integrity are among the most severely affected in response to acute alcohol intoxication. We discovered five transcription factors whose consensus binding motifs are overrepresented in the promoter region of differentially expressed genes. Additionally, we identified 20 highly connected hub genes by co-expression analysis, and validated the differential expression of these genes by real-time quantitative PCR. By determining novel biological pathways and transcription factors that have functional implication to acute alcohol intoxication, our study substantially contributes to the understanding of the molecular mechanism underlying the pathology of acute alcoholism. Copyright © 2014 Elsevier B.V. All rights reserved.
Identifying novel glioma associated pathways based on systems biology level meta-analysis.
Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong
2013-01-01
With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.
Ehrhardt, Anja; Xu, Hui; Huang, Zan; Engler, Jeffrey A; Kay, Mark A
2005-05-01
In this study we performed a head-to-head comparison of the integrase phiC31 derived from a Streptomyces phage and the Sleeping Beauty (SB) transposase, a member of the TC1/mariner superfamily of transposable elements. Mouse liver was cotransfused with a vector containing our most robust human coagulation factor IX expression cassette and the appropriate recombinase recognition site and either a phiC31- or a SB transposase-expressing vector. To analyze transgene persistence and to prove somatic integration in vivo we induced cell cycling of mouse hepatocytes and found that the transgene expression levels dropped by only 16 to 21% and 56 to 66% in mice that received phiC31 and SB, respectively. Notably, no difference in the toxicity profile was detected in mice treated with either recombinase. Moreover we observed that with the integrase-mediated gene transfer, transgene expression levels were dependent on the remaining noncoding vector sequences, which also integrate into the host genome. Further analyses of a hot spot of integration after phiC31-mediated integration revealed small chromosomal deletions at the target site and that the recombination process was not dependent on the orientation in which the phiC31 recognition site attached to the pseudo-recognition sites in the host genome. Coupled together with ongoing improvements in both systems this study suggests that both nonviral vector systems will have important roles in achieving stable gene transfer in vivo.
Saeliw, Thanit; Tangsuwansri, Chayanin; Thongkorn, Surangrat; Chonchaiya, Weerasak; Suphapeetiporn, Kanya; Mutirangura, Apiwat; Tencomnao, Tewin; Hu, Valerie W; Sarachana, Tewarit
2018-01-01
Alu elements are a group of repetitive elements that can influence gene expression through CpG residues and transcription factor binding. Altered gene expression and methylation profiles have been reported in various tissues and cell lines from individuals with autism spectrum disorder (ASD). However, the role of Alu elements in ASD remains unclear. We thus investigated whether Alu elements are associated with altered gene expression profiles in ASD. We obtained five blood-based gene expression profiles from the Gene Expression Omnibus database and human Alu-inserted gene lists from the TranspoGene database. Differentially expressed genes (DEGs) in ASD were identified from each study and overlapped with the human Alu-inserted genes. The biological functions and networks of Alu-inserted DEGs were then predicted by Ingenuity Pathway Analysis (IPA). A combined bisulfite restriction analysis of lymphoblastoid cell lines (LCLs) derived from 36 ASD and 20 sex- and age-matched unaffected individuals was performed to assess the global DNA methylation levels within Alu elements, and the Alu expression levels were determined by quantitative RT-PCR. In ASD blood or blood-derived cells, 320 Alu-inserted genes were reproducibly differentially expressed. Biological function and pathway analysis showed that these genes were significantly associated with neurodevelopmental disorders and neurological functions involved in ASD etiology. Interestingly, estrogen receptor and androgen signaling pathways implicated in the sex bias of ASD, as well as IL-6 signaling and neuroinflammation signaling pathways, were also highlighted. Alu methylation was not significantly different between the ASD and sex- and age-matched control groups. However, significantly altered Alu methylation patterns were observed in ASD cases sub-grouped based on Autism Diagnostic Interview-Revised scores compared with matched controls. Quantitative RT-PCR analysis of Alu expression also showed significant differences between ASD subgroups. Interestingly, Alu expression was correlated with methylation status in one phenotypic ASD subgroup. Alu methylation and expression were altered in LCLs from ASD subgroups. Our findings highlight the association of Alu elements with gene dysregulation in ASD blood samples and warrant further investigation. Moreover, the classification of ASD individuals into subgroups based on phenotypes may be beneficial and could provide insights into the still unknown etiology and the underlying mechanisms of ASD.
Integrative FourD omics approach profiles the target network of the carbon storage regulatory system
Sowa, Steven W.; Gelderman, Grant; Leistra, Abigail N.; Buvanendiran, Aishwarya; Lipp, Sarah; Pitaktong, Areen; Vakulskas, Christopher A.; Romeo, Tony; Baldea, Michael
2017-01-01
Abstract Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets. PMID:28126921
Cenik, Can; Cenik, Elif Sarinay; Byeon, Gun W; Grubert, Fabian; Candille, Sophie I; Spacek, Damek; Alsallakh, Bilal; Tilgner, Hagen; Araya, Carlos L; Tang, Hua; Ricci, Emiliano; Snyder, Michael P
2015-11-01
Elucidating the consequences of genetic differences between humans is essential for understanding phenotypic diversity and personalized medicine. Although variation in RNA levels, transcription factor binding, and chromatin have been explored, little is known about global variation in translation and its genetic determinants. We used ribosome profiling, RNA sequencing, and mass spectrometry to perform an integrated analysis in lymphoblastoid cell lines from a diverse group of individuals. We find significant differences in RNA, translation, and protein levels suggesting diverse mechanisms of personalized gene expression control. Combined analysis of RNA expression and ribosome occupancy improves the identification of individual protein level differences. Finally, we identify genetic differences that specifically modulate ribosome occupancy--many of these differences lie close to start codons and upstream ORFs. Our results reveal a new level of gene expression variation among humans and indicate that genetic variants can cause changes in protein levels through effects on translation. © 2015 Cenik et al.; Published by Cold Spring Harbor Laboratory Press.
Generation of miniaturized planar ecombinant antibody arrays using a microcantilever-based printer
NASA Astrophysics Data System (ADS)
Petersson, Linn; Berthet Duroure, Nathalie; Auger, Angèle; Dexlin-Mellby, Linda; Borrebaeck, Carl AK; Ait Ikhlef, Ali; Wingren, Christer
2014-07-01
Miniaturized (Ø 10 μm), multiplexed (>5-plex), and high-density (>100 000 spots cm-2) antibody arrays will play a key role in generating protein expression profiles in health and disease. However, producing such antibody arrays is challenging, and it is the type and range of available spotters which set the stage. This pilot study explored the use of a novel microspotting tool, BioplumeTM—consisting of an array of micromachined silicon cantilevers with integrated microfluidic channels—to produce miniaturized, multiplexed, and high-density planar recombinant antibody arrays for protein expression profiling which targets crude, directly labelled serum. The results demonstrated that 16-plex recombinant antibody arrays could be produced—based on miniaturized spot features (78.5 um2, Ø 10 μm) at a 7-125-times increased spot density (250 000 spots cm-2), interfaced with a fluorescent-based read-out. This prototype platform was found to display adequate reproducibility (spot-to-spot) and an assay sensitivity in the pM range. The feasibility of the array platform for serum protein profiling was outlined.
Yuan, Yinyin; Failmezger, Henrik; Rueda, Oscar M; Ali, H Raza; Gräf, Stefan; Chin, Suet-Feung; Schwarz, Roland F; Curtis, Christina; Dunning, Mark J; Bardwell, Helen; Johnson, Nicola; Doyle, Sarah; Turashvili, Gulisa; Provenzano, Elena; Aparicio, Sam; Caldas, Carlos; Markowetz, Florian
2012-10-24
Solid tumors are heterogeneous tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Furthermore, tissue architecture is generally not reflected in molecular assays, rendering this rich information underused. To address these challenges, we developed a computational approach based on standard hematoxylin and eosin-stained tissue sections and demonstrated its power in a discovery and validation cohort of 323 and 241 breast tumors, respectively. To deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy number profiles between samples. We next devised a predictor for survival in estrogen receptor-negative breast cancer that integrated both image-based and gene expression analyses and significantly outperformed classifiers that use single data types, such as microarray expression signatures. Image processing also allowed us to describe and validate an independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative, image-based method could benefit any large-scale cancer study by refining and complementing molecular assays of tumor samples.
Ross-Adams, H.; Lamb, A.D.; Dunning, M.J.; Halim, S.; Lindberg, J.; Massie, C.M.; Egevad, L.A.; Russell, R.; Ramos-Montoya, A.; Vowler, S.L.; Sharma, N.L.; Kay, J.; Whitaker, H.; Clark, J.; Hurst, R.; Gnanapragasam, V.J.; Shah, N.C.; Warren, A.Y.; Cooper, C.S.; Lynch, A.G.; Stark, R.; Mills, I.G.; Grönberg, H.; Neal, D.E.
2015-01-01
Background Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts. PMID:26501111
Lee, Byron H
2017-09-01
Dysregulated metabolism is a hallmark of cancer, manifested through alterations in metabolites. We performed metabolomic profiling on 138 matched clear cell renal cell carcinoma (ccRCC)/normal tissue pairs and found that ccRCC is characterized by broad shifts in central carbon metabolism, one-carbon metabolism, and antioxidant response. Tumor progression and metastasis were associated with metabolite increases in glutathione and cysteine/methionine metabolism pathways. We develop an analytic pipeline and visualization tool (metabolograms) to bridge the gap between TCGA transcriptomic profiling and our metabolomic data, which enables us to assemble an integrated pathway-level metabolic atlas and to demonstrate discordance between transcriptome and metabolome. Lastly, expression profiling was performed on a high-glutathione cluster, which corresponds to a poor-survival subgroup in the ccRCC TCGA cohort. Copyright © 2017 Elsevier Inc. All rights reserved.
Meier, Jan; Hovestadt, Volker; Zapatka, Marc; Pscherer, Armin; Lichter, Peter; Seiffert, Martina
2013-01-01
MicroRNAs (miRNAs) are single-stranded, small, non-coding RNAs, which fine-tune protein expression by degrading and/or translationally inhibiting mRNAs. Manipulation of miRNA expression in animal models frequently results in severe phenotypes indicating their relevance in controlling cellular functions, most likely by interacting with multiple targets. To better understand the effect of miRNA activities, genome-wide analysis of their targets are required. MicroRNA profiling as well as transcriptome analysis upon enforced miRNA expression were frequently used to investigate their relevance. However, these approaches often fail to identify relevant miRNAs targets. Therefore, we tested the precision of RNA-interacting protein immunoprecipitation (RIP) using AGO2-specific antibodies, a core component of the “RNA-induced silencing complex” (RISC), followed by RNA sequencing (Seq) in a defined cellular system, the HEK293T cells with stable, ectopic expression of miR-155. Thereby, we identified 100 AGO2-associated mRNAs in miR-155-expressing cells, of which 67 were in silico predicted miR-155 target genes. An integrated analysis of the corresponding expression profiles indicated that these targets were either regulated by mRNA decay or by translational repression. Of the identified miR-155 targets, 17 were related to cell cycle control, suggesting their involvement in the observed increase in cell proliferation of HEK293T cells upon miR-155 expression. Additional, secondary changes within the gene expression profile were detected and might contribute to this phenotype as well. Interestingly, by analyzing RIP-Seq data of HEK-293T cells and two B-cell lines we identified a recurrent disproportional enrichment of several miRNAs, including miR-155 and miRNAs of the miR-17-92 cluster, in the AGO2-associated precipitates, suggesting discrepancies in miRNA expression and activity. PMID:23673373
Wang, Hai-Tao; Kong, Jian-Ping; Ding, Fang; Wang, Xiu-Qin; Wang, Ming-Rong; Liu, Lian-Xin; Wu, Min; Liu, Zhi-Hua
2003-01-01
AIM: To obtain human esophageal cancer cell EC9706 stably expressed epithelial membrane protein-1 (EMP-1) with integrated eukaryotic plasmid harboring the open reading frame (ORF) of human EMP-1, and then to study the mechanism by which EMP-1 exerts its diverse cellular action on cell proliferation and altered gene profile by exploring the effect of EMP-1. METHODS: The authors first constructed pcDNA3.1/myc-his expression vector harboring the ORF of EMP-1 and then transfected it into human esophageal carcinoma cell line EC9706. The positive clones were analyzed by Western blot and RT-PCR. Moreover, the cell growth curve was observed and the cell cycle was checked by FACS technique. Using cDNA microarray technology, the authors compared the gene expression pattern in positive clones with control. To confirm the gene expression profile, semi-quantitative RT-PCR was carried out for 4 of the randomly picked differentially expressed genes. For those differentially expressed genes, classification was performed according to their function and cellular component. RESULTS: Human EMP-1 gene can be stably expressed in EC9706 cell line transfected with human EMP-1. The authors found the cell growth decreased, among which S phase was arrested and G1 phase was prolonged in the transfected positive clones. By cDNA microarray analysis, 35 genes showed an over 2.0 fold change in expression level after transfection, with 28 genes being consistently up-regulated and 7 genes being down-regulated. Among the classified genes, almost half of the induced genes (13 out of 28 genes) were related to cell signaling, cell communication and particularly to adhesion. CONCLUSION: Overexpression of human EMP-1 gene can inhibit the proliferation of EC9706 cell with S phase arrested and G1 phase prolonged. The cDNA microarray analysis suggested that EMP-1 may be one of regulators involved in cell signaling, cell communication and adhesion regulators. PMID:12632483
Wang, Hai-Tao; Kong, Jian-Ping; Ding, Fang; Wang, Xiu-Qin; Wang, Ming-Rong; Liu, Lian-Xin; Wu, Min; Liu, Zhi-Hua
2003-03-01
To obtain human esophageal cancer cell EC9706 stably expressed epithelial membrane protein-1 (EMP-1) with integrated eukaryotic plasmid harboring the open reading frame (ORF) of human EMP-1, and then to study the mechanism by which EMP-1 exerts its diverse cellular action on cell proliferation and altered gene profile by exploring the effect of EMP-1. The authors first constructed pcDNA3.1/myc-his expression vector harboring the ORF of EMP-1 and then transfected it into human esophageal carcinoma cell line EC9706. The positive clones were analyzed by Western blot and RT-PCR. Moreover, the cell growth curve was observed and the cell cycle was checked by FACS technique. Using cDNA microarray technology, the authors compared the gene expression pattern in positive clones with control. To confirm the gene expression profile, semi-quantitative RT-PCR was carried out for 4 of the randomly picked differentially expressed genes. For those differentially expressed genes, classification was performed according to their function and cellular component. Human EMP-1 gene can be stably expressed in EC9706 cell line transfected with human EMP-1. The authors found the cell growth decreased, among which S phase was arrested and G1 phase was prolonged in the transfected positive clones. By cDNA microarray analysis, 35 genes showed an over 2.0 fold change in expression level after transfection, with 28 genes being consistently up-regulated and 7 genes being down-regulated. Among the classified genes, almost half of the induced genes (13 out of 28 genes) were related to cell signaling, cell communication and particularly to adhesion. Overexpression of human EMP-1 gene can inhibit the proliferation of EC9706 cell with S phase arrested and G1 phase prolonged. The cDNA microarray analysis suggested that EMP-1 may be one of regulators involved in cell signaling, cell communication and adhesion regulators.
Senís, Elena; Mockenhaupt, Stefan; Rupp, Daniel; Bauer, Tobias; Paramasivam, Nagarajan; Knapp, Bettina; Gronych, Jan; Grosse, Stefanie; Windisch, Marc P.; Schmidt, Florian; Theis, Fabian J.; Eils, Roland; Lichter, Peter; Schlesner, Matthias; Bartenschlager, Ralf; Grimm, Dirk
2017-01-01
Successful RNAi applications depend on strategies allowing robust and persistent expression of minimal gene silencing triggers without perturbing endogenous gene expression. Here, we propose a novel avenue which is integration of a promoterless shmiRNA, i.e. a shRNA embedded in a micro-RNA (miRNA) scaffold, into an engineered genomic miRNA locus. For proof-of-concept, we used TALE or CRISPR/Cas9 nucleases to site-specifically integrate an anti-hepatitis C virus (HCV) shmiRNA into the liver-specific miR-122/hcr locus in hepatoma cells, with the aim to obtain cellular clones that are genetically protected against HCV infection. Using reporter assays, Northern blotting and qRT-PCR, we confirmed anti-HCV shmiRNA expression as well as miR-122 integrity and functionality in selected cellular progeny. Moreover, we employed a comprehensive battery of PCR, cDNA/miRNA profiling and whole genome sequencing analyses to validate targeted integration of a single shmiRNA molecule at the expected position, and to rule out deleterious effects on the genomes or transcriptomes of the engineered cells. Importantly, a subgenomic HCV replicon and a full-length reporter virus, but not a Dengue virus control, were significantly impaired in the modified cells. Our original combination of DNA engineering and RNAi expression technologies benefits numerous applications, from miRNA, genome and transgenesis research, to human gene therapy. PMID:27614072
Identifying candidate driver genes by integrative ovarian cancer genomics data
NASA Astrophysics Data System (ADS)
Lu, Xinguo; Lu, Jibo
2017-08-01
Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.
Kurashige, Junji; Hasegawa, Takanori; Niida, Atsushi; Sugimachi, Keishi; Deng, Niantao; Mima, Kosuke; Uchi, Ryutaro; Sawada, Genta; Takahashi, Yusuke; Eguchi, Hidetoshi; Inomata, Masashi; Kitano, Seigo; Fukagawa, Takeo; Sasako, Mitsuru; Sasaki, Hiroki; Sasaki, Shin; Mori, Masaki; Yanagihara, Kazuyoshi; Baba, Hideo; Miyano, Satoru; Tan, Patrick; Mimori, Koshi
2016-03-03
Peritoneal dissemination is the most frequent, incurable metastasis occurring in patients with advanced gastric cancer (GC). However, molecular mechanisms driving peritoneal dissemination still remain poorly understood. Here, we aimed to provide novel insights into the molecular mechanisms that drive the peritoneal dissemination of GC. We performed combined expression analysis with in vivo-selected metastatic cell lines and samples from 200 GC patients to identify driver genes of peritoneal dissemination. The driver-gene functions associated with GC dissemination were examined using a mouse xenograft model. We identified a peritoneal dissemination-associated expression signature, whose profile correlated with those of genes related to development, focal adhesion, and the extracellular matrix. Among the genes comprising the expression signature, we identified that discoidin-domain receptor 2 (DDR2) as a potential regulator of peritoneal dissemination. The DDR2 was upregulated by the loss of DNA methylation and that DDR2 knockdown reduced peritoneal metastasis in a xenograft model. Dasatinib, an inhibitor of the DDR2 signaling pathway, effectively suppressed peritoneal dissemination. DDR2 was identified as a driver gene for GC dissemination from the combined expression signature and can potentially serve as a novel therapeutic target for inhibiting GC peritoneal dissemination.
Loke, P'ng; Favre, David; Hunt, Peter W; Leung, Jacqueline M; Kanwar, Bittoo; Martin, Jeffrey N; Deeks, Steven G; McCune, Joseph M
2010-04-15
HIV "controllers" are persons infected with human immunodeficiency virus, type I (HIV) who maintain long-term control of viremia without antiviral therapy and who usually do not develop the acquired immune deficiency syndrome (AIDS). In this study, we have correlated results from polychromatic flow cytometry and oligonucleotide expression arrays to characterize the mucosal immune responses of these subjects in relation to untreated HIV(+) persons with high viral loads and progressive disease ("noncontrollers"). Paired peripheral blood and rectosigmoid biopsies were analyzed from 9 controllers and 11 noncontrollers. Several cellular immune parameters were found to be concordant between the 2 compartments. Compared with noncontrollers, the mucosal tissues of controllers had similar levels of effector T cells and fewer regulatory T cells (Tregs). Using principal component analysis to correlate immunologic parameters with gene expression profiles, transcripts were identified that accurately distinguished between controllers and noncontrollers. Direct 2-way comparison also revealed genes that are significantly different in their expression between controllers and noncontrollers, all of which had reduced expression in controllers. In addition to providing an approach that integrates flow cytometry datasets with transcriptional profiling analysis, these results underscore the importance of the sustained inflammatory response that attends progressive HIV disease.
Perkins, Timothy N.; Peeters, Paul M.; Shukla, Arti; Arijs, Ingrid; Dragon, Julie; Wouters, Emiel F.M.; Reynaert, Niki L.; Mossman, Brooke T.
2015-01-01
Occupational and environmental exposures to airborne asbestos and silica are associated with the development of lung fibrosis in the forms of asbestosis and silicosis, respectively. However, both diseases display distinct pathologic presentations, likely associated with differences in gene expression induced by different mineral structures, composition and bio-persistent properties. We hypothesized that effects of mineral exposure in the airway epithelium may dictate deviating molecular events that may explain the different pathologies of asbestosis versus silicosis. Using robust gene expression-profiling in conjunction with in-depth pathway analysis, we assessed early (24 h) alterations in gene expression associated with crocidolite asbestos or cristobalite silica exposures in primary human bronchial epithelial cells (NHBEs). Observations were confirmed in an immortalized line (BEAS-2B) by QRT-PCR and protein assays. Utilization of overall gene expression, unsupervised hierarchical cluster analysis and integrated pathway analysis revealed gene alterations that were common to both minerals or unique to either mineral. Our findings reveal that both minerals had potent effects on genes governing cell adhesion/migration, inflammation, and cellular stress, key features of fibrosis. Asbestos exposure was most specifically associated with aberrant cell proliferation and carcinogenesis, whereas silica exposure was highly associated with additional inflammatory responses, as well as pattern recognition, and fibrogenesis. These findings illustrate the use of gene-profiling as a means to determine early molecular events that may dictate pathological processes induced by exogenous cellular insults. In addition, it is a useful approach for predicting the pathogenicity of potentially harmful materials. PMID:25351596
Genic insights from integrated human proteomics in GeneCards.
Fishilevich, Simon; Zimmerman, Shahar; Kohn, Asher; Iny Stein, Tsippi; Olender, Tsviya; Kolker, Eugene; Safran, Marilyn; Lancet, Doron
2016-01-01
GeneCards is a one-stop shop for searchable human gene annotations (http://www.genecards.org/). Data are automatically mined from ∼120 sources and presented in an integrated web card for every human gene. We report the application of recent advances in proteomics to enhance gene annotation and classification in GeneCards. First, we constructed the Human Integrated Protein Expression Database (HIPED), a unified database of protein abundance in human tissues, based on the publically available mass spectrometry (MS)-based proteomics sources ProteomicsDB, Multi-Omics Profiling Expression Database, Protein Abundance Across Organisms and The MaxQuant DataBase. The integrated database, residing within GeneCards, compares favourably with its individual sources, covering nearly 90% of human protein-coding genes. For gene annotation and comparisons, we first defined a protein expression vector for each gene, based on normalized abundances in 69 normal human tissues. This vector is portrayed in the GeneCards expression section as a bar graph, allowing visual inspection and comparison. These data are juxtaposed with transcriptome bar graphs. Using the protein expression vectors, we further defined a pairwise metric that helps assess expression-based pairwise proximity. This new metric for finding functional partners complements eight others, including sharing of pathways, gene ontology (GO) terms and domains, implemented in the GeneCards Suite. In parallel, we calculated proteome-based differential expression, highlighting a subset of tissues that overexpress a gene and subserving gene classification. This textual annotation allows users of VarElect, the suite's next-generation phenotyper, to more effectively discover causative disease variants. Finally, we define the protein-RNA expression ratio and correlation as yet another attribute of every gene in each tissue, adding further annotative information. The results constitute a significant enhancement of several GeneCards sections and help promote and organize the genome-wide structural and functional knowledge of the human proteome. Database URL:http://www.genecards.org/. © The Author(s) 2016. Published by Oxford University Press.
Wang, Yumei; Yin, Xiaoling; Yang, Fang
2018-02-01
Sepsis is an inflammatory-related disease, and severe sepsis would induce multiorgan dysfunction, which is the most common cause of death of patients in noncoronary intensive care units. Progression of novel therapeutic strategies has proven to be of little impact on the mortality of severe sepsis, and unfortunately, its mechanisms still remain poorly understood. In this study, we analyzed gene expression profiles of severe sepsis with failure of lung, kidney, and liver for the identification of potential biomarkers. We first downloaded the gene expression profiles from the Gene Expression Omnibus and performed preprocessing of raw microarray data sets and identification of differential expression genes (DEGs) through the R programming software; then, significantly enriched functions of DEGs in lung, kidney, and liver failure sepsis samples were obtained from the Database for Annotation, Visualization, and Integrated Discovery; finally, protein-protein interaction network was constructed for DEGs based on the STRING database, and network modules were also obtained through the MCODE cluster method. As a result, lung failure sepsis has the highest number of DEGs of 859, whereas the number of DEGs in kidney and liver failure sepsis samples is 178 and 175, respectively. In addition, 17 overlaps were obtained among the three lists of DEGs. Biological processes related to immune and inflammatory response were found to be significantly enriched in DEGs. Network and module analysis identified four gene clusters in which all or most of genes were upregulated. The expression changes of Icam1 and Socs3 were further validated through quantitative PCR analysis. This study should shed light on the development of sepsis and provide potential therapeutic targets for sepsis-induced multiorgan failure.
Pulitzer, Melissa P; Brannon, A Rose; Berger, Michael F; Louis, Peter; Scott, Sasinya N; Jungbluth, Achim A; Coit, Daniel G; Brownell, Isaac; Busam, Klaus J
2016-01-01
Cutaneous neuroendocrine (Merkel cell) carcinoma most often arises de novo in the background of a clonally integrated virus, the Merkel cell polyomavirus, and is notable for positive expression of retinoblastoma 1 (RB1) protein and low expression of p53 compared with the rare Merkel cell polyomavirus-negative Merkel cell carcinomas. Combined squamous and Merkel cell tumors are consistently negative for Merkel cell polyomavirus. Little is known about their immunophenotypic or molecular profile. Herein, we studied 10 combined cutaneous squamous cell and neuroendocrine carcinomas for immunohistochemical expression of p53, retinoblastoma 1 protein, neurofilament, p63, and cytokeratin 20 (CK20). We compared mutation profiles of five combined Merkel cell carcinomas and seven ‘pure’ Merkel cell carcinomas using targeted next-generation sequencing. Combined tumors were from the head, trunk, and leg of Caucasian males and one female aged 52–89. All cases were highly p53- and p63-positive and neurofilament-negative in the squamous component, whereas RB1-negative in both components. Eight out of 10 were p53-positive, 3/10 p63-positive, and 3/10 focally neurofilament-positive in the neuroendocrine component. Six out of 10 were CK20-positive in any part. By next-generation sequencing, combined tumors were highly mutated, with an average of 48 mutations per megabase compared with pure tumors, which showed 1.25 mutations per megabase. RB1 and p53 mutations were identified in all five combined tumors. Combined tumors represent an immunophenotypically and genetically distinct variant of primary cutaneous neuroendocrine carcinomas, notable for a highly mutated genetic profile, significant p53 expression and/or mutation, absent RB1 expression in the context of increased RB1 mutation, and minimal neurofilament expression. PMID:26022453
Pulitzer, Melissa P; Brannon, A Rose; Berger, Michael F; Louis, Peter; Scott, Sasinya N; Jungbluth, Achim A; Coit, Daniel G; Brownell, Isaac; Busam, Klaus J
2015-08-01
Cutaneous neuroendocrine (Merkel cell) carcinoma most often arises de novo in the background of a clonally integrated virus, the Merkel cell polyomavirus, and is notable for positive expression of retinoblastoma 1 (RB1) protein and low expression of p53 compared with the rare Merkel cell polyomavirus-negative Merkel cell carcinomas. Combined squamous and Merkel cell tumors are consistently negative for Merkel cell polyomavirus. Little is known about their immunophenotypic or molecular profile. Herein, we studied 10 combined cutaneous squamous cell and neuroendocrine carcinomas for immunohistochemical expression of p53, retinoblastoma 1 protein, neurofilament, p63, and cytokeratin 20 (CK20). We compared mutation profiles of five combined Merkel cell carcinomas and seven 'pure' Merkel cell carcinomas using targeted next-generation sequencing. Combined tumors were from the head, trunk, and leg of Caucasian males and one female aged 52-89. All cases were highly p53- and p63-positive and neurofilament-negative in the squamous component, whereas RB1-negative in both components. Eight out of 10 were p53-positive, 3/10 p63-positive, and 3/10 focally neurofilament-positive in the neuroendocrine component. Six out of 10 were CK20-positive in any part. By next-generation sequencing, combined tumors were highly mutated, with an average of 48 mutations per megabase compared with pure tumors, which showed 1.25 mutations per megabase. RB1 and p53 mutations were identified in all five combined tumors. Combined tumors represent an immunophenotypically and genetically distinct variant of primary cutaneous neuroendocrine carcinomas, notable for a highly mutated genetic profile, significant p53 expression and/or mutation, absent RB1 expression in the context of increased RB1 mutation, and minimal neurofilament expression.
Identification of candidate genes in osteoporosis by integrated microarray analysis.
Li, J J; Wang, B Q; Fei, Q; Yang, Y; Li, D
2016-12-01
In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.Cite this article: J. J. Li, B. Q. Wang, Q. Fei, Y. Yang, D. Li. Identification of candidate genes in osteoporosis by integrated microarray analysis. Bone Joint Res 2016;5:594-601. DOI: 10.1302/2046-3758.512.BJR-2016-0073.R1. © 2016 Fei et al.
Lv, Xiaoyang; Sun, Wei; Yin, Jinfeng; Ni, Rong; Su, Rui; Wang, Qingzeng; Gao, Wen; Bao, Jianjun; Yu, Jiarui; Wang, Lihong; Chen, Ling
2016-01-01
Wave patterns in lambskin hair follicles are an important factor determining the quality of sheep’s wool. Hair follicles in lambskin from Hu sheep, a breed unique to China, have 3 types of waves, designated as large, medium, and small. The quality of wool from small wave follicles is excellent, while the quality of large waves is considered poor. Because no molecular and biological studies on hair follicles of these sheep have been conducted to date, the molecular mechanisms underlying the formation of different wave patterns is currently unknown. The aim of this article was to screen the candidate microRNAs (miRNA) and genes for the development of hair follicles in Hu sheep. Two-day-old Hu lambs were selected from full-sib individuals that showed large, medium, and small waves. Integrated analysis of microRNA and mRNA expression profiles employed high-throughout sequencing technology. Approximately 13, 24, and 18 differentially expressed miRNAs were found between small and large waves, small and medium waves, and medium and large waves, respectively. A total of 54, 190, and 81 differentially expressed genes were found between small and large waves, small and medium waves, and medium and large waves, respectively, by RNA sequencing (RNA-seq) analysis. Differentially expressed genes were classified using gene ontology and pathway analyses. They were found to be mainly involved in cell differentiation, proliferation, apoptosis, growth, immune response, and ion transport, and were associated with MAPK and the Notch signaling pathway. Reverse transcription-polymerase chain reaction (RT-PCR) analyses of differentially-expressed miRNA and genes were consistent with sequencing results. Integrated analysis of miRNA and mRNA expression indicated that, compared to small waves, large waves included 4 downregulated miRNAs that had regulatory effects on 8 upregulated genes and 3 upregulated miRNAs, which in turn influenced 13 downregulated genes. Compared to small waves, medium waves included 13 downregulated miRNAs that had regulatory effects on 64 upregulated genes and 4 upregulated miRNAs, which in turn had regulatory effects on 22 downregulated genes. Compared to medium waves, large waves consisted of 13 upregulated miRNAs that had regulatory effects on 48 downregulated genes. These differentially expressed miRNAs and genes may play a significant role in forming different patterns, and provide evidence for the molecular mechanisms underlying the formation of hair follicles of varying patterns. PMID:27404636
Li, Xiaobo; Zhang, Chengcheng; Bian, Qian; Gao, Na; Zhang, Xin; Meng, Qingtao; Wu, Shenshen; Wang, Shizhi; Xia, Yankai; Chen, Rui
2016-09-01
Gene expression profiling has developed rapidly in recent years and it can predict and define mechanisms underlying chemical toxicity. Here, RNA microarray and computational technology were used to show that aluminum oxide nanoparticles (Al2O3 NPs) were capable of triggering up-regulation of genes related to the cell cycle and cell death in a human A549 lung adenocarcinoma cell line. Gene expression levels were validated in Al2O3 NPs exposed A549 cells and mice lung tissues, most of which showed consistent trends in regulation. Gene-transcription factor network analysis coupled with cell- and animal-based assays demonstrated that the genes encoding PTPN6, RTN4, BAX and IER play a role in the biological responses induced by the nanoparticle exposure, which caused cell death and cell cycle arrest in the G2/S phase. Further, down-regulated PTPN6 expression demonstrated a core role in the network, thus expression level of PTPN6 was rescued by plasmid transfection, which showed ameliorative effects of A549 cells against cell death and cell cycle arrest. These results demonstrate the feasibility of using gene expression profiling to predict cellular responses induced by nanomaterials, which could be used to develop a comprehensive knowledge of nanotoxicity.
Expression profiling of G-protein-coupled receptors in human urothelium and related cell lines.
Ochodnický, Peter; Humphreys, Sian; Eccles, Rachel; Poljakovic, Mirjana; Wiklund, Peter; Michel, Martin C
2012-09-01
What's known on the subject? and What does the study add? Urothelium emerged as a crucial integrator of sensory inputs and outputs in the bladder wall, and urothelial G-protein-coupled receptors (GPCRs) may represent plausible targets for treatment of various bladder pathologies. Urothelial cell lines provide a useful tool to study urothelial receptor function, but their validity as models for native human urothelium remains unclear. We characterize the mRNA expression of genes coding for GPCRs in human freshly isolated urothelium and compare the expression pattern with those in human urothelial cell lines. To characterize the mRNA expression pattern of genes coding for G-protein-coupled receptors (GPCRs) in human freshly isolated urothelium. To compare GPCR expression in human urothelium-derived cell lines to explore the suitability of these cell lines as model systems to study urothelial function. Native human urothelium (commercially sourced) and human urothelium-derived non-cancer (UROtsa and TERT-NHUC) and cancer (J82) cell lines were used. For mRNA expression profiling we used custom-designed real-time polymerase chain reaction array for 40 receptors and several related genes. Native urothelium expressed a wide variety of GPCRs, including α(1A), α(1D) and all subtypes of α(2) and β adrenoceptors. In addition, M(2) and M(3) cholinergic muscarinic receptors, angiotensin II AT(1) receptor, serotonin 5-HT(2A) receptor and all subtypes of bradykinin, endothelin, cannabinoid, tachykinin and sphingosine-1-phosphate receptors were detected. Nerve growth factor and both its low- and high-affinity receptors were also expressed in urothelium. In all cell lines expression of most GPCRs was markedly downregulated, with few exceptions. In UROtsa cells, but much less in other cell lines, the expression of β(2) adrenoceptors, M(3) muscarinic receptors, B(1) and B(2) bradykinin receptors, ET(B) endothelin receptors and several subtypes of sphingosine-1-phosphate receptors was largely retained. Human urothelium expresses a wide range of receptors which enables sensing and integration of various extracellular signals. Human urothelium-derived cell lines, especially UROtsa cells, show comparable mRNA expression to native tissue for several physiologically relevant GPCRs, but lose expression of many other receptors. The use of cell lines as model systems of human urothelium requires careful validation of suitability for the genes of interest. © 2012 BJU INTERNATIONAL.
NASA Astrophysics Data System (ADS)
Gibbs, Holly C.; Dodson, Colin R.; Bai, Yuqiang; Lekven, Arne C.; Yeh, Alvin T.
2014-12-01
During embryogenesis, presumptive brain compartments are patterned by dynamic networks of gene expression. The spatiotemporal dynamics of these networks, however, have not been characterized with sufficient resolution for us to understand the regulatory logic resulting in morphogenetic cellular behaviors that give the brain its shape. We have developed a new, integrated approach using ultrashort pulse microscopy [a high-resolution, two-photon fluorescence (2PF)-optical coherence microscopy (OCM) platform using 10-fs pulses] and image registration to study brain patterning and morphogenesis in zebrafish embryos. As a demonstration, we used time-lapse 2PF to capture midbrain-hindbrain boundary morphogenesis and a wnt1 lineage map from embryos during brain segmentation. We then performed in situ hybridization to deposit NBT/BCIP, where wnt1 remained actively expressed, and reimaged the embryos with combined 2PF-OCM. When we merged these datasets using morphological landmark registration, we found that the mechanism of boundary formation differs along the dorsoventral axis. Dorsally, boundary sharpening is dominated by changes in gene expression, while ventrally, sharpening may be accomplished by lineage sorting. We conclude that the integrated visualization of lineage reporter and gene expression domains simultaneously with brain morphology will be useful for understanding how changes in gene expression give rise to proper brain compartmentalization and structure.
Gibbs, Holly C; Dodson, Colin R; Bai, Yuqiang; Lekven, Arne C; Yeh, Alvin T
2014-12-01
During embryogenesis, presumptive brain compartments are patterned by dynamic networks of gene expression. The spatiotemporal dynamics of these networks, however, have not been characterized with sufficient resolution for us to understand the regulatory logic resulting in morphogenetic cellular behaviors that give the brain its shape. We have developed a new, integrated approach using ultrashort pulse microscopy [a high-resolution, two-photon fluorescence (2PF)-optical coherence microscopy (OCM) platform using 10-fs pulses] and image registration to study brain patterning and morphogenesis in zebrafish embryos. As a demonstration, we used time-lapse 2PF to capture midbrain-hindbrain boundary morphogenesis and a wnt1 lineage map from embryos during brain segmentation. We then performed in situ hybridization to deposit NBT/BCIP, where wnt1 remained actively expressed, and reimaged the embryos with combined 2PF-OCM. When we merged these datasets using morphological landmark registration, we found that the mechanism of boundary formation differs along the dorsoventral axis. Dorsally, boundary sharpening is dominated by changes in gene expression, while ventrally, sharpening may be accomplished by lineage sorting. We conclude that the integrated visualization of lineage reporter and gene expression domains simultaneously with brain morphology will be useful for understanding how changes in gene expression give rise to proper brain compartmentalization and structure.
2014-01-01
Background Cis-regulatory modules (CRMs), or the DNA sequences required for regulating gene expression, play the central role in biological researches on transcriptional regulation in metazoan species. Nowadays, the systematic understanding of CRMs still mainly resorts to computational methods due to the time-consuming and small-scale nature of experimental methods. But the accuracy and reliability of different CRM prediction tools are still unclear. Without comparative cross-analysis of the results and combinatorial consideration with extra experimental information, there is no easy way to assess the confidence of the predicted CRMs. This limits the genome-wide understanding of CRMs. Description It is known that transcription factor binding and epigenetic profiles tend to determine functions of CRMs in gene transcriptional regulation. Thus integration of the genome-wide epigenetic profiles with systematically predicted CRMs can greatly help researchers evaluate and decipher the prediction confidence and possible transcriptional regulatory functions of these potential CRMs. However, these data are still fragmentary in the literatures. Here we performed the computational genome-wide screening for potential CRMs using different prediction tools and constructed the pioneer database, cisMEP (cis-regulatory module epigenetic profile database), to integrate these computationally identified CRMs with genomic epigenetic profile data. cisMEP collects the literature-curated TFBS location data and nine genres of epigenetic data for assessing the confidence of these potential CRMs and deciphering the possible CRM functionality. Conclusions cisMEP aims to provide a user-friendly interface for researchers to assess the confidence of different potential CRMs and to understand the functions of CRMs through experimentally-identified epigenetic profiles. The deposited potential CRMs and experimental epigenetic profiles for confidence assessment provide experimentally testable hypotheses for the molecular mechanisms of metazoan gene regulation. We believe that the information deposited in cisMEP will greatly facilitate the comparative usage of different CRM prediction tools and will help biologists to study the modular regulatory mechanisms between different TFs and their target genes. PMID:25521507
Splenic marginal zone lymphoma: comprehensive analysis of gene expression and miRNA profiling.
Arribas, Alberto J; Gómez-Abad, Cristina; Sánchez-Beato, Margarita; Martinez, Nerea; Dilisio, Lorena; Casado, Felipe; Cruz, Miguel A; Algara, Patrocinio; Piris, Miguel A; Mollejo, Manuela
2013-07-01
Splenic marginal zone lymphoma is a small B-cell neoplasm whose molecular pathogenesis is still essentially unknown and whose differentiation from other small B-cell lymphomas is hampered by the lack of specific markers. We have analyzed the gene expression and miRNA profiles of 31 splenic marginal zone lymphoma cases. For comparison, 7 spleens with reactive lymphoid hyperplasia, 10 spleens infiltrated by chronic lymphocytic leukemia, 12 spleens with follicular lymphoma, 6 spleens infiltrated by mantle cell lymphoma and 15 lymph nodes infiltrated by nodal marginal zone lymphoma were included. The results were validated by qRT-PCR in an independent series including 77 paraffin-embedded splenic marginal zone lymphomas. The splenic marginal zone lymphoma miRNA signature had deregulated expression of 51 miRNAs. The most highly overexpressed miRNAs were miR-155, miR-21, miR-34a, miR-193b and miR-100, while the most repressed miRNAs were miR-377, miR-27b, miR-145, miR-376a and miR-424. MiRNAs located in 14q32-31 were underexpressed in splenic marginal zone lymphoma compared with reactive lymphoid tissues and other B-cell lymphomas. Finally, the gene expression data were integrated with the miRNA profile to identify functional relationships between genes and deregulated miRNAs. Our study reveals miRNAs that are deregulated in splenic marginal zone lymphoma and identifies new candidate diagnostic molecules for splenic marginal zone lymphoma.
O'Brien, M.A.; Costin, B.N.; Miles, M.F.
2014-01-01
Postgenomic studies of the function of genes and their role in disease have now become an area of intense study since efforts to define the raw sequence material of the genome have largely been completed. The use of whole-genome approaches such as microarray expression profiling and, more recently, RNA-sequence analysis of transcript abundance has allowed an unprecedented look at the workings of the genome. However, the accurate derivation of such high-throughput data and their analysis in terms of biological function has been critical to truly leveraging the postgenomic revolution. This chapter will describe an approach that focuses on the use of gene networks to both organize and interpret genomic expression data. Such networks, derived from statistical analysis of large genomic datasets and the application of multiple bioinformatics data resources, poten-tially allow the identification of key control elements for networks associated with human disease, and thus may lead to derivation of novel therapeutic approaches. However, as discussed in this chapter, the leveraging of such networks cannot occur without a thorough understanding of the technical and statistical factors influencing the derivation of genomic expression data. Thus, while the catch phrase may be “it's the network … stupid,” the understanding of factors extending from RNA isolation to genomic profiling technique, multivariate statistics, and bioinformatics are all critical to defining fully useful gene networks for study of complex biology. PMID:23195313
Integrative analyses of leprosy susceptibility genes indicate a common autoimmune profile.
Zhang, Deng-Feng; Wang, Dong; Li, Yu-Ye; Yao, Yong-Gang
2016-04-01
Leprosy is an ancient chronic infection in the skin and peripheral nerves caused by Mycobacterium leprae. The development of leprosy depends on genetic background and the immune status of the host. However, there is no systematic view focusing on the biological pathways, interaction networks and overall expression pattern of leprosy-related immune and genetic factors. To identify the hub genes in the center of leprosy genetic network and to provide an insight into immune and genetic factors contributing to leprosy. We retrieved all reported leprosy-related genes and performed integrative analyses covering gene expression profiling, pathway analysis, protein-protein interaction network, and evolutionary analyses. A list of 123 differentially expressed leprosy related genes, which were enriched in activation and regulation of immune response, was obtained in our analyses. Cross-disorder analysis showed that the list of leprosy susceptibility genes was largely shared by typical autoimmune diseases such as lupus erythematosus and arthritis, suggesting that similar pathways might be affected in leprosy and autoimmune diseases. Protein-protein interaction (PPI) and positive selection analyses revealed a co-evolution network of leprosy risk genes. Our analyses showed that leprosy associated genes constituted a co-evolution network and might undergo positive selection driven by M. leprae. We suggested that leprosy may be a kind of autoimmune disease and the development of leprosy is a matter of defect or over-activation of body immunity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
NorWood: a gene expression resource for evo-devo studies of conifer wood development.
Jokipii-Lukkari, Soile; Sundell, David; Nilsson, Ove; Hvidsten, Torgeir R; Street, Nathaniel R; Tuominen, Hannele
2017-10-01
The secondary xylem of conifers is composed mainly of tracheids that differ anatomically and chemically from angiosperm xylem cells. There is currently no high-spatial-resolution data available profiling gene expression during wood formation for any coniferous species, which limits insight into tracheid development. RNA-sequencing data from replicated, high-spatial-resolution section series throughout the cambial and woody tissues of Picea abies were used to generate the NorWood.conGenIE.org web resource, which facilitates exploration of the associated gene expression profiles and co-expression networks. Integration within PlantGenIE.org enabled a comparative regulomics analysis, revealing divergent co-expression networks between P. abies and the two angiosperm species Arabidopsis thaliana and Populus tremula for the secondary cell wall (SCW) master regulator NAC Class IIB transcription factors. The SCW cellulose synthase genes (CesAs) were located in the neighbourhoods of the NAC factors in A. thaliana and P. tremula, but not in P. abies. The NorWood co-expression network enabled identification of potential SCW CesA regulators in P. abies. The NorWood web resource represents a powerful community tool for generating evo-devo insights into the divergence of wood formation between angiosperms and gymnosperms and for advancing understanding of the regulation of wood development in P. abies. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
Kuuluvainen, Emilia; Hakala, Heini; Havula, Essi; Sahal Estimé, Michelle; Rämet, Mika; Hietakangas, Ville; Mäkelä, Tomi P
2014-06-06
The Cdk8 (cyclin-dependent kinase 8) module of Mediator integrates regulatory cues from transcription factors to RNA polymerase II. It consists of four subunits where Med12 and Med13 link Cdk8 and cyclin C (CycC) to core Mediator. Here we have investigated the contributions of the Cdk8 module subunits to transcriptional regulation using RNA interference in Drosophila cells. Genome-wide expression profiling demonstrated separation of Cdk8-CycC and Med12-Med13 profiles. However, transcriptional regulation by Cdk8-CycC was dependent on Med12-Med13. This observation also revealed that Cdk8-CycC and Med12-Med13 often have opposite transcriptional effects. Interestingly, Med12 and Med13 profiles overlapped significantly with that of the GATA factor Serpent. Accordingly, mutational analyses indicated that GATA sites are required for Med12-Med13 regulation of Serpent-dependent genes. Med12 and Med13 were also found to be required for Serpent-activated innate immunity genes in defense to bacterial infection. The results reveal a novel role for the Cdk8 module in Serpent-dependent transcription and innate immunity. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.
Biton, Jerome; Mansuet-Lupo, Audrey; Pécuchet, Nicolas; Alifano, Marco; Ouakrim, Hanane; Arrondeau, Jennifer; Boudou-Rouquette, Pascaline; Goldwasser, Francois; Leroy, Karen; Goc, Jeremy; Wislez, Marie; Germain, Claire; Laurent-Puig, Pierre; Dieu-Nosjean, Marie-Caroline; Cremer, Isabelle; Herbst, Ronald; Blons, Hélène F; Damotte, Diane
2018-05-15
By unlocking anti-tumor immunity, antibodies targeting programmed cell death 1 (PD-1) exhibit impressive clinical results in non-small cell lung cancer, underlining the strong interactions between tumor and immune cells. However, factors that can robustly predict long-lasting responses are still needed. We performed in depth immune profiling of lung adenocarcinoma using an integrative analysis based on immunohistochemistry, flow-cytometry and transcriptomic data. Tumor mutational status was investigated using next-generation sequencing. The response to PD-1 blockers was analyzed from a prospective cohort according to tumor mutational profiles and to PD-L1 expression, and a public clinical database was used to validate the results obtained. We showed that distinct combinations of STK11 , EGFR and TP53 mutations, were major determinants of the tumor immune profile (TIP) and of the expression of PD-L1 by malignant cells. Indeed, the presence of TP53 mutations without co-occurring STK11 or EGFR alterations ( TP53 -mut/ STK11 - EGFR -WT), independently of KRAS mutations, identified the group of tumors with the highest CD8 T cell density and PD-L1 expression. In this tumor subtype, pathways related to T cell chemotaxis, immune cell cytotoxicity, and antigen processing were up-regulated. Finally, a prolonged progression-free survival (PFS: HR=0.32; 95% CI, 0.16-0.63, p <0.001) was observed in anti-PD-1 treated patients harboring TP53 -mut/ STK11 - EGFR -WT tumors. This clinical benefit was even more remarkable in patients with associated strong PD-L1 expression. Our study reveals that different combinations of TP53 , EGFR and STK11 mutations , together with PD-L1 expression by tumor cells, represent robust parameters to identify best responders to PD-1 blockade. Copyright ©2018, American Association for Cancer Research.
Changes in the transcriptomic profiles of maize roots in response to iron-deficiency stress.
Li, Yan; Wang, Nian; Zhao, Fengtao; Song, Xuejiao; Yin, Zhaohua; Huang, Rong; Zhang, Chunqing
2014-07-01
Plants are often subjected to iron (Fe)-deficiency stress because of its low solubility. Plants have evolved two distinct strategies to solubilize and transport Fe to acclimate to this abiotic stress condition. Transcriptomic profiling analysis was performed using Illumina digital gene expression to understand the mechanism underlying resistance responses of roots to Fe starvation in maize, an important Strategy II plant. A total of 3,427, 4,069, 4,881, and 2,610 genes had significantly changed expression levels after Fe-deficiency treatments of 1, 2, 4 or 7 days, respectively. Genes involved in 2'-deoxymugineic acid (DMA) synthesis, secretion, and Fe(III)-DMA uptake were significantly induced. Many genes related to plant hormones, protein kinases, and protein phosphatases responded to Fe-deficiency stress, suggesting their regulatory roles in response to the Fe-deficiency stress. Functional annotation clustering analysis, using the Database for Annotation, Visualization and Integrated Discovery, revealed maize root responses to Fe starvation. This resulted in 38 functional annotation clusters: 25 for up-regulated genes, and 13 for down-regulated ones. These included genes encoding enzymes involved in the metabolism of carboxylic acids, isoprenoids and aromatic compounds, transporters, and stress response proteins. Our work provides integrated information for understanding maize response to Fe-deficiency stress.
Toxicogenomics concepts and applications to study hepatic effects of food additives and chemicals
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stierum, Rob; Heijne, Wilbert; Kienhuis, Anne
2005-09-01
Transcriptomics, proteomics and metabolomics are genomics technologies with great potential in toxicological sciences. Toxicogenomics involves the integration of conventional toxicological examinations with gene, protein or metabolite expression profiles. An overview together with selected examples of the possibilities of genomics in toxicology is given. The expectations raised by toxicogenomics are earlier and more sensitive detection of toxicity. Furthermore, toxicogenomics will provide a better understanding of the mechanism of toxicity and may facilitate the prediction of toxicity of unknown compounds. Mechanism-based markers of toxicity can be discovered and improved interspecies and in vitro-in vivo extrapolations will drive model developments in toxicology. Toxicologicalmore » assessment of chemical mixtures will benefit from the new molecular biological tools. In our laboratory, toxicogenomics is predominantly applied for elucidation of mechanisms of action and discovery of novel pathway-supported mechanism-based markers of liver toxicity. In addition, we aim to integrate transcriptome, proteome and metabolome data, supported by bioinformatics to develop a systems biology approach for toxicology. Transcriptomics and proteomics studies on bromobenzene-mediated hepatotoxicity in the rat are discussed. Finally, an example is shown in which gene expression profiling together with conventional biochemistry led to the discovery of novel markers for the hepatic effects of the food additives butylated hydroxytoluene, curcumin, propyl gallate and thiabendazole.« less
Garcia-Closas, Montserrat; Davis, Sean; Meltzer, Paul; Lissowska, Jolanta; Horne, Hisani N.; Sherman, Mark E.; Lee, Maxwell
2015-01-01
Identification of prognostic gene expression signatures may enable improved decisions about management of breast cancer. To identify a prognostic signature for breast cancer, we performed DNA methylation profiling and identified methylation markers that were associated with expression of ER, PR, HER2, CK5/6 and EGFR proteins. Methylation markers that were correlated with corresponding mRNA expression levels were identified using 208 invasive tumors from a population-based case-control study conducted in Poland. Using this approach, we defined the Methylation Expression Index (MEI) signature that was based on a weighted sum of mRNA levels of 57 genes. Classification of cases as low or high MEI scores were related to survival using Cox regression models. In the Polish study, women with ER-positive low MEI cancers had reduced survival at a median of 5.20 years of follow-up, HR=2.85 95%CI=1.25-6.47. Low MEI was also related to decreased survival in four independent datasets totaling over 2500 ER-positive breast cancers. These results suggest that integrated analysis of tumor expression markers, DNA methylation, and mRNA data can be an important approach for identifying breast cancer prognostic signatures. Prospective assessment of MEI along with other prognostic signatures should be evaluated in future studies. PMID:25773928
21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Cardiac allograft gene expression profiling test... Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a) Identification. A cardiac allograft gene expression profiling test system is a device that measures the...
Gilroy, Kathryn L; Terry, Anne; Naseer, Asif; de Ridder, Jeroen; Allahyar, Amin; Wang, Weiwei; Carpenter, Eric; Mason, Andrew; Wong, Gane K-S; Cameron, Ewan R; Kilbey, Anna; Neil, James C
2016-01-01
Retroviruses have been foundational in cancer research since early studies identified proto-oncogenes as targets for insertional mutagenesis. Integration of murine gamma-retroviruses into the host genome favours promoters and enhancers and entails interaction of viral integrase with host BET/bromodomain factors. We report that this integration pattern is conserved in feline leukaemia virus (FeLV), a gamma-retrovirus that infects many human cell types. Analysis of FeLV insertion sites in the MCF-7 mammary carcinoma cell line revealed strong bias towards active chromatin marks with no evidence of significant post-integration growth selection. The most prominent FeLV integration targets had little overlap with the most abundantly expressed transcripts, but were strongly enriched for annotated cancer genes. A meta-analysis based on several gamma-retrovirus integration profiling (GRIP) studies in human cells (CD34+, K562, HepG2) revealed a similar cancer gene bias but also remarkable cell-type specificity, with prominent exceptions including a universal integration hotspot at the long non-coding RNA MALAT1. Comparison of GRIP targets with databases of super-enhancers from the same cell lines showed that these have only limited overlap and that GRIP provides unique insights into the upstream drivers of cell growth. These observations elucidate the oncogenic potency of the gamma-retroviruses and support the wider application of GRIP to identify the genes and growth regulatory circuits that drive distinct cancer types.
Global PROTOMAP profiling to search for biomarkers of early-recurrent hepatocellular carcinoma.
Taoka, Masato; Morofuji, Noriaki; Yamauchi, Yoshio; Ojima, Hidenori; Kubota, Daisuke; Terukina, Goro; Nobe, Yuko; Nakayama, Hiroshi; Takahashi, Nobuhiro; Kosuge, Tomoo; Isobe, Toshiaki; Kondo, Tadashi
2014-11-07
This study used global protein expression profiling to search for biomarkers to predict early recurrent hepatocellular carcinoma (HCC). HCC tissues surgically resected from patients with or without recurrence within 2 years (early recurrent) after surgery were compared with adjacent nontumor tissue and with normal liver tissue. We used the PROTOMAP strategy for comparative profiling, which integrates denaturing polyacrylamide gel electrophoresis migratory rates and high-resolution, semiquantitative mass-spectrometry-based identification of in-gel-digested tryptic peptides. PROTOMAP allows examination of global changes in the size, topography, and abundance of proteins in complex tissue samples. This approach identified 8438 unique proteins from 45 708 nonredundant peptides and generated a proteome-wide map of changes in expression and proteolytic events potentially induced by intrinsic apoptotic/necrotic pathways. In the early recurrent HCC tissue, 87 proteins were differentially expressed (≥20-fold) relative to the other tissues, 46 of which were up-regulated or specifically proteolyzed and 41 of which were down-regulated. This data set consisted of proteins that fell into various functional categories, including signal transduction and cell organization and, notably, the major catalytic pathways responsible for liver function, such as the urea cycle and detoxification metabolism. We found that aberrant proteolysis appeared to occur frequently during recurrence of HCC in several key signal transducers, including STAT1 and δ-catenin. Further investigation of these proteins will facilitate the development of novel clinical applications.
Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C
2011-01-01
Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673
Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data.
Racle, Julien; de Jonge, Kaat; Baumgaertner, Petra; Speiser, Daniel E; Gfeller, David
2017-11-13
Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org).
Sowa, Steven W; Gelderman, Grant; Leistra, Abigail N; Buvanendiran, Aishwarya; Lipp, Sarah; Pitaktong, Areen; Vakulskas, Christopher A; Romeo, Tony; Baldea, Michael; Contreras, Lydia M
2017-02-28
Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Furge, Kyle A; Dykema, Karl; Petillo, David; Westphal, Michael; Zhang, Zhongfa; Kort, Eric J; Teh, Bin Tean
2007-01-01
Using high-throughput gene-expression profiling technology, we can now gain a better understanding of the complex biology that is taking place in cancer cells. This complexity is largely dictated by the abnormal genetic makeup of the cancer cells. This abnormal genetic makeup can have profound effects on cellular activities such as cell growth, cell survival and other regulatory processes. Based on the pattern of gene expression, or molecular signatures of the tumours, we can distinguish or subclassify different types of cancers according to their cell of origin, behaviour, and the way they respond to therapeutic agents and radiation. These approaches will lead to better molecular subclassification of tumours, the basis of personalized medicine. We have, to date, done whole-genome microarray gene-expression profiling on several hundreds of kidney tumours. We adopt a combined bioinformatic approach, based on an integrative analysis of the gene-expression data. These data are used to identify both cytogenetic abnormalities and molecular pathways that are deregulated in renal cell carcinoma (RCC). For example, we have identified the deregulation of the VHL-hypoxia pathway in clear-cell RCC, as previously known, and the c-Myc pathway in aggressive papillary RCC. Besides the more common clear-cell, papillary and chromophobe RCCs, we are currently characterizing the molecular signatures of rarer forms of renal neoplasia such as carcinoma of the collecting ducts, mixed epithelial and stromal tumours, chromosome Xp11 translocations associated with papillary RCC, renal medullary carcinoma, mucinous tubular and spindle-cell carcinoma, and a group of unclassified tumours. Continued development and improvement in the field of molecular profiling will better characterize cancer and provide more accurate diagnosis, prognosis and prediction of drug response. PMID:18542781
The BIG Data Center: from deposition to integration to translation
2017-01-01
Biological data are generated at unprecedentedly exponential rates, posing considerable challenges in big data deposition, integration and translation. The BIG Data Center, established at Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, provides a suite of database resources, including (i) Genome Sequence Archive, a data repository specialized for archiving raw sequence reads, (ii) Gene Expression Nebulas, a data portal of gene expression profiles based entirely on RNA-Seq data, (iii) Genome Variation Map, a comprehensive collection of genome variations for featured species, (iv) Genome Warehouse, a centralized resource housing genome-scale data with particular focus on economically important animals and plants, (v) Methylation Bank, an integrated database of whole-genome single-base resolution methylomes and (vi) Science Wikis, a central access point for biological wikis developed for community annotations. The BIG Data Center is dedicated to constructing and maintaining biological databases through big data integration and value-added curation, conducting basic research to translate big data into big knowledge and providing freely open access to a variety of data resources in support of worldwide research activities in both academia and industry. All of these resources are publicly available and can be found at http://bigd.big.ac.cn. PMID:27899658
Duan, Qiaonan; Flynn, Corey; Niepel, Mario; Hafner, Marc; Muhlich, Jeremy L; Fernandez, Nicolas F; Rouillard, Andrew D; Tan, Christopher M; Chen, Edward Y; Golub, Todd R; Sorger, Peter K; Subramanian, Aravind; Ma'ayan, Avi
2014-07-01
For the Library of Integrated Network-based Cellular Signatures (LINCS) project many gene expression signatures using the L1000 technology have been produced. The L1000 technology is a cost-effective method to profile gene expression in large scale. LINCS Canvas Browser (LCB) is an interactive HTML5 web-based software application that facilitates querying, browsing and interrogating many of the currently available LINCS L1000 data. LCB implements two compacted layered canvases, one to visualize clustered L1000 expression data, and the other to display enrichment analysis results using 30 different gene set libraries. Clicking on an experimental condition highlights gene-sets enriched for the differentially expressed genes from the selected experiment. A search interface allows users to input gene lists and query them against over 100 000 conditions to find the top matching experiments. The tool integrates many resources for an unprecedented potential for new discoveries in systems biology and systems pharmacology. The LCB application is available at http://www.maayanlab.net/LINCS/LCB. Customized versions will be made part of the http://lincscloud.org and http://lincs.hms.harvard.edu websites. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
iGC-an integrated analysis package of gene expression and copy number alteration.
Lai, Yi-Pin; Wang, Liang-Bo; Wang, Wei-An; Lai, Liang-Chuan; Tsai, Mong-Hsun; Lu, Tzu-Pin; Chuang, Eric Y
2017-01-14
With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual. We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance. The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .
2015-01-01
Background microRNA (miRNA) expression plays an influential role in cancer classification and malignancy, and miRNAs are feasible as alternative diagnostic markers for pancreatic cancer, a highly aggressive neoplasm with silent early symptoms, high metastatic potential, and resistance to conventional therapies. Methods In this study, we evaluated the benefits of multi-omics data analysis by integrating miRNA and mRNA expression data in pancreatic cancer. Using support vector machine (SVM) modelling and leave-one-out cross validation (LOOCV), we evaluated the diagnostic performance of single- or multi-markers based on miRNA and mRNA expression profiles from 104 PDAC tissues and 17 benign pancreatic tissues. For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) data depositories. For validation, miRNA activity was estimated by miRNA-target gene interaction and mRNA expression datasets in pancreatic cancer. Results Using a comprehensive identification approach, we successfully identified 705 multi-markers having powerful diagnostic performance for PDAC. In addition, these marker candidates annotated with cancer pathways using gene ontology analysis. Conclusions Our prediction models have strong potential for the diagnosis of pancreatic cancer. PMID:26328610
Integrating mean and variance heterogeneities to identify differentially expressed genes.
Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen
2016-12-06
In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment-wide significant MVDE genes. Our results indicate tremendous potential gain of integrating informative variance heterogeneity after adjusting for global confounders and background data structure. The proposed informative integration test better summarizes the impacts of condition change on expression distributions of susceptible genes than do the existent competitors. Therefore, particular attention should be paid to explicitly exploit the variance heterogeneity induced by condition change in functional genomics analysis.
Changes in miRNA expression profile of space-flown Caenorhabditis elegans during Shenzhou-8 mission
NASA Astrophysics Data System (ADS)
Xu, Dan; Gao, Ying; Huang, Lei; Sun, Yeqing
2014-04-01
Recent advances in the field of molecular biology have demonstrated that small non-coding microRNAs (miRNAs) have a broad effect on gene expression networks and play a key role in biological responses to environmental stressors. However, little is known about how space radiation exposure and altered gravity affect miRNA expression. The "International Space Biological Experiments" project was carried out in November 2011 by an international collaboration between China and Germany during the Shenzhou-8 (SZ-8) mission. To study the effects of spaceflight on Caenorhabditis elegans (C. elegans), we explored the expression profile miRNA changes in space-flown C. elegans. Dauer C. elegans larvae were taken by SZ-8 spacecraft and experienced the 16.5-day shuttle spaceflight. We performed miRNA microarray analysis, and the results showed that 23 miRNAs were altered in a complex space environment and different expression patterns were observed in the space synthetic and radiation environments. Most putative target genes of the altered miRNAs in the space synthetic environment were predicted to be involved in developmental processes instead of in the regulation of transcription, and the enrichment of these genes was due to space radiation. Furthermore, integration analysis of the miRNA and mRNA expression profiles confirmed that twelve genes were differently regulated by seven miRNAs. These genes may be involved in embryonic development, reproduction, transcription factor activity, oviposition in a space synthetic environment, positive regulation of growth and body morphogenesis in a space radiation environment. Specifically, we found that cel-miR-52, -55, and -56 of the miR-51 family were sensitive to space environmental stressors and could regulate biological behavioural responses and neprilysin activity through the different isoforms of T01C4.1 and F18A12.8. These findings suggest that C. elegans responded to spaceflight by altering the expression of miRNAs and some target genes that function in diverse regulatory pathways.
Metastatic breast carcinomas display genomic and transcriptomic heterogeneity
Weigelt, Britta; Ng, Charlotte KY; Shen, Ronglai; Popova, Tatiana; Schizas, Michail; Natrajan, Rachael; Mariani, Odette; Stern, Marc-Henri; Norton, Larry; Vincent-Salomon, Anne; Reis-Filho, Jorge S
2015-01-01
Metaplastic breast carcinoma is a rare and aggressive histologic type of breast cancer, preferentially displaying a triple-negative phenotype. We sought to define the transcriptomic heterogeneity of metaplastic breast cancers on the basis of current gene expression microarray-based classifiers, and to determine whether these tumors display gene copy number profiles consistent with those of BRCA1-associated breast cancers. Twenty-eight consecutive triple-negative metaplastic breast carcinomas were reviewed, and the metaplastic component present in each frozen specimen was defined (ie, spindle cell, squamous, chondroid metaplasia). RNA and DNA extracted from frozen sections with tumor cell content >60% were subjected to gene expression (Illumina HumanHT-12 v4) and copy number profiling (Affymetrix SNP 6.0), respectively. Using the best practice PAM50/claudin-low microarray-based classifier, all metaplastic breast carcinomas with spindle cell metaplasia were of claudin-low subtype, whereas those with squamous or chondroid metaplasia were preferentially of basal-like subtype. Triple-negative breast cancer subtyping using a dedicated website (http://cbc.mc.vanderbilt.edu/tnbc/) revealed that all metaplastic breast carcinomas with chondroid metaplasia were of mesenchymal-like subtype, spindle cell carcinomas preferentially of unstable or mesenchymal stem-like subtype, and those with squamous metaplasia were of multiple subtypes. None of the cases was classified as immunomodulatory or luminal androgen receptor subtype. Integrative clustering, combining gene expression and gene copy number data, revealed that metaplastic breast carcinomas with spindle cell and chondroid metaplasia were preferentially classified as of integrative clusters 4 and 9, respectively, whereas those with squamous metaplasia were classified into six different clusters. Eight of the 26 metaplastic breast cancers subjected to SNP6 analysis were classified as BRCA1-like. The diversity of histologic features of metaplastic breast carcinomas is reflected at the transcriptomic level, and an association between molecular subtypes and histology was observed. BRCA1-like genomic profiles were found only in a subset (31%) of metaplastic breast cancers, and were not associated with a specific molecular or histologic subtype. PMID:25412848
Wang, Anping; Zhang, Guibin
2017-11-01
The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.
Molecular Profile of Peripheral Blood Mononuclear Cells from Patients with Rheumatoid Arthritis
Edwards, Christopher J; Feldman, Jeffrey L; Beech, Jonathan; Shields, Kathleen M; Stover, Jennifer A; Trepicchio, William L; Larsen, Glenn; Foxwell, Brian MJ; Brennan, Fionula M; Feldmann, Marc; Pittman, Debra D
2007-01-01
Rheumatoid arthritis (RA) is a chronic inflammatory arthritis. Currently, diagnosis of RA may take several weeks, and factors used to predict a poor prognosis are not always reliable. Gene expression in RA may consist of a unique signature. Gene expression analysis has been applied to synovial tissue to define molecularly distinct forms of RA; however, expression analysis of tissue taken from a synovial joint is invasive and clinically impractical. Recent studies have demonstrated that unique gene expression changes can be identified in peripheral blood mononuclear cells (PBMCs) from patients with cancer, multiple sclerosis, and lupus. To identify RA disease-related genes, we performed a global gene expression analysis. RNA from PBMCs of 9 RA patients and 13 normal volunteers was analyzed on an oligonucleotide array. Compared with normal PBMCs, 330 transcripts were differentially expressed in RA. The differentially regulated genes belong to diverse functional classes and include genes involved in calcium binding, chaperones, cytokines, transcription, translation, signal transduction, extracellular matrix, integral to plasma membrane, integral to intracellular membrane, mitochondrial, ribosomal, structural, enzymes, and proteases. A k-nearest neighbor analysis identified 29 transcripts that were preferentially expressed in RA. Ten genes with increased expression in RA PBMCs compared with controls mapped to a RA susceptibility locus, 6p21.3. These results suggest that analysis of RA PBMCs at the molecular level may provide a set of candidate genes that could yield an easily accessible gene signature to aid in early diagnosis and treatment. PMID:17515956
Moire, Laurence; Rezzonico, Enea; Goepfert, Simon; Poirier, Yves
2004-01-01
Arabidopsis expressing the castor bean (Ricinus communis) oleate 12-hydroxylase or the Crepis palaestina linoleate 12-epoxygenase in developing seeds typically accumulate low levels of ricinoleic acid and vernolic acid, respectively. We have examined the presence of a futile cycle of fatty acid degradation in developing seeds using the synthesis of polyhydroxyalkanoate (PHA) from the intermediates of the peroxisomal beta-oxidation cycle. Both the quantity and monomer composition of the PHA synthesized in transgenic plants expressing the 12-epoxygenase and 12-hydroxylase in developing seeds revealed the presence of a futile cycle of degradation of the corresponding unusual fatty acids, indicating a limitation in their stable integration into lipids. The expression profile of nearly 200 genes involved in fatty acid biosynthesis and degradation has been analyzed through microarray. No significant changes in gene expression have been detected as a consequence of the activity of the 12-epoxygenase or the 12-hydroxylase in developing siliques. Similar results have also been obtained for transgenic plants expressing the Cuphea lanceolata caproyl-acyl carrier protein thioesterase and accumulating high amounts of caproic acid. Only in developing siliques of the tag1 mutant, deficient in the accumulation of triacylglycerols and shown to have a substantial futile cycling of fatty acids toward beta-oxidation, have some changes in gene expression been detected, notably the induction of the isocitrate lyase gene. These results indicate that analysis of peroxisomal PHA is a better indicator of the flux of fatty acid through beta-oxidation than the expression profile of genes involved in lipid metabolism.
Moire, Laurence; Rezzonico, Enea; Goepfert, Simon; Poirier, Yves
2004-01-01
Arabidopsis expressing the castor bean (Ricinus communis) oleate 12-hydroxylase or the Crepis palaestina linoleate 12-epoxygenase in developing seeds typically accumulate low levels of ricinoleic acid and vernolic acid, respectively. We have examined the presence of a futile cycle of fatty acid degradation in developing seeds using the synthesis of polyhydroxyalkanoate (PHA) from the intermediates of the peroxisomal β-oxidation cycle. Both the quantity and monomer composition of the PHA synthesized in transgenic plants expressing the 12-epoxygenase and 12-hydroxylase in developing seeds revealed the presence of a futile cycle of degradation of the corresponding unusual fatty acids, indicating a limitation in their stable integration into lipids. The expression profile of nearly 200 genes involved in fatty acid biosynthesis and degradation has been analyzed through microarray. No significant changes in gene expression have been detected as a consequence of the activity of the 12-epoxygenase or the 12-hydroxylase in developing siliques. Similar results have also been obtained for transgenic plants expressing the Cuphea lanceolata caproyl-acyl carrier protein thioesterase and accumulating high amounts of caproic acid. Only in developing siliques of the tag1 mutant, deficient in the accumulation of triacylglycerols and shown to have a substantial futile cycling of fatty acids toward β-oxidation, have some changes in gene expression been detected, notably the induction of the isocitrate lyase gene. These results indicate that analysis of peroxisomal PHA is a better indicator of the flux of fatty acid through β-oxidation than the expression profile of genes involved in lipid metabolism. PMID:14671017
Tao, Wenjing; Sun, Lina; Shi, Hongjuan; Cheng, Yunying; Jiang, Dongneng; Fu, Beide; Conte, Matthew A; Gammerdinger, William J; Kocher, Thomas D; Wang, Deshou
2016-05-04
MicroRNAs (miRNAs) represent a second regulatory network that has important effects on gene expression and protein translation during biological process. However, the possible role of miRNAs in the early stages of fish sex differentiation is not well understood. In this study, we carried an integrated analysis of miRNA and mRNA expression profiles to explore their possibly regulatory patterns at the critical stage of sex differentiation in tilapia. We identified 279 pre-miRNA genes in tilapia genome, which were highly conserved in other fish species. Based on small RNA library sequencing, we identified 635 mature miRNAs in tilapia gonads, in which 62 and 49 miRNAs showed higher expression in XX and XY gonads, respectively. The predicted targets of these sex-biased miRNAs (e.g., miR-9, miR-21, miR-30a, miR-96, miR-200b, miR-212 and miR-7977) included genes encoding key enzymes in steroidogenic pathways (Cyp11a1, Hsd3b, Cyp19a1a, Hsd11b) and key molecules involved in vertebrate sex differentiation (Foxl2, Amh, Star1, Sf1, Dmrt1, and Gsdf). These genes also showed sex-biased expression in tilapia gonads at 5 dah. Some miRNAs (e.g., miR-96 and miR-737) targeted multiple genes involved in steroid synthesis, suggesting a complex miRNA regulatory network during early sex differentiation in this fish. The sequence and expression patterns of most miRNAs in tilapia are conserved in fishes, indicating the basic functions of vertebrate miRNAs might share a common evolutionary origin. This comprehensive analysis of miRNA and mRNA at the early stage of molecular sex differentiation in tilapia XX and XY gonads lead to the discovery of differentially expressed miRNAs and their putative targets, which will facilitate studies of the regulatory network of molecular sex determination and differentiation in fishes.
He, Hailong; Mao, Lingzhou; Xu, Peng; Xi, Yanhai; Xu, Ning; Xue, Mingtao; Yu, Jiangming; Ye, Xiaojian
2014-01-10
Ossification of the posterior longitudinal ligament (OPLL) is a kind of disease with physical barriers and neurological disorders. The objective of this study was to explore the differentially expressed genes (DEGs) in OPLL patient ligament cells and identify the target sites for the prevention and treatment of OPLL in clinic. Gene expression data GSE5464 was downloaded from Gene Expression Omnibus; then DEGs were screened by limma package in R language, and changed functions and pathways of OPLL cells compared to normal cells were identified by DAVID (The Database for Annotation, Visualization and Integrated Discovery); finally, an interaction network of DEGs was constructed by string. A total of 1536 DEGs were screened, with 31 down-regulated and 1505 up-regulated genes. Response to wounding function and Toll-like receptor signaling pathway may involve in the development of OPLL. Genes, such as PDGFB, PRDX2 may involve in OPLL through response to wounding function. Toll-like receptor signaling pathway enriched genes such as TLR1, TLR5, and TLR7 may involve in spine cord injury in OPLL. PIK3R1 was the hub gene in the network of DEGs with the highest degree; INSR was one of the most closely related genes of it. OPLL related genes screened by microarray gene expression profiling and bioinformatics analysis may be helpful for elucidating the mechanism of OPLL. © 2013.
Trypsteen, Wim; Mohammadi, Pejman; Van Hecke, Clarissa; Mestdagh, Pieter; Lefever, Steve; Saeys, Yvan; De Bleser, Pieter; Vandesompele, Jo; Ciuffi, Angela; Vandekerckhove, Linos; De Spiegelaere, Ward
2016-10-26
Studying the effects of HIV infection on the host transcriptome has typically focused on protein-coding genes. However, recent advances in the field of RNA sequencing revealed that long non-coding RNAs (lncRNAs) add an extensive additional layer to the cell's molecular network. Here, we performed transcriptome profiling throughout a primary HIV infection in vitro to investigate lncRNA expression at the different HIV replication cycle processes (reverse transcription, integration and particle production). Subsequently, guilt-by-association, transcription factor and co-expression analysis were performed to infer biological roles for the lncRNAs identified in the HIV-host interplay. Many lncRNAs were suggested to play a role in mechanisms relying on proteasomal and ubiquitination pathways, apoptosis, DNA damage responses and cell cycle regulation. Through transcription factor binding analysis, we found that lncRNAs display a distinct transcriptional regulation profile as compared to protein coding mRNAs, suggesting that mRNAs and lncRNAs are independently modulated. In addition, we identified five differentially expressed lncRNA-mRNA pairs with mRNA involvement in HIV pathogenesis with possible cis regulatory lncRNAs that control nearby mRNA expression and function. Altogether, the present study demonstrates that lncRNAs add a new dimension to the HIV-host interplay and should be further investigated as they may represent targets for controlling HIV replication.
Sargeant, Tobias; Laperrière, David; Ismail, Houssam; Boucher, Geneviève; Rozendaal, Marieke; Lavallée, Vincent-Philippe; Ashton-Beaucage, Dariel; Wilhelm, Brian; Hébert, Josée; Hilton, Douglas J.
2017-01-01
Abstract Genome-wide transcriptome profiling has enabled non-supervised classification of tumours, revealing different sub-groups characterized by specific gene expression features. However, the biological significance of these subtypes remains for the most part unclear. We describe herein an interactive platform, Minimum Spanning Trees Inferred Clustering (MiSTIC), that integrates the direct visualization and comparison of the gene correlation structure between datasets, the analysis of the molecular causes underlying co-variations in gene expression in cancer samples, and the clinical annotation of tumour sets defined by the combined expression of selected biomarkers. We have used MiSTIC to highlight the roles of specific transcription factors in breast cancer subtype specification, to compare the aspects of tumour heterogeneity targeted by different prognostic signatures, and to highlight biomarker interactions in AML. A version of MiSTIC preloaded with datasets described herein can be accessed through a public web server (http://mistic.iric.ca); in addition, the MiSTIC software package can be obtained (github.com/iric-soft/MiSTIC) for local use with personalized datasets. PMID:28472340
Benitez, Cecil M.; Qu, Kun; Sugiyama, Takuya; Pauerstein, Philip T.; Liu, Yinghua; Tsai, Jennifer; Gu, Xueying; Ghodasara, Amar; Arda, H. Efsun; Zhang, Jiajing; Dekker, Joseph D.; Tucker, Haley O.; Chang, Howard Y.; Kim, Seung K.
2014-01-01
The regulatory logic underlying global transcriptional programs controlling development of visceral organs like the pancreas remains undiscovered. Here, we profiled gene expression in 12 purified populations of fetal and adult pancreatic epithelial cells representing crucial progenitor cell subsets, and their endocrine or exocrine progeny. Using probabilistic models to decode the general programs organizing gene expression, we identified co-expressed gene sets in cell subsets that revealed patterns and processes governing progenitor cell development, lineage specification, and endocrine cell maturation. Purification of Neurog3 mutant cells and module network analysis linked established regulators such as Neurog3 to unrecognized gene targets and roles in pancreas development. Iterative module network analysis nominated and prioritized transcriptional regulators, including diabetes risk genes. Functional validation of a subset of candidate regulators with corresponding mutant mice revealed that the transcription factors Etv1, Prdm16, Runx1t1 and Bcl11a are essential for pancreas development. Our integrated approach provides a unique framework for identifying regulatory genes and functional gene sets underlying pancreas development and associated diseases such as diabetes mellitus. PMID:25330008
NASA Astrophysics Data System (ADS)
Solano-Murillo, M.; Torres-Jardón, R.; Gutiérrez-López, W.; García-Espinosa, M.
2017-12-01
A prototype for the simultaneous sampling of VOC at different heights using a Tethered meteorological balloon was integrated and tested in a smog urban receptor site in southwest Mexico City. A selection of COV species measured at three different heights was used to estimate the chemical aging using the expression:Δt=[ln(ER1,2)-ln(VOC1/VOC2)]/[(K1-K2)[OH
Cardnell, Robert J.G.; Behrens, Carmen; Diao, Lixia; Fan, YouHong; Tang, Ximing; Tong, Pan; John D., Minna; Mills, Gordon B.; Heymach, John V.; Wistuba, Ignacio I.; Wang, Jing; Byers., Lauren A.
2015-01-01
Purpose Thyroid transcription factor-1 (TTF1) immunohistochemistry (IHC) is used clinically to differentiate primary lung adenocarcinomas (LUAD) from squamous lung cancers and metastatic adenocarcinomas from other primary sites. However, a subset of LUAD (15-20%) does not express TTF1 and TTF1-negative patients have worse clinical outcomes. As there are no established targeted agents with activity in TTF1-negative LUAD, we performed an integrated molecular analysis to identify potential therapeutic targets. Experimental Design Using two clinical LUAD cohorts (274 tumors), one from our institution (PROSPECT) and the TCGA, we interrogated proteomic profiles (by reverse-phase protein array (RPPA)), gene expression, and mutational data. Drug response data from 74 cell lines were used to validate potential therapeutic agents. Results Strong correlations were observed between TTF1 IHC and TTF1 measurements by RPPA (Rho=0.57, p<0.001) and gene expression (NKX2-1, Rho=0.61, p<0.001). Established driver mutations (e.g. BRAF and EGFR) were associated with high TTF1 expression. In contrast, TTF1-negative LUAD had a higher frequency of inactivating KEAP1 mutations (p=0.001). Proteomic profiling identified increased expression of DNA repair proteins (e.g., Chk1 and the DNA repair score) and suppressed PI3K/MAPK signaling among TTF1-negative tumors, with differences in total proteins confirmed at the mRNA level. Cell line analysis showed drugs targeting DNA repair to be more active in TTF1-low cell lines. Conclusions Combined genomic and proteomic analyses demonstrated infrequent alteration of validated lung cancer targets (including the absence of BRAF mutations in TTF1-negative LUAD), but identified novel potential targets for TTF1-negative LUAD includingKEAP1/Nrf2 and DNA repair pathways. PMID:25878335
SPARTA: Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis.
Johnson, Benjamin K; Scholz, Matthew B; Teal, Tracy K; Abramovitch, Robert B
2016-02-04
Many tools exist in the analysis of bacterial RNA sequencing (RNA-seq) transcriptional profiling experiments to identify differentially expressed genes between experimental conditions. Generally, the workflow includes quality control of reads, mapping to a reference, counting transcript abundance, and statistical tests for differentially expressed genes. In spite of the numerous tools developed for each component of an RNA-seq analysis workflow, easy-to-use bacterially oriented workflow applications to combine multiple tools and automate the process are lacking. With many tools to choose from for each step, the task of identifying a specific tool, adapting the input/output options to the specific use-case, and integrating the tools into a coherent analysis pipeline is not a trivial endeavor, particularly for microbiologists with limited bioinformatics experience. To make bacterial RNA-seq data analysis more accessible, we developed a Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis (SPARTA). SPARTA is a reference-based bacterial RNA-seq analysis workflow application for single-end Illumina reads. SPARTA is turnkey software that simplifies the process of analyzing RNA-seq data sets, making bacterial RNA-seq analysis a routine process that can be undertaken on a personal computer or in the classroom. The easy-to-install, complete workflow processes whole transcriptome shotgun sequencing data files by trimming reads and removing adapters, mapping reads to a reference, counting gene features, calculating differential gene expression, and, importantly, checking for potential batch effects within the data set. SPARTA outputs quality analysis reports, gene feature counts and differential gene expression tables and scatterplots. SPARTA provides an easy-to-use bacterial RNA-seq transcriptional profiling workflow to identify differentially expressed genes between experimental conditions. This software will enable microbiologists with limited bioinformatics experience to analyze their data and integrate next generation sequencing (NGS) technologies into the classroom. The SPARTA software and tutorial are available at sparta.readthedocs.org.
Design and evaluation of Actichip, a thematic microarray for the study of the actin cytoskeleton
Muller, Jean; Mehlen, André; Vetter, Guillaume; Yatskou, Mikalai; Muller, Arnaud; Chalmel, Frédéric; Poch, Olivier; Friederich, Evelyne; Vallar, Laurent
2007-01-01
Background The actin cytoskeleton plays a crucial role in supporting and regulating numerous cellular processes. Mutations or alterations in the expression levels affecting the actin cytoskeleton system or related regulatory mechanisms are often associated with complex diseases such as cancer. Understanding how qualitative or quantitative changes in expression of the set of actin cytoskeleton genes are integrated to control actin dynamics and organisation is currently a challenge and should provide insights in identifying potential targets for drug discovery. Here we report the development of a dedicated microarray, the Actichip, containing 60-mer oligonucleotide probes for 327 genes selected for transcriptome analysis of the human actin cytoskeleton. Results Genomic data and sequence analysis features were retrieved from GenBank and stored in an integrative database called Actinome. From these data, probes were designed using a home-made program (CADO4MI) allowing sequence refinement and improved probe specificity by combining the complementary information recovered from the UniGene and RefSeq databases. Actichip performance was analysed by hybridisation with RNAs extracted from epithelial MCF-7 cells and human skeletal muscle. Using thoroughly standardised procedures, we obtained microarray images with excellent quality resulting in high data reproducibility. Actichip displayed a large dynamic range extending over three logs with a limit of sensitivity between one and ten copies of transcript per cell. The array allowed accurate detection of small changes in gene expression and reliable classification of samples based on the expression profiles of tissue-specific genes. When compared to two other oligonucleotide microarray platforms, Actichip showed similar sensitivity and concordant expression ratios. Moreover, Actichip was able to discriminate the highly similar actin isoforms whereas the two other platforms did not. Conclusion Our data demonstrate that Actichip is a powerful alternative to commercial high density microarrays for cytoskeleton gene profiling in normal or pathological samples. Actichip is available upon request. PMID:17727702
Lin, Zhaomiao; Wang, Zunxin; Zhang, Xincheng; Li, Ganghua; Wang, Shaohua; Ding, Yanfeng
2017-01-01
Rice grain chalkiness is a highly complex trait involved in multiple metabolic pathways and controlled by polygenes and growth conditions. To uncover novel aspects of chalkiness formation, we performed an integrated profiling of gene activity in the developing grains of a notched-belly rice mutant. Using exhaustive tandem mass spectrometry-based shotgun proteomics and whole-genome RNA sequencing to generate a nearly complete catalog of expressed mRNAs and proteins, we reliably identified 38,476 transcripts and 3,840 proteins. Comparison between the translucent part and chalky part of the notched-belly grains resulted in only a few differently express genes (240) and differently express proteins (363), thus making it possible to focus on ‘core’ genes or common pathways. Several novel key pathways were identified as of relevance to chalkiness formation, in particular the shift of C and N metabolism, the down-regulation of ribosomal proteins and the resulting low abundance of storage proteins especially the 13 kDa prolamin subunit, and the suppressed photosynthetic capacity in the pericarp of the chalky part. Further, genes and proteins as transporters for carbohydrates, amino acid/peptides, proteins, lipids and inorganic ions showed an increasing expression pattern in the chalky part of the notched-belly grains. Similarly, transcripts and proteins of receptors for auxin, ABA, ethylene and brassinosteroid were also up-regulated. In summary, this joint analysis of transcript and protein profiles provides a comprehensive reference map of gene activity regarding the physiological state in the chalky endosperm. PMID:28158863
Dong, Pan; Xiong, Fangjie; Que, Yumei; Wang, Kai; Yu, Lihua; Li, Zhengguo; Ren, Maozhi
2015-01-01
Target of rapamycin (TOR) acts as a master regulator to control cell growth by integrating nutrient, energy, and growth factors in all eukaryotic species. TOR plays an evolutionarily conserved role in regulating the transcription of genes associated with anabolic and catabolic processes in Arabidopsis, but little is known about the functions of TOR in photosynthesis and phytohormone signaling, which are unique features of plants. In this study, AZD8055 (AZD) was screened as the strongest active-site TOR inhibitor (asTORi) in Arabidopsis compared with TORIN1 and KU63794 (KU). Gene expression profiles were evaluated using RNA-seq after treating Arabidopsis seedlings with AZD. More than three-fold differentially expressed genes (DEGs) were identified in AZD-treated plants relative to rapamycin-treated plants in previous studies. Most of the DEGs and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in cell wall elongation, ribosome biogenesis, and cell autophagy were common to both AZD- and rapamycin-treated samples, but AZD displayed much broader and more efficient inhibition of TOR compared with rapamycin. Importantly, the suppression of TOR by AZD resulted in remodeling of the expression profile of the genes associated with photosynthesis and various phytohormones, indicating that TOR plays a crucial role in modulating photosynthesis and phytohormone signaling in Arabidopsis. These newly identified DEGs expand the understanding of TOR signaling in plants. This study elucidates the novel functions of TOR in photosynthesis and phytohormone signaling and provides a platform to study the downstream targets of TOR in Arabidopsis. PMID:26442001
Chandran, Anil Kumar Nalini; Yoo, Yo-Han; Cao, Peijian; Sharma, Rita; Sharma, Manoj; Dardick, Christopher; Ronald, Pamela C; Jung, Ki-Hong
2016-12-01
Protein kinases catalyze the transfer of a phosphate moiety from a phosphate donor to the substrate molecule, thus playing critical roles in cell signaling and metabolism. Although plant genomes contain more than 1000 genes that encode kinases, knowledge is limited about the function of each of these kinases. A major obstacle that hinders progress towards kinase characterization is functional redundancy. To address this challenge, we previously developed the rice kinase database (RKD) that integrated omics-scale data within a phylogenetics context. An updated version of rice kinase database (RKD) that contains metadata derived from NCBI GEO expression datasets has been developed. RKD 2.0 facilitates in-depth transcriptomic analyses of kinase-encoding genes in diverse rice tissues and in response to biotic and abiotic stresses and hormone treatments. We identified 261 kinases specifically expressed in particular tissues, 130 that are significantly up- regulated in response to biotic stress, 296 in response to abiotic stress, and 260 in response to hormones. Based on this update and Pearson correlation coefficient (PCC) analysis, we estimated that 19 out of 26 genes characterized through loss-of-function studies confer dominant functions. These were selected because they either had paralogous members with PCC values of <0.5 or had no paralog. Compared with the previous version of RKD, RKD 2.0 enables more effective estimations of functional redundancy or dominance because it uses comprehensive expression profiles rather than individual profiles. The integrated analysis of RKD with PCC establishes a single platform for researchers to select rice kinases for functional analyses.
Dudal, S; Subramanian, K; Flandre, T; Law, W S; Lowe, P J; Skerjanec, A; Genin, J-C; Duval, M; Piequet, A; Cordier, A; Jarai, G; Van Heeke, G; Taplin, S; Krantz, C; Jones, S; Warren, A P; Brennan, F R; Sims, J; Lloyd, P
2015-01-01
QBP359 is an IgG1 human monoclonal antibody that binds with high affinity to human CCL21, a chemokine hypothesized to play a role in inflammatory disease conditions through activation of resident CCR7-expressing fibroblasts/myofibroblasts. The pharmacokinetics (PK) and pharmacodynamics (PD) of QBP359 in non-human primates were characterized through an integrated approach, combining PK, PD, immunogenicity, immunohistochemistry (IHC) and tissue profiling data from single- and multiple-dose experiments in cynomolgus monkeys. When compared with regular immunoglobulin typical kinetics, faster drug clearance was observed in serum following intravenous administration of 10 mg/kg and 50 mg/kg of QBP359. We have shown by means of PK/PD modeling that clearance of mAb-ligand complex is the most likely explanation for the rapid clearance of QBP359 in cynomolgus monkey. IHC and liquid chromatography mass spectrometry data suggested a high turnover and synthesis rate of CCL21 in tissues. Although lymphoid tissue was expected to accumulate drug due to the high levels of CCL21 present, bioavailability following subcutaneous administration in monkeys was 52%. In human disease states, where CCL21 expression is believed to be expressed at 10-fold higher concentrations compared with cynomolgus monkeys, the PK/PD model of QBP359 and its binding to CCL21 suggested that very large doses requiring frequent administration of mAb would be required to maintain suppression of CCL21 in the clinical setting. This highlights the difficulty in targeting soluble proteins with high synthesis rates.
Tsimakouridze, Elena V; Straume, Marty; Podobed, Peter S; Chin, Heather; LaMarre, Jonathan; Johnson, Ron; Antenos, Monica; Kirby, Gordon M; Mackay, Allison; Huether, Patsy; Simpson, Jeremy A; Sole, Michael; Gadal, Gerard; Martino, Tami A
2012-08-01
There is critical demand in contemporary medicine for gene expression markers in all areas of human disease, for early detection of disease, classification, prognosis, and response to therapy. The integrity of circadian gene expression underlies cardiovascular health and disease; however time-of-day profiling in heart disease has never been examined. We hypothesized that a time-of-day chronomic approach using samples collected across 24-h cycles and analyzed by microarrays and bioinformatics advances contemporary approaches, because it includes sleep-time and/or wake-time molecular responses. As proof of concept, we demonstrate the value of this approach in cardiovascular disease using a murine Transverse Aortic Constriction (TAC) model of pressure overload-induced cardiac hypertrophy in mice. First, microarrays and a novel algorithm termed DeltaGene were used to identify time-of-day differences in gene expression in cardiac hypertrophy 8 wks post-TAC. The top 300 candidates were further analyzed using knowledge-based platforms, paring the list to 20 candidates, which were then validated by real-time polymerase chain reaction (RTPCR). Next, we tested whether the time-of-day gene expression profiles could be indicative of disease progression by comparing the 1- vs. 8-wk TAC. Lastly, since protein expression is functionally relevant, we monitored time-of-day cycling for the analogous cardiac proteins. This approach is generally applicable and can lead to new understanding of disease.
Integrated Genomic and Epigenomic Analysis of Breast Cancer Brain Metastasis
Salhia, Bodour; Kiefer, Jeff; Ross, Julianna T. D.; Metapally, Raghu; Martinez, Rae Anne; Johnson, Kyle N.; DiPerna, Danielle M.; Paquette, Kimberly M.; Jung, Sungwon; Nasser, Sara; Wallstrom, Garrick; Tembe, Waibhav; Baker, Angela; Carpten, John; Resau, Jim; Ryken, Timothy; Sibenaller, Zita; Petricoin, Emanuel F.; Liotta, Lance A.; Ramanathan, Ramesh K.; Berens, Michael E.; Tran, Nhan L.
2014-01-01
The brain is a common site of metastatic disease in patients with breast cancer, which has few therapeutic options and dismal outcomes. The purpose of our study was to identify common and rare events that underlie breast cancer brain metastasis. We performed deep genomic profiling, which integrated gene copy number, gene expression and DNA methylation datasets on a collection of breast brain metastases. We identified frequent large chromosomal gains in 1q, 5p, 8q, 11q, and 20q and frequent broad-level deletions involving 8p, 17p, 21p and Xq. Frequently amplified and overexpressed genes included ATAD2, BRAF, DERL1, DNMTRB and NEK2A. The ATM, CRYAB and HSPB2 genes were commonly deleted and underexpressed. Knowledge mining revealed enrichment in cell cycle and G2/M transition pathways, which contained AURKA, AURKB and FOXM1. Using the PAM50 breast cancer intrinsic classifier, Luminal B, Her2+/ER negative, and basal-like tumors were identified as the most commonly represented breast cancer subtypes in our brain metastasis cohort. While overall methylation levels were increased in breast cancer brain metastasis, basal-like brain metastases were associated with significantly lower levels of methylation. Integrating DNA methylation data with gene expression revealed defects in cell migration and adhesion due to hypermethylation and downregulation of PENK, EDN3, and ITGAM. Hypomethylation and upregulation of KRT8 likely affects adhesion and permeability. Genomic and epigenomic profiling of breast brain metastasis has provided insight into the somatic events underlying this disease, which have potential in forming the basis of future therapeutic strategies. PMID:24489661
High-resolution gene expression data from blastoderm embryos of the scuttle fly Megaselia abdita
Wotton, Karl R; Jiménez-Guri, Eva; Crombach, Anton; Cicin-Sain, Damjan; Jaeger, Johannes
2015-01-01
Gap genes are involved in segment determination during early development in dipteran insects (flies, midges, and mosquitoes). We carried out a systematic quantitative comparative analysis of the gap gene network across different dipteran species. Our work provides mechanistic insights into the evolution of this pattern-forming network. As a central component of our project, we created a high-resolution quantitative spatio-temporal data set of gap and maternal co-ordinate gene expression in the blastoderm embryo of the non-drosophilid scuttle fly, Megaselia abdita. Our data include expression patterns in both wild-type and RNAi-treated embryos. The data—covering 10 genes, 10 time points, and over 1,000 individual embryos—consist of original embryo images, quantified expression profiles, extracted positions of expression boundaries, and integrated expression patterns, plus metadata and intermediate processing steps. These data provide a valuable resource for researchers interested in the comparative study of gene regulatory networks and pattern formation, an essential step towards a more quantitative and mechanistic understanding of developmental evolution. PMID:25977812
Digital signaling decouples activation probability and population heterogeneity.
Kellogg, Ryan A; Tian, Chengzhe; Lipniacki, Tomasz; Quake, Stephen R; Tay, Savaş
2015-10-21
Digital signaling enhances robustness of cellular decisions in noisy environments, but it is unclear how digital systems transmit temporal information about a stimulus. To understand how temporal input information is encoded and decoded by the NF-κB system, we studied transcription factor dynamics and gene regulation under dose- and duration-modulated inflammatory inputs. Mathematical modeling predicted and microfluidic single-cell experiments confirmed that integral of the stimulus (or area, concentration × duration) controls the fraction of cells that activate NF-κB in the population. However, stimulus temporal profile determined NF-κB dynamics, cell-to-cell variability, and gene expression phenotype. A sustained, weak stimulation lead to heterogeneous activation and delayed timing that is transmitted to gene expression. In contrast, a transient, strong stimulus with the same area caused rapid and uniform dynamics. These results show that digital NF-κB signaling enables multidimensional control of cellular phenotype via input profile, allowing parallel and independent control of single-cell activation probability and population heterogeneity.
The Cross-Entropy Based Multi-Filter Ensemble Method for Gene Selection.
Sun, Yingqiang; Lu, Chengbo; Li, Xiaobo
2018-05-17
The gene expression profile has the characteristics of a high dimension, low sample, and continuous type, and it is a great challenge to use gene expression profile data for the classification of tumor samples. This paper proposes a cross-entropy based multi-filter ensemble (CEMFE) method for microarray data classification. Firstly, multiple filters are used to select the microarray data in order to obtain a plurality of the pre-selected feature subsets with a different classification ability. The top N genes with the highest rank of each subset are integrated so as to form a new data set. Secondly, the cross-entropy algorithm is used to remove the redundant data in the data set. Finally, the wrapper method, which is based on forward feature selection, is used to select the best feature subset. The experimental results show that the proposed method is more efficient than other gene selection methods and that it can achieve a higher classification accuracy under fewer characteristic genes.
Rue-Albrecht, Kévin; McGettigan, Paul A; Hernández, Belinda; Nalpas, Nicolas C; Magee, David A; Parnell, Andrew C; Gordon, Stephen V; MacHugh, David E
2016-03-11
Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of differential expression statistics has been used to refine gene set enrichment analyses, such approaches are typically limited to single gene lists resulting from simple two-group comparisons or time-series analyses. In contrast, functional class scoring and machine learning approaches provide powerful alternative methods to leverage molecular measurements for pathway analyses, and to compare continuous and multi-level categorical factors. We introduce GOexpress, a software package for scoring and summarising the capacity of gene ontology features to simultaneously classify samples from multiple experimental groups. GOexpress integrates normalised gene expression data (e.g., from microarray and RNA-seq experiments) and phenotypic information of individual samples with gene ontology annotations to derive a ranking of genes and gene ontology terms using a supervised learning approach. The default random forest algorithm allows interactions between all experimental factors, and competitive scoring of expressed genes to evaluate their relative importance in classifying predefined groups of samples. GOexpress enables rapid identification and visualisation of ontology-related gene panels that robustly classify groups of samples and supports both categorical (e.g., infection status, treatment) and continuous (e.g., time-series, drug concentrations) experimental factors. The use of standard Bioconductor extension packages and publicly available gene ontology annotations facilitates straightforward integration of GOexpress within existing computational biology pipelines.
Farber, Charles R; van Nas, Atila; Ghazalpour, Anatole; Aten, Jason E; Doss, Sudheer; Sos, Brandon; Schadt, Eric E; Ingram-Drake, Leslie; Davis, Richard C; Horvath, Steve; Smith, Desmond J; Drake, Thomas A; Lusis, Aldons J
2009-01-01
Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification. PMID:18767929
Wang, Lili; Fan, Jean; Francis, Joshua M.; Georghiou, George; Hergert, Sarah; Li, Shuqiang; Gambe, Rutendo; Zhou, Chensheng W.; Yang, Chunxiao; Xiao, Sheng; Cin, Paola Dal; Bowden, Michaela; Kotliar, Dylan; Shukla, Sachet A.; Brown, Jennifer R.; Neuberg, Donna; Alessi, Dario R.; Zhang, Cheng-Zhong; Kharchenko, Peter V.; Livak, Kenneth J.; Wu, Catherine J.
2017-01-01
Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype–phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy. PMID:28679620
An integrated mRNA and microRNA expression signature for glioblastoma multiforme prognosis.
Xiong, Jie; Bing, Zhitong; Su, Yanlin; Deng, Defeng; Peng, Xiaoning
2014-01-01
Although patients with Glioblastoma multiforme (GBM) have grave prognosis, significant variability in patient outcome is observed. The objective of this study is to identify a molecular signature for GBM prognosis. We subjected 355 mRNA and microRNA expression profiles to elastic net-regulated Cox regression for identification of an integrated RNA signature for GBM prognosis. A prognostic index (PI) was generated for patient stratification. Survival comparison was conducted by Kaplan-Meier method and a general multivariate Cox regression procedure was applied to evaluate the independence of the PI. The abilities and efficiencies of signatures to predict GBM patient outcome was assessed and compared by the area under the curve (AUC) of the receiver-operator characteristic (ROC). An integrated RNA prognostic signature consisted by 4 protective mRNAs, 12 risky mRNAs, and 1 risky microRNA was identified. Decreased survival was associated with being in the high-risk group (hazard ratio = 2.864, P<0.0001). The prognostic value of the integrated signature was validated in five independent GBM expression datasets (n = 201, hazard ratio = 2.453, P<0.0001). The PI outperformed the known clinical factors, mRNA-only, and miRNA-only prognostic signatures for GBM prognosis (area under the ROC curve for the integrated RNA, mRNA-only, and miRNA-only signatures were 0.828, 0.742, and 0.757 at 3 years of overall survival, respectively, P<0.0001 by permutation test). We describe the first, to our knowledge, robust transcriptome-based integrated RNA signature that improves the current GBM prognosis based on clinical variables, mRNA-only, and miRNA-only signatures.
An Integrated mRNA and microRNA Expression Signature for Glioblastoma Multiforme Prognosis
Xiong, Jie; Bing, Zhitong; Su, Yanlin; Deng, Defeng; Peng, Xiaoning
2014-01-01
Although patients with Glioblastoma multiforme (GBM) have grave prognosis, significant variability in patient outcome is observed. The objective of this study is to identify a molecular signature for GBM prognosis. We subjected 355 mRNA and microRNA expression profiles to elastic net-regulated Cox regression for identification of an integrated RNA signature for GBM prognosis. A prognostic index (PI) was generated for patient stratification. Survival comparison was conducted by Kaplan-Meier method and a general multivariate Cox regression procedure was applied to evaluate the independence of the PI. The abilities and efficiencies of signatures to predict GBM patient outcome was assessed and compared by the area under the curve (AUC) of the receiver-operator characteristic (ROC). An integrated RNA prognostic signature consisted by 4 protective mRNAs, 12 risky mRNAs, and 1 risky microRNA was identified. Decreased survival was associated with being in the high-risk group (hazard ratio = 2.864, P<0.0001). The prognostic value of the integrated signature was validated in five independent GBM expression datasets (n = 201, hazard ratio = 2.453, P<0.0001). The PI outperformed the known clinical factors, mRNA-only, and miRNA-only prognostic signatures for GBM prognosis (area under the ROC curve for the integrated RNA, mRNA-only, and miRNA-only signatures were 0.828, 0.742, and 0.757 at 3 years of overall survival, respectively, P<0.0001 by permutation test). We describe the first, to our knowledge, robust transcriptome-based integrated RNA signature that improves the current GBM prognosis based on clinical variables, mRNA-only, and miRNA-only signatures. PMID:24871302
Qiao, Yan; Zhang, Jinjin; Zhang, Jinwen; Wang, Zhiwei; Ran, An; Guo, Haixia; Wang, Di; Zhang, Junlian
2017-02-01
Light is a major environmental factor that affects metabolic pathways and stimulates the production of secondary metabolites in potato. However, adaptive changes in potato metabolic pathways and physiological functions triggered by light are partly explained by gene expression changes. Regulation of secondary metabolic pathways in potato has been extensively studied at transcriptional level, but little is known about the mechanisms of post-transcriptional regulation by miRNAs. To identify light-responsive miRNAs/mRNAs and construct putative metabolism pathways regulated by the miRNA-mRNA pairs, an integrated omics (sRNAome and transcriptome) analysis was performed to potato under light stimulus. A total of 31 and 48 miRNAs were identified to be differentially expressed in the leaves and tubers, respectively. Among the DEGs, 1353 genes in the leaves and 1841 genes in the tubers were upregulated, while 1595 genes in the leaves and 897 genes in the tubers were downregulated by light. Mapman enrichment analyses showed that genes related to MVA pathway, alkaloids-like, phenylpropanoids, flavonoids, and carotenoids metabolism were significantly upregulated, while genes associated with major CHO metabolism were repressed in the leaves and tubers. Integrated miRNA and mRNA profiles revealed that light-responsive miRNAs are important regulators in alkaloids metabolism, UMP salvage, lipid biosynthesis, and cellulose catabolism. Moreover, several miRNAs may participate in glycoalkaloids metabolism via JA signaling pathway, UDP-glucose biosynthesis and hydroxylation reaction. This study provides a global view of miRNA and mRNA expression profiles in potato response to light, our results suggest that miRNAs might play important roles in secondary metabolic pathways, especially in glycoalkaloid biosynthesis. The findings will enlighten us on the genetic regulation of secondary metabolite pathways and pave the way for future application of genetically engineered potato.
Cañas, Rafael A.; Canales, Javier; Muñoz-Hernández, Carmen; Granados, Jose M.; Ávila, Concepción; García-Martín, María L.; Cánovas, Francisco M.
2015-01-01
Conifers include long-lived evergreen trees of great economic and ecological importance, including pines and spruces. During their long lives conifers must respond to seasonal environmental changes, adapt to unpredictable environmental stresses, and co-ordinate their adaptive adjustments with internal developmental programmes. To gain insights into these responses, we examined metabolite and transcriptomic profiles of needles from naturally growing 25-year-old maritime pine (Pinus pinaster L. Aiton) trees over a year. The effect of environmental parameters such as temperature and rain on needle development were studied. Our results show that seasonal changes in the metabolite profiles were mainly affected by the needles’ age and acclimation for winter, but changes in transcript profiles were mainly dependent on climatic factors. The relative abundance of most transcripts correlated well with temperature, particularly for genes involved in photosynthesis or winter acclimation. Gene network analysis revealed relationships between 14 co-expressed gene modules and development and adaptation to environmental stimuli. Novel Myb transcription factors were identified as candidate regulators during needle development. Our systems-based analysis provides integrated data of the seasonal regulation of maritime pine growth, opening new perspectives for understanding the complex regulatory mechanisms underlying conifers’ adaptive responses. Taken together, our results suggest that the environment regulates the transcriptome for fine tuning of the metabolome during development. PMID:25873654
Sadanandam, Anguraj; Wullschleger, Stephan; Lyssiotis, Costas A.; Grötzinger, Carsten; Barbi, Stefano; Bersani, Samantha; Körner, Jan; Wafy, Ismael; Mafficini, Andrea; Lawlor, Rita T.; Simbolo, Michele; Asara, John M.; Bläker, Hendrik; Cantley, Lewis C.; Wiedenmann, Bertram; Scarpa, Aldo; Hanahan, Douglas
2016-01-01
Seeking to assess the representative and instructive value of an engineered mouse model of pancreatic neuroendocrine tumors (PanNET) for its cognate human cancer, we profiled and compared mRNA and miRNA transcriptomes of tumors from both. Mouse PanNET tumors could be classified into two distinctive subtypes, well-differentiated islet/insulinoma tumors (IT) and poorly differentiated tumors associated with liver metastases, dubbed metastasis-like primary (MLP). Human PanNETs were independently classified into these same two subtypes, along with a third, specific gene mutation–enriched subtype. The MLP subtypes in human and mouse were similar to liver metastases in terms of miRNA and mRNA transcriptome profiles and signature genes. The human/mouse MLP subtypes also similarly expressed genes known to regulate early pancreas development, whereas the IT subtypes expressed genes characteristic of mature islet cells, suggesting different tumorigenesis pathways. In addition, these subtypes exhibit distinct metabolic profiles marked by differential pyruvate metabolism, substantiating the significance of their separate identities. SIGNIFICANCE This study involves a comprehensive cross-species integrated analysis of multi-omics profiles and histology to stratify PanNETs into subtypes with distinctive characteristics. We provide support for the RIP1-TAG2 mouse model as representative of its cognate human cancer with prospects to better understand PanNET heterogeneity and consider future applications of personalized cancer therapy. PMID:26446169
Sadanandam, Anguraj; Wullschleger, Stephan; Lyssiotis, Costas A; Grötzinger, Carsten; Barbi, Stefano; Bersani, Samantha; Körner, Jan; Wafy, Ismael; Mafficini, Andrea; Lawlor, Rita T; Simbolo, Michele; Asara, John M; Bläker, Hendrik; Cantley, Lewis C; Wiedenmann, Bertram; Scarpa, Aldo; Hanahan, Douglas
2015-12-01
Seeking to assess the representative and instructive value of an engineered mouse model of pancreatic neuroendocrine tumors (PanNET) for its cognate human cancer, we profiled and compared mRNA and miRNA transcriptomes of tumors from both. Mouse PanNET tumors could be classified into two distinctive subtypes, well-differentiated islet/insulinoma tumors (IT) and poorly differentiated tumors associated with liver metastases, dubbed metastasis-like primary (MLP). Human PanNETs were independently classified into these same two subtypes, along with a third, specific gene mutation-enriched subtype. The MLP subtypes in human and mouse were similar to liver metastases in terms of miRNA and mRNA transcriptome profiles and signature genes. The human/mouse MLP subtypes also similarly expressed genes known to regulate early pancreas development, whereas the IT subtypes expressed genes characteristic of mature islet cells, suggesting different tumorigenesis pathways. In addition, these subtypes exhibit distinct metabolic profiles marked by differential pyruvate metabolism, substantiating the significance of their separate identities. This study involves a comprehensive cross-species integrated analysis of multi-omics profiles and histology to stratify PanNETs into subtypes with distinctive characteristics. We provide support for the RIP1-TAG2 mouse model as representative of its cognate human cancer with prospects to better understand PanNET heterogeneity and consider future applications of personalized cancer therapy. ©2015 American Association for Cancer Research.
Farag, Mohamed A.; Deavours, Bettina E.; de Fátima, Ângelo; Naoumkina, Marina; Dixon, Richard A.; Sumner, Lloyd W.
2009-01-01
Metabolic profiling of elicited barrel medic (Medicago truncatula) cell cultures using high-performance liquid chromatography coupled to photodiode and mass spectrometry detection revealed the accumulation of the aurone hispidol (6-hydroxy-2-[(4-hydroxyphenyl)methylidene]-1-benzofuran-3-one) as a major response to yeast elicitor. Parallel, large-scale transcriptome profiling indicated that three peroxidases, MtPRX1, MtPRX2, and MtPRX3, were coordinately induced with the accumulation of hispidol. MtPRX1 and MtPRX2 exhibited aurone synthase activity based upon in vitro substrate specificity and product profiles of recombinant proteins expressed in Escherichia coli. Hispidol possessed significant antifungal activity relative to other M. truncatula phenylpropanoids tested but has not been reported in this species before and was not found in differentiated roots in which high levels of the peroxidase transcripts accumulated. We propose that hispidol is formed in cell cultures by metabolic spillover when the pool of its precursor, isoliquiritigenin, builds up as a result of an imbalance between the upstream and downstream segments of the phenylpropanoid pathway, reflecting the plasticity of plant secondary metabolism. The results illustrate that integration of metabolomics and transcriptomics in genetically reprogrammed plant cell cultures is a powerful approach for the discovery of novel bioactive secondary metabolites and the mechanisms underlying their generation. PMID:19571306
Proteomic Analysis of Hair Follicles
NASA Astrophysics Data System (ADS)
Ishioka, Noriaki; Terada, Masahiro; Yamada, Shin; Seki, Masaya; Takahashi, Rika; Majima, Hideyuki J.; Higashibata, Akira; Mukai, Chiaki
2013-02-01
Hair root cells actively divide in a hair follicle, and they sensitively reflect physical conditions. By analyzing the human hair, we can know stress levels on the human body and metabolic conditions caused by microgravity environment and cosmic radiation. The Japan Aerospace Exploration Agency (JAXA) has initiated a human research study to investigate the effects of long-term space flight on gene expression and mineral metabolism by analyzing hair samples of astronauts who stayed in the International Space Station (ISS) for 6 months. During long-term flights, the physiological effects on astronauts include muscle atrophy and bone calcium loss. Furthermore, radiation and psychological effects are important issue to consider. Therefore, an understanding of the effects of the space environment is important for developing countermeasures against the effects experienced by astronauts. In this experiment, we identify functionally important target proteins that integrate transcriptome, mineral metabolism and proteome profiles from human hair. To compare the protein expression data with the gene expression data from hair roots, we developed the protein processing method. We extracted the protein from five strands of hair using ISOGEN reagents. Then, these extracted proteins were analyzed by LC-MS/MS. These collected profiles will give us useful physiological information to examine the effect of space flight.
Wei, Jiankai; Zhang, Xiaojun; Yu, Yang; Huang, Hao; Li, Fuhua; Xiang, Jianhai
2014-01-01
Penaeid shrimp has a distinctive metamorphosis stage during early development. Although morphological and biochemical studies about this ontogeny have been developed for decades, researches on gene expression level are still scarce. In this study, we have investigated the transcriptomes of five continuous developmental stages in Pacific white shrimp (Litopenaeus vannamei) with high throughput Illumina sequencing technology. The reads were assembled and clustered into 66,815 unigenes, of which 32,398 have putative homologues in nr database, 14,981 have been classified into diverse functional categories by Gene Ontology (GO) annotation and 26,257 have been associated with 255 pathways by KEGG pathway mapping. Meanwhile, the differentially expressed genes (DEGs) between adjacent developmental stages were identified and gene expression patterns were clustered. By GO term enrichment analysis, KEGG pathway enrichment analysis and functional gene profiling, the physiological changes during shrimp metamorphosis could be better understood, especially histogenesis, diet transition, muscle development and exoskeleton reconstruction. In conclusion, this is the first study that characterized the integrated transcriptomic profiles during early development of penaeid shrimp, and these findings will serve as significant references for shrimp developmental biology and aquaculture research. PMID:25197823
Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis
Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando
2008-01-01
Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433
Technical variables in high-throughput miRNA expression profiling: much work remains to be done.
Nelson, Peter T; Wang, Wang-Xia; Wilfred, Bernard R; Tang, Guiliang
2008-11-01
MicroRNA (miRNA) gene expression profiling has provided important insights into plant and animal biology. However, there has not been ample published work about pitfalls associated with technical parameters in miRNA gene expression profiling. One source of pertinent information about technical variables in gene expression profiling is the separate and more well-established literature regarding mRNA expression profiling. However, many aspects of miRNA biochemistry are unique. For example, the cellular processing and compartmentation of miRNAs, the differential stability of specific miRNAs, and aspects of global miRNA expression regulation require specific consideration. Additional possible sources of systematic bias in miRNA expression studies include the differential impact of pre-analytical variables, substrate specificity of nucleic acid processing enzymes used in labeling and amplification, and issues regarding new miRNA discovery and annotation. We conclude that greater focus on technical parameters is required to bolster the validity, reliability, and cultural credibility of miRNA gene expression profiling studies.
DOE Office of Scientific and Technical Information (OSTI.GOV)
He, Fei; Maslov, Sergei; Yoo, Shinjae
Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset andmore » found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.« less
He, Fei; Maslov, Sergei; Yoo, Shinjae; ...
2016-05-25
Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset andmore » found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.« less
Han, Junwei; Shang, Desi; Zhang, Yunpeng; Zhang, Wei; Yao, Qianlan; Han, Lei; Xu, Yanjun; Yan, Wei; Bao, Zhaoshi; You, Gan; Jiang, Tao; Kang, Chunsheng; Li, Xia
2014-01-01
The prognosis of glioma patients is usually poor, especially in patients with glioblastoma (World Health Organization (WHO) grade IV). The regulatory functions of microRNA (miRNA) on genes have important implications in glioma cell survival. However, there are not many studies that have investigated glioma survival by integrating miRNAs and genes while also considering pathway structure. In this study, we performed sample-matched miRNA and mRNA expression profilings to systematically analyze glioma patient survival. During this analytical process, we developed pathway-based random walk to identify a glioma core miRNA-gene module, simultaneously considering pathway structure information and multi-level involvement of miRNAs and genes. The core miRNA-gene module we identified was comprised of four apparent sub-modules; all four sub-modules displayed a significant correlation with patient survival in the testing set (P-values≤0.001). Notably, one sub-module that consisted of 6 miRNAs and 26 genes also correlated with survival time in the high-grade subgroup (WHO grade III and IV), P-value = 0.0062. Furthermore, the 26-gene expression signature from this sub-module had robust predictive power in four independent, publicly available glioma datasets. Our findings suggested that the expression signatures, which were identified by integration of miRNA and gene level, were closely associated with overall survival among the glioma patients with various grades. PMID:24809850
Luo, Qing; Li, Xue; Xu, Chuxin; Zeng, Lulu; Ye, Jianqing; Guo, Yang; Huang, Zikun; Li, Junming
2018-03-01
Thousands of long noncoding RNAs (lncRNAs) have been reported and represent an important subset of pervasive genes associated with a broad range of biological functions. Abnormal expression levels of lncRNAs have been demonstrated in multiple types of human disease. However, the role of lncRNAs in systemic lupus erythematosus (SLE) remains poorly understood. In the present study, the expression patterns of lncRNAs and messenger RNAs (mRNAs) were investigated in peripheral blood mononuclear cells (PBMCs) in SLE using Human lncRNA Array v3.0 (8x60 K; Arraystar, Inc., Rockville, MD, USA). The microarray results indicated that 8,868 lncRNAs (3,657 upregulated and 5,211 downregulated) and 6,876 mRNAs (2,862 upregulated and 4,014 downregulated) were highly differentially expressed in SLE samples compared with the healthy group. Gene ontology (GO) analysis of lncRNA target prediction indicated the presence of 474 matched lncRNA‑mRNA pairs for 293 differentially expressed lncRNAs (fold change, ≥3.0) and 381 differentially expressed mRNAs (fold change, ≥3.0). The most enriched pathways were 'Transcriptional misregulation in cancer' and 'Valine, leucine and isoleucine degradation'. Furthermore, reverse transcription‑quantitative polymerase chain reaction data verified six abnormal lncRNAs and mRNAs in SLE. The results indicate that the lncRNA expression profile in SLE was significantly changed. In addition, a range of SLE‑associated lncRNAs were identified. Thus, the present results provide important insights regarding lncRNAs in the pathogenesis of SLE.
Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd
Wang, Zichen; Monteiro, Caroline D.; Jagodnik, Kathleen M.; Fernandez, Nicolas F.; Gundersen, Gregory W.; Rouillard, Andrew D.; Jenkins, Sherry L.; Feldmann, Axel S.; Hu, Kevin S.; McDermott, Michael G.; Duan, Qiaonan; Clark, Neil R.; Jones, Matthew R.; Kou, Yan; Goff, Troy; Woodland, Holly; Amaral, Fabio M R.; Szeto, Gregory L.; Fuchs, Oliver; Schüssler-Fiorenza Rose, Sophia M.; Sharma, Shvetank; Schwartz, Uwe; Bausela, Xabier Bengoetxea; Szymkiewicz, Maciej; Maroulis, Vasileios; Salykin, Anton; Barra, Carolina M.; Kruth, Candice D.; Bongio, Nicholas J.; Mathur, Vaibhav; Todoric, Radmila D; Rubin, Udi E.; Malatras, Apostolos; Fulp, Carl T.; Galindo, John A.; Motiejunaite, Ruta; Jüschke, Christoph; Dishuck, Philip C.; Lahl, Katharina; Jafari, Mohieddin; Aibar, Sara; Zaravinos, Apostolos; Steenhuizen, Linda H.; Allison, Lindsey R.; Gamallo, Pablo; de Andres Segura, Fernando; Dae Devlin, Tyler; Pérez-García, Vicente; Ma'ayan, Avi
2016-01-01
Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization. PMID:27667448
Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd.
Wang, Zichen; Monteiro, Caroline D; Jagodnik, Kathleen M; Fernandez, Nicolas F; Gundersen, Gregory W; Rouillard, Andrew D; Jenkins, Sherry L; Feldmann, Axel S; Hu, Kevin S; McDermott, Michael G; Duan, Qiaonan; Clark, Neil R; Jones, Matthew R; Kou, Yan; Goff, Troy; Woodland, Holly; Amaral, Fabio M R; Szeto, Gregory L; Fuchs, Oliver; Schüssler-Fiorenza Rose, Sophia M; Sharma, Shvetank; Schwartz, Uwe; Bausela, Xabier Bengoetxea; Szymkiewicz, Maciej; Maroulis, Vasileios; Salykin, Anton; Barra, Carolina M; Kruth, Candice D; Bongio, Nicholas J; Mathur, Vaibhav; Todoric, Radmila D; Rubin, Udi E; Malatras, Apostolos; Fulp, Carl T; Galindo, John A; Motiejunaite, Ruta; Jüschke, Christoph; Dishuck, Philip C; Lahl, Katharina; Jafari, Mohieddin; Aibar, Sara; Zaravinos, Apostolos; Steenhuizen, Linda H; Allison, Lindsey R; Gamallo, Pablo; de Andres Segura, Fernando; Dae Devlin, Tyler; Pérez-García, Vicente; Ma'ayan, Avi
2016-09-26
Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.
Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data
Racle, Julien; de Jonge, Kaat; Baumgaertner, Petra; Speiser, Daniel E
2017-01-01
Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org). PMID:29130882
Spatial reconstruction of single-cell gene expression data.
Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv
2015-05-01
Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.
2014-01-01
Background Clinically useful biomarkers for patient stratification and monitoring of disease progression and drug response are in big demand in drug development and for addressing potential safety concerns. Many diseases influence the frequency and phenotype of cells found in the peripheral blood and the transcriptome of blood cells. Changes in cell type composition influence whole blood gene expression analysis results and thus the discovery of true transcript level changes remains a challenge. We propose a robust and reproducible procedure, which includes whole transcriptome gene expression profiling of major subsets of immune cell cells directly sorted from whole blood. Methods Target cells were enriched using magnetic microbeads and an autoMACS® Pro Separator (Miltenyi Biotec). Flow cytometric analysis for purity was performed before and after magnetic cell sorting. Total RNA was hybridized on HGU133 Plus 2.0 expression microarrays (Affymetrix, USA). CEL files signal intensity values were condensed using RMA and a custom CDF file (EntrezGene-based). Results Positive selection by use of MACS® Technology coupled to transcriptomics was assessed for eight different peripheral blood cell types, CD14+ monocytes, CD3+, CD4+, or CD8+ T cells, CD15+ granulocytes, CD19+ B cells, CD56+ NK cells, and CD45+ pan leukocytes. RNA quality from enriched cells was above a RIN of eight. GeneChip analysis confirmed cell type specific transcriptome profiles. Storing whole blood collected in an EDTA Vacutainer® tube at 4°C followed by MACS does not activate sorted cells. Gene expression analysis supports cell enrichment measurements by MACS. Conclusions The proposed workflow generates reproducible cell-type specific transcriptome data which can be translated to clinical settings and used to identify clinically relevant gene expression biomarkers from whole blood samples. This procedure enables the integration of transcriptomics of relevant immune cell subsets sorted directly from whole blood in clinical trial protocols. PMID:25984272
van de Bunt, Martijn; Lako, Majlinda; Barrett, Amy; Gloyn, Anna L.; Hansson, Mattias; McCarthy, Mark I.; Honoré, Christian
2016-01-01
ABSTRACT Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at 6 stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from 2 donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs = 14.2, p-value = 4.9 × 10−5) and the pancreatic agenesis gene GATA6 (log2 FC = 12.1, p-value = 8.6 × 10−5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to our endocrine pancreas-like cells (log2 FC = 5.5, p-value = 2.0 × 10−12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. “insulin secretion”; odds ratio = 4.2, p-value = 1.9 × 10−3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis. PMID:27246810
Li, Qing; Hegge, Raquel; Bridges, Phillip J; Matthews, James C
2017-01-01
Consumption of ergot alkaloid-containing tall fescue grass impairs several metabolic, vascular, growth, and reproductive processes in cattle, collectively producing a clinical condition known as "fescue toxicosis." Despite the apparent association between pituitary function and these physiological parameters, including depressed serum prolactin; no reports describe the effect of fescue toxicosis on pituitary genomic expression profiles. To identify candidate regulatory mechanisms, we compared the global and selected targeted mRNA expression patterns of pituitaries collected from beef steers that had been randomly assigned to undergo summer-long grazing (89 to 105 d) of a high-toxic endophyte-infected tall fescue pasture (HE; 0.746 μg/g ergot alkaloids; 5.7 ha; n = 10; BW = 267 ± 14.5 kg) or a low-toxic endophyte tall fescue-mixed pasture (LE; 0.023 μg/g ergot alkaloids; 5.7 ha; n = 9; BW = 266 ± 10.9 kg). As previously reported, in the HE steers, serum prolactin and body weights decreased and a potential for hepatic gluconeogenesis from amino acid-derived carbons increased. In this manuscript, we report that the pituitaries of HE steers had 542 differentially expressed genes (P < 0.001, false discovery rate ≤ 4.8%), and the pattern of altered gene expression was dependent (P < 0.001) on treatment. Integrated Pathway Analysis revealed that canonical pathways central to prolactin production, secretion, or signaling were affected, in addition to those related to corticotropin-releasing hormone signaling, melanocyte development, and pigmentation signaling. Targeted RT-PCR analysis corroborated these findings, including decreased (P < 0.05) expression of DRD2, PRL, POU1F1, GAL, and VIP and that of POMC and PCSK1, respectively. Canonical pathway analysis identified HE-dependent alteration in signaling of additional pituitary-derived hormones, including growth hormone and GnRH. We conclude that consumption of endophyte-infected tall fescue alters the pituitary transcriptome profiles of steers in a manner consistent with their negatively affected physiological parameters.
L1000CDS2: LINCS L1000 characteristic direction signatures search engine.
Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma'ayan, Avi
2016-01-01
The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS 2 . The L1000CDS 2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS 2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS 2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS 2 , we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS 2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS 2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource.
Protein expression profiling in head fragments during planarian regeneration after amputation.
Chen, Xiaoguang; Xu, Cunshuan
2015-04-01
Following amputation, a planarian tail fragment can regrow into a complete organism including a well-organized brain within about 2-3 weeks, thus restoring the structure and function to presurgical levels. Despite the enormous potential of these animals for regenerative medicine, our understanding of the exact mechanism of planarian regeneration is incomplete. To better understand the molecular nature of planarian head regeneration, we applied two-dimensional electrophoresis (2-DE)/matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF)/time-of-flight mass spectrometry (TOF MS) technique to analyze the dynamic proteomic expression profiles over the course of 6 to 168 h post-decapitation. This approach identified a total of 141 differentially expressed proteins, 47 of which exhibited exceptionally high fold changes (≥3-fold change). Of these, Rx protein, an important regulator of head and brain development, was considered to be closely related to planarian head regeneration because of its exceptional high expression almost throughout the time course of regeneration process. Functional annotation analysis classified the 141 proteins into eight categories: (1) signaling, (2) Ca(2+) binding and translocation, (3) transcription and translation, (4) cytoskeleton, (5) metabolism, (6) cell protection, (7) tissue differentiation, and (8) cell cycle. Signaling pathway analysis indicated that Wnt1/Ca(2+) signaling pathway was activated during head regeneration. Integrating the analyses of proteome expression profiling, functional annotation, and signaling pathway, amputation-induced head reformation requires some mechanisms to promote cell proliferation and differentiation, including differential regulation of proapoptotic and antiapoptotic proteins, and the regulation of proliferation and differentiation-related proteins. Importantly, Wnt1/Ca(2+) signaling pathway upregulates Rx expression, finally facilitating the differentiation of neoblasts into various cell types. Taken together, our study demonstrated that proteomic analysis approach used by us is a powerful tool in understanding molecular process related to head regeneration of planarian.
Sousa, Josane F.; Nam, Ki Taek; Petersen, Christine P.; Lee, Hyuk-Joon; Yang, Han-Kwang; Kim, Woo Ho; Goldenring, James R.
2016-01-01
Objective Intestinal metaplasia and spasmolytic polypeptide-expressing metaplasia (SPEM) are considered neoplastic precursors of gastric adenocarcinoma and are both marked by gene expression alterations in comparison to normal stomach. Since miRNAs are important regulators of gene expression, we sought to investigate the role of miRNAs on the development of stomach metaplasias. Design We performed miRNA profiling using a qRT-PCR approach on laser capture microdissected human intestinal metaplasia and SPEM. Data integration of the miRNA profile with a previous mRNA profile from the same samples was performed to detect potential miRNA-mRNA regulatory circuits. Transfection of gastric cancer cell lines with selected miRNA mimics and inhibitors was used to evaluate their effects on the expression of putative targets and additional metaplasia markers. Results We identified several genes as potential targets of miRNAs altered during metaplasia progression. We showed evidence that HNF4γ (upregulated in intestinal metaplasia) is targeted by miR-30 and that miR-194 targets a known co-regulator of HNF4 activity, NR2F2 (downregulated in intestinal metaplasia). Intestinal metaplasia markers such as VIL1, TFF2 and TFF3 were down-regulated after overexpression of miR-30a in a HNF4γ-dependent manner. In addition, overexpression of HNF4γ was sufficient to induce the expression of VIL1 and this effect was potentiated by down-regulation of NR2F2. Conclusion The interplay of the two transcription factors HNF4γ and NR2F2 and their coordinate regulation by miR-30 and miR-194, respectively, represent a miRNA to transcription factor network responsible for the expression of intestinal transcripts in stomach cell lineages during the development of intestinal metaplasia. PMID:25800782
Santos, Clelton A; Janissen, Richard; Toledo, Marcelo A S; Beloti, Lilian L; Azzoni, Adriano R; Cotta, Monica A; Souza, Anete P
2015-10-01
The intriguing roles of the bacterial Tol-Pal trans-envelope protein complex range from maintenance of cell envelope integrity to potential participation in the process of cell division. In this study, we report the characterization of the XfTolB and XfPal proteins of the Tol-Pal complex of Xylella fastidiosa. X. fastidiosa is a major plant pathogen that forms biofilms inside xylem vessels, triggering the development of diseases in important cultivable plants around the word. Based on functional complementation experiments in Escherichia coli tolB and pal mutant strains, we confirmed the role of xftolB and xfpal in outer membrane integrity. In addition, we observed a dynamic and coordinated protein expression profile during the X. fastidiosa biofilm development process. Using small-angle X-ray scattering (SAXS), the low-resolution structure of the isolated XfTolB-XfPal complex in solution was solved for the first time. Finally, the localization of the XfTolB and XfPal polar ends was visualized via immunofluorescence labeling in vivo during bacterial cell growth. Our results highlight the major role of the components of the cell envelope, particularly the TolB-Pal complex, during the different phases of bacterial biofilm development. Copyright © 2015 Elsevier B.V. All rights reserved.
Pearce, Oliver M T; Delaine-Smith, Robin M; Maniati, Eleni; Nichols, Sam; Wang, Jun; Böhm, Steffen; Rajeeve, Vinothini; Ullah, Dayem; Chakravarty, Probir; Jones, Roanne R; Montfort, Anne; Dowe, Tom; Gribben, John; Jones, J Louise; Kocher, Hemant M; Serody, Jonathan S; Vincent, Benjamin G; Connelly, John; Brenton, James D; Chelala, Claude; Cutillas, Pedro R; Lockley, Michelle; Bessant, Conrad; Knight, Martin M; Balkwill, Frances R
2018-03-01
We have profiled, for the first time, an evolving human metastatic microenvironment by measuring gene expression, matrisome proteomics, cytokine and chemokine levels, cellularity, extracellular matrix organization, and biomechanical properties, all on the same sample. Using biopsies of high-grade serous ovarian cancer metastases that ranged from minimal to extensive disease, we show how nonmalignant cell densities and cytokine networks evolve with disease progression. Multivariate integration of the different components allowed us to define, for the first time, gene and protein profiles that predict extent of disease and tissue stiffness, while also revealing the complexity and dynamic nature of matrisome remodeling during development of metastases. Although we studied a single metastatic site from one human malignancy, a pattern of expression of 22 matrisome genes distinguished patients with a shorter overall survival in ovarian and 12 other primary solid cancers, suggesting that there may be a common matrix response to human cancer. Significance: Conducting multilevel analysis with data integration on biopsies with a range of disease involvement identifies important features of the evolving tumor microenvironment. The data suggest that despite the large spectrum of genomic alterations, some human malignancies may have a common and potentially targetable matrix response that influences the course of disease. Cancer Discov; 8(3); 304-19. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 253 . ©2017 American Association for Cancer Research.
Comparative Expression Profiling of Distinct T Cell Subsets Undergoing Oxidative Stress
Lichtenfels, Rudolf; Mougiakakos, Dimitrios; Johansson, C. Christian; Dressler, Sven P.; Recktenwald, Christian V.; Kiessling, Rolf; Seliger, Barbara
2012-01-01
The clinical outcome of adoptive T cell transfer-based immunotherapies is often limited due to different escape mechanisms established by tumors in order to evade the hosts' immune system. The establishment of an immunosuppressive micromilieu by tumor cells along with distinct subsets of tumor-infiltrating lymphocytes is often associated with oxidative stress that can affect antigen-specific memory/effector cytotoxic T cells thereby substantially reducing their frequency and functional activation. Therefore, protection of tumor-reactive cytotoxic T lymphocytes from oxidative stress may enhance the anti-tumor-directed immune response. In order to better define the key pathways/proteins involved in the response to oxidative stress a comparative 2-DE-based proteome analysis of naïve CD45RA+ and their memory/effector CD45RO+ T cell counterparts in the presence and absence of low dose hydrogen peroxide (H2O2) was performed in this pilot study. Based on the profiling data of these T cell subpopulations under the various conditions, a series of differentially expressed spots were defined, members thereof identified by mass spectrometry and subsequently classified according to their cellular function and localization. Representative targets responding to oxidative stress including proteins involved in signaling pathways, in regulating the cellular redox status as well as in shaping/maintaining the structural cell integrity were independently verified at the transcript and protein level under the same conditions in both T cell subsets. In conclusion the resulting profiling data describe complex, oxidative stress-induced, but not strictly concordant changes within the respective expression profiles of CD45RA+ and CD45RO+ T cells. Some of the differentially expressed genes/proteins might be further exploited as potential targets toward modulating the redox capacity of the distinct lymphocyte subsets thereby providing the basis for further studies aiming at rendering them more resistant to tumor micromilieu-induced oxidative stress. PMID:22911781
McArt, Darragh G.; Dunne, Philip D.; Blayney, Jaine K.; Salto-Tellez, Manuel; Van Schaeybroeck, Sandra; Hamilton, Peter W.; Zhang, Shu-Dong
2013-01-01
The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. PMID:23840550
Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal
Gao, Jianjiong; Aksoy, Bülent Arman; Dogrusoz, Ugur; Dresdner, Gideon; Gross, Benjamin; Sumer, S. Onur; Sun, Yichao; Jacobsen, Anders; Sinha, Rileen; Larsson, Erik; Cerami, Ethan; Sander, Chris; Schultz, Nikolaus
2014-01-01
The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics. PMID:23550210
NASA Astrophysics Data System (ADS)
Deckers, Jef; Van Noten, Koen; Schiltz, Marco; Lecocq, Thomas; Vanneste, Kris
2018-01-01
The Grote Brogel Fault (GBF) is a major WNW-ESE striking normal fault in Belgium that diverges westward from the NW-SE striking western border fault system of the Roer Valley Graben. The GBF delimits the topographically higher Campine Block from the subsiding Roer Valley Graben, and is expressed in the Digital Terrain Model (DTM) by relief gradients or scarps. By integrating DTM, Electrical Resistivity Tomography (ERT), Cone Penetration Test (CPT) and borehole data, we studied the Quaternary activity of the GBF and its effects on local hydrogeology. In the shallow subsurface (< 50 m) underneath these scarps, fault splays of the GBF were interpreted on newly acquired ERT profiles at two investigation sites: one on the eastern section and the other on the western section, near the limit of the visible surface trace of the fault. Borehole and CPT data enabled stratigraphic interpretations of the ERT profiles and thereby allowed measuring vertical fault offsets at the base of Pleistocene fluvial deposits of up to 12 m. Groundwater measurements in the boreholes and CPTs indicate that the GBF acts as a hydrologic boundary that prevents groundwater flow from the elevated footwall towards the hangingwall, resulting in hydraulic head differences of up to 12.7 m. For the two investigation sites, the hydraulic head changes correlate with the relief gradient, which in turn correlates with the Quaternary vertical offset of the GBF. ERT profiles at the eastern site also revealed a local soft-linked stepover in the shallow subsurface, which affects groundwater levels in the different fault blocks, and illustrates the complex small-scale geometry of the GBF.
Zhang, Yu; Zhu, Chenyang; Sun, Bangyao; Lv, Jiawei; Liu, Zhonghua; Liu, Shengwang; Li, Hai
2017-01-01
p53 dysfunction is frequently observed in lung cancer. Although restoring the tumour suppressor function of p53 is recently approved as a putative strategy for combating cancers, the lack of understanding of the molecular mechanism underlying p53-mediated lung cancer suppression has limited the application of p53-based therapies in lung cancer. Using RNA sequencing, we determined the transcriptional profile of human non-small cell lung carcinoma A549 cells after treatment with two p53-activating chemical compounds, nutlin and RITA, which could induce A549 cell cycle arrest and apoptosis, respectively. Bioinformatics analysis of genome-wide gene expression data showed that distinct transcription profiles were induced by nutlin and RITA and 66 pathways were differentially regulated by these two compounds. However, only two of these pathways, 'Adherens junction' and 'Axon guidance', were found to be synthetic lethal with p53 re-activation, as determined via integrated analysis of genome-wide gene expression profile and short hairpin RNA (shRNA) screening. Further functional protein association analysis of significantly regulated genes associated with these two synthetic lethal pathways indicated that GSK3 played a key role in p53-mediated A549 cell apoptosis, and then gene function study was performed, which revealed that GSK3 inhibition promoted p53-mediated A549 cell apoptosis in a p53 post-translational activity-dependent manner. Our findings provide us with new insights regarding the mechanism by which p53 mediates A549 apoptosis and may cast light on the development of more efficient p53-based strategies for treating lung cancer. © 201 The Author(s). Published by S. Karger AG, Basel.
The investigation of improved SHARAD profiles over Martian lobate debris aprons
NASA Astrophysics Data System (ADS)
Kim, J.; Baik, H. S.
2016-12-01
The Shallow Subsurface Radar (SHARAD), a radar sounding radar on the Mars Reconnaissance Orbiter has produced high valuable information concerning subsurface of Mars. It has been successfully used to observe complicate substructures of Mars such as polar deposit, pedestal crater and the other geomorphic features involving possible subsurface ice body. In this study, we summarized all SHARAD profiles over Martian Lobate debris aprons (LDAs) where significant arguments about their origins are undergoing. To make clear result, we used radon transformation for noise filtering. Also, we tried the clutter simulation on our target's Digital elevation model(DEM) produced by High Resolution Stereo Camera(HRSC) of Mars Express; As the comparison results between noise-removed SHARAD profile and clutter simulation, layers were able to be more clearly identified at many LDAs. We integrated our SHARAD profiles over all mid latitude LDAs into GIS. These will be demonstrated together with several radargram structures. However, it appeared the discontinuities over SHARAD profile result is not sufficient to be a clue of its origin. Thus the intensive interpretations employing thermal inertia, high resolution topographic profile with CTX and HiRISE stereo DTM altogether will be further conducted.
Vivanti, Alexandre; Soheili, Tayebeh S.; Cuccuini, Wendy; Luce, Sonia; Mandelbrot, Laurent; Lechenadec, Jerome; Cordier, Anne-Gael; Azria, Elie; Soulier, Jean; Cavazzana, Marina; Blanche, Stéphane; André-Schmutz, Isabelle
2015-01-01
Objectives: Zidovudine and tenofovir are the two main nucleos(t)ide analogs used to prevent mother-to-child transmission of HIV. In vitro, both drugs bind to and integrate into human DNA and inhibit telomerase. The objective of the present study was to assess the genotoxic effects of either zidovudine or tenofovir-based combination therapies on cord blood cells in newborns exposed in utero. Design: We compared the aneuploid rate and the gene expression profiles in cord blood samples from newborns exposed either to zidovudine or tenofovir-based combination therapies during pregnancy and from unexposed controls (n = 8, 9, and 8, respectively). Methods: The aneuploidy rate was measured on the cord blood T-cell karyotype. Gene expression profiles of cord blood T cells and hematopoietic stem and progenitor cells were determined with microarrays, analyzed in a gene set enrichment analysis and confirmed by real-time quantitative PCRs. Results: Aneuploidy was more frequent in the zidovudine-exposed group (26.3%) than in the tenofovir-exposed group (14.2%) or in controls (13.3%; P < 0.05 for both). The transcription of genes involved in DNA repair, telomere maintenance, nucleotide metabolism, DNA/RNA synthesis, and the cell cycle was deregulated in samples from both the zidovudine and the tenofovir-exposed groups. Conclusion: Although tenofovir has a lower clastogenic impact than zidovudine, gene expression profiling showed that both drugs alter the transcription of DNA repair and telomere maintenance genes. PMID:25513819
Vivanti, Alexandre; Soheili, Tayebeh S; Cuccuini, Wendy; Luce, Sonia; Mandelbrot, Laurent; Lechenadec, Jerome; Cordier, Anne-Gael; Azria, Elie; Soulier, Jean; Cavazzana, Marina; Blanche, Stéphane; André-Schmutz, Isabelle
2015-07-17
Zidovudine and tenofovir are the two main nucleos(t)ide analogs used to prevent mother-to-child transmission of HIV. In vitro, both drugs bind to and integrate into human DNA and inhibit telomerase. The objective of the present study was to assess the genotoxic effects of either zidovudine or tenofovir-based combination therapies on cord blood cells in newborns exposed in utero. We compared the aneuploid rate and the gene expression profiles in cord blood samples from newborns exposed either to zidovudine or tenofovir-based combination therapies during pregnancy and from unexposed controls (n = 8, 9, and 8, respectively). The aneuploidy rate was measured on the cord blood T-cell karyotype. Gene expression profiles of cord blood T cells and hematopoietic stem and progenitor cells were determined with microarrays, analyzed in a gene set enrichment analysis and confirmed by real-time quantitative PCRs. Aneuploidy was more frequent in the zidovudine-exposed group (26.3%) than in the tenofovir-exposed group (14.2%) or in controls (13.3%; P < 0.05 for both). The transcription of genes involved in DNA repair, telomere maintenance, nucleotide metabolism, DNA/RNA synthesis, and the cell cycle was deregulated in samples from both the zidovudine and the tenofovir-exposed groups. Although tenofovir has a lower clastogenic impact than zidovudine, gene expression profiling showed that both drugs alter the transcription of DNA repair and telomere maintenance genes.
Differential co-expression analysis of rheumatoid arthritis with microarray data.
Wang, Kunpeng; Zhao, Liqiang; Liu, Xuefeng; Hao, Zhenyong; Zhou, Yong; Yang, Chuandong; Li, Hongqiang
2014-11-01
The aim of the present study was to investigate the underlying molecular mechanisms of rheumatoid arthritis (RA) using microarray expression profiles from osteoarthritis and RA patients, to improve diagnosis and treatment strategies for the condition. The gene expression profile of GSE27390 was downloaded from Gene Expression Omnibus, including 19 samples from patients with RA (n=9) or osteoarthritis (n=10). Firstly, the differentially expressed genes (DEGs) were obtained with the thresholds of |logFC|>1.0 and P<0.05, using the t‑test method in LIMMA package. Then, differentially co-expressed genes (DCGs) and differentially co-expressed links (DCLs) were screened with q<0.25 by the differential coexpression analysis and differential regulation analysis of gene expression microarray data package. Secondly, pathway enrichment analysis for DCGs was performed by the Database for Annotation, Visualization and Integrated Discovery and the DCLs associated with RA were selected by comparing the obtained DCLs with known transcription factor (TF)-targets in the TRANSFAC database. Finally, the obtained TFs were mapped to the known TF-targets to construct the network using cytoscape software. A total of 1755 DEGs, 457 DCGs and 101988 DCLs were achieved and there were 20 TFs in the obtained six TF-target relations (STAT3-TNF, PBX1‑PLAU, SOCS3-STAT3, GATA1-ETS2, ETS1-ICAM4 and CEBPE‑GATA1) and 457 DCGs. A number of TF-target relations in the constructed network were not within DCLs when the TF and target gene were DCGs. The identified TFs may have an important role in the pathogenesis of RA and have the potential to be used as biomarkers for the development of novel diagnostic and therapeutic strategies for RA.
Sakaki, Mizuho; Ebihara, Yukiko; Okamura, Kohji; Nakabayashi, Kazuhiko; Igarashi, Arisa; Matsumoto, Kenji; Hata, Kenichiro; Kobayashi, Yoshiro
2017-01-01
Cellular senescence is classified into two groups: replicative and premature senescence. Gene expression and epigenetic changes are reported to differ between these two groups and cell types. Normal human diploid fibroblast TIG-3 cells have often been used in cellular senescence research; however, their epigenetic profiles are still not fully understood. To elucidate how cellular senescence is epigenetically regulated in TIG-3 cells, we analyzed the gene expression and DNA methylation profiles of three types of senescent cells, namely, replicatively senescent, ras-induced senescent (RIS), and non-permissive temperature-induced senescent SVts8 cells, using gene expression and DNA methylation microarrays. The expression of genes involved in the cell cycle and immune response was commonly either down- or up-regulated in the three types of senescent cells, respectively. The altered DNA methylation patterns were observed in replicatively senescent cells, but not in prematurely senescent cells. Interestingly, hypomethylated CpG sites detected on non-CpG island regions (“open sea”) were enriched in immune response-related genes that had non-CpG island promoters. The integrated analysis of gene expression and methylation in replicatively senescent cells demonstrated that differentially expressed 867 genes, including cell cycle- and immune response-related genes, were associated with DNA methylation changes in CpG sites close to the transcription start sites (TSSs). Furthermore, several miRNAs regulated in part through DNA methylation were found to affect the expression of their targeted genes. Taken together, these results indicate that the epigenetic changes of DNA methylation regulate the expression of a certain portion of genes and partly contribute to the introduction and establishment of replicative senescence. PMID:28158250
Szepsenwol, Ohad; Simpson, Jeffry A
2018-03-15
In this article, we discuss theory and research on how individual differences in adult attachment mediate the adaptive calibration of reproductive strategies, cognitive schemas, and emotional expression and regulation. We first present an integration of attachment theory and life history theory. Then, we discuss how early harsh and/or unpredictable environments may promote insecure attachment by hampering parents' ability to provide sensitive and reliable care to their children. Finally, we discuss how, in the context of harsh and/or unpredictable environments, different types of insecure attachment (i.e. anxiety and avoidance) may promote evolutionary adaptive reproductive strategies, cognitive schemas, and emotional expression and regulation profiles. Copyright © 2018 Elsevier Ltd. All rights reserved.
TRANSFAC: an integrated system for gene expression regulation.
Wingender, E; Chen, X; Hehl, R; Karas, H; Liebich, I; Matys, V; Meinhardt, T; Prüss, M; Reuter, I; Schacherer, F
2000-01-01
TRANSFAC is a database on transcription factors, their genomic binding sites and DNA-binding profiles (http://transfac.gbf.de/TRANSFAC/). Its content has been enhanced, in particular by information about training sequences used for the construction of nucleotide matrices as well as by data on plant sites and factors. Moreover, TRANSFAC has been extended by two new modules: PathoDB provides data on pathologically relevant mutations in regulatory regions and transcription factor genes, whereas S/MARt DB compiles features of scaffold/matrix attached regions (S/MARs) and the proteins binding to them. Additionally, the databases TRANSPATH, about signal transduction, and CYTOMER, about organs and cell types, have been extended and are increasingly integrated with the TRANSFAC data sources.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Jing; Ma, Zihao; Carr, Steven A.
Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC).more » Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies. Molecular & Cellular Proteomics 16: 10.1074/mcp.M116.060301, 121–134, 2017.« less
Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola
2014-12-01
We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named "fight-club hubs" characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named "switch genes" was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. © 2014 American Society of Plant Biologists. All rights reserved.
Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola
2014-01-01
We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named “fight-club hubs” characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named “switch genes” was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. PMID:25490918
Expression of the pol gene of human endogenous retroviruses HERV-K and -W in leukemia patients.
Bergallo, Massimiliano; Montanari, Paola; Mareschi, Katia; Merlino, Chiara; Berger, Massimo; Bini, Ilaria; Daprà, Valentina; Galliano, Ilaria; Fagioli, Franca
2017-12-01
The human endogenous retroviruses (HERVs) are a family of endogenous retroviruses that integrated into the germ cell DNA of primates over 30 million years ago. HERV expression seems impaired in several diseases, ranging from autoimmune to neoplastic disorders. The purpose of this study was to evaluate the overall endogenous retroviral transcription profile in bone marrow (BM) samples. A total of 30 paediatric high-risk leukaemia patients (lymphoid and myeloid malignancies) were tested for HERVs virus gene expression. Our findings show that HERV-K expression was significantly higher in leukaemia patients when compared to healthy donors of a similar median age. We observed a significantly high expression of HERV-K in acute lymphoblastic leukemia (ALL) patients. In this study, we also found a relative overexpression of the endogenous retrovirus HERV-K in BM cells from the majority of leukemia samples analyzed, in particular in ALL. This overexpression might be related to lymphatic leukemogenesis and it warrants further investigations.
Characterization of HPV and host genome interactions in primary head and neck cancers.
Parfenov, Michael; Pedamallu, Chandra Sekhar; Gehlenborg, Nils; Freeman, Samuel S; Danilova, Ludmila; Bristow, Christopher A; Lee, Semin; Hadjipanayis, Angela G; Ivanova, Elena V; Wilkerson, Matthew D; Protopopov, Alexei; Yang, Lixing; Seth, Sahil; Song, Xingzhi; Tang, Jiabin; Ren, Xiaojia; Zhang, Jianhua; Pantazi, Angeliki; Santoso, Netty; Xu, Andrew W; Mahadeshwar, Harshad; Wheeler, David A; Haddad, Robert I; Jung, Joonil; Ojesina, Akinyemi I; Issaeva, Natalia; Yarbrough, Wendell G; Hayes, D Neil; Grandis, Jennifer R; El-Naggar, Adel K; Meyerson, Matthew; Park, Peter J; Chin, Lynda; Seidman, J G; Hammerman, Peter S; Kucherlapati, Raju
2014-10-28
Previous studies have established that a subset of head and neck tumors contains human papillomavirus (HPV) sequences and that HPV-driven head and neck cancers display distinct biological and clinical features. HPV is known to drive cancer by the actions of the E6 and E7 oncoproteins, but the molecular architecture of HPV infection and its interaction with the host genome in head and neck cancers have not been comprehensively described. We profiled a cohort of 279 head and neck cancers with next generation RNA and DNA sequencing and show that 35 (12.5%) tumors displayed evidence of high-risk HPV types 16, 33, or 35. Twenty-five cases had integration of the viral genome into one or more locations in the human genome with statistical enrichment for genic regions. Integrations had a marked impact on the human genome and were associated with alterations in DNA copy number, mRNA transcript abundance and splicing, and both inter- and intrachromosomal rearrangements. Many of these events involved genes with documented roles in cancer. Cancers with integrated vs. nonintegrated HPV displayed different patterns of DNA methylation and both human and viral gene expressions. Together, these data provide insight into the mechanisms by which HPV interacts with the human genome beyond expression of viral oncoproteins and suggest that specific integration events are an integral component of viral oncogenesis.
The BIG Data Center: from deposition to integration to translation.
2017-01-04
Biological data are generated at unprecedentedly exponential rates, posing considerable challenges in big data deposition, integration and translation. The BIG Data Center, established at Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, provides a suite of database resources, including (i) Genome Sequence Archive, a data repository specialized for archiving raw sequence reads, (ii) Gene Expression Nebulas, a data portal of gene expression profiles based entirely on RNA-Seq data, (iii) Genome Variation Map, a comprehensive collection of genome variations for featured species, (iv) Genome Warehouse, a centralized resource housing genome-scale data with particular focus on economically important animals and plants, (v) Methylation Bank, an integrated database of whole-genome single-base resolution methylomes and (vi) Science Wikis, a central access point for biological wikis developed for community annotations. The BIG Data Center is dedicated to constructing and maintaining biological databases through big data integration and value-added curation, conducting basic research to translate big data into big knowledge and providing freely open access to a variety of data resources in support of worldwide research activities in both academia and industry. All of these resources are publicly available and can be found at http://bigd.big.ac.cn. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Beltrami, Caroline Moraes; Dos Reis, Mariana Bisarro; Barros-Filho, Mateus Camargo; Marchi, Fabio Albuquerque; Kuasne, Hellen; Pinto, Clóvis Antônio Lopes; Ambatipudi, Srikant; Herceg, Zdenko; Kowalski, Luiz Paulo; Rogatto, Silvia Regina
2017-01-01
Papillary thyroid carcinoma (PTC) is a common endocrine neoplasm with a recent increase in incidence in many countries. Although PTC has been explored by gene expression and DNA methylation studies, the regulatory mechanisms of the methylation on the gene expression was poorly clarified. In this study, DNA methylation profile (Illumina HumanMethylation 450K) of 41 PTC paired with non-neoplastic adjacent tissues (NT) was carried out to identify and contribute to the elucidation of the role of novel genic and intergenic regions beyond those described in the promoter and CpG islands (CGI). An integrative and cross-validation analysis were performed aiming to identify molecular drivers and pathways that are PTC-related. The comparisons between PTC and NT revealed 4995 methylated probes (88% hypomethylated in PTC) and 1446 differentially expressed transcripts cross-validated by the The Cancer Genome Atlas data. The majority of these probes was found in non-promoters regions, distant from CGI and enriched by enhancers. The integrative analysis between gene expression and DNA methylation revealed 185 and 38 genes (mainly in the promoter and body regions, respectively) with negative and positive correlation, respectively. Genes showing negative correlation underlined FGF and retinoic acid signaling as critical canonical pathways disrupted by DNA methylation in PTC. BRAF mutation was detected in 68% (28 of 41) of the tumors, which presented a higher level of demethylation (95% hypomethylated probes) compared with BRAF wild-type tumors. A similar integrative analysis uncovered 40 of 254 differentially expressed genes, which are potentially regulated by DNA methylation in BRAF V600E-positive tumors. The methylation and expression pattern of six selected genes ( ERBB3 , FGF1 , FGFR2 , GABRB2 , HMGA2 , and RDH5 ) were confirmed as altered by pyrosequencing and RT-qPCR. DNA methylation loss in non-promoter, poor CGI and enhancer-enriched regions was a significant event in PTC, especially in tumors harboring BRAF V600E. In addition to the promoter region, gene body and 3'UTR methylation have also the potential to influence the gene expression levels (both, repressing and inducing). The integrative analysis revealed genes potentially regulated by DNA methylation pointing out potential drivers and biomarkers related to PTC development.
Digital sorting of complex tissues for cell type-specific gene expression profiles.
Zhong, Yi; Wan, Ying-Wooi; Pang, Kaifang; Chow, Lionel M L; Liu, Zhandong
2013-03-07
Cellular heterogeneity is present in almost all gene expression profiles. However, transcriptome analysis of tissue specimens often ignores the cellular heterogeneity present in these samples. Standard deconvolution algorithms require prior knowledge of the cell type frequencies within a tissue or their in vitro expression profiles. Furthermore, these algorithms tend to report biased estimations. Here, we describe a Digital Sorting Algorithm (DSA) for extracting cell-type specific gene expression profiles from mixed tissue samples that is unbiased and does not require prior knowledge of cell type frequencies. The results suggest that DSA is a specific and sensitivity algorithm in gene expression profile deconvolution and will be useful in studying individual cell types of complex tissues.
An integrated bioinformatics analysis to dissect kinase dependency in triple negative breast cancer.
Ryall, Karen A; Kim, Jihye; Klauck, Peter J; Shin, Jimin; Yoo, Minjae; Ionkina, Anastasia; Pitts, Todd M; Tentler, John J; Diamond, Jennifer R; Eckhardt, S Gail; Heasley, Lynn E; Kang, Jaewoo; Tan, Aik Choon
2015-01-01
Triple-Negative Breast Cancer (TNBC) is an aggressive disease with a poor prognosis. Clinically, TNBC patients have limited treatment options besides chemotherapy. The goal of this study was to determine the kinase dependency in TNBC cell lines and to predict compounds that could inhibit these kinases using integrative bioinformatics analysis. We integrated publicly available gene expression data, high-throughput pharmacological profiling data, and quantitative in vitro kinase binding data to determine the kinase dependency in 12 TNBC cell lines. We employed Kinase Addiction Ranker (KAR), a novel bioinformatics approach, which integrated these data sources to dissect kinase dependency in TNBC cell lines. We then used the kinase dependency predicted by KAR for each TNBC cell line to query K-Map for compounds targeting these kinases. We validated our predictions using published and new experimental data. In summary, we implemented an integrative bioinformatics analysis that determines kinase dependency in TNBC. Our analysis revealed candidate kinases as potential targets in TNBC for further pharmacological and biological studies.
Gene integrated set profile analysis: a context-based approach for inferring biological endpoints
Kowalski, Jeanne; Dwivedi, Bhakti; Newman, Scott; Switchenko, Jeffery M.; Pauly, Rini; Gutman, David A.; Arora, Jyoti; Gandhi, Khanjan; Ainslie, Kylie; Doho, Gregory; Qin, Zhaohui; Moreno, Carlos S.; Rossi, Michael R.; Vertino, Paula M.; Lonial, Sagar; Bernal-Mizrachi, Leon; Boise, Lawrence H.
2016-01-01
The identification of genes with specific patterns of change (e.g. down-regulated and methylated) as phenotype drivers or samples with similar profiles for a given gene set as drivers of clinical outcome, requires the integration of several genomic data types for which an ‘integrate by intersection’ (IBI) approach is often applied. In this approach, results from separate analyses of each data type are intersected, which has the limitation of a smaller intersection with more data types. We introduce a new method, GISPA (Gene Integrated Set Profile Analysis) for integrated genomic analysis and its variation, SISPA (Sample Integrated Set Profile Analysis) for defining respective genes and samples with the context of similar, a priori specified molecular profiles. With GISPA, the user defines a molecular profile that is compared among several classes and obtains ranked gene sets that satisfy the profile as drivers of each class. With SISPA, the user defines a gene set that satisfies a profile and obtains sample groups of profile activity. Our results from applying GISPA to human multiple myeloma (MM) cell lines contained genes of known profiles and importance, along with several novel targets, and their further SISPA application to MM coMMpass trial data showed clinical relevance. PMID:26826710
Vertical distribution of ozone at the terminator on Mars
NASA Astrophysics Data System (ADS)
Maattanen, Anni; Lefevre, Franck; Guilbon, Sabrina; Listowski, Constantino; Montmessin, Franck
2016-10-01
The SPICAM/Mars Express UV solar occultation dataset gives access to the ozone vertical distribution via the ozone absorption in the Hartley band (220-280 nm). We present the retrieved ozone profiles and compare them to the LMD Mars Global Climate Model (LMD-MGCM) results.Due to the photochemical reactivity of ozone, a classical comparison of local density profiles is not appropriate for solar occultations that are acquired at the terminator, and we present here a method often used in the Earth community. The principal comparison is made via the slant profiles (integrated ozone concentration on the line-of-sight), since the spherical symmetry hypothesis made in the onion-peeling vertical inversion method is not valid for photochemically active species (e.g., ozone) around terminator. For each occultation, we model the ozone vertical and horizontal distribution with high solar zenith angle (or local time) resolution around the terminator and then integrate the model results following the lines-of-sight of the occultation to construct the modeled slant profile. We will also discuss the difference of results between the above comparison method and a comparison using the local density profiles, i.e., the observed ones inverted by using the spherical symmetry hypothesis and the modeled ones extracted from the LMD-MGCM exactly at the terminator. The method and the results will be presented together with the full dataset.SPICAM is funded by the French Space Agency CNES and this work has received funding from the European Union's Horizon 2020 Programme (H2020-Compet-08-2014) under grant agreement UPWARDS-633127.
Porter, Christopher C.; Kim, Jihye; Fosmire, Susan; Gearheart, Christy M.; van Linden, Annemie; Baturin, Dmitry; Zaberezhnyy, Vadym; Patel, Purvi R.; Gao, Dexiang; Tan, Aik Choon; DeGregori, James
2011-01-01
Acute myeloid leukemia (AML) remains a therapeutic challenge despite increasing knowledge about the molecular origins of the disease, as the mechanisms of AML cell escape from chemotherapy remain poorly defined. We hypothesized that AML cells are addicted to molecular pathways in the context of chemotherapy and used complementary approaches to identify these addictions. Using novel molecular and computational approaches, we performed genome-wide shRNA screens to identify proteins that mediate AML cell fate after cytarabine exposure, gene expression profiling of AML cells exposed to cytarabine to identify genes with induced expression in this context, and examination of existing gene expression data from primary patient samples. The integration of these independent analyses strongly implicates cell cycle checkpoint proteins, particularly WEE1, as critical mediators of AML cell survival after cytarabine exposure. Knockdown of WEE1 in a secondary screen confirmed its role in AML cell survival. Pharmacologic inhibition of WEE1 in AML cell lines and primary cells is synergistic with cytarabine. Further experiments demonstrate that inhibition of WEE1 prevents S-phase arrest induced by cytarabine, broadening the functions of WEE1 that may be exploited therapeutically. These data highlight the power of integrating functional and descriptive genomics, and identify WEE1 as potential therapeutic target in AML. PMID:22289989
Maver, Ales; Medica, Igor; Peterlin, Borut
2009-12-01
The search for gene candidates in multifactorial diseases such as sarcoidosis can be based on the integration of linkage association data, gene expression data, and protein profile data from genomic, transcriptomic and proteomic studies, respectively. In this study we performed a literature-based search for studies reporting such data, followed by integration of collected information. Different databases were examined--Medline, HugGE Navigator, ArrayExpress and Gene Expression Omnibus (GEO). Candidate genes were defined as genes which were reported in at least 2 different types of omics studies. Genes previously investigated in sarcoidosis were excluded from further analyses. We identified 177 genes associated with sarcoidosis as potential new candidate genes. Subsequently, 9 gene candidates identified to overlap in 2 different types of studies (genomic, transcriptomic and/or proteomic) were consistently reported in at least 3 studies: SERPINB1, FABP4, S100A8, HBEGF, IL7R, LRIG1, PTPN23, DPM2 and NUP214. These genes are involved in regulation of immune response, cellular proliferation, apoptosis, inhibition of protease activity, lipid metabolism. Exact biological functions of HBEGF, LRIG1, PTPN23, DPM2 and NUP214 remain to be completely elucidated. We propose 9 candidate genes: SERPINB1, FABP4, S100A8, HBEGF, IL7R, LRIG1, PTPN23, DPM2 and NUP214, as genes with high potential for association with sarcoidosis.
Dannenmann, Benjamin; Lehle, Simon; Hildebrand, Dominic G.; Kübler, Ayline; Grondona, Paula; Schmid, Vera; Holzer, Katharina; Fröschl, Mirjam; Essmann, Frank; Rothfuss, Oliver; Schulze-Osthoff, Klaus
2015-01-01
Summary Pluripotent stem cells must strictly maintain genomic integrity to prevent transmission of mutations. In human induced pluripotent stem cells (iPSCs), we found that genome surveillance is achieved via two ways, namely, a hypersensitivity to apoptosis and a very low accumulation of DNA lesions. The low apoptosis threshold was mediated by constitutive p53 expression and a marked upregulation of proapoptotic p53 target genes of the BCL-2 family, ensuring the efficient iPSC removal upon genotoxic insults. Intriguingly, despite the elevated apoptosis sensitivity, both mitochondrial and nuclear DNA lesions induced by genotoxins were less frequent in iPSCs compared to fibroblasts. Gene profiling identified that mRNA expression of several antioxidant proteins was considerably upregulated in iPSCs. Knockdown of glutathione peroxidase-2 and depletion of glutathione impaired protection against DNA lesions. Thus, iPSCs ensure genomic integrity through enhanced apoptosis induction and increased antioxidant defense, contributing to protection against DNA damage. PMID:25937369
oPOSSUM: integrated tools for analysis of regulatory motif over-representation
Ho Sui, Shannan J.; Fulton, Debra L.; Arenillas, David J.; Kwon, Andrew T.; Wasserman, Wyeth W.
2007-01-01
The identification of over-represented transcription factor binding sites from sets of co-expressed genes provides insights into the mechanisms of regulation for diverse biological contexts. oPOSSUM, an internet-based system for such studies of regulation, has been improved and expanded in this new release. New features include a worm-specific version for investigating binding sites conserved between Caenorhabditis elegans and C. briggsae, as well as a yeast-specific version for the analysis of co-expressed sets of Saccharomyces cerevisiae genes. The human and mouse applications feature improvements in ortholog mapping, sequence alignments and the delineation of multiple alternative promoters. oPOSSUM2, introduced for the analysis of over-represented combinations of motifs in human and mouse genes, has been integrated with the original oPOSSUM system. Analysis using user-defined background gene sets is now supported. The transcription factor binding site models have been updated to include new profiles from the JASPAR database. oPOSSUM is available at http://www.cisreg.ca/oPOSSUM/ PMID:17576675
Sung, Chang Ohk; Choi, Chel Hun; Ko, Young-Hyeh; Ju, Hyunjeong; Choi, Yoon-La; Kim, Nyunsu; Kang, So Young; Ha, Sang Yun; Choi, Kyusam; Bae, Duk-Soo; Lee, Jeong-Won; Kim, Tae-Joong; Song, Sang Yong; Kim, Byoung-Gie
2013-05-01
Ovarian clear cell adenocarcinoma (Ov-CCA) is a distinctive subtype of ovarian epithelial carcinoma. In this study, we performed array comparative genomic hybridization (aCGH) and paired gene expression microarray of 19 fresh-frozen samples and conducted integrative analysis. For the copy number alterations, significantly amplified regions (false discovery rate [FDR] q <0.05) were 1q21.3 and 8q24.3, and significantly deleted regions were 3p21.31, 4q12, 5q13.2, 5q23.2, 5q31.1, 7p22.1, 7q11.23, 8p12, 9p22.1, 11p15.1, 12p13.31, 15q11.2, 15q21.2, 18p11.31, and 22q11.21 using the Genomic Identification of Significant Targets in Cancer (GISTIC) analysis. Integrative analysis revealed 94 genes demonstrating frequent copy number alterations (>25% of samples) that correlated with gene expression (FDR <0.05). These genes were mainly located on 8p11.21, 8p21.2-p21.3, 8q22.1, 8q24.3, 17q23.2-q23.3, 19p13.3, and 19p13.11. Among the regions, 8q24.3 was found to contain the most genes (30 of 94 genes) including PTK2. The 8q24.3 region was indicated as the most significant region, as supported by copy number, GISTIC, and integrative analysis. Pathway analysis using differentially expressed genes on 8q24.3 revealed several major nodes, including PTK2. In conclusion, we identified a set of 94 candidate genes with frequent copy number alterations that correlated with gene expression. Specific chromosomal alterations, such as the 8q24.3 gain containing PTK2, could be a therapeutic target in a subset of Ov-CCAs. Copyright © 2013. Published by Elsevier Inc.
Cassava root membrane proteome reveals activities during storage root maturation.
Naconsie, Maliwan; Lertpanyasampatha, Manassawe; Viboonjun, Unchera; Netrphan, Supatcharee; Kuwano, Masayoshi; Ogasawara, Naotake; Narangajavana, Jarunya
2016-01-01
Cassava (Manihot esculenta Crantz) is one of the most important crops of Thailand. Its storage roots are used as food, feed, starch production, and be the important source for biofuel and biodegradable plastic production. Despite the importance of cassava storage roots, little is known about the mechanisms involved in their formation. This present study has focused on comparison of the expression profiles of cassava root proteome at various developmental stages using two-dimensional gel electrophoresis and LC-MS/MS. Based on an anatomical study using Toluidine Blue, the secondary growth was confirmed to be essential during the development of cassava storage root. To investigate biochemical processes occurring during storage root maturation, soluble and membrane proteins were isolated from storage roots harvested from 3-, 6-, 9-, and 12-month-old cassava plants. The proteins with differential expression pattern were analysed and identified to be associated with 8 functional groups: protein folding and degradation, energy, metabolism, secondary metabolism, stress response, transport facilitation, cytoskeleton, and unclassified function. The expression profiling of membrane proteins revealed the proteins involved in protein folding and degradation, energy, and cell structure were highly expressed during early stages of development. Integration of these data along with the information available in genome and transcriptome databases is critical to expand knowledge obtained solely from the field of proteomics. Possible role of identified proteins were discussed in relation with the activities during storage root maturation in cassava.
Ambroise, Jérôme; Robert, Annie; Macq, Benoit; Gala, Jean-Luc
2012-01-06
An important challenge in system biology is the inference of biological networks from postgenomic data. Among these biological networks, a gene transcriptional regulatory network focuses on interactions existing between transcription factors (TFs) and and their corresponding target genes. A large number of reverse engineering algorithms were proposed to infer such networks from gene expression profiles, but most current methods have relatively low predictive performances. In this paper, we introduce the novel TNIFSED method (Transcriptional Network Inference from Functional Similarity and Expression Data), that infers a transcriptional network from the integration of correlations and partial correlations of gene expression profiles and gene functional similarities through a supervised classifier. In the current work, TNIFSED was applied to predict the transcriptional network in Escherichia coli and in Saccharomyces cerevisiae, using datasets of 445 and 170 affymetrix arrays, respectively. Using the area under the curve of the receiver operating characteristics and the F-measure as indicators, we showed the predictive performance of TNIFSED to be better than unsupervised state-of-the-art methods. TNIFSED performed slightly worse than the supervised SIRENE algorithm for the target genes identification of the TF having a wide range of yet identified target genes but better for TF having only few identified target genes. Our results indicate that TNIFSED is complementary to the SIRENE algorithm, and particularly suitable to discover target genes of "orphan" TFs.
Pannetier, M; Servel, N; Cocquet, J; Besnard, N; Cotinot, C; Pailhoux, E
2003-01-01
In mammals, the Y-located SRY gene is known to induce testis formation from the indifferent gonad. A related gene, SOX9, also plays a critical role in testis differentiation in mammals, in birds and reptiles. It is now assumed that SRY acts upstream of SOX9 in the sex determination cascade, but the regulatory link which should exist between these two genes remains unknown. Studies on XX sex reversal in polled goats (PIS mutation: Polled Intersex Syndrome) have led to the discovery of a female-specific locus crucial for ovarian differentiation. This genomic region is composed of at least two genes, FOXL2 and PISRT1, which share a common transcriptional regulatory region, PIS. In this review, we present the expression pattern of these PIS-regulated genes in mice. The FOXL2 expression profile of mice is similar to that described in goats in accordance with a conserved role of this ovarian differentiating gene in mammals. On the contrary, the PISRT1 expression profile is different between mice and goats, suggesting different mechanisms of the primary switch in the testis determination process within mammals. A model based on two different modes of SOX9 regulation in mice and other mammals is proposed in order to integrate our results into the current scheme of gonad differentiation. Copyright 2003 S. Karger AG, Basel
A comparison of honeybee (Apis mellifera) queen, worker and drone larvae by RNA-Seq.
He, Xu-Jiang; Jiang, Wu-Jun; Zhou, Mi; Barron, Andrew B; Zeng, Zhi-Jiang
2017-11-06
Honeybees (Apis mellifera) have haplodiploid sex determination: males develop from unfertilized eggs and females develop from fertilized ones. The differences in larval food also determine the development of females. Here we compared the total somatic gene expression profiles of 2-day and 4-day-old drone, queen and worker larvae by RNA-Seq. The results from a co-expression network analysis on all expressed genes showed that 2-day-old drone and worker larvae were closer in gene expression profiles than 2-day-old queen larvae. This indicated that for young larvae (2-day-old) environmental factors such as larval diet have a greater effect on gene expression profiles than ploidy or sex determination. Drones had the most distinct gene expression profiles at the 4-day larval stage, suggesting that haploidy, or sex dramatically affects the gene expression of honeybee larvae. Drone larvae showed fewer differences in gene expression profiles at the 2-day and 4-day time points than the worker and queen larval comparisons (598 against 1190 and 1181), suggesting a different pattern of gene expression regulation during the larval development of haploid males compared to diploid females. This study indicates that early in development the queen caste has the most distinct gene expression profile, perhaps reflecting the very rapid growth and morphological specialization of this caste compared to workers and drones. Later in development the haploid male drones have the most distinct gene expression profile, perhaps reflecting the influence of ploidy or sex determination on gene expression. © 2017 Institute of Zoology, Chinese Academy of Sciences.
Viveka Thangaraj, Soundara; Periasamy, Jayaprakash; Bhaskar Rao, Divya; Barnabas, Georgina D.; Raghavan, Swetha; Ganesan, Kumaresan
2013-01-01
Genomic aberrations are common in cancers and the long arm of chromosome 1 is known for its frequent amplifications in breast cancer. However, the key candidate genes of 1q, and their contribution in breast cancer pathogenesis remain unexplored. We have analyzed the gene expression profiles of 1635 breast tumor samples using meta-analysis based approach and identified clinically significant candidates from chromosome 1q. Seven candidate genes including exonuclease 1 (EXO1) are consistently over expressed in breast tumors, specifically in high grade and aggressive breast tumors with poor clinical outcome. We derived a EXO1 co-expression module from the mRNA profiles of breast tumors which comprises 1q candidate genes and their co-expressed genes. By integrative functional genomics investigation, we identified the involvement of EGFR, RAS, PI3K / AKT, MYC, E2F signaling in the regulation of these selected 1q genes in breast tumors and breast cancer cell lines. Expression of EXO1 module was found as indicative of elevated cell proliferation, genomic instability, activated RAS/AKT/MYC/E2F1 signaling pathways and loss of p53 activity in breast tumors. mRNA–drug connectivity analysis indicates inhibition of RAS/PI3K as a possible targeted therapeutic approach for the patients with activated EXO1 module in breast tumors. Thus, we identified seven 1q candidate genes strongly associated with the poor survival of breast cancer patients and identified the possibility of targeting them with EGFR/RAS/PI3K inhibitors. PMID:24147022
Expression profile of circular RNAs in human gastric cancer tissues
Huang, You-Sheng; Jie, Na; Zou, Ke-Jian; Weng, Yang
2017-01-01
Circular RNAs (circRNAs) represent a newly identified class of non-coding RNA molecules, which interfere with gene transcription by adsorbing microRNAs (miRNAs). CircRNAs serve important roles in disease development and have the potential to serve as a novel class of biomarkers for clinical diagnosis. However, the role of circRNAs in the occurrence and development of gastric cancer (GC) remains unclear. In the present study, the expression profiles of circRNAs were compared between GC and adjacent normal tissues using a circRNA microarray, following which quantitative polymerase chain reaction (qPCR) was used to confirm the results of the circRNA microarray. Compared with the adjacent, normal mucosal tissues, 16 circRNAs were upregulated and 84 circRNAs were downregulated in GC. A total of 10 circRNAs were selected for validation in three pairs of GC and adjacent noncancerous tissues. The qPCR results were consistent with the findings of the microarray-based expression analysis. Of the circRNAs studied, only circRNA-0026 (hsa_circ_0000026) exhibited significantly different expression in GC (2.8-fold, P=0.001). Furthermore, online Database for Annotation, Visualization and Integrated Discovery annotation was used to predict circRNA-targeted miRNA-gene interactions. The analysis revealed that circRNA-0026 may regulate RNA transcription, RNA metabolism, gene expression, gene silencing and other biological functions in GC. In conclusion, differential expression of circRNAs may be associated with GC tumorigenesis, and circRNA-0026 is a promising biomarker for GC diagnosis and targeted therapy. PMID:28737829
Lum, Jeremy S; Fernandez, Francesca; Matosin, Natalie; Andrews, Jessica L; Huang, Xu-Feng; Ooi, Lezanne; Newell, Kelly A
2016-10-10
Group 1 metabotropic glutamate receptors (mGluR1/mGluR5) play an integral role in neurodevelopment and are implicated in psychiatric disorders, such as schizophrenia. mGluR1 and mGluR5 are expressed as homodimers, which is important for their functionality and pharmacology. We examined the protein expression of dimeric and monomeric mGluR1α and mGluR5 in the prefrontal cortex (PFC) and hippocampus throughout development (juvenile/adolescence/adulthood) and in the perinatal phencyclidine (PCP) model of schizophrenia. Under control conditions, mGluR1α dimer expression increased between juvenile and adolescence (209-328%), while monomeric levels remained consistent. Dimeric mGluR5 was steadily expressed across all time points; monomeric mGluR5 was present in juveniles, dramatically declining at adolescence and adulthood (-97-99%). The mGluR regulators, Homer 1b/c and Norbin, significantly increased with age in the PFC and hippocampus. Perinatal PCP treatment significantly increased juvenile dimeric mGluR5 levels in the PFC and hippocampus (37-50%) but decreased hippocampal mGluR1α (-50-56%). Perinatal PCP treatment also reduced mGluR1α dimer levels in the PFC at adulthood (-31%). These results suggest that Group 1 mGluRs have distinct dimeric and monomeric neurodevelopmental patterns, which may impact their pharmacological profiles at specific ages. Perinatal PCP treatment disrupted the early expression of Group 1 mGluRs which may underlie neurodevelopmental alterations observed in this model.
An emerging cyberinfrastructure for biodefense pathogen and pathogen-host data.
Zhang, C; Crasta, O; Cammer, S; Will, R; Kenyon, R; Sullivan, D; Yu, Q; Sun, W; Jha, R; Liu, D; Xue, T; Zhang, Y; Moore, M; McGarvey, P; Huang, H; Chen, Y; Zhang, J; Mazumder, R; Wu, C; Sobral, B
2008-01-01
The NIAID-funded Biodefense Proteomics Resource Center (RC) provides storage, dissemination, visualization and analysis capabilities for the experimental data deposited by seven Proteomics Research Centers (PRCs). The data and its publication is to support researchers working to discover candidates for the next generation of vaccines, therapeutics and diagnostics against NIAID's Category A, B and C priority pathogens. The data includes transcriptional profiles, protein profiles, protein structural data and host-pathogen protein interactions, in the context of the pathogen life cycle in vivo and in vitro. The database has stored and supported host or pathogen data derived from Bacillus, Brucella, Cryptosporidium, Salmonella, SARS, Toxoplasma, Vibrio and Yersinia, human tissue libraries, and mouse macrophages. These publicly available data cover diverse data types such as mass spectrometry, yeast two-hybrid (Y2H), gene expression profiles, X-ray and NMR determined protein structures and protein expression clones. The growing database covers over 23 000 unique genes/proteins from different experiments and organisms. All of the genes/proteins are annotated and integrated across experiments using UniProt Knowledgebase (UniProtKB) accession numbers. The web-interface for the database enables searching, querying and downloading at the level of experiment, group and individual gene(s)/protein(s) via UniProtKB accession numbers or protein function keywords. The system is accessible at http://www.proteomicsresource.org/.
Dong, Yongbin; Wang, Qilei; Zhang, Long; Du, Chunguang; Xiong, Wenwei; Chen, Xinjian; Deng, Fei; Ma, Zhiyan; Qiao, Dahe; Hu, Chunhui; Ren, Yangliu; Li, Yuling
2015-01-01
The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize.
Du, Chunguang; Xiong, Wenwei; Chen, Xinjian; Deng, Fei; Ma, Zhiyan; Qiao, Dahe; Hu, Chunhui; Ren, Yangliu; Li, Yuling
2015-01-01
The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize. PMID:26587848
Colak, Dilek; Alaiya, Ayodele A; Kaya, Namik; Muiya, Nzioka P; AlHarazi, Olfat; Shinwari, Zakia; Andres, Editha; Dzimiri, Nduna
2016-01-01
The disease pathways leading to idiopathic dilated cardiomyopathy (DCM) are still elusive. The present study investigated integrated global transcriptional and translational changes in human DCM for disease biomarker discovery. We used identical myocardial tissues from five DCM hearts compared to five non-failing (NF) donor hearts for both transcriptome profiling using the ABI high-density oligonucleotide microarrays and proteome expression with One-Dimensional Nano Acquity liquid chromatography coupled with tandem mass spectrometry on the Synapt G2 system. We identified 1262 differentially expressed genes (DEGs) and 269 proteins (DEPs) between DCM cases and healthy controls. Among the most significantly upregulated (>5-fold) proteins were GRK5, APOA2, IGHG3, ANXA6, HSP90AA1, and ATP5C1 (p< 0.01). On the other hand, the most significantly downregulated proteins were GSTM5, COX17, CAV1 and ANXA3. At least ten entities were concomitantly upregulated on the two analysis platforms: GOT1, ALDH4A1, PDHB, BDH1, SLC2A11, HSP90AA1, HSP90AB1, H2AFV, HSPA5 and NDUFV1. Gene ontology analyses of DEGs and DEPs revealed significant overlap with enrichment of genes/proteins related to metabolic process, biosynthetic process, cellular component organization, oxidative phosphorylation, alterations in glycolysis and ATP synthesis, Alzheimer's disease, chemokine-mediated inflammation and cytokine signalling pathways. The concomitant use of transcriptome and proteome expression to evaluate global changes in DCM has led to the identification of sixteen commonly altered entities as well as novel genes, proteins and pathways whose cardiac functions have yet to be deciphered. This data should contribute towards better management of the disease.
Liu, Jiangang; Wang, Dapeng; Li, Yanyan; Yao, Hui; Zhang, Nan; Zhang, Xuewen; Zhong, Fangping; Huang, Yulun
2018-06-01
The human pituitary tumor-transforming gene is an oncogenic protein which serves as a central hub in the cellular signaling network of medulloblastoma. The protein contains two vicinal PxxP motifs at its C terminus that are potential binding sites of peptide-recognition SH3 domains. Here, a synthetic protocol that integrated in silico analysis and in vitro assay was described to identify the SH3-binding partners of pituitary tumor-transforming gene in the gene expression profile of medulloblastoma. In the procedure, a variety of structurally diverse, non-redundant SH3 domains with high gene expression in medulloblastoma were compiled, and their three-dimensional structures were either manually retrieved from the protein data bank database or computationally modeled through bioinformatics technique. The binding capability of these domains towards the two PxxP-containing peptides m1p: 161 LGPPSPVK 168 and m2p: 168 KMPSPPWE 175 of pituitary tumor-transforming gene were ranked by structure-based scoring and fluorescence-based assay. Consequently, a number of SH3 domains, including MAP3K and PI3K, were found to have moderate or high affinity for m1p and/or m2p. Interestingly, the two overlapping peptides exhibits a distinct binding profile to these identified domain partners, suggesting that the binding selectivity of m1p and m2p is optimized across the medulloblastoma expression spectrum by competing for domain candidates. In addition, two redesigned versions of m1p peptide ware obtained via a structure-based rational mutation approach, which exhibited an increased affinity for the domain as compared to native peptide.
Ponce, Ninez A; Ko, Michelle; Liang, Su-Ying; Armstrong, Joanne; Toscano, Michele; Chanfreau-Coffinier, Catherine; Haas, Jennifer S
2015-04-01
With the Affordable Care Act reducing coverage disparities, social factors could prominently determine where and for whom innovations first diffuse in health care markets. Gene expression profiling is a potentially cost-effective innovation that guides chemotherapy decisions in early-stage breast cancer, but adoption has been uneven across the United States. Using a sample of commercially insured women, we evaluated whether income inequality in metropolitan areas was associated with receipt of gene expression profiling during its initial diffusion in 2006-07. In areas with high income inequality, gene expression profiling receipt was higher than elsewhere, but it was associated with a 10.6-percentage-point gap between high- and low-income women. In areas with low rates of income inequality, gene expression profiling receipt was lower, with no significant differences by income. Even among insured women, income inequality may indirectly shape diffusion of gene expression profiling, with benefits accruing to the highest-income patients in the most unequal places. Policies reducing gene expression profiling disparities should address low-inequality areas and, in unequal places, practice settings serving low-income patients. Project HOPE—The People-to-People Health Foundation, Inc.
Safe Genetic Modification of Cardiac Stem Cells Using a Site-Specific Integration Technique
Lan, Feng; Liu, Junwei; Narsinh, Kazim H.; Hu, Shijun; Han, Leng; Lee, Andrew S.; Karow, Marisa; Nguyen, Patricia K.; Nag, Divya; Calos, Michele P.; Robbins, Robert C.; Wu, Joseph C.
2012-01-01
Background Human cardiac progenitor cells (hCPCs) are a promising cell source for regenerative repair after myocardial infarction. Exploitation of their full therapeutic potential may require stable genetic modification of the cells ex vivo. Safe genetic engineering of stem cells, using facile methods for site-specific integration of transgenes into known genomic contexts, would significantly enhance the overall safety and efficacy of cellular therapy in a variety of clinical contexts. Methods and Results We employed the phiC31 site-specific recombinase to achieve targeted integration of a triple fusion reporter gene into a known chromosomal context in hCPCs and human endothelial cells (hECs). Stable expression of the reporter gene from its unique chromosomal integration site resulted in no discernible genomic instability or adverse changes in cell phenotype. Namely, phiC31-modified hCPCs were unchanged in their differentiation propensity, cellular proliferative rate, and global gene expression profile when compared to unaltered control hCPCs. Expression of the triple fusion reporter gene enabled multimodal assessment of cell fate in vitro and in vivo using fluorescence microscopy, bioluminescence imaging (BLI), and positron emission tomography (PET). Intramyocardial transplantation of genetically modified hCPCs resulted in significant improvement in myocardial function two weeks after cell delivery, as assessed by echocardiography (P = 0.002) and magnetic resonance imaging (P = 0.001). We also demonstrated the feasibility and therapeutic efficacy of genetically modifying differentiated hECs, which enhanced hindlimb perfusion (P<0.05 at day 7 and 14 after transplantation) on laser Doppler imaging. Conclusions The phiC31 integrase genomic modification system is a safe, efficient tool to enable site-specific integration of reporter transgenes in progenitor and differentiated cell types. PMID:22965984
Safe genetic modification of cardiac stem cells using a site-specific integration technique.
Lan, Feng; Liu, Junwei; Narsinh, Kazim H; Hu, Shijun; Han, Leng; Lee, Andrew S; Karow, Marisa; Nguyen, Patricia K; Nag, Divya; Calos, Michele P; Robbins, Robert C; Wu, Joseph C
2012-09-11
Human cardiac progenitor cells (hCPCs) are a promising cell source for regenerative repair after myocardial infarction. Exploitation of their full therapeutic potential may require stable genetic modification of the cells ex vivo. Safe genetic engineering of stem cells, using facile methods for site-specific integration of transgenes into known genomic contexts, would significantly enhance the overall safety and efficacy of cellular therapy in a variety of clinical contexts. We used the phiC31 site-specific recombinase to achieve targeted integration of a triple fusion reporter gene into a known chromosomal context in hCPCs and human endothelial cells. Stable expression of the reporter gene from its unique chromosomal integration site resulted in no discernible genomic instability or adverse changes in cell phenotype. Namely, phiC31-modified hCPCs were unchanged in their differentiation propensity, cellular proliferative rate, and global gene expression profile when compared with unaltered control hCPCs. Expression of the triple fusion reporter gene enabled multimodal assessment of cell fate in vitro and in vivo using fluorescence microscopy, bioluminescence imaging, and positron emission tomography. Intramyocardial transplantation of genetically modified hCPCs resulted in significant improvement in myocardial function 2 weeks after cell delivery, as assessed by echocardiography (P=0.002) and MRI (P=0.001). We also demonstrated the feasibility and therapeutic efficacy of genetically modifying differentiated human endothelial cells, which enhanced hind limb perfusion (P<0.05 at day 7 and 14 after transplantation) on laser Doppler imaging. The phiC31 integrase genomic modification system is a safe, efficient tool to enable site-specific integration of reporter transgenes in progenitor and differentiated cell types.
Srivastava, A. K.; Ramaswamy, N. K.; Mukopadhyaya, R.; Jincy, M. G. Chiramal; D'Souza, S. F.
2009-01-01
Background and Aims Large areas of the globe are becoming saline due to evapotranspiration and poor irrigation practices, and sustainability of agriculture is being seriously affected. Thiourea (TU) has been identified as an effective bioregulator imparting stress tolerance to crops. The molecular mechanisms involved in the TU-mediated response are considered in this study. Methods Differential display was performed in order to identify TU-modulated transcripts in Brassica juncea seeds exposed to various treatments (distilled water; 1 m NaCl; 1 m NaCl + 500 p.p.m. TU). The differential regulation of these transcripts was validated by quantitative real-time PCR. Key Results Thiourea treatment maintained the viability of seeds exposed to NaCl for 6 h. Expression analysis showed that the transcript level of alpha, beta, gamma, delta and epsilon subunits of mitochondrial ATPase (mtATPase) varied in seeds subjected to the different treatments for 1 h: expression level was significantly altered by 1 m NaCl relative to controls; however, in the NaCl + TU treatment it reverted back in an integrated manner. Similar results were obtained from time-kinetics studies of beta and delta subunits in roots of 8-d-old seedlings. These observations were also confirmed by the mtATPase activity from isolated mitochondria. The reversal in the expression and activity profile of mtATPase through the application of a bioregulator such as TU is a novel finding for any plant system. Conclusions The results suggest that TU treatment maintains the integrity and functioning of mitochondria in seeds as well as seedlings exposed to salinity. Thus, TU has the potential to be used as an effective bioregulator to impart salinity tolerance under field conditions, and might prove to be of high economic importance by opening new avenues for both basic and applied research. PMID:19033283
Knowledge-driven genomic interactions: an application in ovarian cancer.
Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D
2014-01-01
Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.
Investigation of candidate genes for osteoarthritis based on gene expression profiles.
Dong, Shuanghai; Xia, Tian; Wang, Lei; Zhao, Qinghua; Tian, Jiwei
2016-12-01
To explore the mechanism of osteoarthritis (OA) and provide valid biological information for further investigation. Gene expression profile of GSE46750 was downloaded from Gene Expression Omnibus database. The Linear Models for Microarray Data (limma) package (Bioconductor project, http://www.bioconductor.org/packages/release/bioc/html/limma.html) was used to identify differentially expressed genes (DEGs) in inflamed OA samples. Gene Ontology function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were performed based on Database for Annotation, Visualization and Integrated Discovery data, and protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins database. Regulatory network was screened based on Encyclopedia of DNA Elements. Molecular Complex Detection was used for sub-network screening. Two sub-networks with highest node degree were integrated with transcriptional regulatory network and KEGG functional enrichment analysis was processed for 2 modules. In total, 401 up- and 196 down-regulated DEGs were obtained. Up-regulated DEGs were involved in inflammatory response, while down-regulated DEGs were involved in cell cycle. PPI network with 2392 protein interactions was constructed. Moreover, 10 genes including Interleukin 6 (IL6) and Aurora B kinase (AURKB) were found to be outstanding in PPI network. There are 214 up- and 8 down-regulated transcription factor (TF)-target pairs in the TF regulatory network. Module 1 had TFs including SPI1, PRDM1, and FOS, while module 2 contained FOSL1. The nodes in module 1 were enriched in chemokine signaling pathway, while the nodes in module 2 were mainly enriched in cell cycle. The screened DEGs including IL6, AGT, and AURKB might be potential biomarkers for gene therapy for OA by being regulated by TFs such as FOS and SPI1, and participating in the cell cycle and cytokine-cytokine receptor interaction pathway. Copyright © 2016 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.
Lemieux, Sebastien; Sargeant, Tobias; Laperrière, David; Ismail, Houssam; Boucher, Geneviève; Rozendaal, Marieke; Lavallée, Vincent-Philippe; Ashton-Beaucage, Dariel; Wilhelm, Brian; Hébert, Josée; Hilton, Douglas J; Mader, Sylvie; Sauvageau, Guy
2017-07-27
Genome-wide transcriptome profiling has enabled non-supervised classification of tumours, revealing different sub-groups characterized by specific gene expression features. However, the biological significance of these subtypes remains for the most part unclear. We describe herein an interactive platform, Minimum Spanning Trees Inferred Clustering (MiSTIC), that integrates the direct visualization and comparison of the gene correlation structure between datasets, the analysis of the molecular causes underlying co-variations in gene expression in cancer samples, and the clinical annotation of tumour sets defined by the combined expression of selected biomarkers. We have used MiSTIC to highlight the roles of specific transcription factors in breast cancer subtype specification, to compare the aspects of tumour heterogeneity targeted by different prognostic signatures, and to highlight biomarker interactions in AML. A version of MiSTIC preloaded with datasets described herein can be accessed through a public web server (http://mistic.iric.ca); in addition, the MiSTIC software package can be obtained (github.com/iric-soft/MiSTIC) for local use with personalized datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
A Novel Role of Periostin in Postnatal Tooth Formation and Mineralization*
Ma, Dedong; Zhang, Rong; Sun, Yao; Rios, Hector F.; Haruyama, Naoto; Han, Xianglong; Kulkarni, Ashok B.; Qin, Chunlin; Feng, Jian Q.
2011-01-01
Periostin plays multiple functions during development. Our previous work showed a critical role of this disulfide-linked cell adhesion protein in maintenance of periodontium integrity in response to occlusal load. In this study, we attempted to address whether this mechanical response molecule played a direct role in postnatal tooth development. Our key findings are 1) periostin is expressed in preodontoblasts, and odontoblasts; and the periostin-null incisor displayed a massive increase in dentin formation after mastication; 2) periostin is also expressed in the ameloblast cells, and an enamel defect is identified in both the adult-null incisor and molar; 3) deletion of periostin leads to changes in expression profiles of many non-collagenous protein such as DSPP, DMP1, BSP, and OPN in incisor dentin; 4) the removal of a biting force leads to reduction of mineralization, which is partially prevented in periostin-null mice; and 6) both in vitro and in vivo data revealed a direct regulation of periostin by TGF-β1 in dentin formation. In conclusion, periostin plays a novel direct role in controlling postnatal tooth formation, which is required for the integrity of both enamel and dentin. PMID:21131362
A Cas9-based toolkit to program gene expression in Saccharomyces cerevisiae
Reider Apel, Amanda; d'Espaux, Leo; Wehrs, Maren; ...
2016-11-28
Despite the extensive use of Saccharomyces cerevisiae as a platform for synthetic biology, strain engineering remains slow and laborious. Here, we employ CRISPR/Cas9 technology to build a cloning-free toolkit that addresses commonly encountered obstacles in metabolic engineering, including chromosomal integration locus and promoter selection, as well as protein localization and solubility. The toolkit includes 23 Cas9-sgRNA plasmids, 37 promoters of various strengths and temporal expression profiles, and 10 protein-localization, degradation and solubility tags. We facilitated the use of these parts via a web-based tool, that automates the generation of DNA fragments for integration. Our system builds upon existing gene editingmore » methods in the thoroughness with which the parts are standardized and characterized, the types and number of parts available and the ease with which our methodology can be used to perform genetic edits in yeast. We demonstrated the applicability of this toolkit by optimizing the expression of a challenging but industrially important enzyme, taxadiene synthase (TXS). This approach enabled us to diagnose an issue with TXS solubility, the resolution of which yielded a 25-fold improvement in taxadiene production.« less
A Cas9-based toolkit to program gene expression in Saccharomyces cerevisiae
DOE Office of Scientific and Technical Information (OSTI.GOV)
Reider Apel, Amanda; d'Espaux, Leo; Wehrs, Maren
Despite the extensive use of Saccharomyces cerevisiae as a platform for synthetic biology, strain engineering remains slow and laborious. Here, we employ CRISPR/Cas9 technology to build a cloning-free toolkit that addresses commonly encountered obstacles in metabolic engineering, including chromosomal integration locus and promoter selection, as well as protein localization and solubility. The toolkit includes 23 Cas9-sgRNA plasmids, 37 promoters of various strengths and temporal expression profiles, and 10 protein-localization, degradation and solubility tags. We facilitated the use of these parts via a web-based tool, that automates the generation of DNA fragments for integration. Our system builds upon existing gene editingmore » methods in the thoroughness with which the parts are standardized and characterized, the types and number of parts available and the ease with which our methodology can be used to perform genetic edits in yeast. We demonstrated the applicability of this toolkit by optimizing the expression of a challenging but industrially important enzyme, taxadiene synthase (TXS). This approach enabled us to diagnose an issue with TXS solubility, the resolution of which yielded a 25-fold improvement in taxadiene production.« less
White-Al Habeeb, Nicole M A; Ho, Linh T; Olkhov-Mitsel, Ekaterina; Kron, Ken; Pethe, Vaijayanti; Lehman, Melanie; Jovanovic, Lidija; Fleshner, Neil; van der Kwast, Theodorus; Nelson, Colleen C; Bapat, Bharati
2014-09-15
Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2'-deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.
Wei, Pi-Jing; Zhang, Di; Xia, Junfeng; Zheng, Chun-Hou
2016-12-23
Cancer is a complex disease which is characterized by the accumulation of genetic alterations during the patient's lifetime. With the development of the next-generation sequencing technology, multiple omics data, such as cancer genomic, epigenomic and transcriptomic data etc., can be measured from each individual. Correspondingly, one of the key challenges is to pinpoint functional driver mutations or pathways, which contributes to tumorigenesis, from millions of functional neutral passenger mutations. In this paper, in order to identify driver genes effectively, we applied a generalized additive model to mutation profiles to filter genes with long length and constructed a new gene-gene interaction network. Then we integrated the mutation data and expression data into the gene-gene interaction network. Lastly, greedy algorithm was used to prioritize candidate driver genes from the integrated data. We named the proposed method Length-Net-Driver (LNDriver). Experiments on three TCGA datasets, i.e., head and neck squamous cell carcinoma, kidney renal clear cell carcinoma and thyroid carcinoma, demonstrated that the proposed method was effective. Also, it can identify not only frequently mutated drivers, but also rare candidate driver genes.
Yang, Mei; Wang, Danhua; Yu, Lingxiang; Guo, Chaonan; Guo, Xiaodong; Lin, Na
2013-01-01
Aim To screen novel markers for hepatocellular carcinoma (HCC) by a combination of expression profile, interaction network analysis and clinical validation. Methods HCC significant molecules which are differentially expressed or had genetic variations in HCC tissues were obtained from five existing HCC related databases (OncoDB.HCC, HCC.net, dbHCCvar, EHCO and Liverome). Then, the protein-protein interaction (PPI) network of these molecules was constructed. Three topological features of the network ('Degree', 'Betweenness', and 'Closeness') and the k-core algorithm were used to screen candidate HCC markers which play crucial roles in tumorigenesis of HCC. Furthermore, the clinical significance of two candidate HCC markers growth factor receptor-bound 2 (GRB2) and GRB2-associated-binding protein 1 (GAB1) was validated. Results In total, 6179 HCC significant genes and 977 HCC significant proteins were collected from existing HCC related databases. After network analysis, 331 candidate HCC markers were identified. Especially, GAB1 has the highest k-coreness suggesting its central localization in HCC related network, and the interaction between GRB2 and GAB1 has the largest edge-betweenness implying it may be biologically important to the function of HCC related network. As the results of clinical validation, the expression levels of both GRB2 and GAB1 proteins were significantly higher in HCC tissues than those in their adjacent nonneoplastic tissues. More importantly, the combined GRB2 and GAB1 protein expression was significantly associated with aggressive tumor progression and poor prognosis in patients with HCC. Conclusion This study provided an integrative analysis by combining expression profile and interaction network analysis to identify a list of biologically significant HCC related markers and pathways. Further experimental validation indicated that the aberrant expression of GRB2 and GAB1 proteins may be strongly related to tumor progression and prognosis in patients with HCC. The overexpression of GRB2 in combination with upregulation of GAB1 may be an unfavorable prognostic factor for HCC. PMID:24391994
NASA Astrophysics Data System (ADS)
Xu, Dan; Sun, Yeqing; Gao, Ying; Xing, Yanfang
microRNAs (miRNAs) is reported to be sensitive to radiation exposure and altered gravity, involved in a variety of biological processes through negative regulation of gene expression. Dystrophin-like dys-1 gene is expressed and required in muscle tissue, which plays a vital role in mechanical transduction when gravity varies. In the present study, we investigated the effect of dys-1 mutation on miRNA expression profile in Caenorhabditis elegans (C. elegans) under space radiation associated with microgravity (R+M) and radiation alone (R) environment during Shenzhou-8 mission. We performed miRNA microarray analysis in dys-1 mutant and wide-type (WT) of dauer larvae and found that 27 miRNAs changed in abundance after spaceflight. Compared with WT, there was different miRNA expression pattern in different treatments in dys-1 mutant. Cel-miR-796 and miR-124 were reversely expressed under R+M and R environment in WT and dys-1 mutant, respectively, indicating they might be affected by microgravity. Mutation of dys-1 remarkably reduced the number of altered miRNAs under space environment, resulting in the decrease of genes in biological categories of “body morphogenesis”, “behavior”, “cell adhesion” and so on. Particularly, we found that those genes controlling regulation of locomotion in WT were lost in dys-1 mutant, while genes in positive regulation of developmental process only existed in dys-1 mutant. miR-796 was predicted to target genes ace-1 and dyc-1 that are functionally linked to dys-1. Integration analysis of miRNA and mRNA expression profile revealed that miR-56 and miR-124 were involved in behavior and locomotion by regulating different target genes under space environment, among which nep-11, deb-1, C07H4.1 and F11H8.2 might be associated with neuromuscular system. Our findings suggest that dys-1 could cause alteration of miRNAs and target genes, involved in regulating the response of C. elegans to space microgravity in neuromuscular system. This research will provide new insight for better understanding of the mechanism in microgravity-induced muscular dystrophy.
Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio
2018-01-01
Most of the research studies developed applying microarray technology to the characterization of different pathological states of any disease may fail in reaching statistically significant results. This is largely due to the small repertoire of analysed samples, and to the limitation in the number of states or pathologies usually addressed. Moreover, the influence of potential deviations on the gene expression quantification is usually disregarded. In spite of the continuous changes in omic sciences, reflected for instance in the emergence of new Next-Generation Sequencing-related technologies, the existing availability of a vast amount of gene expression microarray datasets should be properly exploited. Therefore, this work proposes a novel methodological approach involving the integration of several heterogeneous skin cancer series, and a later multiclass classifier design. This approach is thus a way to provide the clinicians with an intelligent diagnosis support tool based on the use of a robust set of selected biomarkers, which simultaneously distinguishes among different cancer-related skin states. To achieve this, a multi-platform combination of microarray datasets from Affymetrix and Illumina manufacturers was carried out. This integration is expected to strengthen the statistical robustness of the study as well as the finding of highly-reliable skin cancer biomarkers. Specifically, the designed operation pipeline has allowed the identification of a small subset of 17 differentially expressed genes (DEGs) from which to distinguish among 7 involved skin states. These genes were obtained from the assessment of a number of potential batch effects on the gene expression data. The biological interpretation of these genes was inspected in the specific literature to understand their underlying information in relation to skin cancer. Finally, in order to assess their possible effectiveness in cancer diagnosis, a cross-validation Support Vector Machines (SVM)-based classification including feature ranking was performed. The accuracy attained exceeded the 92% in overall recognition of the 7 different cancer-related skin states. The proposed integration scheme is expected to allow the co-integration with other state-of-the-art technologies such as RNA-seq.
Debey-Pascher, Svenja; Hofmann, Andrea; Kreusch, Fatima; Schuler, Gerold; Schuler-Thurner, Beatrice; Schultze, Joachim L.; Staratschek-Jox, Andrea
2011-01-01
Microarray-based transcriptome analysis of peripheral blood as surrogate tissue has become an important approach in clinical implementations. However, application of gene expression profiling in routine clinical settings requires careful consideration of the influence of sample handling and RNA isolation methods on gene expression profile outcome. We evaluated the effect of different sample preservation strategies (eg, cryopreservation of peripheral blood mononuclear cells or freezing of PAXgene-stabilized whole blood samples) on gene expression profiles. Expression profiles obtained from cryopreserved peripheral blood mononuclear cells differed substantially from those of their nonfrozen counterpart samples. Furthermore, expression profiles in cryopreserved peripheral blood mononuclear cell samples were found to undergo significant alterations with increasing storage period, whereas long-term freezing of PAXgene RNA stabilized whole blood samples did not significantly affect stability of gene expression profiles. This report describes important technical aspects contributing toward the establishment of robust and reliable guidance for gene expression studies using peripheral blood and provides a promising strategy for reliable implementation in routine handling for diagnostic purposes. PMID:21704280
Titulaer, Mark K; Siccama, Ivar; Dekker, Lennard J; van Rijswijk, Angelique LCT; Heeren, Ron MA; Sillevis Smitt, Peter A; Luider, Theo M
2006-01-01
Background Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest. Results A new database application is presented, to detect and identify significantly differentially expressed peptides in peptide profiles obtained from body fluids of patient and control groups. The presented modular software is capable of central storage of mass spectra and results in fast analysis. The software architecture consists of 4 pillars, 1) a Graphical User Interface written in Java, 2) a MySQL database, which contains all metadata, such as experiment numbers and sample codes, 3) a FTP (File Transport Protocol) server to store all raw mass spectrometry files and processed data, and 4) the software package R, which is used for modular statistical calculations, such as the Wilcoxon-Mann-Whitney rank sum test. Statistic analysis by the Wilcoxon-Mann-Whitney test in R demonstrates that peptide-profiles of two patient groups 1) breast cancer patients with leptomeningeal metastases and 2) prostate cancer patients in end stage disease can be distinguished from those of control groups. Conclusion The database application is capable to distinguish patient Matrix Assisted Laser Desorption Ionization (MALDI-TOF) peptide profiles from control groups using large size datasets. The modular architecture of the application makes it possible to adapt the application to handle also large sized data from MS/MS- and Fourier Transform Ion Cyclotron Resonance (FT-ICR) mass spectrometry experiments. It is expected that the higher resolution and mass accuracy of the FT-ICR mass spectrometry prevents the clustering of peaks of different peptides and allows the identification of differentially expressed proteins from the peptide profiles. PMID:16953879
Titulaer, Mark K; Siccama, Ivar; Dekker, Lennard J; van Rijswijk, Angelique L C T; Heeren, Ron M A; Sillevis Smitt, Peter A; Luider, Theo M
2006-09-05
Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest. A new database application is presented, to detect and identify significantly differentially expressed peptides in peptide profiles obtained from body fluids of patient and control groups. The presented modular software is capable of central storage of mass spectra and results in fast analysis. The software architecture consists of 4 pillars, 1) a Graphical User Interface written in Java, 2) a MySQL database, which contains all metadata, such as experiment numbers and sample codes, 3) a FTP (File Transport Protocol) server to store all raw mass spectrometry files and processed data, and 4) the software package R, which is used for modular statistical calculations, such as the Wilcoxon-Mann-Whitney rank sum test. Statistic analysis by the Wilcoxon-Mann-Whitney test in R demonstrates that peptide-profiles of two patient groups 1) breast cancer patients with leptomeningeal metastases and 2) prostate cancer patients in end stage disease can be distinguished from those of control groups. The database application is capable to distinguish patient Matrix Assisted Laser Desorption Ionization (MALDI-TOF) peptide profiles from control groups using large size datasets. The modular architecture of the application makes it possible to adapt the application to handle also large sized data from MS/MS- and Fourier Transform Ion Cyclotron Resonance (FT-ICR) mass spectrometry experiments. It is expected that the higher resolution and mass accuracy of the FT-ICR mass spectrometry prevents the clustering of peaks of different peptides and allows the identification of differentially expressed proteins from the peptide profiles.
Abdel-Wahab, May; Rengan, Ramesh; Curran, Bruce; Swerdloff, Stuart; Miettinen, Mika; Field, Colin; Ranjitkar, Sunita; Palta, Jatinder; Tripuraneni, Prabhakar
2010-02-01
To describe the processes and benefits of the integrating healthcare enterprises in radiation oncology (IHE-RO). The IHE-RO process includes five basic steps. The first step is to identify common interoperability issues encountered in radiation treatment planning and the delivery process. IHE-RO committees partner with vendors to develop solutions (integration profiles) to interoperability problems. The broad application of these integration profiles across a variety of vender platforms is tested annually at the Connectathon event. Demonstration of the seamless integration and transfer of patient data to the potential users are then presented by vendors at the public demonstration event. Users can then integrate these profiles into requests for proposals and vendor contracts by institutions. Incorporation of completed integration profiles into requests for proposals can be done when purchasing new equipment. Vendors can publish IHE integration statements to document the integration profiles supported by their products. As a result, users can reference integration profiles in requests for proposals, simplifying the systems acquisition process. These IHE-RO solutions are now available in many of the commercial radiation oncology-related treatment planning, delivery, and information systems. They are also implemented at cancer care sites around the world. IHE-RO serves an important purpose for the radiation oncology community at large. Copyright 2010 Elsevier Inc. All rights reserved.
Integrative Approach to Pain Genetics Identifies Pain Sensitivity Loci across Diseases
Ruau, David; Dudley, Joel T.; Chen, Rong; Phillips, Nicholas G.; Swan, Gary E.; Lazzeroni, Laura C.; Clark, J. David
2012-01-01
Identifying human genes relevant for the processing of pain requires difficult-to-conduct and expensive large-scale clinical trials. Here, we examine a novel integrative paradigm for data-driven discovery of pain gene candidates, taking advantage of the vast amount of existing disease-related clinical literature and gene expression microarray data stored in large international repositories. First, thousands of diseases were ranked according to a disease-specific pain index (DSPI), derived from Medical Subject Heading (MESH) annotations in MEDLINE. Second, gene expression profiles of 121 of these human diseases were obtained from public sources. Third, genes with expression variation significantly correlated with DSPI across diseases were selected as candidate pain genes. Finally, selected candidate pain genes were genotyped in an independent human cohort and prospectively evaluated for significant association between variants and measures of pain sensitivity. The strongest signal was with rs4512126 (5q32, ABLIM3, P = 1.3×10−10) for the sensitivity to cold pressor pain in males, but not in females. Significant associations were also observed with rs12548828, rs7826700 and rs1075791 on 8q22.2 within NCALD (P = 1.7×10−4, 1.8×10−4, and 2.2×10−4 respectively). Our results demonstrate the utility of a novel paradigm that integrates publicly available disease-specific gene expression data with clinical data curated from MEDLINE to facilitate the discovery of pain-relevant genes. This data-derived list of pain gene candidates enables additional focused and efficient biological studies validating additional candidates. PMID:22685391
Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L.; Roberts, Brian S.; Arthur, William T.; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing
2014-01-01
Background Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. Results We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Conclusion Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells. PMID:24651522
Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing
2014-01-01
Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.
Gan, Lin; Denecke, Bernd
2013-01-01
Mature microRNA is a crucial component in the gene expression regulation network. At the same time, microRNA gene expression and procession is regulated in a precise and collaborated way. Pre-microRNAs mediate products during the microRNA transcription process, they can provide hints of microRNA gene expression regulation or can serve as alternative biomarkers. To date, little effort has been devoted to pre-microRNA expression profiling. In this study, three human and three mouse microRNA profile data sets, based on the Affymetrix miRNA 2.0 array, have been re-analyzed for both mature and pre-microRNA signals as a primary test of parallel mature/pre-microRNA expression profiling on a single platform. The results not only demonstrated a glimpse of pre-microRNA expression in human and mouse, but also the relationship of microRNA expressions between pre- and mature forms. The study also showed a possible application of currently available microRNA microarrays in profiling pre-microRNA expression in a time and cost effective manner. PMID:27605179
2013-01-01
Background Qualitative alterations or abnormal expression of microRNAs (miRNAs) in colon cancer have mainly been demonstrated in primary tumors. Poorly overlapping sets of oncomiRs, tumor suppressor miRNAs and metastamiRs have been linked with distinct stages in the progression of colorectal cancer. To identify changes in both miRNA and gene expression levels among normal colon mucosa, primary tumor and liver metastasis samples, and to classify miRNAs into functional networks, in this work miRNA and gene expression profiles in 158 samples from 46 patients were analysed. Results Most changes in miRNA and gene expression levels had already manifested in the primary tumors while these levels were almost stably maintained in the subsequent primary tumor-to-metastasis transition. In addition, comparing normal tissue, tumor and metastasis, we did not observe general impairment or any rise in miRNA biogenesis. While only few mRNAs were found to be differentially expressed between primary colorectal carcinoma and liver metastases, miRNA expression profiles can classify primary tumors and metastases well, including differential expression of miR-10b, miR-210 and miR-708. Of 82 miRNAs that were modulated during tumor progression, 22 were involved in EMT. qRT-PCR confirmed the down-regulation of miR-150 and miR-10b in both primary tumor and metastasis compared to normal mucosa and of miR-146a in metastases compared to primary tumor. The upregulation of miR-201 in metastasis compared both with normal and primary tumour was also confirmed. A preliminary survival analysis considering differentially expressed miRNAs suggested a possible link between miR-10b expression in metastasis and patient survival. By integrating miRNA and target gene expression data, we identified a combination of interconnected miRNAs, which are organized into sub-networks, including several regulatory relationships with differentially expressed genes. Key regulatory interactions were validated experimentally. Specific mixed circuits involving miRNAs and transcription factors were identified and deserve further investigation. The suppressor activity of miR-182 on ENTPD5 gene was identified for the first time and confirmed in an independent set of samples. Conclusions Using a large dataset of CRC miRNA and gene expression profiles, we describe the interplay of miRNA groups in regulating gene expression, which in turn affects modulated pathways that are important for tumor development. PMID:23987127
Zhan, Jian-Wei; Jiao, De-Min; Wang, Yi; Song, Jia; Wu, Jin-Hong; Wu, Li-Jun; Chen, Qing-Yong; Ma, Sheng-Lin
2017-09-01
Curcumin (diferuloylmethane) has chemopreventive and therapeutic properties against many types of tumors, both in vitro and in vivo. Previous reports have shown that curcumin exhibits anti-invasive activities, but the mechanisms remain largely unclear. In this study, both microRNA (miRNA) and messenger RNA (mRNA) expression profiles were used to characterize the anti-metastasis mechanisms of curcumin in human non-small cell lung cancer A549 cell line. Microarray analysis revealed that 36 miRNAs were differentially expressed between the curcumin-treated and control groups. miR-330-5p exhibited maximum upregulation, while miR-25-5p exhibited maximum downregulation in the curcumin treatment group. mRNA expression profiles and functional analysis indicated that 226 differentially expressed mRNAs belonged to different functional categories. Significant pathway analysis showed that mitogen-activated protein kinase, transforming growth factor-β, and Wnt signaling pathways were significantly downregulated. At the same time, axon guidance, glioma, and ErbB tyrosine kinase receptor signaling pathways were significantly upregulated. We constructed a miRNA gene network that contributed to the curcumin inhibition of metastasis in lung cancer cells. let-7a-3p, miR-1262, miR-499a-5p, miR-1276, miR-331-5p, and miR-330-5p were identified as key microRNA regulators in the network. Finally, using miR-330-5p as an example, we confirmed the role of miR-330-5p in mediating the anti-migration effect of curcumin, suggesting the importance of miRNAs in the regulation of curcumin biological activity. Our findings provide new insights into the anti-metastasis mechanism of curcumin in lung cancer. © 2017 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.
Kapsimali, Marika; Kloosterman, Wigard P; de Bruijn, Ewart; Rosa, Frederic; Plasterk, Ronald HA; Wilson, Stephen W
2007-01-01
Background MicroRNA (miRNA) encoding genes are abundant in vertebrate genomes but very few have been studied in any detail. Bioinformatic tools allow prediction of miRNA targets and this information coupled with knowledge of miRNA expression profiles facilitates formulation of hypotheses of miRNA function. Although the central nervous system (CNS) is a prominent site of miRNA expression, virtually nothing is known about the spatial and temporal expression profiles of miRNAs in the brain. To provide an overview of the breadth of miRNA expression in the CNS, we performed a comprehensive analysis of the neuroanatomical expression profiles of 38 abundant conserved miRNAs in developing and adult zebrafish brain. Results Our results show miRNAs have a wide variety of different expression profiles in neural cells, including: expression in neuronal precursors and stem cells (for example, miR-92b); expression associated with transition from proliferation to differentiation (for example, miR-124); constitutive expression in mature neurons (miR-124 again); expression in both proliferative cells and their differentiated progeny (for example, miR-9); regionally restricted expression (for example, miR-222 in telencephalon); and cell-type specific expression (for example, miR-218a in motor neurons). Conclusion The data we present facilitate prediction of likely modes of miRNA function in the CNS and many miRNA expression profiles are consistent with the mutual exclusion mode of function in which there is spatial or temporal exclusion of miRNAs and their targets. However, some miRNAs, such as those with cell-type specific expression, are more likely to be co-expressed with their targets. Our data provide an important resource for future functional studies of miRNAs in the CNS. PMID:17711588
Hsu, Yi-Hsiang; Zillikens, M Carola; Wilson, Scott G; Farber, Charles R; Demissie, Serkalem; Soranzo, Nicole; Bianchi, Estelle N; Grundberg, Elin; Liang, Liming; Richards, J Brent; Estrada, Karol; Zhou, Yanhua; van Nas, Atila; Moffatt, Miriam F; Zhai, Guangju; Hofman, Albert; van Meurs, Joyce B; Pols, Huibert A P; Price, Roger I; Nilsson, Olle; Pastinen, Tomi; Cupples, L Adrienne; Lusis, Aldons J; Schadt, Eric E; Ferrari, Serge; Uitterlinden, André G; Rivadeneira, Fernando; Spector, Timothy D; Karasik, David; Kiel, Douglas P
2010-06-10
Osteoporosis is a complex disorder and commonly leads to fractures in elderly persons. Genome-wide association studies (GWAS) have become an unbiased approach to identify variations in the genome that potentially affect health. However, the genetic variants identified so far only explain a small proportion of the heritability for complex traits. Due to the modest genetic effect size and inadequate power, true association signals may not be revealed based on a stringent genome-wide significance threshold. Here, we take advantage of SNP and transcript arrays and integrate GWAS and expression signature profiling relevant to the skeletal system in cellular and animal models to prioritize the discovery of novel candidate genes for osteoporosis-related traits, including bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), as well as geometric indices of the hip (femoral neck-shaft angle, NSA; femoral neck length, NL; and narrow-neck width, NW). A two-stage meta-analysis of GWAS from 7,633 Caucasian women and 3,657 men, revealed three novel loci associated with osteoporosis-related traits, including chromosome 1p13.2 (RAP1A, p = 3.6x10(-8)), 2q11.2 (TBC1D8), and 18q11.2 (OSBPL1A), and confirmed a previously reported region near TNFRSF11B/OPG gene. We also prioritized 16 suggestive genome-wide significant candidate genes based on their potential involvement in skeletal metabolism. Among them, 3 candidate genes were associated with BMD in women. Notably, 2 out of these 3 genes (GPR177, p = 2.6x10(-13); SOX6, p = 6.4x10(-10)) associated with BMD in women have been successfully replicated in a large-scale meta-analysis of BMD, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of our prioritization strategy. In the absence of direct biological support for identified genes, we highlighted the efficiency of subsequent functional characterization using publicly available expression profiling relevant to the skeletal system in cellular or whole animal models to prioritize candidate genes for further functional validation.
Mishra, Pragya; Singh, Shweta; Rathinam, Maniraj; Nandiganti, Muralimohan; Ram Kumar, Nikhil; Thangaraj, Arulprakash; Thimmegowda, Vinutha; Krishnan, Veda; Mishra, Vagish; Jain, Neha; Rai, Vandna; Pattanayak, Debasis; Sreevathsa, Rohini
2017-02-22
Safety assessment of genetically modified plants is an important aspect prior to deregulation. Demonstration of substantial equivalence of the transgenics compared to their nontransgenic counterparts can be performed using different techniques at various molecular levels. The present study is a first-ever comprehensive evaluation of pigeon pea transgenics harboring two independent cry genes, cry2Aa and cry1AcF. The absence of unintended effects in the transgenic seed components was demonstrated by proteome and nutritional composition profiling. Analysis revealed that no significant differences were found in the various nutritional compositional analyses performed. Additionally, 2-DGE-based proteome analysis of the transgenic and nontransgenic seed protein revealed that there were no major changes in the protein profile, although a minor fold change in the expression of a few proteins was observed. Furthermore, the study also demonstrated that neither the integration of T-DNA nor the expression of the cry genes resulted in the production of unintended effects in the form of new toxins or allergens.
Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks
Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi
2014-01-01
Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481
Coudry, Renata A.; Meireles, Sibele I.; Stoyanova, Radka; Cooper, Harry S.; Carpino, Alan; Wang, Xianqun; Engstrom, Paul F.; Clapper, Margie L.
2007-01-01
The establishment of a reliable method for using RNA from formalin-fixed, paraffin-embedded (FFPE) tissue would provide an opportunity to obtain novel gene expression data from the vast amounts of archived tissue. A custom-designed 22,000 oligonucleotide array was used in the present study to compare the gene expression profile of colonic epithelial cells isolated by laser capture microdissection from FFPE-archived samples with that of the same cell population from matched frozen samples, the preferred source of RNA. Total RNA was extracted from FFPE tissues, amplified, and labeled using the Paradise Reagent System. The quality of the input RNA was assessed by the Bioanalyzer profile, reverse transcriptase-polymerase chain reaction, and agarose gel electrophoresis. The results demonstrate that it is possible to obtain reliable microarray data from FFPE samples using RNA acquired by laser capture microdissection. The concordance between matched FFPE and frozen samples was evaluated and expressed as a Pearson’s correlation coefficient, with values ranging from 0.80 to 0.97. The presence of ribosomal RNA peaks in FFPE-derived RNA was reflected by a high correlation with paired frozen samples. A set of practical recommendations for evaluating the RNA integrity and quality in FFPE samples is reported. PMID:17251338
Guzmán-Flores, Juan Manuel; Flores-Pérez, Elsa Cristina; Hernández-Ortiz, Magdalena; Vargas-Ortiz, Katya; Ramírez-Emiliano, Joel; Encarnación-Guevara, Sergio; Pérez-Vázquez, Victoriano
2018-06-01
Type 2 diabetes mellitus is characterized by insulin resistance in the liver. Insulin is not only involved in carbohydrate metabolism, it also regulates protein synthesis. This work describes the expression of proteins in the liver of a diabetic mouse and identifies the metabolic pathways involved. Twenty-week-old diabetic db/db mice were hepatectomized, after which proteins were separated by 2D-Polyacrylamide Gel Electrophoresis (2D-PAGE). Spots varying in intensity were analyzed using mass spectrometry, and biological function was assigned by the Database for Annotation, Visualization and Integrated Discovery (DAVID) software. A differential expression of 26 proteins was identified; among these were arginase-1, pyruvate carboxylase, peroxiredoxin-1, regucalcin, and sorbitol dehydrogenase. Bioinformatics analysis indicated that many of these proteins are mitochondrial and participate in metabolic pathways, such as the citrate cycle, the fructose and mannose metabolism, and glycolysis or gluconeogenesis. In addition, these proteins are related to oxidation⁻reduction reactions and molecular function of vitamin binding and amino acid metabolism. In conclusion, the proteomic profile of the liver of diabetic mouse db/db exhibited mainly alterations in the metabolism of carbohydrates and nitrogen. These differences illustrate the heterogeneity of diabetes in its different stages and under different conditions and highlights the need to improve treatments for this disease.
Xia, Shengjun; Chen, Yu; Jiang, Jiafu; Chen, Sumei; Guan, Zhiyong; Fang, Weimin; Chen, Fadi
2013-01-01
The molecular mechanisms underlying gravitropic bending of shoots are poorly understood and how genes related with this growing progress is still unclear. To identify genes related to asymmetric growth in the creeping shoots of chrysanthemum, suppression subtractive hybridization was used to visualize differential gene expression in the upper and lower halves of creeping shoots of ground-cover chrysanthemum under gravistimulation. Sequencing of 43 selected clones produced 41 unigenes (40 singletons and 1 unigenes), which were classifiable into 9 functional categories. A notable frequency of genes involve in cell wall biosynthesis up-regulated during gravistimulation in the upper side or lower side were found, such as beta tubulin (TUB), subtilisin-like protease (SBT), Glutathione S-transferase (GST), and expensing-like protein (EXP), lipid transfer proteins (LTPs), glycine-rich protein (GRP) and membrane proteins. Our findings also highlighted the function of some metal transporter during asymmetric growth, including the boron transporter (BT) and ZIP transporter (ZT), which were thought primarily for maintaining the integrity of cell walls and played important roles in cellulose biosynthesis. CmTUB (beta tubulin) was cloned, and the expression profile and phylogeny was examined, because the cytoskeleton of plant cells involved in the plant gravitropic bending growth is well known.
Mackeh, Rafah; Boughorbel, Sabri; Chaussabel, Damien; Kino, Tomoshige
2017-01-01
The collection of large-scale datasets available in public repositories is rapidly growing and providing opportunities to identify and fill gaps in different fields of biomedical research. However, users of these datasets should be able to selectively browse datasets related to their field of interest. Here we made available a collection of transcriptome datasets related to human follicular cells from normal individuals or patients with polycystic ovary syndrome, in the process of their development, during in vitro fertilization. After RNA-seq dataset exclusion and careful selection based on study description and sample information, 12 datasets, encompassing a total of 85 unique transcriptome profiles, were identified in NCBI Gene Expression Omnibus and uploaded to the Gene Expression Browser (GXB), a web application specifically designed for interactive query and visualization of integrated large-scale data. Once annotated in GXB, multiple sample grouping has been made in order to create rank lists to allow easy data interpretation and comparison. The GXB tool also allows the users to browse a single gene across multiple projects to evaluate its expression profiles in multiple biological systems/conditions in a web-based customized graphical views. The curated dataset is accessible at the following link: http://ivf.gxbsidra.org/dm3/landing.gsp.
Lindgren, Emma; Hägg, Sara; Giordano, Fosco; Björkegren, Johan; Ström, Lena
2014-01-01
Genome integrity is fundamental for cell survival and cell cycle progression. Important mechanisms for keeping the genome intact are proper sister chromatid segregation, correct gene regulation and efficient repair of damaged DNA. Cohesin and its DNA loader, the Scc2/4 complex have been implicated in all these cellular actions. The gene regulation role has been described in several organisms. In yeast it has been suggested that the proteins in the cohesin network would effect transcription based on its role as insulator. More recently, data are emerging indicating direct roles for gene regulation also in yeast. Here we extend these studies by investigating whether the cohesin loader Scc2 is involved in regulation of gene expression. We performed global gene expression profiling in the absence and presence of DNA damage, in wild type and Scc2 deficient G2/M arrested cells, when it is known that Scc2 is important for DNA double strand break repair and formation of damage induced cohesion. We found that not only the DNA damage specific transcriptional response is distorted after inactivation of Scc2 but also the overall transcription profile. Interestingly, these alterations did not correlate with changes in cohesin binding. PMID:25483075
Mackeh, Rafah; Boughorbel, Sabri; Chaussabel, Damien; Kino, Tomoshige
2017-01-01
The collection of large-scale datasets available in public repositories is rapidly growing and providing opportunities to identify and fill gaps in different fields of biomedical research. However, users of these datasets should be able to selectively browse datasets related to their field of interest. Here we made available a collection of transcriptome datasets related to human follicular cells from normal individuals or patients with polycystic ovary syndrome, in the process of their development, during in vitro fertilization. After RNA-seq dataset exclusion and careful selection based on study description and sample information, 12 datasets, encompassing a total of 85 unique transcriptome profiles, were identified in NCBI Gene Expression Omnibus and uploaded to the Gene Expression Browser (GXB), a web application specifically designed for interactive query and visualization of integrated large-scale data. Once annotated in GXB, multiple sample grouping has been made in order to create rank lists to allow easy data interpretation and comparison. The GXB tool also allows the users to browse a single gene across multiple projects to evaluate its expression profiles in multiple biological systems/conditions in a web-based customized graphical views. The curated dataset is accessible at the following link: http://ivf.gxbsidra.org/dm3/landing.gsp. PMID:28413616
Airline Passenger Profiling Based on Fuzzy Deep Machine Learning.
Zheng, Yu-Jun; Sheng, Wei-Guo; Sun, Xing-Ming; Chen, Sheng-Yong
2017-12-01
Passenger profiling plays a vital part of commercial aviation security, but classical methods become very inefficient in handling the rapidly increasing amounts of electronic records. This paper proposes a deep learning approach to passenger profiling. The center of our approach is a Pythagorean fuzzy deep Boltzmann machine (PFDBM), whose parameters are expressed by Pythagorean fuzzy numbers such that each neuron can learn how a feature affects the production of the correct output from both the positive and negative sides. We propose a hybrid algorithm combining a gradient-based method and an evolutionary algorithm for training the PFDBM. Based on the novel learning model, we develop a deep neural network (DNN) for classifying normal passengers and potential attackers, and further develop an integrated DNN for identifying group attackers whose individual features are insufficient to reveal the abnormality. Experiments on data sets from Air China show that our approach provides much higher learning ability and classification accuracy than existing profilers. It is expected that the fuzzy deep learning approach can be adapted for a variety of complex pattern analysis tasks.
Bhatti, M M; Zeeshan, A; Ellahi, R
2017-03-01
In this article, simultaneous effects of coagulation (blood clot) and variable magnetic field on peristaltically induced motion of non-Newtonian Jeffrey nanofluid containing gyrotactic microorganism through an annulus have been studied. The effects of an endoscope also taken into consideration in our study as a special case. The governing flow problem is simplified by taking the approximation of long wavelength and creeping flow regime. The resulting highly coupled differential equations are solved analytically with the help of perturbation method and series solution have been presented up to second order approximation. The impact of all the sundry parameters is discussed for velocity profile, temperature profile, nanoparticle concentration profile, motile microorganism density profile, pressure rise and friction forces. Moreover, numerical integration is also used to evaluate the expressions for pressure rise and friction forces for outer tube and inner tube. It is found that velocity of a fluid diminishes near the walls due to the increment in the height of clot. However, the influence of magnetic field depicts opposite behavior near the walls. Copyright © 2016 Elsevier Inc. All rights reserved.
Zou, Dong; Sun, Shixiang; Li, Rujiao; Liu, Jiang; Zhang, Jing; Zhang, Zhang
2015-01-01
DNA methylation plays crucial roles during embryonic development. Here we present MethBank (http://dnamethylome.org), a DNA methylome programming database that integrates the genome-wide single-base nucleotide methylomes of gametes and early embryos in different model organisms. Unlike extant relevant databases, MethBank incorporates the whole-genome single-base-resolution methylomes of gametes and early embryos at multiple different developmental stages in zebrafish and mouse. MethBank allows users to retrieve methylation levels, differentially methylated regions, CpG islands, gene expression profiles and genetic polymorphisms for a specific gene or genomic region. Moreover, it offers a methylome browser that is capable of visualizing high-resolution DNA methylation profiles as well as other related data in an interactive manner and thus is of great helpfulness for users to investigate methylation patterns and changes of gametes and early embryos at different developmental stages. Ongoing efforts are focused on incorporation of methylomes and related data from other organisms. Together, MethBank features integration and visualization of high-resolution DNA methylation data as well as other related data, enabling identification of potential DNA methylation signatures in different developmental stages and accordingly providing an important resource for the epigenetic and developmental studies. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Comparative prion disease gene expression profiling using the prion disease mimetic, cuprizone
Moody, Laura R; Herbst, Allen J; Yoo, Han Sang; Vanderloo, Joshua P
2009-01-01
Identification of genes expressed in response to prion infection may elucidate biomarkers for disease, identify factors involved in agent replication, mechanisms of neuropathology and therapeutic targets. Although several groups have sought to identify gene expression changes specific to prion disease, expression profiles rife with cell population changes have consistently been identified. Cuprizone, a neurotoxicant, qualitatively mimics the cell population changes observed in prion disease, resulting in both spongiform change and astrocytosis. The use of cuprizone-treated animals as an experimental control during comparative expression profiling allows for the identification of transcripts whose expression increases during prion disease and remains unchanged during cuprizone-triggered neuropathology. In this study, expression profiles from the brains of mice preclinically and clinically infected with Rocky Mountain Laboratory (RML) mouse-adapted scrapie agent and age-matched controls were profiled using Affymetrix gene arrays. In total, 164 genes were differentially regulated during prion infection. Eighty-three of these transcripts have been previously undescribed as differentially regulated during prion disease. A 0.4% cuprizone diet was utilized as a control for comparative expression profiling. Cuprizone treatment induced spongiosis and astrocyte proliferation as indicated by glial fibrillary acidic protein (Gfap) transcriptional activation and immunohistochemistry. Gene expression profiles from brain tissue obtained from cuprizone-treated mice identified 307 differentially regulated transcript changes. After comparative analysis, 17 transcripts unaffected by cuprizone treatment but increasing in expression from preclinical to clinical prion infection were identified. Here we describe the novel use of the prion disease mimetic, cuprizone, to control for cell population changes in the brain during prion infection. PMID:19535908
2014-01-01
Background The transcription factor Pax8 is expressed during thyroid development and is involved in the morphogenesis of the thyroid gland and maintenance of the differentiated phenotype. In particular, Pax8 has been shown to regulate genes that are considered markers of thyroid differentiation. Recently, the analysis of the gene expression profile of FRTL-5 differentiated thyroid cells after the silencing of Pax8 identified Wnt4 as a novel target. Like the other members of the Wnt family, Wnt4 has been implicated in several developmental processes including regulation of cell fate and patterning during embryogenesis. To date, the only evidence on Wnt4 in thyroid concerns its down-regulation necessary for the progression of thyroid epithelial tumors. Results Here we demonstrate that Pax8 is involved in the transcriptional modulation of Wnt4 gene expression directly binding to its 5’-flanking region, and that Wnt4 expression in FRTL-5 cells is TSH-dependent. Interestingly, we also show that in thyroid cells a reduced expression of Wnt4 correlates with the alteration of the epithelial phenotype and that the overexpression of Wnt4 in thyroid cancer cells is able to inhibit cellular migration. Conclusions We have identified and characterized a functional Pax8 binding site in the 5’-flanking region of the Wnt4 gene and we show that Pax8 modulates the expression of Wnt4 in thyroid cells. Taken together, our results suggest that in thyroid cells Wnt4 expression correlates with the integrity of the epithelial phenotype and is reduced when this integrity is perturbed. In the end, we would like to suggest that the overexpression of Wnt4 in thyroid cancer cells is able to revert the mesenchymal phenotype. PMID:25270402
Molecular cloning and potential function prediction of homologous SOC1 genes in tree peony.
Wang, Shunli; Beruto, Margherita; Xue, Jingqi; Zhu, Fuyong; Liu, Chuanjiao; Yan, Yueming; Zhang, Xiuxin
2015-08-01
The central flower integrator PsSOC1 was isolated and its expression profiles were analyzed; then the potential function of PsSOC1 in tree peony was postulated. The six flowering genes PrSOC1, PdSOC1, PsSOC1, PsSOC1-1, PsSOC1-2, and PsSOC1-3 were isolated from Paeonia rockii, Paeonia delavayi, and Paeonia suffruticosa, respectively. Sequence comparison analysis showed that the six genes were highly conserved and shared 99.41% nucleotide identity. Further investigation suggested PsSOC1 was highly homologous to the floral integrators, SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1), from Arabidopsis. Phylogenetic analysis showed that the SOC1 protein clustering has family specificity and PsSOC1 has a close relationship with homologous SOC1 from Asteraceae species. The studies of PsSOC1's expression patterns in different buds and flower buds, and vegetative organs indicated that PsSOC1 could express in both vegetative and reproductive organs. While the expression of PsSOC1 in different developmental stages of buds was different; high expression levels of PsSOC1 occurred in the bud at the bud sprouting stage and the type I aborted the flower bud. PsSOC1 expression was also shown to be affected by gibberellins (GA), low temperature, and photoperiod. One of the pathways that regulates tree peony flowering may be the GA-inductive pathway. Ectopic expression of PsSOC1 in tobacco demonstrated that greater PsSOC1 expression in the transgenic tobacco plants not only promoted plant growth, but also advanced the flowering time. Finally, the potential function of PsSOC1 in tree peony was postulated.
Aiese Cigliano, Riccardo; Sanseverino, Walter; Cremona, Gaetana; Ercolano, Maria R; Conicella, Clara; Consiglio, Federica M
2013-01-28
Histone post-translational modifications (HPTMs) including acetylation and methylation have been recognized as playing a crucial role in epigenetic regulation of plant growth and development. Although Solanum lycopersicum is a dicot model plant as well as an important crop, systematic analysis and expression profiling of histone modifier genes (HMs) in tomato are sketchy. Based on recently released tomato whole-genome sequences, we identified in silico 32 histone acetyltransferases (HATs), 15 histone deacetylases (HDACs), 52 histone methytransferases (HMTs) and 26 histone demethylases (HDMs), and compared them with those detected in Arabidopsis (Arabidopsis thaliana), maize (Zea mays) and rice (Oryza sativa) orthologs. Comprehensive analysis of the protein domain architecture and phylogeny revealed the presence of non-canonical motifs and new domain combinations, thereby suggesting for HATs the existence of a new family in plants. Due to species-specific diversification during evolutionary history tomato has fewer HMs than Arabidopsis. The transcription profiles of HMs within tomato organs revealed a broad functional role for some HMs and a more specific activity for others, suggesting key HM regulators in tomato development. Finally, we explored S. pennellii introgression lines (ILs) and integrated the map position of HMs, their expression profiles and the phenotype of ILs. We thereby proved that the strategy was useful to identify HM candidates involved in carotenoid biosynthesis in tomato fruits. In this study, we reveal the structure, phylogeny and spatial expression of members belonging to the classical families of HMs in tomato. We provide a framework for gene discovery and functional investigation of HMs in other Solanaceae species.
Epigenetic dysregulation of key developmental genes in radiation-induced rat mammary carcinomas.
Daino, Kazuhiro; Nishimura, Mayumi; Imaoka, Tatsuhiko; Takabatake, Masaru; Morioka, Takamitsu; Nishimura, Yukiko; Shimada, Yoshiya; Kakinuma, Shizuko
2018-02-13
With the increase in the number of long-term cancer survivors worldwide, there is a growing concern about the risk of secondary cancers induced by radiotherapy. Epigenetic modifications of genes associated with carcinogenesis are attractive targets for the prevention of cancer owing to their reversible nature. To identify genes with possible changes in functionally relevant DNA methylation patterns in mammary carcinomas induced by radiation exposure, we performed microarray-based global DNA methylation and expression profiling in γ-ray-induced rat mammary carcinomas and normal mammary glands. The gene expression profiling identified dysregulation of developmentally related genes, including the downstream targets of polycomb repressive complex 2 (PRC2) and overexpression of enhancer of zeste homolog 2, a component of PRC2, in the carcinomas. By integrating expression and DNA methylation profiles, we identified ten hypermethylated and three hypomethylated genes that possibly act as tumor-suppressor genes and oncogenes dysregulated by aberrant DNA methylation; half of these genes encode developmental transcription factors. Bisulfite sequencing and quantitative PCR confirmed the dysregulation of the polycomb-regulated developmentally related transcription-factor genes Dmrt2, Hoxa7, Foxb1, Sox17, Lhx8, Gata3 and Runx1. Silencing of Hoxa7 was further verified by immunohistochemistry. These results suggest that, in radiation-induced mammary gland carcinomas, PRC2-mediated aberrant DNA methylation leads to dysregulation of developmentally related transcription-factor genes. Our findings provide clues to molecular mechanisms linking epigenetic regulation and radiation-induced breast carcinogenesis and underscore the potential of such epigenetic mechanisms as targets for cancer prevention. © 2018 UICC.
Hsi-Ping, Liu
1990-01-01
Impulse responses including near-field terms have been obtained in closed form for the zero-offset vertical seismic profiles generated by a horizontal point force acting on the surface of an elastic half-space. The method is based on the correspondence principle. Through transformation of variables, the Fourier transform of the elastic impulse response is put in a form such that the Fourier transform of the corresponding anelastic impulse response can be expressed as elementary functions and their definite integrals involving distance angular frequency, phase velocities, and attenuation factors. These results are used for accurate calculation of shear-wave arrival rise times of synthetic seismograms needed for data interpretation of anelastic-attenuation measurements in near-surface sediment. -Author
Scaling laws and vortex profiles in two-dimensional decaying turbulence.
Laval, J P; Chavanis, P H; Dubrulle, B; Sire, C
2001-06-01
We use high resolution numerical simulations over several hundred of turnover times to study the influence of small scale dissipation onto vortex statistics in 2D decaying turbulence. A scaling regime is detected when the scaling laws are expressed in units of mean vorticity and integral scale, like predicted in Carnevale et al., Phys. Rev. Lett. 66, 2735 (1991), and it is observed that viscous effects spoil this scaling regime. The exponent controlling the decay of the number of vortices shows some trends toward xi=1, in agreement with a recent theory based on the Kirchhoff model [C. Sire and P. H. Chavanis, Phys. Rev. E 61, 6644 (2000)]. In terms of scaled variables, the vortices have a similar profile with a functional form related to the Fermi-Dirac distribution.
Advancing haematopoietic stem and progenitor cell biology through single-cell profiling.
Hamey, Fiona K; Nestorowa, Sonia; Wilson, Nicola K; Göttgens, Berthold
2016-11-01
Haematopoietic stem and progenitor cells (HSPCs) sit at the top of the haematopoietic hierarchy, and their fate choices need to be carefully controlled to ensure balanced production of all mature blood cell types. As cell fate decisions are made at the level of the individual cells, recent technological advances in measuring gene and protein expression in increasingly large numbers of single cells have been rapidly adopted to study both normal and pathological HSPC function. In this review we emphasise the importance of combining the correct computational models with single-cell experimental techniques, and illustrate how such integrated approaches have been used to resolve heterogeneities in populations, reconstruct lineage differentiation, identify regulatory relationships and link molecular profiling to cellular function. © 2016 Federation of European Biochemical Societies.
Consequences of a chromospheric temperature gradient on the width of H Alpha in late-type giants
NASA Technical Reports Server (NTRS)
Zarro, D. M.
1984-01-01
An analytic expression for the integrated H alpha optical depth profile is derived for a one dimensional slab geometry model chromosphere, with electron temperature increasing as a power law with height. The formula predicts H alpha opacity and profile width to be sensitive functions of the thermal gradient. Application of the model to observation reveals that broad H alpha absorption widths in G and K giant stars are consistent with a mean H alpha chromospheric optical depth of 50, while narrower widths in M stars indicate slightly lower opacities. It is proposed that differences in H alpha width between late-type giants of similar spectral type may be due, in part, to differences in their chromospheric thermal gradient, and associated H alpha opacity.
2011-01-01
Background Cultivated watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai var. lanatus] is an important agriculture crop world-wide. The fruit of watermelon undergoes distinct stages of development with dramatic changes in its size, color, sweetness, texture and aroma. In order to better understand the genetic and molecular basis of these changes and significantly expand the watermelon transcript catalog, we have selected four critical stages of watermelon fruit development and used Roche/454 next-generation sequencing technology to generate a large expressed sequence tag (EST) dataset and a comprehensive transcriptome profile for watermelon fruit flesh tissues. Results We performed half Roche/454 GS-FLX run for each of the four watermelon fruit developmental stages (immature white, white-pink flesh, red flesh and over-ripe) and obtained 577,023 high quality ESTs with an average length of 302.8 bp. De novo assembly of these ESTs together with 11,786 watermelon ESTs collected from GenBank produced 75,068 unigenes with a total length of approximately 31.8 Mb. Overall 54.9% of the unigenes showed significant similarities to known sequences in GenBank non-redundant (nr) protein database and around two-thirds of them matched proteins of cucumber, the most closely-related species with a sequenced genome. The unigenes were further assigned with gene ontology (GO) terms and mapped to biochemical pathways. More than 5,000 SSRs were identified from the EST collection. Furthermore we carried out digital gene expression analysis of these ESTs and identified 3,023 genes that were differentially expressed during watermelon fruit development and ripening, which provided novel insights into watermelon fruit biology and a comprehensive resource of candidate genes for future functional analysis. We then generated profiles of several interesting metabolites that are important to fruit quality including pigmentation and sweetness. Integrative analysis of metabolite and digital gene expression profiles helped elucidating molecular mechanisms governing these important quality-related traits during watermelon fruit development. Conclusion We have generated a large collection of watermelon ESTs, which represents a significant expansion of the current transcript catalog of watermelon and a valuable resource for future studies on the genomics of watermelon and other closely-related species. Digital expression analysis of this EST collection allowed us to identify a large set of genes that were differentially expressed during watermelon fruit development and ripening, which provide a rich source of candidates for future functional analysis and represent a valuable increase in our knowledge base of watermelon fruit biology. PMID:21936920
Guo, Shaogui; Liu, Jingan; Zheng, Yi; Huang, Mingyun; Zhang, Haiying; Gong, Guoyi; He, Hongju; Ren, Yi; Zhong, Silin; Fei, Zhangjun; Xu, Yong
2011-09-21
Cultivated watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai var. lanatus] is an important agriculture crop world-wide. The fruit of watermelon undergoes distinct stages of development with dramatic changes in its size, color, sweetness, texture and aroma. In order to better understand the genetic and molecular basis of these changes and significantly expand the watermelon transcript catalog, we have selected four critical stages of watermelon fruit development and used Roche/454 next-generation sequencing technology to generate a large expressed sequence tag (EST) dataset and a comprehensive transcriptome profile for watermelon fruit flesh tissues. We performed half Roche/454 GS-FLX run for each of the four watermelon fruit developmental stages (immature white, white-pink flesh, red flesh and over-ripe) and obtained 577,023 high quality ESTs with an average length of 302.8 bp. De novo assembly of these ESTs together with 11,786 watermelon ESTs collected from GenBank produced 75,068 unigenes with a total length of approximately 31.8 Mb. Overall 54.9% of the unigenes showed significant similarities to known sequences in GenBank non-redundant (nr) protein database and around two-thirds of them matched proteins of cucumber, the most closely-related species with a sequenced genome. The unigenes were further assigned with gene ontology (GO) terms and mapped to biochemical pathways. More than 5,000 SSRs were identified from the EST collection. Furthermore we carried out digital gene expression analysis of these ESTs and identified 3,023 genes that were differentially expressed during watermelon fruit development and ripening, which provided novel insights into watermelon fruit biology and a comprehensive resource of candidate genes for future functional analysis. We then generated profiles of several interesting metabolites that are important to fruit quality including pigmentation and sweetness. Integrative analysis of metabolite and digital gene expression profiles helped elucidating molecular mechanisms governing these important quality-related traits during watermelon fruit development. We have generated a large collection of watermelon ESTs, which represents a significant expansion of the current transcript catalog of watermelon and a valuable resource for future studies on the genomics of watermelon and other closely-related species. Digital expression analysis of this EST collection allowed us to identify a large set of genes that were differentially expressed during watermelon fruit development and ripening, which provide a rich source of candidates for future functional analysis and represent a valuable increase in our knowledge base of watermelon fruit biology.
Matigian, Nicholas; Brooke, Gary; Zaibak, Faten; Rossetti, Tony; Kollar, Katarina; Pelekanos, Rebecca; Heazlewood, Celena; Mackay-Sim, Alan; Wells, Christine A.; Atkinson, Kerry
2014-01-01
Multipotent mesenchymal stromal cells derived from human placenta (pMSCs), and unrestricted somatic stem cells (USSCs) derived from cord blood share many properties with human bone marrow-derived mesenchymal stromal cells (bmMSCs) and are currently in clinical trials for a wide range of clinical settings. Here we present gene expression profiles of human cord blood-derived unrestricted somatic stem cells (USSCs), human placental-derived mesenchymal stem cells (hpMSCs), and human bone marrow-derived mesenchymal stromal cells (bmMSCs), all derived from four different donors. The microarray data are available on the ArrayExpress database (www.ebi.ac.uk/arrayexpress) under accession number E-TABM-880. Additionally, the data has been integrated into a public portal, www.stemformatics.org. Our data provide a resource for understanding the differences in MSCs derived from different tissues. PMID:26484151
The protein expression landscape of the Arabidopsis root
Petricka, Jalean J.; Schauer, Monica A.; Megraw, Molly; Breakfield, Natalie W.; Thompson, J. Will; Georgiev, Stoyan; Soderblom, Erik J.; Ohler, Uwe; Moseley, Martin Arthur; Grossniklaus, Ueli; Benfey, Philip N.
2012-01-01
Because proteins are the major functional components of cells, knowledge of their cellular localization is crucial to gaining an understanding of the biology of multicellular organisms. We have generated a protein expression map of the Arabidopsis root providing the identity and cell type-specific localization of nearly 2,000 proteins. Grouping proteins into functional categories revealed unique cellular functions and identified cell type-specific biomarkers. Cellular colocalization provided support for numerous protein–protein interactions. With a binary comparison, we found that RNA and protein expression profiles are weakly correlated. We then performed peak integration at cell type-specific resolution and found an improved correlation with transcriptome data using continuous values. We performed GeLC-MS/MS (in-gel tryptic digestion followed by liquid chromatography-tandem mass spectrometry) proteomic experiments on mutants with ectopic and no root hairs, providing complementary proteomic data. Finally, among our root hair-specific proteins we identified two unique regulators of root hair development. PMID:22447775
Spatial reconstruction of single-cell gene expression
Satija, Rahul; Farrell, Jeffrey A.; Gennert, David; Schier, Alexander F.; Regev, Aviv
2015-01-01
Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. PMID:25867923
Haebig, Eileen; Sterling, Audra
2017-02-01
Previous work has noted that some children with autism spectrum disorder (ASD) display weaknesses in receptive vocabulary relative to expressive vocabulary abilities. The current study extended previous work by examining the receptive-expressive vocabulary profile in boys with idiopathic ASD and boys with concomitant ASD and fragile X syndrome (ASD + FXS). On average, boys with ASD + FXS did not display the same atypical receptive-expressive profile as boys with idiopathic ASD. Notably, there was variation in vocabulary abilities and profiles in both groups. Although we did not identify predictors of receptive-expressive differences, we demonstrated that nonverbal IQ and expressive vocabulary positively predicted concurrent receptive vocabulary knowledge and receptive vocabulary predicted expressive vocabulary. We discuss areas of overlap and divergence in subgroups of ASD.
Sterling, Audra
2016-01-01
Previous work has noted that some children with autism spectrum disorder (ASD) display weaknesses in receptive vocabulary relative to expressive vocabulary abilities. The current study extended previous work by examining the receptive-expressive vocabulary profile in boys with idiopathic ASD and boys with concomitant ASD and fragile X syndrome (ASD + FXS). On average, boys with ASD + FXS did not display the same atypical receptive-expressive profile as boys with idiopathic ASD. Notably, there was variation in vocabulary abilities and profiles in both groups. Although we did not identify predictors of receptive-expressive differences, we demonstrated that nonverbal IQ and expressive vocabulary positively predicted concurrent receptive vocabulary knowledge and receptive vocabulary predicted expressive vocabulary. We discuss areas of overlap and divergence in subgroups of ASD. PMID:27796729
2011-01-01
Background To make sense out of gene expression profiles, such analyses must be pushed beyond the mere listing of affected genes. For example, if a group of genes persistently display similar changes in expression levels under particular experimental conditions, and the proteins encoded by these genes interact and function in the same cellular compartments, this could be taken as very strong indicators for co-regulated protein complexes. One of the key requirements is having appropriate tools to detect such regulatory patterns. Results We have analyzed the global adaptations in gene expression patterns in the budding yeast when the Hsp90 molecular chaperone complex is perturbed either pharmacologically or genetically. We integrated these results with publicly accessible expression, protein-protein interaction and intracellular localization data. But most importantly, all experimental conditions were simultaneously and dynamically visualized with an animation. This critically facilitated the detection of patterns of gene expression changes that suggested underlying regulatory networks that a standard analysis by pairwise comparison and clustering could not have revealed. Conclusions The results of the animation-assisted detection of changes in gene regulatory patterns make predictions about the potential roles of Hsp90 and its co-chaperone p23 in regulating whole sets of genes. The simultaneous dynamic visualization of microarray experiments, represented in networks built by integrating one's own experimental with publicly accessible data, represents a powerful discovery tool that allows the generation of new interpretations and hypotheses. PMID:21672238
De Iudicibus, Sara; Lucafò, Marianna; Vitulo, Nicola; Martelossi, Stefano; Zimbello, Rosanna; De Pascale, Fabio; Forcato, Claudio; Naviglio, Samuele; Di Silvestre, Alessia; Gerdol, Marco; Stocco, Gabriele; Valle, Giorgio; Ventura, Alessandro; Bramuzzo, Matteo; Decorti, Giuliana
2018-05-08
The aim of this research was the identification of novel pharmacogenomic biomarkers for better understanding the complex gene regulation mechanisms underpinning glucocorticoid (GC) action in paediatric inflammatory bowel disease (IBD). This goal was achieved by evaluating high-throughput microRNA (miRNA) profiles during GC treatment, integrated with the assessment of expression changes in GC receptor (GR) heterocomplex genes. Furthermore, we tested the hypothesis that differentially expressed miRNAs could be directly regulated by GCs through investigating the presence of GC responsive elements (GREs) in their gene promoters. Ten IBD paediatric patients responding to GCs were enrolled. Peripheral blood was obtained at diagnosis (T0) and after four weeks of steroid treatment (T4). MicroRNA profiles were analyzed using next generation sequencing, and selected significantly differentially expressed miRNAs were validated by quantitative reverse transcription-polymerase chain reaction. In detail, 18 miRNAs were differentially expressed from T0 to T4, 16 of which were upregulated and 2 of which were downregulated. Out of these, three miRNAs (miR-144, miR-142, and miR-96) could putatively recognize the 3’UTR of the GR gene and three miRNAs (miR-363, miR-96, miR-142) contained GREs sequences, thereby potentially enabling direct regulation by the GR. In conclusion, we identified miRNAs differently expressed during GC treatment and miRNAs which could be directly regulated by GCs in blood cells of young IBD patients. These results could represent a first step towards their translation as pharmacogenomic biomarkers.
Comparative analyses identify molecular signature of MRI-classified SVZ-associated glioblastoma
Lin, Chin-Hsing Annie; Rhodes, Christopher T.; Lin, ChenWei; Phillips, Joanna J.; Berger, Mitchel S.
2017-01-01
ABSTRACT Glioblastoma (GBM) is a highly aggressive brain cancer with limited therapeutic options. While efforts to identify genes responsible for GBM have revealed mutations and aberrant gene expression associated with distinct types of GBM, patients with GBM are often diagnosed and classified based on MRI features. Therefore, we seek to identify molecular representatives in parallel with MRI classification for group I and group II primary GBM associated with the subventricular zone (SVZ). As group I and II GBM contain stem-like signature, we compared gene expression profiles between these 2 groups of primary GBM and endogenous neural stem progenitor cells to reveal dysregulation of cell cycle, chromatin status, cellular morphogenesis, and signaling pathways in these 2 types of MRI-classified GBM. In the absence of IDH mutation, several genes associated with metabolism are differentially expressed in these subtypes of primary GBM, implicating metabolic reprogramming occurs in tumor microenvironment. Furthermore, histone lysine methyltransferase EZH2 was upregulated while histone lysine demethylases KDM2 and KDM4 were downregulated in both group I and II primary GBM. Lastly, we identified 9 common genes across large data sets of gene expression profiles among MRI-classified group I/II GBM, a large cohort of GBM subtypes from TCGA, and glioma stem cells by unsupervised clustering comparison. These commonly upregulated genes have known functions in cell cycle, centromere assembly, chromosome segregation, and mitotic progression. Our findings highlight altered expression of genes important in chromosome integrity across all GBM, suggesting a common mechanism of disrupted fidelity of chromosome structure in GBM. PMID:28278055
Neri, Simona; Vannini, Francesca; Desando, Giovanna; Grigolo, Brunella; Ruffilli, Alberto; Buda, Roberto; Facchini, Andrea; Giannini, Sandro
2013-10-16
Fresh osteochondral allografts represent a treatment option for early ankle posttraumatic arthritis. Transplanted cartilage survivorship, integration, and colonization by recipient cells have not been fully investigated. The aim of this study was to evaluate the ability of recipient cells to colonize the allograft cartilage and to assess allograft cell phenotype. Seventeen ankle allograft samples were studied. Retrieved allograft cartilage DNA from fifteen cases was compared with recipient and donor constitutional DNA by genotyping. In addition, gene expression was evaluated on six allograft cartilage samples by means of real-time reverse transcription-polymerase chain reaction. Histology and immunohistochemistry were performed to support molecular observations. Of fifteen genotyped allografts, ten completely matched to the host, three matched to the donor, and two showed a mixed profile. Gene expression analysis showed that grafted cartilage expressed cartilage-specific markers. The rare persistence of donor cells and the prevailing presence of host DNA in retrieved ankle allografts suggest the ingrowth of recipient cells into the allograft cartilage, presumably migrating from the subchondral bone, in accordance with morphological findings. The expression of chondrogenic markers in some of the samples argues for the acquisition of a chondrocyte-like phenotype by these cells. To our knowledge, this is the first report describing the colonization of ankle allograft cartilage by host cells showing the acquisition of a chondrocyte-like phenotype.
Expression of Hygromycin Phosphotransferase Alters Virulence of Histoplasma capsulatum▿
Smulian, A. George; Gibbons, Reta S.; Demland, Jeffery A.; Spaulding, Deborah T.; Deepe, George S.
2007-01-01
The Escherichia coli hygromycin phosphotransferase (hph) gene, which confers hygromycin resistance, is commonly used as a dominant selectable marker in genetically modified bacteria, fungi, plants, insects, and mammalian cells. Expression of the hph gene has rarely been reported to induce effects other than those expected. Hygromycin B is the most common dominant selectable marker used in the molecular manipulation of Histoplasma capsulatum in the generation of knockout strains of H. capsulatum or as a marker in mutant strains. hph-expressing organisms appear to have no defect in long-term in vitro growth and survival and have been successfully used to exploit host-parasite interaction in short-term cell culture systems and animal experiments. We introduced the hph gene as a selectable marker together with the gene encoding green fluorescent protein into wild-type strains of H. capsulatum. Infection of mice with hph-expressing H. capsulatum yeast cells at sublethal doses resulted in lethality. The lethality was not attributable to the site of integration of the hph construct into the genomes or to the method of integration and was not H. capsulatum strain related. Death of mice was not caused by altered cytokine profiles or an overwhelming fungal burden. The lethality was dependent on the kinase activity of hygromycin phosphotransferase. These results should raise awareness of the potential detrimental effects of the hph gene. PMID:17873086
Expression of hygromycin phosphotransferase alters virulence of Histoplasma capsulatum.
Smulian, A George; Gibbons, Reta S; Demland, Jeffery A; Spaulding, Deborah T; Deepe, George S
2007-11-01
The Escherichia coli hygromycin phosphotransferase (hph) gene, which confers hygromycin resistance, is commonly used as a dominant selectable marker in genetically modified bacteria, fungi, plants, insects, and mammalian cells. Expression of the hph gene has rarely been reported to induce effects other than those expected. Hygromycin B is the most common dominant selectable marker used in the molecular manipulation of Histoplasma capsulatum in the generation of knockout strains of H. capsulatum or as a marker in mutant strains. hph-expressing organisms appear to have no defect in long-term in vitro growth and survival and have been successfully used to exploit host-parasite interaction in short-term cell culture systems and animal experiments. We introduced the hph gene as a selectable marker together with the gene encoding green fluorescent protein into wild-type strains of H. capsulatum. Infection of mice with hph-expressing H. capsulatum yeast cells at sublethal doses resulted in lethality. The lethality was not attributable to the site of integration of the hph construct into the genomes or to the method of integration and was not H. capsulatum strain related. Death of mice was not caused by altered cytokine profiles or an overwhelming fungal burden. The lethality was dependent on the kinase activity of hygromycin phosphotransferase. These results should raise awareness of the potential detrimental effects of the hph gene.
High resolution array CGH and gene expression profiling of alveolar soft part sarcoma
Selvarajah, Shamini; Pyne, Saumyadipta; Chen, Eleanor; Sompallae, Ramakrishna; Ligon, Azra H.; Nielsen, Gunnlaugur P.; Dranoff, Glenn; Stack, Edward; Loda, Massimo; Flavin, Richard
2014-01-01
Purpose Alveolar soft part sarcoma (ASPS) is a soft tissue sarcoma with poor prognosis, and little molecular evidence for its origin, initiation and progression. The aim of this study was to elucidate candidate molecular pathways involved in tumor pathogenesis. Experimental Design We employed high-throughput array comparative genomic hybridization and cDNA-Mediated Annealing, Selection, Ligation, and Extension Assay to profile the genomic and expression signatures of primary and metastatic ASPS from 17 tumors derived from 11 patients. We used an integrative bioinformatics approach to elucidate the molecular pathways associated with ASPS progression. Fluorescence in situ hybridization was performed to validate the presence of the t(X;17)(p11.2;q25) ASPL-TFE3 fusion and hence confirm the aCGH observations. Results FISH analysis identified the ASPL-TFE3 fusion in all cases. ArrayCGH revealed a higher number of numerical aberrations in metastatic tumors relative to primaries, but failed to identify consistent alterations in either group. Gene expression analysis highlighted 1,063 genes which were differentially expressed between the two groups. Gene set enrichment analysis identified 16 enriched gene sets (p < 0.1) associated with differentially expressed genes. Notable among these were several stem cell gene expression signatures and pathways related to differentiation. In particular, the paired box transcription factor PAX6 was up-regulated in the primary tumors, along with several genes whose mouse orthologs have previously been implicated in Pax6-DNA binding during neural stem cell differentiation. Conclusion In addition to suggesting a tentative neural line of differentiation for ASPS, these results implicate transcriptional deregulation from fusion genes in the pathogenesis of ASPS. PMID:24493828
Muñoz-Cano, Rosa; Pascal, Mariona; Bartra, Joan; Picado, Cesar; Valero, Antonio; Kim, Do-Kyun; Brooks, Stephen; Ombrello, Michael; Metcalfe, Dean D.; Rivera, Juan; Olivera, Ana
2015-01-01
Background Lipid transfer protein (LTP), an abundant protein in fruits, vegetables and nuts, is a common food allergen in Mediterranean areas causing diverse allergic reactions. Approximately 40% of food anaphylaxis induced by LTP require non-steroidal anti-inflammatory drugs (NSAIDs) as a triggering cofactor. Objective To better understand the determinants of NSAID-dependent (NSAID-LTP-A) and NSAID-independent LTP-anaphylaxis (LTP-A) Methods Selection of patients was based on a proven clinical history of NSAID-dependent or -independent anaphylaxis to LTP, positive skin prick test to LTP and serum LTP-IgE. Whole transcriptome (RNA-Seq) analysis of blood cells from 14 individuals with NSAID-LTP-A, 7 with LTP-A and 13 healthy controls was performed to identify distinct gene expression signatures. Results Expression of genes regulating gastrointestinal epithelium renewal was altered in both patient sets, particularly in LTP-A, who also presented gene expression profiles characteristic of an inflammatory syndrome. These included altered B cell pathways, increased neutrophil activation markers and elevated levels of reactive oxygen species. Increased expression of the IgG receptor (CD64) in LTP-A patients was mirrored by the presence of LTP-specific IgG1 and 3. Conversely, NSAID-LTP-A patients were characterized by reduced expression of IFN-γ-regulated genes and IFN-γ levels as well as up-regulated adenosine receptor 3 (ADORA3) expression and genes related to adenosine metabolism. Conclusions Gene ontology analysis suggests disturbances in gut epithelium homeostasis in both LTP-related anaphylaxis groups with potential integrity breaches in LTP-A that may explain their distinct inflammatory signature. Differential regulation in LTP-A and NSAID-LTP-A of the IFN-γ pathway, IgG receptors and ADORA3 may provide the pathogenic basis of their distinct responses. PMID:26194548
Small RNA-based prediction of hybrid performance in maize.
Seifert, Felix; Thiemann, Alexander; Schrag, Tobias A; Rybka, Dominika; Melchinger, Albrecht E; Frisch, Matthias; Scholten, Stefan
2018-05-21
Small RNA (sRNA) sequences are known to have a broad impact on gene regulation by various mechanisms. Their performance for the prediction of hybrid traits has not yet been analyzed. Our objective was to analyze the relation of parental sRNA expression with the performance of their hybrids, to develop a sRNA-based prediction approach, and to compare it to more common SNP and mRNA transcript based predictions using a factorial mating scheme of a maize hybrid breeding program. Correlation of genomic differences and messenger RNA (mRNA) or sRNA expression differences between parental lines with hybrid performance of their hybrids revealed that sRNAs showed an inverse relationship in contrast to the other two data types. We associated differences for SNPs, mRNA and sRNA expression between parental inbred lines with the performance of their hybrid combinations and developed two prediction approaches using distance measures based on associated markers. Cross-validations revealed parental differences in sRNA expression to be strong predictors for hybrid performance for grain yield in maize, comparable to genomic and mRNA data. The integration of both positively and negatively associated markers in the prediction approaches enhanced the prediction accurary. The associated sRNAs belong predominantly to the canonical size classes of 22- and 24-nt that show specific genomic mapping characteristics. Expression profiles of sRNA are a promising alternative to SNPs or mRNA expression profiles for hybrid prediction, especially for plant species without reference genome or transcriptome information. The characteristics of the sRNAs we identified suggest that association studies based on breeding populations facilitate the identification of sRNAs involved in hybrid performance.
Bhardwaj, Neeru; Montesion, Meagan; Roy, Farrah; Coffin, John M.
2015-01-01
Human endogenous retrovirus (HERV-K (HML-2)) proviruses are among the few endogenous retroviral elements in the human genome that retain coding sequence. HML-2 expression has been widely associated with human disease states, including different types of cancers as well as with HIV-1 infection. Understanding of the potential impact of this expression requires that it be annotated at the proviral level. Here, we utilized the high throughput capabilities of next-generation sequencing to profile HML-2 expression at the level of individual proviruses and secreted virions in the teratocarcinoma cell line Tera-1. We identified well-defined expression patterns, with transcripts emanating primarily from two proviruses located on chromosome 22, only one of which was efficiently packaged. Interestingly, there was a preference for transcripts of recently integrated proviruses, over those from other highly expressed but older elements, to be packaged into virions. We also assessed the promoter competence of the 5’ long terminal repeats (LTRs) of expressed proviruses via a luciferase assay following transfection of Tera-1 cells. Consistent with the RNASeq results, we found that the activity of most LTRs corresponded to their transcript levels. PMID:25746218
Conde-Muiño, Raquel; Cano, Carlos; Sánchez-Martín, Victoria; Herrera, Antonio; Comino, Ana; Medina, Pedro P.; Palma, Pablo; Cuadros, Marta
2017-01-01
Administration of chemoradiation before tumor resection has revolutionized the management of locally advanced rectal cancer, but many patients have proven resistant to this preoperative therapy. Our group recently reported a negative correlation between c-Myc gene expression and this resistance. In the present study, integrated analysis of miRNA and mRNA expression profiles was conducted in 45 pre-treatment rectal tumors in order to analyze the expressions of miRNAs and c-Myc and their relationship with clinicopathological factors and patient survival. Twelve miRNAs were found to be differentially expressed by responders and non-responders to the chemoradiation. Functional classification revealed an association between the differentially expressed miRNAs and c-Myc. Quantitative real-time PCR results showed that miRNA-148 and miRNA-375 levels were both significantly lower in responders than in non-responders. Notably, a significant negative correlation was found between miRNA-375 expression and c-Myc expression. According to these findings, miRNA-375 and its targeted c-Myc may be useful as a predictive biomarker of the response to neoadjuvant treatment in patients with locally advanced rectal cancer. PMID:29137264
Analysis of translation using polysome profiling
Chassé, Héloïse; Boulben, Sandrine; Costache, Vlad; Cormier, Patrick
2017-01-01
Abstract During the past decade, there has been growing interest in the role of translational regulation of gene expression in many organisms. Polysome profiling has been developed to infer the translational status of a specific mRNA species or to analyze the translatome, i.e. the subset of mRNAs actively translated in a cell. Polysome profiling is especially suitable for emergent model organisms for which genomic data are limited. In this paper, we describe an optimized protocol for the purification of sea urchin polysomes and highlight the critical steps involved in polysome purification. We applied this protocol to obtain experimental results on translational regulation of mRNAs following fertilization. Our protocol should prove useful for integrating the study of the role of translational regulation in gene regulatory networks in any biological model. In addition, we demonstrate how to carry out high-throughput processing of polysome gradient fractions, for the simultaneous screening of multiple biological conditions and large-scale preparation of samples for next-generation sequencing. PMID:28180329
Inferring genome-wide interplay landscape between DNA methylation and transcriptional regulation.
Tang, Binhua; Wang, Xin
2015-01-01
DNA methylation and transcriptional regulation play important roles in cancer cell development and differentiation processes. Based on the currently available cell line profiling information from the ENCODE Consortium, we propose a Bayesian inference model to infer and construct genome-wide interaction landscape between DNA methylation and transcriptional regulation, which sheds light on the underlying complex functional mechanisms important within the human cancer and disease context. For the first time, we select all the currently available cell lines (>=20) and transcription factors (>=80) profiling information from the ENCODE Consortium portal. Through the integration of those genome-wide profiling sources, our genome-wide analysis detects multiple functional loci of interest, and indicates that DNA methylation is cell- and region-specific, due to the interplay mechanisms with transcription regulatory activities. We validate our analysis results with the corresponding RNA-sequencing technique for those detected genomic loci. Our results provide novel and meaningful insights for the interplay mechanisms of transcriptional regulation and gene expression for the human cancer and disease studies.
Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors.
Babcock, Joseph J; Du, Fang; Xu, Kaiping; Wheelan, Sarah J; Li, Min
2013-01-01
Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays.
Integrated Analysis of Drug-Induced Gene Expression Profiles Predicts Novel hERG Inhibitors
Babcock, Joseph J.; Du, Fang; Xu, Kaiping; Wheelan, Sarah J.; Li, Min
2013-01-01
Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays. PMID:23936032
L1000CDS2: LINCS L1000 characteristic direction signatures search engine
Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma’ayan, Avi
2016-01-01
The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS2. The L1000CDS2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS2, we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource. PMID:28413689
Metal-cluster ionization energy: A profile-insensitive exact expression for the size effect
NASA Astrophysics Data System (ADS)
Seidl, Michael; Perdew, John P.; Brajczewska, Marta; Fiolhais, Carlos
1997-05-01
The ionization energy of a large spherical metal cluster of radius R is I(R)=W+(+c)/R, where W is the bulk work function and c~-0.1 is a material-dependent quantum correction to the electrostatic size effect. We present 'Koopmans' and 'displaced-profile change-in-self-consistent-field' expressions for W and c within the ordinary and stabilized-jellium models. These expressions are shown to be exact and equivalent when the exact density profile of a large neutral cluster is employed; these equivalences generalize the Budd-Vannimenus theorem. With an approximate profile obtained from a restricted variational calculation, the 'displaced-profile' expressions are the more accurate ones. This profile insensitivity is important, because it is not practical to extract c from solutions of the Kohn-Sham equations for small metal clusters.
Single cell gene expression profiling of cortical osteoblast lineage cells.
Flynn, James M; Spusta, Steven C; Rosen, Clifford J; Melov, Simon
2013-03-01
In tissues with complex architectures such as bone, it is often difficult to purify and characterize specific cell types via molecular profiling. Single cell gene expression profiling is an emerging technology useful for characterizing transcriptional profiles of individual cells isolated from heterogeneous populations. In this study we describe a novel procedure for the isolation and characterization of gene expression profiles of single osteoblast lineage cells derived from cortical bone. Mixed populations of different cell types were isolated from adult long bones of C57BL/6J mice by enzymatic digestion, and subsequently subjected to FACS to purify and characterize osteoblast lineage cells via a selection strategy using antibodies against CD31, CD45, and alkaline phosphatase (AP), specific for mature osteoblasts. The purified individual osteoblast lineage cells were then profiled at the single cell level via nanofluidic PCR. This method permits robust gene expression profiling on single osteoblast lineage cells derived from mature bone, potentially from anatomically distinct sites. In conjunction with this technique, we have also shown that it is possible to carry out single cell profiling on cells purified from fixed and frozen bone samples without compromising the gene expression signal. The latter finding means the technique can be extended to biopsies of bone from diseased individuals. Our approach for single cell expression profiling provides a new dimension to the transcriptional profile of the primary osteoblast lineage population in vivo, and has the capacity to greatly expand our understanding of how these cells may function in vivo under normal and diseased states. Copyright © 2012 Elsevier Inc. All rights reserved.
Chasman, Deborah; Walters, Kevin B.; Lopes, Tiago J. S.; Eisfeld, Amie J.; Kawaoka, Yoshihiro; Roy, Sushmita
2016-01-01
Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection. PMID:27403523
Integrative radiogenomic analysis for multicentric radiophenotype in glioblastoma
Kong, Doo-Sik; Kim, Jinkuk; Lee, In-Hee; Kim, Sung Tae; Seol, Ho Jun; Lee, Jung-Il; Park, Woong-Yang; Ryu, Gyuha; Wang, Zichen; Ma'ayan, Avi; Nam, Do-Hyun
2016-01-01
We postulated that multicentric glioblastoma (GBM) represents more invasiveness form than solitary GBM and has their own genomic characteristics. From May 2004 to June 2010 we retrospectively identified 51 treatment-naïve GBM patients with available clinical information from the Samsung Medical Center data registry. Multicentricity of the tumor was defined as the presence of multiple foci on the T1 contrast enhancement of MR images or having high signal for multiple lesions without contiguity of each other on the FLAIR image. Kaplan-Meier survival analysis demonstrated that multicentric GBM had worse prognosis than solitary GBM (median, 16.03 vs. 20.57 months, p < 0.05). Copy number variation (CNV) analysis revealed there was an increase in 11 regions, and a decrease in 17 regions, in the multicentric GBM. Gene expression profiling identified 738 genes to be increased and 623 genes to be decreased in the multicentric radiophenotype (p < 0.001). Integration of the CNV and expression datasets identified twelve representative genes: CPM, LANCL2, LAMP1, GAS6, DCUN1D2, CDK4, AGAP2, TSPAN33, PDLIM1, CLDN12, and GTPBP10 having high correlation across CNV, gene expression and patient outcome. Network and enrichment analyses showed that the multicentric tumor had elevated fibrotic signaling pathways compared with a more proliferative and mitogenic signal in the solitary tumors. Noninvasive radiological imaging together with integrative radiogenomic analysis can provide an important tool in helping to advance personalized therapy for the more clinically aggressive subset of GBM. PMID:26863628
2007-05-01
Benign and Malignant Nerve Sheath Tumors in Neurofibromatosis Patients PRINCIPAL INVESTIGATOR: Matt van de Rijn, M.D., Ph.D. Torsten...Annual 3. DATES COVERED 1 May 2006 –30 Apr 2007 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Genomic and Expression Profiling of Benign and Malignant Nerve...Award Number: DAMD17-03-1-0297 Title: Genomic and Expression Profiling of Benign and Malignant Nerve Sheath Tumors in Neurofibromatosis
Cross-platform single cell analysis of kidney development shows stromal cells express Gdnf.
Magella, Bliss; Adam, Mike; Potter, Andrew S; Venkatasubramanian, Meenakshi; Chetal, Kashish; Hay, Stuart B; Salomonis, Nathan; Potter, S Steven
2018-02-01
The developing kidney provides a useful model for study of the principles of organogenesis. In this report we use three independent platforms, Drop-Seq, Chromium 10x Genomics and Fluidigm C1, to carry out single cell RNA-Seq (scRNA-Seq) analysis of the E14.5 mouse kidney. Using the software AltAnalyze, in conjunction with the unsupervised approach ICGS, we were unable to identify and confirm the presence of 16 distinct cell populations during this stage of active nephrogenesis. Using a novel integrative supervised computational strategy, we were able to successfully harmonize and compare the cell profiles across all three technological platforms. Analysis of possible cross compartment receptor/ligand interactions identified the nephrogenic zone stroma as a source of GDNF. This was unexpected because the cap mesenchyme nephron progenitors had been thought to be the sole source of GDNF, which is a key driver of branching morphogenesis of the collecting duct system. The expression of Gdnf by stromal cells was validated in several ways, including Gdnf in situ hybridization combined with immunohistochemistry for SIX2, and marker of nephron progenitors, and MEIS1, a marker of stromal cells. Finally, the single cell gene expression profiles generated in this study confirmed and extended previous work showing the presence of multilineage priming during kidney development. Nephron progenitors showed stochastic expression of genes associated with multiple potential differentiation lineages. Copyright © 2017 Elsevier Inc. All rights reserved.
Care, Matthew A.; Cocco, Mario; Laye, Jon P.; Barnes, Nicholas; Huang, Yuanxue; Wang, Ming; Barrans, Sharon; Du, Ming; Jack, Andrew; Westhead, David R.; Doody, Gina M.; Tooze, Reuben M.
2014-01-01
Interferon regulatory factor 4 (IRF4) is central to the transcriptional network of activated B-cell-like diffuse large B-cell lymphoma (ABC-DLBCL), an aggressive lymphoma subgroup defined by gene expression profiling. Since cofactor association modifies transcriptional regulatory input by IRF4, we assessed genome occupancy by IRF4 and endogenous cofactors in ABC-DLBCL cell lines. IRF4 partners with SPIB, PU.1 and BATF genome-wide, but SPIB provides the dominant IRF4 partner in this context. Upon SPIB knockdown IRF4 occupancy is depleted and neither PU.1 nor BATF acutely compensates. Integration with ENCODE data from lymphoblastoid cell line GM12878, demonstrates that IRF4 adopts either SPIB- or BATF-centric genome-wide distributions in related states of post-germinal centre B-cell transformation. In primary DLBCL high-SPIB and low-BATF or the reciprocal low-SPIB and high-BATF mRNA expression links to differential gene expression profiles across nine data sets, identifying distinct associations with SPIB occupancy, signatures of B-cell differentiation stage and potential pathogenetic mechanisms. In a population-based patient cohort, SPIBhigh/BATFlow-ABC-DLBCL is enriched for mutation of MYD88, and SPIBhigh/BATFlow-ABC-DLBCL with MYD88-L265P mutation identifies a small subgroup of patients among this otherwise aggressive disease subgroup with distinct favourable outcome. We conclude that differential expression of IRF4 cofactors SPIB and BATF identifies biologically and clinically significant heterogeneity among ABC-DLBCL. PMID:24875472
Velardo, Margaret J; Burger, Corinna; Williams, Philip R; Baker, Henry V; López, M Cecilia; Mareci, Thomas H; White, Todd E; Muzyczka, Nicholas; Reier, Paul J
2004-09-29
Spinal cord injury (SCI) induces a progressive pathophysiology affecting cell survival and neurological integrity via complex and evolving molecular cascades whose interrelationships are not fully understood. The present experiments were designed to: (1) determine potential functional interactions within transcriptional expression profiles obtained after a clinically relevant SCI and (2) test the consistency of transcript expression after SCI in two genetically and immunologically diverse rat strains characterized by differences in T cell competence and associated inflammatory responses. By interrogating Affymetrix U34A rat genome GeneChip microarrays, we defined the transcriptional expression patterns in midcervical contusion lesion sites between 1 and 90 d postinjury of athymic nude (AN) and Sprague Dawley (SD) strains. Stringent statistical analyses detected significant changes in 3638 probe sets, with 80 genes differing between the AN and SD groups. Subsequent detailed functional categorization of these transcripts unveiled an overall tissue remodeling response that was common to both strains. The functionally organized gene profiles were temporally distinct and correlated with repair indices observed microscopically and by magnetic resonance microimaging. Our molecular and anatomical observations have identified a novel, longitudinal perspective of the post-SCI response, namely, that of a highly orchestrated tissue repair and remodeling repertoire with a prominent cutaneous wound healing signature that is conserved between two widely differing rat strains. These results have significant bearing on the continuing development of cellular and pharmacological therapeutics directed at tissue rescue and neuronal regeneration in the injured spinal cord.
The functional genomic studies of curcumin.
Huminiecki, Lukasz; Horbańczuk, Jarosław; Atanasov, Atanas G
2017-10-01
Curcumin is a natural plant-derived compound that has attracted a lot of attention for its anti-cancer activities. Curcumin can slow proliferation of and induce apoptosis in cancer cell lines, but the precise mechanisms of these effects are not fully understood. However, many lines of evidence suggested that curcumin has a potent impact on gene expression profiles; thus, functional genomics should be the key to understanding how curcumin exerts its anti-cancer activities. Here, we review the published functional genomic studies of curcumin focusing on cancer. Typically, a cancer cell line or a grafted tumor were exposed to curcumin and profiled with microarrays, methylation assays, or RNA-seq. Crucially, these studies are in agreement that curcumin has a powerful effect on gene expression. In the majority of the studies, among differentially expressed genes we found genes involved in cell signaling, apoptosis, and the control of cell cycle. Curcumin can also induce specific methylation changes, and is a powerful regulator of the expression of microRNAs which control oncogenesis. We also reflect on how the broader technological progress in transcriptomics has been reflected on the field of curcumin. We conclude by discussing the areas where more functional genomic studies are highly desirable. Integrated OMICS approaches will clearly be the key to understanding curcumin's anticancer and chemopreventive effects. Such strategies may become a template for elucidating the mode of action of other natural products; many natural products have pleiotropic effects that are well suited for a systems-level analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.
Santos, Carmen; Duarte, Sofia; Tedesco, Sara; Fevereiro, Pedro; Costa, Rita L.
2017-01-01
The most dangerous pathogen affecting the production of chestnuts is Phytophthora cinnamomi a hemibiotrophic that causes root rot, also known as ink disease. Little information has been acquired in chestnut on the molecular defense strategies against this pathogen. The expression of eight candidate genes potentially involved in the defense to P. cinnamomi was quantified by digital PCR in Castanea genotypes showing different susceptibility to the pathogen. Seven of the eight candidate genes displayed differentially expressed levels depending on genotype and time-point after inoculation. Cast_Gnk2-like revealed to be the most expressed gene across all experiments and the one that best discriminates between susceptible and resistant genotypes. Our data suggest that the pre-formed defenses are crucial for the resistance of C. crenata to P. cinnamomi. A lower and delayed expression of the eight studied genes was found in the susceptible Castanea sativa, which may be related with the establishment and spread of the disease in this species. A working model integrating the obtained results is presented. PMID:28443110
Endometrial Expression of Steroidogenic Factor 1 Promotes Cystic Glandular Morphogenesis
Vasquez, Yasmin M.; Wu, San-Pin; Anderson, Matthew L.; Hawkins, Shannon M.; Creighton, Chad J.; Ray, Madhumita; Tsai, Sophia Y.; Tsai, Ming-Jer; Lydon, John P.
2016-01-01
Epigenetic silencing of steroidogenic factor 1 (SF1) is lost in endometriosis, potentially contributing to de novo local steroidogenesis favoring inflammation and growth of ectopic endometrial tissue. In this study, we examine the impact of SF1 expression in the eutopic uterus by a novel mouse model that conditionally expresses SF1 in endometrium. In vivo SF1 expression promoted the development of enlarged endometrial glands and attenuated estrogen and progesterone responsiveness. Endometriosis induction by autotransplantation of uterine tissue to the mesenteric membrane resulted in the increase in size of ectopic lesions from SF1-expressing mice. By integrating the SF1-dependent transcriptome with the whole genome binding profile of SF1, we identified uterine-specific SF1-regulated genes involved in Wingless and Progesterone receptor-Hedgehog-Chicken ovalbumin upstream promoter transcription factor II signaling for gland development and epithelium-stroma interaction, respectively. The present results indicate that SF1 directly contributes to the abnormal uterine gland morphogenesis, an inhibition of steroid hormone signaling and activation of an immune response, in addition to previously postulated estrogen production. PMID:27018534
BFDCA: A Comprehensive Tool of Using Bayes Factor for Differential Co-Expression Analysis.
Wang, Duolin; Wang, Juexin; Jiang, Yuexu; Liang, Yanchun; Xu, Dong
2017-02-03
Comparing the gene-expression profiles between biological conditions is useful for understanding gene regulation underlying complex phenotypes. Along this line, analysis of differential co-expression (DC) has gained attention in the recent years, where genes under one condition have different co-expression patterns compared with another. We developed an R package Bayes Factor approach for Differential Co-expression Analysis (BFDCA) for DC analysis. BFDCA is unique in integrating various aspects of DC patterns (including Shift, Cross, and Re-wiring) into one uniform Bayes factor. We tested BFDCA using simulation data and experimental data. Simulation results indicate that BFDCA outperforms existing methods in accuracy and robustness of detecting DC pairs and DC modules. Results of using experimental data suggest that BFDCA can cluster disease-related genes into functional DC subunits and estimate the regulatory impact of disease-related genes well. BFDCA also achieves high accuracy in predicting case-control phenotypes by using significant DC gene pairs as markers. BFDCA is publicly available at http://dx.doi.org/10.17632/jdz4vtvnm3.1. Copyright © 2016 Elsevier Ltd. All rights reserved.
DOT National Transportation Integrated Search
1992-03-01
This report provides aircraft takeoff and landing profiles, aircraft aerodynamic performance coefficients and engine performance coefficients for the aircraft data base (Database 9) in the Integrated Noise Model (INM) computer program. Flight profile...
Cuellar-Baena, Sandra; Landeck, Natalie; Sonnay, Sarah; Buck, Kerstin; Mlynarik, Vladimir; In 't Zandt, René; Kirik, Deniz
2016-06-01
In this study, we used proton-localized spectroscopy ((1) H-MRS) for the acquisition of the neurochemical profile longitudinally in a novel rat model of human wild-type alpha-synuclein (α-syn) over-expression. Our goal was to find out if the increased α-syn load in this model could be linked to changes in metabolites in the frontal cortex. Animals injected with AAV vectors encoding for human α-syn formed the experimental group, whereas green fluorescent protein expressing animals were used as the vector-treated control group and a third group of uninjected animals were used as naïve controls. Data were acquired at 2, 4, and 8 month time points. Nineteen metabolites were quantified in the MR spectra using LCModel software. On the basis of 92 spectra, we evaluated any potential gender effect and found that lactate (Lac) levels were lower in males compared to females, while the opposite was observed for ascorbate (Asc). Next, we assessed the effect of age and found increased levels of GABA, Tau, and GPC+PCho. Finally, we analyzed the effect of treatment and found that Lac levels (p = 0.005) were specifically lower in the α-syn group compared to the green fluorescent protein and control groups. In addition, Asc levels (p = 0.05) were increased in the vector-injected groups, whereas glucose levels remained unchanged. This study indicates that the metabolic switch between glucose-lactate could be detectable in vivo and might be modulated by Asc. No concomitant changes were found in markers of neuronal integrity (e.g., N-acetylaspartate) consistent with the fact that α-syn over-expression in cortical neurons did not result in neurodegeneration in this model. We acquired the neurochemical profile longitudinally in a rat model of human wild-type alpha-synuclein (α-syn) over-expression in cortical neurons. We found that Lactate levels were reduced in the α-syn group compared to the control groups and Ascorbate levels were increased in the vector-injected groups. No changes were found in markers of neuronal integrity consistent with the fact that α-syn over-expression did not result in frank neurodegeneration. © 2016 International Society for Neurochemistry.
Lachance, Denis; Giguère, Isabelle; Séguin, Armand
2014-01-01
This research aimed to investigate the role of diverse transcription factors (TFs) and to delineate gene regulatory networks directly in conifers at a relatively high-throughput level. The approach integrated sequence analyses, transcript profiling, and development of a conifer-specific activation assay. Transcript accumulation profiles of 102 TFs and potential target genes were clustered to identify groups of coordinately expressed genes. Several different patterns of transcript accumulation were observed by profiling in nine different organs and tissues: 27 genes were preferential to secondary xylem both in stems and roots, and other genes were preferential to phelloderm and periderm or were more ubiquitous. A robust system has been established as a screening approach to define which TFs have the ability to regulate a given promoter in planta. Trans-activation or repression effects were observed in 30% of TF–candidate gene promoter combinations. As a proof of concept, phylogenetic analysis and expression and trans-activation data were used to demonstrate that two spruce NAC-domain proteins most likely play key roles in secondary vascular growth as observed in other plant species. This study tested many TFs from diverse families in a conifer tree species, which broadens the knowledge of promoter–TF interactions in wood development and enables comparisons of gene regulatory networks found in angiosperms and gymnosperms. PMID:24713992
NASA Astrophysics Data System (ADS)
Kujawinski, E. B.; Longnecker, K.; Alexander, H.; Dyhrman, S.; Jenkins, B. D.; Rynearson, T. A.
2016-02-01
Phytoplankton blooms in coastal areas contribute a large fraction of primary production to the global oceans. Despite their central importance, there are fundamental unknowns in phytoplankton community metabolism, which limit the development of a more complete understanding of the carbon cycle. Within this complex setting, the tools of systems biology hold immense potential for profiling community metabolism and exploring links to the carbon cycle, but have rarely been applied together in this context. Here we focus on phytoplankton community samples collected from a model coastal system over a three-week period. At each sampling point, we combined two assessments of metabolic function: the meta-transcriptome, or the genes that are expressed by all organisms at each sampling point, and the metabolome, or the intracellular molecules produced during the community's metabolism. These datasets are inherently complementary, with gene expression likely to vary in concert with the concentrations of metabolic intermediates. Indeed, preliminary data show coherence in transcripts and metabolites associated with nutrient stress response and with fixed carbon oxidation. To date, these datasets are rarely integrated across their full complexity but together they provide unequivocal evidence of specific metabolic pathways by individual phytoplankton taxa, allowing a more comprehensive systems view of this dynamic environment. Future application of multi-omic profiling will facilitate a more complete understanding of metabolic reactions at the foundation of the carbon cycle.
Jiang, Ning; Liu, Hong-fang; Li, Si-di; Zhou, Wen-xia; Zhang, Yong-xiang; Zhang, Qi; Yan, Xian-zhong
2015-06-01
To investigate specific changes in metabolites and proteins of Kidney-Yin Deficiency Syndrome (KYDS) patients with diabetes mellitus (DM) in China. KYDS (n=29) and non-KYDS (n=23) patients with DM were recruited for this study. The KYDS was diagnosed by two senior TCM clinicians separately. The metabonomic and proteomic profiles of the patients were assessed using a metabonomic strategy based on NMR with multivariate analysis and a proteomic strategy based on MALDI-TOF-MS, respectively. Eighteen upregulated peptides and thirty downregulated peptides were observed in the plasma of the KYDS patients. Comparing the proteomic profiles of the KYDS and non-KYDS groups, however, no significantly differentially expressed peptides were found. At the same time, major metabolic alterations were found to distinguish the two groups, including eight significantly changed metabolites (creatinine, citrate, TMAO, phenylalanine, tyrosine, alanine, glycine and taurine). The levels of creatinine, citrate, TMAO, phenylalanine and tyrosine were decreased, whereas the levels of alanine, glycine and taurine were increased in the KYDS patients. These biochemical changes were found to be associated with alterations in amino acid metabolism, energy metabolism and gut microflora. The identification of distinct expression profiles of metabolites and signaling pathways in KYDS patients with DM suggests that there are indeed molecular signatures underlying the principles of 'Syndrome Differentiation' in traditional Chinese medicine.
An emerging cyberinfrastructure for biodefense pathogen and pathogen–host data
Zhang, C.; Crasta, O.; Cammer, S.; Will, R.; Kenyon, R.; Sullivan, D.; Yu, Q.; Sun, W.; Jha, R.; Liu, D.; Xue, T.; Zhang, Y.; Moore, M.; McGarvey, P.; Huang, H.; Chen, Y.; Zhang, J.; Mazumder, R.; Wu, C.; Sobral, B.
2008-01-01
The NIAID-funded Biodefense Proteomics Resource Center (RC) provides storage, dissemination, visualization and analysis capabilities for the experimental data deposited by seven Proteomics Research Centers (PRCs). The data and its publication is to support researchers working to discover candidates for the next generation of vaccines, therapeutics and diagnostics against NIAID's Category A, B and C priority pathogens. The data includes transcriptional profiles, protein profiles, protein structural data and host–pathogen protein interactions, in the context of the pathogen life cycle in vivo and in vitro. The database has stored and supported host or pathogen data derived from Bacillus, Brucella, Cryptosporidium, Salmonella, SARS, Toxoplasma, Vibrio and Yersinia, human tissue libraries, and mouse macrophages. These publicly available data cover diverse data types such as mass spectrometry, yeast two-hybrid (Y2H), gene expression profiles, X-ray and NMR determined protein structures and protein expression clones. The growing database covers over 23 000 unique genes/proteins from different experiments and organisms. All of the genes/proteins are annotated and integrated across experiments using UniProt Knowledgebase (UniProtKB) accession numbers. The web-interface for the database enables searching, querying and downloading at the level of experiment, group and individual gene(s)/protein(s) via UniProtKB accession numbers or protein function keywords. The system is accessible at http://www.proteomicsresource.org/. PMID:17984082
Gene expression inference with deep learning.
Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui
2016-06-15
Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Gene expression inference with deep learning
Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui
2016-01-01
Motivation: Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. Results: We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. Availability and implementation: D-GEX is available at https://github.com/uci-cbcl/D-GEX. Contact: xhx@ics.uci.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26873929
Chumnanpuen, Pramote; Zhang, Jie; Nookaew, Intawat; Nielsen, Jens
2012-07-01
In the yeast Saccharomyces cerevisiae many genes involved in lipid biosynthesis are transcriptionally controlled by inositol-choline and the protein kinase Snf1. Here we undertook a global study on how inositol-choline and Snf1 interact in controlling lipid metabolism in yeast. Using both a reference strain (CEN.PK113-7D) and a snf1Δ strain cultured at different nutrient limitations (carbon and nitrogen), at a fixed specific growth rate of 0.1 h(-1), and at different inositol choline concentrations, we quantified the expression of genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through integrated analysis of the transcriptome, the lipid profiling and the fluxome, it was possible to obtain a high quality, large-scale dataset that could be used to identify correlations and associations between the different components. At the transcription level, Snf1 and inositol-choline interact either directly through the main phospholipid-involving transcription factors (i.e. Ino2, Ino4, and Opi1) or through other transcription factors e.g. Gis1, Mga2, and Hac1. However, there seems to be flux regulation at the enzyme levels of several lipid involving enzymes. The analysis showed the strength of using both transcriptome and lipid profiling analysis for mapping the co-influence of inositol-choline and Snf1 on phospholipid metabolism.
Profiles of gene expression associated with tetracycline over expression of HSP70 in MCF-7 breast cancer cells.
Heat shock proteins (HSPs) protect cells from damage through their function as molecular chaperones. Some cancers reveal high levels of HSP70 expression in asso...
Zhang, Z; Li, L; Yang, W; Cao, Y; Shi, Y; Li, X; Zhang, Q
2017-02-01
To investigate the effects of different doses of insulin-like growth factor 1 (IGF-1) on the cartilage layer and subchondral bone (SB) during repair of full-thickness articular cartilage (AC) defects. IGF-1-loaded collagen membrane was implanted into full-thickness AC defects in rabbits. The effects of two different doses of IGF-1 on cartilage layer and SB adjacent to the defect, the cartilage structure, formation and integration, and the new SB formation were evaluated at the 1st, 4th and 8th week postoperation. Meanwhile, after 1 week treatment, the relative mRNA expressions in tissues adjacent to the defect, including cartilage and SB were determined by quantitative real-time RT-PCR (qRT-PCR), respectively. Different doses of IGF-1 induced different gene expression profiles in tissues adjacent to the defect and resulted in different repair outcomes. Particularly, at high dose IGF-1 aided cell survival, regulated the gene expressions in cartilage layer adjacent defect and altered ECM composition more effectively, improved the formation and integrity of neo-cartilage. While, at low dose IGF-1 regulated the gene expressions in SB more efficaciously and subsequently promoted the SB remodeling and reconstruction. Different doses of IGF-1 induced different responses of cartilage or SB during the repair of full-thickness AC defects. Particularly, high dose of IGF-1 was more beneficial to the neo-cartilage formation and integration, while low dose of it was more effective for the SB formation. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
Santiago, Jose A; Potashkin, Judith A
2013-01-01
Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP), previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Prognostic Biomarker Study (PROBE), revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients. These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first time that increased expression of APP in blood may modulate the neurodegenerative phenotype in type 2 diabetes patients.
SU-F-T-527: A Novel Dynamic Multileaf Collimator Leaf-Sequencing Algorithm in Radiation Therapy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jing, J; Lin, H; Chow, J
Purpose: A novel leaf-sequencing algorithm is developed for generating arbitrary beam intensity profiles in discrete levels using dynamic multileaf collimator (MLC). The efficiency of this dynamic MLC leaf-sequencing method was evaluated using external beam treatment plans delivered by intensity modulated radiation therapy technique. Methods: To qualify and validate this algorithm, integral test for the beam segment of MLC generated by the CORVUS treatment planning system was performed with clinical intensity map experiments. The treatment plans were optimized and the fluence maps for all photon beams were determined. This algorithm started with the algebraic expression for the area under the beammore » profile. The coefficients in the expression can be transformed into the specifications for the leaf-setting sequence. The leaf optimization procedure was then applied and analyzed for clinical relevant intensity profiles in cancer treatment. Results: The macrophysical effect of this method can be described by volumetric plan evaluation tools such as dose-volume histograms (DVHs). The DVH results are in good agreement compared to those from the CORVUS treatment planning system. Conclusion: We developed a dynamic MLC method to examine the stability of leaf speed including effects of acceleration and deceleration of leaf motion in order to make sure the stability of leaf speed did not affect the intensity profile generated. It was found that the mechanical requirements were better satisfied using this method. The Project is sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry.« less
Similar protein expression profiles of ovarian and endometrial high-grade serous carcinomas.
Hiramatsu, Kosuke; Yoshino, Kiyoshi; Serada, Satoshi; Yoshihara, Kosuke; Hori, Yumiko; Fujimoto, Minoru; Matsuzaki, Shinya; Egawa-Takata, Tomomi; Kobayashi, Eiji; Ueda, Yutaka; Morii, Eiichi; Enomoto, Takayuki; Naka, Tetsuji; Kimura, Tadashi
2016-03-01
Ovarian and endometrial high-grade serous carcinomas (HGSCs) have similar clinical and pathological characteristics; however, exhaustive protein expression profiling of these cancers has yet to be reported. We performed protein expression profiling on 14 cases of HGSCs (7 ovarian and 7 endometrial) and 18 endometrioid carcinomas (9 ovarian and 9 endometrial) using iTRAQ-based exhaustive and quantitative protein analysis. We identified 828 tumour-expressed proteins and evaluated the statistical similarity of protein expression profiles between ovarian and endometrial HGSCs using unsupervised hierarchical cluster analysis (P<0.01). Using 45 statistically highly expressed proteins in HGSCs, protein ontology analysis detected two enriched terms and proteins composing each term: IMP2 and MCM2. Immunohistochemical analyses confirmed the higher expression of IMP2 and MCM2 in ovarian and endometrial HGSCs as well as in tubal and peritoneal HGSCs than in endometrioid carcinomas (P<0.01). The knockdown of either IMP2 or MCM2 by siRNA interference significantly decreased the proliferation rate of ovarian HGSC cell line (P<0.01). We demonstrated the statistical similarity of the protein expression profiles of ovarian and endometrial HGSC beyond the organs. We suggest that increased IMP2 and MCM2 expression may underlie some of the rapid HGSC growth observed clinically.
Wan, B; Yarbrough, J W; Schultz, T W
2008-01-01
This study was undertaken to test the hypothesis that structurally similar PAHs induce similar gene expression profiles. THP-1 cells were exposed to a series of 12 selected PAHs at 50 microM for 24 hours and gene expressions profiles were analyzed using both unsupervised and supervised methods. Clustering analysis of gene expression profiles revealed that the 12 tested chemicals were grouped into five clusters. Within each cluster, the gene expression profiles are more similar to each other than to the ones outside the cluster. One-methylanthracene and 1-methylfluorene were found to have the most similar profiles; dibenzothiophene and dibenzofuran were found to share common profiles with fluorine. As expression pattern comparisons were expanded, similarity in genomic fingerprint dropped off dramatically. Prediction analysis of microarrays (PAM) based on the clustering pattern generated 49 predictor genes that can be used for sample discrimination. Moreover, a significant analysis of Microarrays (SAM) identified 598 genes being modulated by tested chemicals with a variety of biological processes, such as cell cycle, metabolism, and protein binding and KEGG pathways being significantly (p < 0.05) affected. It is feasible to distinguish structurally different PAHs based on their genomic fingerprints, which are mechanism based.
Ficklin, Stephen P; Feltus, Frank Alex
2013-01-01
Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance.
Ficklin, Stephen P.; Feltus, Frank Alex
2013-01-01
Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance. PMID:23874666
Tahiri, Andliena; Leivonen, Suvi-Katri; Lüders, Torben; Steinfeld, Israel; Ragle Aure, Miriam; Geisler, Jürgen; Mäkelä, Rami; Nord, Silje; Riis, Margit L H; Yakhini, Zohar; Kleivi Sahlberg, Kristine; Børresen-Dale, Anne-Lise; Perälä, Merja; Bukholm, Ida R K; Kristensen, Vessela N
2014-01-01
MicroRNAs (miRNAs) are endogenous non-coding RNAs, which play an essential role in the regulation of gene expression during carcinogenesis. The role of miRNAs in breast cancer has been thoroughly investigated, and although many miRNAs are identified as cancer related, little is known about their involvement in benign tumors. In this study, we investigated miRNA expression profiles in the two most common types of human benign tumors (fibroadenoma/fibroadenomatosis) and in malignant breast tumors and explored their role as oncomirs and tumor suppressor miRNAs. Here, we identified 33 miRNAs with similar deregulated expression in both benign and malignant tumors compared with the expression levels of those in normal tissue, including breast cancer-related miRNAs such as let-7, miR-21 and miR-155. Additionally, messenger RNA (mRNA) expression profiles were obtained for some of the same samples. Using integrated mRNA/miRNA expression analysis, we observed that overexpression of certain miRNAs co-occurred with a significant downregulation of their candidate target mRNAs in both benign and malignant tumors. In support of these findings, in vitro functional screening of the downregulated miRNAs in non-malignant and breast cancer cell lines identified several possible tumor suppressor miRNAs, including miR-193b, miR-193a-3p, miR-126, miR-134, miR-132, miR-486-5p, miR-886-3p, miR-195 and miR-497, showing reduced growth when re-expressed in cancer cells. The finding of deregulated expression of oncomirs and tumor suppressor miRNAs in benign breast tumors is intriguing, indicating that they may play a role in proliferation. A role of cancer-related miRNAs in the early phases of carcinogenesis and malignant transformation can, therefore, not be ruled out.
Mei, Nan; Guo, Lei; Zhang, Lu; Shi, Leming; Sun, Yongming Andrew; Fung, Chris; Moland, Carrie L; Dial, Stacey L; Fuscoe, James C; Chen, Tao
2006-01-01
Background Comfrey is consumed by humans as a vegetable and a tea, and has been used as an herbal medicine for more than 2000 years. Comfrey, however, is hepatotoxic in livestock and humans and carcinogenic in experimental animals. Our previous study suggested that comfrey induces liver tumors by a genotoxic mechanism and that the pyrrolizidine alkaloids in the plant are responsible for mutation induction and tumor initiation in rat liver. Results In this study, we identified comfrey-induced gene expression profile in the livers of rats. Groups of 6 male transgenic Big Blue rats were fed a basal diet and a diet containing 8% comfrey roots, a dose that resulted in liver tumors in a previous carcinogenicity bioassay. The animals were treated for 12 weeks and sacrificed one day after the final treatment. We used a rat microarray containing 26,857 genes to perform genome-wide gene expression studies. Dietary comfrey resulted in marked changes in liver gene expression, as well as in significant decreases in the body weight and increases in liver mutant frequency. When a two-fold cutoff value and a P-value less than 0.01 were selected, 2,726 genes were identified as differentially expressed in comfrey-fed rats compared to control animals. Among these genes, there were 1,617 genes associated by Ingenuity Pathway Analysis with particular functions, and the differentially expressed genes in comfrey-fed rat livers were involved in metabolism, injury of endothelial cells, and liver injury and abnormalities, including liver fibrosis and cancer development. Conclusion The gene expression profile provides us a better understanding of underlying mechanisms for comfrey-induced hepatic toxicity. Integration of gene expression changes with known pathological changes can be used to formulate a mechanistic scheme for comfrey-induced liver toxicity and tumorigenesis. PMID:17118137
Cao, Aqin; Jin, Jie; Li, Shaoqing
2017-01-01
Inter-specific hybridization and backcrossing commonly occur in plants. The use of progeny generated from inter-specific hybridization and backcrossing has been developed as a novel model system to explore gene expression divergence. The present study investigated the analysis of gene expression and miRNA regulation in backcrossed introgression lines constructed from cultivated and wild rice. High-throughput sequencing was used to compare gene and miRNA expression profiles in three progeny lines (L1710, L1817 and L1730), with different plant heights resulting from the backcrossing of introgression lines (BC2F12) and their parents (O. sativa and O. longistaminata). A total of 25,387 to 26,139 mRNAs and 379 to 419 miRNAs were obtained in these rice lines. More differentially expressed genes and miRNAs were detected in progeny/O. longistaminata comparison groups than in progeny/O. sativa comparison groups. Approximately 80% of the genes and miRNAs showed expression level dominance to O. sativa, indicating that three progeny lines were closer to the recurrent parent, which might be influenced by their parental genome dosage. Approximately 16% to 64% of the differentially expressed miRNAs possessing coherent target genes were predicted, and many of these miRNAs regulated multiple target genes. Most genes were up-regulated in progeny lines compared with their parents, but down-regulated in the higher plant height line in the comparison groups among the three progeny lines. Moreover, certain genes related to cell walls and plant hormones might play crucial roles in the plant height variations of the three progeny lines. Taken together, these results provided valuable information on the molecular mechanisms of hybrid backcrossing and plant height variations based on the gene and miRNA expression levels in the three progeny lines. PMID:28859136
Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma
Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han; Lim, Jing Quan; Huang, Mi Ni; Padmanabhan, Nisha; Nellore, Vishwa; Kongpetch, Sarinya; Ng, Alvin Wei Tian; Ng, Ley Moy; Choo, Su Pin; Myint, Swe Swe; Thanan, Raynoo; Nagarajan, Sanjanaa; Lim, Weng Khong; Ng, Cedric Chuan Young; Boot, Arnoud; Liu, Mo; Ong, Choon Kiat; Rajasegaran, Vikneswari; Lie, Stefanus; Lim, Alvin Soon Tiong; Lim, Tse Hui; Tan, Jing; Loh, Jia Liang; McPherson, John R.; Khuntikeo, Narong; Bhudhisawasdi, Vajaraphongsa; Yongvanit, Puangrat; Wongkham, Sopit; Totoki, Yasushi; Nakamura, Hiromi; Arai, Yasuhito; Yamasaki, Satoshi; Chow, Pierce Kah-Hoe; Chung, Alexander Yaw Fui; Ooi, London Lucien Peng Jin; Lim, Kiat Hon; Dima, Simona; Duda, Dan G.; Popescu, Irinel; Broet, Philippe; Hsieh, Sen-Yung; Yu, Ming-Chin; Scarpa, Aldo; Lai, Jiaming; Luo, Di-Xian; Carvalho, André Lopes; Vettore, André Luiz; Rhee, Hyungjin; Park, Young Nyun; Alexandrov, Ludmil B.; Gordân, Raluca; Rozen, Steven G.; Shibata, Tatsuhiro; Pairojkul, Chawalit; Teh, Bin Tean; Tan, Patrick
2017-01-01
Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters – Fluke-Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3′UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores – mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer. PMID:28667006
Tan, Jie; Doing, Georgia; Lewis, Kimberley A; Price, Courtney E; Chen, Kathleen M; Cady, Kyle C; Perchuk, Barret; Laub, Michael T; Hogan, Deborah A; Greene, Casey S
2017-07-26
Cross-experiment comparisons in public data compendia are challenged by unmatched conditions and technical noise. The ADAGE method, which performs unsupervised integration with denoising autoencoder neural networks, can identify biological patterns, but because ADAGE models, like many neural networks, are over-parameterized, different ADAGE models perform equally well. To enhance model robustness and better build signatures consistent with biological pathways, we developed an ensemble ADAGE (eADAGE) that integrated stable signatures across models. We applied eADAGE to a compendium of Pseudomonas aeruginosa gene expression profiling experiments performed in 78 media. eADAGE revealed a phosphate starvation response controlled by PhoB in media with moderate phosphate and predicted that a second stimulus provided by the sensor kinase, KinB, is required for this PhoB activation. We validated this relationship using both targeted and unbiased genetic approaches. eADAGE, which captures stable biological patterns, enables cross-experiment comparisons that can highlight measured but undiscovered relationships. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jusakul, Apinya; Cutcutache, Ioana; Yong, Chern Han
Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters - Fluke- Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3’UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation ofmore » H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores - mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Lastly, our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer.« less
ICG: a wiki-driven knowledgebase of internal control genes for RT-qPCR normalization.
Sang, Jian; Wang, Zhennan; Li, Man; Cao, Jiabao; Niu, Guangyi; Xia, Lin; Zou, Dong; Wang, Fan; Xu, Xingjian; Han, Xiaojiao; Fan, Jinqi; Yang, Ye; Zuo, Wanzhu; Zhang, Yang; Zhao, Wenming; Bao, Yiming; Xiao, Jingfa; Hu, Songnian; Hao, Lili; Zhang, Zhang
2018-01-04
Real-time quantitative PCR (RT-qPCR) has become a widely used method for accurate expression profiling of targeted mRNA and ncRNA. Selection of appropriate internal control genes for RT-qPCR normalization is an elementary prerequisite for reliable expression measurement. Here, we present ICG (http://icg.big.ac.cn), a wiki-driven knowledgebase for community curation of experimentally validated internal control genes as well as their associated experimental conditions. Unlike extant related databases that focus on qPCR primers in model organisms (mainly human and mouse), ICG features harnessing collective intelligence in community integration of internal control genes for a variety of species. Specifically, it integrates a comprehensive collection of more than 750 internal control genes for 73 animals, 115 plants, 12 fungi and 9 bacteria, and incorporates detailed information on recommended application scenarios corresponding to specific experimental conditions, which, collectively, are of great help for researchers to adopt appropriate internal control genes for their own experiments. Taken together, ICG serves as a publicly editable and open-content encyclopaedia of internal control genes and accordingly bears broad utility for reliable RT-qPCR normalization and gene expression characterization in both model and non-model organisms. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.
Curtis, Christina; Shah, Sohrab P; Chin, Suet-Feung; Turashvili, Gulisa; Rueda, Oscar M; Dunning, Mark J; Speed, Doug; Lynch, Andy G; Samarajiwa, Shamith; Yuan, Yinyin; Gräf, Stefan; Ha, Gavin; Haffari, Gholamreza; Bashashati, Ali; Russell, Roslin; McKinney, Steven; Langerød, Anita; Green, Andrew; Provenzano, Elena; Wishart, Gordon; Pinder, Sarah; Watson, Peter; Markowetz, Florian; Murphy, Leigh; Ellis, Ian; Purushotham, Arnie; Børresen-Dale, Anne-Lise; Brenton, James D; Tavaré, Simon; Caldas, Carlos; Aparicio, Samuel
2012-04-18
The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.
Kim, Jaehee; Ogden, Robert Todd; Kim, Haseong
2013-10-18
Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization.The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics.
Chaitankar, Vijender; Karakülah, Gökhan; Ratnapriya, Rinki; Giuste, Felipe O.; Brooks, Matthew J.; Swaroop, Anand
2016-01-01
The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well. PMID:27297499
NASA Astrophysics Data System (ADS)
Misu, L.; Budayasa, I. K.; Lukito, A.
2018-01-01
This research is to describe metacognition profile of female and male mathematics’ pre-service teachers in understanding the concept of integral calculus. The subjects of this study are one female and 1 male mathematics’ pre-service teachers who have studied integral calculus. This research type is an explorative study with the qualitative approach. The main data collection of this research was obtained by using Interview technique. In addition, there are supporting data which is the result of the written work of research subjects (SP) in understanding the question of integral calculus. The results of this study are as follows: There is a difference in metacognition profiles between male and female mathematics’ pre-service teachers in the understanding concept of integral calculus in the interpreting category, especially the definite integral concept. While in the category of exemplifying, there is no difference in metacognition profile between male and female mathematics’ pre-service teachers either the definite integral concept and the indefinite integral concept.
Hirayama, Mio; Kobayashi, Daiki; Mizuguchi, Souhei; Morikawa, Takashi; Nagayama, Megumi; Midorikawa, Uichi; Wilson, Masayo M; Nambu, Akiko N; Yoshizawa, Akiyasu C; Kawano, Shin; Araki, Norie
2013-05-01
Neurofibromatosis type 1 (NF1) tumor suppressor gene product, neurofibromin, functions in part as a Ras-GAP, and though its loss is implicated in the neuronal abnormality of NF1 patients, its precise cellular function remains unclear. To study the molecular mechanism of NF1 pathogenesis, we prepared NF1 gene knockdown (KD) PC12 cells, as a NF1 disease model, and analyzed their molecular (gene and protein) expression profiles with a unique integrated proteomics approach, comprising iTRAQ, 2D-DIGE, and DNA microarrays, using an integrated protein and gene expression analysis chart (iPEACH). In NF1-KD PC12 cells showing abnormal neuronal differentiation after NGF treatment, of 3198 molecules quantitatively identified and listed in iPEACH, 97 molecules continuously up- or down-regulated over time were extracted. Pathway and network analysis further revealed overrepresentation of calcium signaling and transcriptional regulation by glucocorticoid receptor (GR) in the up-regulated protein set, whereas nerve system development was overrepresented in the down-regulated protein set. The novel up-regulated network we discovered, "dynein IC2-GR-COX-1 signaling," was then examined in NF1-KD cells. Validation studies confirmed that NF1 knockdown induces altered splicing and phosphorylation patterns of dynein IC2 isomers, up-regulation and accumulation of nuclear GR, and increased COX-1 expression in NGF-treated cells. Moreover, the neurite retraction phenotype observed in NF1-KD cells was significantly recovered by knockdown of the dynein IC2-C isoform and COX-1. In addition, dynein IC2 siRNA significantly inhibited nuclear translocation and accumulation of GR and up-regulation of COX-1 expression. These results suggest that dynein IC2 up-regulates GR nuclear translocation and accumulation, and subsequently causes increased COX-1 expression, in this NF1 disease model. Our integrated proteomics strategy, which combines multiple approaches, demonstrates that NF1-related neural abnormalities are, in part, caused by up-regulation of dynein IC2-GR-COX-1 signaling, which may be a novel therapeutic target for NF1.
Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells.
Gatto, Sole; Puri, Pier Lorenzo; Malecova, Barbora
2017-01-01
Single cell gene expression profiling is a fundamental tool for studying the heterogeneity of a cell population by addressing the phenotypic and functional characteristics of each cell. Technological advances that have coupled microfluidic technologies with high-throughput quantitative RT-PCR analyses have enabled detailed analyses of single cells in various biological contexts. In this chapter, we describe the procedure for isolating the skeletal muscle interstitial cells termed Fibro-Adipogenic Progenitors (FAPs ) and their gene expression profiling at the single cell level. Moreover, we accompany our bench protocol with bioinformatics analysis designed to process raw data as well as to visualize single cell gene expression data. Single cell gene expression profiling is therefore a useful tool in the investigation of FAPs heterogeneity and their contribution to muscle homeostasis.
Gene expression profiles in arsenic-treated MCF-7 breast cancer cells expressing different levels of HSP70
Gail Nelson, Susan Hester, Ernest Winkfield, Jill Barnes, James Allen
Environmental Carcinogenesis Division, NHEERL, ORD, US Environmental Protection Agency, Rese...
iPcc: a novel feature extraction method for accurate disease class discovery and prediction
Ren, Xianwen; Wang, Yong; Zhang, Xiang-Sun; Jin, Qi
2013-01-01
Gene expression profiling has gradually become a routine procedure for disease diagnosis and classification. In the past decade, many computational methods have been proposed, resulting in great improvements on various levels, including feature selection and algorithms for classification and clustering. In this study, we present iPcc, a novel method from the feature extraction perspective to further propel gene expression profiling technologies from bench to bedside. We define ‘correlation feature space’ for samples based on the gene expression profiles by iterative employment of Pearson’s correlation coefficient. Numerical experiments on both simulated and real gene expression data sets demonstrate that iPcc can greatly highlight the latent patterns underlying noisy gene expression data and thus greatly improve the robustness and accuracy of the algorithms currently available for disease diagnosis and classification based on gene expression profiles. PMID:23761440
Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo
2014-01-01
We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782
Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo
2014-01-01
We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.
The Prediction of Drug-Disease Correlation Based on Gene Expression Data.
Cui, Hui; Zhang, Menghuan; Yang, Qingmin; Li, Xiangyi; Liebman, Michael; Yu, Ying; Xie, Lu
2018-01-01
The explosive growth of high-throughput experimental methods and resulting data yields both opportunity and challenge for selecting the correct drug to treat both a specific patient and their individual disease. Ideally, it would be useful and efficient if computational approaches could be applied to help achieve optimal drug-patient-disease matching but current efforts have met with limited success. Current approaches have primarily utilized the measureable effect of a specific drug on target tissue or cell lines to identify the potential biological effect of such treatment. While these efforts have met with some level of success, there exists much opportunity for improvement. This specifically follows the observation that, for many diseases in light of actual patient response, there is increasing need for treatment with combinations of drugs rather than single drug therapies. Only a few previous studies have yielded computational approaches for predicting the synergy of drug combinations by analyzing high-throughput molecular datasets. However, these computational approaches focused on the characteristics of the drug itself, without fully accounting for disease factors. Here, we propose an algorithm to specifically predict synergistic effects of drug combinations on various diseases, by integrating the data characteristics of disease-related gene expression profiles with drug-treated gene expression profiles. We have demonstrated utility through its application to transcriptome data, including microarray and RNASeq data, and the drug-disease prediction results were validated using existing publications and drug databases. It is also applicable to other quantitative profiling data such as proteomics data. We also provide an interactive web interface to allow our Prediction of Drug-Disease method to be readily applied to user data. While our studies represent a preliminary exploration of this critical problem, we believe that the algorithm can provide the basis for further refinement towards addressing a large clinical need.
Kraggerud, Sigrid Marie; Hoei-Hansen, Christina E.; Alagaratnam, Sharmini; Skotheim, Rolf I.; Abeler, Vera M.
2013-01-01
This review focuses on the molecular characteristics and development of rare malignant ovarian germ cell tumors (mOGCTs). We provide an overview of the genomic aberrations assessed by ploidy, cytogenetic banding, and comparative genomic hybridization. We summarize and discuss the transcriptome profiles of mRNA and microRNA (miRNA), and biomarkers (DNA methylation, gene mutation, individual protein expression) for each mOGCT histological subtype. Parallels between the origin of mOGCT and their male counterpart testicular GCT (TGCT) are discussed from the perspective of germ cell development, endocrinological influences, and pathogenesis, as is the GCT origin in patients with disorders of sex development. Integrated molecular profiles of the 3 main histological subtypes, dysgerminoma (DG), yolk sac tumor (YST), and immature teratoma (IT), are presented. DGs show genomic aberrations comparable to TGCT. In contrast, the genome profiles of YST and IT are different both from each other and from DG/TGCT. Differences between DG and YST are underlined by their miRNA/mRNA expression patterns, suggesting preferential involvement of the WNT/β-catenin and TGF-β/bone morphogenetic protein signaling pathways among YSTs. Characteristic protein expression patterns are observed in DG, YST and IT. We propose that mOGCT develop through different developmental pathways, including one that is likely shared with TGCT and involves insufficient sexual differentiation of the germ cell niche. The molecular features of the mOGCTs underline their similarity to pluripotent precursor cells (primordial germ cells, PGCs) and other stem cells. This similarity combined with the process of ovary development, explain why mOGCTs present so early in life, and with greater histological complexity, than most somatic solid tumors. PMID:23575763
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eveillard, Alexandre; Lasserre, Frederic; Tayrac, Marie de
2009-05-01
Phthalates are industrial additives widely used as plasticizers. In addition to deleterious effects on male genital development, population studies have documented correlations between phthalates exposure and impacts on reproductive tract development and on the metabolic syndrome in male adults. In this work we investigated potential mechanisms underlying the impact of DEHP on adult mouse liver in vivo. A parallel analysis of hepatic transcript and metabolic profiles from adult mice exposed to varying DEHP doses was performed. Hepatic genes modulated by DEHP are predominantly PPAR{alpha} targets. However, the induction of prototypic cytochrome P450 genes strongly supports the activation of additional NRmore » pathways, including Constitutive Androstane Receptor (CAR). Integration of transcriptomic and metabonomic profiles revealed a correlation between the impacts of DEHP on genes and metabolites related to heme synthesis and to the Rev-erb{alpha} pathway that senses endogenous heme level. We further confirmed the combined impact of DEHP on the hepatic expression of Alas1, a critical enzyme in heme synthesis and on the expression of Rev-erb{alpha} target genes involved in the cellular clock and in energy metabolism. This work shows that DEHP interferes with hepatic CAR and Rev-erb{alpha} pathways which are both involved in the control of metabolism. The identification of these new hepatic pathways targeted by DEHP could contribute to metabolic and endocrine disruption associated with phthalate exposure. Gene expression profiles performed on microdissected testis territories displayed a differential responsiveness to DEHP. Altogether, this suggests that impacts of DEHP on adult organs, including testis, could be documented and deserve further investigations.« less
IHE cross-enterprise document sharing for imaging: design challenges
NASA Astrophysics Data System (ADS)
Noumeir, Rita
2006-03-01
Integrating the Healthcare Enterprise (IHE) has recently published a new integration profile for sharing documents between multiple enterprises. The Cross-Enterprise Document Sharing Integration Profile (XDS) lays the basic framework for deploying regional and national Electronic Health Record (EHR). This profile proposes an architecture based on a central Registry that holds metadata information describing published Documents residing in one or multiple Documents Repositories. As medical images constitute important information of the patient health record, it is logical to extend the XDS Integration Profile to include images. However, including images in the EHR presents many challenges. The complete image set is very large; it is useful for radiologists and other specialists such as surgeons and orthopedists. The imaging report, on the other hand, is widely needed and its broad accessibility is vital for achieving optimal patient care. Moreover, a subset of relevant images may also be of wide interest along with the report. Therefore, IHE recently published a new integration profile for sharing images and imaging reports between multiple enterprises. This new profile, the Cross-Enterprise Document Sharing for Imaging (XDS-I), is based on the XDS architecture. The XDS-I integration solution that is published as part of the IHE Technical Framework is the result of an extensive investigation effort of several design solutions. This paper presents and discusses the design challenges and the rationales behind the design decisions of the IHE XDS-I Integration Profile, for a better understanding and appreciation of the final published solution.
Weniger, Markus; Engelmann, Julia C; Schultz, Jörg
2007-01-01
Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at . PMID:17543125
Plaisier, Christopher L; Bare, J Christopher; Baliga, Nitin S
2011-07-01
Transcriptome profiling studies have produced staggering numbers of gene co-expression signatures for a variety of biological systems. A significant fraction of these signatures will be partially or fully explained by miRNA-mediated targeted transcript degradation. miRvestigator takes as input lists of co-expressed genes from Caenorhabditis elegans, Drosophila melanogaster, G. gallus, Homo sapiens, Mus musculus or Rattus norvegicus and identifies the specific miRNAs that are likely to bind to 3' un-translated region (UTR) sequences to mediate the observed co-regulation. The novelty of our approach is the miRvestigator hidden Markov model (HMM) algorithm which systematically computes a similarity P-value for each unique miRNA seed sequence from the miRNA database miRBase to an overrepresented sequence motif identified within the 3'-UTR of the query genes. We have made this miRNA discovery tool accessible to the community by integrating our HMM algorithm with a proven algorithm for de novo discovery of miRNA seed sequences and wrapping these algorithms into a user-friendly interface. Additionally, the miRvestigator web server also produces a list of putative miRNA binding sites within 3'-UTRs of the query transcripts to facilitate the design of validation experiments. The miRvestigator is freely available at http://mirvestigator.systemsbiology.net.
Schlecht, Ulrich; Erb, Ionas; Demougin, Philippe; Robine, Nicolas; Borde, Valérie; van Nimwegen, Erik; Nicolas, Alain
2008-01-01
The autonomously replicating sequence binding factor 1 (Abf1) was initially identified as an essential DNA replication factor and later shown to be a component of the regulatory network controlling mitotic and meiotic cell cycle progression in budding yeast. The protein is thought to exert its functions via specific interaction with its target site as part of distinct protein complexes, but its roles during mitotic growth and meiotic development are only partially understood. Here, we report a comprehensive approach aiming at the identification of direct Abf1-target genes expressed during fermentation, respiration, and sporulation. Computational prediction of the protein's target sites was integrated with a genome-wide DNA binding assay in growing and sporulating cells. The resulting data were combined with the output of expression profiling studies using wild-type versus temperature-sensitive alleles. This work identified 434 protein-coding loci as being transcriptionally dependent on Abf1. More than 60% of their putative promoter regions contained a computationally predicted Abf1 binding site and/or were bound by Abf1 in vivo, identifying them as direct targets. The present study revealed numerous loci previously unknown to be under Abf1 control, and it yielded evidence for the protein's variable DNA binding pattern during mitotic growth and meiotic development. PMID:18305101
Wang, Lei; Su, Hongyan; Han, Liya; Wang, Chuanqi; Sun, Yanlin; Liu, Fenghong
2014-07-15
Mitogen-activated protein kinase (MAPK) cascades are universal signal transduction modules that play essential roles in plant growth, development and stress response. MAPK kinases (MAPKKs), which link MAPKs and MAPKK kinases (MAPKKKs), are integral in mediating various stress responses in plants. However, to date few data about the roles of poplar MAPKKs in stress signal transduction are available. In this study, we performed a systemic analysis of poplar MAPKK gene family expression profiles in response to several abiotic stresses and stress-associated hormones. Furthermore, Populus trichocarpa MAPKK4 (PtMKK4) was chosen for functional characterization. Transgenic analysis showed that overexpression of the PtMKK4 gene remarkably enhanced drought stress tolerance in the transgenic poplar plants. The PtMKK4-overexpressing plants also exhibited much lower levels of H2O2 and higher antioxidant enzyme activity after exposure to drought stress compared to the wide type lines. Besides, some drought marker genes including PtP5CS, PtSUS3, PtLTP3 and PtDREB8 exhibited higher expression levels in the transgenic lines than in the wide type under drought conditions. This study provided valuable information for understanding the putative functions of poplar MAPKKs involved in important signaling pathways under different stress conditions. Copyright © 2014 Elsevier B.V. All rights reserved.
Miura, Kenji; Yamano, Takashi; Yoshioka, Satoshi; Kohinata, Tsutomu; Inoue, Yoshihiro; Taniguchi, Fumiya; Asamizu, Erika; Nakamura, Yasukazu; Tabata, Satoshi; Yamato, Katsuyuki T.; Ohyama, Kanji; Fukuzawa, Hideya
2004-01-01
Photosynthetic acclimation to CO2-limiting stress is associated with control of genetic and physiological responses through a signal transduction pathway, followed by integrated monitoring of the environmental changes. Although several CO2-responsive genes have been previously isolated, genome-wide analysis has not been applied to the isolation of CO2-responsive genes that may function as part of a carbon-concentrating mechanism (CCM) in photosynthetic eukaryotes. By comparing expression profiles of cells grown under CO2-rich conditions with those of cells grown under CO2-limiting conditions using a cDNA membrane array containing 10,368 expressed sequence tags, 51 low-CO2 inducible genes and 32 genes repressed by low CO2 whose mRNA levels were changed more than 2.5-fold in Chlamydomonas reinhardtii Dangeard were detected. The fact that the induction of almost all low-CO2 inducible genes was impaired in the ccm1 mutant suggests that CCM1 is a master regulator of CCM through putative low-CO2 signal transduction pathways. Among low-CO2 inducible genes, two novel genes, LciA and LciB, were identified, which may be involved in inorganic carbon transport. Possible functions of low-CO2 inducible and/or CCM1-regulated genes are discussed in relation to the CCM. PMID:15235119
Dysregulation of miRNAs in bladder cancer: altered expression with aberrant biogenesis procedure
Dong, Fan; Xu, Tianyuan; Shen, Yifan; Zhong, Shan; Chen, Shanwen; Ding, Qiang; Shen, Zhoujun
2017-01-01
Aberrant expression profiles of miRNAs are widely observed in the clinical tissue specimens and urine samples as well as the blood samples of bladder cancer patients. These profiles are closely related to the pathological features of bladder cancer, such as the tumour stage/grade, metastasis, recurrence and chemo-sensitivity. MiRNA biogenesis forms the basis of miRNA expression and function, and its dysregulation has been shown to be essential for variations in miRNA expression profiles as well as tumourigenesis and cancer progression. In this review, we summarize the up-to-date and widely reported miRNAs in bladder cancer that display significantly altered expression. We then compare the miRNA expression profiles among three different sample types (tissue, urine and blood) from patients with bladder cancer. Moreover, for the first time, we outline the dysregulated miRNA biogenesis network in bladder cancer from different levels and analyse its possible relationship with aberrant miRNA expression and the pathological characteristics of the disease. PMID:28187437
Riis, Margit L H; Lüders, Torben; Markert, Elke K; Haakensen, Vilde D; Nesbakken, Anne-Jorun; Kristensen, Vessela N; Bukholm, Ida R K
2012-01-01
Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology.
Riis, Margit L. H.; Lüders, Torben; Markert, Elke K.; Haakensen, Vilde D.; Nesbakken, Anne-Jorun; Kristensen, Vessela N.; Bukholm, Ida R. K.
2012-01-01
Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology. PMID:23227362
Delporte, Fabienne; Muhovski, Yordan; Pretova, Anna; Watillon, Bernard
2013-10-01
The physiological, biochemical and molecular mechanisms regulating the initiation of a regenerative pathway remain partially unknown. Efforts to identify the biological features that confer transformation ability, or the tendency of some cells to induce transgene silencing, would help to improve plant genetic engineering. The objective of our study was to monitor the evolution of plant cell competencies in relation to both in vitro tissue culture regeneration and the genetic transformation properties. We used a simple wheat regeneration procedure as an experimental model for studying the regenerative capacity of plant cells and their receptivity to direct gene transfer over the successive steps of the regenerative pathway. Target gene profiling studies and biochemical assays were conducted to follow some of the mechanisms triggered during the somatic-to-embryogenic transition (i.e. dedifferentiation, cell division activation, redifferentiation) and affecting the accessibility of plant cells to receive and stably express the exogenous DNA introduced by bombardment. Our results seem to indicate that the control of cell-cycle (S-phase) and host defense strategies can be crucial determinants of genetic transformation efficiency. The results from studies conducted at macro-, micro- and molecular scales are then integrated into a holistic approach that addresses the question of tissue culture and transgenesis competencies more broadly. Through this multilevel analysis we try to establish functional links between both regenerative capacity and transformation receptiveness, and thereby to provide a more global and integrated vision of both processes, at the core of defense/adaptive mechanisms and survival, between undifferentiated cell proliferation and organization.
Ali-Khan, Sarah E; Black, Lee; Palmour, Nicole; Hallett, Michael T; Avard, Denise
2015-01-01
There have been multiple calls for explicit integration of ethical, legal, and social issues (ELSI) in health technology assessment (HTA) and addressing ELSI has been highlighted as key in optimizing benefits in the Omics/Personalized Medicine field. This study examines HTAs of an early clinical example of Personalized Medicine (gene expression profile tests [GEP] for breast cancer prognosis) aiming to: (i) identify ELSI; (ii) assess whether ELSIs are implicitly or explicitly addressed; and (iii) report methodology used for ELSI integration. A systematic search for HTAs (January 2004 to September 2012), followed by descriptive and qualitative content analysis. Seventeen HTAs for GEP were retrieved. Only three (18%) explicitly presented ELSI, and only one reported methodology. However, all of the HTAs included implicit ELSI. Eight themes of implicit and explicit ELSI were identified. "Classical" ELSI including privacy, informed consent, and concerns about limited patient/clinician genetic literacy were always presented explicitly. Some ELSI, including the need to understand how individual patients' risk tolerances affect clinical decision-making after reception of GEP results, were presented both explicitly and implicitly in HTAs. Others, such as concern about evidentiary deficiencies for clinical utility of GEP tests, occurred only implicitly. Despite a wide variety of important ELSI raised, these were rarely explicitly addressed in HTAs. Explicit treatment would increase their accessibility to decision-makers, and may augment HTA efficiency maximizing their utility. This is particularly important where complex Personalized Medicine applications are rapidly expanding choices for patients, clinicians and healthcare systems.
Integrated geophysical study of the Triassic salt bodies' geometry and evolution in central Tunisia
NASA Astrophysics Data System (ADS)
Azaiez, Hajer; Amri, Dorra Tanfous; Gabtni, Hakim; Bedir, Mourad; Soussi, Mohamed
2008-01-01
A comprehensive study, integrating gravity, magnetic and seismic reflection data, has been used to resolve the complex Triassic salt body geometry and evolution in central Tunisia. Regional seismic lines across the study area show a detachment level in the Upper Triassic evaporites, associated with chaotic seismic facies below the Souinia, Majoura, and Mezzouna structures. The Jurassic and Lower Cretaceous seismic horizons display pinching-outs and onlapping around these structures. A stack-velocity section confirms the existence of a high-velocity body beneath the Souinia Mountain. Regional gravity and magnetic profiles in this area were elaborated from ETAP (the Tunisian Firm of Petroleum Activities) measure stations. These profiles were plotted following the same layout from the west (Souinia) to the east (Mezzouna), across the Majoura and Kharrouba mountains. They highlight associated gravity and magnetic negative anomalies. These gravity and magnetic data coupled to the reflection seismic data demonstrate that, in the Souinia, Majoura, and El Hafey zones, the Triassic salt reaches a salt pillow and a salt-dome stage, without piercing the cover. These stages are expressed by moderately low gravity anomalies. On the other hand, in the Mezzouna area (part of the North-South Axis), the Triassic salt had pierced its cover during the Upper Cretaceous and the Tertiary, reaching a more advanced stage as a salt diapir and salt wall. These stages express important low gravity and magnetic anomalies. These results confirm the model of Tanfous et al. (2005) of halokinetic movements by fault intrusions inducing, from the west to the east, structures at different stages of salt pillow, salt dome, and salt diapir.
Expression profiles of antimicrobial peptides (AMPs) and their regulation by Relish
NASA Astrophysics Data System (ADS)
Wang, Dongdong; Li, Fuhua; Li, Shihao; Wen, Rong; Xiang, Jianhai
2012-07-01
Antimicrobial peptides (AMPs), as key immune effectors, play important roles in the innate immune system of invertebrates. Different types of AMPs, including Penaeidin, Crustin, ALF (antilipopolysaccharide factor) have been identified in different penaeid shrimp; however, systematic analyses on the function of different AMPs in shrimp responsive to different types of bacteria are very limited. In this study, we analyzed the expression profiles of AMPs in the Chinese shrimps, Fenneropenaeus chinensis, simultaneously by real-time RT-PCR (reverse transcription-polymerase chain reaction) when shrimp were challenged with Micrococcus lysodeikticus (Gram-positive, G+) or Vibrio anguillarium (Gram-negative, G-). Different AMPs showed different expression profiles when shrimp were injected with one type of bacterium, and one AMP also showed different expression profiles when shrimp were challenged with different bacteria. Furthermore, the expression of these AMPs showed temporal expression profiles, suggesting that different AMPs function coordinately in bacteria-infected shrimp. An RNA interference approach was used to study the function of the Relish transcription factor in regulating the transcription of different AMPs. The current study showed that Relish could regulate the transcription of different AMPs in shrimp. Differential expression profiles of AMPs in shrimp injected with different types of bacteria indicated that a complicated antimicrobial response network existed in shrimp. These data contribute to our understanding of immunity in shrimp and may provide a strategy for the control of disease in shrimp.
Baculovirus induced transcripts in hemocytes from Heliothis virescens
USDA-ARS?s Scientific Manuscript database
Using RNA-sequencing digital difference expression profiling methods we have assessed the gene expression profiles of hemocytes harvested from Heliothis virescens that were challenged with Helicoverpa zea single nucleopolyhedrovirus (HzSNPV). A reference transcriptome of hemocyte-expressed transcri...
Camphausen, Kevin; Purow, Benjamin; Sproull, Mary; Scott, Tamalee; Ozawa, Tomoko; Deen, Dennis F.; Tofilon, Philip J.
2005-01-01
Defining the molecules that regulate tumor cell survival is an essential prerequisite for the development of targeted approaches to cancer treatment. Whereas many studies aimed at identifying such targets use human tumor cells grown in vitro or as s.c. xenografts, it is unclear whether such experimental models replicate the phenotype of the in situ tumor cell. To begin addressing this issue, we have used microarray analysis to define the gene expression profile of two human glioma cell lines (U251 and U87) when grown in vitro and in vivo as s.c. or as intracerebral (i.c.) xenografts. For each cell line, the gene expression profile generated from tissue culture was significantly different from that generated from the s.c. tumor, which was significantly different from those grown i.c. The disparity between the i.c gene expression profiles and those generated from s.c. xenografts suggests that whereas an in vivo growth environment modulates gene expression, orthotopic growth conditions induce a different set of modifications. In this study the U251 and U87 gene expression profiles generated under the three growth conditions were also compared. As expected, the profiles of the two glioma cell lines were significantly different when grown as monolayer cultures. However, the glioma cell lines had similar gene expression profiles when grown i.c. These results suggest that tumor cell gene expression, and thus phenotype, as defined in vitro is affected not only by in vivo growth but also by orthotopic growth, which may have implications regarding the identification of relevant targets for cancer therapy. PMID:15928080
Hong, Hyerim; Jung, Jaejoon; Park, Woojun
2014-01-01
Acquisition of the extracellular tetracycline (TC) resistance plasmid pAST2 affected host gene expression and phenotype in the oil-degrading soil bacterium, Acinetobacter oleivorans DR1. Whole-transcriptome profiling of DR1 cells harboring pAST2 revealed that all the plasmid genes were highly expressed under TC conditions, and the expression levels of many host chromosomal genes were modulated by the presence of pAST2. The host energy burden imposed by replication of pAST2 led to (i) lowered ATP concentrations, (ii) downregulated expression of many genes involved in cellular growth, and (iii) reduced growth rate. Interestingly, some phenotypes were restored by deleting the plasmid-encoded efflux pump gene tetH, suggesting that the membrane integrity changes resulting from the incorporation of efflux pump proteins also resulted in altered host response under the tested conditions. Alteration of membrane integrity by tetH deletion was shown by measuring permeability of fluorescent probe and membrane hydrophobicity. The presence of the plasmid conferred peroxide and superoxide resistance to cells, but only peroxide resistance was diminished by tetH gene deletion, suggesting that the plasmid-encoded membrane-bound efflux pump protein provided peroxide resistance. The downregulation of fimbriae-related genes presumably led to reduced swimming motility, but this phenotype was recovered by tetH gene deletion. Our data suggest that not only the plasmid replication burden, but also its encoded efflux pump protein altered host chromosomal gene expression and phenotype, which also alters the ecological fitness of the host in the environment. PMID:25229538
Hong, Hyerim; Jung, Jaejoon; Park, Woojun
2014-01-01
Acquisition of the extracellular tetracycline (TC) resistance plasmid pAST2 affected host gene expression and phenotype in the oil-degrading soil bacterium, Acinetobacter oleivorans DR1. Whole-transcriptome profiling of DR1 cells harboring pAST2 revealed that all the plasmid genes were highly expressed under TC conditions, and the expression levels of many host chromosomal genes were modulated by the presence of pAST2. The host energy burden imposed by replication of pAST2 led to (i) lowered ATP concentrations, (ii) downregulated expression of many genes involved in cellular growth, and (iii) reduced growth rate. Interestingly, some phenotypes were restored by deleting the plasmid-encoded efflux pump gene tetH, suggesting that the membrane integrity changes resulting from the incorporation of efflux pump proteins also resulted in altered host response under the tested conditions. Alteration of membrane integrity by tetH deletion was shown by measuring permeability of fluorescent probe and membrane hydrophobicity. The presence of the plasmid conferred peroxide and superoxide resistance to cells, but only peroxide resistance was diminished by tetH gene deletion, suggesting that the plasmid-encoded membrane-bound efflux pump protein provided peroxide resistance. The downregulation of fimbriae-related genes presumably led to reduced swimming motility, but this phenotype was recovered by tetH gene deletion. Our data suggest that not only the plasmid replication burden, but also its encoded efflux pump protein altered host chromosomal gene expression and phenotype, which also alters the ecological fitness of the host in the environment.
Update of aircraft profile data for the Integrated Noise Model computer program, vol 1: final report
DOT National Transportation Integrated Search
1992-03-01
This report provides aircraft takeoff and landing profiles, aircraft aerodynamic performance coefficients and engine performance coefficients for the aircraft data base (Database 9) in the Integrated Noise Model (INM) computer program. Flight profile...
Hebecker, Betty; Vlaic, Sebastian; Conrad, Theresia; Bauer, Michael; Brunke, Sascha; Kapitan, Mario; Linde, Jörg; Hube, Bernhard; Jacobsen, Ilse D
2016-11-03
Candida albicans is a common cause of life-threatening fungal bloodstream infections. In the murine model of systemic candidiasis, the kidney is the primary target organ while the fungal load declines over time in liver and spleen. To better understand these organ-specific differences in host-pathogen interaction, we performed gene expression profiling of murine kidney, liver and spleen and determined the fungal transcriptome in liver and kidney. We observed a delayed transcriptional immune response accompanied by late induction of fungal stress response genes in the kidneys. In contrast, early upregulation of the proinflammatory response in the liver was associated with a fungal transcriptome resembling response to phagocytosis, suggesting that phagocytes contribute significantly to fungal control in the liver. Notably, C. albicans hypha-associated genes were upregulated in the absence of visible filamentation in the liver, indicating an uncoupling of gene expression and morphology and a morphology-independent effect by hypha-associated genes in this organ. Consistently, integration of host and pathogen transcriptional data in an inter-species gene regulatory network indicated connections of C. albicans cell wall remodelling and metabolism to the organ-specific immune responses.
Hebecker, Betty; Vlaic, Sebastian; Conrad, Theresia; Bauer, Michael; Brunke, Sascha; Kapitan, Mario; Linde, Jörg; Hube, Bernhard; Jacobsen, Ilse D.
2016-01-01
Candida albicans is a common cause of life-threatening fungal bloodstream infections. In the murine model of systemic candidiasis, the kidney is the primary target organ while the fungal load declines over time in liver and spleen. To better understand these organ-specific differences in host-pathogen interaction, we performed gene expression profiling of murine kidney, liver and spleen and determined the fungal transcriptome in liver and kidney. We observed a delayed transcriptional immune response accompanied by late induction of fungal stress response genes in the kidneys. In contrast, early upregulation of the proinflammatory response in the liver was associated with a fungal transcriptome resembling response to phagocytosis, suggesting that phagocytes contribute significantly to fungal control in the liver. Notably, C. albicans hypha-associated genes were upregulated in the absence of visible filamentation in the liver, indicating an uncoupling of gene expression and morphology and a morphology-independent effect by hypha-associated genes in this organ. Consistently, integration of host and pathogen transcriptional data in an inter-species gene regulatory network indicated connections of C. albicans cell wall remodelling and metabolism to the organ-specific immune responses. PMID:27808111
Data-Driven Discovery of Extravasation Pathway in Circulating Tumor Cells
Yadavalli, S.; Jayaram, S.; Manda, S. S.; Madugundu, A. K.; Nayakanti, D. S.; Tan, T. Z.; Bhat, R.; Rangarajan, A.; Chatterjee, A.; Gowda, H.; Thiery, J. P.; Kumar, P.
2017-01-01
Circulating tumor cells (CTCs) play a crucial role in cancer dissemination and provide a promising source of blood-based markers. Understanding the spectrum of transcriptional profiles of CTCs and their corresponding regulatory mechanisms will allow for a more robust analysis of CTC phenotypes. The current challenge in CTC research is the acquisition of useful clinical information from the multitude of high-throughput studies. To gain a deeper understanding of CTC heterogeneity and identify genes, pathways and processes that are consistently affected across tumors, we mined the literature for gene expression profiles in CTCs. Through in silico analysis and the integration of CTC-specific genes, we found highly significant biological mechanisms and regulatory processes acting in CTCs across various cancers, with a particular enrichment of the leukocyte extravasation pathway. This pathway appears to play a pivotal role in the migration of CTCs to distant metastatic sites. We find that CTCs from multiple cancers express both epithelial and mesenchymal markers in varying amounts, which is suggestive of dynamic and hybrid states along the epithelial-mesenchymal transition (EMT) spectrum. Targeting the specific molecular nodes to monitor disease and therapeutic control of CTCs in real time will likely improve the clinical management of cancer progression and metastases. PMID:28262832
Epigenomics and bolting tolerance in sugar beet genotypes.
Hébrard, Claire; Peterson, Daniel G; Willems, Glenda; Delaunay, Alain; Jesson, Béline; Lefèbvre, Marc; Barnes, Steve; Maury, Stéphane
2016-01-01
In sugar beet (Beta vulgaris altissima), bolting tolerance is an essential agronomic trait reflecting the bolting response of genotypes after vernalization. Genes involved in induction of sugar beet bolting have now been identified, and evidence suggests that epigenetic factors are involved in their control. Indeed, the time course and amplitude of DNA methylation variations in the shoot apical meristem have been shown to be critical in inducing sugar beet bolting, and a few functional targets of DNA methylation during vernalization have been identified. However, molecular mechanisms controlling bolting tolerance levels among genotypes are still poorly understood. Here, gene expression and DNA methylation profiles were compared in shoot apical meristems of three bolting-resistant and three bolting-sensitive genotypes after vernalization. Using Cot fractionation followed by 454 sequencing of the isolated low-copy DNA, 6231 contigs were obtained that were used along with public sugar beet DNA sequences to design custom Agilent microarrays for expression (56k) and methylation (244k) analyses. A total of 169 differentially expressed genes and 111 differentially methylated regions were identified between resistant and sensitive vernalized genotypes. Fourteen sequences were both differentially expressed and differentially methylated, with a negative correlation between their methylation and expression levels. Genes involved in cold perception, phytohormone signalling, and flowering induction were over-represented and collectively represent an integrative gene network from environmental perception to bolting induction. Altogether, the data suggest that the genotype-dependent control of DNA methylation and expression of an integrative gene network participate in bolting tolerance in sugar beet, opening up perspectives for crop improvement. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.
Evolution of Daily Gene Co-expression Patterns from Algae to Plants
de los Reyes, Pedro; Romero-Campero, Francisco J.; Ruiz, M. Teresa; Romero, José M.; Valverde, Federico
2017-01-01
Daily rhythms play a key role in transcriptome regulation in plants and microalgae orchestrating responses that, among other processes, anticipate light transitions that are essential for their metabolism and development. The recent accumulation of genome-wide transcriptomic data generated under alternating light:dark periods from plants and microalgae has made possible integrative and comparative analysis that could contribute to shed light on the evolution of daily rhythms in the green lineage. In this work, RNA-seq and microarray data generated over 24 h periods in different light regimes from the eudicot Arabidopsis thaliana and the microalgae Chlamydomonas reinhardtii and Ostreococcus tauri have been integrated and analyzed using gene co-expression networks. This analysis revealed a reduction in the size of the daily rhythmic transcriptome from around 90% in Ostreococcus, being heavily influenced by light transitions, to around 40% in Arabidopsis, where a certain independence from light transitions can be observed. A novel Multiple Bidirectional Best Hit (MBBH) algorithm was applied to associate single genes with a family of potential orthologues from evolutionary distant species. Gene duplication, amplification and divergence of rhythmic expression profiles seems to have played a central role in the evolution of gene families in the green lineage such as Pseudo Response Regulators (PRRs), CONSTANS-Likes (COLs), and DNA-binding with One Finger (DOFs). Gene clustering and functional enrichment have been used to identify groups of genes with similar rhythmic gene expression patterns. The comparison of gene clusters between species based on potential orthologous relationships has unveiled a low to moderate level of conservation of daily rhythmic expression patterns. However, a strikingly high conservation was found for the gene clusters exhibiting their highest and/or lowest expression value during the light transitions. PMID:28751903
A gene expression resource generated by genome-wide lacZ profiling in the mouse
Tuck, Elizabeth; Estabel, Jeanne; Oellrich, Anika; Maguire, Anna Karin; Adissu, Hibret A.; Souter, Luke; Siragher, Emma; Lillistone, Charlotte; Green, Angela L.; Wardle-Jones, Hannah; Carragher, Damian M.; Karp, Natasha A.; Smedley, Damian; Adams, Niels C.; Bussell, James N.; Adams, David J.; Ramírez-Solis, Ramiro; Steel, Karen P.; Galli, Antonella; White, Jacqueline K.
2015-01-01
ABSTRACT Knowledge of the expression profile of a gene is a critical piece of information required to build an understanding of the normal and essential functions of that gene and any role it may play in the development or progression of disease. High-throughput, large-scale efforts are on-going internationally to characterise reporter-tagged knockout mouse lines. As part of that effort, we report an open access adult mouse expression resource, in which the expression profile of 424 genes has been assessed in up to 47 different organs, tissues and sub-structures using a lacZ reporter gene. Many specific and informative expression patterns were noted. Expression was most commonly observed in the testis and brain and was most restricted in white adipose tissue and mammary gland. Over half of the assessed genes presented with an absent or localised expression pattern (categorised as 0-10 positive structures). A link between complexity of expression profile and viability of homozygous null animals was observed; inactivation of genes expressed in ≥21 structures was more likely to result in reduced viability by postnatal day 14 compared with more restricted expression profiles. For validation purposes, this mouse expression resource was compared with Bgee, a federated composite of RNA-based expression data sets. Strong agreement was observed, indicating a high degree of specificity in our data. Furthermore, there were 1207 observations of expression of a particular gene in an anatomical structure where Bgee had no data, indicating a large amount of novelty in our data set. Examples of expression data corroborating and extending genotype-phenotype associations and supporting disease gene candidacy are presented to demonstrate the potential of this powerful resource. PMID:26398943
Analysis of gene expression profile microarray data in complex regional pain syndrome.
Tan, Wulin; Song, Yiyan; Mo, Chengqiang; Jiang, Shuangjian; Wang, Zhongxing
2017-09-01
The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein‑protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB‑binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.
Ning, Tongbo; Cui, Hao; Sun, Feng; Zou, Jidian
2017-09-05
Glioblastoma represents one of the most aggressive malignant brain tumors with high morbidity and motility. Demethylation drugs have been developed for its treatment with little efficacy has been observed. The purpose of this study was to screen therapeutic targets of demethylation drugs or bioactive molecules for glioblastoma through systemic bioinformatics analysis. We firstly downloaded genome-wide expression profiles from the Gene Expression Omnibus (GEO) and conducted the primary analysis through R software, mainly including preprocessing of raw microarray data, transformation between probe ID and gene symbol and identification of differential expression genes (DEGs). Secondly, functional enrichment analysis was conducted via the Database for Annotation, Visualization and Integrated Discovery (DAVID) to explore biological processes involved in the development of glioblastoma. Thirdly, we constructed protein-protein interaction (PPI) network of interested genes and conducted cross analysis for multi datasets to obtain potential therapeutic targets for glioblastoma. Finally, we further confirmed the therapeutic targets through real-time RT-PCR. As a result, biological processes that related to cancer development, amino metabolism, immune response and etc. were found to be significantly enriched in genes that differential expression in glioblastoma and regulated by 5'aza-dC. Besides, network and cross analysis identified ACAT2, UFC1 and CYB5R1 as novel therapeutic targets of demethylation drugs which also confirmed by real time RT-PCR. In conclusions, our study identified several biological processes and genes that involved in the development of glioblastoma and regulated by 5'aza-dC, which would be helpful for the treatment of glioblastoma. Copyright © 2017 Elsevier B.V. All rights reserved.
Sgadò, Paola; Provenzano, Giovanni; Dassi, Erik; Adami, Valentina; Zunino, Giulia; Genovesi, Sacha; Casarosa, Simona; Bozzi, Yuri
2013-12-19
Transcriptome analysis has been used in autism spectrum disorder (ASD) to unravel common pathogenic pathways based on the assumption that distinct rare genetic variants or epigenetic modifications affect common biological pathways. To unravel recurrent ASD-related neuropathological mechanisms, we took advantage of the En2-/- mouse model and performed transcriptome profiling on cerebellar and hippocampal adult tissues. Cerebellar and hippocampal tissue samples from three En2-/- and wild type (WT) littermate mice were assessed for differential gene expression using microarray hybridization followed by RankProd analysis. To identify functional categories overrepresented in the differentially expressed genes, we used integrated gene-network analysis, gene ontology enrichment and mouse phenotype ontology analysis. Furthermore, we performed direct enrichment analysis of ASD-associated genes from the SFARI repository in our differentially expressed genes. Given the limited number of animals used in the study, we used permissive criteria and identified 842 differentially expressed genes in En2-/- cerebellum and 862 in the En2-/- hippocampus. Our functional analysis revealed that the molecular signature of En2-/- cerebellum and hippocampus shares convergent pathological pathways with ASD, including abnormal synaptic transmission, altered developmental processes and increased immune response. Furthermore, when directly compared to the repository of the SFARI database, our differentially expressed genes in the hippocampus showed enrichment of ASD-associated genes significantly higher than previously reported. qPCR was performed for representative genes to confirm relative transcript levels compared to those detected in microarrays. Despite the limited number of animals used in the study, our bioinformatic analysis indicates the En2-/- mouse is a valuable tool for investigating molecular alterations related to ASD.
Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher
2016-01-01
Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669
Tang, Pei-An; Wu, Hai-Jing; Xue, Hao; Ju, Xing-Rong; Song, Wei; Zhang, Qi-Lin; Yuan, Ming-Long
2017-07-30
The Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) is a worldwide pest that causes serious damage to stored foods. Although many efforts have been conducted on this species due to its economic importance, the study of genetic basis of development, behavior and insecticide resistance has been greatly hampered due to lack of genomic information. In this study, we used high throughput sequencing platform to perform a de novo transcriptome assembly and tag-based digital gene expression profiling (DGE) analyses across four different developmental stages of P. interpunctella (egg, third-instar larvae, pupae and adult). We obtained approximate 9gigabyte (GB) of clean data and recovered 84,938 unigenes, including 37,602 clusters and 47,336 singletons. These unigenes were annotated using BLAST against the non-redundant protein databases and then functionally classified based on Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes databases (KEGG). A large number of differentially expressed genes were identified by pairwise comparisons among different developmental stages. Gene expression profiles dramatically changed between developmental stage transitions. Some of these differentially expressed genes were related to digestion and cuticularization. Quantitative real-time PCR results of six randomly selected genes conformed the findings in the DGEs. Furthermore, we identified over 8000 microsatellite markers and 97,648 single nucleotide polymorphisms which will be useful for population genetics studies of P. interpunctella. This transcriptomic information provided insight into the developmental basis of P. interpunctella and will be helpful for establishing integrated management strategies and developing new targets of insecticides for this serious pest. Copyright © 2017 Elsevier B.V. All rights reserved.
Jiang, Shu-Ye; Ma, Ali; Ramamoorthy, Rengasamy; Ramachandran, Srinivasan
2013-01-01
Expression profiling is one of the most important tools for dissecting biological functions of genes and the upregulation or downregulation of gene expression is sufficient for recreating phenotypic differences. Expression divergence of genes significantly contributes to phenotypic variations. However, little is known on the molecular basis of expression divergence and evolution among rice genotypes with contrasting phenotypes. In this study, we have implemented an integrative approach using bioinformatics and experimental analyses to provide insights into genomic variation, expression divergence, and evolution between salinity-sensitive rice variety Nipponbare and tolerant rice line Pokkali under normal and high salinity stress conditions. We have detected thousands of differentially expressed genes between these two genotypes and thousands of up- or downregulated genes under high salinity stress. Many genes were first detected with expression evidence using custom microarray analysis. Some gene families were preferentially regulated by high salinity stress and might play key roles in stress-responsive biological processes. Genomic variations in promoter regions resulted from single nucleotide polymorphisms, indels (1–10 bp of insertion/deletion), and structural variations significantly contributed to the expression divergence and regulation. Our data also showed that tandem and segmental duplication, CACTA and hAT elements played roles in the evolution of gene expression divergence and regulation between these two contrasting genotypes under normal or high salinity stress conditions. PMID:24121498
Gene Expression Profiling Predicts the Development of Oral Cancer
Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li
2011-01-01
Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635
Chromatin Landscapes of Retroviral and Transposon Integration Profiles
Badhai, Jitendra; Rust, Alistair G.; Rad, Roland; Hilkens, John; Berns, Anton; van Lohuizen, Maarten; Wessels, Lodewyk F. A.; de Ridder, Jeroen
2014-01-01
The ability of retroviruses and transposons to insert their genetic material into host DNA makes them widely used tools in molecular biology, cancer research and gene therapy. However, these systems have biases that may strongly affect research outcomes. To address this issue, we generated very large datasets consisting of to unselected integrations in the mouse genome for the Sleeping Beauty (SB) and piggyBac (PB) transposons, and the Mouse Mammary Tumor Virus (MMTV). We analyzed (epi)genomic features to generate bias maps at both local and genome-wide scales. MMTV showed a remarkably uniform distribution of integrations across the genome. More distinct preferences were observed for the two transposons, with PB showing remarkable resemblance to bias profiles of the Murine Leukemia Virus. Furthermore, we present a model where target site selection is directed at multiple scales. At a large scale, target site selection is similar across systems, and defined by domain-oriented features, namely expression of proximal genes, proximity to CpG islands and to genic features, chromatin compaction and replication timing. Notable differences between the systems are mainly observed at smaller scales, and are directed by a diverse range of features. To study the effect of these biases on integration sites occupied under selective pressure, we turned to insertional mutagenesis (IM) screens. In IM screens, putative cancer genes are identified by finding frequently targeted genomic regions, or Common Integration Sites (CISs). Within three recently completed IM screens, we identified 7%–33% putative false positive CISs, which are likely not the result of the oncogenic selection process. Moreover, results indicate that PB, compared to SB, is more suited to tag oncogenes. PMID:24721906
Godard-Codding, Céline A J; Clark, Rebecca; Fossi, Maria Cristina; Marsili, Letizia; Maltese, Silvia; West, Adam G; Valenzuela, Luciano; Rowntree, Victoria; Polyak, Ildiko; Cannon, John C; Pinkerton, Kim; Rubio-Cisneros, Nadia; Mesnick, Sarah L; Cox, Stephen B; Kerr, Iain; Payne, Roger; Stegeman, John J
2011-03-01
Ocean pollution affects marine organisms and ecosystems as well as humans. The International Oceanographic Commission recommends ocean health monitoring programs to investigate the presence of marine contaminants and the health of threatened species and the use of multiple and early-warning biomarker approaches. We explored the hypothesis that biomarker and contaminant analyses in skin biopsies of the threatened sperm whale (Physeter macrocephalus) could reveal geographical trends in exposure on an oceanwide scale. We analyzed cytochrome P450 1A1 (CYP1A1) expression (by immunohistochemistry), stable nitrogen and carbon isotope ratios (as general indicators of trophic position and latitude, respectively), and contaminant burdens in skin biopsies to explore regional trends in the Pacific Ocean. Biomarker analyses revealed significant regional differences within the Pacific Ocean. CYP1A1 expression was highest in whales from the Galapagos, a United Nations Educational, Scientific, and Cultural Organization World Heritage marine reserve, and was lowest in the sampling sites farthest away from continents. We examined the possible influence of the whales' sex, diet, or range and other parameters on regional variation in CYP1A1 expression, but data were inconclusive. In general, CYP1A1 expression was not significantly correlated with contaminant burdens in blubber. However, small sample sizes precluded detailed chemical analyses, and power to detect significant associations was limited. Our large-scale monitoring study was successful at identifying regional differences in CYP1A1 expression, providing a baseline for this known biomarker of exposure to aryl hydrocarbon receptor agonists. However, we could not identify factors that explained this variation. Future oceanwide CYP1A1 expression profiles in cetacean skin biopsies are warranted and could reveal whether globally distributed chemicals occur at biochemically relevant concentrations on a global basis, which may provide a measure of ocean integrity.
A cross-species analysis method to analyze animal models' similarity to human's disease state
2012-01-01
Background Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism. Results We developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery. We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning. Conclusions We developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for drug research, such as potential drug candidates, possible drug repositioning, side effects and information about pharmacology. PMID:23282076
Godard-Codding, Céline A.J.; Clark, Rebecca; Fossi, Maria Cristina; Marsili, Letizia; Maltese, Silvia; West, Adam G.; Valenzuela, Luciano; Rowntree, Victoria; Polyak, Ildiko; Cannon, John C.; Pinkerton, Kim; Rubio-Cisneros, Nadia; Mesnick, Sarah L.; Cox, Stephen B.; Kerr, Iain; Payne, Roger; Stegeman, John J.
2011-01-01
Background Ocean pollution affects marine organisms and ecosystems as well as humans. The International Oceanographic Commission recommends ocean health monitoring programs to investigate the presence of marine contaminants and the health of threatened species and the use of multiple and early-warning biomarker approaches. Objective We explored the hypothesis that biomarker and contaminant analyses in skin biopsies of the threatened sperm whale (Physeter macrocephalus) could reveal geographical trends in exposure on an oceanwide scale. Methods We analyzed cytochrome P450 1A1 (CYP1A1) expression (by immunohistochemistry), stable nitrogen and carbon isotope ratios (as general indicators of trophic position and latitude, respectively), and contaminant burdens in skin biopsies to explore regional trends in the Pacific Ocean. Results Biomarker analyses revealed significant regional differences within the Pacific Ocean. CYP1A1 expression was highest in whales from the Galapagos, a United Nations Educational, Scientific, and Cultural Organization World Heritage marine reserve, and was lowest in the sampling sites farthest away from continents. We examined the possible influence of the whales’ sex, diet, or range and other parameters on regional variation in CYP1A1 expression, but data were inconclusive. In general, CYP1A1 expression was not significantly correlated with contaminant burdens in blubber. However, small sample sizes precluded detailed chemical analyses, and power to detect significant associations was limited. Conclusions Our large-scale monitoring study was successful at identifying regional differences in CYP1A1 expression, providing a baseline for this known biomarker of exposure to aryl hydrocarbon receptor agonists. However, we could not identify factors that explained this variation. Future oceanwide CYP1A1 expression profiles in cetacean skin biopsies are warranted and could reveal whether globally distributed chemicals occur at biochemically relevant concentrations on a global basis, which may provide a measure of ocean integrity. PMID:21134820