Gene Expression Profile Change and Associated Physiological and Pathological Effects in Mouse Liver Induced by Fasting and Refeeding

PubMed Central

Zhang, Fang; Xu, Xiang; Zhou, Ben; He, Zhishui; Zhai, Qiwei

2011-01-01

Food availability regulates basal metabolism and progression of many diseases, and liver plays an important role in these processes. The effects of food availability on digital gene expression profile, physiological and pathological functions in liver are yet to be further elucidated. In this study, we applied high-throughput sequencing technology to detect digital gene expression profile of mouse liver in fed, fasted and refed states. Totally 12162 genes were detected, and 2305 genes were significantly regulated by food availability. Biological process and pathway analysis showed that fasting mainly affected lipid and carboxylic acid metabolic processes in liver. Moreover, the genes regulated by fasting and refeeding in liver were mainly enriched in lipid metabolic process or fatty acid metabolism. Network analysis demonstrated that fasting mainly regulated Drug Metabolism, Small Molecule Biochemistry and Endocrine System Development and Function, and the networks including Lipid Metabolism, Small Molecule Biochemistry and Gene Expression were affected by refeeding. In addition, FunDo analysis showed that liver cancer and diabetes mellitus were most likely to be affected by food availability. This study provides the digital gene expression profile of mouse liver regulated by food availability, and demonstrates the main biological processes, pathways, gene networks and potential hepatic diseases regulated by fasting and refeeding. These results show that food availability mainly regulates hepatic lipid metabolism and is highly correlated with liver-related diseases including liver cancer and diabetes. PMID:22096593

Gene expression profile change and associated physiological and pathological effects in mouse liver induced by fasting and refeeding.

PubMed

Zhang, Fang; Xu, Xiang; Zhou, Ben; He, Zhishui; Zhai, Qiwei

2011-01-01

Food availability regulates basal metabolism and progression of many diseases, and liver plays an important role in these processes. The effects of food availability on digital gene expression profile, physiological and pathological functions in liver are yet to be further elucidated. In this study, we applied high-throughput sequencing technology to detect digital gene expression profile of mouse liver in fed, fasted and refed states. Totally 12162 genes were detected, and 2305 genes were significantly regulated by food availability. Biological process and pathway analysis showed that fasting mainly affected lipid and carboxylic acid metabolic processes in liver. Moreover, the genes regulated by fasting and refeeding in liver were mainly enriched in lipid metabolic process or fatty acid metabolism. Network analysis demonstrated that fasting mainly regulated Drug Metabolism, Small Molecule Biochemistry and Endocrine System Development and Function, and the networks including Lipid Metabolism, Small Molecule Biochemistry and Gene Expression were affected by refeeding. In addition, FunDo analysis showed that liver cancer and diabetes mellitus were most likely to be affected by food availability. This study provides the digital gene expression profile of mouse liver regulated by food availability, and demonstrates the main biological processes, pathways, gene networks and potential hepatic diseases regulated by fasting and refeeding. These results show that food availability mainly regulates hepatic lipid metabolism and is highly correlated with liver-related diseases including liver cancer and diabetes.

Gene expression profile in cerebrum in the filial imprinting of domestic chicks (Gallus gallus domesticus).

PubMed

Yamaguchi, Shinji; Fujii-Taira, Ikuko; Katagiri, Sachiko; Izawa, Ei-Ichi; Fujimoto, Yasuyuki; Takeuchi, Hideaki; Takano, Tatsuya; Matsushima, Toshiya; Homma, Koichi J

2008-06-15

In newly hatched chicks, gene expression in the brain has previously been shown to be up-regulated following filial imprinting. By applying cDNA microarrays containing 13,007 expressed sequence tags, we examined the comprehensive gene expression profiling of the intermediate medial mesopallium in the chick cerebrum, which has been shown to play a key role in filial imprinting. We found 52 up-regulated genes and 6 down-regulated genes of at least 2.0-fold changes 3h after the training of filial imprinting, compared to the gene expression of the dark-reared chick brain. The up-regulated genes are known to be involved in a variety of pathways, including signal transduction, cytoskeletal organization, nuclear function, cell metabolism, RNA binding, endoplasmic reticulum or Golgi function, synaptic function, ion channel, and transporter. In contrast, fewer genes were down-regulated in the imprinting, coinciding with the previous data that the total RNA synthesis increased associated with filial imprinting. Our data suggests that the filial imprinting involves the modulation of multiple signaling pathways.

Genome-Wide Expression Profiling of Five Mouse Models Identifies Similarities and Differences with Human Psoriasis

PubMed Central

Swindell, William R.; Johnston, Andrew; Carbajal, Steve; Han, Gangwen; Wohn, Christian; Lu, Jun; Xing, Xianying; Nair, Rajan P.; Voorhees, John J.; Elder, James T.; Wang, Xiao-Jing; Sano, Shigetoshi; Prens, Errol P.; DiGiovanni, John; Pittelkow, Mark R.; Ward, Nicole L.; Gudjonsson, Johann E.

2011-01-01

Development of a suitable mouse model would facilitate the investigation of pathomechanisms underlying human psoriasis and would also assist in development of therapeutic treatments. However, while many psoriasis mouse models have been proposed, no single model recapitulates all features of the human disease, and standardized validation criteria for psoriasis mouse models have not been widely applied. In this study, whole-genome transcriptional profiling is used to compare gene expression patterns manifested by human psoriatic skin lesions with those that occur in five psoriasis mouse models (K5-Tie2, imiquimod, K14-AREG, K5-Stat3C and K5-TGFbeta1). While the cutaneous gene expression profiles associated with each mouse phenotype exhibited statistically significant similarity to the expression profile of psoriasis in humans, each model displayed distinctive sets of similarities and differences in comparison to human psoriasis. For all five models, correspondence to the human disease was strong with respect to genes involved in epidermal development and keratinization. Immune and inflammation-associated gene expression, in contrast, was more variable between models as compared to the human disease. These findings support the value of all five models as research tools, each with identifiable areas of convergence to and divergence from the human disease. Additionally, the approach used in this paper provides an objective and quantitative method for evaluation of proposed mouse models of psoriasis, which can be strategically applied in future studies to score strengths of mouse phenotypes relative to specific aspects of human psoriasis. PMID:21483750

Refinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancy.

PubMed

Jung, Ki-Hong; Dardick, Christopher; Bartley, Laura E; Cao, Peijian; Phetsom, Jirapa; Canlas, Patrick; Seo, Young-Su; Shultz, Michael; Ouyang, Shu; Yuan, Qiaoping; Frank, Bryan C; Ly, Eugene; Zheng, Li; Jia, Yi; Hsia, An-Ping; An, Kyungsook; Chou, Hui-Hsien; Rocke, David; Lee, Geun Cheol; Schnable, Patrick S; An, Gynheung; Buell, C Robin; Ronald, Pamela C

2008-10-06

Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics.

Early gene expression during natural spinal cord regeneration in the salamander Ambystoma mexicanum.

PubMed

Monaghan, James R; Walker, John A; Page, Robert B; Putta, Srikrishna; Beachy, Christopher K; Voss, S Randal

2007-04-01

In contrast to mammals, salamanders have a remarkable ability to regenerate their spinal cord and recover full movement and function after tail amputation. To identify genes that may be associated with this greater regenerative ability, we designed an oligonucleotide microarray and profiled early gene expression during natural spinal cord regeneration in Ambystoma mexicanum. We sampled tissue at five early time points after tail amputation and identified genes that registered significant changes in mRNA abundance during the first 7 days of regeneration. A list of 1036 statistically significant genes was identified. Additional statistical and fold change criteria were applied to identify a smaller list of 360 genes that were used to describe predominant expression patterns and gene functions. Our results show that a diverse injury response is activated in concert with extracellular matrix remodeling mechanisms during the early acute phase of natural spinal cord regeneration. We also report gene expression similarities and differences between our study and studies that have profiled gene expression after spinal cord injury in rat. Our study illustrates the utility of a salamander model for identifying genes and gene functions that may enhance regenerative ability in mammals.

Gene Discovery in Bladder Cancer Progression using cDNA Microarrays

PubMed Central

Sanchez-Carbayo, Marta; Socci, Nicholas D.; Lozano, Juan Jose; Li, Wentian; Charytonowicz, Elizabeth; Belbin, Thomas J.; Prystowsky, Michael B.; Ortiz, Angel R.; Childs, Geoffrey; Cordon-Cardo, Carlos

2003-01-01

To identify gene expression changes along progression of bladder cancer, we compared the expression profiles of early-stage and advanced bladder tumors using cDNA microarrays containing 17,842 known genes and expressed sequence tags. The application of bootstrapping techniques to hierarchical clustering segregated early-stage and invasive transitional carcinomas into two main clusters. Multidimensional analysis confirmed these clusters and more importantly, it separated carcinoma in situ from papillary superficial lesions and subgroups within early-stage and invasive tumors displaying different overall survival. Additionally, it recognized early-stage tumors showing gene profiles similar to invasive disease. Different techniques including standard t-test, single-gene logistic regression, and support vector machine algorithms were applied to identify relevant genes involved in bladder cancer progression. Cytokeratin 20, neuropilin-2, p21, and p33ING1 were selected among the top ranked molecular targets differentially expressed and validated by immunohistochemistry using tissue microarrays (n = 173). Their expression patterns were significantly associated with pathological stage, tumor grade, and altered retinoblastoma (RB) expression. Moreover, p33ING1 expression levels were significantly associated with overall survival. Analysis of the annotation of the most significant genes revealed the relevance of critical genes and pathways during bladder cancer progression, including the overexpression of oncogenic genes such as DEK in superficial tumors or immune response genes such as Cd86 antigen in invasive disease. Gene profiling successfully classified bladder tumors based on their progression and clinical outcome. The present study has identified molecular biomarkers of potential clinical significance and critical molecular targets associated with bladder cancer progression. PMID:12875971

Comprehensive evaluation of gene expression signatures in response to electroacupuncture stimulation at Zusanli (ST36) acupoint by transcriptomic analysis.

PubMed

Wu, Jing-Shan; Lo, Hsin-Yi; Li, Chia-Cheng; Chen, Feng-Yuan; Hsiang, Chien-Yun; Ho, Tin-Yun

2017-08-15

Electroacupuncture (EA) has been applied to treat and prevent diseases for years. However, molecular events happened in both the acupunctured site and the internal organs after EA stimulation have not been clarified. Here we applied transcriptomic analysis to explore the gene expression signatures after EA stimulation. Mice were applied EA stimulation at ST36 for 15 min and nine tissues were collected three hours later for microarray analysis. We found that EA affected the expression of genes not only in the acupunctured site but also in the internal organs. EA commonly affected biological networks involved in cytoskeleton and cell adhesion, and also regulated unique process networks in specific organs, such as γ-aminobutyric acid-ergic neurotransmission in brain and inflammation process in lung. In addition, EA affected the expression of genes related to various diseases, such as neurodegenerative diseases in brain and obstructive pulmonary diseases in lung. This report applied, for the first time, a global comprehensive genome-wide approach to analyze the gene expression profiling of acupunctured site and internal organs after EA stimulation. The connection between gene expression signatures, biological processes, and diseases might provide a basis for prediction and explanation on the therapeutic potentials of acupuncture in organs.

Identification of differentially expressed genes in cucumber (Cucumis sativus L.) root under waterlogging stress by digital gene expression profile.

PubMed

Qi, Xiao-Hua; Xu, Xue-Wen; Lin, Xiao-Jian; Zhang, Wen-Jie; Chen, Xue-Hao

2012-03-01

High-throughput tag-sequencing (Tag-seq) analysis based on the Solexa Genome Analyzer platform was applied to analyze the gene expression profiling of cucumber plant at 5 time points over a 24h period of waterlogging treatment. Approximately 5.8 million total clean sequence tags per library were obtained with 143013 distinct clean tag sequences. Approximately 23.69%-29.61% of the distinct clean tags were mapped unambiguously to the unigene database, and 53.78%-60.66% of the distinct clean tags were mapped to the cucumber genome database. Analysis of the differentially expressed genes revealed that most of the genes were down-regulated in the waterlogging stages, and the differentially expressed genes mainly linked to carbon metabolism, photosynthesis, reactive oxygen species generation/scavenging, and hormone synthesis/signaling. Finally, quantitative real-time polymerase chain reaction using nine genes independently verified the tag-mapped results. This present study reveals the comprehensive mechanisms of waterlogging-responsive transcription in cucumber. Copyright © 2011 Elsevier Inc. All rights reserved.

Dynamic association rules for gene expression data analysis.

PubMed

Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

2015-10-14

The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed DAR algorithm not only was able to identify a set of differentially expressed genes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to gene expression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.

Biological characterization of adult MYC-translocation-positive mature B-cell lymphomas other than molecular Burkitt lymphoma.

PubMed

Aukema, Sietse M; Kreuz, Markus; Kohler, Christian W; Rosolowski, Maciej; Hasenclever, Dirk; Hummel, Michael; Küppers, Ralf; Lenze, Dido; Ott, German; Pott, Christiane; Richter, Julia; Rosenwald, Andreas; Szczepanowski, Monika; Schwaenen, Carsten; Stein, Harald; Trautmann, Heiko; Wessendorf, Swen; Trümper, Lorenz; Loeffler, Markus; Spang, Rainer; Kluin, Philip M; Klapper, Wolfram; Siebert, Reiner

2014-04-01

Chromosomal translocations affecting the MYC oncogene are the biological hallmark of Burkitt lymphomas but also occur in a subset of other mature B-cell lymphomas. If accompanied by a chromosomal break targeting the BCL2 and/or BCL6 oncogene these MYC translocation-positive (MYC(+)) lymphomas are called double-hit lymphomas, otherwise the term single-hit lymphomas is applied. In order to characterize the biological features of these MYC(+) lymphomas other than Burkitt lymphoma we explored, after exclusion of molecular Burkitt lymphoma as defined by gene expression profiling, the molecular, pathological and clinical aspects of 80 MYC-translocation-positive lymphomas (31 single-hit, 46 double-hit and 3 MYC(+)-lymphomas with unknown BCL6 status). Comparison of single-hit and double-hit lymphomas revealed no difference in MYC partner (IG/non-IG), genomic complexity, MYC expression or gene expression profile. Double-hit lymphomas more frequently showed a germinal center B-cell-like gene expression profile and had higher IGH and MYC mutation frequencies. Gene expression profiling revealed 130 differentially expressed genes between BCL6(+)/MYC(+) and BCL2(+)/MYC(+) double-hit lymphomas. BCL2(+)/MYC(+) double-hit lymphomas more frequently showed a germinal center B-like gene expression profile. Analysis of all lymphomas according to MYC partner (IG/non-IG) revealed no substantial differences. In this series of lymphomas, in which immunochemotherapy was administered in only a minority of cases, single-hit and double-hit lymphomas had a similar poor outcome in contrast to the outcome of molecular Burkitt lymphoma and lymphomas without the MYC break. Our data suggest that, after excluding molecular Burkitt lymphoma and pediatric cases, MYC(+) lymphomas are biologically quite homogeneous with single-hit and double-hit lymphomas as well as IG-MYC and non-IG-MYC(+) lymphomas sharing various molecular characteristics.

Placental gene-expression profiles of intrahepatic cholestasis of pregnancy reveal involvement of multiple molecular pathways in blood vessel formation and inflammation.

PubMed

Du, QiaoLing; Pan, YouDong; Zhang, YouHua; Zhang, HaiLong; Zheng, YaJuan; Lu, Ling; Wang, JunLei; Duan, Tao; Chen, JianFeng

2014-07-07

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-associated liver disease with potentially deleterious consequences for the fetus, particularly when maternal serum bile-acid concentration >40 μM. However, the etiology and pathogenesis of ICP remain elusive. To reveal the underlying molecular mechanisms for the association of maternal serum bile-acid level and fetal outcome in ICP patients, DNA microarray was applied to characterize the whole-genome expression profiles of placentas from healthy women and women diagnosed with ICP. Thirty pregnant women recruited in this study were categorized evenly into three groups: healthy group; mild ICP, with serum bile-acid concentration ranging from 10-40 μM; and severe ICP, with bile-acid concentration >40 μM. Gene Ontology analysis in combination with construction of gene-interaction and gene co-expression networks were applied to identify the core regulatory genes associated with ICP pathogenesis, which were further validated by quantitative real-time PCR and histological staining. The core regulatory genes were mainly involved in immune response, VEGF signaling pathway and G-protein-coupled receptor signaling, implying essential roles of immune response, vasculogenesis and angiogenesis in ICP pathogenesis. This implication was supported by the observed aggregated immune-cell infiltration and deficient blood vessel formation in ICP placentas. Our study provides a system-level insight into the placental gene-expression profiles of women with mild or severe ICP, and reveals multiple molecular pathways in immune response and blood vessel formation that might contribute to ICP pathogenesis.

Using expression genetics to study the neurobiology of ethanol and alcoholism.

PubMed

Farris, Sean P; Wolen, Aaron R; Miles, Michael F

2010-01-01

Recent simultaneous progress in human and animal model genetics and the advent of microarray whole genome expression profiling have produced prodigious data sets on genetic loci, potential candidate genes, and differential gene expression related to alcoholism and ethanol behaviors. Validated target genes or gene networks functioning in alcoholism are still of meager proportions. Genetical genomics, which combines genetic analysis of both traditional phenotypes and whole genome expression data, offers a potential methodology for characterizing brain gene networks functioning in alcoholism. This chapter will describe concepts, approaches, and recent findings in the field of genetical genomics as it applies to alcohol research. Copyright 2010 Elsevier Inc. All rights reserved.

New Statistics for Testing Differential Expression of Pathways from Microarray Data

NASA Astrophysics Data System (ADS)

Siu, Hoicheong; Dong, Hua; Jin, Li; Xiong, Momiao

Exploring biological meaning from microarray data is very important but remains a great challenge. Here, we developed three new statistics: linear combination test, quadratic test and de-correlation test to identify differentially expressed pathways from gene expression profile. We apply our statistics to two rheumatoid arthritis datasets. Notably, our results reveal three significant pathways and 275 genes in common in two datasets. The pathways we found are meaningful to uncover the disease mechanisms of rheumatoid arthritis, which implies that our statistics are a powerful tool in functional analysis of gene expression data.

Transcriptome profiling of two maize inbreds with distinct responses to Gibberella ear rot disease to identify candidate resistance genes.

PubMed

Kebede, Aida Z; Johnston, Anne; Schneiderman, Danielle; Bosnich, Whynn; Harris, Linda J

2018-02-09

Gibberella ear rot (GER) is one of the most economically important fungal diseases of maize in the temperate zone due to moldy grain contaminated with health threatening mycotoxins. To develop resistant genotypes and control the disease, understanding the host-pathogen interaction is essential. RNA-Seq-derived transcriptome profiles of fungal- and mock-inoculated developing kernel tissues of two maize inbred lines were used to identify differentially expressed transcripts and propose candidate genes mapping within GER resistance quantitative trait loci (QTL). A total of 1255 transcripts were significantly (P ≤ 0.05) up regulated due to fungal infection in both susceptible and resistant inbreds. A greater number of transcripts were up regulated in the former (1174) than the latter (497) and increased as the infection progressed from 1 to 2 days after inoculation. Focusing on differentially expressed genes located within QTL regions for GER resistance, we identified 81 genes involved in membrane transport, hormone regulation, cell wall modification, cell detoxification, and biosynthesis of pathogenesis related proteins and phytoalexins as candidate genes contributing to resistance. Applying droplet digital PCR, we validated the expression profiles of a subset of these candidate genes from QTL regions contributed by the resistant inbred on chromosomes 1, 2 and 9. By screening global gene expression profiles for differentially expressed genes mapping within resistance QTL regions, we have identified candidate genes for gibberella ear rot resistance on several maize chromosomes which could potentially lead to a better understanding of Fusarium resistance mechanisms.

Global Analysis of Gene Expression Profiles in Physic Nut (Jatropha curcas L.) Seedlings Exposed to Salt Stress

PubMed Central

Wu, Pingzhi; Chen, Yaping; Li, Meiru; Jiang, Huawu; Wu, Guojiang

2014-01-01

Background Salt stress interferes with plant growth and production. Plants have evolved a series of molecular and morphological adaptations to cope with this abiotic stress, and overexpression of salt response genes reportedly enhances the productivity of various crops. However, little is known about the salt responsive genes in the energy plant physic nut (Jatropha curcas L.). Thus, excavate salt responsive genes in this plant are informative in uncovering the molecular mechanisms for the salt response in physic nut. Methodology/Principal Findings We applied next-generation Illumina sequencing technology to analyze global gene expression profiles of physic nut plants (roots and leaves) 2 hours, 2 days and 7 days after the onset of salt stress. A total of 1,504 and 1,115 genes were significantly up and down-regulated in roots and leaves, respectively, under salt stress condition. Gene ontology (GO) analysis of physiological process revealed that, in the physic nut, many “biological processes” were affected by salt stress, particular those categories belong to “metabolic process”, such as “primary metabolism process”, “cellular metabolism process” and “macromolecule metabolism process”. The gene expression profiles indicated that the associated genes were responsible for ABA and ethylene signaling, osmotic regulation, the reactive oxygen species scavenging system and the cell structure in physic nut. Conclusions/Significance The major regulated genes detected in this transcriptomic data were related to trehalose synthesis and cell wall structure modification in roots, while related to raffinose synthesis and reactive oxygen scavenger in leaves. The current study shows a comprehensive gene expression profile of physic nut under salt stress. The differential expression genes detected in this study allows the underling the salt responsive mechanism in physic nut with the aim of improving its salt resistance in the future. PMID:24837971

Global analysis of gene expression profiles in physic nut (Jatropha curcas L.) seedlings exposed to salt stress.

PubMed

Zhang, Lin; Zhang, Chao; Wu, Pingzhi; Chen, Yaping; Li, Meiru; Jiang, Huawu; Wu, Guojiang

2014-01-01

Salt stress interferes with plant growth and production. Plants have evolved a series of molecular and morphological adaptations to cope with this abiotic stress, and overexpression of salt response genes reportedly enhances the productivity of various crops. However, little is known about the salt responsive genes in the energy plant physic nut (Jatropha curcas L.). Thus, excavate salt responsive genes in this plant are informative in uncovering the molecular mechanisms for the salt response in physic nut. We applied next-generation Illumina sequencing technology to analyze global gene expression profiles of physic nut plants (roots and leaves) 2 hours, 2 days and 7 days after the onset of salt stress. A total of 1,504 and 1,115 genes were significantly up and down-regulated in roots and leaves, respectively, under salt stress condition. Gene ontology (GO) analysis of physiological process revealed that, in the physic nut, many "biological processes" were affected by salt stress, particular those categories belong to "metabolic process", such as "primary metabolism process", "cellular metabolism process" and "macromolecule metabolism process". The gene expression profiles indicated that the associated genes were responsible for ABA and ethylene signaling, osmotic regulation, the reactive oxygen species scavenging system and the cell structure in physic nut. The major regulated genes detected in this transcriptomic data were related to trehalose synthesis and cell wall structure modification in roots, while related to raffinose synthesis and reactive oxygen scavenger in leaves. The current study shows a comprehensive gene expression profile of physic nut under salt stress. The differential expression genes detected in this study allows the underling the salt responsive mechanism in physic nut with the aim of improving its salt resistance in the future.

Utility and Limitations of Using Gene Expression Data to Identify Functional Associations

PubMed Central

Peng, Cheng; Shiu, Shin-Han

2016-01-01

Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets. PMID:27935950

Customized Molecular Phenotyping by Quantitative Gene Expression and Pattern Recognition Analysis

PubMed Central

Akilesh, Shreeram; Shaffer, Daniel J.; Roopenian, Derry

2003-01-01

Description of the molecular phenotypes of pathobiological processes in vivo is a pressing need in genomic biology. We have implemented a high-throughput real-time PCR strategy to establish quantitative expression profiles of a customized set of target genes. It enables rapid, reproducible data acquisition from limited quantities of RNA, permitting serial sampling of mouse blood during disease progression. We developed an easy to use statistical algorithm—Global Pattern Recognition—to readily identify genes whose expression has changed significantly from healthy baseline profiles. This approach provides unique molecular signatures for rheumatoid arthritis, systemic lupus erythematosus, and graft versus host disease, and can also be applied to defining the molecular phenotype of a variety of other normal and pathological processes. PMID:12840047

Differential Gene Expression (DEX) and Alternative Splicing Events (ASE) for Temporal Dynamic Processes Using HMMs and Hierarchical Bayesian Modeling Approaches.

PubMed

Oh, Sunghee; Song, Seongho

2017-01-01

In gene expression profile, data analysis pipeline is categorized into four levels, major downstream tasks, i.e., (1) identification of differential expression; (2) clustering co-expression patterns; (3) classification of subtypes of samples; and (4) detection of genetic regulatory networks, are performed posterior to preprocessing procedure such as normalization techniques. To be more specific, temporal dynamic gene expression data has its inherent feature, namely, two neighboring time points (previous and current state) are highly correlated with each other, compared to static expression data which samples are assumed as independent individuals. In this chapter, we demonstrate how HMMs and hierarchical Bayesian modeling methods capture the horizontal time dependency structures in time series expression profiles by focusing on the identification of differential expression. In addition, those differential expression genes and transcript variant isoforms over time detected in core prerequisite steps can be generally further applied in detection of genetic regulatory networks to comprehensively uncover dynamic repertoires in the aspects of system biology as the coupled framework.

A Practical Platform for Blood Biomarker Study by Using Global Gene Expression Profiling of Peripheral Whole Blood

PubMed Central

Schmid, Patrick; Yao, Hui; Galdzicki, Michal; Berger, Bonnie; Wu, Erxi; Kohane, Isaac S.

2009-01-01

Background Although microarray technology has become the most common method for studying global gene expression, a plethora of technical factors across the experiment contribute to the variable of genome gene expression profiling using peripheral whole blood. A practical platform needs to be established in order to obtain reliable and reproducible data to meet clinical requirements for biomarker study. Methods and Findings We applied peripheral whole blood samples with globin reduction and performed genome-wide transcriptome analysis using Illumina BeadChips. Real-time PCR was subsequently used to evaluate the quality of array data and elucidate the mode in which hemoglobin interferes in gene expression profiling. We demonstrated that, when applied in the context of standard microarray processing procedures, globin reduction results in a consistent and significant increase in the quality of beadarray data. When compared to their pre-globin reduction counterparts, post-globin reduction samples show improved detection statistics, lowered variance and increased sensitivity. More importantly, gender gene separation is remarkably clearer in post-globin reduction samples than in pre-globin reduction samples. Our study suggests that the poor data obtained from pre-globin reduction samples is the result of the high concentration of hemoglobin derived from red blood cells either interfering with target mRNA binding or giving the pseudo binding background signal. Conclusion We therefore recommend the combination of performing globin mRNA reduction in peripheral whole blood samples and hybridizing on Illumina BeadChips as the practical approach for biomarker study. PMID:19381341

Importance of correlation between gene expression levels: application to the type I interferon signature in rheumatoid arthritis.

PubMed

Reynier, Frédéric; Petit, Fabien; Paye, Malick; Turrel-Davin, Fanny; Imbert, Pierre-Emmanuel; Hot, Arnaud; Mougin, Bruno; Miossec, Pierre

2011-01-01

The analysis of gene expression data shows that many genes display similarity in their expression profiles suggesting some co-regulation. Here, we investigated the co-expression patterns in gene expression data and proposed a correlation-based research method to stratify individuals. Using blood from rheumatoid arthritis (RA) patients, we investigated the gene expression profiles from whole blood using Affymetrix microarray technology. Co-expressed genes were analyzed by a biclustering method, followed by gene ontology analysis of the relevant biclusters. Taking the type I interferon (IFN) pathway as an example, a classification algorithm was developed from the 102 RA patients and extended to 10 systemic lupus erythematosus (SLE) patients and 100 healthy volunteers to further characterize individuals. We developed a correlation-based algorithm referred to as Classification Algorithm Based on a Biological Signature (CABS), an alternative to other approaches focused specifically on the expression levels. This algorithm applied to the expression of 35 IFN-related genes showed that the IFN signature presented a heterogeneous expression between RA, SLE and healthy controls which could reflect the level of global IFN signature activation. Moreover, the monitoring of the IFN-related genes during the anti-TNF treatment identified changes in type I IFN gene activity induced in RA patients. In conclusion, we have proposed an original method to analyze genes sharing an expression pattern and a biological function showing that the activation levels of a biological signature could be characterized by its overall state of correlation.

Gene co-expression network analysis in Rhodobacter capsulatus and application to comparative expression analysis of Rhodobacter sphaeroides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pena-Castillo, Lourdes; Mercer, Ryan; Gurinovich, Anastasia

2014-08-28

The genus Rhodobacter contains purple nonsulfur bacteria found mostly in freshwater environments. Representative strains of two Rhodobacter species, R. capsulatus and R. sphaeroides, have had their genomes fully sequenced and both have been the subject of transcriptional profiling studies. Gene co-expression networks can be used to identify modules of genes with similar expression profiles. Functional analysis of gene modules can then associate co-expressed genes with biological pathways, and network statistics can determine the degree of module preservation in related networks. In this paper, we constructed an R. capsulatus gene co-expression network, performed functional analysis of identified gene modules, and investigatedmore » preservation of these modules in R. capsulatus proteomics data and in R. sphaeroides transcriptomics data. Results: The analysis identified 40 gene co-expression modules in R. capsulatus. Investigation of the module gene contents and expression profiles revealed patterns that were validated based on previous studies supporting the biological relevance of these modules. We identified two R. capsulatus gene modules preserved in the protein abundance data. We also identified several gene modules preserved between both Rhodobacter species, which indicate that these cellular processes are conserved between the species and are candidates for functional information transfer between species. Many gene modules were non-preserved, providing insight into processes that differentiate the two species. In addition, using Local Network Similarity (LNS), a recently proposed metric for expression divergence, we assessed the expression conservation of between-species pairs of orthologs, and within-species gene-protein expression profiles. Conclusions: Our analyses provide new sources of information for functional annotation in R. capsulatus because uncharacterized genes in modules are now connected with groups of genes that constitute a joint functional annotation. We identified R. capsulatus modules enriched with genes for ribosomal proteins, porphyrin and bacteriochlorophyll anabolism, and biosynthesis of secondary metabolites to be preserved in R. sphaeroides whereas modules related to RcGTA production and signalling showed lack of preservation in R. sphaeroides. In addition, we demonstrated that network statistics may also be applied within-species to identify congruence between mRNA expression and protein abundance data for which simple correlation measurements have previously had mixed results.« less

GeneChip Expression Profiling Reveals the Alterations of Energy Metabolism Related Genes in Osteocytes under Large Gradient High Magnetic Fields

PubMed Central

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

GeneChip expression profiling reveals the alterations of energy metabolism related genes in osteocytes under large gradient high magnetic fields.

PubMed

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.

Transcriptional profiling of Haemophilus parasuis SH0165 response to tilmicosin.

PubMed

Liu, Yingyu; Chen, Pin; Wang, Yang; Li, Wentao; Cheng, Shuang; Wang, Chunmei; Zhang, Anding; He, Qigai

2012-12-01

The Haemophilus parasuis respiratory tract pathogen poses a severe threat to the swine industry despite available antimicrobial therapies. To gain a more detailed understanding of the molecular mechanisms underlying H. parasuis response to tilmicosin treatment, microarray technology was applied to analyze the variation in gene expression of isolated H. parasuis SH0165 treated in vitro with subinhibitory (0.25 μg/ml) and inhibitory (8 μg/ml) concentrations. Tilmicosin treatment induced differential expression of 405 genes, the encoded products of which are mainly involved in the heat shock response, protein synthesis, and intracellular transportation. The subinhibitory and inhibitory concentrations of tilmicosin induced distinctive gene expression profiles of shared and unique changes, respectively. These changes included 302 genes mainly involved in protein export and the phosphotransferase system to sustain cell growth, and 198 genes mainly related to RNA polymerase, recombination, and repair to inhibit cell growth. In silico analysis of functions related to the differentially expressed genes suggested that adaptation of H. parasuis SH0165 to tilmicosin involves modulation of protein synthesis and membrane transport. Collectively, the genes comprising each transcriptional profile of H. parasuis response to tilmicosin provide novel insights into the physiological functions of this economically significant bacterium and may represent targets of future molecular therapeutic strategies.

Biological mechanism analysis of acute renal allograft rejection: integrated of mRNA and microRNA expression profiles.

PubMed

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.

Biological mechanism analysis of acute renal allograft rejection: integrated of mRNA and microRNA expression profiles

PubMed Central

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

Quantifying whole transcriptome size, a prerequisite for understanding transcriptome evolution across species: an example from a plant allopolyploid.

PubMed

Coate, Jeremy E; Doyle, Jeff J

2010-01-01

Evolutionary biologists are increasingly comparing gene expression patterns across species. Due to the way in which expression assays are normalized, such studies provide no direct information about expression per gene copy (dosage responses) or per cell and can give a misleading picture of genes that are differentially expressed. We describe an assay for estimating relative expression per cell. When used in conjunction with transcript profiling data, it is possible to compare the sizes of whole transcriptomes, which in turn makes it possible to compare expression per cell for each gene in the transcript profiling data set. We applied this approach, using quantitative reverse transcriptase-polymerase chain reaction and high throughput RNA sequencing, to a recently formed allopolyploid and showed that its leaf transcriptome was approximately 1.4-fold larger than either progenitor transcriptome (70% of the sum of the progenitor transcriptomes). In contrast, the allopolyploid genome is 94.3% as large as the sum of its progenitor genomes and retains > or =93.5% of the sum of its progenitor gene complements. Thus, "transcriptome downsizing" is greater than genome downsizing. Using this transcriptome size estimate, we inferred dosage responses for several thousand genes and showed that the majority exhibit partial dosage compensation. Homoeologue silencing is nonrandomly distributed across dosage responses, with genes showing extreme responses in either direction significantly more likely to have a silent homoeologue. This experimental approach will add value to transcript profiling experiments involving interspecies and interploidy comparisons by converting expression per transcriptome to expression per genome, eliminating the need for assumptions about transcriptome size.

[Study on action mechanism and material base of compound Danshen dripping pills in treatment of carotid atherosclerosis based on techniques of gene expression profile and molecular fingerprint].

PubMed

Zhou, Wei; Song, Xiang-gang; Chen, Chao; Wang, Shu-mei; Liang, Sheng-wang

2015-08-01

Action mechanism and material base of compound Danshen dripping pills in treatment of carotid atherosclerosis were discussed based on gene expression profile and molecular fingerprint in this paper. First, gene expression profiles of atherosclerotic carotid artery tissues and histologically normal tissues in human body were collected, and were screened using significance analysis of microarray (SAM) to screen out differential gene expressions; then differential genes were analyzed by Gene Ontology (GO) analysis and KEGG pathway analysis; to avoid some genes with non-outstanding differential expression but biologically importance, Gene Set Enrichment Analysis (GSEA) were performed, and 7 chemical ingredients with higher negative enrichment score were obtained by Cmap method, implying that they could reversely regulate the gene expression profiles of pathological tissues; and last, based on the hypotheses that similar structures have similar activities, 336 ingredients of compound Danshen dripping pills were compared with 7 drug molecules in 2D molecular fingerprints method. The results showed that 147 differential genes including 60 up-regulated genes and 87 down regulated genes were screened out by SAM. And in GO analysis, Biological Process ( BP) is mainly concerned with biological adhesion, response to wounding and inflammatory response; Cellular Component (CC) is mainly concerned with extracellular region, extracellular space and plasma membrane; while Molecular Function (MF) is mainly concerned with antigen binding, metalloendopeptidase activity and peptide binding. KEGG pathway analysis is mainly concerned with JAK-STAT, RIG-I like receptor and PPAR signaling pathway. There were 10 compounds, such as hexadecane, with Tanimoto coefficients greater than 0.85, which implied that they may be the active ingredients (AIs) of compound Danshen dripping pills in treatment of carotid atherosclerosis (CAs). The present method can be applied to the research on material base and molecular action mechanism of TCM.

The complexity of gene expression dynamics revealed by permutation entropy

PubMed Central

2010-01-01

Background High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity. Results Applying the PE complexity metric to abiotic stress response time series data in Arabidopsis thaliana, genes involved in stress response and signaling were found to be associated with the highest complexity not only under stress, but surprisingly, also under reference, non-stress conditions. Genes with house-keeping functions exhibited lower PE complexity. Compared to reference conditions, the PE of temporal gene expression patterns generally increased upon stress exposure. High-complexity genes were found to have longer upstream intergenic regions and more cis-regulatory motifs in their promoter regions indicative of a more complex regulatory apparatus needed to orchestrate their expression, and to be associated with higher correlation network connectivity degree. Arabidopsis genes also present in other plant species were observed to exhibit decreased PE complexity compared to Arabidopsis specific genes. Conclusions We show that Permutation Entropy is a simple yet robust and powerful approach to identify temporal gene expression profiles of varying complexity that is equally applicable to other types of molecular profile data. PMID:21176199

Unravelling the neurophysiological basis of aggression in a fish model

PubMed Central

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

F-MAP: A Bayesian approach to infer the gene regulatory network using external hints

PubMed Central

Shahdoust, Maryam; Mahjub, Hossein; Sadeghi, Mehdi

2017-01-01

The Common topological features of related species gene regulatory networks suggest reconstruction of the network of one species by using the further information from gene expressions profile of related species. We present an algorithm to reconstruct the gene regulatory network named; F-MAP, which applies the knowledge about gene interactions from related species. Our algorithm sets a Bayesian framework to estimate the precision matrix of one species microarray gene expressions dataset to infer the Gaussian Graphical model of the network. The conjugate Wishart prior is used and the information from related species is applied to estimate the hyperparameters of the prior distribution by using the factor analysis. Applying the proposed algorithm on six related species of drosophila shows that the precision of reconstructed networks is improved considerably compared to the precision of networks constructed by other Bayesian approaches. PMID:28938012

Constrained clusters of gene expression profiles with pathological features.

PubMed

Sese, Jun; Kurokawa, Yukinori; Monden, Morito; Kato, Kikuya; Morishita, Shinichi

2004-11-22

Gene expression profiles should be useful in distinguishing variations in disease, since they reflect accurately the status of cells. The primary clustering of gene expression reveals the genotypes that are responsible for the proximity of members within each cluster, while further clustering elucidates the pathological features of the individual members of each cluster. However, since the first clustering process and the second classification step, in which the features are associated with clusters, are performed independently, the initial set of clusters may omit genes that are associated with pathologically meaningful features. Therefore, it is important to devise a way of identifying gene expression clusters that are associated with pathological features. We present the novel technique of 'itemset constrained clustering' (IC-Clustering), which computes the optimal cluster that maximizes the interclass variance of gene expression between groups, which are divided according to the restriction that only divisions that can be expressed using common features are allowed. This constraint automatically labels each cluster with a set of pathological features which characterize that cluster. When applied to liver cancer datasets, IC-Clustering revealed informative gene expression clusters, which could be annotated with various pathological features, such as 'tumor' and 'man', or 'except tumor' and 'normal liver function'. In contrast, the k-means method overlooked these clusters.

Computational gene expression profiling under salt stress reveals patterns of co-expression

PubMed Central

Sanchita; Sharma, Ashok

2016-01-01

Plants respond differently to environmental conditions. Among various abiotic stresses, salt stress is a condition where excess salt in soil causes inhibition of plant growth. To understand the response of plants to the stress conditions, identification of the responsible genes is required. Clustering is a data mining technique used to group the genes with similar expression. The genes of a cluster show similar expression and function. We applied clustering algorithms on gene expression data of Solanum tuberosum showing differential expression in Capsicum annuum under salt stress. The clusters, which were common in multiple algorithms were taken further for analysis. Principal component analysis (PCA) further validated the findings of other cluster algorithms by visualizing their clusters in three-dimensional space. Functional annotation results revealed that most of the genes were involved in stress related responses. Our findings suggest that these algorithms may be helpful in the prediction of the function of co-expressed genes. PMID:26981411

CHESS (CgHExpreSS): a comprehensive analysis tool for the analysis of genomic alterations and their effects on the expression profile of the genome.

PubMed

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.

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...

Challenges of microarray applications for microbial detection and gene expression profiling in food

USDA-ARS?s Scientific Manuscript database

Microarray technology represents one of the latest advances in molecular biology. The diverse types of microarrays have been applied to clinical and environmental microbiology, microbial ecology, and in human, veterinary, and plant diagnostics. Since multiple genes can be analyzed simultaneously, ...

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.

PubMed

Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne

2005-04-15

The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.

Differential co-expression and regulation analyses reveal different mechanisms underlying major depressive disorder and subsyndromal symptomatic depression.

PubMed

Xu, Fan; Yang, Jing; Chen, Jin; Wu, Qingyuan; Gong, Wei; Zhang, Jianguo; Shao, Weihua; Mu, Jun; Yang, Deyu; Yang, Yongtao; Li, Zhiwei; Xie, Peng

2015-04-03

Recent depression research has revealed a growing awareness of how to best classify depression into depressive subtypes. Appropriately subtyping depression can lead to identification of subtypes that are more responsive to current pharmacological treatment and aid in separating out depressed patients in which current antidepressants are not particularly effective. Differential co-expression analysis (DCEA) and differential regulation analysis (DRA) were applied to compare the transcriptomic profiles of peripheral blood lymphocytes from patients with two depressive subtypes: major depressive disorder (MDD) and subsyndromal symptomatic depression (SSD). Six differentially regulated genes (DRGs) (FOSL1, SRF, JUN, TFAP4, SOX9, and HLF) and 16 transcription factor-to-target differentially co-expressed gene links or pairs (TF2target DCLs) appear to be the key differential factors in MDD; in contrast, one DRG (PATZ1) and eight TF2target DCLs appear to be the key differential factors in SSD. There was no overlap between the MDD target genes and SSD target genes. Venlafaxine (Efexor™, Effexor™) appears to have a significant effect on the gene expression profile of MDD patients but no significant effect on the gene expression profile of SSD patients. DCEA and DRA revealed no apparent similarities between the differential regulatory processes underlying MDD and SSD. This bioinformatic analysis may provide novel insights that can support future antidepressant R&D efforts.

Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

PubMed Central

Moretti, Stefano; van Leeuwen, Danitsja; Gmuender, Hans; Bonassi, Stefano; van Delft, Joost; Kleinjans, Jos; Patrone, Fioravante; Merlo, Domenico Franco

2008-01-01

Background In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. Results In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. Conclusion CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between coalitional games and statistics that resulted in a selection of genes with a potential impact in the regulation of complex pathways. PMID:18764936

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes.

PubMed

Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

2014-01-01

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice.

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes

PubMed Central

Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

2014-01-01

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice. PMID:25374455

Global analysis of gene expression profiles in developing physic nut (Jatropha curcas L.) seeds.

PubMed

Jiang, Huawu; Wu, Pingzhi; Zhang, Sheng; Song, Chi; Chen, Yaping; Li, Meiru; Jia, Yongxia; Fang, Xiaohua; Chen, Fan; Wu, Guojiang

2012-01-01

Physic nut (Jatropha curcas L.) is an oilseed plant species with high potential utility as a biofuel. Furthermore, following recent sequencing of its genome and the availability of expressed sequence tag (EST) libraries, it is a valuable model plant for studying carbon assimilation in endosperms of oilseed plants. There have been several transcriptomic analyses of developing physic nut seeds using ESTs, but they have provided limited information on the accumulation of stored resources in the seeds. We applied next-generation Illumina sequencing technology to analyze global gene expression profiles of developing physic nut seeds 14, 19, 25, 29, 35, 41, and 45 days after pollination (DAP). The acquired profiles reveal the key genes, and their expression timeframes, involved in major metabolic processes including: carbon flow, starch metabolism, and synthesis of storage lipids and proteins in the developing seeds. The main period of storage reserves synthesis in the seeds appears to be 29-41 DAP, and the fatty acid composition of the developing seeds is consistent with relative expression levels of different isoforms of acyl-ACP thioesterase and fatty acid desaturase genes. Several transcription factor genes whose expression coincides with storage reserve deposition correspond to those known to regulate the process in Arabidopsis. The results will facilitate searches for genes that influence de novo lipid synthesis, accumulation and their regulatory networks in developing physic nut seeds, and other oil seeds. Thus, they will be helpful in attempts to modify these plants for efficient biofuel production.

Comparative transcriptional profiling of tildipirosin-resistant and sensitive Haemophilus parasuis.

PubMed

Lei, Zhixin; Fu, Shulin; Yang, Bing; Liu, Qianying; Ahmed, Saeed; Xu, Lei; Xiong, Jincheng; Cao, Jiyue; Qiu, Yinsheng

2017-08-08

Numerous studies have been conducted to examine the molecular mechanism of Haemophilus parasuis resistance to antibiotic, but rarely to tildipirosin. In the current study, transcriptional profiling was applied to analyse the variation in gene expression of JS0135 and tildipirosin-resistant JS32. The growth curves showed that JS32 had a higher growth rate but fewer bacteria than JS0135. The cell membranes of JS32 and a resistant clinical isolate (HB32) were observed to be smoother than those of JS0135. From the comparative gene expression profile 349 up- and 113 downregulated genes were observed, covering 37 GO and 63 KEGG pathways which are involved in biological processes (11), cellular components (17), molecular function (9), cellular processes (1), environmental information processing (4), genetic information processing (9) and metabolism (49) affected in JS32. In addition, the relative overexpression of genes of the metabolism pathway (HAPS_RS09315, HAPS_RS09320), ribosomes (HAPS_RS07815) and ABC transporters (HAPS_RS10945) was detected, particularly the metabolism pathway, and verified with RT-qPCR. Collectively, the gene expression profile in connection with tildipirosin resistance factors revealed unique and highly resistant determinants of H. parasuis to macrolides that warrant further attention due to the significant threat of bacterial resistance.

Comparing Pearson, Spearman and Hoeffding's D measure for gene expression association analysis.

PubMed

Fujita, André; Sato, João Ricardo; Demasi, Marcos Angelo Almeida; Sogayar, Mari Cleide; Ferreira, Carlos Eduardo; Miyano, Satoru

2009-08-01

DNA microarrays have become a powerful tool to describe gene expression profiles associated with different cellular states, various phenotypes and responses to drugs and other extra- or intra-cellular perturbations. In order to cluster co-expressed genes and/or to construct regulatory networks, definition of distance or similarity between measured gene expression data is usually required, the most common choices being Pearson's and Spearman's correlations. Here, we evaluate these two methods and also compare them with a third one, namely Hoeffding's D measure, which is used to infer nonlinear and non-monotonic associations, i.e. independence in a general sense. By comparing three different variable association approaches, namely Pearson's correlation, Spearman's correlation and Hoeffding's D measure, we aimed at assessing the most appropriate one for each purpose. Using simulations, we demonstrate that the Hoeffding's D measure outperforms Pearson's and Spearman's approaches in identifying nonlinear associations. Our results demonstrate that Hoeffding's D measure is less sensitive to outliers and is a more powerful tool to identify nonlinear and non-monotonic associations. We have also applied Hoeffding's D measure in order to identify new putative genes associated with tp53. Therefore, we propose the Hoeffding's D measure to identify nonlinear associations between gene expression profiles.

Analysis of blood-based gene expression in idiopathic Parkinson disease.

PubMed

Shamir, Ron; Klein, Christine; Amar, David; Vollstedt, Eva-Juliane; Bonin, Michael; Usenovic, Marija; Wong, Yvette C; Maver, Ales; Poths, Sven; Safer, Hershel; Corvol, Jean-Christophe; Lesage, Suzanne; Lavi, Ofer; Deuschl, Günther; Kuhlenbaeumer, Gregor; Pawlack, Heike; Ulitsky, Igor; Kasten, Meike; Riess, Olaf; Brice, Alexis; Peterlin, Borut; Krainc, Dimitri

2017-10-17

To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples). Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks. A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E-6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E-4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1 , ATP5A1 , and VDAC3 . We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers. © 2017 American Academy of Neurology.

Microarray Analysis of Differential Gene Expression Profile Between Human Fetal and Adult Heart.

PubMed

Geng, Zhimin; Wang, Jue; Pan, Lulu; Li, Ming; Zhang, Jitai; Cai, Xueli; Chu, Maoping

2017-04-01

Although many changes have been discovered during heart maturation, the genetic mechanisms involved in the changes between immature and mature myocardium have only been partially elucidated. Here, gene expression profile changed between the human fetal and adult heart was characterized. A human microarray was applied to define the gene expression signatures of the fetal (13-17 weeks of gestation, n = 4) and adult hearts (30-40 years old, n = 4). Gene ontology analyses, pathway analyses, gene set enrichment analyses, and signal transduction network were performed to predict the function of the differentially expressed genes. Ten mRNAs were confirmed by quantificational real-time polymerase chain reaction. 5547 mRNAs were found to be significantly differentially expressed. "Cell cycle" was the most enriched pathway in the down-regulated genes. EFGR, IGF1R, and ITGB1 play a central role in the regulation of heart development. EGFR, IGF1R, and FGFR2 were the core genes regulating cardiac cell proliferation. The quantificational real-time polymerase chain reaction results were concordant with the microarray data. Our data identified the transcriptional regulation of heart development in the second trimester and the potential regulators that play a prominent role in the regulation of heart development and cardiac cells proliferation.

Evidence of Dynamically Dysregulated Gene Expression Pathways in Hyperresponsive B Cells from African American Lupus Patients

PubMed Central

Dozmorov, Igor; Dominguez, Nicolas; Sestak, Andrea L.; Robertson, Julie M.; Harley, John B.; James, Judith A.; Guthridge, Joel M.

2013-01-01

Recent application of gene expression profiling to the immune system has shown a great potential for characterization of complex regulatory processes. It is becoming increasingly important to characterize functional systems through multigene interactions to provide valuable insights into differences between healthy controls and autoimmune patients. Here we apply an original systematic approach to the analysis of changes in regulatory gene interconnections between in Epstein-Barr virus transformed hyperresponsive B cells from SLE patients and normal control B cells. Both traditional analysis of differential gene expression and analysis of the dynamics of gene expression variations were performed in combination to establish model networks of functional gene expression. This Pathway Dysregulation Analysis identified known transcription factors and transcriptional regulators activated uniquely in stimulated B cells from SLE patients. PMID:23977035

Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile.

PubMed

Long, Jin; Liu, Zhe; Wu, Xingda; Xu, Yuanhong; Ge, Chunlin

2016-05-01

The present study aimed to screen for potential genes and subnetworks associated with pancreatic cancer (PC) using the gene expression profile. The expression profile GSE 16515 was downloaded from the Gene Expression Omnibus database, which included 36 PC tissue samples and 16 normal samples. Limma package in R language was used to screen differentially expressed genes (DEGs), which were grouped as up‑ and downregulated genes. Then, PFSNet was applied to perform subnetwork analysis for all the DEGs. Moreover, Gene Ontology (GO) and REACTOME pathway enrichment analysis of up‑ and downregulated genes was performed, followed by protein‑protein interaction (PPI) network construction using Search Tool for the Retrieval of Interacting Genes Search Tool for the Retrieval of Interacting Genes. In total, 1,989 DEGs including 1,461 up‑ and 528 downregulated genes were screened out. Subnetworks including pancreatic cancer in PC tissue samples and intercellular adhesion in normal samples were identified, respectively. A total of 8 significant REACTOME pathways for upregulated DEGs, such as hemostasis and cell cycle, mitotic were identified. Moreover, 4 significant REACTOME pathways for downregulated DEGs, including regulation of β‑cell development and transmembrane transport of small molecules were screened out. Additionally, DEGs with high connectivity degrees, such as CCNA2 (cyclin A2) and PBK (PDZ binding kinase), of the module in the protein‑protein interaction network were mainly enriched with cell‑division cycle. CCNA2 and PBK of the module and their relative pathway cell‑division cycle, and two subnetworks (pancreatic cancer and intercellular adhesion subnetworks) may be pivotal for further understanding of the molecular mechanism of PC.

Transcriptomic Modification in the Cerebral Cortex following Noninvasive Brain Stimulation: RNA-Sequencing Approach

PubMed Central

Holmes, Ben; Jung, Seung Ho; Lu, Jing; Wagner, Jessica A.; Rubbi, Liudmilla; Pellegrini, Matteo

2016-01-01

Transcranial direct current stimulation (tDCS) has been shown to modulate neuroplasticity. Beneficial effects are observed in patients with psychiatric disorders and enhancement of brain performance in healthy individuals has been observed following tDCS. However, few studies have attempted to elucidate the underlying molecular mechanisms of tDCS in the brain. This study was conducted to assess the impact of tDCS on gene expression within the rat cerebral cortex. Anodal tDCS was applied at 3 different intensities followed by RNA-sequencing and analysis. In each current intensity, approximately 1,000 genes demonstrated statistically significant differences compared to the sham group. A variety of functional pathways, biological processes, and molecular categories were found to be modified by tDCS. The impact of tDCS on gene expression was dependent on current intensity. Results show that inflammatory pathways, antidepressant-related pathways (GTP signaling, calcium ion binding, and transmembrane/signal peptide pathways), and receptor signaling pathways (serotonergic, adrenergic, GABAergic, dopaminergic, and glutamate) were most affected. Of the gene expression profiles induced by tDCS, some changes were observed across multiple current intensities while other changes were unique to a single stimulation intensity. This study demonstrates that tDCS can modify the expression profile of various genes in the cerebral cortex and that these tDCS-induced alterations are dependent on the current intensity applied. PMID:28119786

Discovering functional modules by topic modeling RNA-Seq based toxicogenomic data.

PubMed

Yu, Ke; Gong, Binsheng; Lee, Mikyung; Liu, Zhichao; Xu, Joshua; Perkins, Roger; Tong, Weida

2014-09-15

Toxicogenomics (TGx) endeavors to elucidate the underlying molecular mechanisms through exploring gene expression profiles in response to toxic substances. Recently, RNA-Seq is increasingly regarded as a more powerful alternative to microarrays in TGx studies. However, realizing RNA-Seq's full potential requires novel approaches to extracting information from the complex TGx data. Considering read counts as the number of times a word occurs in a document, gene expression profiles from RNA-Seq are analogous to a word by document matrix used in text mining. Topic modeling aiming at to discover the latent structures in text corpora would be helpful to explore RNA-Seq based TGx data. In this study, topic modeling was applied on a typical RNA-Seq based TGx data set to discover hidden functional modules. The RNA-Seq based gene expression profiles were transformed into "documents", on which latent Dirichlet allocation (LDA) was used to build a topic model. We found samples treated by the compounds with the same modes of actions (MoAs) could be clustered based on topic similarities. The topic most relevant to each cluster was identified as a "marker" topic, which was interpreted by gene enrichment analysis with MoAs then confirmed by compound and pathways associations mined from literature. To further validate the "marker" topics, we tested topic transferability from RNA-Seq to microarrays. The RNA-Seq based gene expression profile of a topic specifically associated with peroxisome proliferator-activated receptors (PPAR) signaling pathway was used to query samples with similar expression profiles in two different microarray data sets, yielding accuracy of about 85%. This proof-of-concept study demonstrates the applicability of topic modeling to discover functional modules in RNA-Seq data and suggests a valuable computational tool for leveraging information within TGx data in RNA-Seq era.

Transcriptome profiling of a Saccharomyces cerevisiae mutant with a constitutively activated Ras/cAMP pathway.

PubMed

Jones, D L; Petty, J; Hoyle, D C; Hayes, A; Ragni, E; Popolo, L; Oliver, S G; Stateva, L I

2003-12-16

Often changes in gene expression levels have been considered significant only when above/below some arbitrarily chosen threshold. We investigated the effect of applying a purely statistical approach to microarray analysis and demonstrated that small changes in gene expression have biological significance. Whole genome microarray analysis of a pde2Delta mutant, constructed in the Saccharomyces cerevisiae reference strain FY23, revealed altered expression of approximately 11% of protein encoding genes. The mutant, characterized by constitutive activation of the Ras/cAMP pathway, has increased sensitivity to stress, reduced ability to assimilate nonfermentable carbon sources, and some cell wall integrity defects. Applying the Munich Information Centre for Protein Sequences (MIPS) functional categories revealed increased expression of genes related to ribosome biogenesis and downregulation of genes in the cell rescue, defense, cell death and aging category, suggesting a decreased response to stress conditions. A reduced level of gene expression in the unfolded protein response pathway (UPR) was observed. Cell wall genes whose expression was affected by this mutation were also identified. Several of the cAMP-responsive orphan genes, upon further investigation, revealed cell wall functions; others had previously unidentified phenotypes assigned to them. This investigation provides a statistical global transcriptome analysis of the cellular response to constitutive activation of the Ras/cAMP pathway.

Gene-expression profiles of epithelial cells treated with EMD in vitro: analysis using complementary DNA arrays.

PubMed

Kapferer, I; Schmidt, S; Gstir, R; Durstberger, G; Huber, L A; Vietor, I

2011-02-01

During surgical periodontal treatment, EMD is topically applied in order to facilitate regeneration of the periodontal ligament, acellular cementum and alveolar bone. Suppresion of epithelial down-growth is essential for successful periodontal regeneration; however, the underlying mechanisms of how EMD influences epithelial wound healing are poorly understood. In the present study, the effects of EMD on gene-expression profiling in an epithelial cell line (HSC-2) model were investigated. Gene-expression modifications, determined using a comparative genome-wide expression-profiling strategy, were independently validated by quantitative real-time RT-PCR. Additionally, cell cycle, cell growth and in vitro wound-healing assays were conducted. A set of 43 EMD-regulated genes was defined, which may be responsible for the reduced epithelial down-growth upon EMD application. Gene ontology analysis revealed genes that could be attributed to pathways of locomotion, developmental processes and associated processes such as regulation of cell size and cell growth. Additionally, eight regulated genes have previously been reported to take part in the process of epithelial-to-mesenchymal transition. Several independent experimental assays revealed significant inhibition of cell migration, growth and cell cycle by EMD. The set of EMD-regulated genes identified in this study offers the opportunity to clarify mechanisms underlying the effects of EMD on epithelial cells. Reduced epithelial repopulation of the dental root upon periodontal surgery may be the consequence of reduced migration and cell growth, as well as epithelial-to-mesenchymal transition. © 2010 John Wiley & Sons A/S.

Epigenomics of Total Acute Sleep Deprivation in Relation to Genome-Wide DNA Methylation Profiles and RNA Expression.

PubMed

Nilsson, Emil K; Boström, Adrian E; Mwinyi, Jessica; Schiöth, Helgi B

2016-06-01

Despite an established link between sleep deprivation and epigenetic processes in humans, it remains unclear to what extent sleep deprivation modulates DNA methylation. We performed a within-subject randomized blinded study with 16 healthy subjects to examine the effect of one night of total sleep deprivation (TSD) on the genome-wide methylation profile in blood compared with that in normal sleep. Genome-wide differences in methylation between both conditions were assessed by applying a paired regression model that corrected for monocyte subpopulations. In addition, the correlations between the methylation of genes detected to be modulated by TSD and gene expression were examined in a separate, publicly available cohort of 10 healthy male donors (E-GEOD-49065). Sleep deprivation significantly affected the DNA methylation profile both independently and in dependency of shifts in monocyte composition. Our study detected differential methylation of 269 probes. Notably, one CpG site was located 69 bp upstream of ING5, which has been shown to be differentially expressed after sleep deprivation. Gene set enrichment analysis detected the Notch and Wnt signaling pathways to be enriched among the differentially methylated genes. These results provide evidence that total acute sleep deprivation alters the methylation profile in healthy human subjects. This is, to our knowledge, the first study that systematically investigated the impact of total acute sleep deprivation on genome-wide DNA methylation profiles in blood and related the epigenomic findings to the expression data.

Comparing effects of perfusion and hydrostatic pressure on gene profiles of human chondrocyte.

PubMed

Zhu, Ge; Mayer-Wagner, Susanne; Schröder, Christian; Woiczinski, Matthias; Blum, Helmut; Lavagi, Ilaria; Krebs, Stefan; Redeker, Julia I; Hölzer, Andreas; Jansson, Volkmar; Betz, Oliver; Müller, Peter E

2015-09-20

Hydrostatic pressure and perfusion have been shown to regulate the chondrogenic potential of articular chondrocytes. In order to compare the effects of hydrostatic pressure plus perfusion (HPP) and perfusion (P) we investigated the complete gene expression profiles of human chondrocytes under HPP and P. A simplified bioreactor was constructed to apply loading (0.1 MPa for 2 h) and perfusion (2 ml) through the same piping by pressurizing the medium directly. High-density monolayer cultures of human chondrocytes were exposed to HPP or P for 4 days. Controls (C) were maintained in static cultures. Gene expression was evaluated by sequencing (RNAseq) and quantitative real-time PCR analysis. Both treatments changed gene expression levels of human chondrocytes significantly. Specifically, HPP and P increased COL2A1 expression and decreased COL1A1 and MMP-13 expression. Despite of these similarities, RNAseq revealed a list of cartilage genes including ACAN, ITGA10 and TNC, which were differentially expressed by HPP and P. Of these candidates, adhesion related molecules were found to be upregulated in HPP. Both HPP and P treatment had beneficial effects on chondrocyte differentiation and decreased catabolic enzyme expression. The study provides new insight into how hydrostatic pressure and perfusion enhance cartilage differentiation and inhibit catabolic effects. Copyright © 2015 Elsevier B.V. All rights reserved.

Simultaneous monitoring of independent gene expression patterns in two types of cocultured fibroblasts with different color-emitting luciferases

PubMed Central

Noguchi, Takako; Ikeda, Masaaki; Ohmiya, Yoshihiro; Nakajima, Yoshihiro

2008-01-01

Background Luciferase assay systems enable the real-time monitoring of gene expression in living cells. We have developed a dual-color luciferase assay system in which the expression of multiple genes can be tracked simultaneously using green- and red-emitting beetle luciferases. We have applied the system to monitoring independent gene expressions in two types of cocultured fibroblasts in real time. Results Two Rat-1 cell lines were established that stably express either green- or red-emitting luciferases under the control of the mBmal1 promoter, a canonical clock gene. We cocultured these cell lines, and gene expression profiles in both were monitored simultaneously. The circadian rhythms of these cell lines are independent, oscillating following their intrinsic circadian phases, even when cocultured. Furthermore, the independent rhythms were synchronized by medium change as an external stimulus. Conclusion Using this system, we successfully monitored independent gene expression patterns in two lines of cocultured fibroblasts. PMID:18416852

Discovering Functions of Unannotated Genes from a Transcriptome Survey of Wild Fungal Isolates

PubMed Central

Ellison, Christopher E.; Kowbel, David; Glass, N. Louise; Taylor, John W.

2014-01-01

ABSTRACT Most fungal genomes are poorly annotated, and many fungal traits of industrial and biomedical relevance are not well suited to classical genetic screens. Assigning genes to phenotypes on a genomic scale thus remains an urgent need in the field. We developed an approach to infer gene function from expression profiles of wild fungal isolates, and we applied our strategy to the filamentous fungus Neurospora crassa. Using transcriptome measurements in 70 strains from two well-defined clades of this microbe, we first identified 2,247 cases in which the expression of an unannotated gene rose and fell across N. crassa strains in parallel with the expression of well-characterized genes. We then used image analysis of hyphal morphologies, quantitative growth assays, and expression profiling to test the functions of four genes predicted from our population analyses. The results revealed two factors that influenced regulation of metabolism of nonpreferred carbon and nitrogen sources, a gene that governed hyphal architecture, and a gene that mediated amino acid starvation resistance. These findings validate the power of our population-transcriptomic approach for inference of novel gene function, and we suggest that this strategy will be of broad utility for genome-scale annotation in many fungal systems. PMID:24692637

Single cell gene expression profiling in Alzheimer's disease.

PubMed

Ginsberg, Stephen D; Che, Shaoli; Counts, Scott E; Mufson, Elliott J

2006-07-01

Development and implementation of microarray techniques to quantify expression levels of dozens to hundreds to thousands of transcripts simultaneously within select tissue samples from normal control subjects and neurodegenerative diseased brains has enabled scientists to create molecular fingerprints of vulnerable neuronal populations in Alzheimer's disease (AD) and related disorders. A goal is to sample gene expression from homogeneous cell types within a defined region without potential contamination by expression profiles of adjacent neuronal subpopulations and nonneuronal cells. The precise resolution afforded by single cell and population cell RNA analysis in combination with microarrays and real-time quantitative polymerase chain reaction (qPCR)-based analyses allows for relative gene expression level comparisons across cell types under different experimental conditions and disease progression. The ability to analyze single cells is an important distinction from global and regional assessments of mRNA expression and can be applied to optimally prepared tissues from animal models of neurodegeneration as well as postmortem human brain tissues. Gene expression analysis in postmortem AD brain regions including the hippocampal formation and neocortex reveals selectively vulnerable cell types share putative pathogenetic alterations in common classes of transcripts, for example, markers of glutamatergic neurotransmission, synaptic-related markers, protein phosphatases and kinases, and neurotrophins/neurotrophin receptors. Expression profiles of vulnerable regions and neurons may reveal important clues toward the understanding of the molecular pathogenesis of various neurological diseases and aid in identifying rational targets toward pharmacotherapeutic interventions for progressive, late-onset neurodegenerative disorders such as mild cognitive impairment (MCI) and AD.

A comparison of honeybee (Apis mellifera) queen, worker and drone larvae by RNA-Seq.

PubMed

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.

Microarray analysis of port wine stains before and after pulsed dye laser treatment.

PubMed

Laquer, Vivian T; Hevezi, Peter A; Albrecht, Huguette; Chen, Tina S; Zlotnik, Albert; Kelly, Kristen M

2013-02-01

Neither the pathogenesis of port wine stain (PWS) birthmarks nor tissue effects of pulsed dye laser (PDL) treatment of these lesions is fully understood. There are few published reports utilizing gene expression analysis in human PWS skin. We aim to compare gene expression in PWS before and after PDL, using DNA microarrays that represent most, if not all, human genes to obtain comprehensive molecular profiles of PWS lesions and PDL-associated tissue effects. Five human subjects had PDL treatment of their PWS. One week later, three biopsies were taken from each subject: normal skin (N); untreated PWS (PWS); PWS post-PDL (PWS + PDL). Samples included two lower extremity lesions, two facial lesions, and one facial nodule. High-quality total RNA isolated from skin biopsies was processed and applied to Affymetrix Human gene 1.0ST microarrays for gene expression analysis. We performed a 16 pair-wise comparison identifying either up- or down-regulated genes between N versus PWS and PWS versus PWS + PDL for four of the donor samples. The PWS nodule (nPWS) was analyzed separately. There was significant variation in gene expression profiles between individuals. By doing pair-wise comparisons between samples taken from the same donor, we were able to identify genes that may participate in the formation of PWS lesions and PDL tissue effects. Genes associated with immune, epidermal, and lipid metabolism were up-regulated in PWS skin. The nPWS exhibited more profound differences in gene expression than the rest of the samples, with significant differential expression of genes associated with angiogenesis, tumorigenesis, and inflammation. In summary, gene expression profiles from N, PWS, and PWS + PDL demonstrated significant variation within samples from the same donor and between donors. By doing pair-wise comparisons between samples taken from the same donor and comparing these results between donors, we were able to identify genes that may participate in formation of PWS and PDL effects. Our preliminary results indicate changes in gene expression of angiogenesis-related genes, suggesting that dysregulation of angiogenic signals and/or components may contribute to PWS pathology. Copyright © 2012 Wiley Periodicals, Inc.

Global Analysis of Gene Expression Profiles in Developing Physic Nut (Jatropha curcas L.) Seeds

PubMed Central

Jiang, Huawu; Wu, Pingzhi; Zhang, Sheng; Song, Chi; Chen, Yaping; Li, Meiru; Jia, Yongxia; Fang, Xiaohua; Chen, Fan; Wu, Guojiang

2012-01-01

Background Physic nut (Jatropha curcas L.) is an oilseed plant species with high potential utility as a biofuel. Furthermore, following recent sequencing of its genome and the availability of expressed sequence tag (EST) libraries, it is a valuable model plant for studying carbon assimilation in endosperms of oilseed plants. There have been several transcriptomic analyses of developing physic nut seeds using ESTs, but they have provided limited information on the accumulation of stored resources in the seeds. Methodology/Principal Findings We applied next-generation Illumina sequencing technology to analyze global gene expression profiles of developing physic nut seeds 14, 19, 25, 29, 35, 41, and 45 days after pollination (DAP). The acquired profiles reveal the key genes, and their expression timeframes, involved in major metabolic processes including: carbon flow, starch metabolism, and synthesis of storage lipids and proteins in the developing seeds. The main period of storage reserves synthesis in the seeds appears to be 29–41 DAP, and the fatty acid composition of the developing seeds is consistent with relative expression levels of different isoforms of acyl-ACP thioesterase and fatty acid desaturase genes. Several transcription factor genes whose expression coincides with storage reserve deposition correspond to those known to regulate the process in Arabidopsis. Conclusions/Significance The results will facilitate searches for genes that influence de novo lipid synthesis, accumulation and their regulatory networks in developing physic nut seeds, and other oil seeds. Thus, they will be helpful in attempts to modify these plants for efficient biofuel production. PMID:22574177

Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome.

PubMed

Tothill, Richard W; Tinker, Anna V; George, Joshy; Brown, Robert; Fox, Stephen B; Lade, Stephen; Johnson, Daryl S; Trivett, Melanie K; Etemadmoghadam, Dariush; Locandro, Bianca; Traficante, Nadia; Fereday, Sian; Hung, Jillian A; Chiew, Yoke-Eng; Haviv, Izhak; Gertig, Dorota; DeFazio, Anna; Bowtell, David D L

2008-08-15

The study aim to identify novel molecular subtypes of ovarian cancer by gene expression profiling with linkage to clinical and pathologic features. Microarray gene expression profiling was done on 285 serous and endometrioid tumors of the ovary, peritoneum, and fallopian tube. K-means clustering was applied to identify robust molecular subtypes. Statistical analysis identified differentially expressed genes, pathways, and gene ontologies. Laser capture microdissection, pathology review, and immunohistochemistry validated the array-based findings. Patient survival within k-means groups was evaluated using Cox proportional hazards models. Class prediction validated k-means groups in an independent dataset. A semisupervised survival analysis of the array data was used to compare against unsupervised clustering results. Optimal clustering of array data identified six molecular subtypes. Two subtypes represented predominantly serous low malignant potential and low-grade endometrioid subtypes, respectively. The remaining four subtypes represented higher grade and advanced stage cancers of serous and endometrioid morphology. A novel subtype of high-grade serous cancers reflected a mesenchymal cell type, characterized by overexpression of N-cadherin and P-cadherin and low expression of differentiation markers, including CA125 and MUC1. A poor prognosis subtype was defined by a reactive stroma gene expression signature, correlating with extensive desmoplasia in such samples. A similar poor prognosis signature could be found using a semisupervised analysis. Each subtype displayed distinct levels and patterns of immune cell infiltration. Class prediction identified similar subtypes in an independent ovarian dataset with similar prognostic trends. Gene expression profiling identified molecular subtypes of ovarian cancer of biological and clinical importance.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

PubMed Central

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

PubMed

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

sscMap: an extensible Java application for connecting small-molecule drugs using gene-expression signatures.

PubMed

Zhang, Shu-Dong; Gant, Timothy W

2009-07-31

Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap.

Genome-wide expression profiling in pediatric septic shock

PubMed Central

Wong, Hector R.

2013-01-01

For nearly a decade, our research group has had the privilege of developing and mining a multi-center, microarray-based, genome-wide expression database of critically ill children (≤ 10 years of age) with septic shock. Using bioinformatic and systems biology approaches, the expression data generated through this discovery-oriented, exploratory approach have been leveraged for a variety of objectives, which will be reviewed. Fundamental observations include wide spread repression of gene programs corresponding to the adaptive immune system, and biologically significant differential patterns of gene expression across developmental age groups. The data have also identified gene expression-based subclasses of pediatric septic shock having clinically relevant phenotypic differences. The data have also been leveraged for the discovery of novel therapeutic targets, and for the discovery and development of novel stratification and diagnostic biomarkers. Almost a decade of genome-wide expression profiling in pediatric septic shock is now demonstrating tangible results. The studies have progressed from an initial discovery-oriented and exploratory phase, to a new phase where the data are being translated and applied to address several areas of clinical need. PMID:23329198

Unsupervised Outlier Profile Analysis

PubMed Central

Ghosh, Debashis; Li, Song

2014-01-01

In much of the analysis of high-throughput genomic data, “interesting” genes have been selected based on assessment of differential expression between two groups or generalizations thereof. Most of the literature focuses on changes in mean expression or the entire distribution. In this article, we explore the use of C(α) tests, which have been applied in other genomic data settings. Their use for the outlier expression problem, in particular with continuous data, is problematic but nevertheless motivates new statistics that give an unsupervised analog to previously developed outlier profile analysis approaches. Some simulation studies are used to evaluate the proposal. A bivariate extension is described that can accommodate data from two platforms on matched samples. The proposed methods are applied to data from a prostate cancer study. PMID:25452686

Reprogramming Methods Do Not Affect Gene Expression Profile of Human Induced Pluripotent Stem Cells.

PubMed

Trevisan, Marta; Desole, Giovanna; Costanzi, Giulia; Lavezzo, Enrico; Palù, Giorgio; Barzon, Luisa

2017-01-20

Induced pluripotent stem cells (iPSCs) are pluripotent cells derived from adult somatic cells. After the pioneering work by Yamanaka, who first generated iPSCs by retroviral transduction of four reprogramming factors, several alternative methods to obtain iPSCs have been developed in order to increase the yield and safety of the process. However, the question remains open on whether the different reprogramming methods can influence the pluripotency features of the derived lines. In this study, three different strategies, based on retroviral vectors, episomal vectors, and Sendai virus vectors, were applied to derive iPSCs from human fibroblasts. The reprogramming efficiency of the methods based on episomal and Sendai virus vectors was higher than that of the retroviral vector-based approach. All human iPSC clones derived with the different methods showed the typical features of pluripotent stem cells, including the expression of alkaline phosphatase and stemness maker genes, and could give rise to the three germ layer derivatives upon embryoid bodies assay. Microarray analysis confirmed the presence of typical stem cell gene expression profiles in all iPSC clones and did not identify any significant difference among reprogramming methods. In conclusion, the use of different reprogramming methods is equivalent and does not affect gene expression profile of the derived human iPSCs.

Gene expression profiles in liver of mouse after chronic exposure to drinking water.

PubMed

Wu, Bing; Zhang, Yan; Zhao, Dayong; Zhang, Xuxiang; Kong, Zhiming; Cheng, Shupei

2009-10-01

cDNA micorarray approach was applied to hepatic transcriptional profile analysis in male mouse (Mus musculus, ICR) to assess the potential health effects of drinking water in Nanjing, China. Mice were treated with continuous exposure to drinking water for 90 days. Hepatic gene expression was analyzed with Affymetrix Mouse Genome 430A 2.0 arrays, and pathway analysis was carried out by Molecule Annotation System 2.0 and KEGG pathway database. A total of 836 genes were found to be significantly altered (1.5-fold, P < or = 0.05), including 294 up-regulated genes and 542 down-regulated genes. According to biological pathway analysis, drinking water exposure resulted in aberration of gene expression and biological pathways linked to xenobiotic metabolism, signal transduction, cell cycle and oxidative stress response. Further, deregulation of several genes associated with carcinogenesis or tumor progression including Ccnd1, Egfr, Map2k3, Mcm2, Orc2l and Smad2 was observed. Although transcription changes in identified genes are unlikely to be used as a sole indicator of adverse health effects, the results of this study could enhance our understanding of early toxic effects of drinking water exposure and support future studies on drinking water safety.

A method to identify differential expression profiles of time-course gene data with Fourier transformation.

PubMed

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.

Gene expression inference with deep learning.

PubMed

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

PubMed Central

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

Early diffusion of gene expression profiling in breast cancer patients associated with areas of high income inequality.

PubMed

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.

Joint mapping of genes and conditions via multidimensional unfolding analysis

PubMed Central

Van Deun, Katrijn; Marchal, Kathleen; Heiser, Willem J; Engelen, Kristof; Van Mechelen, Iven

2007-01-01

Background Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding. Results We present a novel algorithm for multidimensional unfolding that overcomes both general problems and problems that are specific for the analysis of gene expression data sets. Applying the algorithm to two publicly available microarray compendia illustrates its power as a tool for exploratory data analysis: The unfolding analysis of a first data set resulted in a two-dimensional representation which clearly reveals temporal regulation patterns for the genes and a meaningful structure for the time points, while the analysis of a second data set showed the algorithm's ability to go beyond a mere identification of those genes that discriminate between different patient or tissue types. Conclusion Multidimensional unfolding offers a useful tool for preliminary explorations of microarray data: By relying on an easy-to-grasp low-dimensional geometric framework, relations among genes, among conditions and between genes and conditions are simultaneously represented in an accessible way which may reveal interesting patterns in the data. An additional advantage of the method is that it can be applied to the raw data without necessitating the choice of suitable genewise transformations of the data. PMID:17550582

Predicting Gene Expression Level from Relative Codon Usage Bias: An Application to Escherichia coli Genome

PubMed Central

Roymondal, Uttam; Das, Shibsankar; Sahoo, Satyabrata

2009-01-01

We present an expression measure of a gene, devised to predict the level of gene expression from relative codon bias (RCB). There are a number of measures currently in use that quantify codon usage in genes. Based on the hypothesis that gene expressivity and codon composition is strongly correlated, RCB has been defined to provide an intuitively meaningful measure of an extent of the codon preference in a gene. We outline a simple approach to assess the strength of RCB (RCBS) in genes as a guide to their likely expression levels and illustrate this with an analysis of Escherichia coli (E. coli) genome. Our efforts to quantitatively predict gene expression levels in E. coli met with a high level of success. Surprisingly, we observe a strong correlation between RCBS and protein length indicating natural selection in favour of the shorter genes to be expressed at higher level. The agreement of our result with high protein abundances, microarray data and radioactive data demonstrates that the genomic expression profile available in our method can be applied in a meaningful way to the study of cell physiology and also for more detailed studies of particular genes of interest. PMID:19131380

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

PubMed

Feltus, F Alex

2014-06-01

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Transcriptional network inference from functional similarity and expression data: a global supervised approach.

PubMed

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.

Complexity of Gene Expression Evolution after Duplication: Protein Dosage Rebalancing

PubMed Central

Rogozin, Igor B.

2014-01-01

Ongoing debates about functional importance of gene duplications have been recently intensified by a heated discussion of the “ortholog conjecture” (OC). Under the OC, which is central to functional annotation of genomes, orthologous genes are functionally more similar than paralogous genes at the same level of sequence divergence. However, a recent study challenged the OC by reporting a greater functional similarity, in terms of gene ontology (GO) annotations and expression profiles, among within-species paralogs compared to orthologs. These findings were taken to indicate that functional similarity of homologous genes is primarily determined by the cellular context of the genes, rather than evolutionary history. Subsequent studies suggested that the OC appears to be generally valid when applied to mammalian evolution but the complete picture of evolution of gene expression also has to incorporate lineage-specific aspects of paralogy. The observed complexity of gene expression evolution after duplication can be explained through selection for gene dosage effect combined with the duplication-degeneration-complementation model. This paper discusses expression divergence of recent duplications occurring before functional divergence of proteins encoded by duplicate genes. PMID:25197576

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

PubMed Central

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

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

PubMed

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.

Discovering functions of unannotated genes from a transcriptome survey of wild fungal isolates.

PubMed

Ellison, Christopher E; Kowbel, David; Glass, N Louise; Taylor, John W; Brem, Rachel B

2014-04-01

Most fungal genomes are poorly annotated, and many fungal traits of industrial and biomedical relevance are not well suited to classical genetic screens. Assigning genes to phenotypes on a genomic scale thus remains an urgent need in the field. We developed an approach to infer gene function from expression profiles of wild fungal isolates, and we applied our strategy to the filamentous fungus Neurospora crassa. Using transcriptome measurements in 70 strains from two well-defined clades of this microbe, we first identified 2,247 cases in which the expression of an unannotated gene rose and fell across N. crassa strains in parallel with the expression of well-characterized genes. We then used image analysis of hyphal morphologies, quantitative growth assays, and expression profiling to test the functions of four genes predicted from our population analyses. The results revealed two factors that influenced regulation of metabolism of nonpreferred carbon and nitrogen sources, a gene that governed hyphal architecture, and a gene that mediated amino acid starvation resistance. These findings validate the power of our population-transcriptomic approach for inference of novel gene function, and we suggest that this strategy will be of broad utility for genome-scale annotation in many fungal systems. IMPORTANCE Some fungal species cause deadly infections in humans or crop plants, and other fungi are workhorses of industrial chemistry, including the production of biofuels. Advances in medical and industrial mycology require an understanding of the genes that control fungal traits. We developed a method to infer functions of uncharacterized genes by observing correlated expression of their mRNAs with those of known genes across wild fungal isolates. We applied this strategy to a filamentous fungus and predicted functions for thousands of unknown genes. In four cases, we experimentally validated the predictions from our method, discovering novel genes involved in the metabolism of nutrient sources relevant for biofuel production, as well as colony morphology and starvation resistance. Our strategy is straightforward, inexpensive, and applicable for predicting gene function in many fungal species.

L1000CDS2: LINCS L1000 characteristic direction signatures search engine.

PubMed

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.

Digital sorting of complex tissues for cell type-specific gene expression profiles.

PubMed

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.

A method to identify differential expression profiles of time-course gene data with Fourier transformation

PubMed Central

2013-01-01

Background 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. Results 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. Conclusions 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. PMID:24134721

Surviving in a toxic world: transcriptomics and gene expression profiling in response to environmental pollution in the critically endangered European eel.

PubMed

Pujolar, Jose Martin; Marino, Ilaria A M; Milan, Massimo; Coppe, Alessandro; Maes, Gregory E; Capoccioni, Fabrizio; Ciccotti, Eleonora; Bervoets, Lieven; Covaci, Adrian; Belpaire, Claude; Cramb, Gordon; Patarnello, Tomaso; Bargelloni, Luca; Bortoluzzi, Stefania; Zane, Lorenzo

2012-09-25

Genomic and transcriptomic approaches have the potential for unveiling the genome-wide response to environmental perturbations. The abundance of the catadromous European eel (Anguilla anguilla) stock has been declining since the 1980s probably due to a combination of anthropogenic and climatic factors. In this paper, we explore the transcriptomic dynamics between individuals from high (river Tiber, Italy) and low pollution (lake Bolsena, Italy) environments, which were measured for 36 PCBs, several organochlorine pesticides and brominated flame retardants and nine metals. To this end, we first (i) updated the European eel transcriptome using deep sequencing data with a total of 640,040 reads assembled into 44,896 contigs (Eeelbase release 2.0), and (ii) developed a transcriptomic platform for global gene expression profiling in the critically endangered European eel of about 15,000 annotated contigs, which was applied to detect differentially expressed genes between polluted sites. Several detoxification genes related to metabolism of pollutants were upregulated in the highly polluted site, including genes that take part in phase I of the xenobiotic metabolism (CYP3A), phase II (glutathione-S-transferase) and oxidative stress (glutathione peroxidase). In addition, key genes in the mitochondrial respiratory chain and oxidative phosphorylation were down-regulated at the Tiber site relative to the Bolsena site. Together with the induced high expression of detoxification genes, the suggested lowered expression of genes supposedly involved in metabolism suggests that pollution may also be associated with decreased respiratory and energy production.

Uncovering Hidden Layers of Cell Cycle Regulation through Integrative Multi-omic Analysis

PubMed Central

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

Construction of diagnosis system and gene regulatory networks based on microarray analysis.

PubMed

Hong, Chun-Fu; Chen, Ying-Chen; Chen, Wei-Chun; Tu, Keng-Chang; Tsai, Meng-Hsiun; Chan, Yung-Kuan; Yu, Shyr Shen

2018-05-01

A microarray analysis generally contains expression data of thousands of genes, but most of them are irrelevant to the disease of interest, making analyzing the genes concerning specific diseases complicated. Therefore, filtering out a few essential genes as well as their regulatory networks is critical, and a disease can be easily diagnosed just depending on the expression profiles of a few critical genes. In this study, a target gene screening (TGS) system, which is a microarray-based information system that integrates F-statistics, pattern recognition matching, a two-layer K-means classifier, a Parameter Detection Genetic Algorithm (PDGA), a genetic-based gene selector (GBG selector) and the association rule, was developed to screen out a small subset of genes that can discriminate malignant stages of cancers. During the first stage, F-statistic, pattern recognition matching, and a two-layer K-means classifier were applied in the system to filter out the 20 critical genes most relevant to ovarian cancer from 9600 genes, and the PDGA was used to decide the fittest values of the parameters for these critical genes. Among the 20 critical genes, 15 are associated with cancer progression. In the second stage, we further employed a GBG selector and the association rule to screen out seven target gene sets, each with only four to six genes, and each of which can precisely identify the malignancy stage of ovarian cancer based on their expression profiles. We further deduced the gene regulatory networks of the 20 critical genes by applying the Pearson correlation coefficient to evaluate the correlationship between the expression of each gene at the same stages and at different stages. Correlationships between gene pairs were calculated, and then, three regulatory networks were deduced. Their correlationships were further confirmed by the Ingenuity pathway analysis. The prognostic significances of the genes identified via regulatory networks were examined using online tools, and most represented biomarker candidates. In summary, our proposed system provides a new strategy to identify critical genes or biomarkers, as well as their regulatory networks, from microarray data. Copyright © 2018. Published by Elsevier Inc.

Microarray analysis of laser capture microdissected-anulus cells from the human intervertebral disc.

PubMed

Gruber, Helen E; Mougeot, Jean-Luc; Hoelscher, Gretchen; Ingram, Jane A; Hanley, Edward N

2007-05-15

Five Thompson Grade I/II discs (Group 1), 7 Grade III discs (Group 2), and 3 Grade IV discs (Group IV) were studied here in a project approved by the authors' Human Subjects Institutional Review Board. Our objective was to use laser capture microdissection (LCM) to harvest cells from the human anulus and to derive gene expression profiles using microarray analysis. Appropriate gene expression is essential in the intervertebral disc for maintenance of extracellular matrix (ECM), ECM remodeling, and maintenance of a viable disc cell population. During disc degeneration, cell numbers drop, making gene expression studies challenging. LCM was used to harvest cells from paraffin-embedded sections of human anulus tissue. Gene profiling used Affymetrix GeneChip Human X3P arrays. ANOVA and SAM permutation analysis were applied to dCHIP normalized, filtered, and log-transformed gene expression data ( approximately 33,500 probes), and data analyzed to identify genes that were significantly differentially expressed between the 3 groups. We identified 47 genes that were significantly differentially expressed between the 3 groups (P < 0.001 and lowest q values). Compared with the healthiest discs (Grade I/II), 13 genes were up-regulated and 19 down-regulated in both the Grade III and the Grade IV discs. Genes with biologic significance regulated during degeneration involved cell senescence, low cell division rates, hypoxia-related genes, heat-shock protein 70 interacting protein, neuropilin 2, and interleukin-23p19 (interleukin-12 family). Results expand our understanding of disc aging and degeneration and show that LCM is a valuable technique that can be used to collect mRNA amounts adequate for microarray analysis from the sparse cell population of the human anulus.

Storage time does not modify the gene expression profile of cryopreserved human metaphase II oocytes.

PubMed

Stigliani, Sara; Moretti, Stefano; Anserini, Paola; Casciano, Ida; Venturini, Pier Luigi; Scaruffi, Paola

2015-11-01

Does storage time have any impact on the transcriptome of slowly frozen cryopreserved human metaphase II (MII) oocytes? The length of cryostorage has no effect on the gene expression profile of human MII oocytes. Oocyte cryopreservation is a widely used technique in IVF for storage of surplus oocytes, as well as for fertility preservation (i.e. women undergoing gonadotoxic therapies) and oocyte donation programs. Although cryopreservation has negative impacts on oocyte physiology and it is associated with decrease of transcripts, no experimental data about the effect of storage time on the oocyte molecular profile are available to date. This study included 27 women, ≤38 years aged, without any ovarian pathology, undergoing IVF treatment. Surplus MII oocytes were donated after written informed consent. A total of 31 non-cryopreserved oocytes and 68 surviving slow-frozen/rapid-thawed oocytes (32 oocytes cryostored for 3 years and 36 cryostored for 6 years) were analyzed. Pools of ≈10 oocytes for each group were prepared. Total RNA was extracted from each pool, amplified, labeled and hybridized on oligonucleotide microarrays. Analyses were performed by R software using the limma package. Comparison of gene expression profiles between surviving thawed oocytes after 3 and 6 years of storage in liquid nitrogen found no differently expressed genes. The expression profiles of cryopreserved MII oocytes significantly differed from those of non-cryopreserved oocytes in 107 probe sets corresponding to 73 down-regulated and 29 up-regulated unique transcripts. Gene Ontology analysis by DAVID bioinformatics resource disclosed that cryopreservation deregulates genes involved in oocyte function and early embryo development, such as chromosome organization, RNA splicing and processing, cell cycle, cellular response to DNA damage and to stress, DNA repair, calcium ion binding, malate dehydrogenase activity and mitochondrial activity. Among the probes significantly up-regulated in cryopreserved oocytes, two corresponded to ovary-specific expressed large intergenic noncoding (linc)RNAs. Data validation in a larger cohort of samples would be beneficial, although we applied stringent criteria for gene selection (fold-change >3 or <1/3 and FDR < 0.1). Further research should be undertaken to verify experimentally that the length of cryostorage has no effect on gene expression profile of vitrified/warmed MII oocytes, as well as to include in analyses 'older' frozen oocytes. Confirmation that the length of storage does not alter the gene expression profile of frozen oocytes is noteworthy for the safety issue of long-term oocyte banking, i.e. fertility preservation, gamete donation. This study was supported by a grant of the Italian Ministry of Health (CCM 2012) and by Ferring Pharmaceutical company. The authors have no conflicts of interest to declare. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

Markers of epithelial-to-mesenchymal transition reflect tumor biology according to patient age and Gleason score in prostate cancer

PubMed Central

Jędroszka, Dorota; Hamouz, Raneem; Górniak, Karolina; Bednarek, Andrzej K.

2017-01-01

Introduction Prostate carcinoma (PRAD) is one of the most frequently diagnosed malignancies amongst men worldwide. It is well-known that androgen receptor (AR) plays a pivotal role in a vast majority of prostate tumors. However, recent evidence emerged stating that estrogen receptors (ERs) may also contribute to prostate tumor development. Moreover, progression and aggressiveness of prostate cancer may be associated with differential expression genes of epithelial-to-mesenchymal transition (EMT). Therefore we aimed to assess the significance of receptors status as well as EMT marker genes expression among PRAD patients in accordance to their age and Gleason score. Materials and methods We analyzed TCGA gene expression profiles of 497 prostate tumor samples according to 43 genes involved in EMT and 3 hormone receptor genes (AR, ESR1, ESR2) as well as clinical characteristic of cancer patients. Then patients were divided into four groups according to their age and 5 groups according to Gleason score. Next, we evaluated PRAD samples according to relationship between the set of variables in different combinations and compared differential expression in subsequent groups of patients. The analysis was applied using R packages: FactoMineR, gplots, RColorBrewer and NMF. Results MFA analysis resulted in distinct grouping of PRAD patients into four age categories according to expression level of AR, ESR1 and ESR2 with the most distinct group of age less than 50 years old. Further investigations indicated opposite expression profiles of EMT markers between different age groups as well as strong association of EMT gene expression with Gleason score. We found that depending on age of prostate cancer patients and Gleason score EMT genes with distinctly altered expression are: KRT18, KRT19, MUC1 and COL4A1, CTNNB1, SNAI2, ZEB1 and MMP3. Conclusions Our major observation is that prostate cancer from patients under 50 years old compared to older ones has entirely different EMT gene expression profiles showing potentially more aggressive invasive phenotype, despite Gleason score classification. PMID:29206234

Markers of epithelial-to-mesenchymal transition reflect tumor biology according to patient age and Gleason score in prostate cancer.

PubMed

Jędroszka, Dorota; Orzechowska, Magdalena; Hamouz, Raneem; Górniak, Karolina; Bednarek, Andrzej K

2017-01-01

Prostate carcinoma (PRAD) is one of the most frequently diagnosed malignancies amongst men worldwide. It is well-known that androgen receptor (AR) plays a pivotal role in a vast majority of prostate tumors. However, recent evidence emerged stating that estrogen receptors (ERs) may also contribute to prostate tumor development. Moreover, progression and aggressiveness of prostate cancer may be associated with differential expression genes of epithelial-to-mesenchymal transition (EMT). Therefore we aimed to assess the significance of receptors status as well as EMT marker genes expression among PRAD patients in accordance to their age and Gleason score. We analyzed TCGA gene expression profiles of 497 prostate tumor samples according to 43 genes involved in EMT and 3 hormone receptor genes (AR, ESR1, ESR2) as well as clinical characteristic of cancer patients. Then patients were divided into four groups according to their age and 5 groups according to Gleason score. Next, we evaluated PRAD samples according to relationship between the set of variables in different combinations and compared differential expression in subsequent groups of patients. The analysis was applied using R packages: FactoMineR, gplots, RColorBrewer and NMF. MFA analysis resulted in distinct grouping of PRAD patients into four age categories according to expression level of AR, ESR1 and ESR2 with the most distinct group of age less than 50 years old. Further investigations indicated opposite expression profiles of EMT markers between different age groups as well as strong association of EMT gene expression with Gleason score. We found that depending on age of prostate cancer patients and Gleason score EMT genes with distinctly altered expression are: KRT18, KRT19, MUC1 and COL4A1, CTNNB1, SNAI2, ZEB1 and MMP3. Our major observation is that prostate cancer from patients under 50 years old compared to older ones has entirely different EMT gene expression profiles showing potentially more aggressive invasive phenotype, despite Gleason score classification.

Variation-preserving normalization unveils blind spots in gene expression profiling

PubMed Central

Roca, Carlos P.; Gomes, Susana I. L.; Amorim, Mónica J. B.; Scott-Fordsmand, Janeck J.

2017-01-01

RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the normalization of gene expression levels, which is currently performed following the implicit assumption that most genes are not differentially expressed. Here, we present a mathematical approach to normalization that makes no assumption of this sort. We have found that variation in gene expression is much larger than currently believed, and that it can be measured with available assays. Our results also explain, at least partially, the reproducibility problems encountered in transcriptomics studies. We expect that this improvement in detection will help efforts to realize the full potential of gene expression profiling, especially in analyses of cellular processes involving complex modulations of gene expression. PMID:28276435

Risk stratification in myelodysplastic syndromes: is there a role for gene expression profiling?

PubMed

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.

Technical variables in high-throughput miRNA expression profiling: much work remains to be done.

PubMed

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.

Analysis of high-throughput biological data using their rank values.

PubMed

Dembélé, Doulaye

2018-01-01

High-throughput biological technologies are routinely used to generate gene expression profiling or cytogenetics data. To achieve high performance, methods available in the literature become more specialized and often require high computational resources. Here, we propose a new versatile method based on the data-ordering rank values. We use linear algebra, the Perron-Frobenius theorem and also extend a method presented earlier for searching differentially expressed genes for the detection of recurrent copy number aberration. A result derived from the proposed method is a one-sample Student's t-test based on rank values. The proposed method is to our knowledge the only that applies to gene expression profiling and to cytogenetics data sets. This new method is fast, deterministic, and requires a low computational load. Probabilities are associated with genes to allow a statistically significant subset selection in the data set. Stability scores are also introduced as quality parameters. The performance and comparative analyses were carried out using real data sets. The proposed method can be accessed through an R package available from the CRAN (Comprehensive R Archive Network) website: https://cran.r-project.org/web/packages/fcros .

Molecular profiles of pre- and postoperative breast cancer tumours reveal differentially expressed genes.

PubMed

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.

Molecular Profiles of Pre- and Postoperative Breast Cancer Tumours Reveal Differentially Expressed Genes

PubMed Central

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

Neighboring Genes Show Correlated Evolution in Gene Expression

PubMed Central

Ghanbarian, Avazeh T.; Hurst, Laurence D.

2015-01-01

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

The effects of administration of the Lactobacillus gasseri strain CP2305 on quality of life, clinical symptoms and changes in gene expression in patients with irritable bowel syndrome.

PubMed

Nobutani, K; Sawada, D; Fujiwara, S; Kuwano, Y; Nishida, K; Nakayama, J; Kutsumi, H; Azuma, T; Rokutan, K

2017-01-01

To clarify the effects of Lactobacillus gasseri CP2305 (CP2305) on quality of life and clinical symptoms and its functional mechanisms in patients with irritable bowel syndrome (IBS). After the patients were administered CP2305 daily for 4 weeks, the IBS-severity index score was significantly improved compared with that of the placebo group, and this improvement was accompanied by a reduction in health-related worry and changes in intestinal microbiota. The gene expression profiling of the peripheral blood leucocytes showed that CP2305 treatment significantly up-regulated genes related to eukaryotic initiation factor 2 (EIF2) signalling. Eighty-two genes were down-regulated in IBS patients compared with healthy controls. The expression of 23 of these genes exhibited a CP2305-dependent increase associated with an improvement in IBS severity. The majority of the restored genes were related to EIF2 signalling. CP2305 administration is a potential candidate therapeutic option for patients with IBS. Although probiotics have been proposed to benefit IBS patients, objective clinical evidence and elucidation of the functional mechanism remain insufficient. Our study demonstrated that CP2305 administration beneficially influences IBS patients in both subjective and objective evaluations, and gene expression profiling provided insights into the functional mechanism. © 2016 The Society for Applied Microbiology.

Structure-related clustering of gene expression fingerprints of thp-1 cells exposed to smaller polycyclic aromatic hydrocarbons.

PubMed

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.

Gene Expression Profiling Predicts the Development of Oral Cancer

PubMed Central

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

RNA-Stabilized Whole Blood Samples but Not Peripheral Blood Mononuclear Cells Can Be Stored for Prolonged Time Periods Prior to Transcriptome Analysis

PubMed Central

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

Analysis of the Human Prostate-Specific Proteome Defined by Transcriptomics and Antibody-Based Profiling Identifies TMEM79 and ACOXL as Two Putative, Diagnostic Markers in Prostate Cancer

PubMed Central

O'Hurley, Gillian; Busch, Christer; Fagerberg, Linn; Hallström, Björn M.; Stadler, Charlotte; Tolf, Anna; Lundberg, Emma; Schwenk, Jochen M.; Jirström, Karin; Bjartell, Anders; Gallagher, William M.; Uhlén, Mathias; Pontén, Fredrik

2015-01-01

To better understand prostate function and disease, it is important to define and explore the molecular constituents that signify the prostate gland. The aim of this study was to define the prostate specific transcriptome and proteome, in comparison to 26 other human tissues. Deep sequencing of mRNA (RNA-seq) and immunohistochemistry-based protein profiling were combined to identify prostate specific gene expression patterns and to explore tissue biomarkers for potential clinical use in prostate cancer diagnostics. We identified 203 genes with elevated expression in the prostate, 22 of which showed more than five-fold higher expression levels compared to all other tissue types. In addition to previously well-known proteins we identified two poorly characterized proteins, TMEM79 and ACOXL, with potential to differentiate between benign and cancerous prostatic glands in tissue biopsies. In conclusion, we have applied a genome-wide analysis to identify the prostate specific proteome using transcriptomics and antibody-based protein profiling to identify genes with elevated expression in the prostate. Our data provides a starting point for further functional studies to explore the molecular repertoire of normal and diseased prostate including potential prostate cancer markers such as TMEM79 and ACOXL. PMID:26237329

iPcc: a novel feature extraction method for accurate disease class discovery and prediction

PubMed Central

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

Gene expression profiles in chondrosarcoma cells subjected to cyclic stretching and hydrostatic pressure. A cDNA array study.

PubMed

Karjalainen, Hannu M; Sironen, Reijo K; Elo, Mika A; Kaarniranta, Kai; Takigawa, Masaharu; Helminen, Heikki J; Lammi, Mikko J

2003-01-01

Mechanical forces have a profound effect on cartilage tissue and chondrocyte metabolism. Strenuous loading inhibits the cellular metabolism, while optimal level of loading at correct frequency raises an anabolic response in chondrocytes. In this study, we used Atlas Human Cancer cDNA array to investigate mRNA expression profiles in human chondrosarcoma cells stretched 8% for 6 hours at a frequency of 0.5 Hz. In addition, cultures were exposed to continuous and cyclic (0.5 Hz) 5 MPa hydrostatic pressure. Cyclic stretch had a more profound effect on the gene expression profiles than 5 MPa hydrostatic pressure. Several genes involved with the regulation of cell cycle were increased in stretched cells, as well as mRNAs for PDGF-B, glucose-1-phosphate uridylyltransferase, Tiam1, cdc37 homolog, Gem, integrin alpha6, and matrix metalloproteinase-3. Among down-regulated genes were plakoglobin, TGF-alpha, retinoic acid receptor-alpha and Wnt8b. A smaller number of changes was detected after pressure treatments. Plakoglobin was increased under cyclic and continuous 5 MPa hydrostatic pressure, while mitogen-activated protein kinase-9, proliferating cell nuclear antigen, Rad6, CD9 antigen, integrins alphaE and beta8, and vimentin were decreased. Cyclic and continuous pressurization induces a number of specific changes. In conclusion, a different set of genes were affected by three different types of mechanical stimuli applied on chondrosarcoma cells.

Examining the Genetic Background of Porcine Muscle Growth and Development Based on Transcriptome and miRNAome Data.

PubMed

Ropka-Molik, Katarzyna; Pawlina-Tyszko, Klaudia; Żukowski, Kacper; Piórkowska, Katarzyna; Żak, Grzegorz; Gurgul, Artur; Derebecka, Natalia; Wesoły, Joanna

2018-04-16

Recently, selection in pigs has been focused on improving the lean meat content in carcasses; this focus has been most evident in breeds constituting a paternal component in breeding. Such sire-breeds are used to improve the meat quantity of cross-breed pig lines. However, even in one breed, a significant variation in the meatiness level can be observed. In the present study, the comprehensive analysis of genes and microRNA expression profiles in porcine muscle tissue was applied to identify the genetic background of meat content. The comparison was performed between whole gene expression and miRNA profiles of muscle tissue collected from two sire-line pig breeds (Pietrain, Hampshire). The RNA-seq approach allowed the identification of 627 and 416 differentially expressed genes (DEGs) between pig groups differing in terms of loin weight between Pietrain and Hampshire breeds, respectively. The comparison of miRNA profiles showed differential expression of 57 microRNAs for Hampshire and 34 miRNAs for Pietrain pigs. Next, 43 genes and 18 miRNAs were selected as differentially expressed in both breeds and potentially related to muscle development. According to Gene Ontology analysis, identified DEGs and microRNAs were involved in the regulation of the cell cycle, fatty acid biosynthesis and regulation of the actin cytoskeleton. The most deregulated pathways dependent on muscle mass were the Hippo signalling pathway connected with the TGF-β signalling pathway and controlling organ size via the regulation of ubiquitin-mediated proteolysis, cell proliferation and apoptosis. The identified target genes were also involved in pathways such as the FoxO signalling pathway, signalling pathways regulating pluripotency of stem cells and the PI3K-Akt signalling pathway. The obtained results indicate molecular mechanisms controlling porcine muscle growth and development. Identified genes ( SOX2 , SIRT1 , KLF4 , PAX6 and genes belonging to the transforming growth factor beta superfamily) could be considered candidate genes for determining muscle mass in pigs.

Dissecting modes of action of non-genotoxic carcinogens in primary mouse hepatocytes.

PubMed

Schaap, Mirjam M; Zwart, Edwin P; Wackers, Paul F K; Huijskens, Ilse; van de Water, Bob; Breit, Timo M; van Steeg, Harry; Jonker, Martijs J; Luijten, Mirjam

2012-11-01

Under REACH, the European Community Regulation on chemicals, the testing strategy for carcinogenicity is based on in vitro and in vivo genotoxicity assays. Given that non-genotoxic carcinogens are negative for genotoxicity and chronic bioassays are no longer regularly performed, this class of carcinogens will go undetected. Therefore, test systems detecting non-genotoxic carcinogens, or even better their modes of action, are required. Here, we investigated whether gene expression profiling in primary hepatocytes can be used to distinguish different modes of action of non-genotoxic carcinogens. For this, primary mouse hepatocytes were exposed to 16 non-genotoxic carcinogens with diverse modes of action. Upon profiling, pathway analysis was performed to obtain insight into the biological relevance of the observed changes in gene expression. Subsequently, both a supervised and an unsupervised comparison approach were applied to recognize the modes of action at the transcriptomic level. These analyses resulted in the detection of three of eight compound classes, that is, peroxisome proliferators, metalloids and skin tumor promotors. In conclusion, gene expression profiles in primary hepatocytes, at least in rodent hepatocytes, appear to be useful to detect some, certainly not all, modes of action of non-genotoxic carcinogens.

GTA: a game theoretic approach to identifying cancer subnetwork markers.

PubMed

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.

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data.

PubMed

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R; Del Río-Navarro, Blanca E; Mendoza-Vargas, Alfredo; Sánchez, Filiberto; Ochoa-Leyva, Adrian

2017-01-01

In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.

Gene expression profile differences in left and right liver lobes from mid-gestation fetal baboons: a cautionary tale

PubMed Central

Cox, Laura A; Schlabritz-Loutsevitch, Natalia; Hubbard, Gene B; Nijland, Mark J; McDonald, Thomas J; Nathanielsz, Peter W

2006-01-01

Interpretation of gene array data presents many potential pitfalls in adult tissues. Gene array techniques applied to fetal tissues present additional confounding pitfalls. The left lobe of the fetal liver is supplied with blood containing more oxygen than the right lobe. Since synthetic activity and cell function are oxygen dependent, we hypothesized major differences in mRNA expression between the fetal right and left liver lobes. Our aim was to demonstrate the need to evaluate RNA samples from both lobes. We performed whole genome expression profiling on left and right liver lobe RNA from six 90-day gestation baboon fetuses (term 180 days). Comparing right with left, we found 875 differentially expressed genes – 312 genes were up-regulated and 563 down-regulated. Pathways for damaged DNA binding, endonuclease activity, interleukin binding and receptor activity were up-regulated in right lobe; ontological pathways related to cell signalling, cell organization, cell biogenesis, development, intracellular transport, phospholipid metabolism, protein biosynthesis, protein localization, protein metabolism, translational regulation and vesicle mediated transport were down-regulated in right lobe. Molecular pathway analysis showed down-regulation of pathways related to heat shock protein binding, ion channel and transporter activities, oxygen binding and transporter activities, translation initiation and translation regulator activities. Genes involved in amino acid biosynthesis, lipid biosynthesis and oxygen transport were also differentially expressed. This is the first demonstration of RNA differences between the two lobes of the fetal liver. The data support the argument that a complete interpretation of gene expression in the developing liver requires data from both lobes. PMID:16484296

Comprehensive Genome-Wide Survey, Genomic Constitution and Expression Profiling of the NAC Transcription Factor Family in Foxtail Millet (Setaria italica L.)

PubMed Central

Puranik, Swati; Sahu, Pranav Pankaj; Mandal, Sambhu Nath; B., Venkata Suresh; Parida, Swarup Kumar; Prasad, Manoj

2013-01-01

The NAC proteins represent a major plant-specific transcription factor family that has established enormously diverse roles in various plant processes. Aided by the availability of complete genomes, several members of this family have been identified in Arabidopsis, rice, soybean and poplar. However, no comprehensive investigation has been presented for the recently sequenced, naturally stress tolerant crop, Setaria italica (foxtail millet) that is famed as a model crop for bioenergy research. In this study, we identified 147 putative NAC domain-encoding genes from foxtail millet by systematic sequence analysis and physically mapped them onto nine chromosomes. Genomic organization suggested that inter-chromosomal duplications may have been responsible for expansion of this gene family in foxtail millet. Phylogenetically, they were arranged into 11 distinct sub-families (I-XI), with duplicated genes fitting into one cluster and possessing conserved motif compositions. Comparative mapping with other grass species revealed some orthologous relationships and chromosomal rearrangements including duplication, inversion and deletion of genes. The evolutionary significance as duplication and divergence of NAC genes based on their amino acid substitution rates was understood. Expression profiling against various stresses and phytohormones provides novel insights into specific and/or overlapping expression patterns of SiNAC genes, which may be responsible for functional divergence among individual members in this crop. Further, we performed structure modeling and molecular simulation of a stress-responsive protein, SiNAC128, proffering an initial framework for understanding its molecular function. Taken together, this genome-wide identification and expression profiling unlocks new avenues for systematic functional analysis of novel NAC gene family candidates which may be applied for improvising stress adaption in plants. PMID:23691254

Comprehensive genome-wide survey, genomic constitution and expression profiling of the NAC transcription factor family in foxtail millet (Setaria italica L.).

PubMed

Puranik, Swati; Sahu, Pranav Pankaj; Mandal, Sambhu Nath; B, Venkata Suresh; Parida, Swarup Kumar; Prasad, Manoj

2013-01-01

The NAC proteins represent a major plant-specific transcription factor family that has established enormously diverse roles in various plant processes. Aided by the availability of complete genomes, several members of this family have been identified in Arabidopsis, rice, soybean and poplar. However, no comprehensive investigation has been presented for the recently sequenced, naturally stress tolerant crop, Setaria italica (foxtail millet) that is famed as a model crop for bioenergy research. In this study, we identified 147 putative NAC domain-encoding genes from foxtail millet by systematic sequence analysis and physically mapped them onto nine chromosomes. Genomic organization suggested that inter-chromosomal duplications may have been responsible for expansion of this gene family in foxtail millet. Phylogenetically, they were arranged into 11 distinct sub-families (I-XI), with duplicated genes fitting into one cluster and possessing conserved motif compositions. Comparative mapping with other grass species revealed some orthologous relationships and chromosomal rearrangements including duplication, inversion and deletion of genes. The evolutionary significance as duplication and divergence of NAC genes based on their amino acid substitution rates was understood. Expression profiling against various stresses and phytohormones provides novel insights into specific and/or overlapping expression patterns of SiNAC genes, which may be responsible for functional divergence among individual members in this crop. Further, we performed structure modeling and molecular simulation of a stress-responsive protein, SiNAC128, proffering an initial framework for understanding its molecular function. Taken together, this genome-wide identification and expression profiling unlocks new avenues for systematic functional analysis of novel NAC gene family candidates which may be applied for improvising stress adaption in plants.

Neighboring Genes Show Correlated Evolution in Gene Expression.

PubMed

Ghanbarian, Avazeh T; Hurst, Laurence D

2015-07-01

When considering the evolution of a gene's expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells.

PubMed

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.

The changes of gene expression profiling between segmental vitiligo, generalized vitiligo and healthy individual.

PubMed

Wang, Ping; Li, Yong; Nie, Huiqiong; Zhang, Xiaoyan; Shao, Qiongyan; Hou, Xiuli; Xu, Wen; Hong, Weisong; Xu, Aie

2016-10-01

Vitiligo is a common acquired depigmentation skin disease characterized by loss or dysfunction of melanocytes within the skin lesion, but its pathologenesis is far from lucid. The gene expression profiling of segmental vitiligo (SV) and generalized vitiligo (GV) need further investigation. To better understanding the common and distinct factors, especially in the view of gene expression profile, which were involved in the diseases development and maintenance of segmental vitiligo (SV) and generalized vitiligo (GV). Peripheral bloods were collected from SV, GV and healthy individual (HI), followed by leukocytes separation and total RNA extraction. The high-throughput whole genome expression microarrays were used to assay the gene expression profiles between HI, SV and GV. Bioinformatics tools were employed to annotated the biological function of differently expressed genes. Quantitative PCR assay was used to validate the gene expression of array. Compared to HI, 239 over-expressed genes and 175 down-expressed genes detected in SV, 688 over-expressed genes and 560 down-expressed genes were found in GV, following the criteria of log2 (fold change)≥0.585 and P value<0.05. In these differently expressed genes, 60 over-expressed genes and 60 down-expressed genes had similar tendency in SV and GV. Compared to SV, 223 genes were up regulated and 129 genes were down regulated in GV. In the SV with HI as control, the differently expressed genes were mainly involved in the adaptive immune response, cytokine-cytokine receptor interaction, chemokine signaling, focal adhesion and sphingolipid metabolism. The differently expressed genes between GV and HI were mainly involved in the innate immune, autophagy, apoptosis, melanocyte biology, ubiquitin mediated proteolysis and tyrosine metabolism, which was different from SV. While the differently expressed genes between SV and GV were mainly involved in the metabolism pathway of purine, pyrimidine, glycolysis and sphingolipid. Above results suggested that they not only shared part bio-process and signal pathway, but more important, they utilized different biological mechanism in their pathogenesis and maintenance. Our results provide a comprehensive view on the gene expression profiling change between SV and GV especially in the side of leukocytes, and may facilitate the future study on their molecular mechanism and theraputic targets. Copyright © 2016 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.

A gene expression resource generated by genome-wide lacZ profiling in the mouse

PubMed Central

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

Gene Expression Profiles of Chlamydophila pneumoniae during the Developmental Cycle and Iron Depletion–Mediated Persistence

PubMed Central

Mäurer, André P; Mehlitz, Adrian; Mollenkopf, Hans J; Meyer, Thomas F

2007-01-01

The obligate intracellular, gram-negative bacterium Chlamydophila pneumoniae (Cpn) has impact as a human pathogen. Little is known about changes in the Cpn transcriptome during its biphasic developmental cycle (the acute infection) and persistence. The latter stage has been linked to chronic diseases. To analyze Cpn CWL029 gene expression, we designed a pathogen-specific oligo microarray and optimized the extraction method for pathogen RNA. Throughout the acute infection, ratio expression profiles for each gene were generated using 48 h post infection as a reference. Based on these profiles, significantly expressed genes were separated into 12 expression clusters using self-organizing map clustering and manual sorting into the “early”, “mid”, “late”, and “tardy” cluster classes. The latter two were differentiated because the “tardy” class showed steadily increasing expression at the end of the cycle. The transcriptome of the Cpn elementary body (EB) and published EB proteomics data were compared to the cluster profile of the acute infection. We found an intriguing association between “late” genes and genes coding for EB proteins, whereas “tardy” genes were mainly associated with genes coding for EB mRNA. It has been published that iron depletion leads to Cpn persistence. We compared the gene expression profiles during iron depletion–mediated persistence with the expression clusters of the acute infection. This led to the finding that establishment of iron depletion–mediated persistence is more likely a mid-cycle arrest in development rather than a completely distinct gene expression pattern. Here, we describe the Cpn transcriptome during the acute infection, differentiating “late” genes, which correlate to EB proteins, and “tardy” genes, which lead to EB mRNA. Expression profiles during iron mediated–persistence led us to propose the hypothesis that the transcriptomic “clock” is arrested during acute mid-cycle. PMID:17590080

A metabolomics-based method for studying the effect of yfcC gene in Escherichia coli on metabolism.

PubMed

Wang, Xiyue; Xie, Yuping; Gao, Peng; Zhang, Sufang; Tan, Haidong; Yang, Fengxu; Lian, Rongwei; Tian, Jing; Xu, Guowang

2014-04-15

Metabolomics is a potent tool to assist in identifying the function of unknown genes through analysis of metabolite changes in the context of varied genetic backgrounds. However, the availability of a universal unbiased profiling analysis is still a big challenge. In this study, we report an optimized metabolic profiling method based on gas chromatography-mass spectrometry for Escherichia coli. It was found that physiological saline at -80°C could ensure satisfied metabolic quenching with less metabolite leakage. A solution of methanol/water (21:79, v/v) was proved to be efficient for intracellular metabolite extraction. This method was applied to investigate the metabolome difference among wild-type E. coli, its yfcC deletion, and overexpression mutants. Statistical and bioinformatic analysis of the metabolic profiling data indicated that the expression of yfcC potentially affected the metabolism of glyoxylate shunt. This finding was further validated by real-time quantitative polymerase chain reactions showing that expression of aceA and aceB, the key genes in glyoxylate shunt, was upregulated by yfcC. This study exemplifies the robustness of the proposed metabolic profiling analysis strategy and its potential roles in investigating unknown gene functions in view of metabolome difference. Copyright © 2014 Elsevier Inc. All rights reserved.

Expression Profiling-Based Identification of CO2-Responsive Genes Regulated by CCM1 Controlling a Carbon-Concentrating Mechanism in Chlamydomonas reinhardtii1

PubMed Central

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

cDNA microarray reveals the alterations of cytoskeleton-related genes in osteoblast under high magneto-gravitational environment.

PubMed

Qian, Airong; Di, Shengmeng; Gao, Xiang; Zhang, Wei; Tian, Zongcheng; Li, Jingbao; Hu, Lifang; Yang, Pengfei; Yin, Dachuan; Shang, Peng

2009-07-01

The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has been widely applied in many fields. In this study, a special designed superconducting magnet, which can produce three apparent gravity levels (0, 1, and 2 g), namely high magneto-gravitational environment (HMGE), was used to simulate space gravity environment. The effects of HMGE on osteoblast gene expression profile were investigated by microarray. Genes sensitive to diamagnetic levitation environment (0 g), gravity changes, and high magnetic field changes were sorted on the basis of typical cell functions. Cytoskeleton, as an intracellular load-bearing structure, plays an important role in gravity perception. Therefore, 13 cytoskeleton-related genes were chosen according to the results of microarray analysis, and the expressions of these genes were found to be altered under HMGE by real-time PCR. Based on the PCR results, the expressions of WASF2 (WAS protein family, member 2), WIPF1 (WAS/WASL interacting protein family, member 1), paxillin, and talin 1 were further identified by western blot assay. Results indicated that WASF2 and WIPF1 were more sensitive to altered gravity levels, and talin 1 and paxillin were sensitive to both magnetic field and gravity changes. Our findings demonstrated that HMGE can affect osteoblast gene expression profile and cytoskeleton-related genes expression. The identification of mechanosensitive genes may enhance our understandings to the mechanism of bone loss induced by microgravity and may provide some potential targets for preventing and treating bone loss or osteoporosis.

Surviving in a toxic world: transcriptomics and gene expression profiling in response to environmental pollution in the critically endangered European eel

PubMed Central

2012-01-01

Background Genomic and transcriptomic approaches have the potential for unveiling the genome-wide response to environmental perturbations. The abundance of the catadromous European eel (Anguilla anguilla) stock has been declining since the 1980s probably due to a combination of anthropogenic and climatic factors. In this paper, we explore the transcriptomic dynamics between individuals from high (river Tiber, Italy) and low pollution (lake Bolsena, Italy) environments, which were measured for 36 PCBs, several organochlorine pesticides and brominated flame retardants and nine metals. Results To this end, we first (i) updated the European eel transcriptome using deep sequencing data with a total of 640,040 reads assembled into 44,896 contigs (Eeelbase release 2.0), and (ii) developed a transcriptomic platform for global gene expression profiling in the critically endangered European eel of about 15,000 annotated contigs, which was applied to detect differentially expressed genes between polluted sites. Several detoxification genes related to metabolism of pollutants were upregulated in the highly polluted site, including genes that take part in phase I of the xenobiotic metabolism (CYP3A), phase II (glutathione-S-transferase) and oxidative stress (glutathione peroxidase). In addition, key genes in the mitochondrial respiratory chain and oxidative phosphorylation were down-regulated at the Tiber site relative to the Bolsena site. Conclusions Together with the induced high expression of detoxification genes, the suggested lowered expression of genes supposedly involved in metabolism suggests that pollution may also be associated with decreased respiratory and energy production. PMID:23009661

The Peripheral Whole Blood Transcriptome of Acute Pyelonephritis in Human Pregnancy

PubMed Central

Madan, Ichchha; Than, Nandor Gabor; Romero, Roberto; Chaemsaithong, Piya; Miranda, Jezid; Tarca, Adi L.; Bhatti, Gaurav; Draghici, Sorin; Yeo, Lami; Mazor, Moshe; Hassan, Sonia S.; Chaiworapongsa, Tinnakorn

2018-01-01

Objective Human pregnancy is characterized by activation of the innate immune response and suppression of adaptive immunity. The former is thought to provide protection against infection to the mother, and the latter, tolerance against paternal antigens expressed in fetal cells. Acute pyelonephritis is associated with an increased risk of acute respiratory distress syndrome and sepsis in pregnant (vs. nonpregnant) women. The objective of this study was to describe the gene expression profile (transcriptome) of maternal whole blood in acute pyelonephritis. Method A case-control study was conducted to include pregnant women with acute pyelonephritis (n=15) and women with a normal pregnancy (n=34). Affymetrix HG-U133 Plus 2.0 arrays (Affymetrix, Santa Clara, CA, USA) were used for gene expression profiling. A linear model was used to test the association between the presence of pyelonephritis and gene expression levels while controlling for white blood cell count and gestational age. A fold change of 1.5 was considered significant at a false discovery rate of 0.1. A subset of differentially expressed genes (n=56) was tested with real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) (cases, n=19; controls, n=59). Gene ontology and pathway analysis were applied. Results A total of 983 genes were differentially expressed in acute pyelonephritis: 457 were up-regulated and 526 were down-regulated. Significant enrichment of 300 biological processes and 63 molecular functions was found in pyelonephritis. Significantly impacted pathways in pyelonephritis included a) cytokine-cytokine receptor interaction; b) T-cell receptor signaling; c) Jak-STAT signaling; and d) complement and coagulation cascades. Of 56 genes tested by qRT-PCR, 48 (85.7%) had confirmation of differential expression. Conclusion This is the first study of the transcriptomic signature of whole blood in pregnant women with acute pyelonephritis. Acute infection during pregnancy is associated with the increased expression of genes involved in innate immunity and the decreased expression of genes involved in lymphocyte function. PMID:24293448

Gene expression studies of reference genes for quantitative real-time PCR: an overview in insects.

PubMed

Shakeel, Muhammad; Rodriguez, Alicia; Tahir, Urfa Bin; Jin, Fengliang

2018-02-01

Whenever gene expression is being examined, it is essential that a normalization process is carried out to eliminate non-biological variations. The use of reference genes, such as glyceraldehyde-3-phosphate dehydrogenase, actin, and ribosomal protein genes, is the usual method of choice for normalizing gene expression. Although reference genes are used to normalize target gene expression, a major problem is that the stability of these genes differs among tissues, developmental stages, species, and responses to abiotic factors. Therefore, the use and validation of multiple reference genes are required. This review discusses the reasons that why RT-qPCR has become the preferred method for validating results of gene expression profiles, the use of specific and non-specific dyes and the importance of use of primers and probes for qPCR as well as to discuss several statistical algorithms developed to help the validation of potential reference genes. The conflicts arising in the use of classical reference genes in gene normalization and their replacement with novel references are also discussed by citing the high stability and low stability of classical and novel reference genes under various biotic and abiotic experimental conditions by employing various methods applied for the reference genes amplification.

Microarray-based cancer prediction using soft computing approach.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2009-05-26

One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

Gene expression profiling in multiple myeloma--reporting of entities, risk, and targets in clinical routine.

PubMed

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.

Comparative prion disease gene expression profiling using the prion disease mimetic, cuprizone

PubMed Central

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

Medroxyprogesterone acetate-treated human, primary endometrial epithelial cells reveal unique gene expression signature linked to innate immunity and HIV-1 susceptibility.

PubMed

Woods, Matthew W; Zahoor, Muhammad Atif; Dizzell, Sara; Verschoor, Chris P; Kaushic, Charu

2018-01-01

Medroxyprogesterone acetate (MPA), a progestin-based hormonal contraceptive designed to mimic progesterone, has been linked to increased human immunodeficiency virus (HIV-1) susceptibility. Genital epithelial cells (GECs) form the mucosal lining of the female genital tract (FGT) and provide the first line of protection against HIV-1. The impact of endogenous sex hormones or MPA on the gene expression profile of GECs has not been comprehensively documented. Using microarray analysis, we characterized the transcriptional profile of primary endometrial epithelial cells grown in physiological levels of E2, P4, and MPA. Each hormone treatment altered the gene expression profile of GECs in a unique manner. Interestingly, although MPA is a progestogen, the gene expression profile induced by it was distinct from P4. MPA increased gene expression of genes related to inflammation and cholesterol synthesis linked to innate immunity and HIV-1 susceptibility. The analysis of gene expression profiles provides insights into the effects of sex hormones and MPA on GECs and allows us to posit possible mechanisms of the MPA-mediated increase in HIV-1 acquisition. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Gene expression profiles of Vibrio parahaemolyticus in the early stationary phase.

PubMed

Meng, L; Alter, T; Aho, T; Huehn, S

2015-09-01

Vibrio (V.) parahaemolyticus is an aquatic bacterium capable of causing foodborne gastroenteritis. In the environment or the food chain, V. parahaemolyticus cells are usually forced into the stationary phase, the common phase for bacterial survival in the environment. So far, little is known about whole genomic expression of V. parahaemolyticus in the early stationary phase compared with the exponential growth phase. We performed whole transcriptomic profiling of V. parahaemolyticus cells in both phases (exponential and early stationary phase). Our data showed in total that 172 genes were induced in early stationary phase, while 61 genes were repressed in early stationary phase compared with the exponential phase. Three functional categories showed stable gene expression in the early stationary phase. Eleven functional categories showed that up-regulation of genes was dominant over down-regulation in the early stationary phase. Although genes related to endogenous metabolism were repressed in the early stationary phase, massive regulation of gene expression occurred in the early stationary phase, indicating the expressed gene set of V. parahaemolyticus in the early stationary phase impacts environmental survival. Vibrio (V.) parahaemolyticus is one of the main bacterial causes of foodborne intestinal infections. This bacterium usually is forced into stationary phase in the environment, which includes, e.g. seafood. When bacteria are in stationary phase, physiological changes can lead to a resistance to many stresses, including physical and chemical challenges during food processing. To the best of our knowledge, highlighting the whole genome expression changes in the early stationary phase compared with exponential phase, as well as the investigation of physiological changes of V. parahaemolyticus such as the survival mechanism in the stationary phase has been the very first study in this field. © 2015 The Society for Applied Microbiology.

Gene expression profile predicting the response to anti-TNF treatment in patients with rheumatoid arthritis; analysis of GEO datasets.

PubMed

Kim, Tae-Hwan; Choi, Sung Jae; Lee, Young Ho; Song, Gwan Gyu; Ji, Jong Dae

2014-07-01

Anti-tumor necrosis factor (TNF) therapy is the treatment of choice for rheumatoid arthritis (RA) patients in whom standard disease-modifying anti-rheumatic drugs are ineffective. However, a substantial proportion of RA patients treated with anti-TNF agents do not show a significant clinical response. Therefore, biomarkers predicting response to anti-TNF agents are needed. Recently, gene expression profiling has been applied in research for developing such biomarkers. We compared gene expression profiles reported by previous studies dealing with the responsiveness of anti-TNF therapy in RA patients and attempted to identify differentially expressed genes (DEGs) that discriminated between responders and non-responders to anti-TNF therapy. We used microarray datasets available at the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO). This analysis included 6 studies and 5 sets of microarray data that used peripheral blood samples for identification of DEGs predicting response to anti-TNF therapy. We found little overlap in the DEGs that were highly ranked in each study. Three DEGs including IL2RB, SH2D2A and G0S2 appeared in more than 1 study. In addition, a meta-analysis designed to increase statistical power found one DEG, G0S2 by the Fisher's method. Our finding suggests the possibility that G0S2 plays as a biomarker to predict response to anti-TNF therapy in patients with rheumatoid arthritis. Further investigations based on larger studies are therefore needed to confirm the significance of G0S2 in predicting response to anti-TNF therapy. Copyright © 2014 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.

The synergistic effects of shear stress and cyclic hydrostatic pressure modulate chondrogenic induction of human mesenchymal stem cells.

PubMed

Hosseini, Motahare-Sadat; Tafazzoli-Shadpour, Mohammad; Haghighipour, Nooshin; Aghdami, Naser; Goodarzi, Alireza

2015-10-01

In this study, we examined chondrogenic regulation of 2 types of mesenchymal stem cells seeded on the bioengineered substrate in monolayer cultures under mechanically defined conditions to mimic the in vivo microenvironment of chondrocytes within articular cartilage tissues. Human adipose-derived mesenchymal stem cells (ASCs) and bone marrow mesenchymal stem cells (BSCs) were exposed to 0.2 Pa shear stress, 3 MPa cyclic hydrostatic pressure, and combined loading with different sequences on chemically designed medical-grade silicone rubber, while no soluble growth factors were added to the culture medium. The expression levels of chondrogenic-specific genes of SOX9, aggrecan, and type II collagen (Col II) were measured. Results were compared to those of cells treated by biological growth factor. Gene expression patterns were dependent on the loading regime. Moreover, the source of mesenchymal stem cells (adipose or bone marrow) was influential in gene expression. Overall, enhanced expression of chondrogenic markers was found through application of mechanical stimuli. The response was generally found to be significantly promoted when the 2 loading regimes were superimposed. Differentiation of ASCs was shown by a modest increase in gene expression profiles. In general, BSCs expressed higher levels of chondrogenic gene expression than ASCs after 3 weeks. A greater effect on Col II and SOX9 mRNA expression was observed when combined loadings were applied. Results may be applied in determining the proper loading sequence for obtaining functional target cells in cartilage engineering applications.

Influence of in vivo growth on human glioma cell line gene expression: Convergent profiles under orthotopic conditions

PubMed Central

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

Genes involved in host-parasite interactions can be revealed by their correlated expression.

PubMed

Reid, Adam James; Berriman, Matthew

2013-02-01

Molecular interactions between a parasite and its host are key to the ability of the parasite to enter the host and persist. Our understanding of the genes and proteins involved in these interactions is limited. To better understand these processes it would be advantageous to have a range of methods to predict pairs of genes involved in such interactions. Correlated gene expression profiles can be used to identify molecular interactions within a species. Here we have extended the concept to different species, showing that genes with correlated expression are more likely to encode proteins, which directly or indirectly participate in host-parasite interaction. We go on to examine our predictions of molecular interactions between the malaria parasite and both its mammalian host and insect vector. Our approach could be applied to study any interaction between species, for example, between a host and its parasites or pathogens, but also symbiotic and commensal pairings.

Approximate geodesic distances reveal biologically relevant structures in microarray data.

PubMed

Nilsson, Jens; Fioretos, Thoas; Höglund, Mattias; Fontes, Magnus

2004-04-12

Genome-wide gene expression measurements, as currently determined by the microarray technology, can be represented mathematically as points in a high-dimensional gene expression space. Genes interact with each other in regulatory networks, restricting the cellular gene expression profiles to a certain manifold, or surface, in gene expression space. To obtain knowledge about this manifold, various dimensionality reduction methods and distance metrics are used. For data points distributed on curved manifolds, a sensible distance measure would be the geodesic distance along the manifold. In this work, we examine whether an approximate geodesic distance measure captures biological similarities better than the traditionally used Euclidean distance. We computed approximate geodesic distances, determined by the Isomap algorithm, for one set of lymphoma and one set of lung cancer microarray samples. Compared with the ordinary Euclidean distance metric, this distance measure produced more instructive, biologically relevant, visualizations when applying multidimensional scaling. This suggests the Isomap algorithm as a promising tool for the interpretation of microarray data. Furthermore, the results demonstrate the benefit and importance of taking nonlinearities in gene expression data into account.

Functional Analyses of NSF1 in Wine Yeast Using Interconnected Correlation Clustering and Molecular Analyses

PubMed Central

Bessonov, Kyrylo; Walkey, Christopher J.; Shelp, Barry J.; van Vuuren, Hennie J. J.; Chiu, David; van der Merwe, George

2013-01-01

Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of correlation values related to gene expression profiles extracted from given microarray datasets. ICC can be applied to any microarray dataset and any target gene. We applied this method to microarray data generated from wine fermentations and selected NSF1, which encodes a C2H2 zinc finger-type transcription factor, as the target gene. The validity of the method was verified by accurate identifications of the previously known functional roles of NSF1. In addition, we identified and verified potential new functions for this gene; specifically, NSF1 is a negative regulator for the expression of sulfur metabolism genes, the nuclear localization of Nsf1 protein (Nsf1p) is controlled in a sulfur-dependent manner, and the transcription of NSF1 is regulated by Met4p, an important transcriptional activator of sulfur metabolism genes. The inter-disciplinary approach adopted here highlighted the accuracy and relevancy of the ICC method in mining for novel gene functions using complex microarray datasets with a limited number of samples. PMID:24130853

Gene Expression Profiling of Peripheral Blood From Kidney Transplant Recipients for the Early Detection of Digestive System Cancer.

PubMed

Kusaka, M; Okamoto, M; Takenaka, M; Sasaki, H; Fukami, N; Kataoka, K; Ito, T; Kenmochi, T; Hoshinaga, K; Shiroki, R

2017-06-01

Kidney transplant recipients are at increased risk of developing cancer in comparison with the general population. To effectively manage post-transplantation malignancies, it is essential to proactively monitor patients. A long-term intensive screening program was associated with a reduced incidence of cancer after transplantation. This study evaluated the usefulness of the gene expression profiling of peripheral blood samples obtained from kidney transplant patients and adopted a screening test for detecting cancer of the digestive system (gastric, colon, pancreas, and biliary tract). Nineteen patients were included in this study and a total of 53 gene expression screening tests were performed. The gene expression profiles of blood-delivered total RNA and whole genome human gene expression profiles were obtained. We investigated the expression levels of 2665 genes associated with digestive cancers and counted the number of genes in which expression was altered. A hierarchical clustering analysis was also performed. The final prediction of the cancer possibility was determined according to an algorithm. The number of genes in which expression was altered was significantly increased in the kidney transplant recipients in comparison with the general population (1091 ± 63 vs 823 ± 94; P = .0024). The number of genes with altered expression decreased after the induction of mechanistic target of rapamycin (mTOR) inhibitor (1484 ± 227 vs 883 ± 154; P = .0439). No cases of possible digestive cancer were detected in this study period. The gene expression profiling of peripheral blood samples may be a useful and noninvasive diagnostic tool that allows for the early detection of cancer of the digestive system. Copyright © 2017 Elsevier Inc. All rights reserved.

Substrate-Specific Differential Gene Expression and RNA editing in the Brown Rot Fungus Fomitopsis pinicola.

PubMed

Wu, Baojun; Gaskell, Jill; Held, Benjamin W; Toapanta, Cristina; Vuong, Thu; Ahrendt, Steven; Lipzen, Anna; Zhang, Jiwei; Schilling, Jonathan S; Master, Emma; Grigoriev, Igor V; Blanchette, Robert A; Cullen, Dan; Hibbett, David S

2018-06-08

Wood-decaying fungi tend to have characteristic substrate ranges that partly define their ecological niche. Fomitopsis pinicola is a brown rot species of Polyporales that is reported on 82 species of softwoods and 42 species of hardwoods. We analyzed gene expression levels and RNA editing profiles of F. pinicola from submerged cultures with ground wood powder (sampled at five days) or solid wood wafers (sampled at ten and thirty days), using aspen, pine, and spruce substrates (aspen was used only in submerged cultures). Fomitopsis pinicola expressed similar sets of wood-degrading enzymes typical of brown rot fungi across all culture conditions and timepoints. Nevertheless, differential gene expression and RNA editing were observed across all pairwise comparisons of substrates and timepoints. Genes exhibiting differential expression and RNA editing encode diverse enzymes with known or potential function in brown rot decay, including laccase, benzoquinone reductase, aryl alcohol oxidase, cytochrome P450s, and various glycoside hydrolases. There was no overlap between differentially expressed and differentially edited genes, suggesting that these may provide F. pinicola with independent mechanisms for responding to different conditions. Comparing transcriptomes from submerged cultures and wood wafers, we found that culture conditions had a greater impact on global expression profiles than substrate wood species. In contrast, the suites of genes subject to RNA editing were much less affected by culture conditions. These findings highlight the need for standardization of culture conditions in studies of gene expression in wood-decaying fungi. IMPORTANCE All species of wood-decaying fungi occur on a characteristic range of substrates (host plants), which may be broad or narrow. Understanding the mechanisms that allow fungi to grow on particular substrates is important for both fungal ecology and applied uses of different feedstocks in industrial processes. We grew the wood-decaying polypore Fomitopsis pinicola on three different wood species, aspen, pine and spruce, under various culture conditions. We examined both gene expression (transcription levels) and RNA editing (post-transcriptional modification of RNA, which can potentially yield different proteins from the same gene). We found that F. pinicola is able to modify both gene expression and RNA editing profiles across different substrate species and culture conditions. Many of the genes involved encode enzymes with known or predicted functions in wood decay. This work provides clues to how wood-decaying fungi may adjust their arsenal of decay enzymes to accommodate different host substrates. Copyright © 2018 American Society for Microbiology.

Novel bioresources for studies of Brassica oleracea: identification of a kale MYB transcription factor responsible for glucosinolate production.

PubMed

Araki, Ryoichi; Hasumi, Akiko; Nishizawa, Osamu Ishizaki; Sasaki, Katsunori; Kuwahara, Ayuko; Sawada, Yuji; Totoki, Yasushi; Toyoda, Atsushi; Sakaki, Yoshiyuki; Li, Yimeng; Saito, Kazuki; Ogawa, Toshiya; Hirai, Masami Yokota

2013-10-01

Plants belonging to the Brassicaceae family exhibit species-specific profiles of glucosinolates (GSLs), a class of defence compounds against pathogens and insects. GSLs also exhibit various human health-promoting properties. Among them, glucoraphanin (aliphatic 4-methylsulphinylbutyl GSL) has attracted the most attention because it hydrolyses to form a potent anticancer compound. Increased interest in developing commercial varieties of Brassicaceae crops with desirable GSL profiles has led to attempts to identify genes that are potentially valuable for controlling GSL biosynthesis. However, little attention has been focused on genes of kale (Brassica oleracea var. acephala). In this study, we established full-length kale cDNA libraries containing 59 904 clones, which were used to generate an expressed sequence tag (EST) data set with 119 204 entries. The EST data set clarified genes related to the GSL biosynthesis pathway in kale. We specifically focused on BoMYB29, a homolog of Arabidopsis MYB29/PMG2/HAG3, not only to characterize its function but also to demonstrate its usability as a biological resource. BoMYB29 overexpression in wild-type Arabidopsis enhanced the expression of aliphatic GSL biosynthetic genes and the accumulation of aliphatic GSLs. When expressed in the myb28myb29 mutant, which exhibited no detectable aliphatic GSLs, BoMYB29 restored the expression of biosynthetic genes and aliphatic GSL accumulation. Interestingly, the ratio of methylsulphinyl GSL content, including glucoraphanin, to that of methylthio GSLs was greatly increased, indicating the suitability of BoMYB29 as a regulator for increasing methylsulphinyl GSL content. Our results indicate that these biological resources can facilitate further identification of genes useful for modifications of GSL profiles and accumulation in kale. © 2013 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis.

PubMed

Mei, Hao; Li, Lianna; Liu, Shijian; Jiang, Fan; Griswold, Michael; Mosley, Thomas

2017-01-21

We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.

Advanced colorectal adenoma related gene expression signature may predict prognostic for colorectal cancer patients with adenoma-carcinoma sequence.

PubMed

Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun

2015-01-01

There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinformatics software, and we analyzed the relationship between gene expression profiles of adenoma-adenocarcinoma sequence and clinical prognosis of colorectal cancer. The mRNA expressions of adenoma-carcinoma sequence were significantly different between high-grade intraepithelial neoplasia group and adenocarcinoma group. The biological process of gene ontology function enrichment analysis on differentially expressed genes between high-grade intraepithelial neoplasia group and adenocarcinoma group showed that genes enriched in the extracellular structure organization, skeletal system development, biological adhesion and itself regulated growth regulation, with the P value after FDR correction of less than 0.05. In addition, IPR-related protein mainly focused on the insulin-like growth factor binding proteins. The variable trends of gene expression profiles for adenoma-carcinoma sequence were mainly concentrated in high-grade intraepithelial neoplasia and adenocarcinoma. The differentially expressed genes are significantly correlated between high-grade intraepithelial neoplasia group and adenocarcinoma group. Bioinformatics analysis is an effective way to study the gene expression profiles in the adenoma-carcinoma sequence, and may provide an effective tool to involve colorectal cancer research strategy into colorectal adenoma or advanced adenoma.

L1000CDS2: LINCS L1000 characteristic direction signatures search engine

PubMed Central

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

Characterization of stem cells and cancer cells on the basis of gene expression profile stability, plasticity, and robustness: dynamical systems theory of gene expressions under cell-cell interaction explains mutational robustness of differentiated cells and suggests how cancer cells emerge.

PubMed

Kaneko, Kunihiko

2011-06-01

Here I present and discuss a model that, among other things, appears able to describe the dynamics of cancer cell origin from the perspective of stable and unstable gene expression profiles. In identifying such aberrant gene expression profiles as lying outside the normal stable states attracted through development and normal cell differentiation, the hypothesis explains why cancer cells accumulate mutations, to which they are not robust, and why these mutations create a new stable state far from the normal gene expression profile space. Such cells are in strong contrast with normal cell types that appeared as an attractor state in the gene expression dynamical system under cell-cell interaction and achieved robustness to noise through evolution, which in turn also conferred robustness to mutation. In complex gene regulation networks, other aberrant cellular states lacking such high robustness are expected to remain, which would correspond to cancer cells. Copyright © 2011 WILEY Periodicals, Inc.

Selecting the most appropriate time points to profile in high-throughput studies

PubMed Central

Kleyman, Michael; Sefer, Emre; Nicola, Teodora; Espinoza, Celia; Chhabra, Divya; Hagood, James S; Kaminski, Naftali; Ambalavanan, Namasivayam; Bar-Joseph, Ziv

2017-01-01

Biological systems are increasingly being studied by high throughput profiling of molecular data over time. Determining the set of time points to sample in studies that profile several different types of molecular data is still challenging. Here we present the Time Point Selection (TPS) method that solves this combinatorial problem in a principled and practical way. TPS utilizes expression data from a small set of genes sampled at a high rate. As we show by applying TPS to study mouse lung development, the points selected by TPS can be used to reconstruct an accurate representation for the expression values of the non selected points. Further, even though the selection is only based on gene expression, these points are also appropriate for representing a much larger set of protein, miRNA and DNA methylation changes over time. TPS can thus serve as a key design strategy for high throughput time series experiments. Supporting Website: www.sb.cs.cmu.edu/TPS DOI: http://dx.doi.org/10.7554/eLife.18541.001 PMID:28124972

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

PubMed Central

Summerfield, Taryn L.; Yu, Lianbo; Gulati, Parul; Zhang, Jie; Huang, Kun; Romero, Roberto; Kniss, Douglas A.

2011-01-01

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals. PMID:21655103

[Preliminary analysis of retinal gene expression profile of diabetic rat].

PubMed

Mei, Yan; Zhou, Hong-ying; Xiang, Tao; Lu, You-guang; Li, Ai-dong; Tang, En-jie; Yang, Hui-jun

2005-10-01

Establishing the retinal gene expression profiles of non-diabetic rat and diabetic rat and comparing the profiles in order to analyze the possible genes related with diabetic retinopathy. The whole retinal transcriptional fragments of non-diabetic rat and 8-week diabetic rat were obtained by restriction fragments differential display-PCR (RFDD-PCR). Bioinformatic analysis of retinal gene expression was performed using soft wares, including Fragment Analysis. After comparison of the expression profiles, the related gene fragments of diabetic retinopathy were initially selected as the target gene of further approach. A total of 3639 significant fragments were obtained. By means of more than 3-fold contrast of fluorescent intensity as the differential expression standard, the authors got 840 differential fragments, accounting for 23.08% of the expressed numbers and including 5 visual related genes, 13 excitatory neruotransmitter genes and 3 inhibitory neurotransmitter genes. At the 8th week, the expression of Rhodopsin kinase, beta-arrestin, Phosducinìrod photoreceptor cGMP-gated channel and Rpe65 as well as iGlu R1-4 were down-regulated. mGluRs and GABA-Rs were all up-regulated, whereas the expression of GlyR was unchanged. These results prompt again that the changes in retinal nervous layer of rat have occurred at an early stage of diabetes. The genes expression pattern of visual related genes and excitatory and inhibitory neurotransmitters in rat diabetic retina have been involved in neuro-dysfunctions of diabetic retina.

Expression profiling of cardiovascular disease

PubMed Central

2004-01-01

Cardiovascular disease is the most important cause of morbidity and mortality in developed countries, causing twice as many deaths as cancer in the USA. The major cardiovascular diseases, including coronary artery disease (CAD), myocardial infarction (MI), congestive heart failure (CHF) and common congenital heart disease (CHD), are caused by multiple genetic and environmental factors, as well as the interactions between them. The underlying molecular pathogenic mechanisms for these disorders are still largely unknown, but gene expression may play a central role in the development and progression of cardiovascular disease. Microarrays are high-throughput genomic tools that allow the comparison of global expression changes in thousands of genes between normal and diseased cells/tissues. Microarrays have recently been applied to CAD/MI, CHF and CHD to profile changes in gene expression patterns in diseased and non-diseased patients. This same technology has also been used to characterise endothelial cells, vascular smooth muscle cells and inflammatory cells, with or without various treatments that mimic disease processes involved in CAD/MI. These studies have led to the identification of unique subsets of genes associated with specific diseases and disease processes. Ongoing microarray studies in the field will provide insights into the molecular mechanism of cardiovascular disease and may generate new diagnostic and therapeutic markers. PMID:15588496

Characterization of the transcriptome profiles related to globin gene switching during in vitro erythroid maturation

PubMed Central

2012-01-01

Background The fetal and adult globin genes in the human β-globin cluster on chromosome 11 are sequentially expressed to achieve normal hemoglobin switching during human development. The pharmacological induction of fetal γ-globin (HBG) to replace abnormal adult sickle βS-globin is a successful strategy to treat sickle cell disease; however the molecular mechanism of γ-gene silencing after birth is not fully understood. Therefore, we performed global gene expression profiling using primary erythroid progenitors grown from human peripheral blood mononuclear cells to characterize gene expression patterns during the γ-globin to β-globin (γ/β) switch observed throughout in vitro erythroid differentiation. Results We confirmed erythroid maturation in our culture system using cell morphologic features defined by Giemsa staining and the γ/β-globin switch by reverse transcription-quantitative PCR (RT-qPCR) analysis. We observed maximal γ-globin expression at day 7 with a switch to a predominance of β-globin expression by day 28 and the γ/β-globin switch occurred around day 21. Expression patterns for transcription factors including GATA1, GATA2, KLF1 and NFE2 confirmed our system produced the expected pattern of expression based on the known function of these factors in globin gene regulation. Subsequent gene expression profiling was performed with RNA isolated from progenitors harvested at day 7, 14, 21, and 28 in culture. Three major gene profiles were generated by Principal Component Analysis (PCA). For profile-1 genes, where expression decreased from day 7 to day 28, we identified 2,102 genes down-regulated > 1.5-fold. Ingenuity pathway analysis (IPA) for profile-1 genes demonstrated involvement of the Cdc42, phospholipase C, NF-Kβ, Interleukin-4, and p38 mitogen activated protein kinase (MAPK) signaling pathways. Transcription factors known to be involved in γ-and β-globin regulation were identified. The same approach was used to generate profile-2 genes where expression was up-regulated over 28 days in culture. IPA for the 2,437 genes with > 1.5-fold induction identified the mitotic roles of polo-like kinase, aryl hydrocarbon receptor, cell cycle control, and ATM (Ataxia Telangiectasia Mutated Protein) signaling pathways; transcription factors identified included KLF1, GATA1 and NFE2 among others. Finally, profile-3 was generated from 1,579 genes with maximal expression at day 21, around the time of the γ/β-globin switch. IPA identified associations with cell cycle control, ATM, and aryl hydrocarbon receptor signaling pathways. Conclusions The transcriptome analysis completed with erythroid progenitors grown in vitro identified groups of genes with distinct expression profiles, which function in metabolic pathways associated with cell survival, hematopoiesis, blood cells activation, and inflammatory responses. This study represents the first report of a transcriptome analysis in human primary erythroid progenitors to identify transcription factors involved in hemoglobin switching. Our results also demonstrate that the in vitro liquid culture system is an excellent model to define mechanisms of global gene expression and the DNA-binding protein and signaling pathways involved in globin gene regulation. PMID:22537182

Morphological and transcriptomic effects of endocrine modulators on the gonadal differentiation of chicken embryos: The case of tributyltin (TBT).

PubMed

Scheider, Jessica; Afonso-Grunz, Fabian; Jessl, Luzie; Hoffmeier, Klaus; Winter, Peter; Oehlmann, Jörg

2018-03-01

Morphological malformations induced by tributyltin (TBT) exposure during embryonic development have already been characterized in various taxonomic groups, but, nonetheless, the molecular processes underlying these changes remain obscure. The present study provides the first genome-wide screening for differentially expressed genes that are linked to morphological alterations of gonadal tissue from chicken embryos after exposure to TBT. We applied a single injection of TBT (between 0.5 and 30 pg as Sn/g egg) into incubated fertile eggs to simulate maternal transfer of the endocrine disruptive compound. Methyltestosterone (MT) served as a positive control (30 pg/g egg). After 19 days of incubation, structural features of the gonads as well as genome-wide gene expression profiles were assessed simultaneously. TBT induced significant morphological and histological malformations of gonadal tissue from female embryos that show a virilization of the ovaries. This phenotypical virilization was mirrored by altered expression profiles of sex-dependent genes. Among these are several transcription and growth factors (e.g. FGF12, CTCF, NFIB), whose altered expression might serve as a set of markers for early identification of endocrine active chemicals that affect embryonic development by transcriptome profiling without the need of elaborate histological analyses. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Gene expression variability in human hepatic drug metabolizing enzymes and transporters.

PubMed

Yang, Lun; Price, Elvin T; Chang, Ching-Wei; Li, Yan; Huang, Ying; Guo, Li-Wu; Guo, Yongli; Kaput, Jim; Shi, Leming; Ning, Baitang

2013-01-01

Interindividual variability in the expression of drug-metabolizing enzymes and transporters (DMETs) in human liver may contribute to interindividual differences in drug efficacy and adverse reactions. Published studies that analyzed variability in the expression of DMET genes were limited by sample sizes and the number of genes profiled. We systematically analyzed the expression of 374 DMETs from a microarray data set consisting of gene expression profiles derived from 427 human liver samples. The standard deviation of interindividual expression for DMET genes was much higher than that for non-DMET genes. The 20 DMET genes with the largest variability in the expression provided examples of the interindividual variation. Gene expression data were also analyzed using network analysis methods, which delineates the similarities of biological functionalities and regulation mechanisms for these highly variable DMET genes. Expression variability of human hepatic DMET genes may affect drug-gene interactions and disease susceptibility, with concomitant clinical implications.

Biasogram: Visualization of Confounding Technical Bias in Gene Expression Data

PubMed Central

Krzystanek, Marcin; Szallasi, Zoltan; Eklund, Aron C.

2013-01-01

Gene expression profiles of clinical cohorts can be used to identify genes that are correlated with a clinical variable of interest such as patient outcome or response to a particular drug. However, expression measurements are susceptible to technical bias caused by variation in extraneous factors such as RNA quality and array hybridization conditions. If such technical bias is correlated with the clinical variable of interest, the likelihood of identifying false positive genes is increased. Here we describe a method to visualize an expression matrix as a projection of all genes onto a plane defined by a clinical variable and a technical nuisance variable. The resulting plot indicates the extent to which each gene is correlated with the clinical variable or the technical variable. We demonstrate this method by applying it to three clinical trial microarray data sets, one of which identified genes that may have been driven by a confounding technical variable. This approach can be used as a quality control step to identify data sets that are likely to yield false positive results. PMID:23613961

Similarity of markers identified from cancer gene expression studies: observations from GEO.

PubMed

Shi, Xingjie; Shen, Shihao; Liu, Jin; Huang, Jian; Zhou, Yong; Ma, Shuangge

2014-09-01

Gene expression profiling has been extensively conducted in cancer research. The analysis of multiple independent cancer gene expression datasets may provide additional information and complement single-dataset analysis. In this study, we conduct multi-dataset analysis and are interested in evaluating the similarity of cancer-associated genes identified from different datasets. The first objective of this study is to briefly review some statistical methods that can be used for such evaluation. Both marginal analysis and joint analysis methods are reviewed. The second objective is to apply those methods to 26 Gene Expression Omnibus (GEO) datasets on five types of cancers. Our analysis suggests that for the same cancer, the marker identification results may vary significantly across datasets, and different datasets share few common genes. In addition, datasets on different cancers share few common genes. The shared genetic basis of datasets on the same or different cancers, which has been suggested in the literature, is not observed in the analysis of GEO data. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data

PubMed Central

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R.; del Río-Navarro, Blanca E.; Mendoza-Vargas, Alfredo; Sánchez, Filiberto

2017-01-01

Background In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. Methods We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6–10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). Results From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Discussion Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments. PMID:29230367

Generation of novel pharmacogenomic candidates in the response to methotrexate in juvenile idiopathic arthritis: correlation between gene expression and genotype

PubMed Central

Moncrieffe, Halima; Hinks, Anne; Ursu, Simona; Kassoumeri, Laura; Etheridge, Angela; Hubank, Mike; Martin, Paul; Weiler, Tracey; Glass, David N; Thompson, Susan D.; Thomson, Wendy; Wedderburn, Lucy R

2010-01-01

Objectives Little is known about mechanisms of efficacy of methotrexate (MTX) in childhood arthritis, or genetic influences upon response to MTX. The aims of this study were to use gene expression profiling to identify novel pathways/genes altered by MTX and then investigate these genes for genotype associations with response to MTX treatment. Methods Gene expression profiling before and after MTX treatment was performed on 11 children with juvenile idiopathic arthritis (JIA) treated with MTX, in whom response at 6 months of treatment was defined. Genes showing the most differential gene expression after treatment were selected for SNP genotyping. Genotype frequencies were compared between non-responders and responders (ACR-Ped70). An independent cohort was available for validation. Results Gene expression profiling before and after MTX treatment revealed 1222 differentially expressed probes sets (fold change >1.7, p< 0.05) and 1065 when restricted to full responder cases only. Six highly differentially expressed genes were analysed for genetic association to response to MTX. Three SNPs in the SLC16A7 gene showed significant association with MTX response. One SNP showed validated association in an independent cohort. Conclusions This study is the first, to our knowledge, to evaluate gene expression profiles in children with JIA before and after MTX, and to analyse genetic variation in differentially expressed genes. We have identified a gene which may contribute to genetic variability in MTX response in JIA, and established as proof of principle that genes which are differentially expressed at mRNA level after drug administration may also be good candidates for genetic analysis. PMID:20827233

Integrated lipidomics and transcriptomic analysis of peripheral blood reveals significantly enriched pathways in type 2 diabetes mellitus.

PubMed

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.

Water deficits accelerate ripening and induce changes in gene expression regulating flavonoid biosynthesis in grape berries.

PubMed

Castellarin, Simone D; Matthews, Mark A; Di Gaspero, Gabriele; Gambetta, Gregory A

2007-12-01

Water deficits consistently promote higher concentrations of anthocyanins in red winegrapes and their wines. However, controversy remains as to whether there is any direct effect on berry metabolism other than inhibition of growth. Early (ED) and late (LD) season water deficits, applied before or after the onset of ripening (veraison), were imposed on field grown Vitis vinifera "Cabernet Sauvignon", and the responses of gene expression in the flavonoid pathway and their corresponding metabolites were determined. ED accelerated sugar accumulation and the onset of anthocyanin synthesis. Both ED and LD increased anthocyanin accumulation after veraison. Expression profiling revealed that the increased anthocyanin accumulation resulted from earlier and greater expression of the genes controlling flux through the anthocyanin biosynthetic pathway, including F3H, DFR, UFGT and GST. Increases in total anthocyanins resulted predominantly from an increase of 3'4'5'-hydroxylated forms through the differential regulation of F3'H and F3'5'H. There were limited effects on proanthocyanidin, other flavonols, and on expression of genes committed to their synthesis. These results demonstrate that manipulation of abiotic stress through applied water deficits not only modulates compositional changes during berry ripening, but also alters the timing of particular aspects of the ripening process.

A systems biology approach to defining regulatory mechanisms for cartilage and tendon cell phenotypes.

PubMed

Mueller, A J; Tew, S R; Vasieva, O; Clegg, P D; Canty-Laird, E G

2016-09-27

Phenotypic plasticity of adult somatic cells has provided emerging avenues for the development of regenerative therapeutics. In musculoskeletal biology the mechanistic regulatory networks of genes governing the phenotypic plasticity of cartilage and tendon cells has not been considered systematically. Additionally, a lack of strategies to effectively reproduce in vitro functional models of cartilage and tendon is retarding progress in this field. De- and redifferentiation represent phenotypic transitions that may contribute to loss of function in ageing musculoskeletal tissues. Applying a systems biology network analysis approach to global gene expression profiles derived from common in vitro culture systems (monolayer and three-dimensional cultures) this study demonstrates common regulatory mechanisms governing de- and redifferentiation transitions in cartilage and tendon cells. Furthermore, evidence of convergence of gene expression profiles during monolayer expansion of cartilage and tendon cells, and the expression of key developmental markers, challenges the physiological relevance of this culture system. The study also suggests that oxidative stress and PI3K signalling pathways are key modulators of in vitro phenotypes for cells of musculoskeletal origin.

Accumulated Expression Level of Cytosolic Glutamine Synthetase 1 Gene (OsGS1;1 or OsGS1;2) Alter Plant Development and the Carbon-Nitrogen Metabolic Status in Rice

PubMed Central

Bao, Aili; Zhao, Zhuqing; Ding, Guangda; Shi, Lei; Xu, Fangsen; Cai, Hongmei

2014-01-01

Maintaining an appropriate balance of carbon to nitrogen metabolism is essential for rice growth and yield. Glutamine synthetase is a key enzyme for ammonium assimilation. In this study, we systematically analyzed the growth phenotype, carbon-nitrogen metabolic status and gene expression profiles in GS1;1-, GS1;2-overexpressing rice and wildtype plants. Our results revealed that the GS1;1-, GS1;2-overexpressing plants exhibited a poor plant growth phenotype and yield and decreased carbon/nitrogen ratio in the stem caused by the accumulation of nitrogen in the stem. In addition, the leaf SPAD value and photosynthetic parameters, soluble proteins and carbohydrates varied greatly in the GS1;1-, GS1;2-overexpressing plants. Furthermore, metabolite profile and gene expression analysis demonstrated significant changes in individual sugars, organic acids and free amino acids, and gene expression patterns in GS1;1-, GS1;2-overexpressing plants, which also indicated the distinct roles that these two GS1 genes played in rice nitrogen metabolism, particularly when sufficient nitrogen was applied in the environment. Thus, the unbalanced carbon-nitrogen metabolic status and poor ability of nitrogen transportation from stem to leaf in GS1;1-, GS1;2-overexpressing plants may explain the poor growth and yield. PMID:24743556

A deep auto-encoder model for gene expression prediction.

PubMed

Xie, Rui; Wen, Jia; Quitadamo, Andrew; Cheng, Jianlin; Shi, Xinghua

2017-11-17

Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance. To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns. We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

Gene expression analysis predicts insect venom anaphylaxis in indolent systemic mastocytosis.

PubMed

Niedoszytko, M; Bruinenberg, M; van Doormaal, J J; de Monchy, J G R; Nedoszytko, B; Koppelman, G H; Nawijn, M C; Wijmenga, C; Jassem, E; Elberink, J N G Oude

2011-05-01

Anaphylaxis to insect venom (Hymenoptera) is most severe in patients with mastocytosis and may even lead to death. However, not all patients with mastocytosis suffer from anaphylaxis. The aim of the study was to analyze differences in gene expression between patients with indolent systemic mastocytosis (ISM) and a history of insect venom anaphylaxis (IVA) compared to those patients without a history of anaphylaxis, and to determine the predictive use of gene expression profiling. Whole-genome gene expression analysis was performed in peripheral blood cells. Twenty-two adults with ISM were included: 12 with a history of IVA and 10 without a history of anaphylaxis of any kind. Significant differences in single gene expression corrected for multiple testing were found for 104 transcripts (P < 0.05). Gene ontology analysis revealed that the differentially expressed genes were involved in pathways responsible for the development of cancer and focal and cell adhesion suggesting that the expression of genes related to the differentiation state of cells is higher in patients with a history of anaphylaxis. Based on the gene expression profiles, a naïve Bayes prediction model was built identifying patients with IVA. In ISM, gene expression profiles are different between patients with a history of IVA and those without. These findings might reflect a more pronounced mast cells dysfunction in patients without a history of anaphylaxis. Gene expression profiling might be a useful tool to predict the risk of anaphylaxis on insect venom in patients with ISM. Prospective studies are needed to substantiate any conclusions. © 2010 John Wiley & Sons A/S.

Gene expression profiling in liver and testis of rats to characterize the toxicity of triazole fungicides.

PubMed

Tully, Douglas B; Bao, Wenjun; Goetz, Amber K; Blystone, Chad R; Ren, Hongzu; Schmid, Judith E; Strader, Lillian F; Wood, Carmen R; Best, Deborah S; Narotsky, Michael G; Wolf, Douglas C; Rockett, John C; Dix, David J

2006-09-15

Four triazole fungicides were studied using toxicogenomic techniques to identify potential mechanisms of action. Adult male Sprague-Dawley rats were dosed for 14 days by gavage with fluconazole, myclobutanil, propiconazole, or triadimefon. Following exposure, serum was collected for hormone measurements, and liver and testes were collected for histology, enzyme biochemistry, or gene expression profiling. Body and testis weights were unaffected, but liver weights were significantly increased by all four triazoles, and hepatocytes exhibited centrilobular hypertrophy. Myclobutanil exposure increased serum testosterone and decreased sperm motility, but no treatment-related testis histopathology was observed. We hypothesized that gene expression profiles would identify potential mechanisms of toxicity and used DNA microarrays and quantitative real-time PCR (qPCR) to generate profiles. Triazole fungicides are designed to inhibit fungal cytochrome P450 (CYP) 51 enzyme but can also modulate the expression and function of mammalian CYP genes and enzymes. Triazoles affected the expression of numerous CYP genes in rat liver and testis, including multiple Cyp2c and Cyp3a isoforms as well as other xenobiotic metabolizing enzyme (XME) and transporter genes. For some genes, such as Ces2 and Udpgtr2, all four triazoles had similar effects on expression, suggesting possible common mechanisms of action. Many of these CYP, XME and transporter genes are regulated by xeno-sensing nuclear receptors, and hierarchical clustering of CAR/PXR-regulated genes demonstrated the similarities of toxicogenomic responses in liver between all four triazoles and in testis between myclobutanil and triadimefon. Triazoles also affected expression of multiple genes involved in steroid hormone metabolism in the two tissues. Thus, gene expression profiles helped identify possible toxicological mechanisms of the triazole fungicides.

RNA sample preparation applied to gene expression profiling for the horse biological passport.

PubMed

Bailly-Chouriberry, Ludovic; Baudoin, Florent; Cormant, Florence; Glavieux, Yohan; Loup, Benoit; Garcia, Patrice; Popot, Marie-Agnès; Bonnaire, Yves

2017-09-01

The improvement of doping control is an ongoing race. Techniques to fight doping are usually based on the direct detection of drugs or their metabolites by analytical methods such as chromatography hyphenated to mass spectrometry after ad hoc sample preparation. Nowadays, omic methods constitute an attractive development and advances have been achieved particularly by application of molecular biology tools for detection of anabolic androgenic steroids (AAS), erythropoiesis-stimulating agent (ESA), or to control human growth hormone misuses. These interesting results across different animal species have suggested that modification of gene expression offers promising new methods of improving the window of detection of banned substances by targeting their effects on blood cell gene expression. In this context, the present study describes the possibility of using a modified version of the dedicated Human IVD (in vitro Diagnostics) PAXgene® Blood RNA Kit for horse gene expression analysis in blood collected on PAXgene® tubes applied to the horse biological passport. The commercial kit was only approved for human blood samples and has required an optimization of specific technical requirements for equine blood samples. Improvements and recommendations were achieved for sample collection, storage and RNA extraction procedure. Following these developments, RNA yield and quality were demonstrated to be suitable for downstream gene expression analysis by qPCR techniques. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Different HER2 protein expression profiles aid in the histologic differential diagnosis between urothelial carcinoma in situ (CIS) and non-CIS conditions (dysplasia and reactive atypia) of the urinary bladder mucosa.

PubMed

Gunia, Sven; Koch, Stefan; Hakenberg, Oliver W; May, Matthias; Kakies, Christoph; Erbersdobler, Andreas

2011-12-01

We evaluated HER2 expression profiles in 32 carcinoma in situ (CIS) and 31 non-CIS conditions (5 dysplasia and 26 reactive atypia) of the urinary bladder mucosa by applying breast cancer scoring rules. In situ hybridization was performed on tissue microarrays to assess HER2 gene amplification status. Our immunoprofiling data disclosed moderate to strong HER2 expression in CIS, including the basal layer of the urothelium, and absent to weak HER2 expression in non-CIS conditions. From the histologic differential diagnostic standpoint, immunostaining for HER2 protein represents a useful adjunct to aid in the delineation between CIS and non-CIS conditions of the bladder mucosa. Pathogenically, aberrant HER2 protein expression in CIS seems to be more commonly associated with polysomy than with gene amplification. From a therapeutic viewpoint, prospective clinical studies should investigate the potential benefit of HER2-targeted therapies in CIS, particularly in cases unresponsive to conventional therapeutic regimens.

Optimal aggregation of binary classifiers for multiclass cancer diagnosis using gene expression profiles.

PubMed

Yukinawa, Naoto; Oba, Shigeyuki; Kato, Kikuya; Ishii, Shin

2009-01-01

Multiclass classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. There have been many studies of aggregating binary classifiers to construct a multiclass classifier based on one-versus-the-rest (1R), one-versus-one (11), or other coding strategies, as well as some comparison studies between them. However, the studies found that the best coding depends on each situation. Therefore, a new problem, which we call the "optimal coding problem," has arisen: how can we determine which coding is the optimal one in each situation? To approach this optimal coding problem, we propose a novel framework for constructing a multiclass classifier, in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. Although there is no a priori answer to the optimal coding problem, our weight tuning method can be a consistent answer to the problem. We apply this method to various classification problems including a synthesized data set and some cancer diagnosis data sets from gene expression profiling. The results demonstrate that, in most situations, our method can improve classification accuracy over simple voting heuristics and is better than or comparable to state-of-the-art multiclass predictors.

Metastatic canine mammary carcinomas can be identified by a gene expression profile that partly overlaps with human breast cancer profiles

PubMed Central

2010-01-01

Background Similar to human breast cancer mammary tumors of the female dog are commonly associated with a fatal outcome due to the development of distant metastases. However, the molecular defects leading to metastasis are largely unknown and the value of canine mammary carcinoma as a model for human breast cancer is unclear. In this study, we analyzed the gene expression signatures associated with mammary tumor metastasis and asked for parallels with the human equivalent. Methods Messenger RNA expression profiles of twenty-seven lymph node metastasis positive or negative canine mammary carcinomas were established by microarray analysis. Differentially expressed genes were functionally characterized and associated with molecular pathways. The findings were also correlated with published data on human breast cancer. Results Metastatic canine mammary carcinomas had 1,011 significantly differentially expressed genes when compared to non-metastatic carcinomas. Metastatic carcinomas had a significant up-regulation of genes associated with cell cycle regulation, matrix modulation, protein folding and proteasomal degradation whereas cell differentiation genes, growth factor pathway genes and regulators of actin organization were significantly down-regulated. Interestingly, 265 of the 1,011 differentially expressed canine genes are also related to human breast cancer and, vice versa, parts of a human prognostic gene signature were identified in the expression profiles of the metastatic canine tumors. Conclusions Metastatic canine mammary carcinomas can be discriminated from non-metastatic carcinomas by their gene expression profiles. More than one third of the differentially expressed genes are also described of relevance for human breast cancer. Many of the differentially expressed genes are linked to functions and pathways which appear to be relevant for the induction and maintenance of metastatic progression and may represent new therapeutic targets. Furthermore, dogs are in some aspects suitable as a translational model for human breast tumors in order to identify prognostic molecular signatures and potential therapeutic targets. PMID:21062462

Microarray profiling of gene expression in human adipocytes in response to anthocyanins.

PubMed

Tsuda, Takanori; Ueno, Yuki; Yoshikawa, Toshikazu; Kojo, Hitoshi; Osawa, Toshihiko

2006-04-14

Adipocyte dysfunction is strongly associated with the development of obesity and insulin resistance. It is accepted that the regulation of adipocytokine secretion or the adipocyte specific gene expression is one of the most important targets for the prevention of obesity and amelioration of insulin sensitivity. Recently, we demonstrated that anthocyanins, which are pigments widespread in the plant kingdom, have the potency of anti-obesity in mice and the enhancement adipocytokine secretion and its gene expression in adipocytes. In this study, we have shown the gene expression profile in human adipocytes treated with anthocyanins (cyanidin 3-glucoside; C3G or cyanidin; Cy). The human adipocytes were treated with 100 microM C3G, Cy or vehicle for 24 h. The total RNA from the adipocytes was isolated and carried out GeneChip microarray analysis. Based on the gene expression profile, we demonstrated the significant changes of adipocytokine expression (up-regulation of adiponectin and down-regulation of plasminogen activator inhibitor-1 and interleukin-6). Some of lipid metabolism related genes (uncoupling protein2, acylCoA oxidase1 and perilipin) also significantly induced in both common the C3G or Cy treatment groups. These studies have provided an overview of the gene expression profiles in human adipocytes treated with anthocyanins and demonstrated that anthocyanins can regulate adipocytokine gene expression to ameliorate adipocyte function related with obesity and diabetes that merit further investigation.

A cross-species analysis method to analyze animal models' similarity to human's disease state

PubMed Central

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

A cross-species analysis method to analyze animal models' similarity to human's disease state.

PubMed

Yu, Shuhao; Zheng, Lulu; Li, Yun; Li, Chunyan; Ma, Chenchen; Li, Yixue; Li, Xuan; Hao, Pei

2012-01-01

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. 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. 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.

Glycosyltransferase Gene Expression Profiles Classify Cancer Types and Propose Prognostic Subtypes

NASA Astrophysics Data System (ADS)

Ashkani, Jahanshah; Naidoo, Kevin J.

2016-05-01

Aberrant glycosylation in tumours stem from altered glycosyltransferase (GT) gene expression but can the expression profiles of these signature genes be used to classify cancer types and lead to cancer subtype discovery? The differential structural changes to cellular glycan structures are predominantly regulated by the expression patterns of GT genes and are a hallmark of neoplastic cell metamorphoses. We found that the expression of 210 GT genes taken from 1893 cancer patient samples in The Cancer Genome Atlas (TCGA) microarray data are able to classify six cancers; breast, ovarian, glioblastoma, kidney, colon and lung. The GT gene expression profiles are used to develop cancer classifiers and propose subtypes. The subclassification of breast cancer solid tumour samples illustrates the discovery of subgroups from GT genes that match well against basal-like and HER2-enriched subtypes and correlates to clinical, mutation and survival data. This cancer type glycosyltransferase gene signature finding provides foundational evidence for the centrality of glycosylation in cancer.

ABC gene expression profiles have clinical importance and possibly form a new hallmark of cancer.

PubMed

Dvorak, Pavel; Pesta, Martin; Soucek, Pavel

2017-05-01

Adenosine triphosphate-binding cassette proteins constitute a large family of active transporters through extracellular and intracellular membranes. Increased drug efflux based on adenosine triphosphate-binding cassette protein activity is related to the development of cancer cell chemoresistance. Several articles have focused on adenosine triphosphate-binding cassette gene expression profiles (signatures), based on the expression of all 49 human adenosine triphosphate-binding cassette genes, in individual tumor types and reported connections to established clinicopathological features. The aim of this study was to test our theory about the existence of adenosine triphosphate-binding cassette gene expression profiles common to multiple types of tumors, which may modify tumor progression and provide clinically relevant information. Such general adenosine triphosphate-binding cassette profiles could constitute a new attribute of carcinogenesis. Our combined cohort consisted of tissues from 151 cancer patients-breast, colorectal, and pancreatic carcinomas. Standard protocols for RNA isolation and quantitative real-time polymerase chain reaction were followed. Gene expression data from individual tumor types as well as a merged tumor dataset were analyzed by bioinformatics tools. Several general adenosine triphosphate-binding cassette profiles, with differences in gene functions, were established and shown to have significant relations to clinicopathological features such as tumor size, histological grade, or clinical stage. Genes ABCC7, A3, A8, A12, and C8 prevailed among the most upregulated or downregulated ones. In conclusion, the results supported our theory about general adenosine triphosphate-binding cassette gene expression profiles and their importance for cancer on clinical as well as research levels. The presence of ABCC7 (official symbol CFTR) among the genes with key roles in the profiles supports the emerging evidence about its crucial role in various cancers. Graphical abstract.

Stress amplifies sex differences in primate prefrontal profiles of gene expression.

PubMed

Lee, Alex G; Hagenauer, Megan; Absher, Devin; Morrison, Kathleen E; Bale, Tracy L; Myers, Richard M; Watson, Stanley J; Akil, Huda; Schatzberg, Alan F; Lyons, David M

2017-11-02

Stress is a recognized risk factor for mood and anxiety disorders that occur more often in women than men. Prefrontal brain regions mediate stress coping, cognitive control, and emotion. Here, we investigate sex differences and stress effects on prefrontal cortical profiles of gene expression in squirrel monkey adults. Dorsolateral, ventrolateral, and ventromedial prefrontal cortical regions from 18 females and 12 males were collected after stress or no-stress treatment conditions. Gene expression profiles were acquired using HumanHT-12v4.0 Expression BeadChip arrays adapted for squirrel monkeys. Extensive variation between prefrontal cortical regions was discerned in the expression of numerous autosomal and sex chromosome genes. Robust sex differences were also identified across prefrontal cortical regions in the expression of mostly autosomal genes. Genes with increased expression in females compared to males were overrepresented in mitogen-activated protein kinase and neurotrophin signaling pathways. Many fewer genes with increased expression in males compared to females were discerned, and no molecular pathways were identified. Effect sizes for sex differences were greater in stress compared to no-stress conditions for ventromedial and ventrolateral prefrontal cortical regions but not dorsolateral prefrontal cortex. Stress amplifies sex differences in gene expression profiles for prefrontal cortical regions involved in stress coping and emotion regulation. Results suggest molecular targets for new treatments of stress disorders in human mental health.

Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes

PubMed Central

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

Gene Expression Profiling of Monkeypox Virus-Infected Cells Reveals Novel Interfaces for Host-Virus Interactions

DTIC Science & Technology

2010-07-28

expression is plotted on Y -axis after normalization to mock-treated samples. Results plotted to compare calculated fold change in expression of each gene ...RESEARCH Open Access Gene expression profiling of monkeypox virus-infected cells reveals novel interfaces for host-virus interactions Abdulnaser...suppress antiviral cell defenses, exploit host cell machinery, and delay infection-induced cell death. However, a comprehensive study of all host genes

Identification of human circadian genes based on time course gene expression profiles by using a deep learning method.

PubMed

Cui, Peng; Zhong, Tingyan; Wang, Zhuo; Wang, Tao; Zhao, Hongyu; Liu, Chenglin; Lu, Hui

2018-06-01

Circadian genes express periodically in an approximate 24-h period and the identification and study of these genes can provide deep understanding of the circadian control which plays significant roles in human health. Although many circadian gene identification algorithms have been developed, large numbers of false positives and low coverage are still major problems in this field. In this study we constructed a novel computational framework for circadian gene identification using deep neural networks (DNN) - a deep learning algorithm which can represent the raw form of data patterns without imposing assumptions on the expression distribution. Firstly, we transformed time-course gene expression data into categorical-state data to denote the changing trend of gene expression. Two distinct expression patterns emerged after clustering of the state data for circadian genes from our manually created learning dataset. DNN was then applied to discriminate the aperiodic genes and the two subtypes of periodic genes. In order to assess the performance of DNN, four commonly used machine learning methods including k-nearest neighbors, logistic regression, naïve Bayes, and support vector machines were used for comparison. The results show that the DNN model achieves the best balanced precision and recall. Next, we conducted large scale circadian gene detection using the trained DNN model for the remaining transcription profiles. Comparing with JTK_CYCLE and a study performed by Möller-Levet et al. (doi: https://doi.org/10.1073/pnas.1217154110), we identified 1132 novel periodic genes. Through the functional analysis of these novel circadian genes, we found that the GTPase superfamily exhibits distinct circadian expression patterns and may provide a molecular switch of circadian control of the functioning of the immune system in human blood. Our study provides novel insights into both the circadian gene identification field and the study of complex circadian-driven biological control. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang. Copyright © 2017. Published by Elsevier B.V.

Integrating Genomic Analysis with the Genetic Basis of Gene Expression: Preliminary Evidence of the Identification of Causal Genes for Cardiovascular and Metabolic Traits Related to Nutrition in Mexicans123

PubMed Central

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

Divergence between motoneurons: gene expression profiling provides a molecular characterization of functionally discrete somatic and autonomic motoneurons

PubMed Central

Cui, Dapeng; Dougherty, Kimberly J.; Machacek, David W.; Sawchuk, Michael; Hochman, Shawn; Baro, Deborah J.

2009-01-01

Studies in the developing spinal cord suggest that different motoneuron (MN) cell types express very different genetic programs, but the degree to which adult programs differ is unknown. To compare genetic programs between adult MN columnar cell types, we used laser capture micro-dissection (LCM) and Affymetrix microarrays to create expression profiles for three columnar cell types: lateral and medial MNs from lumbar segments and sympathetic preganglionic motoneurons located in the thoracic intermediolateral nucleus. A comparison of the three expression profiles indicated that ~7% (813/11,552) of the genes showed significant differences in their expression levels. The largest differences were observed between sympathetic preganglionic MNs and the lateral motor column, with 6% (706/11,552) of the genes being differentially expressed. Significant differences in expression were observed for 1.8% (207/11,552) of the genes when comparing sympathetic preganglionic MNs with the medial motor column. Lateral and medial MNs showed the least divergence, with 1.3% (150/11,552) of the genes being differentially expressed. These data indicate that the amount of divergence in expression profiles between identified columnar MNs does not strictly correlate with divergence of function as defined by innervation patterns (somatic/muscle vs. autonomic/viscera). Classification of the differentially expressed genes with regard to function showed that they underpin all fundamental cell systems and processes, although most differentially expressed genes encode proteins involved in signal transduction. Mining the expression profiles to examine transcription factors essential for MN development suggested that many of the same transcription factors participatein combinatorial codes in embryonic and adult neurons, but patterns of expression change significantly. PMID:16317082

Integrative analysis of gut microbiota composition, host colonic gene expression and intraluminal metabolites in aging C57BL/6J mice.

PubMed

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.

A network-based method to evaluate quality of reproducibility of differential expression in cancer genomics studies

PubMed Central

Geng, Haijiang; Li, Zhihui; Li, Jiabing; Lu, Tao; Yan, Fangrong

2015-01-01

BACKGROUND Personalized cancer treatments depend on the determination of a patient's genetic status according to known genetic profiles for which targeted treatments exist. Such genetic profiles must be scientifically validated before they is applied to general patient population. Reproducibility of findings that support such genetic profiles is a fundamental challenge in validation studies. The percentage of overlapping genes (POG) criterion and derivative methods produce unstable and misleading results. Furthermore, in a complex disease, comparisons between different tumor subtypes can produce high POG scores that do not capture the consistencies in the functions. RESULTS We focused on the quality rather than the quantity of the overlapping genes. We defined the rank value of each gene according to importance or quality by PageRank on basis of a particular topological structure. Then, we used the p-value of the rank-sum of the overlapping genes (PRSOG) to evaluate the quality of reproducibility. Though the POG scores were low in different studies of the same disease, the PRSOG was statistically significant, which suggests that sets of differentially expressed genes might be highly reproducible. CONCLUSIONS Evaluations of eight datasets from breast cancer, lung cancer and four other disorders indicate that quality-based PRSOG method performs better than a quantity-based method. Our analysis of the components of the sets of overlapping genes supports the utility of the PRSOG method. PMID:26556852

Malignant pleural mesothelioma and mesothelial hyperplasia: A new molecular tool for the differential diagnosis.

PubMed

Bruno, Rossella; Alì, Greta; Giannini, Riccardo; Proietti, Agnese; Lucchi, Marco; Chella, Antonio; Melfi, Franca; Mussi, Alfredo; Fontanini, Gabriella

2017-01-10

Malignant pleural mesothelioma (MPM) is a rare asbestos related cancer, aggressive and unresponsive to therapies. Histological examination of pleural lesions is the gold standard of MPM diagnosis, although it is sometimes hard to discriminate the epithelioid type of MPM from benign mesothelial hyperplasia (MH).This work aims to define a new molecular tool for the differential diagnosis of MPM, using the expression profile of 117 genes deregulated in this tumour.The gene expression analysis was performed by nanoString System on tumour tissues from 36 epithelioid MPM and 17 MH patients, and on 14 mesothelial pleural samples analysed in a blind way. Data analysis included raw nanoString data normalization, unsupervised cluster analysis by Pearson correlation, non-parametric Mann Whitney U-test and molecular classification by the Uncorrelated Shrunken Centroid (USC) Algorithm.The Mann-Whitney U-test found 35 genes upregulated and 31 downregulated in MPM. The unsupervised cluster analysis revealed two clusters, one composed only of MPM and one only of MH samples, thus revealing class-specific gene profiles. The Uncorrelated Shrunken Centroid algorithm identified two classifiers, one including 22 genes and the other 40 genes, able to properly classify all the samples as benign or malignant using gene expression data; both classifiers were also able to correctly determine, in a blind analysis, the diagnostic categories of all the 14 unknown samples.In conclusion we delineated a diagnostic tool combining molecular data (gene expression) and computational analysis (USC algorithm), which can be applied in the clinical practice for the differential diagnosis of MPM.

Gene expression profiles in peripheral blood mononuclear cells of Chinese nickel refinery workers with high exposures to nickel and control subjects

PubMed Central

Arita, Adriana; Muñoz, Alexandra; Chervona, Yana; Niu, Jingping; Qu, Qingshan; Zhao, Najuan; Ruan, Ye; Kiok, Kathrin; Kluz, Thomas; Sun, Hong; Clancy, Hailey A.; Shamy, Magdy; Costa, Max

2012-01-01

Background Occupational exposure to nickel (Ni) is associated with an increased risk of lung and nasal cancers. Ni compounds exhibit weak mutagenic activity, alter the cell’s epigenetic homeostasis, and activate signaling pathways. However, changes in gene expression associated with Ni exposure have only been investigated in vitro. This study was conducted in a Chinese population to determine whether occupational exposure to Ni was associated with differential gene expression profiles in the peripheral blood mononuclear cells (PBMCs) of Ni-refinery workers when compared to referents. Methods Eight Ni-refinery workers and ten referents were selected. PBMC RNA was extracted and gene expression profiling was performed using Affymetrix exon arrays. Differentially expressed genes between both groups were identified in a global analysis. Results There were a total of 2756 differentially expressed genes (DEG) in the Ni-refinery workers relative to the control subjects (FDR adjusted p<0.05) with 770 up-regulated genes and 1986 down-regulated genes. DNA repair and epigenetic genes were significantly overrepresented (p< 0.0002) among the DEG. Of 31 DNA repair genes, 29 were repressed in the high exposure group and two were overexpressed. Of the 16 epigenetic genes 12 were repressed in the high exposure group and 4 were overexpressed. Conclusions The results of this study indicate that occupational exposure to Ni is associated with alterations in gene expression profiles in PBMCs of subjects. Impact Gene expression may be useful in identifying patterns of deregulation that precede clinical identification of Ni-induced cancers. PMID:23195993

Gene expression profiling of single cells on large-scale oligonucleotide arrays

PubMed Central

Hartmann, Claudia H.; Klein, Christoph A.

2006-01-01

Over the last decade, important insights into the regulation of cellular responses to various stimuli were gained by global gene expression analyses of cell populations. More recently, specific cell functions and underlying regulatory networks of rare cells isolated from their natural environment moved to the center of attention. However, low cell numbers still hinder gene expression profiling of rare ex vivo material in biomedical research. Therefore, we developed a robust method for gene expression profiling of single cells on high-density oligonucleotide arrays with excellent coverage of low abundance transcripts. The protocol was extensively tested with freshly isolated single cells of very low mRNA content including single epithelial, mature and immature dendritic cells and hematopoietic stem cells. Quantitative PCR confirmed that the PCR-based global amplification method did not change the relative ratios of transcript abundance and unsupervised hierarchical cluster analysis revealed that the histogenetic origin of an individual cell is correctly reflected by the gene expression profile. Moreover, the gene expression data from dendritic cells demonstrate that cellular differentiation and pathway activation can be monitored in individual cells. PMID:17071717

Metabolic Pathway Assignment of Plant Genes based on Phylogenetic Profiling–A Feasibility Study

PubMed Central

Weißenborn, Sandra; Walther, Dirk

2017-01-01

Despite many developed experimental and computational approaches, functional gene annotation remains challenging. With the rapidly growing number of sequenced genomes, the concept of phylogenetic profiling, which predicts functional links between genes that share a common co-occurrence pattern across different genomes, has gained renewed attention as it promises to annotate gene functions based on presence/absence calls alone. We applied phylogenetic profiling to the problem of metabolic pathway assignments of plant genes with a particular focus on secondary metabolism pathways. We determined phylogenetic profiles for 40,960 metabolic pathway enzyme genes with assigned EC numbers from 24 plant species based on sequence and pathway annotation data from KEGG and Ensembl Plants. For gene sequence family assignments, needed to determine the presence or absence of particular gene functions in the given plant species, we included data of all 39 species available at the Ensembl Plants database and established gene families based on pairwise sequence identities and annotation information. Aside from performing profiling comparisons, we used machine learning approaches to predict pathway associations from phylogenetic profiles alone. Selected metabolic pathways were indeed found to be composed of gene families of greater than expected phylogenetic profile similarity. This was particularly evident for primary metabolism pathways, whereas for secondary pathways, both the available annotation in different species as well as the abstraction of functional association via distinct pathways proved limiting. While phylogenetic profile similarity was generally not found to correlate with gene co-expression, direct physical interactions of proteins were reflected by a significantly increased profile similarity suggesting an application of phylogenetic profiling methods as a filtering step in the identification of protein-protein interactions. This feasibility study highlights the potential and challenges associated with phylogenetic profiling methods for the detection of functional relationships between genes as well as the need to enlarge the set of plant genes with proven secondary metabolism involvement as well as the limitations of distinct pathways as abstractions of relationships between genes. PMID:29163570

Identifying potential maternal genes of Bombyx mori using digital gene expression profiling

PubMed Central

Xu, Pingzhen

2018-01-01

Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

Modelling gene expression profiles related to prostate tumor progression using binary states

PubMed Central

2013-01-01

Background Cancer is a complex disease commonly characterized by the disrupted activity of several cancer-related genes such as oncogenes and tumor-suppressor genes. Previous studies suggest that the process of tumor progression to malignancy is dynamic and can be traced by changes in gene expression. Despite the enormous efforts made for differential expression detection and biomarker discovery, few methods have been designed to model the gene expression level to tumor stage during malignancy progression. Such models could help us understand the dynamics and simplify or reveal the complexity of tumor progression. Methods We have modeled an on-off state of gene activation per sample then per stage to select gene expression profiles associated to tumor progression. The selection is guided by statistical significance of profiles based on random permutated datasets. Results We show that our method identifies expected profiles corresponding to oncogenes and tumor suppressor genes in a prostate tumor progression dataset. Comparisons with other methods support our findings and indicate that a considerable proportion of significant profiles is not found by other statistical tests commonly used to detect differential expression between tumor stages nor found by other tailored methods. Ontology and pathway analysis concurred with these findings. Conclusions Results suggest that our methodology may be a valuable tool to study tumor malignancy progression, which might reveal novel cancer therapies. PMID:23721350

A Gene Co-Expression Network in Whole Blood of Schizophrenia Patients Is Independent of Antipsychotic-Use and Enriched for Brain-Expressed Genes

PubMed Central

de Jong, Simone; Boks, Marco P. M.; Fuller, Tova F.; Strengman, Eric; Janson, Esther; de Kovel, Carolien G. F.; Ori, Anil P. S.; Vi, Nancy; Mulder, Flip; Blom, Jan Dirk; Glenthøj, Birte; Schubart, Chris D.; Cahn, Wiepke; Kahn, René S.; Horvath, Steve; Ophoff, Roel A.

2012-01-01

Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network. PMID:22761806

Alteration in gene expression profile and oncogenicity of esophageal squamous cell carcinoma by RIZ1 upregulation.

PubMed

Dong, Shang-Wen; Li, Dong; Xu, Cong; Sun, Pei; Wang, Yuan-Guo; Zhang, Peng

2013-10-07

To investigate the effect of retinoblastoma protein-interacting zinc finger gene 1 (RIZ1) upregulation in gene expression profile and oncogenicity of human esophageal squamous cell carcinoma (ESCC) cell line TE13. TE13 cells were transfected with pcDNA3.1(+)/RIZ1 and pcDNA3.1(+). Changes in gene expression profile were screened and the microarray results were confirmed by reverse transcription-polymerase chain reaction (RT-PCR). Nude mice were inoculated with TE13 cells to establish ESCC xenografts. After two weeks, the inoculated mice were randomly divided into three groups. Tumors were injected with normal saline, transfection reagent pcDNA3.1(+) and transfection reagent pcDNA3.1(+)/RIZ1, respectively. Tumor development was quantified, and changes in gene expression of RIZ1 transfected tumors were detected by RT-PCR and Western blotting. DNA microarray data showed that RIZ1 transfection induced widespread changes in gene expression profile of cell line TE13, with 960 genes upregulated and 1163 downregulated. Treatment of tumor xenografts with RIZ1 recombinant plasmid significantly inhibited tumor growth, decreased tumor size, and increased expression of RIZ1 mRNA compared to control groups. The changes in gene expression profile were also observed in vivo after RIZ1 transfection. Most of the differentially expressed genes were associated with cell development, supervision of viral replication, lymphocyte costimulatory and immune system development in esophageal cells. RIZ1 gene may be involved in multiple cancer pathways, such as cytokine receptor interaction and transforming growth factor beta signaling. The development and progression of esophageal cancer are related to the inactivation of RIZ1. Virus infection may also be an important factor.

Phytophthora megakarya and P. palmivora, Causal Agents of Black Pod Rot, Induce Similar Plant Defense Responses Late during Infection of Susceptible Cacao Pods

PubMed Central

Ali, Shahin S.; Shao, Jonathan; Lary, David J.; Strem, Mary D.; Meinhardt, Lyndel W.; Bailey, Bryan A.

2017-01-01

Phytophthora megakarya (Pmeg) and Phytophthora palmivora (Ppal) cause black pod rot of Theobroma cacao L. (cacao). Of these two clade 4 species, Pmeg is more virulent and is displacing Ppal in many cacao production areas in Africa. Symptoms and species specific sporangia production were compared when the two species were co-inoculated onto pod pieces in staggered 24 h time intervals. Pmeg sporangia were predominantly recovered from pod pieces with unwounded surfaces even when inoculated 24 h after Ppal. On wounded surfaces, sporangia of Ppal were predominantly recovered if the two species were simultaneously applied or Ppal was applied first but not if Pmeg was applied first. Pmeg demonstrated an advantage over Ppal when infecting un-wounded surfaces while Ppal had the advantage when infecting wounded surfaces. RNA-Seq was carried out on RNA isolated from control and Pmeg and Ppal infected pod pieces 3 days post inoculation to assess their abilities to alter/suppress cacao defense. Expression of 4,482 and 5,264 cacao genes was altered after Pmeg and Ppal infection, respectively, with most genes responding to both species. Neural network self-organizing map analyses separated the cacao RNA-Seq gene expression profiles into 24 classes, 6 of which were largely induced in response to infection. Using KEGG analysis, subsets of genes composing interrelated pathways leading to phenylpropanoid biosynthesis, ethylene and jasmonic acid biosynthesis and action, plant defense signal transduction, and endocytosis showed induction in response to infection. A large subset of genes encoding putative Pr-proteins also showed differential expression in response to infection. A subset of 36 cacao genes was used to validate the RNA-Seq expression data and compare infection induced gene expression patterns in leaves and wounded and unwounded pod husks. Expression patterns between RNA-Seq and RT-qPCR were generally reproducible. The level and timing of altered gene expression was influenced by the tissues studied and by wounding. Although, in these susceptible interactions gene expression patterns were similar, some genes did show differential expression in a Phytophthora species dependent manner. The biggest difference was the more intense changes in expression in Ppal inoculated wounded pod pieces further demonstrating its rapid progression when penetrating through wounds. PMID:28261234

Expression Profile of Drug and Nutrient Absorption Related Genes in Madin-Darby Canine Kidney (MDCK) Cells Grown under Differentiation Conditions.

PubMed

Quan, Yong; Jin, Yisheng; Faria, Teresa N; Tilford, Charles A; He, Aiqing; Wall, Doris A; Smith, Ronald L; Vig, Balvinder S

2012-06-18

The expression levels of genes involved in drug and nutrient absorption were evaluated in the Madin-Darby Canine Kidney (MDCK) in vitro drug absorption model. MDCK cells were grown on plastic surfaces (for 3 days) or on Transwell® membranes (for 3, 5, 7, and 9 days). The expression profile of genes including ABC transporters, SLC transporters, and cytochrome P450 (CYP) enzymes was determined using the Affymetrix® Canine GeneChip®. Expression of genes whose probe sets passed a stringent confirmation process was examined. Expression of a few transporter (MDR1, PEPT1 and PEPT2) genes in MDCK cells was confirmed by RT-PCR. The overall gene expression profile was strongly influenced by the type of support the cells were grown on. After 3 days of growth, expression of 28% of the genes was statistically different (1.5-fold cutoff, p < 0.05) between the cells grown on plastic and Transwell® membranes. When cells were differentiated on Transwell® membranes, large changes in gene expression profile were observed during the early stages, which then stabilized after 5-7 days. Only a small number of genes encoding drug absorption related SLC, ABC, and CYP were detected in MDCK cells, and most of them exhibited low hybridization signals. Results from this study provide valuable reference information on endogenous gene expression in MDCK cells that could assist in design of drug-transporter and/or drug-enzyme interaction studies, and help interpret the contributions of various transporters and metabolic enzymes in studies with MDCK cells.

Expression Profile of Drug and Nutrient Absorption Related Genes in Madin-Darby Canine Kidney (MDCK) Cells Grown under Differentiation Conditions

PubMed Central

Quan, Yong; Jin, Yisheng; Faria, Teresa N.; Tilford, Charles A.; He, Aiqing; Wall, Doris A.; Smith, Ronald L.; Vig, Balvinder S.

2012-01-01

The expression levels of genes involved in drug and nutrient absorption were evaluated in the Madin-Darby Canine Kidney (MDCK) in vitro drug absorption model. MDCK cells were grown on plastic surfaces (for 3 days) or on Transwell® membranes (for 3, 5, 7, and 9 days). The expression profile of genes including ABC transporters, SLC transporters, and cytochrome P450 (CYP) enzymes was determined using the Affymetrix® Canine GeneChip®. Expression of genes whose probe sets passed a stringent confirmation process was examined. Expression of a few transporter (MDR1, PEPT1 and PEPT2) genes in MDCK cells was confirmed by RT-PCR. The overall gene expression profile was strongly influenced by the type of support the cells were grown on. After 3 days of growth, expression of 28% of the genes was statistically different (1.5-fold cutoff, p < 0.05) between the cells grown on plastic and Transwell® membranes. When cells were differentiated on Transwell® membranes, large changes in gene expression profile were observed during the early stages, which then stabilized after 5–7 days. Only a small number of genes encoding drug absorption related SLC, ABC, and CYP were detected in MDCK cells, and most of them exhibited low hybridization signals. Results from this study provide valuable reference information on endogenous gene expression in MDCK cells that could assist in design of drug-transporter and/or drug-enzyme interaction studies, and help interpret the contributions of various transporters and metabolic enzymes in studies with MDCK cells. PMID:24300234

De novo transcriptome characterization and gene expression profiling of the desiccation tolerant moss Bryum argenteum following rehydration.

PubMed

Gao, Bei; Zhang, Daoyuan; Li, Xiaoshuang; Yang, Honglan; Zhang, Yuanming; Wood, Andrew J

2015-05-28

The desiccation-tolerant moss Bryum argenteum is an important component of the Biological Soil Crusts (BSCs) found in the Gurbantunggut desert. Desiccation tolerance is defined as the ability to revive from the air dried state. To elucidate the molecular mechanisms related to desiccation tolerance, we employed RNA-Seq and digital gene expression (DGE) technologies to study the genome-wide expression profiles of the dehydration and rehydration processes in this important desert plant. We applied a two-step approach to investigate the gene expression profile upon rehydration in the moss Bryum argenteum using Illumina HiSeq2000 sequencing platform. First, a total of 57,247 transcript assembly contigs (TACs) were obtained from 54.79 million reads by de novo assembly, with an average length of 863 bp and N50 of 1,372 bp. Among the reconstructed TACs, 36,916 (64.5%) revealed similarity with existing protein sequences in the public databases. 23,509 and 21,607 TACs were assigned GO and KEGG annotation information, respectively. Second, samples were taken from 3 hydration stages: desiccated (Dry), rehydrated 2 h (R2) and rehydrated 24 h (R24), and DEG libraries were constructed for Differentially Expressed Genes (DEGs) discovery. 4,081 and 6,709 DEGs were identified in R2 and R24, compared with Dry, respectively. Compared to the desiccated sample, up-regulated genes after two hours of hydration are primarily related to stress responses. GO function enrichment network, EKGG metabolic pathway and MapMan analysis supports the idea of the rapid recovery of photosynthesis after 24 h of rehydration. We identified 770 transcription factors (TFs) which were classified into 50 TF families. 142 TF transcripts were up-regulated upon rehydration including 23 members of the ERF family. In this study, we constructed a pioneering, high-quality reference transcriptome in B. argenteum and generated three DGE libraries to elucidate the changes of gene expression upon rehydration. Expression profiles consistent with the rapid recovery of photosynthesis (at R2) and the re-establishment of a positive carbon balance following rehydration (at R24) were observed. Our study will extend our knowledge of bryophyte transcriptomes and provide further insight into the molecular mechanisms related to rehydration and desiccation-tolerance.

[Differential gene expression profile in ischemic myocardium of Wistar rats with acute myocardial infarction: the study on gene construction, identification and function].

PubMed

Guo, Chun Yu; Yin, Hui Jun; Jiang, Yue Rong; Xue, Mei; Zhang, Lu; Shi, Da Zhuo

2008-06-18

To construct the differential genes expressed profile in the ischemic myocardium tissue reduced from acute myocardial infarction(AMI), and determine the biological functions of target genes. AMI model was generated by ligation of the left anterior descending coronary artery in Wistar rats. Total RNA was extracted from the normal and the ischemic heart tissues under the ligation point 7 days after the operation. Differential gene expression profiles of the two samples were constructed using Long Serial Analysis of Gene Expression(LongSAGE). Real time fluorescence quantitative PCR was used to verify gene expression profile and to identify the expression of 2 functional genes. The activities of enzymes from functional genes were determined by histochemistry. A total of 15,966 tags were screened from the normal and the ischemic LongSAGE maps. The similarities of the sequences were compared using the BLAST algebra in NCBI and 7,665 novel tags were found. In the ischemic tissue 142 genes were significantly changed compared with those in the normal tissue (P<0.05). These differentially expressed genes represented the proteins which might play important roles in the pathways of oxidation and phosphorylation, ATP synthesis and glycolysis. The partial genes identified by LongSAGE were confirmed using real time fluorescence quantitative PCR. Two genes related to energy metabolism, COX5a and ATP5e, were screened and quantified. Expression of two functional genes down-regulated at their mRNA levels and the activities of correlative functional enzymes decreased compared with those in the normal tissue. AMI causes a series of changes in gene expression, in which the abnormal expression of genes related to energy metabolism could be one of the molecular mechanisms of AMI. The intervention of the expressions of COX5a and ATP5e may be a new target for AMI therapy.

Changes in gene expression associated with response to neoadjuvant chemotherapy in breast cancer.

PubMed

Hannemann, Juliane; Oosterkamp, Hendrika M; Bosch, Cathy A J; Velds, Arno; Wessels, Lodewyk F A; Loo, Claudette; Rutgers, Emiel J; Rodenhuis, Sjoerd; van de Vijver, Marc J

2005-05-20

At present, clinically useful markers predicting response of primary breast carcinomas to either doxorubicin-cyclophosphamide (AC) or doxorubicin-docetaxel (AD) are lacking. We investigated whether gene expression profiles of the primary tumor could be used to predict treatment response to either of those chemotherapy regimens. Within a single-institution, randomized, phase II trial, patients with locally advanced breast cancer received six courses of either AC (n = 24) or AD (n = 24) neoadjuvant chemotherapy. Gene expression profiles were generated from core-needle biopsies obtained before treatment and correlated with the response of the primary tumor to the chemotherapy administered. Additionally, pretreatment gene expression profiles were compared with those in tumors remaining after chemotherapy. Ten (20%) of 48 patients showed a (near) pathologic complete remission of the primary tumor after treatment. No gene expression pattern correlating with response could be identified for all patients or for the AC or AD groups separately. The comparison of the pretreatment biopsy and the tumor excised after chemotherapy revealed differences in gene expression in tumors that showed a partial remission but not in tumors that did not respond to chemotherapy. No gene expression profile predicting the response of primary breast carcinomas to AC- or AD-based neoadjuvant chemotherapy could be detected in this interim analysis. More subtle differences in gene expression are likely to be present but can only be reliably identified by studying a larger group of patients. Response of a breast tumor to neoadjuvant chemotherapy results in alterations in gene expression.

Characterizing mutation-expression network relationships in multiple cancers.

PubMed

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.

Gene expression profiling in respond to TBT exposure in small abalone Haliotis diversicolor.

PubMed

Jia, Xiwei; Zou, Zhihua; Wang, Guodong; Wang, Shuhong; Wang, Yilei; Zhang, Ziping

2011-10-01

In this study, we investigated the gene expression profiling of small abalone, Haliotis diversicolor by tributyltin (TBT) exposure using a cDNA microarray containing 2473 unique transcripts. Totally, 107 up-regulated genes and 41 down-regulated genes were found. For further investigation of candidate genes from microarray data and EST analysis, quantitative real-time PCR was performed at 6 h, 24 h, 48 h, 96 h and 192 h TBT exposure. 26 genes were found to be significantly differentially expressed in different time course, 3 of them were unknown. Some gene homologues like cellulose, endo-beta-1,4-glucanase, ferritin subunit 1 and thiolester containing protein II CG7052-PB might be the good biomarker candidate for TBT monitor. The identification of stress response genes and their expression profiles will permit detailed investigation of the defense responses of small abalone genes. Published by Elsevier Ltd.

Gene expression profiles in stage I uterine serous carcinoma in comparison to grade 3 and grade 1 stage I endometrioid adenocarcinoma.

PubMed

Mhawech-Fauceglia, Paulette; Wang, Dan; Kesterson, Joshua; Syriac, Susanna; Clark, Kimberly; Frederick, Peter J; Lele, Shashikant; Liu, Song

2011-03-23

Endometrial cancer is the most common gynecologic malignancy in the developed countries. Clinical studies have shown that early stage uterine serous carcinoma (USC) has outcomes similar to early stage high grade endometrioid adenocarcinoma (EAC-G3) than to early stage low grade endometrioid adenocarcinoma (EAC-G1). However, little is known about the origin of these different clinical outcomes. This study applied the whole genome expression profiling to explore the expression difference of stage I USC (n = 11) relative to stage I EAC-G3 (n = 11) and stage I EAC-G1 (n = 11), respectively. We found that the expression difference between USC and EAC-G3, as measured by the number of differentially expressed genes (DEGs), is consistently less than that found between USC and EAC-G1. Pathway enrichment analyses suggested that DEGs specific to USC vs. EAC-G3 are enriched for genes involved in signaling transduction, while DEGs specific to USC vs. EAC-G1 are enriched for genes involved in cell cycle. Gene expression differences for selected DEGs are confirmed by quantitative RT-PCR with a high validation rate. This data, although preliminary, indicates that stage I USC is genetically similar to stage I EAC-G3 compared to stage I EAC-G1. DEGs identified from this study might provide an insight in to the potential mechanisms that influence the clinical outcome differences between endometrial cancer subtypes. They might also have potential prognostic and therapeutic impacts on patients diagnosed with uterine cancer.

Conditional clustering of temporal expression profiles

PubMed Central

Wang, Ling; Montano, Monty; Rarick, Matt; Sebastiani, Paola

2008-01-01

Background Many microarray experiments produce temporal profiles in different biological conditions but common cluster techniques are not able to analyze the data conditional on the biological conditions. Results This article presents a novel technique to cluster data from time course microarray experiments performed across several experimental conditions. Our algorithm uses polynomial models to describe the gene expression patterns over time, a full Bayesian approach with proper conjugate priors to make the algorithm invariant to linear transformations, and an iterative procedure to identify genes that have a common temporal expression profile across two or more experimental conditions, and genes that have a unique temporal profile in a specific condition. Conclusion We use simulated data to evaluate the effectiveness of this new algorithm in finding the correct number of clusters and in identifying genes with common and unique profiles. We also use the algorithm to characterize the response of human T cells to stimulations of antigen-receptor signaling gene expression temporal profiles measured in six different biological conditions and we identify common and unique genes. These studies suggest that the methodology proposed here is useful in identifying and distinguishing uniquely stimulated genes from commonly stimulated genes in response to variable stimuli. Software for using this clustering method is available from the project home page. PMID:18334028

Stage-specific differential gene expression profiling and functional network analysis during morphogenesis of diphyodont dentition in miniature pigs, Sus Scrofa

PubMed Central

2014-01-01

Background Our current knowledge of tooth development derives mainly from studies in mice, which have only one set of non-replaced teeth, compared with the diphyodont dentition in humans. The miniature pig is also diphyodont, making it a valuable alternative model for understanding human tooth development and replacement. However, little is known about gene expression and function during swine odontogenesis. The goal of this study is to undertake the survey of differential gene expression profiling and functional network analysis during morphogenesis of diphyodont dentition in miniature pigs. The identification of genes related to diphyodont development should lead to a better understanding of morphogenetic patterns and the mechanisms of diphyodont replacement in large animal models and humans. Results The temporal gene expression profiles during early diphyodont development in miniature pigs were detected with the Affymetrix Porcine GeneChip. The gene expression data were further evaluated by ANOVA as well as pathway and STC analyses. A total of 2,053 genes were detected with differential expression. Several signal pathways and 151 genes were then identified through the construction of pathway and signal networks. Conclusions The gene expression profiles indicated that spatio-temporal down-regulation patterns of gene expression were predominant; while, both dynamic activation and inhibition of pathways occurred during the morphogenesis of diphyodont dentition. Our study offers a mechanistic framework for understanding dynamic gene regulation of early diphyodont development and provides a molecular basis for studying teeth development, replacement, and regeneration in miniature pigs. PMID:24498892

Spatial reconstruction of single-cell gene expression data.

PubMed

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.

Gene expression profiles characterize early graft response in living donor small bowel transplantation: a case report.

PubMed

Bradley, S P; Pahari, M; Uknis, M E; Rastellini, C; Cicalese, L

2006-01-01

The cellular and histological events that occur during the regeneration process in invertebrates have been studied in the field of visceral regeneration. We would like to explore the molecular aspects of the regeneration process in the small intestine. The aim of this study was to characterize the gene expression profiles of the intestinal graft to identify which genes may have a role in regeneration of graft tissue posttransplant. In a patient undergoing living related small bowel transplantation (LRSBTx) in our institution, mucosal biopsies were obtained from the recipient intestine and donor graft at the time of transplant and at weeks 1, 2, 3, and 6 posttransplant. Total RNA was isolated from sample biopsies followed by gene expression profiles determined from the replicate samples (n = 3) for each biopsy using the Affymetrix U133 Plus 2.0 Human GeneChip set. Two profiles were obtained from the data. One profile showed rapid increase of 45 genes immediately after transplant by week 1 with significant changes (P < .05) greater than threefold including the chemokine CXC9 and glutathione-related stress factors, GPX2 and GSTA4. The second profile identified 133 genes that were significantly decreased by threefold or greater immediately after transplant week 1, including UCC1, the human homolog of the Ependymin gene. We have identified two gene expression profiles representing early graft responses to small bowel transplantation. These profiles will serve to identify and study those genes whose products may play a role in accelerating tissue regeneration following segmental LRSBTx.

Transcriptome profiling identified differentially expressed genes and pathways associated with tamoxifen resistance in human breast cancer

PubMed Central

Men, Xin; Ma, Jun; Wu, Tong; Pu, Junyi; Wen, Shaojia; Shen, Jianfeng; Wang, Xun; Wang, Yamin; Chen, Chao; Dai, Penggao

2018-01-01

Tamoxifen (TAM) resistance is an important clinical problem in the treatment of breast cancer. In order to identify the mechanism of TAM resistance for estrogen receptor (ER)-positive breast cancer, we screened the transcriptome using RNA-seq and compared the gene expression profiles between the MCF-7 mamma carcinoma cell line and the TAM-resistant cell line TAMR/MCF-7, 52 significant differential expression genes (DEGs) were identified including SLIT2, ROBO, LHX, KLF, VEGFC, BAMBI, LAMA1, FLT4, PNMT, DHRS2, MAOA and ALDH. The DEGs were annotated in the GO, COG and KEGG databases. Annotation of the function of the DEGs in the KEGG database revealed the top three pathways enriched with the most DEGs, including pathways in cancer, the PI3K-AKT pathway, and focal adhesion. Then we compared the gene expression profiles between the Clinical progressive disease (PD) and the complete response (CR) from the cancer genome altas (TCGA). 10 common DEGs were identified through combining the clinical and cellular analysis results. Protein-protein interaction network was applied to analyze the association of ER signal pathway with the 10 DEGs. 3 significant genes (GFRA3, NPY1R and PTPRN2) were closely related to ER related pathway. These significant DEGs regulated many biological activities such as cell proliferation and survival, motility and migration, and tumor cell invasion. The interactions between these DEGs and drug resistance phenomenon need to be further elucidated at a functional level in further studies. Based on our findings, we believed that these DEGs could be therapeutic targets, which can be explored to develop new treatment options. PMID:29423105

PROFILES OF GENE EXPRESSION ASSOCIATED WITH TETRACYCLINE OVER EXPRESSION OF HSP70 IN MCF-7 BREAST CANCER CELLS

EPA Science Inventory

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...

A hierarchical approach employing metabolic and gene expression profiles to identify the pathways that confer cytotoxicity in HepG2 cells

PubMed Central

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

Molecular Phenotypes Distinguish Patients with Relatively Stable from Progressive Idiopathic Pulmonary Fibrosis (IPF)

PubMed Central

Boon, Kathy; Bailey, Nathaniel W.; Yang, Jun; Steel, Mark P.; Groshong, Steve; Kervitsky, Dolly; Brown, Kevin K.; Schwarz, Marvin I.; Schwartz, David A.

2009-01-01

Background Idiopathic pulmonary fibrosis (IPF) is a progressive, chronic interstitial lung disease that is unresponsive to current therapy and often leads to death. However, the rate of disease progression differs among patients. We hypothesized that comparing the gene expression profiles between patients with stable disease and those in which the disease progressed rapidly will lead to biomarker discovery and contribute to the understanding of disease pathogenesis. Methodology and Principal Findings To begin to address this hypothesis, we applied Serial Analysis of Gene Expression (SAGE) to generate lung expression profiles from diagnostic surgical lung biopsies in 6 individuals with relatively stable (or slowly progressive) IPF and 6 individuals with progressive IPF (based on changes in DLCO and FVC over 12 months). Our results indicate that this comprehensive lung IPF SAGE transcriptome is distinct from normal lung tissue and other chronic lung diseases. To identify candidate markers of disease progression, we compared the IPF SAGE profiles in stable and progressive disease, and identified a set of 102 transcripts that were at least 5-fold up regulated and a set of 89 transcripts that were at least 5-fold down regulated in the progressive group (P-value≤0.05). The over expressed genes included surfactant protein A1, two members of the MAPK-EGR-1-HSP70 pathway that regulate cigarette-smoke induced inflammation, and Plunc (palate, lung and nasal epithelium associated), a gene not previously implicated in IPF. Interestingly, 26 of the up regulated genes are also increased in lung adenocarcinomas and have low or no expression in normal lung tissue. More importantly, we defined a SAGE molecular expression signature of 134 transcripts that sufficiently distinguished relatively stable from progressive IPF. Conclusions These findings indicate that molecular signatures from lung parenchyma at the time of diagnosis could prove helpful in predicting the likelihood of disease progression or possibly understanding the biological activity of IPF. PMID:19347046

Establishment of a New Quality Control and Vaccine Safety Test for Influenza Vaccines and Adjuvants Using Gene Expression Profiling

PubMed Central

Momose, Haruka; Mizukami, Takuo; Kuramitsu, Madoka; Takizawa, Kazuya; Masumi, Atsuko; Araki, Kumiko; Furuhata, Keiko; Yamaguchi, Kazunari; Hamaguchi, Isao

2015-01-01

We have previously identified 17 biomarker genes which were upregulated by whole virion influenza vaccines, and reported that gene expression profiles of these biomarker genes had a good correlation with conventional animal safety tests checking body weight and leukocyte counts. In this study, we have shown that conventional animal tests showed varied and no dose-dependent results in serially diluted bulk materials of influenza HA vaccines. In contrast, dose dependency was clearly shown in the expression profiles of biomarker genes, demonstrating higher sensitivity of gene expression analysis than the current animal safety tests of influenza vaccines. The introduction of branched DNA based-concurrent expression analysis could simplify the complexity of multiple gene expression approach, and could shorten the test period from 7 days to 3 days. Furthermore, upregulation of 10 genes, Zbp1, Mx2, Irf7, Lgals9, Ifi47, Tapbp, Timp1, Trafd1, Psmb9, and Tap2, was seen upon virosomal-adjuvanted vaccine treatment, indicating that these biomarkers could be useful for the safety control of virosomal-adjuvanted vaccines. In summary, profiling biomarker gene expression could be a useful, rapid, and highly sensitive method of animal safety testing compared with conventional methods, and could be used to evaluate the safety of various types of influenza vaccines, including adjuvanted vaccine. PMID:25909814

Microarray evaluation of gene expression profiles in inflamed and healthy human dental pulp: the role of IL1beta and CD40 in pulp inflammation.

PubMed

Gatta, V; Zizzari, V L; Dd ' Amico, V; Salini, L; D' Aurora, M; Franchi, S; Antonucci, I; Sberna, M T; Gherlone, E; Stuppia, L; Tetè, S

2012-01-01

Dental pulp undergoes a number of changes passing from healthy status to inflammation due to deep decay. These changes are regulated by several genes resulting differently expressed in inflamed and healthy dental pulp, and the knowledge of the processes underlying this differential expression is of great relevance in the identification of the pathogenesis of the disease. In this study, the gene expression profile of inflamed and healthy dental pulps were compared by microarray analysis, and data obtained were analyzed by Ingenuity Pathway Analysis (IPA) software. This analysis allows to focus on a variety of genes, typically expressed in inflamed tissues. The comparison analysis showed an increased expression of several genes in inflamed pulp, among which IL1β and CD40 resulted of particular interest. These results indicate that gene expression profile of human dental pulp in different physiological and pathological conditions may become an useful tool for improving our knowledge about processes regulating pulp inflammation.

Single cell gene expression profiling of cortical osteoblast lineage cells.

PubMed

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.

TANDEM: a two-stage approach to maximize interpretability of drug response models based on multiple molecular data types.

PubMed

Aben, Nanne; Vis, Daniel J; Michaut, Magali; Wessels, Lodewyk F A

2016-09-01

Clinical response to anti-cancer drugs varies between patients. A large portion of this variation can be explained by differences in molecular features, such as mutation status, copy number alterations, methylation and gene expression profiles. We show that the classic approach for combining these molecular features (Elastic Net regression on all molecular features simultaneously) results in models that are almost exclusively based on gene expression. The gene expression features selected by the classic approach are difficult to interpret as they often represent poorly studied combinations of genes, activated by aberrations in upstream signaling pathways. To utilize all data types in a more balanced way, we developed TANDEM, a two-stage approach in which the first stage explains response using upstream features (mutations, copy number, methylation and cancer type) and the second stage explains the remainder using downstream features (gene expression). Applying TANDEM to 934 cell lines profiled across 265 drugs (GDSC1000), we show that the resulting models are more interpretable, while retaining the same predictive performance as the classic approach. Using the more balanced contributions per data type as determined with TANDEM, we find that response to MAPK pathway inhibitors is largely predicted by mutation data, while predicting response to DNA damaging agents requires gene expression data, in particular SLFN11 expression. TANDEM is available as an R package on CRAN (for more information, see http://ccb.nki.nl/software/tandem). m.michaut@nki.nl or l.wessels@nki.nl 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.

Application of Gene Expression Trajectories Initiated from ErbB Receptor Activation Highlights the Dynamics of Divergent Promoter Usage.

PubMed

Carbajo, Daniel; Magi, Shigeyuki; Itoh, Masayoshi; Kawaji, Hideya; Lassmann, Timo; Arner, Erik; Forrest, Alistair R R; Carninci, Piero; Hayashizaki, Yoshihide; Daub, Carsten O; Okada-Hatakeyama, Mariko; Mar, Jessica C

2015-01-01

Understanding how cells use complex transcriptional programs to alter their fate in response to specific stimuli is an important question in biology. For the MCF-7 human breast cancer cell line, we applied gene expression trajectory models to identify the genes involved in driving cell fate transitions. We modified trajectory models to account for the scenario where cells were exposed to different stimuli, in this case epidermal growth factor and heregulin, to arrive at different cell fates, i.e. proliferation and differentiation respectively. Using genome-wide CAGE time series data collected from the FANTOM5 consortium, we identified the sets of promoters that were involved in the transition of MCF-7 cells to their specific fates versus those with expression changes that were generic to both stimuli. Of the 1,552 promoters identified, 1,091 had stimulus-specific expression while 461 promoters had generic expression profiles over the time course surveyed. Many of these stimulus-specific promoters mapped to key regulators of the ERK (extracellular signal-regulated kinases) signaling pathway such as FHL2 (four and a half LIM domains 2). We observed that in general, generic promoters peaked in their expression early on in the time course, while stimulus-specific promoters tended to show activation of their expression at a later stage. The genes that mapped to stimulus-specific promoters were enriched for pathways that control focal adhesion, p53 signaling and MAPK signaling while generic promoters were enriched for cell death, transcription and the cell cycle. We identified 162 genes that were controlled by an alternative promoter during the time course where a subset of 37 genes had separate promoters that were classified as stimulus-specific and generic. The results of our study highlighted the degree of complexity involved in regulating a cell fate transition where multiple promoters mapping to the same gene can demonstrate quite divergent expression profiles.

Defining the Human Macula Transcriptome and Candidate Retinal Disease Genes UsingEyeSAGE

PubMed Central

Rickman, Catherine Bowes; Ebright, Jessica N.; Zavodni, Zachary J.; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P.; Wistow, Graeme; Boon, Kathy; Hauser, Michael A.

2009-01-01

Purpose To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Methods Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Results Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. Conclusions The EyeSAGE database, combining three different gene-profiling platforms including the authors’ multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions. PMID:16723438

Defining the human macula transcriptome and candidate retinal disease genes using EyeSAGE.

PubMed

Bowes Rickman, Catherine; Ebright, Jessica N; Zavodni, Zachary J; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P; Wistow, Graeme; Boon, Kathy; Hauser, Michael A

2006-06-01

To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. The EyeSAGE database, combining three different gene-profiling platforms including the authors' multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions.

GENE EXPRESSION PROFILES IN ARSENIC-TREATED MCF-7 BREAST CANCER CELLS EXPRESSING DIFFERENT LEVELS OF HSP70

EPA Science Inventory

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...

Molecular Profile of Peripheral Blood Mononuclear Cells from Patients with Rheumatoid Arthritis

PubMed Central

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

Prediction of miRNA-mRNA associations in Alzheimer's disease mice using network topology.

PubMed

Noh, Haneul; Park, Charny; Park, Soojun; Lee, Young Seek; Cho, Soo Young; Seo, Hyemyung

2014-08-03

Little is known about the relationship between miRNA and mRNA expression in Alzheimer's disease (AD) at early- or late-symptomatic stages. Sequence-based target prediction algorithms and anti-correlation profiles have been applied to predict miRNA targets using omics data, but this approach often leads to false positive predictions. Here, we applied the joint profiling analysis of mRNA and miRNA expression levels to Tg6799 AD model mice at 4 and 8 months of age using a network topology-based method. We constructed gene regulatory networks and used the PageRank algorithm to predict significant interactions between miRNA and mRNA. In total, 8 cluster modules were predicted by the transcriptome data for co-expression networks of AD pathology. In total, 54 miRNAs were identified as being differentially expressed in AD. Among these, 50 significant miRNA-mRNA interactions were predicted by integrating sequence target prediction, expression analysis, and the PageRank algorithm. We identified a set of miRNA-mRNA interactions that were changed in the hippocampus of Tg6799 AD model mice. We determined the expression levels of several candidate genes and miRNA. For functional validation in primary cultured neurons from Tg6799 mice (MT) and littermate (LM) controls, the overexpression of ARRDC3 enhanced PPP1R3C expression. ARRDC3 overexpression showed the tendency to decrease the expression of miR139-5p and miR3470a in both LM and MT primary cells. Pathological environment created by Aβ treatment increased the gene expression of PPP1R3C and Sfpq but did not significantly alter the expression of miR139-5p or miR3470a. Aβ treatment increased the promoter activity of ARRDC3 gene in LM primary cells but not in MT primary cells. Our results demonstrate AD-specific changes in the miRNA regulatory system as well as the relationship between the expression levels of miRNAs and their targets in the hippocampus of Tg6799 mice. These data help further our understanding of the function and mechanism of various miRNAs and their target genes in the molecular pathology of AD.

Identifying arsenic trioxide (ATO) functions in leukemia cells by using time series gene expression profiles.

PubMed

Yang, Hong; Lin, Shan; Cui, Jingru

2014-02-10

Arsenic trioxide (ATO) is presently the most active single agent in the treatment of acute promyelocytic leukemia (APL). In order to explore the molecular mechanism of ATO in leukemia cells with time series, we adopted bioinformatics strategy to analyze expression changing patterns and changes in transcription regulation modules of time series genes filtered from Gene Expression Omnibus database (GSE24946). We totally screened out 1847 time series genes for subsequent analysis. The KEGG (Kyoto encyclopedia of genes and genomes) pathways enrichment analysis of these genes showed that oxidative phosphorylation and ribosome were the top 2 significantly enriched pathways. STEM software was employed to compare changing patterns of gene expression with assigned 50 expression patterns. We screened out 7 significantly enriched patterns and 4 tendency charts of time series genes. The result of Gene Ontology showed that functions of times series genes mainly distributed in profiles 41, 40, 39 and 38. Seven genes with positive regulation of cell adhesion function were enriched in profile 40, and presented the same first increased model then decreased model as profile 40. The transcription module analysis showed that they mainly involved in oxidative phosphorylation pathway and ribosome pathway. Overall, our data summarized the gene expression changes in ATO treated K562-r cell lines with time and suggested that time series genes mainly regulated cell adhesive. Furthermore, our result may provide theoretical basis of molecular biology in treating acute promyelocytic leukemia. Copyright © 2013 Elsevier B.V. All rights reserved.

Changes in global gene expression profiles induced by HPV 16 E6 oncoprotein variants in cervical carcinoma C33-A cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zacapala-Gómez, Ana Elvira, E-mail: zak_ana@yahoo.com.mx; Del Moral-Hernández, Oscar, E-mail: odelmoralh@gmail.com; Villegas-Sepúlveda, Nicolás, E-mail: nvillega@cinvestav.mx

We analyzed the effects of the expression of HPV 16 E6 oncoprotein variants (AA-a, AA-c, E-A176/G350, E-C188/G350, E-G350), and the E-Prototype in global gene expression profiles in an in vitro model. E6 gene was cloned into an expression vector fused to GFP and was transfected in C33-A cells. Affymetrix GeneChip Human Transcriptome Array 2.0 platform was used to analyze the expression of over 245,000 coding transcripts. We found that HPV16 E6 variants altered the expression of 387 different genes in comparison with E-Prototype. The altered genes are involved in cellular processes related to the development of cervical carcinoma, such asmore » adhesion, angiogenesis, apoptosis, differentiation, cell cycle, proliferation, transcription and protein translation. Our results show that polymorphic changes in HPV16 E6 natural variants are sufficient to alter the overall gene expression profile in C33-A cells, explaining in part the observed differences in oncogenic potential of HPV16 variants. - Highlights: • Amino acid changes in HPV16 E6 variants modulate the transciption of specific genes. • This is the first comparison of global gene expression profile of HPV 16 E6 variants. • Each HPV 16 E6 variant appears to have its own molecular signature.« less

Arabidopsis Gene Family Profiler (aGFP)--user-oriented transcriptomic database with easy-to-use graphic interface.

PubMed

Dupl'áková, Nikoleta; Renák, David; Hovanec, Patrik; Honysová, Barbora; Twell, David; Honys, David

2007-07-23

Microarray technologies now belong to the standard functional genomics toolbox and have undergone massive development leading to increased genome coverage, accuracy and reliability. The number of experiments exploiting microarray technology has markedly increased in recent years. In parallel with the rapid accumulation of transcriptomic data, on-line analysis tools are being introduced to simplify their use. Global statistical data analysis methods contribute to the development of overall concepts about gene expression patterns and to query and compose working hypotheses. More recently, these applications are being supplemented with more specialized products offering visualization and specific data mining tools. We present a curated gene family-oriented gene expression database, Arabidopsis Gene Family Profiler (aGFP; http://agfp.ueb.cas.cz), which gives the user access to a large collection of normalised Affymetrix ATH1 microarray datasets. The database currently contains NASC Array and AtGenExpress transcriptomic datasets for various tissues at different developmental stages of wild type plants gathered from nearly 350 gene chips. The Arabidopsis GFP database has been designed as an easy-to-use tool for users needing an easily accessible resource for expression data of single genes, pre-defined gene families or custom gene sets, with the further possibility of keyword search. Arabidopsis Gene Family Profiler presents a user-friendly web interface using both graphic and text output. Data are stored at the MySQL server and individual queries are created in PHP script. The most distinguishable features of Arabidopsis Gene Family Profiler database are: 1) the presentation of normalized datasets (Affymetrix MAS algorithm and calculation of model-based gene-expression values based on the Perfect Match-only model); 2) the choice between two different normalization algorithms (Affymetrix MAS4 or MAS5 algorithms); 3) an intuitive interface; 4) an interactive "virtual plant" visualizing the spatial and developmental expression profiles of both gene families and individual genes. Arabidopsis GFP gives users the possibility to analyze current Arabidopsis developmental transcriptomic data starting with simple global queries that can be expanded and further refined to visualize comparative and highly selective gene expression profiles.

Skin transcriptome profiles associated with coat color in sheep

PubMed Central

2013-01-01

Background Previous molecular genetic studies of physiology and pigmentation of sheep skin have focused primarily on a limited number of genes and proteins. To identify additional genes that may play important roles in coat color regulation, Illumina sequencing technology was used to catalog global gene expression profiles in skin of sheep with white versus black coat color. Results There were 90,006 and 74,533 unigenes assembled from the reads obtained from white and black sheep skin, respectively. Genes encoding for the ribosomal proteins and keratin associated proteins were most highly expressed. A total of 2,235 known genes were differentially expressed in black versus white sheep skin, with 479 genes up-regulated and 1,756 genes down-regulated. A total of 845 novel genes were differentially expressed in black versus white sheep skin, consisting of 107 genes which were up-regulated (including 2 highly expressed genes exclusively expressed in black sheep skin) and 738 genes that were down-regulated. There was also a total of 49 known coat color genes expressed in sheep skin, from which 13 genes showed higher expression in black sheep skin. Many of these up-regulated genes, such as DCT, MATP, TYR and TYRP1, are members of the components of melanosomes and their precursor ontology category. Conclusion The white and black sheep skin transcriptome profiles obtained provide a valuable resource for future research to understand the network of gene expression controlling skin physiology and melanogenesis in sheep. PMID:23758853

Influence of white spot syndrome virus infection on hepatopancreas gene expression of `Huanghai No. 2' shrimp ( Fenneropenaeus chinensis)

NASA Astrophysics Data System (ADS)

Meng, Xianhong; Shi, Xiaoli; Kong, Jie; Luan, Sheng; Luo, Kun; Cao, Baoxiang; Liu, Ning; Lu, Xia; Li, Xupeng; Deng, Kangyu; Cao, Jiawang; Zhang, Yingxue; Zhang, Hengheng

2017-10-01

To elucidate the molecular response of shrimp hepatopancreas to white spot syndrome virus (WSSV) infection, microarray was applied to investigate the differentially expressed genes in the hepatopancreas of `Huanghai No. 2' ( Fenneropenaeus chinensis). A total of 59137 unigenes were designed onto a custom-made 60K Agilent chip. After infection, the gene expression profiles in the hepatopancreas of the shrimp with a lower viral load at early (48-96 h), peak (168-192 h) and late (264-288 h) infection phases were analyzed. Of 18704 differentially expressed genes, 6412 were annotated. In total, 5453 differentially expressed genes (1916 annotated) expressed at all three phases, and most of the annotated were either up- or down-regulated continuously. These genes function diversely in, for example, immune response, cytoskeletal system, signal transduction, stress resistance, protein synthesis and processing, metabolism among others. Some of the immune-related genes, including antilipopolysaccharide factor, Kazal-type proteinase inhibitor, C-type lectin and serine protease encoding genes, were up-regulated after WSSV infection. These genes have been reported to be involved in the anti-WSSV responses. The expression of genes related to the cytoskeletal system, including β-actin and myosin but without tubulin genes, were down-regulated after WSSV infection. Astakine was found for the first time in the WSSV-infected F. chinensis. To further confirm the expression of differentially expressed genes, quantitative real-time PCR was performed to test the expression of eight randomly selected genes and verified the reliability and accuracy of the microarray expression analysis. The data will provide valuable information to understanding the immune mechanism of shrimp's response to WSSV.

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...

Selection and Validation of Reference Genes for qRT-PCR Expression Analysis of Candidate Genes Involved in Olfactory Communication in the Butterfly Bicyclus anynana

PubMed Central

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M.

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes. PMID:25793735

Selection and validation of reference genes for qRT-PCR expression analysis of candidate genes involved in olfactory communication in the butterfly Bicyclus anynana.

PubMed

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes.

Synergistic and Antagonistic Interplay between Myostatin Gene Expression and Physical Activity Levels on Gene Expression Patterns in Triceps Brachii Muscles of C57/BL6 Mice

PubMed Central

Caetano-Anollés, Kelsey; Mishra, Sanjibita; Rodriguez-Zas, Sandra L.

2015-01-01

Levels of myostatin expression and physical activity have both been associated with transcriptome dysregulation and skeletal muscle hypertrophy. The transcriptome of triceps brachii muscles from male C57/BL6 mice corresponding to two genotypes (wild-type and myostatin-reduced) under two conditions (high and low physical activity) was characterized using RNA-Seq. Synergistic and antagonistic interaction and ortholog modes of action of myostatin genotype and activity level on genes and gene pathways in this skeletal muscle were uncovered; 1,836, 238, and 399 genes exhibited significant (FDR-adjusted P-value < 0.005) activity-by-genotype interaction, genotype and activity effects, respectively. The most common differentially expressed profiles were (i) inactive myostatin-reduced relative to active and inactive wild-type, (ii) inactive myostatin-reduced and active wild-type, and (iii) inactive myostatin-reduced and inactive wild-type. Several remarkable genes and gene pathways were identified. The expression profile of nascent polypeptide-associated complex alpha subunit (Naca) supports a synergistic interaction between activity level and myostatin genotype, while Gremlin 2 (Grem2) displayed an antagonistic interaction. Comparison between activity levels revealed expression changes in genes encoding for structural proteins important for muscle function (including troponin, tropomyosin and myoglobin) and for fatty acid metabolism (some linked to diabetes and obesity, DNA-repair, stem cell renewal, and various forms of cancer). Conversely, comparison between genotype groups revealed changes in genes associated with G1-to-S-phase transition of the cell cycle of myoblasts and the expression of Grem2 proteins that modulate the cleavage of the myostatin propeptide. A number of myostatin-feedback regulated gene products that are primarily regulatory were uncovered, including microRNA impacting central functions and Piezo proteins that make cationic current-controlling mechanosensitive ion channels. These important findings extend hypotheses of myostatin and physical activity master regulation of genes and gene pathways, impacting medical practices and therapies associated with muscle atrophy in humans and companion animal species and genome-enabled selection practices applied to food-production animal species. PMID:25710176

A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors

DTIC Science & Technology

2015-10-01

1 Award Number: W81XWH-10-1-0585 TITLE: A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors...TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors 5a. CONTRACT NUMBER W81XWH...BRCAlike, i.e. not HR deficient and are resistant to PARPis but are sensitive to platinum . These tumors exhibit alterations in another DNA repair

Clinical Application of Prognostic Gene Expression Signature in Fusion Gene-Negative Rhabdomyosarcoma: A Report from the Children's Oncology Group.

PubMed

Hingorani, Pooja; Missiaglia, Edoardo; Shipley, Janet; Anderson, James R; Triche, Timothy J; Delorenzi, Mauro; Gastier-Foster, Julie; Wing, Michele; Hawkins, Douglas S; Skapek, Stephen X

2015-10-15

Pediatric rhabdomyosarcoma (RMS) has two common histologic subtypes: embryonal (ERMS) and alveolar (ARMS). PAX-FOXO1 fusion gene status is a more reliable prognostic marker than alveolar histology, whereas fusion gene-negative (FN) ARMS patients are clinically similar to ERMS patients. A five-gene expression signature (MG5) previously identified two diverse risk groups within the fusion gene-negative RMS (FN-RMS) patients, but this has not been independently validated. The goal of this study was to test whether expression of the MG5 metagene, measured using a technical platform that can be applied to routine pathology material, would correlate with outcome in a new cohort of patients with FN-RMS. Cases were taken from the Children's Oncology Group (COG) D9803 study of children with intermediate-risk RMS, and gene expression profiling for the MG5 genes was performed using the nCounter assay. The MG5 score was correlated with clinical and pathologic characteristics as well as overall and event-free survival. MG5 standardized score showed no significant association with any of the available clinicopathologic variables. The MG5 signature score showed a significant correlation with overall (N = 57; HR, 7.3; 95% CI, 1.9-27.0; P = 0.003) and failure-free survival (N = 57; HR, 6.1; 95% CI, 1.9-19.7; P = 0.002). This represents the first, validated molecular prognostic signature for children with FN-RMS who otherwise have intermediate-risk disease. The capacity to measure the expression of a small number of genes in routine pathology material and apply a simple mathematical formula to calculate the MG5 metagene score provides a clear path toward better risk stratification in future prospective clinical trials. ©2015 American Association for Cancer Research.

Developmental transcriptional profiling reveals key insights into Triticeae reproductive development.

PubMed

Tran, Frances; Penniket, Carolyn; Patel, Rohan V; Provart, Nicholas J; Laroche, André; Rowland, Owen; Robert, Laurian S

2013-06-01

Despite their importance, there remains a paucity of large-scale gene expression-based studies of reproductive development in species belonging to the Triticeae. As a first step to address this deficiency, a gene expression atlas of triticale reproductive development was generated using the 55K Affymetrix GeneChip(®) wheat genome array. The global transcriptional profiles of the anther/pollen, ovary and stigma were analyzed at concurrent developmental stages, and co-expressed as well as preferentially expressed genes were identified. Data analysis revealed both novel and conserved regulatory factors underlying Triticeae floral development and function. This comprehensive resource rests upon detailed gene annotations, and the expression profiles are readily accessible via a web browser. © 2013 Her Majesty the Queen in Right of Canada as represented by the Minister of Agriculture and Agri-Food Canada.

Estimation of Dynamic Systems for Gene Regulatory Networks from Dependent Time-Course Data.

PubMed

Kim, Yoonji; Kim, Jaejik

2018-06-15

Dynamic system consisting of ordinary differential equations (ODEs) is a well-known tool for describing dynamic nature of gene regulatory networks (GRNs), and the dynamic features of GRNs are usually captured through time-course gene expression data. Owing to high-throughput technologies, time-course gene expression data have complex structures such as heteroscedasticity, correlations between genes, and time dependence. Since gene experiments typically yield highly noisy data with small sample size, for a more accurate prediction of the dynamics, the complex structures should be taken into account in ODE models. Hence, this study proposes an ODE model considering such data structures and a fast and stable estimation method for the ODE parameters based on the generalized profiling approach with data smoothing techniques. The proposed method also provides statistical inference for the ODE estimator and it is applied to a zebrafish retina cell network.

RAS oncogene-mediated deregulation of the transcriptome: from molecular signature to function.

PubMed

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.

Transcriptional responses in Lactococcus lactis subsp. cremoris to the changes in oxygen and redox potential during milk acidification.

PubMed

Larsen, N; Brøsted Werner, B; Jespersen, L

2016-08-01

Milk acidification and metabolic activity of the starter cultures are affected by oxygen; however, molecular factors related to the redox changes are poorly defined. The objective of the study was to investigate transcriptional responses in Lactococcus lactis subsp. cremoris CHCCO2 grown in milk to the shifts of oxygen and redox potential (Eh7 ). Transcriptomic studies were performed with the use of Illumina HiSeq 2000 mRNA sequencing and validated by the real-time quantitative PCR. In total 105 differentially expressed genes were assigned functional gene names. Most of the differentially expressed genes were detected during aerobic reduction phase. Upregulated genes were implicated in lactose utilization, glycogen biosynthesis, amino sugar metabolism, oxidation-reduction, pyrimidine biosynthesis and DNA integration processes. Genes of purine nucleotide biosynthesis and genes encoding amino acid, multidrug resistance and ion ABC transporters were mostly downregulated, while oligopeptide transporter genes were reduced during oxygen depletion and induced at minimum Eh7 . Understanding of gene responses in starter cultures to the changes of oxidation-reduction state is important for the better control and reproducibility of dairy fermentations. We applied mRNA sequencing by Illumina HiSeq 2000 to investigate gene expression profile in a dairy strain of Lactococcus lactis subsp. cremoris during milk acidification. Novelty of this study lies in linking transcriptional responses to oxygen depletion and the changes of redox potential with the fermentation kinetics and clarification of molecular factors specifically expressed in milk which might be essential for bacterial performance and the final quality of cheeses. © 2016 The Society for Applied Microbiology.

Primary Characterization of Small RNAs in Symbiotic Nitrogen-Fixing Bacteria.

PubMed

Robledo, Marta; García-Tomsig, Natalia I; Jiménez-Zurdo, José I

2018-01-01

High-throughput transcriptome profiling (RNAseq) has uncovered large and heterogeneous populations of small noncoding RNA species (sRNAs) with potential regulatory roles in bacteria. A large fraction of sRNAs are differentially regulated and rely on protein-assisted antisense interactions to trans-encoded target mRNAs to fine-tune posttranscriptional reprogramming of gene expression in response to external cues. However, annotation and function of sRNAs are still largely overlooked in nonmodel bacteria with complex lifestyles. Here, we describe experimental protocols successfully applied for the accurate annotation, expression profiling and target mRNA identification of trans-acting sRNAs in the nitrogen-fixing α-rhizobium Sinorhizobium meliloti. The protocols presented here can be similarly applied for the characterization of trans-sRNAs in genetically tractable α-proteobacteria of agronomical or clinical relevance interacting with eukaryotic hosts.

Digital gene expression for non-model organisms

PubMed Central

Hong, Lewis Z.; Li, Jun; Schmidt-Küntzel, Anne; Warren, Wesley C.; Barsh, Gregory S.

2011-01-01

Next-generation sequencing technologies offer new approaches for global measurements of gene expression but are mostly limited to organisms for which a high-quality assembled reference genome sequence is available. We present a method for gene expression profiling called EDGE, or EcoP15I-tagged Digital Gene Expression, based on ultra-high-throughput sequencing of 27-bp cDNA fragments that uniquely tag the corresponding gene, thereby allowing direct quantification of transcript abundance. We show that EDGE is capable of assaying for expression in >99% of genes in the genome and achieves saturation after 6–8 million reads. EDGE exhibits very little technical noise, reveals a large (106) dynamic range of gene expression, and is particularly suited for quantification of transcript abundance in non-model organisms where a high-quality annotated genome is not available. In a direct comparison with RNA-seq, both methods provide similar assessments of relative transcript abundance, but EDGE does better at detecting gene expression differences for poorly expressed genes and does not exhibit transcript length bias. Applying EDGE to laboratory mice, we show that a loss-of-function mutation in the melanocortin 1 receptor (Mc1r), recognized as a Mendelian determinant of yellow hair color in many different mammals, also causes reduced expression of genes involved in the interferon response. To illustrate the application of EDGE to a non-model organism, we examine skin biopsy samples from a cheetah (Acinonyx jubatus) and identify genes likely to control differences in the color of spotted versus non-spotted regions. PMID:21844123

Stem cell and neurogenic gene-expression profiles link prostate basal cells to aggressive prostate cancer

PubMed Central

Zhang, Dingxiao; Park, Daechan; Zhong, Yi; Lu, Yue; Rycaj, Kiera; Gong, Shuai; Chen, Xin; Liu, Xin; Chao, Hsueh-Ping; Whitney, Pamela; Calhoun-Davis, Tammy; Takata, Yoko; Shen, Jianjun; Iyer, Vishwanath R.; Tang, Dean G.

2016-01-01

The prostate gland mainly contains basal and luminal cells constructed as a pseudostratified epithelium. Annotation of prostate epithelial transcriptomes provides a foundation for discoveries that can impact disease understanding and treatment. Here we describe a genome-wide transcriptome analysis of human benign prostatic basal and luminal epithelial populations using deep RNA sequencing. Through molecular and biological characterizations, we show that the differential gene-expression profiles account for their distinct functional properties. Strikingly, basal cells preferentially express gene categories associated with stem cells, neurogenesis and ribosomal RNA (rRNA) biogenesis. Consistent with this profile, basal cells functionally exhibit intrinsic stem-like and neurogenic properties with enhanced rRNA transcription activity. Of clinical relevance, the basal cell gene-expression profile is enriched in advanced, anaplastic, castration-resistant and metastatic prostate cancers. Therefore, we link the cell-type-specific gene signatures to aggressive subtypes of prostate cancer and identify gene signatures associated with adverse clinical features. PMID:26924072

Stem cell and neurogenic gene-expression profiles link prostate basal cells to aggressive prostate cancer.

PubMed

Zhang, Dingxiao; Park, Daechan; Zhong, Yi; Lu, Yue; Rycaj, Kiera; Gong, Shuai; Chen, Xin; Liu, Xin; Chao, Hsueh-Ping; Whitney, Pamela; Calhoun-Davis, Tammy; Takata, Yoko; Shen, Jianjun; Iyer, Vishwanath R; Tang, Dean G

2016-02-29

The prostate gland mainly contains basal and luminal cells constructed as a pseudostratified epithelium. Annotation of prostate epithelial transcriptomes provides a foundation for discoveries that can impact disease understanding and treatment. Here we describe a genome-wide transcriptome analysis of human benign prostatic basal and luminal epithelial populations using deep RNA sequencing. Through molecular and biological characterizations, we show that the differential gene-expression profiles account for their distinct functional properties. Strikingly, basal cells preferentially express gene categories associated with stem cells, neurogenesis and ribosomal RNA (rRNA) biogenesis. Consistent with this profile, basal cells functionally exhibit intrinsic stem-like and neurogenic properties with enhanced rRNA transcription activity. Of clinical relevance, the basal cell gene-expression profile is enriched in advanced, anaplastic, castration-resistant and metastatic prostate cancers. Therefore, we link the cell-type-specific gene signatures to aggressive subtypes of prostate cancer and identify gene signatures associated with adverse clinical features.

Electroporation transiently decreases GJB2 (connexin 26) expression in B16/BL6 melanoma cell line.

PubMed

Rangel, Marcelo Monte Mór; Chaible, Lucas Martins; Nagamine, Marcia Kazumi; Mennecier, Gregory; Cogliati, Bruno; de Oliveira, Krishna Duro; Fukumasu, Heidge; Sinhorini, Idércio Luiz; Mir, Lluis Maria; Dagli, Maria Lúcia Zaidan

2015-02-01

Connexins are proteins that form gap junctions. Perturbations in the cell membrane reportedly promote changes in the expression profile of connexins. Electroporation promotes destabilization by applying electrical pulses, and this procedure is used in electrochemotherapy and gene therapy, among others. This in vitro work aimed to study the interference of electroporation on the expression profile of GJB2 (Cx26 gene) and Connexin 26 in melanoma cell line B16/BL6. The techniques of immunocytochemistry, Western blot, and real-time PCR were used. After electroporation, cells showed a transient decrease in GJB2 mRNA. The immunostaining of Cx26 showed no noticeable change after electroporation at different time points. However, Western blot showed a significant reduction in Cx26 30 min after electroporation. Our results showed that electroporation interferes transiently in the expression of Connexin 26 in melanoma and are consistent with the idea that electroporation is a process of intense stress that promotes cell homeostatic imbalance and results in disruption of cell physiological processes such as transcription and translation.

The Prediction of Drug-Disease Correlation Based on Gene Expression Data.

PubMed

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.

Temporal Changes in Gene Expression in Rainbow Trout Exposed to Ethynyl Estradiol*

PubMed Central

Skillman, Ann D.; Small, Jack A.; Schultz, Irvin R.

2007-01-01

We examined changes in the genomic response during continuous exposure to the xenoestrogen ethynylestradiol. Isogenic rainbow trout Oncorhynchus mykiss were exposed to nominal concentrations of 100 ng/L ethynyl estradiol (EE2) for a period of three weeks. At fixed time points within the exposure, fish were euthanized, livers harvested and RNA extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Salmonid array (GRASP project, University of Victoria, Canada) spotted with 16,000 cDNAs. The slides were scanned to measure abundance of a given transcript in each sample relative to controls. Data were analyzed via Genespring (Silicon Genetics) to identify a list of up and down regulated genes, and to determine gene clustering patterns that can be used as “expression signatures”. Gene ontology was determined using the annotation available from the GRASP website. Our analysis indicates each exposure time period generated specific gene expression profiles. Changes in gene expression were best understood by grouping genes by their gene expression profiles rather than examining fold change at a particular time point. Many of the genes commonly used as biomarkers of exposure to xenoestrogens were not induced initially and did not have gene expression profiles typical of the majority of genes with altered expression. PMID:17215170

Temporal changes in gene expression in rainbow trout exposed to ethynyl estradiol.

PubMed

Hook, Sharon E; Skillman, Ann D; Small, Jack A; Schultz, Irvin R

2007-02-01

We examined changes in the genomic response during continuous exposure to the xenoestrogen ethynyl estradiol. Isogenic rainbow trout Oncorhynchus mykiss were exposed to nominal concentrations of 100 ng/L ethynyl estradiol (EE2) for a period of 3 weeks. At fixed time points within the exposure, fish were euthanized, livers harvested and RNA extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Salmonid array (GRASP project, University of Victoria, Canada) spotted with 16,000 cDNAs. The slides were scanned to measure abundance of a given transcript in each sample relative to controls. Data were analyzed via Genespring (Silicon Genetics) to identify a list of up and down regulated genes, and to determine gene clustering patterns that can be used as "expression signatures". Gene ontology was determined using the annotation available from the GRASP website. Our analysis indicates each exposure time period generated specific gene expression profiles. Changes in gene expression were best understood by grouping genes by their gene expression profiles rather than examining fold change at a particular time point. Many of the genes commonly used as biomarkers of exposure to xenoestrogens were not induced initially and did not have gene expression profiles typical of the majority of genes with altered expression.

Alteration of gene expression profiling including GPR174 and GNG2 is associated with vasovagal syncope.

PubMed

Huang, Yu-Juan; Zhou, Zai-wei; Xu, Miao; Ma, Qing-wen; Yan, Jing-bin; Wang, Jian-yi; Zhang, Quo-qin; Huang, Min; Bao, Liming

2015-03-01

Vasovagal syncope (VVS) causes accidental harm for susceptible patients. However, pathophysiology of this disorder remains largely unknown. In an effort to understanding of molecular mechanism for VVS, genome-wide gene expression profiling analyses were performed on VVS patients at syncope state. A total of 66 Type 1 VVS child patients and the same number healthy controls were enrolled in this study. Peripheral blood RNAs were isolated from all subjects, of which 10 RNA samples were randomly selected from each groups for gene expression profile analysis using Gene ST 1.0 arrays (Affymetrix). The results revealed that 103 genes were differently expressed between the patients and controls. Significantly, two G-proteins related genes, GPR174 and GNG2 that have not been related to VVS were among the differently expressed genes. The microarray results were confirmed by qRT-PCR in all the tested individuals. Ingenuity pathway analysis and gene ontology annotation study showed that the differently expressed genes are associated with stress response and apoptosis, suggesting that the alteration of some gene expression including G-proteins related genes is associated with VVS. This study provides new insight into the molecular mechanism of VVS and would be helpful to further identify new molecular biomarkers for the disease.

Digital gene expression analysis of corky split vein caused by boron deficiency in 'Newhall' Navel Orange (Citrus sinensis Osbeck) for selecting differentially expressed genes related to vascular hypertrophy.

PubMed

Yang, Cheng-Quan; Liu, Yong-Zhong; An, Ji-Cui; Li, Shuang; Jin, Long-Fei; Zhou, Gao-Feng; Wei, Qing-Jiang; Yan, Hui-Qing; Wang, Nan-Nan; Fu, Li-Na; Liu, Xiao; Hu, Xiao-Mei; Yan, Ting-Shuai; Peng, Shu-Ang

2013-01-01

Corky split vein caused by boron (B) deficiency in 'Newhall' Navel Orange was studied in the present research. The boron-deficient citrus exhibited a symptom of corky split vein in mature leaves. Morphologic and anatomical surveys at four representative phases of corky split veins showed that the symptom was the result of vascular hypertrophy. Digital gene expression (DGE) analysis was performed based on the Illumina HiSeq™ 2000 platform, which was applied to analyze the gene expression profilings of corky split veins at four morphologic phases. Over 5.3 million clean reads per library were successfully mapped to the reference database and more than 22897 mapped genes per library were simultaneously obtained. Analysis of the differentially expressed genes (DEGs) revealed that the expressions of genes associated with cytokinin signal transduction, cell division, vascular development, lignin biosynthesis and photosynthesis in corky split veins were all affected. The expressions of WOL and ARR12 involved in the cytokinin signal transduction pathway were up-regulated at 1(st) phase of corky split vein development. Furthermore, the expressions of some cell cycle genes, CYCs and CDKB, and vascular development genes, WOX4 and VND7, were up-regulated at the following 2(nd) and 3(rd) phases. These findings indicated that the cytokinin signal transduction pathway may play a role in initiating symptom observed in our study.

Gene expression profiling of two distinct neuronal populations in the rodent spinal cord.

PubMed

Ryge, Jesper; Westerdahl, Ann-Charlotte; Alstrøm, Preben; Kiehn, Ole

2008-01-01

In the field of neuroscience microarray gene expression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global gene expression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level. We examine the microarray gene expression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The gene expression profiles of the respective cell populations were obtained from amplified mRNA originating from 50-250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential gene expression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population. We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional differences between these two cell populations in generating and transmitting the motor output in the rodent spinal cord.

Gene Expression Profiling of Two Distinct Neuronal Populations in the Rodent Spinal Cord

PubMed Central

Alstrøm, Preben; Kiehn, Ole

2008-01-01

Background In the field of neuroscience microarray gene expression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global gene expression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level. Methodology/Principal Findings We examine the microarray gene expression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The gene expression profiles of the respective cell populations were obtained from amplified mRNA originating from 50–250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential gene expression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population. Conclusions/Significance We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional differences between these two cell populations in generating and transmitting the motor output in the rodent spinal cord. PMID:18923679

Gene expression profiling of intestinal regeneration in the sea cucumber

PubMed Central

Ortiz-Pineda, Pablo A; Ramírez-Gómez, Francisco; Pérez-Ortiz, Judit; González-Díaz, Sebastián; Santiago-De Jesús, Francisco; Hernández-Pasos, Josue; Del Valle-Avila, Cristina; Rojas-Cartagena, Carmencita; Suárez-Castillo, Edna C; Tossas, Karen; Méndez-Merced, Ana T; Roig-López, José L; Ortiz-Zuazaga, Humberto; García-Arrarás, José E

2009-01-01

Background Among deuterostomes, the regenerative potential is maximally expressed in echinoderms, animals that can quickly replace most injured organs. In particular, sea cucumbers are excellent models for studying organ regeneration since they regenerate their digestive tract after evisceration. However, echinoderms have been sidelined in modern regeneration studies partially because of the lack of genome-wide profiling approaches afforded by modern genomic tools. For the last decade, our laboratory has been using the sea cucumber Holothuria glaberrima to dissect the cellular and molecular events that allow for such amazing regenerative processes. We have already established an EST database obtained from cDNA libraries of normal and regenerating intestine at two different regeneration stages. This database now has over 7000 sequences. Results In the present work we used a custom-made microchip from Agilent with 60-mer probes for these ESTs, to determine the gene expression profile during intestinal regeneration. Here we compared the expression profile of animals at three different intestinal regeneration stages (3-, 7- and 14-days post evisceration) against the profile from normal (uneviscerated) intestines. The number of differentially expressed probes ranged from 70% at p < 0.05 to 39% at p < 0.001. Clustering analyses show specific profiles of expression for early (first week) and late (second week) regeneration stages. We used semiquantitative reverse transcriptase polymerase chain reaction (RT-PCR) to validate the expression profile of fifteen microarray detected differentially expressed genes which resulted in over 86% concordance between both techniques. Most of the differentially expressed ESTs showed no clear similarity to sequences in the databases and might represent novel genes associated with regeneration. However, other ESTs were similar to genes known to be involved in regeneration-related processes, wound healing, cell proliferation, differentiation, morphological plasticity, cell survival, stress response, immune challenge, and neoplastic transformation. Among those that have been validated, cytoskeletal genes, such as actins, and developmental genes, such as Wnt and Hox genes, show interesting expression profiles during regeneration. Conclusion Our findings set the base for future studies into the molecular basis of intestinal regeneration. Moreover, it advances the use of echinoderms in regenerative biology, animals that because of their amazing properties and their key evolutionary position, might provide important clues to the genetic basis of regenerative processes. PMID:19505337

Biochemical characteristics and gene expression profiles of two paralogous luciferases from the Japanese firefly Pyrocoelia atripennis (Coleoptera, Lampyridae, Lampyrinae): insight into the evolution of firefly luciferase genes.

PubMed

Bessho-Uehara, Manabu; Konishi, Kaori; Oba, Yuichi

2017-08-09

Two paralogous genes of firefly luciferase, Luc1 and Luc2, have been isolated from the species in two subfamilies, Luciolinae and Photurinae, of the family Lampyridae. The gene expression profiles have previously been examined only in the species of Luciolinae. Here we isolated Luc1 and Luc2 genes from the Japanese firefly Pyrocoelia atripennis. This is the first report of the presence of both Luc1 and Luc2 genes in the species of the subfamily Lampyrinae and of the exon-intron structure of Luc2 in the family Lampyridae. The luminescence of both gene products peaked at 547 nm under neutral buffer conditions, and the spectrum of Luc1, but not Luc2, was red-shifted under acidic conditions, as observed for Luc2 in the Luciolinae species. The semi-quantitative reverse transcription-polymerase chain reaction suggested that Luc1 was expressed in lanterns of all the stages except eggs, while Luc2 was expressed in the non-lantern bodies of eggs, prepupae, pupae, and female adults. These expression profiles are consistent with those in the Luciolinae species. Considering the distant phylogenetic relationship between Lampyrinae and Luciolinae in Lampyridae, we propose that fireflies generally possess two different luciferase genes and the biochemical properties and gene expression profiles for each paralog are conserved among lampyrid species.

miR-34a screened by miRNA profiling negatively regulates Wnt/β-catenin signaling pathway in Aflatoxin B1 induced hepatotoxicity

PubMed Central

Zhu, Liye; Gao, Jing; Huang, Kunlun; Luo, Yunbo; Zhang, Boyang; Xu, Wentao

2015-01-01

Aflatoxin-B1 (AFB1), a hepatocarcinogenic mycotoxin, was demonstrated to induce the high rate of hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) participate in the regulation of several biological processes in HCC. However, the function of miRNAs in AFB1-induced HCC has received a little attention. Here, we applied Illumina deep sequencing technology for high-throughout profiling of microRNAs in HepG2 cells lines after treatment with AFB1. Analysis of the differential expression profile of miRNAs in two libraries, we identified 9 known miRNAs and 1 novel miRNA which exhibited abnormal expression. KEGG analysis indicated that predicted target genes of differentially expressed miRNAs are involved in cancer-related pathways. Down-regulated of Drosha, DGCR8 and Dicer 1 indicated an impairment of miRNA biogenesis in response to AFB1. miR-34a was up-regulated significantly, down-regulating the expression of Wnt/β-catenin signaling pathway by target gene β-catenin. Anti-miR-34a can significantly relieved the down-regulated β-catenin and its downstream genes, c-myc and Cyclin D1, and the S-phase arrest in cell cycle induced by AFB1 can also be relieved. These results suggested that AFB1 might down-regulate Wnt/β-catenin signaling pathway in HepG2 cells by up-regulating miR-34a, which may involve in the mechanism of liver tumorigenesis. PMID:26567713

Identification of a Novel Reference Gene for Apple Transcriptional Profiling under Postharvest Conditions

PubMed Central

Storch, Tatiane Timm; Pegoraro, Camila; Finatto, Taciane; Quecini, Vera; Rombaldi, Cesar Valmor; Girardi, César Luis

2015-01-01

Reverse Transcription quantitative PCR (RT-qPCR) is one of the most important techniques for gene expression profiling due to its high sensibility and reproducibility. However, the reliability of the results is highly dependent on data normalization, performed by comparisons between the expression profiles of the genes of interest against those of constitutively expressed, reference genes. Although the technique is widely used in fruit postharvest experiments, the transcription stability of reference genes has not been thoroughly investigated under these experimental conditions. Thus, we have determined the transcriptional profile, under these conditions, of three genes commonly used as reference—ACTIN (MdACT), PROTEIN DISULPHIDE ISOMERASE (MdPDI) and UBIQUITIN-CONJUGATING ENZYME E2 (MdUBC)—along with two novel candidates—HISTONE 1 (MdH1) and NUCLEOSSOME ASSEMBLY 1 PROTEIN (MdNAP1). The expression profile of the genes was investigated throughout five experiments, with three of them encompassing the postharvest period and the other two, consisting of developmental and spatial phases. The transcriptional stability was comparatively investigated using four distinct software packages: BestKeeper, NormFinder, geNorm and DataAssist. Gene ranking results for transcriptional stability were similar for the investigated software packages, with the exception of BestKeeper. The classic reference gene MdUBC ranked among the most stably transcribed in all investigated experimental conditions. Transcript accumulation profiles for the novel reference candidate gene MdH1 were stable throughout the tested conditions, especially in experiments encompassing the postharvest period. Thus, our results present a novel reference gene for postharvest experiments in apple and reinforce the importance of checking the transcription profile of reference genes under the experimental conditions of interest. PMID:25774904

Identification of a novel reference gene for apple transcriptional profiling under postharvest conditions.

PubMed

Storch, Tatiane Timm; Pegoraro, Camila; Finatto, Taciane; Quecini, Vera; Rombaldi, Cesar Valmor; Girardi, César Luis

2015-01-01

Reverse Transcription quantitative PCR (RT-qPCR) is one of the most important techniques for gene expression profiling due to its high sensibility and reproducibility. However, the reliability of the results is highly dependent on data normalization, performed by comparisons between the expression profiles of the genes of interest against those of constitutively expressed, reference genes. Although the technique is widely used in fruit postharvest experiments, the transcription stability of reference genes has not been thoroughly investigated under these experimental conditions. Thus, we have determined the transcriptional profile, under these conditions, of three genes commonly used as reference--ACTIN (MdACT), PROTEIN DISULPHIDE ISOMERASE (MdPDI) and UBIQUITIN-CONJUGATING ENZYME E2 (MdUBC)--along with two novel candidates--HISTONE 1 (MdH1) and NUCLEOSSOME ASSEMBLY 1 PROTEIN (MdNAP1). The expression profile of the genes was investigated throughout five experiments, with three of them encompassing the postharvest period and the other two, consisting of developmental and spatial phases. The transcriptional stability was comparatively investigated using four distinct software packages: BestKeeper, NormFinder, geNorm and DataAssist. Gene ranking results for transcriptional stability were similar for the investigated software packages, with the exception of BestKeeper. The classic reference gene MdUBC ranked among the most stably transcribed in all investigated experimental conditions. Transcript accumulation profiles for the novel reference candidate gene MdH1 were stable throughout the tested conditions, especially in experiments encompassing the postharvest period. Thus, our results present a novel reference gene for postharvest experiments in apple and reinforce the importance of checking the transcription profile of reference genes under the experimental conditions of interest.

Dynamics of wound healing signaling as a potential therapeutic target for radiation-induced tissue damage.

PubMed

Chung, Yih-Lin; Pui, Newman N M

2015-01-01

We hypothesized the histone deacetylase inhibitor phenylbutyrate (PB) has beneficial effects on radiation-induced injury by modulating the expression of DNA repair and wound healing genes. Hamsters received a radiosurgical dose of radiation (40 Gy) to the cheek and were treated with varying PB dosing regimens. Gross alteration of the irradiated cheeks, eating function, histological changes, and gene expression during the course of wound healing were compared between treatment groups. Pathological analysis showed decreased radiation-induced mucositis, facilitated epithelial cell growth, and preventing ulcerative wound formation, after short-term PB treatment, but not after vehicle or sustained PB. The radiation-induced wound healing gene expression profile exhibited a sequential transition from the inflammatory and DNA repair phases to the tissue remodeling phase in the vehicle group. Sustained PB treatment resulted in a prolonged wound healing gene expression profile and delayed the wound healing process. Short-term PB shortened the duration of inflammatory cytokine expression, triggered repeated pulsed expression of cell cycle and DNA repair-regulating genes, and promoted earlier oscillatory expression of tissue remodeling genes. Distinct gene expression patterns between sustained and short-term treatment suggest dynamic profiling of wound healing gene expression can be an important part of a biological therapeutic strategy to mitigate radiation-related tissue injury. © 2015 by the Wound Healing Society.

Profiling Pre-MicroRNA and Mature MicroRNA Expressions Using a Single Microarray and Avoiding Separate Sample Preparation

PubMed Central

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

Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects

PubMed Central

2012-01-01

Background Time-course gene expression data such as yeast cell cycle data may be periodically expressed. To cluster such data, currently used Fourier series approximations of periodic gene expressions have been found not to be sufficiently adequate to model the complexity of the time-course data, partly due to their ignoring the dependence between the expression measurements over time and the correlation among gene expression profiles. We further investigate the advantages and limitations of available models in the literature and propose a new mixture model with autoregressive random effects of the first order for the clustering of time-course gene-expression profiles. Some simulations and real examples are given to demonstrate the usefulness of the proposed models. Results We illustrate the applicability of our new model using synthetic and real time-course datasets. We show that our model outperforms existing models to provide more reliable and robust clustering of time-course data. Our model provides superior results when genetic profiles are correlated. It also gives comparable results when the correlation between the gene profiles is weak. In the applications to real time-course data, relevant clusters of coregulated genes are obtained, which are supported by gene-function annotation databases. Conclusions Our new model under our extension of the EMMIX-WIRE procedure is more reliable and robust for clustering time-course data because it adopts a random effects model that allows for the correlation among observations at different time points. It postulates gene-specific random effects with an autocorrelation variance structure that models coregulation within the clusters. The developed R package is flexible in its specification of the random effects through user-input parameters that enables improved modelling and consequent clustering of time-course data. PMID:23151154

Lex-SVM: exploring the potential of exon expression profiling for disease classification.

PubMed

Yuan, Xiongying; Zhao, Yi; Liu, Changning; Bu, Dongbo

2011-04-01

Exon expression profiling technologies, including exon arrays and RNA-Seq, measure the abundance of every exon in a gene. Compared with gene expression profiling technologies like 3' array, exon expression profiling technologies could detect alterations in both transcription and alternative splicing, therefore they are expected to be more sensitive in diagnosis. However, exon expression profiling also brings higher dimension, more redundancy, and significant correlation among features. Ignoring the correlation structure among exons of a gene, a popular classification method like L1-SVM selects exons individually from each gene and thus is vulnerable to noise. To overcome this limitation, we present in this paper a new variant of SVM named Lex-SVM to incorporate correlation structure among exons and known splicing patterns to promote classification performance. Specifically, we construct a new norm, ex-norm, including our prior knowledge on exon correlation structure to regularize the coefficients of a linear SVM. Lex-SVM can be solved efficiently using standard linear programming techniques. The advantage of Lex-SVM is that it can select features group-wisely, force features in a subgroup to take equal weihts and exclude the features that contradict the majority in the subgroup. Experimental results suggest that on exon expression profile, Lex-SVM is more accurate than existing methods. Lex-SVM also generates a more compact model and selects genes more consistently in cross-validation. Unlike L1-SVM selecting only one exon in a gene, Lex-SVM assigns equal weights to as many exons in a gene as possible, lending itself easier for further interpretation.

[Differential expression genes of bone tissues surrounding implants in diabetic rats by gene chip].

PubMed

Wang, Xin-xin; Ma, Yue; Li, Qing; Jiang, Bao-qi; Lan, Jing

2012-10-01

To compare mRNA expression profiles of bone tissues surrounding implants between normal rats and rats with diabetes using microarray technology. Six Wistar rats were randomly selected and divided into normal model group and diabetic group. Diabetic model condition was established by injecting Streptozotocin into peritoneal space. Titanium implants were implanted into the epiphyseal end of the rats' tibia. Bone tissues surrounding implant were harvested and sampled after 3 months to perform comprehensive RNA gene expression profiling, including 17983 for genome-wide association study.GO analysis was used to compare different gene expression and real-time PCR was used to confirm the results on core samples. The results indicated that there were 1084 differential gene expression. In the diabetic model, there were 352 enhanced expression genes, 732 suppressed expression genes. GO analysis involved 1154 different functional type. Osteoblast related gene expressions in bone tissue samples of diabetic rats were decreased, and lipid metabolism pathway related gene expression was increased.

Toxicogenomic analysis of N-nitrosomorpholine induced changes in rat liver: Comparison of genomic and proteomic responses and anchoring to histopathological parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oberemm, A., E-mail: axel.oberemm@bfr.bund.d; Ahr, H.-J.; Bannasch, P.

2009-12-01

A common animal model of chemical hepatocarcinogenesis was used to examine the utility of transcriptomic and proteomic data to identify early biomarkers related to chemically induced carcinogenesis. N-nitrosomorpholine, a frequently used genotoxic model carcinogen, was applied via drinking water at 120 mg/L to male Wistar rats for 7 weeks followed by an exposure-free period of 43 weeks. Seven specimens of each treatment group (untreated control and 120 mg/L N-nitrosomorpholine in drinking water) were sacrificed at nine time points during and after N-nitrosomorpholine treatment. Individual samples from the liver were prepared for histological and toxicogenomic analyses. For histological detection of preneoplasticmore » and neoplastic tissue areas, sections were stained using antibodies against the placental form of glutathione-S-transferase (GST-P). Gene and protein expression profiles of liver tissue homogenates were analyzed using RG-U34A Affymetrix rat gene chips and two-dimensional gel electrophoresis-based proteomics, respectively. In order to compare results obtained by histopathology, transcriptomics and proteomics, GST-P-stained liver sections were evaluated morphometrically, which revealed a parallel time course of the area fraction of preneoplastic lesions and gene plus protein expression patterns. On the transcriptional level, an increase of hepatic GST-P expression was detectable as early as 3 weeks after study onset. Comparing deregulated genes and proteins, eight species were identified which showed a corresponding expression profile on both expression levels. Functional analysis suggests that these genes and corresponding proteins may be useful as biomarkers of early hepatocarcinogenesis.« less

Candidate EDA targets revealed by expression profiling of primary keratinocytes from Tabby mutant mice

PubMed Central

Esibizione, Diana; Cui, Chang-Yi; Schlessinger, David

2009-01-01

EDA, the gene mutated in anhidrotic ectodermal dysplasia, encodes ectodysplasin, a TNF superfamily member that activates NF-kB mediated transcription. To identify EDA target genes, we have earlier used expression profiling to infer genes differentially expressed at various developmental time points in Tabby (Eda-deficient) compared to wild-type mouse skin. To increase the resolution to find genes whose expression may be restricted to epidermal cells, we have now extended studies to primary keratinocyte cultures established from E19 wild-type and Tabby skin. Using microarrays bearing 44,000 gene probes, we found 385 preliminary candidate genes whose expression was significantly affected by Eda loss. By comparing expression profiles to those from Eda-A1 transgenic skin, we restricted the list to 38 “candidate EDA targets”, 14 of which were already known to be expressed in hair follicles or epidermis. We confirmed expression changes for 3 selected genes, Tbx1, Bmp7, and Jag1, both in keratinocytes and in whole skin, by Q-PCR and Western blotting analyses. Thus, by the analysis of keratinocytes, novel candidate pathways downstream of EDA were detected. PMID:18848976

HDACis (class I), cancer stem cell, and phytochemicals: Cancer therapy and prevention implications.

PubMed

Bayat, Sahar; Shekari Khaniani, Mahmoud; Choupani, Jalal; Alivand, Mohammad Reza; Mansoori Derakhshan, Sima

2018-01-01

Epigenetics is independent of the sequence events that physically affect the condensing of chromatin and genes expression. The unique epigenetic memories of various cells trigger exclusive gene expression profiling. According to different studies, the aberrant epigenetic signatures and impaired gene expression profiles are master occurrences in cancer cells in which oncogene and tumor suppressor genes are affected. Owing to the facts that epigenetic modifications are performed earlier than expression and are reversible, the epigenetic reprogramming of cancer cells could be applied potentially for their prevention, control, and therapy. The disruption of the acetylation signature, as a master epigenetic change in cancers, is related to the expression and the activity of HDACs. In this context, class I HDACs play a significant role in the regulation of cell proliferation and cancer. More recently, cancer stem cell (CSC) has been introduced as a minority population of tumor that is responsible for invasiveness, drug resistance, and relapse of cancers. It is now believed that controlling CSC via epigenetic reprogramming such as targeting HDACs could be helpful in regulating the acetylation pattern of chromatin. Recently, a number of reports have introduced some phytochemicals as HDAC inhibitors. The use of phytochemicals with the HDAC inhibition property could be potentially efficient in overcoming the mentioned problems of CSCs. This review presents a perspective concerning HDAC-targeted phytochemicals to control CSC in tumors. Hopefully, this new route would have more advantages in therapeutic applications and prevention against cancer. Copyright © 2017. Published by Elsevier Masson SAS.

Decoherence in yeast cell populations and its implications for genome-wide expression noise.

PubMed

Briones, M R S; Bosco, F

2009-01-20

Gene expression "noise" is commonly defined as the stochastic variation of gene expression levels in different cells of the same population under identical growth conditions. Here, we tested whether this "noise" is amplified with time, as a consequence of decoherence in global gene expression profiles (genome-wide microarrays) of synchronized cells. The stochastic component of transcription causes fluctuations that tend to be amplified as time progresses, leading to a decay of correlations of expression profiles, in perfect analogy with elementary relaxation processes. Measuring decoherence, defined here as a decay in the auto-correlation function of yeast genome-wide expression profiles, we found a slowdown in the decay of correlations, opposite to what would be expected if, as in mixing systems, correlations decay exponentially as the equilibrium state is reached. Our results indicate that the populational variation in gene expression (noise) is a consequence of temporal decoherence, in which the slow decay of correlations is a signature of strong interdependence of the transcription dynamics of different genes.

Reconstructing Dynamic Promoter Activity Profiles from Reporter Gene Data.

PubMed

Kannan, Soumya; Sams, Thomas; Maury, Jérôme; Workman, Christopher T

2018-03-16

Accurate characterization of promoter activity is important when designing expression systems for systems biology and metabolic engineering applications. Promoters that respond to changes in the environment enable the dynamic control of gene expression without the necessity of inducer compounds, for example. However, the dynamic nature of these processes poses challenges for estimating promoter activity. Most experimental approaches utilize reporter gene expression to estimate promoter activity. Typically the reporter gene encodes a fluorescent protein that is used to infer a constant promoter activity despite the fact that the observed output may be dynamic and is a number of steps away from the transcription process. In fact, some promoters that are often thought of as constitutive can show changes in activity when growth conditions change. For these reasons, we have developed a system of ordinary differential equations for estimating dynamic promoter activity for promoters that change their activity in response to the environment that is robust to noise and changes in growth rate. Our approach, inference of dynamic promoter activity (PromAct), improves on existing methods by more accurately inferring known promoter activity profiles. This method is also capable of estimating the correct scale of promoter activity and can be applied to quantitative data sets to estimate quantitative rates.

Gene expression profiles in whole blood and associations with metabolic dysregulation in obesity.

PubMed

Cox, Amanda J; Zhang, Ping; Evans, Tiffany J; Scott, Rodney J; Cripps, Allan W; West, Nicholas P

Gene expression data provides one tool to gain further insight into the complex biological interactions linking obesity and metabolic disease. This study examined associations between blood gene expression profiles and metabolic disease in obesity. Whole blood gene expression profiles, performed using the Illumina HT-12v4 Human Expression Beadchip, were compared between (i) individuals with obesity (O) or lean (L) individuals (n=21 each), (ii) individuals with (M) or without (H) Metabolic Syndrome (n=11 each) matched on age and gender. Enrichment of differentially expressed genes (DEG) into biological pathways was assessed using Ingenuity Pathway Analysis. Association between sets of genes from biological pathways considered functionally relevant and Metabolic Syndrome were further assessed using an area under the curve (AUC) and cross-validated classification rate (CR). For OvL, only 50 genes were significantly differentially expressed based on the selected differential expression threshold (1.2-fold, p<0.05). For MvH, 582 genes were significantly differentially expressed (1.2-fold, p<0.05) and pathway analysis revealed enrichment of DEG into a diverse set of pathways including immune/inflammatory control, insulin signalling and mitochondrial function pathways. Gene sets from the mTOR signalling pathways demonstrated the strongest association with Metabolic Syndrome (p=8.1×10 -8 ; AUC: 0.909, CR: 72.7%). These results support the use of expression profiling in whole blood in the absence of more specific tissue types for investigations of metabolic disease. Using a pathway analysis approach it was possible to identify an enrichment of DEG into biological pathways that could be targeted for in vitro follow-up. Copyright © 2017 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Recrudescence Mechanisms and Gene Expression Profile of the Reproductive Tracts from Chickens during the Molting Period

PubMed Central

Ahn, Suzie E.; Lim, Chul-Hong; Lee, Jin-Young; Bae, Seung-Min; Kim, Jinyoung; Bazer, Fuller W.; Song, Gwonhwa

2013-01-01

The reproductive system of chickens undergoes dynamic morphological and functional tissue remodeling during the molting period. The present study identified global gene expression profiles following oviductal tissue regression and regeneration in laying hens in which molting was induced by feeding high levels of zinc in the diet. During the molting and recrudescence processes, progressive morphological and physiological changes included regression and re-growth of reproductive organs and fluctuations in concentrations of testosterone, progesterone, estradiol and corticosterone in blood. The cDNA microarray analysis of oviductal tissues revealed the biological significance of gene expression-based modulation in oviductal tissue during its remodeling. Based on the gene expression profiles, expression patterns of selected genes such as, TF, ANGPTL3, p20K, PTN, AvBD11 and SERPINB3 exhibited similar patterns in expression with gradual decreases during regression of the oviduct and sequential increases during resurrection of the functional oviduct. Also, miR-1689* inhibited expression of Sp1, while miR-17-3p, miR-22* and miR-1764 inhibited expression of STAT1. Similarly, chicken miR-1562 and miR-138 reduced the expression of ANGPTL3 and p20K, respectively. These results suggest that these differentially regulated genes are closely correlated with the molecular mechanism(s) for development and tissue remodeling of the avian female reproductive tract, and that miRNA-mediated regulation of key genes likely contributes to remodeling of the avian reproductive tract by controlling expression of those genes post-transcriptionally. The discovered global gene profiles provide new molecular candidates responsible for regulating morphological and functional recrudescence of the avian reproductive tract, and provide novel insights into understanding the remodeling process at the genomic and epigenomic levels. PMID:24098561

Near-isogenic cotton germplasm lines that differ in fiber-bundle strength have temporal differences in fiber gene expression patterns as revealed by comparative high-throughput profiling.

PubMed

Hinchliffe, Doug J; Meredith, William R; Yeater, Kathleen M; Kim, Hee Jin; Woodward, Andrew W; Chen, Z Jeffrey; Triplett, Barbara A

2010-05-01

Gene expression profiles of developing cotton (Gossypium hirsutum L.) fibers from two near-isogenic lines (NILs) that differ in fiber-bundle strength, short-fiber content, and in fewer than two genetic loci were compared using an oligonucleotide microarray. Fiber gene expression was compared at five time points spanning fiber elongation and secondary cell wall (SCW) biosynthesis. Fiber samples were collected from field plots in a randomized, complete block design, with three spatially distinct biological replications for each NIL at each time point. Microarray hybridizations were performed in a loop experimental design that allowed comparisons of fiber gene expression profiles as a function of time between the two NILs. Overall, developmental expression patterns revealed by the microarray experiment agreed with previously reported cotton fiber gene expression patterns for specific genes. Additionally, genes expressed coordinately with the onset of SCW biosynthesis in cotton fiber correlated with gene expression patterns of other SCW-producing plant tissues. Functional classification and enrichment analysis of differentially expressed genes between the two NILs revealed that genes associated with SCW biosynthesis were significantly up-regulated in fibers of the high-fiber quality line at the transition stage of cotton fiber development. For independent corroboration of the microarray results, 15 genes were selected for quantitative reverse transcription PCR analysis of fiber gene expression. These analyses, conducted over multiple field years, confirmed the temporal difference in fiber gene expression between the two NILs. We hypothesize that the loci conferring temporal differences in fiber gene expression between the NILs are important regulatory sequences that offer the potential for more targeted manipulation of cotton fiber quality.

Bone-related gene profiles in developing calvaria.

PubMed

Cho, Je-Yoel; Lee, Won-Bong; Kim, Hyun-Jung; Mi Woo, Kyung; Baek, Jeong-Hwa; Choi, Je-Yong; Hur, Cheol-Gu; Ryoo, Hyun-Mo

2006-05-10

Generating a comprehensive understanding of osteogenesis-related gene profiles is very important in the development of new treatments for osteopenic conditions. Developing calvaria undergoes a typical intramembranous bone-forming process. To identify genes associated with osteoblast differentiation, we isolated total RNAs from parietal bones, that represent active osteoblasts, and sutural mesenchyme, that represents osteoprogenitor cells, and comprehensively analyzed their gene expression profiles using an oligo-based Affymetrix microarray chip containing 22,690 probes. About 2100 genes with "Present" calls had more than 2-fold higher expression in bone compared to sutures while 73 of these genes had more than 8-fold expression. Some of these genes are already known to be bone-related biomarkers: VitD receptor, bone sialoprotein, osteocalcin, osteopontin, MMP13, etc. Eight genes were selected and subjected to confirmation by quantitative real-time RT-PCR analyses. All the genes tested showed higher expression in bones, ranging from 5- to 140-fold. Several of these genes are ESTs while others are already known but their functions in osteogenesis were not previously known. Most genes of the BMP and FGF families probed in the Genechip analysis were more highly expressed in bone tissues compared to suture. All differentially-expressed Runx and Dlx family genes also showed higher expression in bone. These results imply that our data is valid and can be used as a good standard for the mining of osteogenesis-related genes.

Downregulation of immediate-early genes linking to suppression of neuronal plasticity in rats after 28-day exposure to glycidol

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akane, Hirotoshi; Saito, Fumiyo; Shiraki, Ayako

2014-09-01

We previously found that the 28-day oral toxicity study of glycidol at 200 mg/kg/day in rats resulted in axonopathy in both the central and peripheral nervous systems and aberrations in the late-stage of hippocampal neurogenesis targeting the process of neurite extension. To capture the neuronal parameters in response to glycidol toxicity, these animals were subjected to region-specific global gene expression profiling in four regions of cerebral and cerebellar architectures, followed by immunohistochemical analysis of selected gene products. Expression changes of genes related to axonogenesis and synaptic transmission were observed in the hippocampal dentate gyrus, cingulate cortex and cerebellar vermis atmore » 200 mg/kg showing downregulation in most genes. In the corpus callosum, genes related to growth, survival and functions of glial cells fluctuated their expression. Immunohistochemically, neurons expressing gene products of immediate-early genes, i.e., Arc, Fos and Jun, decreased in their number in the dentate granule cell layer, cingulate cortex and cerebellar vermis. We also applied immunohistochemical analysis in rat offspring after developmental exposure to glycidol through maternal drinking water. The results revealed increases of Arc{sup +} neurons at 1000 ppm and Fos{sup +} neurons at ≥ 300 ppm in the dentate granule cell layer of offspring only at the adult stage. These results suggest that glycidol suppressed neuronal plasticity in the brain after 28-day exposure to young adult animals, in contrast to the operation of restoration mechanism to increase neuronal plasticity at the adult stage in response to aberrations in neurogenesis after developmental exposure. - Highlights: • Neuronal toxicity parameters after 28-day glycidol treatment were examined in rats. • Region-specific global gene expression profiling was conducted in brain regions. • Cortical tissues downregulated genes on axonogenesis and synaptic transmission. • Cortical tissues decreased immunoreactive neurons for Arc, Fos or Jun. • The results suggest that 28-day glycidol treatment suppressed neuronal plasticity.« less

Identification of suitable genes contributes to lung adenocarcinoma clustering by multiple meta-analysis methods.

PubMed

Yang, Ze-Hui; Zheng, Rui; Gao, Yuan; Zhang, Qiang

2016-09-01

With the widespread application of high-throughput technology, numerous meta-analysis methods have been proposed for differential expression profiling across multiple studies. We identified the suitable differentially expressed (DE) genes that contributed to lung adenocarcinoma (ADC) clustering based on seven popular multiple meta-analysis methods. Seven microarray expression profiles of ADC and normal controls were extracted from the ArrayExpress database. The Bioconductor was used to perform the data preliminary preprocessing. Then, DE genes across multiple studies were identified. Hierarchical clustering was applied to compare the classification performance for microarray data samples. The classification efficiency was compared based on accuracy, sensitivity and specificity. Across seven datasets, 573 ADC cases and 222 normal controls were collected. After filtering out unexpressed and noninformative genes, 3688 genes were remained for further analysis. The classification efficiency analysis showed that DE genes identified by sum of ranks method separated ADC from normal controls with the best accuracy, sensitivity and specificity of 0.953, 0.969 and 0.932, respectively. The gene set with the highest classification accuracy mainly participated in the regulation of response to external stimulus (P = 7.97E-04), cyclic nucleotide-mediated signaling (P = 0.01), regulation of cell morphogenesis (P = 0.01) and regulation of cell proliferation (P = 0.01). Evaluation of DE genes identified by different meta-analysis methods in classification efficiency provided a new perspective to the choice of the suitable method in a given application. Varying meta-analysis methods always present varying abilities, so synthetic consideration should be taken when providing meta-analysis methods for particular research. © 2015 John Wiley & Sons Ltd.

Fractal Clustering and Knowledge-driven Validation Assessment for Gene Expression Profiling.

PubMed

Wang, Lu-Yong; Balasubramanian, Ammaiappan; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

DNA microarray experiments generate a substantial amount of information about the global gene expression. Gene expression profiles can be represented as points in multi-dimensional space. It is essential to identify relevant groups of genes in biomedical research. Clustering is helpful in pattern recognition in gene expression profiles. A number of clustering techniques have been introduced. However, these traditional methods mainly utilize shape-based assumption or some distance metric to cluster the points in multi-dimension linear Euclidean space. Their results shows poor consistence with the functional annotation of genes in previous validation study. From a novel different perspective, we propose fractal clustering method to cluster genes using intrinsic (fractal) dimension from modern geometry. This method clusters points in such a way that points in the same clusters are more self-affine among themselves than to the points in other clusters. We assess this method using annotation-based validation assessment for gene clusters. It shows that this method is superior in identifying functional related gene groups than other traditional methods.

Immunological network signatures of cancer progression and survival

PubMed Central

2011-01-01

Background The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors. Methods To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions. Results The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival. Conclusions The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding of immune involvement in complex biological networks. The application of this approach to tumor immunity represents an automated systems strategy that quantifies the immunological component in complex disease. In so doing, it stratifies patients according to their immune profiles, which may lead to effective computational prognostic and clinical guides. PMID:21453479

svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identification.

PubMed

Zhang, Wensheng; Edwards, Andrea; Fan, Wei; Zhu, Dongxiao; Zhang, Kun

2010-06-22

Comparative analysis of gene expression profiling of multiple biological categories, such as different species of organisms or different kinds of tissue, promises to enhance the fundamental understanding of the universality as well as the specialization of mechanisms and related biological themes. Grouping genes with a similar expression pattern or exhibiting co-expression together is a starting point in understanding and analyzing gene expression data. In recent literature, gene module level analysis is advocated in order to understand biological network design and system behaviors in disease and life processes; however, practical difficulties often lie in the implementation of existing methods. Using the singular value decomposition (SVD) technique, we developed a new computational tool, named svdPPCS (SVD-based Pattern Pairing and Chart Splitting), to identify conserved and divergent co-expression modules of two sets of microarray experiments. In the proposed methods, gene modules are identified by splitting the two-way chart coordinated with a pair of left singular vectors factorized from the gene expression matrices of the two biological categories. Importantly, the cutoffs are determined by a data-driven algorithm using the well-defined statistic, SVD-p. The implementation was illustrated on two time series microarray data sets generated from the samples of accessory gland (ACG) and malpighian tubule (MT) tissues of the line W118 of M. drosophila. Two conserved modules and six divergent modules, each of which has a unique characteristic profile across tissue kinds and aging processes, were identified. The number of genes contained in these models ranged from five to a few hundred. Three to over a hundred GO terms were over-represented in individual modules with FDR < 0.1. One divergent module suggested the tissue-specific relationship between the expressions of mitochondrion-related genes and the aging process. This finding, together with others, may be of biological significance. The validity of the proposed SVD-based method was further verified by a simulation study, as well as the comparisons with regression analysis and cubic spline regression analysis plus PAM based clustering. svdPPCS is a novel computational tool for the comparative analysis of transcriptional profiling. It especially fits the comparison of time series data of related organisms or different tissues of the same organism under equivalent or similar experimental conditions. The general scheme can be directly extended to the comparisons of multiple data sets. It also can be applied to the integration of data sets from different platforms and of different sources.

Computational synchronization of microarray data with application to Plasmodium falciparum.

PubMed

Zhao, Wei; Dauwels, Justin; Niles, Jacquin C; Cao, Jianshu

2012-06-21

Microarrays are widely used to investigate the blood stage of Plasmodium falciparum infection. Starting with synchronized cells, gene expression levels are continually measured over the 48-hour intra-erythrocytic cycle (IDC). However, the cell population gradually loses synchrony during the experiment. As a result, the microarray measurements are blurred. In this paper, we propose a generalized deconvolution approach to reconstruct the intrinsic expression pattern, and apply it to P. falciparum IDC microarray data. We develop a statistical model for the decay of synchrony among cells, and reconstruct the expression pattern through statistical inference. The proposed method can handle microarray measurements with noise and missing data. The original gene expression patterns become more apparent in the reconstructed profiles, making it easier to analyze and interpret the data. We hypothesize that reconstructed gene expression patterns represent better temporally resolved expression profiles that can be probabilistically modeled to match changes in expression level to IDC transitions. In particular, we identify transcriptionally regulated protein kinases putatively involved in regulating the P. falciparum IDC. By analyzing publicly available microarray data sets for the P. falciparum IDC, protein kinases are ranked in terms of their likelihood to be involved in regulating transitions between the ring, trophozoite and schizont developmental stages of the P. falciparum IDC. In our theoretical framework, a few protein kinases have high probability rankings, and could potentially be involved in regulating these developmental transitions. This study proposes a new methodology for extracting intrinsic expression patterns from microarray data. By applying this method to P. falciparum microarray data, several protein kinases are predicted to play a significant role in the P. falciparum IDC. Earlier experiments have indeed confirmed that several of these kinases are involved in this process. Overall, these results indicate that further functional analysis of these additional putative protein kinases may reveal new insights into how the P. falciparum IDC is regulated.

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

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

Molecular Classifiers for Acute Kidney Transplant Rejection in Peripheral Blood by Whole Genome Gene Expression Profiling

PubMed Central

Kurian, S. M.; Williams, A. N.; Gelbart, T.; Campbell, D.; Mondala, T. S.; Head, S. R.; Horvath, S.; Gaber, L.; Thompson, R.; Whisenant, T.; Lin, W.; Langfelder, P.; Robison, E. H.; Schaffer, R. L.; Fisher, J. S.; Friedewald, J.; Flechner, S. M.; Chan, L. K.; Wiseman, A. C.; Shidban, H.; Mendez, R.; Heilman, R.; Abecassis, M. M.; Marsh, C. L.; Salomon, D. R.

2015-01-01

There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction. PMID:24725967

Transcriptome Profiling of Bovine Milk Oligosaccharide Metabolism Genes Using RNA-Sequencing

PubMed Central

Wickramasinghe, Saumya; Hua, Serenus; Rincon, Gonzalo; Islas-Trejo, Alma; German, J. Bruce; Lebrilla, Carlito B.; Medrano, Juan F.

2011-01-01

This study examines the genes coding for enzymes involved in bovine milk oligosaccharide metabolism by comparing the oligosaccharide profiles with the expressions of glycosylation-related genes. Fresh milk samples (n = 32) were collected from four Holstein and Jersey cows at days 1, 15, 90 and 250 of lactation and free milk oligosaccharide profiles were analyzed. RNA was extracted from milk somatic cells at days 15 and 250 of lactation (n = 12) and gene expression analysis was conducted by RNA-Sequencing. A list was created of 121 glycosylation-related genes involved in oligosaccharide metabolism pathways in bovine by analyzing the oligosaccharide profiles and performing an extensive literature search. No significant differences were observed in either oligosaccharide profiles or expressions of glycosylation-related genes between Holstein and Jersey cows. The highest concentrations of free oligosaccharides were observed in the colostrum samples and a sharp decrease was observed in the concentration of free oligosaccharides on day 15, followed by progressive decrease on days 90 and 250. Ninety-two glycosylation-related genes were expressed in milk somatic cells. Most of these genes exhibited higher expression in day 250 samples indicating increases in net glycosylation-related metabolism in spite of decreases in free milk oligosaccharides in late lactation milk. Even though fucosylated free oligosaccharides were not identified, gene expression indicated the likely presence of fucosylated oligosaccharides in bovine milk. Fucosidase genes were expressed in milk and a possible explanation for not detecting fucosylated free oligosaccharides is the degradation of large fucosylated free oligosaccharides by the fucosidases. Detailed characterization of enzymes encoded by the 92 glycosylation-related genes identified in this study will provide the basic knowledge for metabolic network analysis of oligosaccharides in mammalian milk. These candidate genes will guide the design of a targeted breeding strategy to optimize the content of beneficial oligosaccharides in bovine milk. PMID:21541029

RNA-sequencing quantification of hepatic ontogeny of phase-I enzymes in mice.

PubMed

Peng, Lai; Cui, Julia Y; Yoo, Byunggil; Gunewardena, Sumedha S; Lu, Hong; Klaassen, Curtis D; Zhong, Xiao-Bo

2013-12-01

Phase-I drug metabolizing enzymes catalyze reactions of hydrolysis, reduction, and oxidation of drugs and play a critical role in drug metabolism. However, the functions of most phase-I enzymes are not mature at birth, which markedly affects drug metabolism in newborns. Therefore, characterization of the expression profiles of phase-I enzymes and the underlying regulatory mechanisms during liver maturation is needed for better estimation of using drugs in pediatric patients. The mouse is an animal model widely used for studying the mechanisms in the regulation of developmental expression of phase-I genes. Therefore, we applied RNA sequencing to provide a "true quantification" of the mRNA expression of phase-I genes in the mouse liver during development. Liver samples of male C57BL/6 mice at 12 different ages from prenatal to adulthood were used for defining the ontogenic mRNA profiles of phase-I families, including hydrolysis: carboxylesterase (Ces), paraoxonase (Pon), and epoxide hydrolase (Ephx); reduction: aldo-keto reductase (Akr), quinone oxidoreductase (Nqo), and dihydropyrimidine dehydrogenase (Dpyd); and oxidation: alcohol dehydrogenase (Adh), aldehyde dehydrogenase (Aldh), flavin monooxygenases (Fmo), molybdenum hydroxylase (Aox and Xdh), cytochrome P450 (P450), and cytochrome P450 oxidoreductase (Por). Two rapidly increasing stages of total phase-I gene expression after birth reflect functional transition of the liver during development. Diverse expression patterns were identified, and some large gene families contained the mRNA of genes that are enriched at different stages of development. Our study reveals the mRNA abundance of phase-I genes in the mouse liver during development and provides a valuable foundation for mechanistic studies in the future.

Developing Toxicogenomics as a Research Tool by Applying Benchmark Dose-Response Modeling to inform Chemical Mode of Action and Tumorigenic Potency

EPA Science Inventory

ABSTRACT Results of global gene expression profiling after short-term exposures can be used to inform tumorigenic potency and chemical mode of action (MOA) and thus serve as a strategy to prioritize future or data-poor chemicals for further evaluation. This compilation of cas...

Use of Microarray to Analyze Gene Expression Profiles of Acute Effects of Prochloraz on Fathead Minnows Pimephales promelas

EPA Science Inventory

Microarray technology is a powerful tool to investigate the gene expression profiles for thousands of genes simultaneously. In recent years, microarrays have been used to characterize environmental pollutants and identify molecular mode(s) of action of chemicals including endocri...

The Role of Vitamin D in the Transcriptional Program of Human Pregnancy

PubMed Central

Al-Garawi, Amal; Carey, Vincent J.; Chhabra, Divya; Morrow, Jarrett; Lasky-Su, Jessica; Qiu, Weiliang; Laranjo, Nancy; Litonjua, Augusto A.; Weiss, Scott T.

2016-01-01

Background Patterns of gene expression of human pregnancy are poorly understood. In a trial of vitamin D supplementation in pregnant women, peripheral blood transcriptomes were measured longitudinally on 30 women and used to characterize gene co-expression networks. Objective Studies suggest that increased maternal Vitamin D levels may reduce the risk of asthma in early life, yet the underlying mechanisms have not been examined. In this study, we used a network-based approach to examine changes in gene expression profiles during the course of normal pregnancy and evaluated their association with maternal Vitamin D levels. Design The VDAART study is a randomized clinical trial of vitamin D supplementation in pregnancy for reduction of pediatric asthma risk. The trial enrolled 881 women at 10–18 weeks of gestation. Longitudinal gene expression measures were obtained on thirty pregnant women, using RNA isolated from peripheral blood samples obtained in the first and third trimesters. Differentially expressed genes were identified using significance of analysis of microarrays (SAM), and clustered using a weighted gene co-expression network analysis (WGCNA). Gene-set enrichment was performed to identify major biological pathways. Results Comparison of transcriptional profiles between first and third trimesters of pregnancy identified 5839 significantly differentially expressed genes (FDR<0.05). Weighted gene co-expression network analysis clustered these transcripts into 14 co-expression modules of which two showed significant correlation with maternal vitamin D levels. Pathway analysis of these two modules revealed genes enriched in immune defense pathways and extracellular matrix reorganization as well as genes enriched in notch signaling and transcription factor networks. Conclusion Our data show that gene expression profiles of healthy pregnant women change during the course of pregnancy and suggest that maternal Vitamin D levels influence transcriptional profiles. These alterations of the maternal transcriptome may contribute to fetal immune imprinting and reduce allergic sensitization in early life. Trial Registration clinicaltrials.gov NCT00920621 PMID:27711190

Gene Expression Profiling of Bronchoalveolar Lavage Cells During Aspergillus Colonization of the Lung Allograft.

PubMed

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.

RNA Expression Profiles from Blood for the Diagnosis of Stroke and its Causes

PubMed Central

Sharp, Frank R; Jickling, Glen C; Stamova, Boryana; Tian, Yingfang; Zhan, Xinhua; Ander, Bradley P; Cox, Christopher; Kuczynski, Beth; Liu, DaZhi

2013-01-01

A blood test to detect stroke and its causes would be particularly useful in babies, young children, and patients in intensive care units, and for emergencies when imaging is difficult to obtain or unavailable. Using whole genome microarrays, we first showed specific gene expression profiles in rats 24 hours after ischemic and hemorrhagic stroke, hypoxia, and hypoglycemia. These proof-of-principle studies revealed that groups of genes (called gene profiles) can distinguish ischemic stroke patients from controls 3 hours to 24 hours after the strokes. In addition, gene expression profiles have been developed that distinguish stroke due to large-vessel atherosclerosis from cardioembolic stroke. These profiles will be useful for predicting the causes of cryptogenic stroke. Our results in adults suggest similar diagnostic tools could be developed for children. PMID:21636778

Genome-wide DNA methylation profiling integrated with gene expression profiling identifies PAX9 as a novel prognostic marker in chronic lymphocytic leukemia.

PubMed

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.

Gene Expression Profiles in Stage I Uterine Serous Carcinoma in Comparison to Grade 3 and Grade 1 Stage I Endometrioid Adenocarcinoma

PubMed Central

Mhawech-Fauceglia, Paulette; Wang, Dan; Kesterson, Joshua; Syriac, Susanna; Clark, Kimberly; Frederick, Peter J.; Lele, Shashikant; Liu, Song

2011-01-01

Background Endometrial cancer is the most common gynecologic malignancy in the developed countries. Clinical studies have shown that early stage uterine serous carcinoma (USC) has outcomes similar to early stage high grade endometrioid adenocarcinoma (EAC-G3) than to early stage low grade endometrioid adenocarcinoma (EAC-G1). However, little is known about the origin of these different clinical outcomes. This study applied the whole genome expression profiling to explore the expression difference of stage I USC (n = 11) relative to stage I EAC-G3 (n = 11) and stage I EAC-G1 (n = 11), respectively. Methodology/Principal Finding We found that the expression difference between USC and EAC-G3, as measured by the number of differentially expressed genes (DEGs), is consistently less than that found between USC and EAC-G1. Pathway enrichment analyses suggested that DEGs specific to USC vs. EAC-G3 are enriched for genes involved in signaling transduction, while DEGs specific to USC vs. EAC-G1 are enriched for genes involved in cell cycle. Gene expression differences for selected DEGs are confirmed by quantitative RT-PCR with a high validation rate. Conclusion This data, although preliminary, indicates that stage I USC is genetically similar to stage I EAC-G3 compared to stage I EAC-G1. DEGs identified from this study might provide an insight in to the potential mechanisms that influence the clinical outcome differences between endometrial cancer subtypes. They might also have potential prognostic and therapeutic impacts on patients diagnosed with uterine cancer. PMID:21448288

Gene expression complex networks: synthesis, identification, and analysis.

PubMed

Lopes, Fabrício M; Cesar, Roberto M; Costa, Luciano Da F

2011-10-01

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdös-Rényi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabási-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree variation, decreasing its network recovery rate with the increase of . The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Exposure to metals mixtures: Genomic alterations of infectious ...

EPA Pesticide Factsheets

Exposure to toxic metals can have harmful health effects, particularly in children. Although studies have investigated the individual effects toxic metals have on gene expression and health outcomes, there are no studies assessing the effect of metal mixtures on gene expression profiles. Here, we assessed the mixture effect of six toxic metals (arsenic, beryllium, cadmium, chromium, mercury, and lead) on gene expression profiles in children in Detroit, Michigan. As part of the Mechanistic Indicators of Childhood Asthma (MICA) cross sectional study, we assessed metal exposure in 131 children in Detroit using fingernail metals levels. A metals mixture score was calculated and compared to gene expression profiles across the population adjusting for age and race. There were 145 unique genes that were significantly differentially expressed when comparing children exposed to low and high levels of the metals mixture. Of the genes differentially expressed, 107 (74%) had increased expression while 38 (26%) had decreased expression. The main biological function associated with multiple metals was infectious disease. Within that group, genes were associated with infection of respiratory tract (P < 10-6) severe acute respiratory syndrome (P < 10-5), and sepsis (P < 10-3). Taken together, these data demonstrate that exposure to metals mixtures may activate gene networks related to infectious disease response. This abstract does not necessarily reflect the views or policie

A Modified ABCDE Model of Flowering in Orchids Based on Gene Expression Profiling Studies of the Moth Orchid Phalaenopsis aphrodite

PubMed Central

Lee, Ann-Ying; Chen, Chun-Yi; Chang, Yao-Chien Alex; Chao, Ya-Ting; Shih, Ming-Che

2013-01-01

Previously we developed genomic resources for orchids, including transcriptomic analyses using next-generation sequencing techniques and construction of a web-based orchid genomic database. Here, we report a modified molecular model of flower development in the Orchidaceae based on functional analysis of gene expression profiles in Phalaenopsis aphrodite (a moth orchid) that revealed novel roles for the transcription factors involved in floral organ pattern formation. Phalaenopsis orchid floral organ-specific genes were identified by microarray analysis. Several critical transcription factors including AP3, PI, AP1 and AGL6, displayed distinct spatial distribution patterns. Phylogenetic analysis of orchid MADS box genes was conducted to infer the evolutionary relationship among floral organ-specific genes. The results suggest that gene duplication MADS box genes in orchid may have resulted in their gaining novel functions during evolution. Based on these analyses, a modified model of orchid flowering was proposed. Comparison of the expression profiles of flowers of a peloric mutant and wild-type Phalaenopsis orchid further identified genes associated with lip morphology and peloric effects. Large scale investigation of gene expression profiles revealed that homeotic genes from the ABCDE model of flower development classes A and B in the Phalaenopsis orchid have novel functions due to evolutionary diversification, and display differential expression patterns. PMID:24265826

Gene expression profiling in the hippocampus of learned helpless and nonhelpless rats.

PubMed

Kohen, R; Kirov, S; Navaja, G P; Happe, H Kevin; Hamblin, M W; Snoddy, J R; Neumaier, J F; Petty, F

2005-01-01

In the learned helplessness (LH) animal model of depression, failure to attempt escape from avoidable environmental stress, LH, indicates behavioral despair, whereas nonhelpless (NH) behavior reflects behavioral resilience to the effects of environmental stress. Comparing hippocampal gene expression with large-scale oligonucleotide microarrays, we found that stress-resilient (NH) rats, although behaviorally indistinguishable from controls, showed a distinct gene expression profile compared to LH, sham stressed, and naïve control animals. Genes that were confirmed as differentially expressed in the NH group by quantitative PCR strongly correlated in their levels of expression across all four animal groups. Differential expression could not be confirmed at the protein level. We identified several shared degenerate sequence motifs in the 3' untranslated region (3'UTR) of differentially expressed genes that could be a factor in this tight correlation of expression levels among differentially expressed genes.

A comparative study of P450 gene expression in field and laboratory Musca domestica L. strains.

PubMed

Højland, Dorte H; Vagn Jensen, Karl-Martin; Kristensen, Michael

2014-08-01

The housefly is a global pest that has developed resistance to most insecticides applied for its control. Resistance has been associated with cytochrome P450 monooxygenases (P450s). The authors compare the expression of six genes possibly associated with insecticide resistance in three unselected strains: a multiresistant strain (791a), a neonicotinoid-resistant strain (766b) and a new field strain (845b). CYP4G2 was highly expressed throughout the range of strains and proved to be the one of the most interesting expression profiles of all P450s analysed. CYP6G4 was expressed up to 11-fold higher in 766b than in WHO-SRS. Significant differences between expression of P450 genes between F1 flies from 845b and established laboratory strains were shown. In general, P450 gene expression in 845b was 2-14-fold higher than in the reference strain (P < 0.0101) and 2-23-fold higher than in the multiresistant strain (P < 0.0110). The newly collected field strain 845b had significantly higher constitutive gene expression than both WHO-SRS and 791a. High constitutive expression of CYP4G2 in houseflies indicates a possible role of this gene in metabolic resistance. There is a strong indication that CYP6G4 is a major insecticide resistance gene involved in neonicotinoid resistance. © 2013 Society of Chemical Industry.

Gene expression profile of isolated rat adipocytes treated with anthocyanins.

PubMed

Tsuda, Takanori; Ueno, Yuki; Kojo, Hitoshi; Yoshikawa, Toshikazu; Osawa, Toshihiko

2005-04-15

Adipocyte dysfunction is strongly associated with the development of obesity and insulin resistance. It is accepted that the regulation of adipocytokine secretion or the adipocyte specific gene expression is one of the most important targets for the prevention of obesity and amelioration of insulin sensitivity. Recently, we demonstrated that anthocyanins, which are pigments widespread in the plant kingdom, have the potency of anti-obesity in mice and the enhancement adipocytokine secretion and adipocyte gene expression in adipocytes. In this study, we have shown for the first time the gene expression profile in isolated rat adipocytes treated with anthocyanins (cyanidin 3-glucoside; C3G or cyanidin; Cy). The rat adipocytes were treated with 100 muM C3G, Cy or vehicle for 24 h. The total RNA from the adipocytes was isolated and carried out GeneChip microarray analysis. A total of 633 or 427 genes was up-regulated (>1.5-fold) by the treatment of adipocytes with C3G or Cy, respectively. The up-regulated genes include lipid metabolism and signal transduction-related genes, however, the altered genes were partly different between the C3G- and Cy-treated groups. Based on the gene expression profile, we demonstrated the up-regulation of hormone sensitive lipase and enhancement of the lipolytic activity by the treatment of adipocytes with C3G or Cy. These data have provided an overview of the gene expression profiles in adipocytes treated with anthocyanins and identified new responsive genes with potentially important functions in adipocytes related with obesity and diabetes that merit further investigation.

Differential gene expression for Curvularia eragrostidis pathogenic incidence in crabgrass (Digitaria sanguinalis) revealed by cDNA-AFLP analysis.

PubMed

Wang, Jianshu; Wang, Xuemin; Yuan, Bohua; Qiang, Sheng

2013-01-01

Gene expression profiles of Digitaria sanguinalis infected by Curvularia eragrostidis strain QZ-2000 at two concentrations of conidia and two dew durations were analyzed by cDNA amplified fragment length polymorphisms (cDNA-AFLP). Inoculum strength was more determinant of gene expression than dew duration. A total of 256 primer combinations were used for selective amplification and 1214 transcript-derived fragments (TDFs) were selected for their differential expression. Of these, 518 up-regulated differentially expressed TDFs were identified. Forty-six differential cDNA fragments were chosen to be cloned and 35 of them were successfully cloned and sequenced, of which 25 were homologous to genes of known function according to the GenBank database. Only 6 genes were up-regulated in Curvularia eragrostidis-inoculated D. sanguinalis, with functions involved in signal transduction, energy metabolism, cell growth and development, stress responses, abscisic acid biosynthesis and response. It appears that a few pathways may be important parts of the pathogenic strategy of C. eragrostidis strain QZ-2000 on D. sanguinalis. Our study provides the fundamentals to further study the pathogenic mechanism, screen for optimal C. eragrostidis strains as potential mycoherbicide and apply this product to control D. sanguinalis.

Improved Escherichia coli Bactofection and Cytotoxicity by Heterologous Expression of Bacteriophage ΦX174 Lysis Gene E.

PubMed

Chung, Tai-Chun; Jones, Charles H; Gollakota, Akhila; Kamal Ahmadi, Mahmoud; Rane, Snehal; Zhang, Guojian; Pfeifer, Blaine A

2015-05-04

Bactofection offers a gene delivery option particularly useful in the context of immune modulation. The bacterial host naturally attracts recognition and cellular uptake by antigen presenting cells (APCs) as the initial step in triggering an immune response. Moreover, depending on the bacterial vector, molecular biology tools are available to influence and/or overcome additional steps and barriers to effective antigen presentation. In this work, molecular engineering was applied using Escherichia coli as a bactofection vector. In particular, the bacteriophage ΦX174 lysis E (LyE) gene was designed for variable expression across strains containing different levels of lysteriolysin O (LLO). The objective was to generate a bacterial vector with improved attenuation and delivery characteristics. The resulting strains exhibited enhanced gene and protein release and inducible cellular death. In addition, the new vectors demonstrated improved gene delivery and cytotoxicity profiles to RAW264.7 macrophage APCs.

Gene-expression profiling for rejection surveillance after cardiac transplantation.

PubMed

Pham, Michael X; Teuteberg, Jeffrey J; Kfoury, Abdallah G; Starling, Randall C; Deng, Mario C; Cappola, Thomas P; Kao, Andrew; Anderson, Allen S; Cotts, William G; Ewald, Gregory A; Baran, David A; Bogaev, Roberta C; Elashoff, Barbara; Baron, Helen; Yee, James; Valantine, Hannah A

2010-05-20

Endomyocardial biopsy is the standard method of monitoring for rejection in recipients of a cardiac transplant. However, this procedure is uncomfortable, and there are risks associated with it. Gene-expression profiling of peripheral-blood specimens has been shown to correlate with the results of an endomyocardial biopsy. We randomly assigned 602 patients who had undergone cardiac transplantation 6 months to 5 years previously to be monitored for rejection with the use of gene-expression profiling or with the use of routine endomyocardial biopsies, in addition to clinical and echocardiographic assessment of graft function. We performed a noninferiority comparison of the two approaches with respect to the composite primary outcome of rejection with hemodynamic compromise, graft dysfunction due to other causes, death, or retransplantation. During a median follow-up period of 19 months, patients who were monitored with gene-expression profiling and those who underwent routine biopsies had similar 2-year cumulative rates of the composite primary outcome (14.5% and 15.3%, respectively; hazard ratio with gene-expression profiling, 1.04; 95% confidence interval, 0.67 to 1.68). The 2-year rates of death from any cause were also similar in the two groups (6.3% and 5.5%, respectively; P=0.82). Patients who were monitored with the use of gene-expression profiling underwent fewer biopsies per person-year of follow-up than did patients who were monitored with the use of endomyocardial biopsies (0.5 vs. 3.0, P<0.001). Among selected patients who had received a cardiac transplant more than 6 months previously and who were at a low risk for rejection, a strategy of monitoring for rejection that involved gene-expression profiling, as compared with routine biopsies, was not associated with an increased risk of serious adverse outcomes and resulted in the performance of significantly fewer biopsies. (ClinicalTrials.gov number, NCT00351559.) 2010 Massachusetts Medical Society

Transcriptome Profile Analysis from Different Sex Types of Ginkgo biloba L.

PubMed

Du, Shuhui; Sang, Yalin; Liu, Xiaojing; Xing, Shiyan; Li, Jihong; Tang, Haixia; Sun, Limin

2016-01-01

In plants, sex determination is a comprehensive process of correlated events, which involves genes that are differentially and/or specifically expressed in distinct developmental phases. Exploring gene expression profiles from different sex types will contribute to fully understanding sex determination in plants. In this study, we conducted RNA-sequencing of female and male buds (FB and MB) as well as ovulate strobilus and staminate strobilus (OS and SS) of Ginkgo biloba to gain insights into the genes potentially related to sex determination in this species. Approximately 60 Gb of clean reads were obtained from eight cDNA libraries. De novo assembly of the clean reads generated 108,307 unigenes with an average length of 796 bp. Among these unigenes, 51,953 (47.97%) had at least one significant match with a gene sequence in the public databases searched. A total of 4709 and 9802 differentially expressed genes (DEGs) were identified in MB vs. FB and SS vs. OS, respectively. Genes involved in plant hormone signal and transduction as well as those encoding DNA methyltransferase were found to be differentially expressed between different sex types. Their potential roles in sex determination of G. biloba were discussed. Pistil-related genes were expressed in male buds while anther-specific genes were identified in female buds, suggesting that dioecism in G. biloba was resulted from the selective arrest of reproductive primordia. High correlation of expression level was found between the RNA-Seq and quantitative real-time PCR results. The transcriptome resources that we generated allowed us to characterize gene expression profiles and examine differential expression profiles, which provided foundations for identifying functional genes associated with sex determination in G. biloba.

Transcriptome Profile Analysis from Different Sex Types of Ginkgo biloba L.

PubMed Central

Du, Shuhui; Sang, Yalin; Liu, Xiaojing; Xing, Shiyan; Li, Jihong; Tang, Haixia; Sun, Limin

2016-01-01

In plants, sex determination is a comprehensive process of correlated events, which involves genes that are differentially and/or specifically expressed in distinct developmental phases. Exploring gene expression profiles from different sex types will contribute to fully understanding sex determination in plants. In this study, we conducted RNA-sequencing of female and male buds (FB and MB) as well as ovulate strobilus and staminate strobilus (OS and SS) of Ginkgo biloba to gain insights into the genes potentially related to sex determination in this species. Approximately 60 Gb of clean reads were obtained from eight cDNA libraries. De novo assembly of the clean reads generated 108,307 unigenes with an average length of 796 bp. Among these unigenes, 51,953 (47.97%) had at least one significant match with a gene sequence in the public databases searched. A total of 4709 and 9802 differentially expressed genes (DEGs) were identified in MB vs. FB and SS vs. OS, respectively. Genes involved in plant hormone signal and transduction as well as those encoding DNA methyltransferase were found to be differentially expressed between different sex types. Their potential roles in sex determination of G. biloba were discussed. Pistil-related genes were expressed in male buds while anther-specific genes were identified in female buds, suggesting that dioecism in G. biloba was resulted from the selective arrest of reproductive primordia. High correlation of expression level was found between the RNA-Seq and quantitative real-time PCR results. The transcriptome resources that we generated allowed us to characterize gene expression profiles and examine differential expression profiles, which provided foundations for identifying functional genes associated with sex determination in G. biloba. PMID:27379148

A Graphical Modelling Approach to the Dissection of Highly Correlated Transcription Factor Binding Site Profiles

PubMed Central

Stojnic, Robert; Fu, Audrey Qiuyan; Adryan, Boris

2012-01-01

Inferring the combinatorial regulatory code of transcription factors (TFs) from genome-wide TF binding profiles is challenging. A major reason is that TF binding profiles significantly overlap and are therefore highly correlated. Clustered occurrence of multiple TFs at genomic sites may arise from chromatin accessibility and local cooperation between TFs, or binding sites may simply appear clustered if the profiles are generated from diverse cell populations. Overlaps in TF binding profiles may also result from measurements taken at closely related time intervals. It is thus of great interest to distinguish TFs that directly regulate gene expression from those that are indirectly associated with gene expression. Graphical models, in particular Bayesian networks, provide a powerful mathematical framework to infer different types of dependencies. However, existing methods do not perform well when the features (here: TF binding profiles) are highly correlated, when their association with the biological outcome is weak, and when the sample size is small. Here, we develop a novel computational method, the Neighbourhood Consistent PC (NCPC) algorithms, which deal with these scenarios much more effectively than existing methods do. We further present a novel graphical representation, the Direct Dependence Graph (DDGraph), to better display the complex interactions among variables. NCPC and DDGraph can also be applied to other problems involving highly correlated biological features. Both methods are implemented in the R package ddgraph, available as part of Bioconductor (http://bioconductor.org/packages/2.11/bioc/html/ddgraph.html). Applied to real data, our method identified TFs that specify different classes of cis-regulatory modules (CRMs) in Drosophila mesoderm differentiation. Our analysis also found depletion of the early transcription factor Twist binding at the CRMs regulating expression in visceral and somatic muscle cells at later stages, which suggests a CRM-specific repression mechanism that so far has not been characterised for this class of mesodermal CRMs. PMID:23144600

A chronological expression profile of gene activity during embryonic mouse brain development.

PubMed

Goggolidou, P; Soneji, S; Powles-Glover, N; Williams, D; Sethi, S; Baban, D; Simon, M M; Ragoussis, I; Norris, D P

2013-12-01

The brain is a functionally complex organ, the patterning and development of which are key to adult health. To help elucidate the genetic networks underlying mammalian brain patterning, we conducted detailed transcriptional profiling during embryonic development of the mouse brain. A total of 2,400 genes were identified as showing differential expression between three developmental stages. Analysis of the data identified nine gene clusters to demonstrate analogous expression profiles. A significant group of novel genes of as yet undiscovered biological function were detected as being potentially relevant to brain development and function, in addition to genes that have previously identified roles in the brain. Furthermore, analysis for genes that display asymmetric expression between the left and right brain hemispheres during development revealed 35 genes as putatively asymmetric from a combined data set. Our data constitute a valuable new resource for neuroscience and neurodevelopment, exposing possible functional associations between genes, including novel loci, and encouraging their further investigation in human neurological and behavioural disorders.

Gene expression profiling in the early phases of DMD: a constant molecular signature characterizes DMD muscle from early postnatal life throughout disease progression.

PubMed

Pescatori, Mario; Broccolini, Aldobrando; Minetti, Carlo; Bertini, Enrico; Bruno, Claudio; D'amico, Adele; Bernardini, Camilla; Mirabella, Massimiliano; Silvestri, Gabriella; Giglio, Vincenzo; Modoni, Anna; Pedemonte, Marina; Tasca, Giorgio; Galluzzi, Giuliana; Mercuri, Eugenio; Tonali, Pietro A; Ricci, Enzo

2007-04-01

Genome-wide gene expression profiling of skeletal muscle from Duchenne muscular dystrophy (DMD) patients has been used to describe muscle tissue alterations in DMD children older than 5 years. By studying the expression profile of 19 patients younger than 2 years, we describe with high resolution the gene expression signature that characterizes DMD muscle during the initial or "presymptomatic" phase of the disease. We show that in the first 2 years of the disease, DMD muscle is already set to express a distinctive gene expression pattern considerably different from the one expressed by normal, age-matched muscle. This "dystrophic" molecular signature is characterized by a coordinate induction of genes involved in the inflammatory response, extracellular matrix (ECM) remodeling and muscle regeneration, and the reduced transcription of those involved in energy metabolism. Despite the lower degree of muscle dysfunction experienced, our younger patients showed abnormal expression of most of the genes reported as differentially expressed in more advanced stages of the disease. By analyzing our patients as a time series, we provide evidence that some genes, including members of three pathways involved in morphogenetic signaling-Wnt, Notch, and BMP-are progressively induced or repressed in the natural history of DMD.

[Study of testicular cancer gene expression in samples of oral leukoplakia and squamous cell carcinoma of the mouth].

PubMed

Skorodumova, L O; Muraev, A A; Zakharova, E S; Shepelev, M V; Korobko, I V; Zaderenko, I A; Ivanov, S Iu; Gnuchev, N V; Georgiev, G P; Larin, S S

2012-01-01

Cancer-testis (CT) antigens are normally expressed mostly in human germ cells, there is also an aberrant expression in some tumor cells. This expression profile makes them potential tumor growth biomarkers and a promising target for tumor immunotherapy. Specificity of CT genes expression in oral malignant and potentially malignant diseases, e.g. oral leukoplakia, is not yet studied. Data on CT genes expression profile in leukoplakia would allow developing new diagnostic methods with potential value for immunotherapy and prophylaxis of leukoplakia malignization. In our study we compared CT genes expression in normal oral mucosa, oral leukoplakia and oral squamous cell carcinoma. We are the first to describe CT genes expression in oral leukoplakia without dysplasia. This findings make impossible differential diagnosis of oral leukoplakia and squamous cell carcinoma on the basis of CT genes expression. The prognostic value of CT genes expression is still unclear, therefore the longitudinal studies are necessary.

The Use of EST Expression Matrixes for the Quality Control of Gene Expression Data

PubMed Central

Milnthorpe, Andrew T.; Soloviev, Mikhail

2012-01-01

EST expression profiling provides an attractive tool for studying differential gene expression, but cDNA libraries' origins and EST data quality are not always known or reported. Libraries may originate from pooled or mixed tissues; EST clustering, EST counts, library annotations and analysis algorithms may contain errors. Traditional data analysis methods, including research into tissue-specific gene expression, assume EST counts to be correct and libraries to be correctly annotated, which is not always the case. Therefore, a method capable of assessing the quality of expression data based on that data alone would be invaluable for assessing the quality of EST data and determining their suitability for mRNA expression analysis. Here we report an approach to the selection of a small generic subset of 244 UniGene clusters suitable for identification of the tissue of origin for EST libraries and quality control of the expression data using EST expression information alone. We created a small expression matrix of UniGene IDs using two rounds of selection followed by two rounds of optimisation. Our selection procedures differ from traditional approaches to finding “tissue-specific” genes and our matrix yields consistency high positive correlation values for libraries with confirmed tissues of origin and can be applied for tissue typing and quality control of libraries as small as just a few hundred total ESTs. Furthermore, we can pick up tissue correlations between related tissues e.g. brain and peripheral nervous tissue, heart and muscle tissues and identify tissue origins for a few libraries of uncharacterised tissue identity. It was possible to confirm tissue identity for some libraries which have been derived from cancer tissues or have been normalised. Tissue matching is affected strongly by cancer progression or library normalisation and our approach may potentially be applied for elucidating the stage of normalisation in normalised libraries or for cancer staging. PMID:22412959

Seasonal Changes in Bacterial and Archaeal Gene Expression Patterns across Salinity Gradients in the Columbia River Coastal Margin

PubMed Central

Smith, Maria W.; Herfort, Lydie; Tyrol, Kaitlin; Suciu, Dominic; Campbell, Victoria; Crump, Byron C.; Peterson, Tawnya D.; Zuber, Peter; Baptista, Antonio M.; Simon, Holly M.

2010-01-01

Through their metabolic activities, microbial populations mediate the impact of high gradient regions on ecological function and productivity of the highly dynamic Columbia River coastal margin (CRCM). A 2226-probe oligonucleotide DNA microarray was developed to investigate expression patterns for microbial genes involved in nitrogen and carbon metabolism in the CRCM. Initial experiments with the environmental microarrays were directed toward validation of the platform and yielded high reproducibility in multiple tests. Bioinformatic and experimental validation also indicated that >85% of the microarray probes were specific for their corresponding target genes and for a few homologs within the same microbial family. The validated probe set was used to query gene expression responses by microbial assemblages to environmental variability. Sixty-four samples from the river, estuary, plume, and adjacent ocean were collected in different seasons and analyzed to correlate the measured variability in chemical, physical and biological water parameters to differences in global gene expression profiles. The method produced robust seasonal profiles corresponding to pre-freshet spring (April) and late summer (August). Overall relative gene expression was high in both seasons and was consistent with high microbial abundance measured by total RNA, heterotrophic bacterial production, and chlorophyll a. Both seasonal patterns involved large numbers of genes that were highly expressed relative to background, yet each produced very different gene expression profiles. April patterns revealed high differential gene expression in the coastal margin samples (estuary, plume and adjacent ocean) relative to freshwater, while little differential gene expression was observed along the river-to-ocean transition in August. Microbial gene expression profiles appeared to relate, in part, to seasonal differences in nutrient availability and potential resource competition. Furthermore, our results suggest that highly-active particle-attached microbiota in the Columbia River water column may perform dissimilatory nitrate reduction (both dentrification and DNRA) within anoxic particle microniches. PMID:20967204

Peripheral blood gene expression profiles in metabolic syndrome, coronary artery disease and type 2 diabetes.

PubMed

Grayson, B L; Wang, L; Aune, T M

2011-07-01

To determine if individuals with metabolic disorders possess unique gene expression profiles, we compared transcript levels in peripheral blood from patients with coronary artery disease (CAD), type 2 diabetes (T2D) and their precursor state, metabolic syndrome to those of control (CTRL) subjects and subjects with rheumatoid arthritis (RA). The gene expression profile of each metabolic state was distinguishable from CTRLs and correlated with other metabolic states more than with RA. Of note, subjects in the metabolic cohorts overexpressed gene sets that participate in the innate immune response. Genes involved in activation of the pro-inflammatory transcription factor, NF-κB, were overexpressed in CAD whereas genes differentially expressed in T2D have key roles in T-cell activation and signaling. Reverse transcriptase PCR validation confirmed microarray results. Furthermore, several genes differentially expressed in human metabolic disorders have been previously shown to participate in inflammatory responses in murine models of obesity and T2D. Taken together, these data demonstrate that peripheral blood from individuals with metabolic disorders display overlapping and non-overlapping patterns of gene expression indicative of unique, underlying immune processes.

Discovery of Transcriptional Targets Regulated by Nuclear Receptors Using a Probabilistic Graphical Model

PubMed Central

Lee, Mikyung; Huang, Ruili; Tong, Weida

2016-01-01

Nuclear receptors (NRs) are ligand-activated transcriptional regulators that play vital roles in key biological processes such as growth, differentiation, metabolism, reproduction, and morphogenesis. Disruption of NRs can result in adverse health effects such as NR-mediated endocrine disruption. A comprehensive understanding of core transcriptional targets regulated by NRs helps to elucidate their key biological processes in both toxicological and therapeutic aspects. In this study, we applied a probabilistic graphical model to identify the transcriptional targets of NRs and the biological processes they govern. The Tox21 program profiled a collection of approximate 10 000 environmental chemicals and drugs against a panel of human NRs in a quantitative high-throughput screening format for their NR disruption potential. The Japanese Toxicogenomics Project, one of the most comprehensive efforts in the field of toxicogenomics, generated large-scale gene expression profiles on the effect of 131 compounds (in its first phase of study) at various doses, and different durations, and their combinations. We applied author-topic model to these 2 toxicological datasets, which consists of 11 NRs run in either agonist and/or antagonist mode (18 assays total) and 203 in vitro human gene expression profiles connected by 52 shared drugs. As a result, a set of clusters (topics), which consists of a set of NRs and their associated target genes were determined. Various transcriptional targets of the NRs were identified by assays run in either agonist or antagonist mode. Our results were validated by functional analysis and compared with TRANSFAC data. In summary, our approach resulted in effective identification of associated/affected NRs and their target genes, providing biologically meaningful hypothesis embedded in their relationships. PMID:26643261

Expression profiling of the mouse early embryo: Reflections and Perspectives

PubMed Central

Ko, Minoru S. H.

2008-01-01

Laboratory mouse plays important role in our understanding of early mammalian development and provides invaluable model for human early embryos, which are difficult to study for ethical and technical reasons. Comprehensive collection of cDNA clones, their sequences, and complete genome sequence information, which have been accumulated over last two decades, have provided even more advantages to mouse models. Here the progress in global gene expression profiling in early mouse embryos and, to some extent, stem cells are reviewed and the future directions and challenges are discussed. The discussions include the restatement of global gene expression profiles as snapshot of cellular status, and subsequent distinction between the differentiation state and physiological state of the cells. The discussions then extend to the biological problems that can be addressed only through global expression profiling, which include: bird’s-eye view of global gene expression changes, molecular index for developmental potency, cell lineage trajectory, microarray-guided cell manipulation, and the possibility of delineating gene regulatory cascades and networks. PMID:16739220

Global Gene Expression Profiling in Omental Adipose Tissue of Morbidly Obese Diabetic African Americans.

PubMed

Doumatey, Ayo P; Xu, Huichun; Huang, Hanxia; Trivedi, Niraj S; Lei, Lin; Elkahloun, Abdel; Adeyemo, Adebowale; Rotimi, Charles N

2015-06-01

Adipose tissues play important role in the pathophysiology of obesity-related diseases including type 2 diabetes (T2D). To describe gene expression patterns and functional pathways in obesity-related T2D, we performed global transcript profiling of omental adipose tissue (OAT) in morbidly obese individuals with or without T2D. Twenty morbidly obese (mean BMI: about 54 kg/m 2 ) subjects were studied, including 14 morbidly obese individuals with T2D (cases) and 6 morbidly obese individuals without T2D (reference group). Gene expression profiling was performed using the Affymetrix U133 Plus 2.0 human genome expression array. Analysis of covariance was performed to identify differentially expressed genes (DEGs). Bioinformatics tools including PANTHER and Ingenuity Pathway Analysis (IPA) were applied to the DEGs to determine biological functions, networks and canonical pathways that were overrepresented in these individuals. At an absolute fold-change threshold of 2 and false discovery rate (FDR) < 0.05, 68 DEGs were identified in cases compared to the reference group. Myosin X (MYO10) and transforming growth factor beta regulator 1 (TBRG1) were upregulated. MYO10 encodes for an actin-based motor protein that has been associated with T2D. Telomere extension by telomerase ( HNRNPA1, TNKS2 ), D-myo-inositol (1, 4, 5)-trisphosphate biosynthesis (PIP5K1A, PIP4K2A), and regulation of actin-based motility by Rho (ARPC3) were the most significant canonical pathways and overlay with T2D signaling pathway. Upstream regulator analysis predicted 5 miRNAs (miR-320b, miR-381-3p, miR-3679-3p, miR-494-3p, and miR-141-3p,) as regulators of the expression changes identified. This study identified a number of transcripts and miRNAs in OAT as candidate novel players in the pathophysiology of T2D in African Americans.

Analysis of the differential gene and protein expression profile of the rolled leaf mutant of transgenic rice (Oryza sativa L.).

PubMed

Zhu, Qiuqiang; Yu, Shuguang; Chen, Guanshui; Ke, Lanlan; Pan, Daren

2017-01-01

The importance of leaf rolling in rice (Oryza sativa L.) has been widely recognized. Although several studies have investigated rice leaf rolling and identified some related genes, knowledge of the molecular mechanism underlying rice leaf rolling, especially outward leaf rolling, is limited. Therefore, in this study, differential proteomics and gene expression profiling were used to analyze rolled leaf mutant of transgenic rice in order to investigate differentially expressed genes and proteins related to rice leaf rolling. To this end, 28 differentially expressed proteins related to rolling leaf traits were isolated and identified. Digital expression profiling detected 10 genes related to rice leaf rolling. Some of the proteins and genes detected are involved in lipid metabolism, which is related to the development of bulliform cells, such as phosphoinositide phospholipase C, Mgll gene, and At4g26790 gene. The "omics"-level techniques were useful for simultaneously isolating several proteins and genes related to rice leaf rolling. In addition, the results of the analysis of differentially expressed proteins and genes were closely consistent with those from a corresponding functional analysis of cellular mechanisms; our study findings might form the basis for further research on the molecular mechanisms underlying rice leaf rolling.

Exploiting the full power of temporal gene expression profiling through a new statistical test: application to the analysis of muscular dystrophy data.

PubMed

Vinciotti, Veronica; Liu, Xiaohui; Turk, Rolf; de Meijer, Emile J; 't Hoen, Peter A C

2006-04-03

The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Most statistical methods used in the literature do not fully exploit the temporal ordering in the dataset and are not suited to the case where temporal profiles are measured for a number of different biological conditions. We present a statistical test that makes explicit use of the temporal order in the data by fitting polynomial functions to the temporal profile of each gene and for each biological condition. A Hotelling T2-statistic is derived to detect the genes for which the parameters of these polynomials are significantly different from each other. We validate the temporal Hotelling T2-test on muscular gene expression data from four mouse strains which were profiled at different ages: dystrophin-, beta-sarcoglycan and gamma-sarcoglycan deficient mice, and wild-type mice. The first three are animal models for different muscular dystrophies. Extensive biological validation shows that the method is capable of finding genes with temporal profiles significantly different across the four strains, as well as identifying potential biomarkers for each form of the disease. The added value of the temporal test compared to an identical test which does not make use of temporal ordering is demonstrated via a simulation study, and through confirmation of the expression profiles from selected genes by quantitative PCR experiments. The proposed method maximises the detection of the biologically interesting genes, whilst minimising false detections. The temporal Hotelling T2-test is capable of finding relatively small and robust sets of genes that display different temporal profiles between the conditions of interest. The test is simple, it can be used on gene expression data generated from any experimental design and for any number of conditions, and it allows fast interpretation of the temporal behaviour of genes. The R code is available from V.V. The microarray data have been submitted to GEO under series GSE1574 and GSE3523.

Exploiting the full power of temporal gene expression profiling through a new statistical test: Application to the analysis of muscular dystrophy data

PubMed Central

Vinciotti, Veronica; Liu, Xiaohui; Turk, Rolf; de Meijer, Emile J; 't Hoen, Peter AC

2006-01-01

Background The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Most statistical methods used in the literature do not fully exploit the temporal ordering in the dataset and are not suited to the case where temporal profiles are measured for a number of different biological conditions. We present a statistical test that makes explicit use of the temporal order in the data by fitting polynomial functions to the temporal profile of each gene and for each biological condition. A Hotelling T2-statistic is derived to detect the genes for which the parameters of these polynomials are significantly different from each other. Results We validate the temporal Hotelling T2-test on muscular gene expression data from four mouse strains which were profiled at different ages: dystrophin-, beta-sarcoglycan and gamma-sarcoglycan deficient mice, and wild-type mice. The first three are animal models for different muscular dystrophies. Extensive biological validation shows that the method is capable of finding genes with temporal profiles significantly different across the four strains, as well as identifying potential biomarkers for each form of the disease. The added value of the temporal test compared to an identical test which does not make use of temporal ordering is demonstrated via a simulation study, and through confirmation of the expression profiles from selected genes by quantitative PCR experiments. The proposed method maximises the detection of the biologically interesting genes, whilst minimising false detections. Conclusion The temporal Hotelling T2-test is capable of finding relatively small and robust sets of genes that display different temporal profiles between the conditions of interest. The test is simple, it can be used on gene expression data generated from any experimental design and for any number of conditions, and it allows fast interpretation of the temporal behaviour of genes. The R code is available from V.V. The microarray data have been submitted to GEO under series GSE1574 and GSE3523. PMID:16584545

Topical Application of a Bioadhesive Black Raspberry Gel Modulates Gene Expression and Reduces Cyclooxygenase 2 Protein in Human Premalignant Oral Lesions

PubMed Central

Mallery, Susan R.; Zwick, Jared C.; Pei, Ping; Tong, Meng; Larsen, Peter E.; Shumway, Brian S.; Lu, Bo; Fields, Henry W.; Mumper, Russell J.; Stoner, Gary D.

2010-01-01

Reduced expression of proapoptotic and terminal differentiation genes in conjunction with increased levels of the proinflammatory and angiogenesis-inducing enzymes, cyclooxygenase 2 (COX-2) and inducible nitric oxide synthase (iNOS), correlate with malignant transformation of oral intraepithelial neoplasia (IEN). Accordingly, this study investigated the effects of a 10% (w/w) freeze-dried black raspberry gel on oral IEN histopathology, gene expression profiles, intraepithelial COX-2 and iNOS proteins, and microvascular densities. Our laboratories have shown that freeze-dried black raspberries possess antioxidant properties and also induce keratinocyte apoptosis and terminal differentiation. Oral IEN tissues were hemisected to provide samples for pretreatment diagnoses and establish baseline biochemical and molecular variables. Treatment of the remaining lesional tissue (0.5 g gel applied four times daily for 6 weeks) began 1 week after the initial biopsy. RNA was isolated from snap-frozen IEN lesions for microarray analyses, followed by quantitative reverse transcription-PCR validation. Additional epithelial gene-specific quantitative reverse transcription-PCR analyses facilitated the assessment of target tissue treatment effects. Surface epithelial COX-2 and iNOS protein levels and microvascular densities were determined by image analysis quantified immunohistochemistry. Topical berry gel application uniformly suppressed genes associated with RNA processing, growth factor recycling, and inhibition of apoptosis. Although the majority of participants showed posttreatment decreases in epithelial iNOS and COX-2 proteins, only COX-2 reductions were statistically significant. These data show that berry gel application modulated oral IEN gene expression profiles, ultimately reducing epithelial COX-2 protein. In a patient subset, berry gel application also reduced vascular densities in the superficial connective tissues and induced genes associated with keratinocyte terminal differentiation. PMID:18559542

Gene expression profiles of metabolic aggressiveness and tumor recurrence in benign meningioma.

PubMed

Serna, Eva; Morales, José Manuel; Mata, Manuel; Gonzalez-Darder, José; San Miguel, Teresa; Gil-Benso, Rosario; Lopez-Gines, Concha; Cerda-Nicolas, Miguel; Monleon, Daniel

2013-01-01

Around 20% of meningiomas histologically benign may be clinically aggressive and recur. This strongly affects management of meningioma patients. There is a need to evaluate the potential aggressiveness of an individual meningioma. Additional criteria for better classification of meningiomas will improve clinical decisions as well as patient follow up strategy after surgery. The aim of this study was to determine the relationship between gene expression profiles and new metabolic subgroups of benign meningioma with potential clinical relevance. Forty benign and fourteen atypical meningioma tissue samples were included in the study. We obtained metabolic profiles by NMR and recurrence after surgery information for all of them. We measured gene expression by oligonucleotide microarray measurements on 19 of them. To our knowledge, this is the first time that distinct gene expression profiles are reported for benign meningioma molecular subgroups with clinical correlation. Our results show that metabolic aggressiveness in otherwise histological benign meningioma proceeds mostly through alterations in the expression of genes involved in the regulation of transcription, mainly the LMO3 gene. Genes involved in tumor metabolism, like IGF1R, are also differentially expressed in those meningioma subgroups with higher rates of membrane turnover, higher energy demand and increased resistance to apoptosis. These new subgroups of benign meningiomas exhibit different rates of recurrence. This work shows that benign meningioma with metabolic aggressiveness constitute a subgroup of potentially recurrent tumors in which alterations in genes regulating critical features of aggressiveness, like increased angiogenesis or cell invasion, are still no predominant. The determination of these gene expression biosignatures may allow the early detection of clinically aggressive tumors.

Building gene expression profile classifiers with a simple and efficient rejection option in R.

PubMed

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.

Transcriptome meta-analysis reveals common differential and global gene expression profiles in cystic fibrosis and other respiratory disorders and identifies CFTR regulators.

PubMed

Clarke, Luka A; Botelho, Hugo M; Sousa, Lisete; Falcao, Andre O; Amaral, Margarida D

2015-11-01

A meta-analysis of 13 independent microarray data sets was performed and gene expression profiles from cystic fibrosis (CF), similar disorders (COPD: chronic obstructive pulmonary disease, IPF: idiopathic pulmonary fibrosis, asthma), environmental conditions (smoking, epithelial injury), related cellular processes (epithelial differentiation/regeneration), and non-respiratory "control" conditions (schizophrenia, dieting), were compared. Similarity among differentially expressed (DE) gene lists was assessed using a permutation test, and a clustergram was constructed, identifying common gene markers. Global gene expression values were standardized using a novel approach, revealing that similarities between independent data sets run deeper than shared DE genes. Correlation of gene expression values identified putative gene regulators of the CF transmembrane conductance regulator (CFTR) gene, of potential therapeutic significance. Our study provides a novel perspective on CF epithelial gene expression in the context of other lung disorders and conditions, and highlights the contribution of differentiation/EMT and injury to gene signatures of respiratory disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis

PubMed Central

Dinalankara, Wikum; Bravo, Héctor Corrada

2015-01-01

Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings. PMID:26078586

Single-Cell RNA-Seq Reveals the Transcriptional Landscape and Heterogeneity of Aortic Macrophages in Murine Atherosclerosis.

PubMed

Cochain, Clément; Vafadarnejad, Ehsan; Arampatzi, Panagiota; Jaroslav, Pelisek; Winkels, Holger; Ley, Klaus; Wolf, Dennis; Saliba, Antoine-Emmanuel; Zernecke, Alma

2018-03-15

Rationale: It is assumed that atherosclerotic arteries contain several macrophage subsets endowed with specific functions. The precise identity of these subsets is poorly characterized as they ha ve been defined by the expression of a restricted number of markers. Objective: We have applied single-cell RNA-seq as an unbiased profiling strategy to interrogate and classify aortic macrophage heterogeneity at the single-cell level in atherosclerosis. Methods and Results: We performed single-cell RNA sequencing of total aortic CD45 + cells extracted from the non-diseased (chow fed) and atherosclerotic (11 weeks of high fat diet) aorta of Ldlr -/- mice. Unsupervised clustering singled out 13 distinct aortic cell clusters. Among the myeloid cell populations, Resident-like macrophages with a gene expression profile similar to aortic resident macrophages were found in healthy and diseased aortae, whereas monocytes, monocyte-derived dendritic cells (MoDC), and two populations of macrophages were almost exclusively detectable in atherosclerotic aortae, comprising Inflammatory macrophages showing enrichment in I l1b , and previously undescribed TREM2 hi macrophages. Differential gene expression and gene ontology enrichment analyses revealed specific gene expression patterns distinguishing these three macrophage subsets and MoDC, and uncovered putative functions of each cell type. Notably, TREM2 hi macrophages appeared to be endowed with specialized functions in lipid metabolism and catabolism, and presented a gene expression signature reminiscent of osteoclasts, suggesting a role in lesion calcification. TREM2 expression was moreover detected in human lesional macrophages. Importantly, these macrophage populations were present also in advanced atherosclerosis and in Apoe -/- aortae, indicating relevance of our findings in different stages of atherosclerosis and mouse models. Conclusions: These data unprecedentedly uncovered the transcriptional landscape and phenotypic heterogeneity of aortic macrophages and MoDCs in atherosclerotic and identified previously unrecognized macrophage populations and their gene expression signature, suggesting specialized functions. Our findings will open up novel opportunities to explore distinct myeloid cell populations and their functions in atherosclerosis.

Dose-response relationships in gene expression profiles in rainbow trout, Oncorhyncus mykiss, exposed to ethynylestradiol.

PubMed

Hook, Sharon E; Skillman, Ann D; Small, Jack A; Schultz, Irvin R

2006-07-01

Determining how gene expression profiles change with toxicant dose will improve the utility of arrays in identifying biomarkers and modes of toxic action. Isogenic rainbow trout, Oncorhyncus mykiss,were exposed to 10, 50 or 100 ng/L ethynylestradiol (a xeno-estrogen) for 7 days. Following exposure hepatic RNA was extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Atlantic Salmon/Trout array (GRASP project, University of Victoria) spotted with 16,000 cDNAs. Transcript expression in treated vs control fish was analyzed via Genespring (Silicon Genetics) to identify genes with altered expression, as well as to determine gene clustering patterns that can be used as "expression signatures". Array results were confirmed via qRT PCR. Our analysis indicates that gene expression profiles varied somewhat with dose. Established biomarkers of exposure to estrogenic chemicals, such as vitellogenin, vitelline envelope proteins, and the estrogen receptor alpha, were induced at every dose. Other genes were dose specific, suggesting that different doses induce distinct physiological responses. These findings demonstrate that cDNA microarrays could be used to identify both toxicant class and relative dose.

A proof of the DBRF-MEGN method, an algorithm for deducing minimum equivalent gene networks

PubMed Central

2011-01-01

Background We previously developed the DBRF-MEGN (difference-based regulation finding-minimum equivalent gene network) method, which deduces the most parsimonious signed directed graphs (SDGs) consistent with expression profiles of single-gene deletion mutants. However, until the present study, we have not presented the details of the method's algorithm or a proof of the algorithm. Results We describe in detail the algorithm of the DBRF-MEGN method and prove that the algorithm deduces all of the exact solutions of the most parsimonious SDGs consistent with expression profiles of gene deletion mutants. Conclusions The DBRF-MEGN method provides all of the exact solutions of the most parsimonious SDGs consistent with expression profiles of gene deletion mutants. PMID:21699737

Profiling differential gene expression of corals along a transect of waters adjacent to the Bermuda municipal dump.

PubMed

Morgan, Michael B; Edge, Sara E; Snell, Terry W

2005-01-01

A coral cDNA array containing 32 genes was used to examine the gene expression profiles of coral populations located at four sites that varied with distance from a semi-submerged municipal dump in Castle Harbour, Bermuda (previously identified as a point source of anthropogenic stressors). Genes on the array represent transcripts induced under controlled laboratory conditions to a variety of stressors both natural (temperature, sediment, salinity, darkness) and xenobiotic (heavy metals, pesticides, PAH) in origin. The gene expression profiles produced revealed information about the types of stressors. Consistent with other studies undertaken in Castle Harbour, the coral cDNA array detected responses to heavy metals, sedimentation, as well as oxidative stress.

CHANGES IN GENE EXPRESSION PROFILE FOLLOWING SHORT-TERM EXPOSURE TO AN ENVIRONMENTALLY RELEVANT MIXTURE OF PHAHS

EPA Science Inventory

Changes in gene expression profile following short-term exposure to an environmentally relevant mixture of PHAHs
Polyhalogenated aromatic hydrocarbons (PHAH) including, polychlorinated biphenyls (PCBs), polychlorinated dibenzodioxins (PCDDS) and polychlorinated dibenzofurans...

Distinct profiles of expressed sequence tags during intestinal regeneration in the sea cucumber Holothuria glaberrima

PubMed Central

Rojas-Cartagena, Carmencita; Ortíz-Pineda, Pablo; Ramírez-Gómez, Francisco; Suárez-Castillo, Edna C.; Matos-Cruz, Vanessa; Rodríguez, Carlos; Ortíz-Zuazaga, Humberto; García-Arrarás, José E.

2010-01-01

Repair and regeneration are key processes for tissue maintenance, and their disruption may lead to disease states. Little is known about the molecular mechanisms that underline the repair and regeneration of the digestive tract. The sea cucumber Holothuria glaberrima represents an excellent model to dissect and characterize the molecular events during intestinal regeneration. To study the gene expression profile, cDNA libraries were constructed from normal, 3-day, and 7-day regenerating intestines of H. glaberrima. Clones were randomly sequenced and queried against the nonredundant protein database at the National Center for Biotechnology Information. RT-PCR analyses were made of several genes to determine their expression profile during intestinal regeneration. A total of 5,173 sequences from three cDNA libraries were obtained. About 46.2, 35.6, and 26.2% of the sequences for the normal, 3-days, and 7-days cDNA libraries, respectively, shared significant similarity with known sequences in the protein database of GenBank but only present 10% of similarity among them. Analysis of the libraries in terms of functional processes, protein domains, and most common sequences suggests that a differential expression profile is taking place during the regeneration process. Further examination of the expressed sequence tag dataset revealed that 12 putative genes are differentially expressed at significant level (R > 6). Experimental validation by RT-PCR analysis reveals that at least three genes (unknown C-4677-1, melanotransferrin, and centaurin) present a differential expression during regeneration. These findings strongly suggest that the gene expression profile varies among regeneration stages and provide evidence for the existence of differential gene expression. PMID:17579180

Altered Expression of Diabetes-Related Genes in Alzheimer's Disease Brains: The Hisayama Study

PubMed Central

Hokama, Masaaki; Oka, Sugako; Leon, Julio; Ninomiya, Toshiharu; Honda, Hiroyuki; Sasaki, Kensuke; Iwaki, Toru; Ohara, Tomoyuki; Sasaki, Tomio; LaFerla, Frank M.; Kiyohara, Yutaka; Nakabeppu, Yusaku

2014-01-01

Diabetes mellitus (DM) is considered to be a risk factor for dementia including Alzheimer's disease (AD). However, the molecular mechanism underlying this risk is not well understood. We examined gene expression profiles in postmortem human brains donated for the Hisayama study. Three-way analysis of variance of microarray data from frontal cortex, temporal cortex, and hippocampus was performed with the presence/absence of AD and vascular dementia, and sex, as factors. Comparative analyses of expression changes in the brains of AD patients and a mouse model of AD were also performed. Relevant changes in gene expression identified by microarray analysis were validated by quantitative real-time reverse-transcription polymerase chain reaction and western blotting. The hippocampi of AD brains showed the most significant alteration in gene expression profile. Genes involved in noninsulin-dependent DM and obesity were significantly altered in both AD brains and the AD mouse model, as were genes related to psychiatric disorders and AD. The alterations in the expression profiles of DM-related genes in AD brains were independent of peripheral DM-related abnormalities. These results indicate that altered expression of genes related to DM in AD brains is a result of AD pathology, which may thereby be exacerbated by peripheral insulin resistance or DM. PMID:23595620

Sister grouping of chimpanzees and humans as revealed by genome-wide phylogenetic analysis of brain gene expression profiles

PubMed Central

Uddin, Monica; Wildman, Derek E.; Liu, Guozhen; Xu, Wenbo; Johnson, Robert M.; Hof, Patrick R.; Kapatos, Gregory; Grossman, Lawrence I.; Goodman, Morris

2004-01-01

Gene expression profiles from the anterior cingulate cortex (ACC) of human, chimpanzee, gorilla, and macaque samples provide clues about genetic regulatory changes in human and other catarrhine primate brains. The ACC, a cerebral neocortical region, has human-specific histological features. Physiologically, an individual's ACC displays increased activity during that individual's performance of cognitive tasks. Of ≈45,000 probe sets on microarray chips representing transcripts of all or most human genes, ≈16,000 were commonly detected in human ACC samples and comparable numbers, 14,000–15,000, in gorilla and chimpanzee ACC samples. Phylogenetic results obtained from gene expression profiles contradict the traditional expectation that the non-human African apes (i.e., chimpanzee and gorilla) should be more like each other than either should be like humans. Instead, the chimpanzee ACC profiles are more like the human than like the gorilla; these profiles demonstrate that chimpanzees are the sister group of humans. Moreover, for those unambiguous expression changes mapping to important biological processes and molecular functions that statistically are significantly represented in the data, the chimpanzee clade shows at least as much apparent regulatory evolution as does the human clade. Among important changes in the ancestry of both humans and chimpanzees, but to a greater extent in humans, are the up-regulated expression profiles of aerobic energy metabolism genes and neuronal function-related genes, suggesting that increased neuronal activity required increased supplies of energy. PMID:14976249

A 3,000-loci transcription map of chromosome 3B unravels the structural and functional features of gene islands in hexaploid wheat.

PubMed

Rustenholz, Camille; Choulet, Frédéric; Laugier, Christel; Safár, Jan; Simková, Hana; Dolezel, Jaroslav; Magni, Federica; Scalabrin, Simone; Cattonaro, Federica; Vautrin, Sonia; Bellec, Arnaud; Bergès, Hélène; Feuillet, Catherine; Paux, Etienne

2011-12-01

To improve our understanding of the organization and regulation of the wheat (Triticum aestivum) gene space, we established a transcription map of a wheat chromosome (3B) by hybridizing a newly developed wheat expression microarray with bacterial artificial chromosome pools from a new version of the 3B physical map as well as with cDNA probes derived from 15 RNA samples. Mapping data for almost 3,000 genes showed that the gene space spans the whole chromosome 3B with a 2-fold increase of gene density toward the telomeres due to an increase in the number of genes in islands. Comparative analyses with rice (Oryza sativa) and Brachypodium distachyon revealed that these gene islands are composed mainly of genes likely originating from interchromosomal gene duplications. Gene Ontology and expression profile analyses for the 3,000 genes located along the chromosome revealed that the gene islands are enriched significantly in genes sharing the same function or expression profile, thereby suggesting that genes in islands acquired shared regulation during evolution. Only a small fraction of these clusters of cofunctional and coexpressed genes was conserved with rice and B. distachyon, indicating a recent origin. Finally, genes with the same expression profiles in remote islands (coregulation islands) were identified suggesting long-distance regulation of gene expression along the chromosomes in wheat.

Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients.

PubMed

Rapin, Nicolas; Bagger, Frederik Otzen; Jendholm, Johan; Mora-Jensen, Helena; Krogh, Anders; Kohlmann, Alexander; Thiede, Christian; Borregaard, Niels; Bullinger, Lars; Winther, Ole; Theilgaard-Mönch, Kim; Porse, Bo T

2014-02-06

Gene expression profiling has been used extensively to characterize cancer, identify novel subtypes, and improve patient stratification. However, it has largely failed to identify transcriptional programs that differ between cancer and corresponding normal cells and has not been efficient in identifying expression changes fundamental to disease etiology. Here we present a method that facilitates the comparison of any cancer sample to its nearest normal cellular counterpart, using acute myeloid leukemia (AML) as a model. We first generated a gene expression-based landscape of the normal hematopoietic hierarchy, using expression profiles from normal stem/progenitor cells, and next mapped the AML patient samples to this landscape. This allowed us to identify the closest normal counterpart of individual AML samples and determine gene expression changes between cancer and normal. We find the cancer vs normal method (CvN method) to be superior to conventional methods in stratifying AML patients with aberrant karyotype and in identifying common aberrant transcriptional programs with potential importance for AML etiology. Moreover, the CvN method uncovered a novel poor-outcome subtype of normal-karyotype AML, which allowed for the generation of a highly prognostic survival signature. Collectively, our CvN method holds great potential as a tool for the analysis of gene expression profiles of cancer patients.

Cardiac Endothelial Cell Transcriptome.

PubMed

Lother, Achim; Bergemann, Stella; Deng, Lisa; Moser, Martin; Bode, Christoph; Hein, Lutz

2018-03-01

Endothelial cells (ECs) are a highly specialized cell type with marked diversity between different organs or vascular beds. Cardiac ECs are an important player in cardiac physiology and pathophysiology but are not sufficiently characterized yet. Thus, the aim of the present study was to analyze the cardiac EC transcriptome. We applied fluorescence-assisted cell sorting to isolate pure ECs from adult mouse hearts. RNAseq revealed 1288 genes predominantly expressed in cardiac ECs versus heart tissue including several transcription factors. We found an overrepresentation of corresponding transcription factor binding motifs within the promotor region of EC-enriched genes, suggesting that they control the EC transcriptome. Cardiac ECs exhibit a distinct gene expression profile when compared with renal, cerebral, or pulmonary ECs. For example, we found the Meox2 / Tcf15, Fabp4 , and Cd36 signaling cascade higher expressed in cardiac ECs which is a key regulator of fatty acid uptake and involved in the development of atherosclerosis. The results from this study provide a comprehensive resource of gene expression and transcriptional control in cardiac ECs. The cardiac EC transcriptome exhibits distinct differences in gene expression compared with other cardiac cell types and ECs from other organs. We identified new candidate genes that have not been investigated in ECs yet as promising targets for future evaluation. © 2018 American Heart Association, Inc.

Temporal network analysis identifies early physiological and transcriptomic indicators of mild drought in Brassica rapa

PubMed Central

Gehan, Malia A; Mockler, Todd C; Weinig, Cynthia; Ewers, Brent E

2017-01-01

The dynamics of local climates make development of agricultural strategies challenging. Yield improvement has progressed slowly, especially in drought-prone regions where annual crop production suffers from episodic aridity. Underlying drought responses are circadian and diel control of gene expression that regulate daily variations in metabolic and physiological pathways. To identify transcriptomic changes that occur in the crop Brassica rapa during initial perception of drought, we applied a co-expression network approach to associate rhythmic gene expression changes with physiological responses. Coupled analysis of transcriptome and physiological parameters over a two-day time course in control and drought-stressed plants provided temporal resolution necessary for correlation of network modules with dynamic changes in stomatal conductance, photosynthetic rate, and photosystem II efficiency. This approach enabled the identification of drought-responsive genes based on their differential rhythmic expression profiles in well-watered versus droughted networks and provided new insights into the dynamic physiological changes that occur during drought. PMID:28826479

Genome-Wide Evolutionary Characterization and Expression Analyses of WRKY Family Genes in Brachypodium distachyon

PubMed Central

Wen, Feng; Zhu, Hong; Li, Peng; Jiang, Min; Mao, Wenqing; Ong, Chermaine; Chu, Zhaoqing

2014-01-01

Members of plant WRKY gene family are ancient transcription factors that function in plant growth and development and respond to biotic and abiotic stresses. In our present study, we have investigated WRKY family genes in Brachypodium distachyon, a new model plant of family Poaceae. We identified a total of 86 WRKY genes from B. distachyon and explored their chromosomal distribution and evolution, domain alignment, promoter cis-elements, and expression profiles. Combining the analysis of phylogenetic tree of BdWRKY genes and the result of expression profiling, results showed that most of clustered gene pairs had higher similarities in the WRKY domain, suggesting that they might be functionally redundant. Neighbour-joining analysis of 301 WRKY domains from Oryza sativa, Arabidopsis thaliana, and B. distachyon suggested that BdWRKY domains are evolutionarily more closely related to O. sativa WRKY domains than those of A. thaliana. Moreover, tissue-specific expression profile of BdWRKY genes and their responses to phytohormones and several biotic or abiotic stresses were analysed by quantitative real-time PCR. The results showed that the expression of BdWRKY genes was rapidly regulated by stresses and phytohormones, and there was a strong correlation between promoter cis-elements and the phytohormones-induced BdWRKY gene expression. PMID:24453041

A Gene Expression Signature Associated with Overall Survival in Patients with Hepatocellular Carcinoma Suggests a New Treatment Strategy.

PubMed

Gillet, Jean-Pierre; Andersen, Jesper B; Madigan, James P; Varma, Sudhir; Bagni, Rachel K; Powell, Katie; Burgan, William E; Wu, Chung-Pu; Calcagno, Anna Maria; Ambudkar, Suresh V; Thorgeirsson, Snorri S; Gottesman, Michael M

2016-02-01

Despite improvements in the management of liver cancer, the survival rate for patients with hepatocellular carcinoma (HCC) remains dismal. The survival benefit of systemic chemotherapy for the treatment of liver cancer is only marginal. Although the reasons for treatment failure are multifactorial, intrinsic resistance to chemotherapy plays a primary role. Here, we analyzed the expression of 377 multidrug resistance (MDR)-associated genes in two independent cohorts of patients with advanced HCC, with the aim of finding ways to improve survival in this poor-prognosis cancer. Taqman-based quantitative polymerase chain reaction revealed a 45-gene signature that predicts overall survival (OS) in patients with HCC. Using the Connectivity Map Tool, we were able to identify drugs that converted the gene expression profiles of HCC cell lines from ones matching patients with poor OS to profiles associated with good OS. We found three compounds that convert the gene expression profiles of three HCC cell lines to gene expression profiles associated with good OS. These compounds increase histone acetylation, which correlates with the synergistic sensitization of those MDR tumor cells to conventional chemotherapeutic agents, including cisplatin, sorafenib, and 5-fluorouracil. Our results indicate that it is possible to modulate gene expression profiles in HCC cell lines to those associated with better outcome. This approach also increases sensitization of HCC cells toward conventional chemotherapeutic agents. This work suggests new treatment strategies for a disease for which few therapeutic options exist. U.S. Government work not protected by U.S. copyright.

Lipidomic profiling of patient-specific iPSC-derived hepatocyte-like cells

PubMed Central

Viiri, Leena E.; Vihervaara, Terhi; Koistinen, Kaisa M.; Hilvo, Mika; Ekroos, Kim; Käkelä, Reijo; Aalto-Setälä, Katriina

2017-01-01

ABSTRACT Hepatocyte-like cells (HLCs) differentiated from human induced pluripotent stem cells (iPSCs) offer an alternative model to primary human hepatocytes to study lipid aberrations. However, the detailed lipid profile of HLCs is yet unknown. In the current study, functional HLCs were differentiated from iPSCs generated from dermal fibroblasts of three individuals by a three-step protocol through the definitive endoderm (DE) stage. In parallel, detailed lipidomic analyses as well as gene expression profiling of a set of lipid-metabolism-related genes were performed during the entire differentiation process from iPSCs to HLCs. Additionally, fatty acid (FA) composition of the cell culture media at different stages was determined. Our results show that major alterations in the molecular species of lipids occurring during DE and early hepatic differentiation stages mainly mirror the quality and quantity of the FAs supplied in culture medium at each stage. Polyunsaturated phospholipids and sphingolipids with a very long FA were produced in the cells at a later stage of differentiation. This work uncovers the previously unknown lipid composition of iPSC-HLCs and its alterations during the differentiation in conjunction with the expression of key lipid-associated genes. Together with biochemical, functional and gene expression measurements, the lipidomic analyses allowed us to improve our understanding of the concerted influence of the exogenous metabolite supply and cellular biosynthesis essential for iPSC-HLC differentiation and function. Importantly, the study describes in detail a cell model that can be applied in exploring, for example, the lipid metabolism involved in the development of fatty liver disease or atherosclerosis. PMID:28733363

The Rice B-Box Zinc Finger Gene Family: Genomic Identification, Characterization, Expression Profiling and Diurnal Analysis

PubMed Central

Huang, Jianyan; Zhao, Xiaobo; Weng, Xiaoyu; Wang, Lei; Xie, Weibo

2012-01-01

Background The B-box (BBX) -containing proteins are a class of zinc finger proteins that contain one or two B-box domains and play important roles in plant growth and development. The Arabidopsis BBX gene family has recently been re-identified and renamed. However, there has not been a genome-wide survey of the rice BBX (OsBBX) gene family until now. Methodology/Principal Findings In this study, we identified 30 rice BBX genes through a comprehensive bioinformatics analysis. Each gene was assigned a uniform nomenclature. We described the chromosome localizations, gene structures, protein domains, phylogenetic relationship, whole life-cycle expression profile and diurnal expression patterns of the OsBBX family members. Based on the phylogeny and domain constitution, the OsBBX gene family was classified into five subfamilies. The gene duplication analysis revealed that only chromosomal segmental duplication contributed to the expansion of the OsBBX gene family. The expression profile of the OsBBX genes was analyzed by Affymetrix GeneChip microarrays throughout the entire life-cycle of rice cultivar Zhenshan 97 (ZS97). In addition, microarray analysis was performed to obtain the expression patterns of these genes under light/dark conditions and after three phytohormone treatments. This analysis revealed that the expression patterns of the OsBBX genes could be classified into eight groups. Eight genes were regulated under the light/dark treatments, and eleven genes showed differential expression under at least one phytohormone treatment. Moreover, we verified the diurnal expression of the OsBBX genes using the data obtained from the Diurnal Project and qPCR analysis, and the results indicated that many of these genes had a diurnal expression pattern. Conclusions/Significance The combination of the genome-wide identification and the expression and diurnal analysis of the OsBBX gene family should facilitate additional functional studies of the OsBBX genes. PMID:23118960

Comparisons of Robustness and Sensitivity between Cancer and Normal Cells by Microarray Data

PubMed Central

Chu, Liang-Hui; Chen, Bor-Sen

2008-01-01

Robustness is defined as the ability to uphold performance in face of perturbations and uncertainties, and sensitivity is a measure of the system deviations generated by perturbations to the system. While cancer appears as a robust but fragile system, few computational and quantitative evidences demonstrate robustness tradeoffs in cancer. Microarrays have been widely applied to decipher gene expression signatures in human cancer research, and quantification of global gene expression profiles facilitates precise prediction and modeling of cancer in systems biology. We provide several efficient computational methods based on system and control theory to compare robustness and sensitivity between cancer and normal cells by microarray data. Measurement of robustness and sensitivity by linear stochastic model is introduced in this study, which shows oscillations in feedback loops of p53 and demonstrates robustness tradeoffs that cancer is a robust system with some extreme fragilities. In addition, we measure sensitivity of gene expression to perturbations in other gene expression and kinetic parameters, discuss nonlinear effects in feedback loops of p53 and extend our method to robustness-based cancer drug design. PMID:19259409

Lung tumor diagnosis and subtype discovery by gene expression profiling.

PubMed

Wang, Lu-yong; Tu, Zhuowen

2006-01-01

The optimal treatment of patients with complex diseases, such as cancers, depends on the accurate diagnosis by using a combination of clinical and histopathological data. In many scenarios, it becomes tremendously difficult because of the limitations in clinical presentation and histopathology. To accurate diagnose complex diseases, the molecular classification based on gene or protein expression profiles are indispensable for modern medicine. Moreover, many heterogeneous diseases consist of various potential subtypes in molecular basis and differ remarkably in their response to therapies. It is critical to accurate predict subgroup on disease gene expression profiles. More fundamental knowledge of the molecular basis and classification of disease could aid in the prediction of patient outcome, the informed selection of therapies, and identification of novel molecular targets for therapy. In this paper, we propose a new disease diagnostic method, probabilistic boosting tree (PB tree) method, on gene expression profiles of lung tumors. It enables accurate disease classification and subtype discovery in disease. It automatically constructs a tree in which each node combines a number of weak classifiers into a strong classifier. Also, subtype discovery is naturally embedded in the learning process. Our algorithm achieves excellent diagnostic performance, and meanwhile it is capable of detecting the disease subtype based on gene expression profile.

Global gene expression profiling of brown to white adipose tissue transformation in sheep reveals novel transcriptional components linked to adipose remodeling.

PubMed

Basse, Astrid L; Dixen, Karen; Yadav, Rachita; Tygesen, Malin P; Qvortrup, Klaus; Kristiansen, Karsten; Quistorff, Bjørn; Gupta, Ramneek; Wang, Jun; Hansen, Jacob B

2015-03-19

Large mammals are capable of thermoregulation shortly after birth due to the presence of brown adipose tissue (BAT). The majority of BAT disappears after birth and is replaced by white adipose tissue (WAT). We analyzed the postnatal transformation of adipose in sheep with a time course study of the perirenal adipose depot. We observed changes in tissue morphology, gene expression and metabolism within the first two weeks of postnatal life consistent with the expected transition from BAT to WAT. The transformation was characterized by massively decreased mitochondrial abundance and down-regulation of gene expression related to mitochondrial function and oxidative phosphorylation. Global gene expression profiling demonstrated that the time points grouped into three phases: a brown adipose phase, a transition phase and a white adipose phase. Between the brown adipose and the transition phase 170 genes were differentially expressed, and 717 genes were differentially expressed between the transition and the white adipose phase. Thirty-eight genes were shared among the two sets of differentially expressed genes. We identified a number of regulated transcription factors, including NR1H3, MYC, KLF4, ESR1, RELA and BCL6, which were linked to the overall changes in gene expression during the adipose tissue remodeling. Finally, the perirenal adipose tissue expressed both brown and brite/beige adipocyte marker genes at birth, the expression of which changed substantially over time. Using global gene expression profiling of the postnatal BAT to WAT transformation in sheep, we provide novel insight into adipose tissue plasticity in a large mammal, including identification of novel transcriptional components linked to adipose tissue remodeling. Moreover, our data set provides a useful resource for further studies in adipose tissue plasticity.

Genome-wide Gene Expression Profiling of Acute Metal Exposures in Male Zebrafish

DTIC Science & Technology

2014-10-23

Data in Brief Genome-wide gene expression profiling of acute metal exposures in male zebrafish Christine E. Baer a,⁎, Danielle L. Ippolito b, Naissan... Zebrafish Whole organism Nickel Chromium Cobalt Toxicogenomics To capture global responses to metal poisoning and mechanistic insights into metal...toxicity, gene expression changes were evaluated in whole adult male zebrafish following acute 24 h high dose exposure to three metals with known human

Gene expression profiling reveals different molecular patterns in G-protein coupled receptor signaling pathways between early- and late-onset preeclampsia.

PubMed

Liang, Mengmeng; Niu, Jianmin; Zhang, Liang; Deng, Hua; Ma, Jian; Zhou, Weiping; Duan, Dongmei; Zhou, Yuheng; Xu, Huikun; Chen, Longding

2016-04-01

Early-onset preeclampsia and late-onset preeclampsia have been regarded as two different phenotypes with heterogeneous manifestations; To gain insights into the pathogenesis of the two traits, we analyzed the gene expression profiles in preeclamptic placentas. A whole genome-wide microarray was used to determine the gene expression profiles in placental tissues from patients with early-onset (n = 7; <34 weeks), and late-onset (n = 8; >36 weeks) preeclampsia and their controls who delivered preterm (n = 5; <34 weeks) or at term (n = 5; >36 weeks). Genes were termed differentially expressed if they showed a fold-change ≥ 2 and q-value < 0.05. Quantitative real-time reverse transcriptase PCR was used to verify the results. Western blotting was performed to verify the expressions of secreted genes at the protein level. Six hundred twenty-seven genes were differentially expressed in early-compared with late-onset preeclampsia (177 genes were up-regulated and 450 were down-regulated). Gene ontology analysis identified significant alterations in several biological processes; the top two were immune response and cell surface receptor linked signal transduction. Among the cell surface receptor linked signal transduction-related, differentially expressed genes, those involved in the G-protein coupled receptor protein signaling pathway were significantly enriched. G-protein coupled receptor signaling pathway related genes, such as GPR124 and MRGPRF, were both found to be down-regulated in early-onset preeclampsia. The results were consistent with those of western blotting that the abundance of GPR124 was lower in early-onset compared with late-onset preeclampsia. The different gene expression profiles reflect the different levels of transcription regulation between the two conditions and supported the hypothesis that they are separate disease entities. Moreover, the G-protein coupled receptor signaling pathway related genes may contribute to the mechanism underlying early- and late-onset preeclampsia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of gene expression profiling associated with erlotinib-related skin toxicity in pancreatic adenocarcinoma patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caba, Octavio, E-mail: ocaba@ujaen.es

Erlotinib is an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor that showed activity against pancreatic ductal adenocarcinoma (PDAC). The drug's most frequently reported side effect as a result of EGFR inhibition is skin rash (SR), a symptom which has been associated with a better therapeutic response to the drug. Gene expression profiling can be used as a tool to predict which patients will develop this important cutaneous manifestation. The aim of the present study was to identify which genes may influence the appearance of SR in PDAC patients. The study included 34 PDAC patients treated with erlotinib: 21 patientsmore » developed any grade of SR, while 13 patients did not (controls). Before administering any chemotherapy regimen and the development of SR, we collected RNA from peripheral blood samples of all patients and studied the differential gene expression pattern using the Illumina microarray platform HumanHT-12 v4 Expression BeadChip. Seven genes (FAM46C, IFITM3, GMPR, DENND6B, SELENBP1, NOL10, and SIAH2), involved in different pathways including regulatory, migratory, and signalling processes, were downregulated in PDAC patients with SR. Our results suggest the existence of a gene expression profiling significantly correlated with erlotinib-induced SR in PDAC that could be used as prognostic indicator in this patients. - Highlights: • Skin rash (SR) is the most characteristic side effect of erlotinib in PDAC patients. • Erlotinib-induced SR has been associated with a better clinical outcome. • Gene expression profiling was used to determine who will develop this manifestation. • 7 genes involved in different pathways were downregulated in PDAC patients with SR. • Our profile correlated with erlotinib-induced SR in PDAC could be used for prognosis.« less

Gene structure, phylogeny and expression profile of the sucrose synthase gene family in cacao (Theobroma cacao L.).

PubMed

Li, Fupeng; Hao, Chaoyun; Yan, Lin; Wu, Baoduo; Qin, Xiaowei; Lai, Jianxiong; Song, Yinghui

2015-09-01

In higher plants, sucrose synthase (Sus, EC 2.4.1.13) is widely considered as a key enzyme involved in sucrose metabolism. Although, several paralogous genes encoding different isozymes of Sus have been identified and characterized in multiple plant genomes, to date detailed information about the Sus genes is lacking for cacao. This study reports the identification of six novel Sus genes from economically important cacao tree. Analyses of the gene structure and phylogeny of the Sus genes demonstrated evolutionary conservation in the Sus family across cacao and other plant species. The expression of cacao Sus genes was investigated via real-time PCR in various tissues, different developmental phases of leaf, flower bud and pod. The Sus genes exhibited distinct but partially redundant expression profiles in cacao, with TcSus1, TcSus5 and TcSus6, being the predominant genes in the bark with phloem, TcSus2 predominantly expressing in the seed during the stereotype stage. TcSus3 and TcSus4 were significantly detected more in the pod husk and seed coat along the pod development, and showed development dependent expression profiles in the cacao pod. These results provide new insights into the evolution, and basic information that will assist in elucidating the functions of cacao Sus gene family.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

PubMed

Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

PubMed

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

The resemblance and disparity of gene expression in dormant and non-dormant seeds and crown buds of leafy spurge (Euphorbia esula)

USDA-ARS?s Scientific Manuscript database

Overlaps in transcriptome profiles between different phases of bud and seed dormancy have not been determined. Thus, we compared various phases of dormancy between seeds and buds to identify common genes and molecular processes. Cluster analysis of expression profiles for 201 selected genes indicate...

A combined analysis of genome-wide expression profiling of bipolar disorder in human prefrontal cortex.

PubMed

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.

Aberrant Calreticulin Expression in Articular Cartilage of Dio2 Deficient Mice

PubMed Central

Bomer, Nils; Cornelis, Frederique M. F.; Ramos, Yolande F. M.; den Hollander, Wouter; Lakenberg, Nico; van der Breggen, Ruud; Storms, Lies; Slagboom, P. Eline; Lories, Rik J. U.; Meulenbelt, Ingrid

2016-01-01

Objective To identify intrinsic differences in cartilage gene expression profiles between wild-type- and Dio2-/--mice, as a mechanism to investigate factors that contribute to prolonged healthy tissue homeostasis. Methods Previously generated microarray-data (Illumina MouseWG-6 v2) of knee cartilage of wild-type and Dio2 -/- -mice were re-analyzed to identify differential expressed genes independent of mechanical loading conditions by forced treadmill-running. RT-qPCR and western blot analyses of overexpression and knockdown of Calr in mouse chondro-progenitor cells (ATDC5) were applied to assess the direct effect of differential Calr expression on cartilage deposition. Results Differential expression analyses of articular cartilage of Dio2-/- (N = 9) and wild-type-mice (N = 11) while applying a cutoff threshold (P < 0.05 (FDR) and FC > |1,5|) resulted in 1 probe located in Calreticulin (Calr) that was found significantly downregulated in Dio2-/- mice (FC = -1.731; P = 0.044). Furthermore, overexpression of Calr during early chondrogenesis in ATDC5 cells leads to decreased proteoglycan deposition and corresponding lower Aggrecan expression, whereas knocking down Calr expression does not lead to histological differences of matrix composition. Conclusion We here demonstrate that the beneficial homeostatic state of articular cartilage in Dio2-/- mice is accompanied with significant lower expression of Calr. Functional analyses further showed that upregulation of Calr expression could act as an initiator of cartilage destruction. The consistent association between Calr and Dio2 expression suggests that enhanced expression of these genes facilitate detrimental effects on cartilage integrity. PMID:27163789

Differential chemokine, chemokine receptor and cytokine expression in Epstein-Barr virus-associated lymphoproliferative diseases.

PubMed

Ohshima, Koichi; Karube, Kennosuke; Hamasaki, Makoto; Tutiya, Takeshi; Yamaguchi, Takahiro; Suefuji, Hiroaki; Suzuki, Keiko; Suzumiya, Junji; Ohga, Shouichi; Kikuchi, Masahiro

2003-08-01

T cell immunity plays an important role in the clinicopathology of Epstein-Barr virus (EBV)-associated diseases. Acute EBV-induced infectious mononucleosis (IM) is a common self-limiting disease, however, other EBV-associated diseases, including chronic active EBV infection (CAEBV), NK cell lymphoma (NKL), and Hodgkin's lymphoma (HL), exhibit distinct clinical features. Chemokines are members of a family of small-secreted proteins. The relationships between chemokines and the chemokine receptor (R) are thought to be important for selectivity of local immunity. Some chemokines, chemokine R and cytokines closely associate with the T cell subtypes, Th1 and Th2 T cells and cytotoxic cells. To clarify the role of T cell immunity in EBV-associated diseases, we conducted gene expression profiling, using chemokine, chemokine R and cytokine DNA chips. Compared to EBV negative non-specific lymphadenitis, CAEBV and NKL exhibited diffuse down- and up-regulation, respectively, of these gene profiles. IM had a predominantly Th1-type profile, whereas HL had a mixed Th1/Th2-type profile. Reduction of the Th1-type cytokine interferon gamma (IFN-gamma) in CAEBV was confirmed by Reverse transcriptase-polymerase chain reaction, whereas IFN-gamma expression was markedly enhanced in NKL, and moderately enhanced in IM. Compared to IM, CAEBV showed slight elevation of "regulated upon activation, normal T expressed and secreted" (RANTES), but almost all other genes assayed were down-regulated. NKL exhibited elevated expression of numerous genes, particularly IFN-gamma-inducible-10 (IP-10) and monokine induced by IFN-gamma (MIG). HL showed variable elevated and reduced expression of various genes, with increased expression of IL-13 receptor and MIG. Our study demonstrated the enormous potential of gene expression profiling for clarifying the pathogenesis of EBV-associated diseases.

[Differentially expressed genes of cell signal transduction associated with benzene poisoning by cDNA microarray].

PubMed

Wang, Hong; Bi, Yongyi; Tao, Ning; Wang, Chunhong

2005-08-01

To detect the differential expression of cell signal transduction genes associated with benzene poisoning, and to explore the pathogenic mechanisms of blood system damage induced by benzene. Peripheral white blood cell gene expression profile of 7 benzene poisoning patients, including one aplastic anemia, was determined by cDNA microarray. Seven chips from normal workers were served as controls. Cluster analysis of gene expression profile was performed. Among the 4265 target genes, 176 genes associated with cell signal transduction were differentially expressed. 35 up-regulated genes including PTPRC, STAT4, IFITM1 etc were found in at least 6 pieces of microarray; 45 down-regulated genes including ARHB, PPP3CB, CDC37 etc were found in at least 5 pieces of microarray. cDNA microarray technology is an effective technique for screening the differentially expressed genes of cell signal transduction. Disorder in cell signal transduction may play certain role in the pathogenic mechanism of benzene poisoning.

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.

Oxidative stress gene expression profile in inbred mouse after ischemia/reperfusion small bowel injury.

PubMed

Bertoletto, Paulo Roberto; Ikejiri, Adauto Tsutomu; Somaio Neto, Frederico; Chaves, José Carlos; Teruya, Roberto; Bertoletto, Eduardo Rodrigues; Taha, Murched Omar; Fagundes, Djalma José

2012-11-01

To determine the profile of gene expressions associated with oxidative stress and thereby contribute to establish parameters about the role of enzyme clusters related to the ischemia/reperfusion intestinal injury. Twelve male inbred mice (C57BL/6) were randomly assigned: Control Group (CG) submitted to anesthesia, laparotomy and observed by 120 min; Ischemia/reperfusion Group (IRG) submitted to anesthesia, laparotomy, 60 min of small bowel ischemia and 60 min of reperfusion. A pool of six samples was submitted to the qPCR-RT protocol (six clusters) for mouse oxidative stress and antioxidant defense pathways. On the 84 genes investigated, 64 (76.2%) had statistic significant expression and 20 (23.8%) showed no statistical difference to the control group. From these 64 significantly expressed genes, 60 (93.7%) were up-regulated and 04 (6.3%) were down-regulated. From the group with no statistical significantly expression, 12 genes were up-regulated and 8 genes were down-regulated. Surprisingly, 37 (44.04%) showed a higher than threefold up-regulation and then arbitrarily the values was considered as a very significant. Thus, 37 genes (44.04%) were expressed very significantly up-regulated. The remained 47 (55.9%) genes were up-regulated less than three folds (35 genes - 41.6%) or down-regulated less than three folds (12 genes - 14.3%). The intestinal ischemia and reperfusion promote a global hyper-expression profile of six different clusters genes related to antioxidant defense and oxidative stress.

Seasonal Variation in the Skin Transcriptome of Common Bottlenose Dolphins (Tursiops truncatus) from the Northern Gulf of Mexico

PubMed Central

Van Dolah, Frances M.; Neely, Marion G.; McGeorge, Lauren E.; Balmer, Brian C.; Ylitalo, Gina M.; Zolman, Eric S.; Speakman, Todd; Sinclair, Carrie; Kellar, Nicholas M.; Rosel, Patricia E.; Mullin, Keith D.; Schwacke, Lori H.

2015-01-01

As long-lived predators that integrate exposures across multiple trophic levels, cetaceans are recognized as sentinels for the health of marine ecosystems. Their utility as sentinels requires the establishment of baseline health parameters. Because cetaceans are protected, measurements obtained with minimal disruption to free ranging animals are highly desirable. In this study we investigated the utility of skin gene expression profiling to monitor health and contaminant exposure in common bottlenose dolphins (Tursiops truncatus). Remote integument biopsies were collected in the northern Gulf of Mexico prior to the Deepwater Horizon oil spill (May 2010) and during summer and winter for two years following oil contamination (2010-2011). A bottlenose dolphin microarray was used to characterize the skin transcriptomes of 94 individuals from three populations: Barataria Bay, Louisiana, Chandeleur Sound, Louisiana, and Mississippi Sound, Mississippi/Alabama. Skin transcriptomes did not differ significantly between populations. In contrast, season had a profound effect on gene expression, with nearly one-third of all genes on the array differing in expression between winter and the warmer seasons (moderated T-test; p<0.01, fold-change≥1.5). Persistent organic pollutants (POPs) in blubber changed concurrently, reaching >two-fold higher concentrations in summer compared to winter, due to a seasonal decrease in blubber thickness and loss of stored lipid. However, global gene expression did not correlate strongly with seasonally changing contaminant concentrations, most likely because the refractory, lipid-stored metabolites are not substrates for phase I or II xenobiotic detoxification pathways. Rather, processes related to cell proliferation, motility, and differentiation dominated the differences in expression in winter and the warmer seasons. More subtle differences were seen between spring and summer (1.5% of genes differentially expressed). However, two presumed oil-exposed animals from spring presented gene expression profiles more similar to the summer animals (presumed exposed) than to other spring animals. Seasonal effects have not previously been considered in studies assessing gene expression in cetaceans, but clearly must be taken into account when applying transcriptomic analyses to investigate their contaminant exposure or health status. PMID:26110790

Seasonal variation in the skin transcriptome of common bottlenose dolphins (Tursiops truncatus) from the northern Gulf of Mexico.

PubMed

Van Dolah, Frances M; Neely, Marion G; McGeorge, Lauren E; Balmer, Brian C; Ylitalo, Gina M; Zolman, Eric S; Speakman, Todd; Sinclair, Carrie; Kellar, Nicholas M; Rosel, Patricia E; Mullin, Keith D; Schwacke, Lori H

2015-01-01

As long-lived predators that integrate exposures across multiple trophic levels, cetaceans are recognized as sentinels for the health of marine ecosystems. Their utility as sentinels requires the establishment of baseline health parameters. Because cetaceans are protected, measurements obtained with minimal disruption to free ranging animals are highly desirable. In this study we investigated the utility of skin gene expression profiling to monitor health and contaminant exposure in common bottlenose dolphins (Tursiops truncatus). Remote integument biopsies were collected in the northern Gulf of Mexico prior to the Deepwater Horizon oil spill (May 2010) and during summer and winter for two years following oil contamination (2010-2011). A bottlenose dolphin microarray was used to characterize the skin transcriptomes of 94 individuals from three populations: Barataria Bay, Louisiana, Chandeleur Sound, Louisiana, and Mississippi Sound, Mississippi/Alabama. Skin transcriptomes did not differ significantly between populations. In contrast, season had a profound effect on gene expression, with nearly one-third of all genes on the array differing in expression between winter and the warmer seasons (moderated T-test; p<0.01, fold-change≥1.5). Persistent organic pollutants (POPs) in blubber changed concurrently, reaching >two-fold higher concentrations in summer compared to winter, due to a seasonal decrease in blubber thickness and loss of stored lipid. However, global gene expression did not correlate strongly with seasonally changing contaminant concentrations, most likely because the refractory, lipid-stored metabolites are not substrates for phase I or II xenobiotic detoxification pathways. Rather, processes related to cell proliferation, motility, and differentiation dominated the differences in expression in winter and the warmer seasons. More subtle differences were seen between spring and summer (1.5% of genes differentially expressed). However, two presumed oil-exposed animals from spring presented gene expression profiles more similar to the summer animals (presumed exposed) than to other spring animals. Seasonal effects have not previously been considered in studies assessing gene expression in cetaceans, but clearly must be taken into account when applying transcriptomic analyses to investigate their contaminant exposure or health status.

Blood gene expression profiling of an early acetaminophen response.

PubMed

Bushel, P R; Fannin, R D; Gerrish, K; Watkins, P B; Paules, R S

2017-06-01

Acetaminophen can adversely affect the liver especially when overdosed. We used whole blood as a surrogate to identify genes as potential early indicators of an acetaminophen-induced response. In a clinical study, healthy human subjects were dosed daily with 4 g of either acetaminophen or placebo pills for 7 days and evaluated over the course of 14 days. Alanine aminotransferase (ALT) levels for responders to acetaminophen increased between days 4 and 9 after dosing, and 12 genes were detected with expression profiles significantly altered within 24 h. The early responsive genes separated the subjects by class and dose period. In addition, the genes clustered patients who overdosed on acetaminophen apart from controls and also predicted the exposure classifications with 100% accuracy. The responsive genes serve as early indicators of an acetaminophen exposure, and their gene expression profiles can potentially be evaluated as molecular indicators for further consideration.

Blood Gene Expression Profiling of an Early Acetaminophen Response

PubMed Central

Bushel, Pierre R.; Fannin, Rick D.; Gerrish, Kevin; Watkins, Paul B.; Paules, Richard S.

2018-01-01

Acetaminophen can adversely affect the liver especially when overdosed. We used whole blood as a surrogate to identify genes as potential early indicators of an acetaminophen-induced response. In a clinical study, healthy human subjects were dosed daily with 4g of either acetaminophen or placebo pills for 7 days and evaluated over the course of 14 days. Alanine aminotransferase (ALT) levels for responders to acetaminophen increased between days 4 and 9 after dosing and 12 genes were detected with expression profiles significantly altered within 24 hrs. The early responsive genes separated the subjects by class and dose period. In addition, the genes clustered patients who overdosed on acetaminophen apart from controls and also predicted the exposure classifications with 100% accuracy. The responsive genes serve as early indicators of an acetaminophen exposure and their gene expression profiles can potentially be evaluated as molecular indicators for further consideration. PMID:26927286

Automated cell-type classification in intact tissues by single-cell molecular profiling

PubMed Central

2018-01-01

A major challenge in biology is identifying distinct cell classes and mapping their interactions in vivo. Tissue-dissociative technologies enable deep single cell molecular profiling but do not provide spatial information. We developed a proximity ligation in situ hybridization technology (PLISH) with exceptional signal strength, specificity, and sensitivity in tissue. Multiplexed data sets can be acquired using barcoded probes and rapid label-image-erase cycles, with automated calculation of single cell profiles, enabling clustering and anatomical re-mapping of cells. We apply PLISH to expression profile ~2900 cells in intact mouse lung, which identifies and localizes known cell types, including rare ones. Unsupervised classification of the cells indicates differential expression of ‘housekeeping’ genes between cell types, and re-mapping of two sub-classes of Club cells highlights their segregated spatial domains in terminal airways. By enabling single cell profiling of various RNA species in situ, PLISH can impact many areas of basic and medical research. PMID:29319504

Differential expression profiles and pathways of genes in sugarcane leaf at elongation stage in response to drought stress

PubMed Central

Li, Changning; Nong, Qian; Solanki, Manoj Kumar; Liang, Qiang; Xie, Jinlan; Liu, Xiaoyan; Li, Yijie; Wang, Weizan; Yang, Litao; Li, Yangrui

2016-01-01

Water stress causes considerable yield losses in sugarcane. To investigate differentially expressed genes under water stress, a pot experiment was performed with the sugarcane variety GT21 at three water-deficit levels (mild, moderate, and severe) during the elongation stage and gene expression was analyzed using microarray technology. Physiological parameters of sugarcane showed significant alterations in response to drought stress. Based on the expression profile of 15,593 sugarcane genes, 1,501 (9.6%) genes were differentially expressed under different water-level treatments; 821 genes were upregulated and 680 genes were downregulated. A gene similarity analysis showed that approximately 62.6% of the differentially expressed genes shared homology with functional proteins. In a Gene Ontology (GO) analysis, 901 differentially expressed genes were assigned to 36 GO categories. Moreover, 325 differentially expressed genes were classified into 101 pathway categories involved in various processes, such as the biosynthesis of secondary metabolites, ribosomes, carbon metabolism, etc. In addition, some unannotated genes were detected; these may provide a basis for studies of water-deficit tolerance. The reliability of the observed expression patterns was confirmed by RT-PCR. The results of this study may help identify useful genes for improving drought tolerance in sugarcane. PMID:27170459

[Chiparray-based identification of gene expression in HUVECs treated with low frequency electric fields].

PubMed

Ulrich, D; Ulrich, F; Silny, J; Unglaub, F; Pallua, N

2006-06-01

After high-voltage electric injury, patients often show progressive tissue necrosis and thrombosis of blood vessels even remote from the entry and exit sites of electrical current. Recently, we were able to demonstrate IN VIVO and VITRO the release of several prothrombotic factors. In this study, we report on IN VITRO studies performed to characterize gene expression profiles using a DNA-microarray in HUVECs (human umbilical vein endothelial cells) exposed to low frequency electrical current. HUVECs were plated and grown to confluence in a culture chamber. They were exposed to 25 periods of 50 Hz sinusoidal waves. The periods had field strength of 60 V/cm and duration of 100 ms. Periods were interrupted by 10-second intervals to prevent significant joule heating. Control HUVECs were treated identically except that no electric field was applied. Samples from control and treated cells were taken after six and 24 hours. A PIQOR Immunology Array (Milteny Biotech) containing 1076 cDNAs was used for gene expression analysis. Hybridization of Cy3- and Cy5-labelled samples, image capture, and signal quantification of hybridized arrays were performed. Local background was subtracted from the signal to obtain the net signal intensity and the ratio of Cy5/Cy3. The ratios were normalized to the median of all ratios and the mean of the ratios of four corresponding spots was computed. More than two-fold increases or decreases of the gene expression were regarded as relevant. A total of 413 genes (1s + s) respectively 345 genes (2s + s) could be detected. The results obtained display a distinct expression pattern of up-regulated genes known to be important for hemostasis (e.g. UPA, UPAR, ECE1, PAFAH1B1, PGT, INOS, ENOS, TPA, ICAM1, VCAM1, PAI1, PAI2, VWF, PTGDR, F3, THBD), which was most evident after 24 hours. This expression profile might lead to a hypercoagulated state. Furthermore, the expression of genes involved in angiogenesis was reduced whereas the expression of those involved in platelet formation was increased. Our results indicate that low frequency electrical fields induce a distinct signature of differential gene expression in exposed HUVECs. This might explain the clinical observation of thrombosis and progressive tissue necrosis after electrical injury.

ColoLipidGene: signature of lipid metabolism-related genes to predict prognosis in stage-II colon cancer patients

PubMed Central

Vargas, Teodoro; Moreno-Rubio, Juan; Herranz, Jesús; Cejas, Paloma; Molina, Susana; González-Vallinas, Margarita; Mendiola, Marta; Burgos, Emilio; Aguayo, Cristina; Custodio, Ana B.; Machado, Isidro; Ramos, David; Gironella, Meritxell; Espinosa-Salinas, Isabel; Ramos, Ricardo; Martín-Hernández, Roberto; Risueño, Alberto; De Las Rivas, Javier; Reglero, Guillermo; Yaya, Ricardo; Fernández-Martos, Carlos; Aparicio, Jorge; Maurel, Joan; Feliu, Jaime; de Molina, Ana Ramírez

2015-01-01

Lipid metabolism plays an essential role in carcinogenesis due to the requirements of tumoral cells to sustain increased structural, energetic and biosynthetic precursor demands for cell proliferation. We investigated the association between expression of lipid metabolism-related genes and clinical outcome in intermediate-stage colon cancer patients with the aim of identifying a metabolic profile associated with greater malignancy and increased risk of relapse. Expression profile of 70 lipid metabolism-related genes was determined in 77 patients with stage II colon cancer. Cox regression analyses using c-index methodology was applied to identify a metabolic-related signature associated to prognosis. The metabolic signature was further confirmed in two independent validation sets of 120 patients and additionally, in a group of 264 patients from a public database. The combined analysis of these 4 genes, ABCA1, ACSL1, AGPAT1 and SCD, constitutes a metabolic-signature (ColoLipidGene) able to accurately stratify stage II colon cancer patients with 5-fold higher risk of relapse with strong statistical power in the four independent groups of patients. The identification of a group of 4 genes that predict survival in intermediate-stage colon cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy, and avoids the toxic and unnecessary chemotherapy in patients classified as low-risk group. PMID:25749516

Case-based retrieval framework for gene expression data.

PubMed

Anaissi, Ali; Goyal, Madhu; Catchpoole, Daniel R; Braytee, Ali; Kennedy, Paul J

2015-01-01

The process of retrieving similar cases in a case-based reasoning system is considered a big challenge for gene expression data sets. The huge number of gene expression values generated by microarray technology leads to complex data sets and similarity measures for high-dimensional data are problematic. Hence, gene expression similarity measurements require numerous machine-learning and data-mining techniques, such as feature selection and dimensionality reduction, to be incorporated into the retrieval process. This article proposes a case-based retrieval framework that uses a k-nearest-neighbor classifier with a weighted-feature-based similarity to retrieve previously treated patients based on their gene expression profiles. The herein-proposed methodology is validated on several data sets: a childhood leukemia data set collected from The Children's Hospital at Westmead, as well as the Colon cancer, the National Cancer Institute (NCI), and the Prostate cancer data sets. Results obtained by the proposed framework in retrieving patients of the data sets who are similar to new patients are as follows: 96% accuracy on the childhood leukemia data set, 95% on the NCI data set, 93% on the Colon cancer data set, and 98% on the Prostate cancer data set. The designed case-based retrieval framework is an appropriate choice for retrieving previous patients who are similar to a new patient, on the basis of their gene expression data, for better diagnosis and treatment of childhood leukemia. Moreover, this framework can be applied to other gene expression data sets using some or all of its steps.

SPERM RNA AMPLIFICATION FOR GENE EXPRESSION PROFILING BY DNA MICROARRAY TECHNOLOGY

EPA Science Inventory

Sperm RNA Amplification for Gene Expression Profiling by DNA Microarray Technology
Hongzu Ren, Kary E. Thompson, Judith E. Schmid and David J. Dix, Reproductive Toxicology Division, NHEERL, Office of Research and Development, US Environmental Protection Agency, Research Triang...

EXPRESSION PROFILING OF FIVE RAT STRAINS REVEAL TRANSCRIPTIONAL MODES IN THE ANTIGEN PROCESSING PATHWAY

EPA Science Inventory

Comparative gene expression profiling of rat strains with genetic predisposition to diverse cardiovascular diseases can help decode the transcriptional program that governs cellular behavior. We hypothesized that co-transcribed, intra-pathway, functionally coherent genes can be r...

GENE EXPRESSION PROFILING TO IDENTIFY MECHANISMS OF MALE REPRODUCTIVE TOXICITY

EPA Science Inventory

Gene Expression Profiling to Identify Mechanisms of Male Reproductive Toxicity
David J. Dix
National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA.
Ab...

Expression profiles of sugarcane under drought conditions: Variation in gene regulation.

PubMed

Andrade, Júlio César Farias de; Terto, Jackeline; Silva, José Vieira; Almeida, Cícero

2015-12-01

Drought is a major factor in decreased sugarcane productivity because of the resulting morphophysiological effects that it causes. Gene expression studies that have examined the influence of water stress in sugarcane have yielded divergent results, indicating the absence of a fixed pattern of changes in gene expression. In this work, we investigated the expression profiles of 12 genes in the leaves of a drought-tolerant genotype (RB72910) of sugarcane and compared the results with those of other studies. The genotype was subjected to 80-100% water availability (control condition) and 0-20% water availability (simulated drought). To analyze the physiological status, the SPAD index, Fv/Fm ratio, net photosynthesis (A), stomatal conductance (gs) and stomatal transpiration (E) were measured. Total RNA was extracted from leaves and the expression of SAMDC, ZmPIP2-1 protein, ZmTIP4-2 protein, WIP protein, LTP protein, histone H3, DNAj, ferredoxin I, β-tubulin, photosystem I, gene 1 and gene 2 was analyzed by quantitative real-time PCR (RT-PCR). Important differences in the expression profiles of these genes were observed when compared with other genotypes, suggesting that complex defense mechanisms are activated in response to water stress. However, there was no recognizable pattern for the changes in expression of the different proteins associated with tolerance to drought stress.

mRNA expression profiling of laser microbeam microdissected cells from slender embryonic structures.

PubMed

Scheidl, Stefan J; Nilsson, Sven; Kalén, Mattias; Hellström, Mats; Takemoto, Minoru; Håkansson, Joakim; Lindahl, Per

2002-03-01

Microarray hybridization has rapidly evolved as an important tool for genomic studies and studies of gene regulation at the transcriptome level. Expression profiles from homogenous samples such as yeast and mammalian cell cultures are currently extending our understanding of biology, whereas analyses of multicellular organisms are more difficult because of tissue complexity. The combination of laser microdissection, RNA amplification, and microarray hybridization has the potential to provide expression profiles from selected populations of cells in vivo. In this article, we present and evaluate an experimental procedure for global gene expression analysis of slender embryonic structures using laser microbeam microdissection and laser pressure catapulting. As a proof of principle, expression profiles from 1000 cells in the mouse embryonic (E9.5) dorsal aorta were generated and compared with profiles for captured mesenchymal cells located one cell diameter further away from the aortic lumen. A number of genes were overexpressed in the aorta, including 11 previously known markers for blood vessels. Among the blood vessel markers were endoglin, tie-2, PDGFB, and integrin-beta1, that are important regulators of blood vessel formation. This demonstrates that microarray analysis of laser microbeam micro-dissected cells is sufficiently sensitive for identifying genes with regulative functions.

Genome-Wide Expression Profiling of Complex Regional Pain Syndrome

PubMed Central

Jin, Eun-Heui; Zhang, Enji; Ko, Youngkwon; Sim, Woo Seog; Moon, Dong Eon; Yoon, Keon Jung; Hong, Jang Hee; Lee, Won Hyung

2013-01-01

Complex regional pain syndrome (CRPS) is a chronic, progressive, and devastating pain syndrome characterized by spontaneous pain, hyperalgesia, allodynia, altered skin temperature, and motor dysfunction. Although previous gene expression profiling studies have been conducted in animal pain models, there genome-wide expression profiling in the whole blood of CRPS patients has not been reported yet. Here, we successfully identified certain pain-related genes through genome-wide expression profiling in the blood from CRPS patients. We found that 80 genes were differentially expressed between 4 CRPS patients (2 CRPS I and 2 CRPS II) and 5 controls (cut-off value: 1.5-fold change and p<0.05). Most of those genes were associated with signal transduction, developmental processes, cell structure and motility, and immunity and defense. The expression levels of major histocompatibility complex class I A subtype (HLA-A29.1), matrix metalloproteinase 9 (MMP9), alanine aminopeptidase N (ANPEP), l-histidine decarboxylase (HDC), granulocyte colony-stimulating factor 3 receptor (G-CSF3R), and signal transducer and activator of transcription 3 (STAT3) genes selected from the microarray were confirmed in 24 CRPS patients and 18 controls by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). We focused on the MMP9 gene that, by qRT-PCR, showed a statistically significant difference in expression in CRPS patients compared to controls with the highest relative fold change (4.0±1.23 times and p = 1.4×10−4). The up-regulation of MMP9 gene in the blood may be related to the pain progression in CRPS patients. Our findings, which offer a valuable contribution to the understanding of the differential gene expression in CRPS may help in the understanding of the pathophysiology of CRPS pain progression. PMID:24244504

DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data

PubMed Central

Glez-Peña, Daniel; Álvarez, Rodrigo; Díaz, Fernando; Fdez-Riverola, Florentino

2009-01-01

Background Expression profiling assays done by using DNA microarray technology generate enormous data sets that are not amenable to simple analysis. The greatest challenge in maximizing the use of this huge amount of data is to develop algorithms to interpret and interconnect results from different genes under different conditions. In this context, fuzzy logic can provide a systematic and unbiased way to both (i) find biologically significant insights relating to meaningful genes, thereby removing the need for expert knowledge in preliminary steps of microarray data analyses and (ii) reduce the cost and complexity of later applied machine learning techniques being able to achieve interpretable models. Results DFP is a new Bioconductor R package that implements a method for discretizing and selecting differentially expressed genes based on the application of fuzzy logic. DFP takes advantage of fuzzy membership functions to assign linguistic labels to gene expression levels. The technique builds a reduced set of relevant genes (FP, Fuzzy Pattern) able to summarize and represent each underlying class (pathology). A last step constructs a biased set of genes (DFP, Discriminant Fuzzy Pattern) by intersecting existing fuzzy patterns in order to detect discriminative elements. In addition, the software provides new functions and visualisation tools that summarize achieved results and aid in the interpretation of differentially expressed genes from multiple microarray experiments. Conclusion DFP integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It has the advantage that its parameters are highly configurable, facilitating the discovery of biologically relevant connections between sets of genes belonging to different pathologies. This information makes it possible to automatically filter irrelevant genes thereby reducing the large volume of data supplied by microarray experiments. Based on these contributions GENECBR, a successful tool for cancer diagnosis using microarray datasets, has recently been released. PMID:19178723

DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data.

PubMed

Glez-Peña, Daniel; Alvarez, Rodrigo; Díaz, Fernando; Fdez-Riverola, Florentino

2009-01-29

Expression profiling assays done by using DNA microarray technology generate enormous data sets that are not amenable to simple analysis. The greatest challenge in maximizing the use of this huge amount of data is to develop algorithms to interpret and interconnect results from different genes under different conditions. In this context, fuzzy logic can provide a systematic and unbiased way to both (i) find biologically significant insights relating to meaningful genes, thereby removing the need for expert knowledge in preliminary steps of microarray data analyses and (ii) reduce the cost and complexity of later applied machine learning techniques being able to achieve interpretable models. DFP is a new Bioconductor R package that implements a method for discretizing and selecting differentially expressed genes based on the application of fuzzy logic. DFP takes advantage of fuzzy membership functions to assign linguistic labels to gene expression levels. The technique builds a reduced set of relevant genes (FP, Fuzzy Pattern) able to summarize and represent each underlying class (pathology). A last step constructs a biased set of genes (DFP, Discriminant Fuzzy Pattern) by intersecting existing fuzzy patterns in order to detect discriminative elements. In addition, the software provides new functions and visualisation tools that summarize achieved results and aid in the interpretation of differentially expressed genes from multiple microarray experiments. DFP integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It has the advantage that its parameters are highly configurable, facilitating the discovery of biologically relevant connections between sets of genes belonging to different pathologies. This information makes it possible to automatically filter irrelevant genes thereby reducing the large volume of data supplied by microarray experiments. Based on these contributions GENECBR, a successful tool for cancer diagnosis using microarray datasets, has recently been released.

Effects of clofibric acid on mRNA expression profiles in primary cultures of rat, mouse and human hepatocytes.

PubMed

Richert, Lysiane; Lamboley, Christelle; Viollon-Abadie, Catherine; Grass, Peter; Hartmann, Nicole; Laurent, Stephane; Heyd, Bruno; Mantion, Georges; Chibout, Salah-Dine; Staedtler, Frank

2003-09-01

The mRNA expression profile in control and clofibric acid (CLO)-treated mouse, rat, and human hepatocytes was analyzed using species-specific oligonucleotide DNA microarrays (Affymetrix). A statistical empirical Bayes procedure was applied in order to select the significantly differentially expressed genes. Treatment with the peroxisome proliferator CLO induced up-regulation of genes involved in peroxisome proliferation and in cell proliferation as well as down-regulation of genes involved in apoptosis in hepatocytes of rodent but not of human origin. CLO treatment induced up-regulation of microsomal cytochrome P450 4a genes in rodent hepatocytes and in two of six human hepatocyte cultures. In addition, genes encoding phenobarbital-inducible cytochrome P450s were also up-regulated by CLO in rodent and human hepatocyte cultures. Up-regulation of phenobarbital-inducible UDP-glucuronosyl-transferase genes by CLO was observed in both rat and human but not in mouse hepatocytes. CLO treatment induced up-regulation of L-fatty acid binding protein (L-FABP) gene in hepatocytes of both rodent and human origin. However, while genes of the cytosolic, microsomal, and mitochondrial pathways involved in fatty acid transport and metabolism were up-regulated by CLO in both rodent and human hepatocyte cultures, genes of the peroxisomal pathway of lipid metabolism were up-regulated in rodents only. An up-regulation of hepatocyte nuclear factor 1alpha (HNF1alpha) by CLO was observed only in human hepatocyte cultures, suggesting that this trans-activating factor may play a key role in the regulation of fatty acid metabolism in human liver as well as in the nonresponsiveness of human liver to CLO-induced regulation of cell proliferation and apoptosis.

Identification of Differentially Expressed K-Ras Transcript Variants in Patients With Leiomyoma.

PubMed

Zolfaghari, Nooshin; Shahbazi, Shirin; Torfeh, Mahnaz; Khorasani, Maryam; Hashemi, Mehrdad; Mahdian, Reza

2017-10-01

Molecular studies have demonstrated a wide range of gene expression variations in uterine leiomyoma. The rat sarcoma virus/rapidly accelerated fibrosarcoma/mitogen-activated protein kinase (RAS/RAF/MAPK) is the crucial cellular pathway in transmitting external signals into nucleus. Deregulation of this pathway contributes to excessive cell proliferation and tumorigenesis. The present study aims to investigate the expression profile of the K-Ras transcripts in tissue samples from patients with leiomyoma. The patients were leiomyoma cases who had no mutation in mediator complex subunit 12 ( MED12) gene. A quantitative approach has been applied to determine the difference in the expression of the 2 main K-Ras messenger RNA (mRNA) variants. The comparison between gene expression levels in leiomyoma and normal myometrium group was performed using relative expression software tool. The expression of K-Ras4B gene was upregulated in leiomyoma group ( P = .016), suggesting the involvement of K-Ras4B in the disease pathogenesis. Pairwise comparison of the K-Ras4B expression between each leiomyoma tissue and its matched adjacent normal myometrium revealed gene upregulation in 68% of the cases. The expression of K-Ras4A mRNA was relatively upregulated in leiomyoma group ( P = .030). In addition, the mean expression of K-Ras4A gene in leiomyoma tissues relative to normal samples was 4.475 (95% confidence interval: 0.10-20.42; standard error: 0.53-12.67). In total, 58% of the cases showed more than 2-fold increase in K-Ras4A gene expression. Our results demonstrated increased expression of both K-Ras mRNA splicing variants in leiomyoma tissue. However, the ultimate result of KRAS expression on leiomyoma development depends on the overall KRAS isoform balance and, consequently, on activated signaling pathways.

IL-17A Mediates a Selective Gene Expression Profile in Asthmatic Human Airway Smooth Muscle Cells

PubMed Central

Dragon, Stéphane; Hirst, Stuart J.; Lee, Tak H.

2014-01-01

Airway smooth muscle (ASM) cells are thought to contribute to the pathogenesis of allergic asthma by orchestrating and perpetuating airway inflammation and remodeling responses. In this study, we evaluated the IL-17RA signal transduction and gene expression profile in ASM cells from subjects with mild asthma and healthy individuals. Human primary ASM cells were treated with IL-17A and probed by the Affymetrix GeneChip array, and gene targets were validated by real-time quantitative RT-PCR. Genomic analysis underlined the proinflammatory nature of IL-17A, as multiple NF-κB regulatory factors and chemokines were induced in ASM cells. Transcriptional regulators consisting of primary response genes were overrepresented and displayed dynamic expression profiles. IL-17A poorly enhanced IL-1β or IL-22 gene responses in ASM cells from both subjects with mild asthma and healthy donors. Interestingly, protein modifications to the NF-κB regulatory network were not observed after IL-17A stimulation, although oscillations in IκBε expression were detected. ASM cells from subjects with mild asthma up-regulated more genes with greater overall variability in response to IL-17A than from healthy donors. Finally, in response to IL-17A, ASM cells displayed rapid activation of the extracellular signal–regulated kinase/ribosomal S6 kinase signaling pathway and increased nuclear levels of phosphorylated extracellular signal–regulated kinase. Taken together, our results suggest that IL-17A mediated modest gene expression response, which, in cooperation with the NF-κB signaling network, may regulate the gene expression profile in ASM cells. PMID:24393021

Gene expression profiling demonstrates WNT/β-catenin pathway genes alteration in Mexican patients with colorectal cancer and diabetes mellitus.

PubMed

Ivonne Wence-Chavez, Laura; Palomares-Chacon, Ulises; Pablo Flores-Gutierrez, Juan; Felipe Jave-Suarez, Luis; Del Carmen Aguilar-Lemarroy, Adriana; Barros-Nunez, Patricio; Esperanza Flores-Martinez, Silvia; Sanchez-Corona, Jose; Alejandra Rosales-Reynoso, Monica

2017-01-01

Several studies have shown a strong association between diabetes mellitus (DM) and increased risk of colorectal cancer (CRC). The fundamental mechanisms that support this association are not entirely understood; however, it is believed that hyperinsulinemia and hyperglycemia may be involved. Some proposed mechanisms include upregulation of mitogenic signaling pathways like MAPK, PI3K, mTOR, and WNT, which are involved in cell proliferation, growth, and cancer cell survival. The purpose of this study was to evaluate the gene expression profile and identify differently expressed genes involved in mitogenic pathways in CRC patients with and without DM. In this study, microarray analysis of gene expression followed by quantitative PCR (qPCR) was performed in cancer tissue from CRC patients with and without DM to identify the gene expression profiles and validate the differently expressed genes. Among the study groups, some differently expressed genes were identified. However, when bioinformatics clustering tools were used, a significant modulation of genes involved in the WNT pathway was evident. Therefore, we focused on genes participating in this pathway, such as WNT3A, LRP6, TCF7L2, and FRA-1. Validation of the expression levels of those genes by qPCR showed that CRC patients without type 2 diabetes mellitus (T2DM) expressed significantly more WNT3Ay LRP6, but less TCF7L2 and FRA-1 compared to controls, while in CRC patients with DM the expression levels of WNT3A, LRP6, TCF7L2, and FRA-1 were significantly higher compared to controls. Our results suggest that WNT/β-catenin pathway is upregulated in patients with CRC and DM, demonstrating its importance and involvement in both pathologies.

Peripheral blood gene expression signature differentiates children with autism from unaffected siblings

PubMed Central

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

Modulation of intestinal gene expression by dietary zinc status: Effectiveness of cDNA arrays for expression profiling of a single nutrient deficiency

PubMed Central

Blanchard, Raymond K.; Moore, J. Bernadette; Green, Calvert L.; Cousins, Robert J.

2001-01-01

Mammalian nutritional status affects the homeostatic balance of multiple physiological processes and their associated gene expression. Although DNA array analysis can monitor large numbers of genes, there are no reports of expression profiling of a micronutrient deficiency in an intact animal system. In this report, we have tested the feasibility of using cDNA arrays to compare the global changes in expression of genes of known function that occur in the early stages of rodent zinc deficiency. The gene-modulating effects of this deficiency were demonstrated by real-time quantitative PCR measurements of altered mRNA levels for metallothionein 1, zinc transporter 2, and uroguanylin, all of which have been previously documented as zinc-regulated genes. As a result of the low level of inherent noise within this model system and application of a recently reported statistical tool for statistical analysis of microarrays [Tusher, V.G., Tibshirani, R. & Chu, G. (2001) Proc. Natl. Acad. Sci. USA 98, 5116–5121], we demonstrate the ability to reproducibly identify the modest changes in mRNA abundance produced by this single micronutrient deficiency. Among the genes identified by this array profile are intestinal genes that influence signaling pathways, growth, transcription, redox, and energy utilization. Additionally, the influence of dietary zinc supply on the expression of some of these genes was confirmed by real-time quantitative PCR. Overall, these data support the effectiveness of cDNA array expression profiling to investigate the pleiotropic effects of specific nutrients and may provide an approach to establishing markers for assessment of nutritional status. PMID:11717422

ARG1 Functions in the Physiological Adaptation of Undifferentiated Plant Cells to Spaceflight

NASA Astrophysics Data System (ADS)

Zupanska, Agata K.; Schultz, Eric R.; Yao, JiQiang; Sng, Natasha J.; Zhou, Mingqi; Callaham, Jordan B.; Ferl, Robert J.; Paul, Anna-Lisa

2017-11-01

Scientific access to spaceflight and especially the International Space Station has revealed that physiological adaptation to spaceflight is accompanied or enabled by changes in gene expression that significantly alter the transcriptome of cells in spaceflight. A wide range of experiments have shown that plant physiological adaptation to spaceflight involves gene expression changes that alter cell wall and other metabolisms. However, while transcriptome profiling aptly illuminates changes in gene expression that accompany spaceflight adaptation, mutation analysis is required to illuminate key elements required for that adaptation. Here we report how transcriptome profiling was used to gain insight into the spaceflight adaptation role of Altered response to gravity 1 (Arg1), a gene known to affect gravity responses in plants on Earth. The study compared expression profiles of cultured lines of Arabidopsis thaliana derived from wild-type (WT) cultivar Col-0 to profiles from a knock-out line deficient in the gene encoding ARG1 (ARG1 KO), both on the ground and in space. The cell lines were launched on SpaceX CRS-2 as part of the Cellular Expression Logic (CEL) experiment of the BRIC-17 spaceflight mission. The cultured cell lines were grown within 60 mm Petri plates in Petri Dish Fixation Units (PDFUs) that were housed within the Biological Research In Canisters (BRIC) hardware. Spaceflight samples were fixed on orbit. Differentially expressed genes were identified between the two environments (spaceflight and comparable ground controls) and the two genotypes (WT and ARG1 KO). Each genotype engaged unique genes during physiological adaptation to the spaceflight environment, with little overlap. Most of the genes altered in expression in spaceflight in WT cells were found to be Arg1-dependent, suggesting a major role for that gene in the physiological adaptation of undifferentiated cells to spaceflight.

Metatranscriptomic profiles of Eastern subterranean termites, Reticulitermes flavipes (Kollar) fed on second generation feedstocks.

PubMed

Rajarapu, Swapna Priya; Shreve, Jacob T; Bhide, Ketaki P; Thimmapuram, Jyothi; Scharf, Michael E

2015-04-22

Second generation lignocellulosic feedstocks are being considered as an alternative to first generation biofuels that are derived from grain starches and sugars. However, the current pre-treatment methods for second generation biofuel production are inefficient and expensive due to the recalcitrant nature of lignocellulose. In this study, we used the lower termite Reticulitermes flavipes (Kollar), as a model to identify potential pretreatment genes/enzymes specifically adapted for use against agricultural feedstocks. Metatranscriptomic profiling was performed on worker termite guts after feeding on corn stover (CS), soybean residue (SR), or 98% pure cellulose (paper) to identify (i) microbial community, (ii) pathway level and (iii) gene-level responses. Microbial community profiles after CS and SR feeding were different from the paper feeding profile, and protist symbiont abundance decreased significantly in termites feeding on SR and CS relative to paper. Functional profiles after CS feeding were similar to paper and SR; whereas paper and SR showed different profiles. Amino acid and carbohydrate metabolism pathways were downregulated in termites feeding on SR relative to paper and CS. Gene expression analyses showed more significant down regulation of genes after SR feeding relative to paper and CS. Stereotypical lignocellulase genes/enzymes were not differentially expressed, but rather were among the most abundant/constitutively-expressed genes. These results suggest that the effect of CS and SR feeding on termite gut lignocellulase composition is minimal and thus, the most abundantly expressed enzymes appear to encode the best candidate catalysts for use in saccharification of these and related second-generation feedstocks. Further, based on these findings we hypothesize that the most abundantly expressed lignocellulases, rather than those that are differentially expressed have the best potential as pretreatment enzymes for CS and SR feedstocks.

Molecular profiling identifies prognostic markers of stage IA lung adenocarcinoma.

PubMed

Zhang, Jie; Shao, Jinchen; Zhu, Lei; Zhao, Ruiying; Xing, Jie; Wang, Jun; Guo, Xiaohui; Tu, Shichun; Han, Baohui; Yu, Keke

2017-09-26

We previously showed that different pathologic subtypes were associated with different prognostic values in patients with stage IA lung adenocarcinoma (AC). We hypothesize that differential gene expression profiles of different subtypes may be valuable factors for prognosis in stage IA lung adenocarcinoma. We performed microarray gene expression profiling on tumor tissues micro-dissected from patients with acinar and solid predominant subtypes of stage IA lung adenocarcinoma. These patients had undergone a lobectomy and mediastinal lymph node dissection at the Shanghai Chest Hospital, Shanghai, China in 2012. No patient had preoperative treatment. We performed the Gene Set Enrichment Analysis (GSEA) analysis to look for gene expression signatures associated with tumor subtypes. The histologic subtypes of all patients were classified according to the 2015 WHO lung Adenocarcinoma classification. We found that patients with the solid predominant subtype are enriched for genes involved in RNA polymerase activity as well as inactivation of the p53 pathway. Further, we identified a list of genes that may serve as prognostic markers for stage IA lung adenocarcinoma. Validation in the TCGA database shows that these genes are correlated with survival, suggesting that they are novel prognostic factors for stage IA lung adenocarcinoma. In conclusion, we have uncovered novel prognostic factors for stage IA lung adenocarcinoma using gene expression profiling in combination with histopathology subtyping.

Regulation and Gene Expression Profiling of NKG2D Positive Human Cytomegalovirus-Primed CD4+ T-Cells

PubMed Central

Jensen, Helle; Folkersen, Lasse; Skov, Søren

2012-01-01

NKG2D is a stimulatory receptor expressed by natural killer (NK) cells, CD8+ T-cells, and γδ T-cells. NKG2D expression is normally absent from CD4+ T-cells, however recently a subset of NKG2D+ CD4+ T-cells has been found, which is specific for human cytomegalovirus (HCMV). This particular subset of HCMV-specific NKG2D+ CD4+ T-cells possesses effector-like functions, thus resembling the subsets of NKG2D+ CD4+ T-cells found in other chronic inflammations. However, the precise mechanism leading to NKG2D expression on HCMV-specific CD4+ T-cells is currently not known. In this study we used genome-wide analysis of individual genes and gene set enrichment analysis (GSEA) to investigate the gene expression profile of NKG2D+ CD4+ T-cells, generated from HCMV-primed CD4+ T-cells. We show that the HCMV-primed NKG2D+ CD4+ T-cells possess a higher differentiated phenotype than the NKG2D– CD4+ T-cells, both at the gene expression profile and cytokine profile. The ability to express NKG2D at the cell surface was primarily determined by the activation or differentiation status of the CD4+ T-cells and not by the antigen presenting cells. We observed a correlation between CD94 and NKG2D expression in the CD4+ T-cells following HCMV stimulation. However, knock-down of CD94 did not affect NKG2D cell surface expression or signaling. In addition, we show that NKG2D is recycled at the cell surface of activated CD4+ T-cells, whereas it is produced de novo in resting CD4+ T-cells. These findings provide novel information about the gene expression profile of HCMV-primed NKG2D+ CD4+ T-cells, as well as the mechanisms regulating NKG2D cell surface expression. PMID:22870231

Regulation and gene expression profiling of NKG2D positive human cytomegalovirus-primed CD4+ T-cells.

PubMed

Jensen, Helle; Folkersen, Lasse; Skov, Søren

2012-01-01

NKG2D is a stimulatory receptor expressed by natural killer (NK) cells, CD8(+) T-cells, and γδ T-cells. NKG2D expression is normally absent from CD4(+) T-cells, however recently a subset of NKG2D(+) CD4(+) T-cells has been found, which is specific for human cytomegalovirus (HCMV). This particular subset of HCMV-specific NKG2D(+) CD4(+) T-cells possesses effector-like functions, thus resembling the subsets of NKG2D(+) CD4(+) T-cells found in other chronic inflammations. However, the precise mechanism leading to NKG2D expression on HCMV-specific CD4(+) T-cells is currently not known. In this study we used genome-wide analysis of individual genes and gene set enrichment analysis (GSEA) to investigate the gene expression profile of NKG2D(+) CD4(+) T-cells, generated from HCMV-primed CD4(+) T-cells. We show that the HCMV-primed NKG2D(+) CD4(+) T-cells possess a higher differentiated phenotype than the NKG2D(-) CD4(+) T-cells, both at the gene expression profile and cytokine profile. The ability to express NKG2D at the cell surface was primarily determined by the activation or differentiation status of the CD4(+) T-cells and not by the antigen presenting cells. We observed a correlation between CD94 and NKG2D expression in the CD4(+) T-cells following HCMV stimulation. However, knock-down of CD94 did not affect NKG2D cell surface expression or signaling. In addition, we show that NKG2D is recycled at the cell surface of activated CD4(+) T-cells, whereas it is produced de novo in resting CD4(+) T-cells. These findings provide novel information about the gene expression profile of HCMV-primed NKG2D(+) CD4(+) T-cells, as well as the mechanisms regulating NKG2D cell surface expression.

Fidelity and enhanced sensitivity of differential transcription profiles following linear amplification of nanogram amounts of endothelial mRNA

NASA Technical Reports Server (NTRS)

Polacek, Denise C.; Passerini, Anthony G.; Shi, Congzhu; Francesco, Nadeene M.; Manduchi, Elisabetta; Grant, Gregory R.; Powell, Steven; Bischof, Helen; Winkler, Hans; Stoeckert, Christian J Jr;

Impacts of temperature and lunar day on gene expression profiles during a monthly reproductive cycle in the brooding coral Pocillopora damicornis.

PubMed

Crowder, Camerron M; Meyer, Eli; Fan, Tung-Yung; Weis, Virginia M

2017-08-01

Reproductive timing in brooding corals has been correlated to temperature and lunar irradiance, but the mechanisms by which corals transduce these environmental variables into molecular signals are unknown. To gain insight into these processes, global gene expression profiles in the coral Pocillopora damicornis were examined (via RNA-Seq) across lunar phases and between temperature treatments, during a monthly planulation cycle. The interaction of temperature and lunar day together had the largest influence on gene expression. Mean timing of planulation, which occurred at lunar days 7.4 and 12.5 for 28- and 23°C-treated corals, respectively, was associated with an upregulation of transcripts in individual temperature treatments. Expression profiles of planulation-associated genes were compared between temperature treatments, revealing that elevated temperatures disrupted expression profiles associated with planulation. Gene functions inferred from homologous matches to online databases suggest complex neuropeptide signalling, with calcium as a central mediator, acting through tyrosine kinase and G protein-coupled receptor pathways. This work contributes to our understanding of coral reproductive physiology and the impacts of environmental variables on coral reproductive pathways. © 2017 John Wiley & Sons Ltd.

Genome-Level Longitudinal Expression of Signaling Pathways and Gene Networks in Pediatric Septic Shock

PubMed Central

Shanley, Thomas P; Cvijanovich, Natalie; Lin, Richard; Allen, Geoffrey L; Thomas, Neal J; Doctor, Allan; Kalyanaraman, Meena; Tofil, Nancy M; Penfil, Scott; Monaco, Marie; Odoms, Kelli; Barnes, Michael; Sakthivel, Bhuvaneswari; Aronow, Bruce J; Wong, Hector R

2007-01-01

We have conducted longitudinal studies focused on the expression profiles of signaling pathways and gene networks in children with septic shock. Genome-level expression profiles were generated from whole blood-derived RNA of children with septic shock (n = 30) corresponding to day one and day three of septic shock, respectively. Based on sequential statistical and expression filters, day one and day three of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to controls (n = 15). Venn analysis demonstrated 239 unique genes in the day one dataset, 598 unique genes in the day three dataset, and 1,906 genes common to both datasets. Functional analyses demonstrated time-dependent, differential regulation of genes involved in multiple signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biology were persistently downregulated on both day one and day three. Further analyses demonstrated large scale, persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock subjected to longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses. PMID:17932561

A dynamic interplay of nucleosome and Msn2 binding regulates kinetics of gene activation and repression following stress

PubMed Central

Elfving, Nils; Chereji, Răzvan V.; Bharatula, Vasudha; Björklund, Stefan; Morozov, Alexandre V.; Broach, James R.

2014-01-01

The transcription factor Msn2 mediates a significant proportion of the environmental stress response, in which a common cohort of genes changes expression in a stereotypic fashion upon exposure to any of a wide variety of stresses. We have applied genome-wide chromatin immunoprecipitation and nucleosome profiling to determine where Msn2 binds under stressful conditions and how that binding affects, and is affected by, nucleosome positioning. We concurrently determined the effect of Msn2 activity on gene expression following stress and demonstrated that Msn2 stimulates both activation and repression. We found that some genes responded to both intermittent and continuous Msn2 nuclear occupancy while others responded only to continuous occupancy. Finally, these studies document a dynamic interplay between nucleosomes and Msn2 such that nucleosomes can restrict access of Msn2 to its canonical binding sites while Msn2 can promote reposition, expulsion and recruitment of nucleosomes to alter gene expression. This interplay may allow the cell to discriminate between different types of stress signaling. PMID:24598258

Identification of genes showing differential expression profile associated with growth rate in skeletal muscle tissue of Landrace weanling pig.

PubMed

Komatsu, Yuuta; Sukegawa, Shin; Yamashita, Mai; Katsuda, Naoki; Tong, Bin; Ohta, Takeshi; Kose, Hiroyuki; Yamada, Takahisa

2016-06-01

Suppression subtractive hybridization was used to identify genes showing differential expression profile associated with growth rate in skeletal muscle tissue of Landrace weanling pig. Two subtracted cDNA populations were generated from musculus longissimus muscle tissues of selected pigs with extreme expected breeding values at the age of 100 kg. Three upregulated genes (EEF1A2, TSG101 and TTN) and six downregulated genes (ATP5B, ATP5C1, COQ3, HADHA, MYH1 and MYH7) in pig with genetic propensity for higher growth rate were identified by sequence analysis of 12 differentially expressed clones selected by differential screening following the generation of the subtracted cDNA population. Real-time PCR analysis confirmed difference in expression profiles of the identified genes in musculus longissimus muscle tissues between the two Landrace weanling pig groups with divergent genetic propensity for growth rate. Further, differential expression of the identified genes except for the TTN was validated by Western blot analysis. Additionally, the eight genes other than the ATP5C1 colocalized with the same chromosomal positions as QTLs that have been previously identified for growth rate traits. Finally, the changes of expression predicted from gene function suggested association of upregulation of expression of the EEF1A2, TSG101 and TTN genes and downregulation of the ATP5B, ATP5C1, COQ3, HADHA, MYH1 and MYH7 gene expression with increased growth rate. The identified genes will provide an important insight in understanding the molecular mechanism underlying growth rate in Landrace pig breed.

Expression profiling of endometrium from women with endometriosis reveals candidate genes for disease-based implantation failure and infertility.

PubMed

Kao, L C; Germeyer, A; Tulac, S; Lobo, S; Yang, J P; Taylor, R N; Osteen, K; Lessey, B A; Giudice, L C

2003-07-01

Endometriosis is clinically associated with pelvic pain and infertility, with implantation failure strongly suggested as an underlying cause for the observed infertility. Eutopic endometrium of women with endometriosis provides a unique experimental paradigm for investigation into molecular mechanisms of reproductive dysfunction and an opportunity to identify specific markers for this disease. We applied paralleled gene expression profiling using high-density oligonucleotide microarrays to investigate differentially regulated genes in endometrium from women with vs. without endometriosis. Fifteen endometrial biopsy samples (obtained during the window of implantation from eight subjects with and seven subjects without endometriosis) were processed for expression profiling on Affymetrix Hu95A microarrays. Data analysis was conducted with GeneChip Analysis Suite, version 4.01, and GeneSpring version 4.0.4. Nonparametric testing was applied, using a P value of 0.05, to assess statistical significance. Of the 12,686 genes analyzed, 91 genes were significantly increased more than 2-fold in their expression, and 115 genes were decreased more than 2-fold. Unsupervised clustering demonstrated down-regulation of several known cell adhesion molecules, endometrial epithelial secreted proteins, and proteins not previously known to be involved in the pathogenesis of endometriosis, as well as up-regulated genes. Selected dysregulated genes were randomly chosen and validated with RT-PCR and/or Northern/dot-blot analyses, and confirmed up-regulation of collagen alpha2 type I, 2.6-fold; bile salt export pump, 2.0-fold; and down-regulation of N-acetylglucosamine-6-O-sulfotransferase (important in synthesis of L-selectin ligands), 1.7-fold; glycodelin, 51.5-fold; integrin alpha2, 1.8-fold; and B61 (Ephrin A1), 4.5-fold. Two-way overlapping layer analysis used to compare endometrial genes in the window of implantation from women with and without endometriosis further identified three unique groups of target genes, which differ with respect to the implantation window and the presence of disease. Group 1 target genes are up-regulated during the normal window of implantation but significantly decreased in women with endometriosis: IL-15, proline-rich protein, B61, Dickkopf-1, glycodelin, N-acetylglucosamine-6-O-sulfotransferase, G0S2 protein, and purine nucleoside phosphorylase. Group 2 genes are normally down-regulated during the window of implantation but are significantly increased with endometriosis: semaphorin E, neuronal olfactomedin-related endoplasmic reticulum localized protein mRNA and Sam68-like phosphotyrosine protein alpha. Group 3 consists of a single gene, neuronal pentraxin II, normally down-regulated during the window of implantation and further decreased in endometrium from women with endometriosis. The data support dysregulation of select genes leading to an inhospitable environment for implantation, including genes involved in embryonic attachment, embryo toxicity, immune dysfunction, and apoptotic responses, as well as genes likely contributing to the pathogenesis of endometriosis, including aromatase, progesterone receptor, angiogenic factors, and others. Identification and validation of selected genes and their functions will contribute to uncovering previously unknown mechanism(s) underlying implantation failure in women with endometriosis and infertility, mechanisms underlying the pathogenesis of endometriosis and providing potential new targets for diagnostic screening and intervention.

Molecular evolution and expression profile of the chemerine encoding gene RARRES2 in baboon and chimpanzee.

PubMed

González-Alvarez, Rafael; Garza-Rodríguez, María de Lourdes; Delgado-Enciso, Iván; Treviño-Alvarado, Víctor Manuel; Canales-Del-Castillo, Ricardo; Martínez-De-Villarreal, Laura Elia; Lugo-Trampe, Ángel; Tejero, María Elizabeth; Schlabritz-Loutsevitch, Natalia E; Rocha-Pizaña, María Del Refugio; Cole, Shelley A; Reséndez-Pérez, Diana; Moises-Alvarez, Mario; Comuzzie, Anthony G; Barrera-Saldaña, Hugo Alberto; Garza-Guajardo, Raquel; Barboza-Quintana, Oralia; Rodríguez-Sánchez, Irám Pablo

2015-06-12

Chemerin, encoded by the retinoic acid receptor responder 2 (RARRES2) gene is an adipocytesecreted protein with autocrine/paracrine functions in adipose tissue, metabolism and inflammation with a recently described function in vascular tone regulation, liver, steatosis, etc. This molecule is believed to represent a critical endocrine signal linking obesity to diabetes. There are no data available regarding evolution of RARRES2 in non-human primates and great apes. Expression profile and orthology in RARRES2 genes are unknown aspects in the biology of this multigene family in primates. Thus; we attempt to describe expression profile and phylogenetic relationship as complementary knowledge in the function of this gene in primates. To do that, we performed A RT-PCR from different tissues obtained during necropsies. Also we tested the hypotheses of positive evolution, purifying selection, and neutrality. And finally a phylogenetic analysis was made between primates RARRES2 protein. RARRES2 transcripts were present in liver, lung, adipose tissue, ovary, pancreas, heart, hypothalamus and pituitary tissues. Expression in kidney and leukocytes were not detectable in either species. It was determined that the studied genes are orthologous. RARRES2 evolution fits the hypothesis of purifying selection. Expression profiles of the RARRES2 gene are similar in baboons and chimpanzees and are also phylogenetically related.

Identification of specific gene expression profiles in fibroblasts derived from middle ear cholesteatoma.

PubMed

Yoshikawa, Mamoru; Kojima, Hiromi; Wada, Kota; Tsukidate, Toshiharu; Okada, Naoko; Saito, Hirohisa; Moriyama, Hiroshi

2006-07-01

To investigate the role of fibroblasts in the pathogenesis of cholesteatoma. Tissue specimens were obtained from our patients. Middle ear cholesteatoma-derived fibroblasts (MECFs) and postauricular skin-derived fibroblasts (SFs) as controls were then cultured for a few weeks. These fibroblasts were stimulated with interleukin (IL) 1alpha and/or IL-1beta before gene expression assays. We used the human genome U133A probe array (GeneChip) and real-time polymerase chain reaction to examine and compare the gene expression profiles of the MECFs and SFs. Six patients who had undergone tympanoplasty. The IL-1alpha-regulated genes were classified into 4 distinct clusters on the basis of profiles differentially regulated by SF and MECF using a hierarchical clustering analysis. The messenger RNA expressions of LARC (liver and activation-regulated chemokine), GMCSF (granulocyte-macrophage colony-stimulating factor), epiregulin, ICAM1 (intercellular adhesion molecule 1), and TGFA (transforming growth factor alpha) were more strongly up-regulated by IL-1alpha and/or IL-1beta in MECF than in SF, suggesting that these fibroblasts derived from different tissues retained their typical gene expression profiles. Fibroblasts may play a role in hyperkeratosis of middle ear cholesteatoma by releasing molecules involved in inflammation and epidermal growth. These fibroblasts may retain tissue-specific characteristics presumably controlled by epigenetic mechanisms.

Embryonic stem cell-like features of testicular carcinoma in situ revealed by genome-wide gene expression profiling.

PubMed

Almstrup, Kristian; Hoei-Hansen, Christina E; Wirkner, Ute; Blake, Jonathon; Schwager, Christian; Ansorge, Wilhelm; Nielsen, John E; Skakkebaek, Niels E; Rajpert-De Meyts, Ewa; Leffers, Henrik

2004-07-15

Carcinoma in situ (CIS) is the common precursor of histologically heterogeneous testicular germ cell tumors (TGCTs), which in recent decades have markedly increased and now are the most common malignancy of young men. Using genome-wide gene expression profiling, we identified >200 genes highly expressed in testicular CIS, including many never reported in testicular neoplasms. Expression was further verified by semiquantitative reverse transcription-PCR and in situ hybridization. Among the highest expressed genes were NANOG and POU5F1, and reverse transcription-PCR revealed possible changes in their stoichiometry on progression into embryonic carcinoma. We compared the CIS expression profile with patterns reported in embryonic stem cells (ESCs), which revealed a substantial overlap that may be as high as 50%. We also demonstrated an over-representation of expressed genes in regions of 17q and 12, reported as unstable in cultured ESCs. The close similarity between CIS and ESCs explains the pluripotency of CIS. Moreover, the findings are consistent with an early prenatal origin of TGCTs and thus suggest that etiologic factors operating in utero are of primary importance for the incidence trends of TGCTs. Finally, some of the highly expressed genes identified in this study are promising candidates for new diagnostic markers for CIS and/or TGCTs.

Infrequent and low expression of cancer-testis antigens located on the X chromosome in colorectal cancer: implications for immunotherapy in South African populations.

PubMed

Dakshinamurthy, Amirtha Ganesh; Ramesar, Rajkumar; Goldberg, Paul; Blackburn, Jonathan M

2008-11-01

Cancer-testis (CT) antigens are a group of tumor antigens that are expressed in the testis and aberrantly in cancerous tissue but not in somatic tissues. The testis is an immune-privileged site because of the presence of a blood-testis barrier; as a result, CT antigens are considered to be essentially tumor specific and are attractive targets for immunotherapy. CT antigens are classified as the CT-X and the non-X CT antigens depending on the chromosomal location to which the genes are mapped. CT-X antigens are typically highly immunogenic and hence the first step towards tailored immunotherapy is to elucidate the expression profile of CT-X antigens in the respective tumors. In this study we investigated the expression profile of 16 CT-X antigen genes in 34 colorectal cancer (CRC) patients using reverse transcription-polymerase chain reaction. We observed that 12 of the 16 CT-X antigen genes studied did not show expression in any of the CRC samples analyzed. The other 4 CT-X antigen genes showed low frequency of expression and exhibited a highly variable expression profile when compared to other populations. Thus, our study forms the first report on the expression profile of CT-X antigen genes among CRC patients in the genetically diverse South African population. The results of our study suggest that genetic and ethnic variations in population might have a role in the expression of the CT-X antigen genes. Thus our results have significant implications for anti-CT antigen-based immunotherapy trials in this population.

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

A Prognostic Gene Expression Profile That Predicts Circulating Tumor Cell Presence in Breast Cancer Patients

PubMed Central

Molloy, Timothy J.; Roepman, Paul; Naume, Bjørn; van't Veer, Laura J.

2012-01-01

The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into “good prognosis” or “poor prognosis” are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the “CTC profile” also provided prognostic information independent of the well-established and powerful ‘70-gene’ prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays. PMID:22384245

A Gata2-Dependent Transcription Network Regulates Uterine Progesterone Responsiveness and Endometrial Function.

PubMed

Rubel, Cory A; Wu, San-Pin; Lin, Lin; Wang, Tianyuan; Lanz, Rainer B; Li, Xilong; Kommagani, Ramakrishna; Franco, Heather L; Camper, Sally A; Tong, Qiang; Jeong, Jae-Wook; Lydon, John P; DeMayo, Francesco J

2016-10-25

Altered progesterone responsiveness leads to female infertility and cancer, but underlying mechanisms remain unclear. Mice with uterine-specific ablation of GATA binding protein 2 (Gata2) are infertile, showing failures in embryo implantation, endometrial decidualization, and uninhibited estrogen signaling. Gata2 deficiency results in reduced progesterone receptor (PGR) expression and attenuated progesterone signaling, as evidenced by genome-wide expression profiling and chromatin immunoprecipitation. GATA2 not only occupies at and promotes expression of the Pgr gene but also regulates downstream progesterone responsive genes in conjunction with the PGR. Additionally, Gata2 knockout uteri exhibit abnormal luminal epithelia with ectopic TRP63 expressing squamous cells and a cancer-related molecular profile in a progesterone-independent manner. Lastly, we found a conserved GATA2-PGR regulatory network in both human and mice based on gene signature and path analyses using gene expression profiles of human endometrial tissues. In conclusion, uterine Gata2 regulates a key regulatory network of gene expression for progesterone signaling at the early pregnancy stage. Published by Elsevier Inc.

High interleukin-15 expression characterizes childhood acute lymphoblastic leukemia with involvement of the CNS.

PubMed

Cario, Gunnar; Izraeli, Shai; Teichert, Anja; Rhein, Peter; Skokowa, Julia; Möricke, Anja; Zimmermann, Martin; Schrauder, Andre; Karawajew, Leonid; Ludwig, Wolf-Dieter; Welte, Karl; Schünemann, Holger J; Schlegelberger, Brigitte; Schrappe, Martin; Stanulla, Martin

2007-10-20

Applying current diagnostic methods, overt CNS involvement is a rare event in childhood acute lymphoblastic leukemia (ALL). In contrast, CNS-directed therapy is essential for all patients with ALL because without it, the majority of patients eventually will experience relapse. To approach this discrepancy and to explore potential distinct biologic properties of leukemic cells that migrate into the CNS, we compared gene expression profiles of childhood ALL patients with initial CNS involvement with the profiles of CNS-negative patients. We evaluated leukemic gene expression profiles from the bone marrow of 17 CNS-positive patients and 26 CNS-negative patients who were frequency matched for risk factors associated with CNS involvement. Results were confirmed by real-time quantitative polymerase chain reaction analysis and validated using independent patient samples. Interleukin-15 (IL-15) expression was consistently upregulated in leukemic cells of CNS-positive patients compared with CNS-negative patients. In multivariate analysis, IL-15 expression levels greater than the median were associated with CNS involvement compared with expression equal to or less than the median (odds ratio [OR] = 10.70; 95% CI, 2.95 to 38.81). Diagnostic likelihood ratios for CNS positivity were 0.09 (95% CI, 0.01 to 0.65) for the first and 6.93 (95% CI, 2.55 to 18.83) for the fourth IL-15 expression quartiles. In patients who were CNS negative at diagnosis, IL-15 levels greater than the median were associated with subsequent CNS relapse compared with expression equal to or less than the median (OR = 13.80; 95% CI, 3.38 to 56.31). Quantification of leukemic IL-15 expression at diagnosis predicts CNS status and could be a new tool to further tailor CNS-directed therapy in childhood ALL.

Culture conditions tailored to the cell of origin are critical for maintaining native properties and tumorigenicity of glioma cells

PubMed Central

Ledur, Pítia F.; He, Hua; Harris, Alexandra R.; Minussi, Darlan C.; Zhou, Hai-Yan; Shaffrey, Mark E.; Asthagiri, Ashok; Lopes, Maria Beatriz S.; Schiff, David; Lu, Yi-Cheng; Mandell, James W.; Lenz, Guido; Zong, Hui

2016-01-01

Background Cell culture plays a pivotal role in cancer research. However, culture-induced changes in biological properties of tumor cells profoundly affect research reproducibility and translational potential. Establishing culture conditions tailored to the cancer cell of origin could resolve this problem. For glioma research, it has been previously shown that replacing serum with defined growth factors for neural stem cells (NSCs) greatly improved the retention of gene expression profile and tumorigenicity. However, among all molecular subtypes of glioma, our laboratory and others have previously shown that the oligodendrocyte precursor cell (OPC) rather than the NSC serves as the cell of origin for the proneural subtype, raising questions regarding the suitability of NSC-tailored media for culturing proneural glioma cells. Methods OPC-originated mouse glioma cells were cultured in conditions for normal OPCs or NSCs, respectively, for multiple passages. Gene expression profiles, morphologies, tumorigenicity, and drug responsiveness of cultured cells were examined in comparison with freshly isolated tumor cells. Results OPC media-cultured glioma cells maintained tumorigenicity, gene expression profiles, and morphologies similar to freshly isolated tumor cells. In contrast, NSC-media cultured glioma cells gradually lost their OPC features and most tumor-initiating ability and acquired heightened sensitivity to temozolomide. Conclusions To improve experimental reproducibility and translational potential of glioma research, it is important to identify the cell of origin, and subsequently apply this knowledge to establish culture conditions that allow the retention of native properties of tumor cells. PMID:27106408

Come one, come all.

PubMed

Lee, Siu Sylvia

2004-05-05

Aging is a complex process that involves the gradual functional decline of many different tissues and cells. Gene expression microarray analysis provides a comprehensive view of the gene expression signature associated with age and is particularly valuable for understanding the molecular mechanisms that contribute to the aging process. However, because of the stochastic nature of the aging process, animals of the same chronological age often manifest great physiological differences. Therefore, profiling the gene expression pattern of a large population of aging animals risks either exaggerating or masking the changes in gene expression that correspond to physiological aging. In a recent paper, Golden and Melov surveyed the gene expression profiles of individual aging Caenorhabditis elegans, hoping to circumvent the problem of variability among worms of the same chronological age. This initial analysis of age-dependent gene expression in individual aging worms is an important step toward deciphering the molecular basis of physiological aging.

Partitioning of functional gene expression data using principal points.

PubMed

Kim, Jaehee; Kim, Haseong

2017-10-12

DNA microarrays offer motivation and hope for the simultaneous study of variations in multiple genes. Gene expression is a temporal process that allows variations in expression levels with a characterized gene function over a period of time. Temporal gene expression curves can be treated as functional data since they are considered as independent realizations of a stochastic process. This process requires appropriate models to identify patterns of gene functions. The partitioning of the functional data can find homogeneous subgroups of entities for the massive genes within the inherent biological networks. Therefor it can be a useful technique for the analysis of time-course gene expression data. We propose a new self-consistent partitioning method of functional coefficients for individual expression profiles based on the orthonormal basis system. A principal points based functional partitioning method is proposed for time-course gene expression data. The method explores the relationship between genes using Legendre coefficients as principal points to extract the features of gene functions. Our proposed method provides high connectivity in connectedness after clustering for simulated data and finds a significant subsets of genes with the increased connectivity. Our approach has comparative advantages that fewer coefficients are used from the functional data and self-consistency of principal points for partitioning. As real data applications, we are able to find partitioned genes through the gene expressions found in budding yeast data and Escherichia coli data. The proposed method benefitted from the use of principal points, dimension reduction, and choice of orthogonal basis system as well as provides appropriately connected genes in the resulting subsets. We illustrate our method by applying with each set of cell-cycle-regulated time-course yeast genes and E. coli genes. The proposed method is able to identify highly connected genes and to explore the complex dynamics of biological systems in functional genomics.

Validation of Biomarkers Predictive of Recurrence Following Prostatectomy

DTIC Science & Technology

2011-04-14

Bergerheim U, Ekman P, DeMarzo AM, Tibshirani R, Botstein D, Brown PO, Brooks JD, Pollack JR: Gene expression profiling identifies clinically...P, DeMarzo AM, Tibshirani R, Botstein D, Brown PO, Brooks JD, Pollack JR: Gene expression profiling identifies clinically relevant subtypes of

Diversity in the carotenoid profiles and the expression of genes related to carotenoid accumulation among citrus genotypes

PubMed Central

Ikoma, Yoshinori; Matsumoto, Hikaru; Kato, Masaya

2016-01-01

Carotenoids are not only important to the plants themselves but also are beneficial to human health. Since citrus fruit is a good source of carotenoids for the human diet, it is important to study carotenoid profiles and the accumulation mechanism in citrus fruit. Thus, in the present paper, we describe the diversity in the carotenoid profiles of fruit among citrus genotypes. In regard to carotenoids, such as β-cryptoxanthin, violaxanthin, lycopene, and β-citraurin, the relationship between the carotenoid profile and the expression of carotenoid-biosynthetic genes is discussed. Finally, recent results of quantitative trait locus (QTL) analyses of carotenoid contents and expression levels of carotenoid-biosynthetic genes in citrus fruit are shown. PMID:27069398

Effect of leaf incubation temperature profiles on Agrobacterium tumefaciens-mediated transient expression.

PubMed

Jung, Sang-Kyu; McDonald, Karen A; Dandekar, Abhaya M

2015-01-01

Agrobacterium tumefaciens-mediated transient expression is known to be highly dependent on incubation temperature. Compared with early studies that were conducted at constant temperature, we examined the effect of variable leaf incubation temperature on transient expression. As a model system, synthetic endoglucanase (E1) and endoxylanase (Xyn10A) genes were transiently expressed in detached whole sunflower leaves via vacuum infiltration for biofuel applications. We found that the kinetics of transient expression strongly depended on timing of the temperature change as well as leaf incubation temperature. Surprisingly, we found that high incubation temperature (27-30 °C) which is suboptimal for T-DNA transfer, significantly enhanced transient expression if the high temperature was applied during the late phase (Day 3-6) of leaf incubation whereas incubation temperature in a range of 20-25 °C for an early phase (Day 0-2) resulted in higher production. On the basis of these results, we propose that transient expression is governed by both T-DNA transfer and protein synthesis in plant cells that have different temperature dependent kinetics. Because the phases were separated in time and had different optimal temperatures, we were then able to develop a novel two phase optimization strategy for leaf incubation temperature. Applying the time-varying temperature profile, we were able to increase the protein accumulation by fivefold compared with the control at a constant temperature of 20 °C. From our knowledge, this is the first report illustrating the effect of variable temperature profiling for improved transient expression. © 2015 American Institute of Chemical Engineers.

Identification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis.

PubMed

Vukmirovic, Milica; Herazo-Maya, Jose D; Blackmon, John; Skodric-Trifunovic, Vesna; Jovanovic, Dragana; Pavlovic, Sonja; Stojsic, Jelena; Zeljkovic, Vesna; Yan, Xiting; Homer, Robert; Stefanovic, Branko; Kaminski, Naftali

2017-01-12

Idiopathic Pulmonary Fibrosis (IPF) is a lethal lung disease of unknown etiology. A major limitation in transcriptomic profiling of lung tissue in IPF has been a dependence on snap-frozen fresh tissues (FF). In this project we sought to determine whether genome scale transcript profiling using RNA Sequencing (RNA-Seq) could be applied to archived Formalin-Fixed Paraffin-Embedded (FFPE) IPF tissues. We isolated total RNA from 7 IPF and 5 control FFPE lung tissues and performed 50 base pair paired-end sequencing on Illumina 2000 HiSeq. TopHat2 was used to map sequencing reads to the human genome. On average ~62 million reads (53.4% of ~116 million reads) were mapped per sample. 4,131 genes were differentially expressed between IPF and controls (1,920 increased and 2,211 decreased (FDR < 0.05). We compared our results to differentially expressed genes calculated from a previously published dataset generated from FF tissues analyzed on Agilent microarrays (GSE47460). The overlap of differentially expressed genes was very high (760 increased and 1,413 decreased, FDR < 0.05). Only 92 differentially expressed genes changed in opposite directions. Pathway enrichment analysis performed using MetaCore confirmed numerous IPF relevant genes and pathways including extracellular remodeling, TGF-beta, and WNT. Gene network analysis of MMP7, a highly differentially expressed gene in both datasets, revealed the same canonical pathways and gene network candidates in RNA-Seq and microarray data. For validation by NanoString nCounter® we selected 35 genes that had a fold change of 2 in at least one dataset (10 discordant, 10 significantly differentially expressed in one dataset only and 15 concordant genes). High concordance of fold change and FDR was observed for each type of the samples (FF vs FFPE) with both microarrays (r = 0.92) and RNA-Seq (r = 0.90) and the number of discordant genes was reduced to four. Our results demonstrate that RNA sequencing of RNA obtained from archived FFPE lung tissues is feasible. The results obtained from FFPE tissue are highly comparable to FF tissues. The ability to perform RNA-Seq on archived FFPE IPF tissues should greatly enhance the availability of tissue biopsies for research in IPF.

PanGEA: identification of allele specific gene expression using the 454 technology.

PubMed

Kofler, Robert; Teixeira Torres, Tatiana; Lelley, Tamas; Schlötterer, Christian

2009-05-14

Next generation sequencing technologies hold great potential for many biological questions. While mainly used for genomic sequencing, they are also very promising for gene expression profiling. Sequencing of cDNA does not only provide an estimate of the absolute expression level, it can also be used for the identification of allele specific gene expression. We developed PanGEA, a tool which enables a fast and user-friendly analysis of allele specific gene expression using the 454 technology. PanGEA allows mapping of 454-ESTs to genes or whole genomes, displaying gene expression profiles, identification of SNPs and the quantification of allele specific gene expression. The intuitive GUI of PanGEA facilitates a flexible and interactive analysis of the data. PanGEA additionally implements a modification of the Smith-Waterman algorithm which deals with incorrect estimates of homopolymer length as occuring in the 454 technology To our knowledge, PanGEA is the first tool which facilitates the identification of allele specific gene expression. PanGEA is distributed under the Mozilla Public License and available at: http://www.kofler.or.at/bioinformatics/PanGEA

PanGEA: Identification of allele specific gene expression using the 454 technology

PubMed Central

Kofler, Robert; Teixeira Torres, Tatiana; Lelley, Tamas; Schlötterer, Christian

2009-01-01

Background Next generation sequencing technologies hold great potential for many biological questions. While mainly used for genomic sequencing, they are also very promising for gene expression profiling. Sequencing of cDNA does not only provide an estimate of the absolute expression level, it can also be used for the identification of allele specific gene expression. Results We developed PanGEA, a tool which enables a fast and user-friendly analysis of allele specific gene expression using the 454 technology. PanGEA allows mapping of 454-ESTs to genes or whole genomes, displaying gene expression profiles, identification of SNPs and the quantification of allele specific gene expression. The intuitive GUI of PanGEA facilitates a flexible and interactive analysis of the data. PanGEA additionally implements a modification of the Smith-Waterman algorithm which deals with incorrect estimates of homopolymer length as occuring in the 454 technology Conclusion To our knowledge, PanGEA is the first tool which facilitates the identification of allele specific gene expression. PanGEA is distributed under the Mozilla Public License and available at: PMID:19442283

Large-scale gene expression profiling data for the model moss Physcomitrella patens aid understanding of developmental progression, culture and stress conditions.

PubMed

Hiss, Manuel; Laule, Oliver; Meskauskiene, Rasa M; Arif, Muhammad A; Decker, Eva L; Erxleben, Anika; Frank, Wolfgang; Hanke, Sebastian T; Lang, Daniel; Martin, Anja; Neu, Christina; Reski, Ralf; Richardt, Sandra; Schallenberg-Rüdinger, Mareike; Szövényi, Peter; Tiko, Theodhor; Wiedemann, Gertrud; Wolf, Luise; Zimmermann, Philip; Rensing, Stefan A

2014-08-01

The moss Physcomitrella patens is an important model organism for studying plant evolution, development, physiology and biotechnology. Here we have generated microarray gene expression data covering the principal developmental stages, culture forms and some environmental/stress conditions. Example analyses of developmental stages and growth conditions as well as abiotic stress treatments demonstrate that (i) growth stage is dominant over culture conditions, (ii) liquid culture is not stressful for the plant, (iii) low pH might aid protoplastation by reduced expression of cell wall structure genes, (iv) largely the same gene pool mediates response to dehydration and rehydration, and (v) AP2/EREBP transcription factors play important roles in stress response reactions. With regard to the AP2 gene family, phylogenetic analysis and comparison with Arabidopsis thaliana shows commonalities as well as uniquely expressed family members under drought, light perturbations and protoplastation. Gene expression profiles for P. patens are available for the scientific community via the easy-to-use tool at https://www.genevestigator.com. By providing large-scale expression profiles, the usability of this model organism is further enhanced, for example by enabling selection of control genes for quantitative real-time PCR. Now, gene expression levels across a broad range of conditions can be accessed online for P. patens. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

EvoCor: a platform for predicting functionally related genes using phylogenetic and expression profiles.

PubMed

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.

Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

PubMed Central

Li, Xia; Rao, Shaoqi; Jiang, Wei; Li, Chuanxing; Xiao, Yun; Guo, Zheng; Zhang, Qingpu; Wang, Lihong; Du, Lei; Li, Jing; Li, Li; Zhang, Tianwen; Wang, Qing K

2006-01-01

Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network) to address the underlying regulations of genes that can span any unit(s) of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex gene regulations related to the development, aging and progressive pathogenesis of a complex disease where potential dependences between different experiment units might occurs. PMID:16420705

Analysis of differential gene expression by bead-based fiber-optic array in nonfunctioning pituitary adenomas.

PubMed

Jiang, Z; Gui, S; Zhang, Y

2011-05-01

Nonfunctioning pituitary adenomas (NFPAs) are relatively common, accounting for 30% of all pituitary adenomas; however, their pathogenesis remains enigmatic. To explore the possible pathogenesis of NFPAs, we used fiber-optic BeadArray to examine gene expression in 5 NFPAs compared with 3 normal pituitaries. 4 differentially expressed genes were chosen randomly for validation by reverse transcriptase-real time quantitative polymerase chain reaction (RT-qPCR). We then analyzed the differentially expressed gene profile with Kyoto Encyclopedia of Genes and Genomes (KEGG). The array analysis indentified significant increases in the expression of 1,402 genes and 383 expressed sequence tags (ESTs), and decreases in 1,697 genes and 113 ESTs in the NFPAs. Bioinformatic and pathway analysis showed that the genes HIGD1B, FAM5C, PMAIP1 and the pathway cell-cycle regulation may play an important role in tumorigenesis and progression of NFPAs. Our data suggest fiber-optic BeadArray combined with pathway analysis of differential gene expression profile appears to be a valid approach for investigating the pathogenesis of tumors. © Georg Thieme Verlag KG Stuttgart · New York.

Gene Expression Profiling of Multiple Leiomyomata Uteri and Matched Normal Tissue from a Single Patient

PubMed Central

Dimitrova, Irina K.; Richer, Jennifer K.; Rudolph, Michael C.; Spoelstra, Nicole S.; Reno, Elaine M.; Medina, Theresa M.; Bradford, Andrew P.

2009-01-01

Objective To identify differentially expressed genes between fibroid and adjacent normal myometrium in an identical hormonal and genetic background. Design Array analysis of 3 leiomyomata and matched adjacent normal myometrium in a single patient. Setting University of Colorado Hospital. Patient(s) A single female undergoing medically indicated hysterectomy for symptomatic fibroids. Interventions(s) mRNA isolation and microarray analysis, reverse-transcriptase polymerase chain reaction, western blotting and immunohistochemistry. Main Outcome Measure(s) Changes in mRNA and protein levels in leiomyomata and matched normal myometrium. Result(s) Expression of 197 genes was increased and 619 decreased, significantly by at least 2 fold, in leiomyomata relative to normal myometrium. Expression profiles between tumors were similar and normal myometrial samples showed minimal variation. Changes in, and variation of, expression of selected genes were confirmed in additional normal and leiomyoma samples from multiple patients. Conclusion(s) Analysis of multiple tumors from a single patient confirmed changes in expression of genes described in previous, apparently disparate, studies and identified novel targets. Gene expression profiles in leiomyomata are consistent with increased activation of mitogenic pathways and inhibition of apoptosis. Down-regulation of genes implicated in invasion and metastasis, of cancers, was observed in fibroids. This expression pattern may underlie the benign nature of uterine leiomyomata and may aid in the differential diagnosis of leiomyosarcoma. PMID:18672237

Cellular expansion and gene expression in the developing grape (Vitis vinifera L.).

PubMed

Schlosser, J; Olsson, N; Weis, M; Reid, K; Peng, F; Lund, S; Bowen, P

2008-01-01

Expression profiles of genes involved in cell wall metabolism and water transport were compared with changes in grape (Vitis vinifera L.) berry growth, basic chemical composition, and the shape, size, and wall thickness of cells within tissues of the berry pericarp. Expression of cell wall-modifying and aquaporin genes in berry pericarp tissues generally followed a bimodal expression profile with high levels of expression coinciding with the two periods of rapid berry growth, stages I and III, and low levels of expression corresponding to the slow-growth period, stage II. Cellular expansion was observed throughout all tissues during stage I, and only mesocarp cellular expansion was observed during stage III. Expansion of only exocarp cells was evident during transition between stages II and III. Cell wall-modifying and aquaporin gene expression profiles followed similar trends in exocarp and mesocarp tissues throughout berry development, with the exception of the up-regulation of pectin methylesterase, pectate lyase, two aquaporin genes (AQ1 and AQ2), and two expansin genes (EXP3 and EXPL) during stage II, which was delayed in the exocarp tissue compared with mesocarp tissue. Exocarp endo-(1-->3)-beta-glucanase and expansin-like gene expression was concurrent with increases in epidermal and hypodermal cell wall thickness. These results indicate a potential role of the grape berry skin in modulating grape berry growth.

Classification of early-stage non-small cell lung cancer by weighing gene expression profiles with connectivity information.

PubMed

Zhang, Ao; Tian, Suyan

2018-05-01

Pathway-based feature selection algorithms, which utilize biological information contained in pathways to guide which features/genes should be selected, have evolved quickly and become widespread in the field of bioinformatics. Based on how the pathway information is incorporated, we classify pathway-based feature selection algorithms into three major categories-penalty, stepwise forward, and weighting. Compared to the first two categories, the weighting methods have been underutilized even though they are usually the simplest ones. In this article, we constructed three different genes' connectivity information-based weights for each gene and then conducted feature selection upon the resulting weighted gene expression profiles. Using both simulations and a real-world application, we have demonstrated that when the data-driven connectivity information constructed from the data of specific disease under study is considered, the resulting weighted gene expression profiles slightly outperform the original expression profiles. In summary, a big challenge faced by the weighting method is how to estimate pathway knowledge-based weights more accurately and precisely. Only until the issue is conquered successfully will wide utilization of the weighting methods be impossible. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Lipidomic fatty acid profile and global gene expression pattern in mammary gland of rats that were exposed to lard-based high fat diet during fetal and lactation periods associated to breast cancer risk in adulthood.

PubMed

Andrade, Fábia de Oliveira; de Assis, Sonia; Jin, Lu; Fontelles, Camile Castilho; Barbisan, Luís Fernando; Purgatto, Eduardo; Hilakivi-Clarke, Leena; Ong, Thomas Prates

2015-09-05

The persistent effects of animal fat consumption during pregnancy and nursing on the programming of breast cancer risk among female offspring were studied here. We have previously found that female offspring of rat dams that consumed a lard-based high-fat (HF) diet (60% fat-derived energy) during pregnancy, or during pregnancy and lactation, were at a reduced risk of developing mammary cancer. To better understand the unexpected protective effects of early life lard exposure, we have applied lipidomics and nutrigenomics approaches to investigate the fatty acid profile and global gene expression patterns in the mammary tissue of the female offspring. Consumption of this HF diet during gestation had few effects on the mammary tissue fatty acids profile of young adult offspring, while exposure from gestation throughout nursing promoted significant alterations in the fatty acids profile. Major differences were related to decreases in saturated fatty acids (SFA) and increases in omega-6 polyunsaturated fatty acids (PUFAs), monounsaturated fatty acids (MUFAs) and conjugated linolenic acid (CLA) concentrations. In addition several differences in gene expression patterns by microarray analysis between the control and in utero or in utero and during lactation HF exposed offspring were identified. Differential dependency network (DDN) analysis indicated that many of the genes exhibited unique connections to other genes only in the HF offspring. These unique connections included Hrh1-Ythdf1 and Repin1-Elavl2 in the in utero HF offspring, and Rnf213-Htr3b and Klf5-Chrna4 in the in utero and lactation HF offspring, compared with the control offspring. We conclude that an exposure to a lard-based HF diet during early life changes the fatty acid profile and transcriptional network in mammary gland in young adult rats, and these changes appear to be consistent with reduced mammary cancer risk observed in our previous study. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Dose–response relationships in gene expression profiles in rainbow trout, Oncorhyncus mykiss, exposed to ethynylestradiol

PubMed Central

Hook, Sharon E.; Skillman, Ann D.; Small, Jack A.; Schultz, Irvin R.

2008-01-01

Determining how gene expression profiles change with toxicant dose will improve the utility of arrays in identifying biomarkers and modes of toxic action. Isogenic rainbow trout, Oncorhyncus mykiss, were exposed to 10, 50 or 100 ng/L ethynylestradiol (a xeno-estrogen) for 7 days. Following exposure hepatic RNA was extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Atlantic Salmon/Trout array (GRASP project, University of Victoria) spotted with 16,000 cDNAs. Transcript expression in treated vs control fish was analyzed via Genespring (Silicon Genetics) to identify genes with altered expression, as well as to determine gene clustering patterns that can be used as “expression signatures”. Array results were confirmed via qRT PCR. Our analysis indicates that gene expression profiles varied somewhat with dose. Established biomarkers of exposure to estrogenic chemicals, such as vitellogenin, vitelline envelope proteins, and the estrogen receptor alpha, were induced at every dose. Other genes were dose specific, suggesting that diffierent doses induce distinct physiological responses. These findings demonstrate that cDNA microarrays could be used to identify both toxicant class and relative dose. PMID:16725192

Cell-specific prediction and application of drug-induced gene expression profiles.

PubMed

Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David; Dudley, Joel

2018-01-01

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes.

Cell-specific prediction and application of drug-induced gene expression profiles

PubMed Central

Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R.; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David

2017-01-01

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes. PMID:29218867

Gene expression profiling of the hippocampal dentate gyrus in an adult toxicity study captures a variety of neurodevelopmental dysfunctions in rat models of hypothyroidism.

PubMed

Shiraki, Ayako; Saito, Fumiyo; Akane, Hirotoshi; Akahori, Yumi; Imatanaka, Nobuya; Itahashi, Megu; Yoshida, Toshinori; Shibutani, Makoto

2016-01-01

We previously found that developmental hypothyroidism changed the expression of genes in the rat hippocampal dentate gyrus, a brain region where adult neurogenesis is known to occur. In the present study, we performed brain region-specific global gene expression profiling in an adult rat hypothyroidism model to see if it reflected the developmental neurotoxicity we saw in the developmental hypothyroidism model. Starting when male rats were 5 weeks old, we administered 6-propyl-2-thiouracil at a doses of 0, 0.1 and 10 mg kg(-1) body weight by gavage for 28 days. We selected four brain regions to represent both cerebral and cerebellar tissues: hippocampal dentate gyrus, cerebral cortex, corpus callosum and cerebellar vermis. We observed significant alterations in the expression of genes related to neural development (Eph family genes and Robo3) in the cerebral cortex and hippocampal dentate gyrus and in the expression of genes related to myelination (Plp1 and Mbp) in the hippocampal dentate gyrus. We observed only minor changes in the expression of these genes in the corpus callosum and cerebellar vermis. We used real-time reverse-transcription polymerase chain reaction to confirm Chrdl1, Hes5, Mbp, Plp1, Slit1, Robo3 and the Eph family transcript expression changes. The most significant changes in gene expression were found in the dentate gyrus. Considering that the gene expression profile of the adult dentate gyrus closely related to neurogenesis, 28-day toxicity studies looking at gene expression changes in adult hippocampal dentate gyrus may also detect possible developmental neurotoxic effects. Copyright © 2015 John Wiley & Sons, Ltd.

Circular RNA and gene expression profiles in gastric cancer based on microarray chip technology.

PubMed

Sui, Weiguo; Shi, Zhoufang; Xue, Wen; Ou, Minglin; Zhu, Ying; Chen, Jiejing; Lin, Hua; Liu, Fuhua; Dai, Yong

2017-03-01

The aim of the present study was to screen gastric cancer (GC) tissue and adjacent tissue for differences in mRNA and circular (circRNA) expression, to analyze the differences in circRNA and mRNA expression, and to investigate the circRNA expression in gastric carcinoma and its mechanism. circRNA and mRNA differential expression profiles generated using Agilent microarray technology were analyzed in the GC tissues and adjacent tissues. qRT-PCR was used to verify the differential expression of circRNAs and mRNAs according to the interactions between circRNAs and miRNAs as well as the possible existence of miRNA and mRNA interactions. We found that: i) the circRNA expression profile revealed 1,285 significant differences in circRNA expression, with circRNA expression downregulated in 594 samples and upregulated in 691 samples via interactions with miRNAs. The qRT-PCR validation experiments showed that hsa_circRNA_400071, hsa_circRNA_000543 and hsa_circRNA_001959 expression was consistent with the microarray analysis results. ii) 29,112 genes were found in the GC tissues and adjacent tissues, including 5,460 differentially expressed genes. Among them, 2,390 differentially expressed genes were upregulated and 3,070 genes were downregulated. Gene Ontology (GO) analysis of the differentially expressed genes revealed these genes involved in biological process classification, cellular component classification and molecular function classification. Pathway analysis of the differentially expressed genes identified 83 significantly enriched genes, including 28 upregulated genes and 55 downregulated genes. iii) 69 differentially expressed circRNAs were found that might adsorb specific miRNAs to regulate the expression of their target gene mRNAs. The conclusions are: i) differentially expressed circRNAs had corresponding miRNA binding sites. These circRNAs regulated the expression of target genes through interactions with miRNAs and might become new molecular biomarkers for GC in the future. ii) Differentially expressed genes may be involved in the occurrence of GC via a variety of mechanisms. iii) CD44, CXXC5, MYH9, MALAT1 and other genes may have important implications for the occurrence and development of GC through the regulation, interaction, and mutual influence of circRNA-miRNA-mRNA via different mechanisms.

Global transcriptional responses of Bacillus subtilis to xenocoumacin 1.

PubMed

Zhou, T; Zeng, H; Qiu, D; Yang, X; Wang, B; Chen, M; Guo, L; Wang, S

2011-09-01

To determine the global transcriptional response of Bacillus subtilis to an antimicrobial agent, xenocoumacin 1 (Xcn1). Subinhibitory concentration of Xcn1 applied to B. subtilis was measured according to Hutter's method for determining optimal concentrations. cDNA microarray technology was used to study the global transcriptional response of B. subtilis to Xcn1. Real-time RT-PCR was employed to verify alterations in the transcript levels of six genes. The subinhibitory concentration was determined to be 1 μg ml(-1). The microarray data demonstrated that Xcn1 treatment of B. subtilis led to more than a 2.0-fold up-regulation of 480 genes and more than a 2.0-fold down-regulation of 479 genes (q ≤ 0.05). The transcriptional responses of B. subtilis to Xcn1 were determined, and several processes were affected by Xcn1. Additionally, cluster analysis of gene expression profiles after treatment with Xcn1 or 37 previously studied antibiotics indicated that Xcn1 has similar mechanisms of action to protein synthesis inhibitors. These microarray data showed alterations of gene expression in B. subtilis after exposure to Xcn1. From the results, we identified various processes affected by Xcn1. This study provides a whole-genome perspective to elucidate the action of Xcn1 as a potential antimicrobial agent. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.

Histological staining methods preparatory to laser capture microdissection significantly affect the integrity of the cellular RNA.

PubMed

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.

Histological staining methods preparatory to laser capture microdissection significantly affect the integrity of the cellular RNA

PubMed Central

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

RNA-Seq Transcriptome Profiling of Upland Cotton (Gossypium hirsutum L.) Root Tissue under Water-Deficit Stress

PubMed Central

Bowman, Megan J.; Park, Wonkeun; Bauer, Philip J.; Udall, Joshua A.; Page, Justin T.; Raney, Joshua; Scheffler, Brian E.; Jones, Don. C.; Campbell, B. Todd

2013-01-01

An RNA-Seq experiment was performed using field grown well-watered and naturally rain fed cotton plants to identify differentially expressed transcripts under water-deficit stress. Our work constitutes the first application of the newly published diploid D5 Gossypium raimondii sequence in the study of tetraploid AD1 upland cotton RNA-seq transcriptome analysis. A total of 1,530 transcripts were differentially expressed between well-watered and water-deficit stressed root tissues, in patterns that confirm the accuracy of this technique for future studies in cotton genomics. Additionally, putative sequence based genome localization of differentially expressed transcripts detected A2 genome specific gene expression under water-deficit stress. These data will facilitate efforts to understand the complex responses governing transcriptomic regulatory mechanisms and to identify candidate genes that may benefit applied plant breeding programs. PMID:24324815

Effects of seawater acidification on gene expression: resolving broader-scale trends in sea urchins.

PubMed

Evans, Tyler G; Watson-Wynn, Priscilla

2014-06-01

Sea urchins are ecologically and economically important calcifying organisms threatened by acidification of the global ocean caused by anthropogenic CO2 emissions. Propelled by the sequencing of the purple sea urchin (Strongylocentrotus purpuratus) genome, profiling changes in gene expression during exposure to high pCO2 seawater has emerged as a powerful and increasingly common method to infer the response of urchins to ocean change. However, analyses of gene expression are sensitive to experimental methodology, and comparisons between studies of genes regulated by ocean acidification are most often made in the context of major caveats. Here we perform meta-analyses as a means of minimizing experimental discrepancies and resolving broader-scale trends regarding the effects of ocean acidification on gene expression in urchins. Analyses across eight studies and four urchin species largely support prevailing hypotheses about the impact of ocean acidification on marine calcifiers. The predominant expression pattern involved the down-regulation of genes within energy-producing pathways, a clear indication of metabolic depression. Genes with functions in ion transport were significantly over-represented and are most plausibly contributing to intracellular pH regulation. Expression profiles provided extensive evidence for an impact on biomineralization, epitomized by the down-regulation of seven spicule matrix proteins. In contrast, expression profiles provided limited evidence for CO2-mediated developmental delay or induction of a cellular stress response. Congruence between studies of gene expression and the ocean acidification literature in general validates the accuracy of gene expression in predicting the consequences of ocean change and justifies its continued use in future studies. © 2014 Marine Biological Laboratory.

Deciphering defective amelogenesis using in vitro culture systems.

PubMed

Arinawati, Dian Yosi; Miyoshi, Keiko; Tanimura, Ayako; Horiguchi, Taigo; Hagita, Hiroko; Noma, Takafumi

2018-04-01

The conventional two-dimensional (2D) in vitro culture system is frequently used to analyze the gene expression with or without extracellular signals. However, the cells derived from primary culture and cell lines frequently deviate the gene expression profile compared to the corresponding in vivo samples, which sometimes misleads the actual gene regulation in vivo. To overcome this gap, we developed the comparative 2D and 3D in vitro culture systems and applied them to the genetic study of amelogenesis imperfecta (AI) as a model. Recently, we found specificity protein 6 (Sp6) mutation in an autosomal-recessive AI rat that was previously named AMI. We constructed 3D structure of ARE-B30 cells (AMI-derived rat dental epithelial cells) or G5 (control wild type cells) combined with RPC-C2A cells (rat pulp cell line) separated by the collagen membrane, while in 2D structure, ARE-B30 or G5 was cultured with or without the collagen membrane. Comparative analysis of amelogenesis-related gene expression in ARE-B30 and G5 using our 2D and 3D in vitro systems revealed distinct expression profiles, showing the causative outcomes. Bone morphogenetic protein 2 and follistatin were reciprocally expressed in G5, but not in ARE-B30 cells. All-or-none expression of amelotin, kallikrein-related peptidase 4, and nerve growth factor receptor was observed in both cell types. In conclusion, our in vitro culture systems detected the phenotypical differences in the expression of the stage-specific amelogenesis-related genes. Parallel analysis with 2D and 3D culture systems may provide a platform to understand the molecular basis for defective amelogenesis caused by Sp6 mutation. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

ARG1 Functions in the Physiological Adaptation of Undifferentiated Plant Cells to Spaceflight.

PubMed

Zupanska, Agata K; Schultz, Eric R; Yao, JiQiang; Sng, Natasha J; Zhou, Mingqi; Callaham, Jordan B; Ferl, Robert J; Paul, Anna-Lisa

2017-11-01

Scientific access to spaceflight and especially the International Space Station has revealed that physiological adaptation to spaceflight is accompanied or enabled by changes in gene expression that significantly alter the transcriptome of cells in spaceflight. A wide range of experiments have shown that plant physiological adaptation to spaceflight involves gene expression changes that alter cell wall and other metabolisms. However, while transcriptome profiling aptly illuminates changes in gene expression that accompany spaceflight adaptation, mutation analysis is required to illuminate key elements required for that adaptation. Here we report how transcriptome profiling was used to gain insight into the spaceflight adaptation role of Altered response to gravity 1 (Arg1), a gene known to affect gravity responses in plants on Earth. The study compared expression profiles of cultured lines of Arabidopsis thaliana derived from wild-type (WT) cultivar Col-0 to profiles from a knock-out line deficient in the gene encoding ARG1 (ARG1 KO), both on the ground and in space. The cell lines were launched on SpaceX CRS-2 as part of the Cellular Expression Logic (CEL) experiment of the BRIC-17 spaceflight mission. The cultured cell lines were grown within 60 mm Petri plates in Petri Dish Fixation Units (PDFUs) that were housed within the Biological Research In Canisters (BRIC) hardware. Spaceflight samples were fixed on orbit. Differentially expressed genes were identified between the two environments (spaceflight and comparable ground controls) and the two genotypes (WT and ARG1 KO). Each genotype engaged unique genes during physiological adaptation to the spaceflight environment, with little overlap. Most of the genes altered in expression in spaceflight in WT cells were found to be Arg1-dependent, suggesting a major role for that gene in the physiological adaptation of undifferentiated cells to spaceflight. Key Words: ARG1-Spaceflight-Gene expression-Physiological adaptation-BRIC. Astrobiology 17, 1077-1111.

Comparison of Glomerular and Podocyte mRNA Profiles in Streptozotocin-Induced Diabetes

PubMed Central

Fu, Jia; Wei, Chengguo; Lee, Kyung; Zhang, Weijia; He, Wu; Chuang, Peter

2016-01-01

Evaluating the mRNA profile of podocytes in the diabetic kidney may indicate genes involved in the pathogenesis of diabetic nephropathy. To determine if the podocyte-specific gene information contained in mRNA profiles of the whole glomerulus of the diabetic kidney accurately reflects gene expression in the isolated podocytes, we crossed Nos3−/− IRG mice with podocin-rtTA and TetON-Cre mice for enhanced green fluorescent protein labeling of podocytes before diabetic injury. Diabetes was induced by streptozotocin, and mRNA profiles of isolated glomeruli and sorted podocytes from diabetic and control mice were examined 10 weeks later. Expression of podocyte-specific markers in glomeruli was downregulated in diabetic mice compared with controls. However, expression of these markers was not altered in sorted podocytes from diabetic mice. When mRNA levels of glomeruli were corrected for podocyte number per glomerulus, the differences in podocyte marker expression disappeared. Analysis of the differentially expressed genes in diabetic mice also revealed distinct upregulated pathways in the glomeruli (mitochondrial function, oxidative stress) and in podocytes (actin organization). In conclusion, our data suggest reduced expression of podocyte markers in glomeruli is a secondary effect of reduced podocyte number, thus podocyte-specific gene expression detected in the whole glomerulus may not represent that in podocytes in the diabetic kidney. PMID:26264855

Hepatic gene expression in rainbow trout (Oncorhynchus mykiss) exposed to different hydrocarbon mixtures.

PubMed

Hook, Sharon E; Lampi, Mark A; Febbo, Eric J; Ward, Jeff A; Parkerton, Thomas F

2010-09-01

Traditional biomarkers for hydrocarbon exposure are not induced by all petroleum substances. The objective of this study was to determine if exposure to a crude oil and different refined oils would generate a common hydrocarbon-specific response in gene expression profiles that could be used as generic biomarkers of hydrocarbon exposure. Juvenile rainbow trout (Oncorhynchus mykiss) were exposed to the water accommodated fraction (WAF) of either kerosene, gas oil, heavy fuel oil, or crude oil for 96 h. Tissue was collected for RNA extraction and microarray analysis. Exposure to each WAF resulted in a different list of differentially regulated genes, with few genes in common across treatments. Exposure to crude oil WAF changed the expression of genes including cytochrome P4501A (CYP1A) and glutathione-S-transferase (GST) with known roles in detoxification pathways. These gene expression profiles were compared to others from previous experiments that used a diverse suite of toxicants. Clustering algorithms successfully identified gene expression profiles resulting from hydrocarbon exposure. These preliminary analyses highlight the difficulties of using single genes as diagnostic of petroleum hydrocarbon exposures. Further work is needed to determine if multivariate transcriptomic-based biomarkers may be a more effective tool than single gene studies for exposure monitoring of different oils. Copyright 2010 SETAC.

Genome-wide evolutionary characterization and expression analyses of WRKY family genes in Brachypodium distachyon.

PubMed

Wen, Feng; Zhu, Hong; Li, Peng; Jiang, Min; Mao, Wenqing; Ong, Chermaine; Chu, Zhaoqing

2014-06-01

Members of plant WRKY gene family are ancient transcription factors that function in plant growth and development and respond to biotic and abiotic stresses. In our present study, we have investigated WRKY family genes in Brachypodium distachyon, a new model plant of family Poaceae. We identified a total of 86 WRKY genes from B. distachyon and explored their chromosomal distribution and evolution, domain alignment, promoter cis-elements, and expression profiles. Combining the analysis of phylogenetic tree of BdWRKY genes and the result of expression profiling, results showed that most of clustered gene pairs had higher similarities in the WRKY domain, suggesting that they might be functionally redundant. Neighbour-joining analysis of 301 WRKY domains from Oryza sativa, Arabidopsis thaliana, and B. distachyon suggested that BdWRKY domains are evolutionarily more closely related to O. sativa WRKY domains than those of A. thaliana. Moreover, tissue-specific expression profile of BdWRKY genes and their responses to phytohormones and several biotic or abiotic stresses were analysed by quantitative real-time PCR. The results showed that the expression of BdWRKY genes was rapidly regulated by stresses and phytohormones, and there was a strong correlation between promoter cis-elements and the phytohormones-induced BdWRKY gene expression. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

A multiplex branched DNA assay for parallel quantitative gene expression profiling.

PubMed

Flagella, Michael; Bui, Son; Zheng, Zhi; Nguyen, Cung Tuong; Zhang, Aiguo; Pastor, Larry; Ma, Yunqing; Yang, Wen; Crawford, Kimberly L; McMaster, Gary K; Witney, Frank; Luo, Yuling

2006-05-01

We describe a novel method to quantitatively measure messenger RNA (mRNA) expression of multiple genes directly from crude cell lysates and tissue homogenates without the need for RNA purification or target amplification. The multiplex branched DNA (bDNA) assay adapts the bDNA technology to the Luminex fluorescent bead-based platform through the use of cooperative hybridization, which ensures an exceptionally high degree of assay specificity. Using in vitro transcribed RNA as reference standards, we demonstrated that the assay is highly specific, with cross-reactivity less than 0.2%. We also determined that the assay detection sensitivity is 25,000 RNA transcripts with intra- and interplate coefficients of variance of less than 10% and less than 15%, respectively. Using three 10-gene panels designed to measure proinflammatory and apoptosis responses, we demonstrated sensitive and specific multiplex gene expression profiling directly from cell lysates. The gene expression change data demonstrate a high correlation coefficient (R(2)=0.94) compared with measurements obtained using the single-plex bDNA assay. Thus, the multiplex bDNA assay provides a powerful means to quantify the gene expression profile of a defined set of target genes in large sample populations.

PULMONARY GENE EXPRESSION PROFILES OF SPONTANEOUSLY HYPERTENSIVE RATS EXPOSED TO ENVIRONMENTAL TOBACCO SMOKE (ETS)

EPA Science Inventory

Global gene expression profile analysis can be utilized to derive molecular footprints to understand biochemical

pathways implicated in the origin and progression of disease. Functional genomics efforts with tissue-specific focused

genearray appears to be the most...

GENE EXPRESSION PROFILING IN THE LIVER OF CD-1 MICE TO CHARACTERIZE THE HEPATOTOXICITY OF TRIAZOLE FUNGICIDES.

EPA Science Inventory

Four triazole fungicides used in agricultural or pharmaceutical applications were examined for hepatotoxic effects in mouse liver. Besides organ weight, histopathology, and cytochrome P450 (CYP) enzyme induction, DNA microarrays were used to generate gene expression profiles and ...

GENE EXPRESSION PROFILING IN THE LIVER OF CD-1 MICE TO CHARACTERIZE THE HEPATOTOXICITY OF TRIAZOLE FUNGICIDES

EPA Science Inventory

Four triazole fungicides used in agricultural or pharmaceutical applications were examined for hepatotoxic effects in mouse liver. Besides organ weight, histopathology, and cytochrome P450 (CYP) enzyme induction, DNA microarrays were used to generate gene expression profiles and ...

CARDIOPULMONARY GENE EXPRESSION PROFILES IN NORMO- AND SPONTANEOUSLY HYPERSENSITIVE (SH) RATS: IMPACT OF PARTICULATE MATTER (PM) EXPOSURE

EPA Science Inventory

CARDIOPULMONARY GENE EXPRESSION PROFILES IN NORMO- AND SPONTANEOUSLY HYPERTENSIVE (SH) RATS: IMPACT OF PARTICULATE MATTER (PM) EXPOSURE. SS Nadadur UP Kodavanti, Pulmonary Toxicology Branch, ETD, ORD, NHEERL, US Environmental Protection Agency, Research Triangle Park, NC 27711.

Estimating replicate time shifts using Gaussian process regression

PubMed Central

Liu, Qiang; Andersen, Bogi; Smyth, Padhraic; Ihler, Alexander

2010-01-01

Motivation: Time-course gene expression datasets provide important insights into dynamic aspects of biological processes, such as circadian rhythms, cell cycle and organ development. In a typical microarray time-course experiment, measurements are obtained at each time point from multiple replicate samples. Accurately recovering the gene expression patterns from experimental observations is made challenging by both measurement noise and variation among replicates' rates of development. Prior work on this topic has focused on inference of expression patterns assuming that the replicate times are synchronized. We develop a statistical approach that simultaneously infers both (i) the underlying (hidden) expression profile for each gene, as well as (ii) the biological time for each individual replicate. Our approach is based on Gaussian process regression (GPR) combined with a probabilistic model that accounts for uncertainty about the biological development time of each replicate. Results: We apply GPR with uncertain measurement times to a microarray dataset of mRNA expression for the hair-growth cycle in mouse back skin, predicting both profile shapes and biological times for each replicate. The predicted time shifts show high consistency with independently obtained morphological estimates of relative development. We also show that the method systematically reduces prediction error on out-of-sample data, significantly reducing the mean squared error in a cross-validation study. Availability: Matlab code for GPR with uncertain time shifts is available at http://sli.ics.uci.edu/Code/GPRTimeshift/ Contact: ihler@ics.uci.edu PMID:20147305

Digital gene expression analysis of the zebra finch genome

PubMed Central

2010-01-01

Background In order to understand patterns of adaptation and molecular evolution it is important to quantify both variation in gene expression and nucleotide sequence divergence. Gene expression profiling in non-model organisms has recently been facilitated by the advent of massively parallel sequencing technology. Here we investigate tissue specific gene expression patterns in the zebra finch (Taeniopygia guttata) with special emphasis on the genes of the major histocompatibility complex (MHC). Results Almost 2 million 454-sequencing reads from cDNA of six different tissues were assembled and analysed. A total of 11,793 zebra finch transcripts were represented in this EST data, indicating a transcriptome coverage of about 65%. There was a positive correlation between the tissue specificity of gene expression and non-synonymous to synonymous nucleotide substitution ratio of genes, suggesting that genes with a specialised function are evolving at a higher rate (or with less constraint) than genes with a more general function. In line with this, there was also a negative correlation between overall expression levels and expression specificity of contigs. We found evidence for expression of 10 different genes related to the MHC. MHC genes showed relatively tissue specific expression levels and were in general primarily expressed in spleen. Several MHC genes, including MHC class I also showed expression in brain. Furthermore, for all genes with highest levels of expression in spleen there was an overrepresentation of several gene ontology terms related to immune function. Conclusions Our study highlights the usefulness of next-generation sequence data for quantifying gene expression in the genome as a whole as well as in specific candidate genes. Overall, the data show predicted patterns of gene expression profiles and molecular evolution in the zebra finch genome. Expression of MHC genes in particular, corresponds well with expression patterns in other vertebrates. PMID:20359325

Methylation and expression profiles of MGMT gene in thymic epithelial tumors.

PubMed

Mokhtar, Mohamed; Kondo, Kazuya; Namura, Toshiaki; Ali, Abdellah H K; Fujita, Yui; Takai, Chikako; Takizawa, Hiromitsu; Nakagawa, Yasushi; Toba, Hiroaki; Kajiura, Koichiro; Yoshida, Mitsuteru; Kawakami, Gyokei; Sakiyama, Shoji; Tangoku, Akira

2014-02-01

A key challenge in diagnosis and treatment of thymic epithelial tumors (TET) is in improving our understanding of the genetic and epigenetic changes of these relatively rare tumors. Methylation specific PCR (MSP) and immunohistochemistry were applied to 66 TET to profile the methylation status of DNA repair gene O6-methylguanine DNA methyltransferase (MGMT) and its protein expression in TET to clarify the association between MGMT status and clinicopathological features, response to chemotherapy and overall survival. MGMT methylation was significantly more frequent in thymic carcinoma than in thymoma (17/23, 74% versus 13/44, 29%; P<0.001). Loss of expression of MGMT protein was significantly more frequent in thymic carcinoma than in thymoma (20/23, 87% versus 10/44, 23%; P<0.0001). There is a significant correlation between of MGMT methylation and loss of its protein expression (P<0.0003). MGMT methylation and loss of expression were significantly more frequent in advanced thymic epithelial tumors (III/IV) than in early tumors (I/II). MGMT methylation plays a soul role in development of TET, especially in thymic carcinoma. Therefore, translation of our results from basic molecular research to clinical practice may have important implication for considering MGMT methylation as a marker and a target of future therapies in TET. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Circular RNA profile in gliomas revealed by identification tool UROBORUS.

PubMed

Song, Xiaofeng; Zhang, Naibo; Han, Ping; Moon, Byoung-San; Lai, Rose K; Wang, Kai; Lu, Wange

2016-05-19

Recent evidence suggests that many endogenous circular RNAs (circRNAs) may play roles in biological processes. However, the expression patterns and functions of circRNAs in human diseases are not well understood. Computationally identifying circRNAs from total RNA-seq data is a primary step in studying their expression pattern and biological roles. In this work, we have developed a computational pipeline named UROBORUS to detect circRNAs in total RNA-seq data. By applying UROBORUS to RNA-seq data from 46 gliomas and normal brain samples, we detected thousands of circRNAs supported by at least two read counts, followed by successful experimental validation on 24 circRNAs from the randomly selected 27 circRNAs. UROBORUS is an efficient tool that can detect circRNAs with low expression levels in total RNA-seq without RNase R treatment. The circRNAs expression profiling revealed more than 476 circular RNAs differentially expressed in control brain tissues and gliomas. Together with parental gene expression, we found that circRNA and its parental gene have diversified expression patterns in gliomas and control brain tissues. This study establishes an efficient and sensitive approach for predicting circRNAs using total RNA-seq data. The UROBORUS pipeline can be accessed freely for non-commercial purposes at http://uroborus.openbioinformatics.org/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Divergent evolution of arrested development in the dauer stage of Caenorhabditis elegans and the infective stage of Heterodera glycines

PubMed Central

Elling, Axel A; Mitreva, Makedonka; Recknor, Justin; Gai, Xiaowu; Martin, John; Maier, Thomas R; McDermott, Jeffrey P; Hewezi, Tarek; McK Bird, David; Davis, Eric L; Hussey, Richard S; Nettleton, Dan; McCarter, James P; Baum, Thomas J

2007-01-01

Background The soybean cyst nematode Heterodera glycines is the most important parasite in soybean production worldwide. A comprehensive analysis of large-scale gene expression changes throughout the development of plant-parasitic nematodes has been lacking to date. Results We report an extensive genomic analysis of H. glycines, beginning with the generation of 20,100 expressed sequence tags (ESTs). In-depth analysis of these ESTs plus approximately 1,900 previously published sequences predicted 6,860 unique H. glycines genes and allowed a classification by function using InterProScan. Expression profiling of all 6,860 genes throughout the H. glycines life cycle was undertaken using the Affymetrix Soybean Genome Array GeneChip. Our data sets and results represent a comprehensive resource for molecular studies of H. glycines. Demonstrating the power of this resource, we were able to address whether arrested development in the Caenorhabditis elegans dauer larva and the H. glycines infective second-stage juvenile (J2) exhibits shared gene expression profiles. We determined that the gene expression profiles associated with the C. elegans dauer pathway are not uniformly conserved in H. glycines and that the expression profiles of genes for metabolic enzymes of C. elegans dauer larvae and H. glycines infective J2 are dissimilar. Conclusion Our results indicate that hallmark gene expression patterns and metabolism features are not shared in the developmentally arrested life stages of C. elegans and H. glycines, suggesting that developmental arrest in these two nematode species has undergone more divergent evolution than previously thought and pointing to the need for detailed genomic analyses of individual parasite species. PMID:17919324

Blood expression profiles of fragile X premutation carriers identify candidate genes involved in neurodegenerative and infertility phenotypes.

PubMed

Mateu-Huertas, Elisabet; Rodriguez-Revenga, Laia; Alvarez-Mora, Maria Isabel; Madrigal, Irene; Willemsen, Rob; Milà, Montserrat; Martí, Eulàlia; Estivill, Xavier

2014-05-01

Male premutation carriers presenting between 55 and 200 CGG repeats in the Fragile-X-associated (FMR1) gene are at risk of developing Fragile X Tremor/Ataxia Syndrome (FXTAS), and females undergo Premature Ovarian Failure (POF1). Here, we have evaluated gene expression profiles from blood in male FMR1 premutation carriers and detected a strong deregulation of genes enriched in FXTAS relevant biological pathways, including inflammation, neuronal homeostasis and viability. Gene expression profiling distinguished between control individuals, carriers with FXTAS and carriers without FXTAS, with levels of expanded FMR1 mRNA being increased in FXTAS patients. In vitro studies in a neuronal cell model indicate that expression levels of expanded FMR1 5'-UTR are relevant in modulating the transcriptome. Thus, perturbations of the transcriptome may be an interplay between the CGG expansion size and FMR1 expression levels. Several deregulated genes (DFFA, BCL2L11, BCL2L1, APP, SOD1, RNF10, HDAC5, KCNC3, ATXN7, ATXN3 and EAP1) were validated in brain samples of a FXTAS mouse model. Downregulation of EAP1, a gene involved in the female reproductive system physiology, was confirmed in female carriers. Decreased levels were detected in female carriers with POF1 compared to those without POF1, suggesting that EAP1 levels contribute to ovarian insufficiency. In summary, gene expression profiling in blood has uncovered mechanisms that may underlie different pathological aspects of the premutation. A better understanding of the transcriptome dynamics in relation with expanded FMR1 mRNA expression levels and CGG expansion size may provide mechanistic insights into the disease process and a more accurate FXTAS diagnosis to the myriad of phenotypes associated with the premutation. Copyright © 2014. Published by Elsevier Inc.

Transcriptional profiling reveals regulated genes in the hippocampus during memory formation

NASA Technical Reports Server (NTRS)

Donahue, Christine P.; Jensen, Roderick V.; Ochiishi, Tomoyo; Eisenstein, Ingrid; Zhao, Mingrui; Shors, Tracey; Kosik, Kenneth S.

2002-01-01

Transcriptional profiling (TP) offers a powerful approach to identify genes activated during memory formation and, by inference, the molecular pathways involved. Trace eyeblink conditioning is well suited for the study of regional gene expression because it requires the hippocampus, whereas the highly parallel task, delay conditioning, does not. First, we determined when gene expression was most regulated during trace conditioning. Rats were exposed to 200 trials per day of paired and unpaired stimuli each day for 4 days. Changes in gene expression were most apparent 24 h after exposure to 200 trials. Therefore, we profiled gene expression in the hippocampus 24 h after 200 trials of trace eyeblink conditioning, on multiple arrays using additional animals. Of 1,186 genes on the filter array, seven genes met the statistical criteria and were also validated by real-time polymerase chain reaction. These genes were growth hormone (GH), c-kit receptor tyrosine kinase (c-kit), glutamate receptor, metabotropic 5 (mGluR5), nerve growth factor-beta (NGF-beta), Jun oncogene (c-Jun), transmembrane receptor Unc5H1 (UNC5H1), and transmembrane receptor Unc5H2 (UNC5H2). All these genes, except for GH, were downregulated in response to trace conditioning. GH was upregulated; therefore, we also validated the downregulation of the GH inhibitor, somatostatin (SST), even though it just failed to meet criteria on the arrays. By during situ hybridization, GH was expressed throughout the cell layers of the hippocampus in response to trace conditioning. None of the genes regulated in trace eyeblink conditioning were similarly affected by delay conditioning, a task that does not require the hippocampus. These findings demonstrate that transcriptional profiling can exhibit a repertoire of genes sensitive to the formation of hippocampal-dependent associative memories.

Genome-wide analysis of soybean HD-Zip gene family and expression profiling under salinity and drought treatments.

PubMed

Chen, Xue; Chen, Zhu; Zhao, Hualin; Zhao, Yang; Cheng, Beijiu; Xiang, Yan

2014-01-01

Homeodomain-leucine zipper (HD-Zip) proteins, a group of homeobox transcription factors, participate in various aspects of normal plant growth and developmental processes as well as environmental responses. To date, no overall analysis or expression profiling of the HD-Zip gene family in soybean (Glycine max) has been reported. An investigation of the soybean genome revealed 88 putative HD-Zip genes. These genes were classified into four subfamilies, I to IV, based on phylogenetic analysis. In each subfamily, the constituent parts of gene structure and motif were relatively conserved. A total of 87 out of 88 genes were distributed unequally on 20 chromosomes with 36 segmental duplication events, indicating that segmental duplication is important for the expansion of the HD-Zip family. Analysis of the Ka/Ks ratios showed that the duplicated genes of the HD-Zip family basically underwent purifying selection with restrictive functional divergence after the duplication events. Analysis of expression profiles showed that 80 genes differentially expressed across 14 tissues, and 59 HD-Zip genes are differentially expressed under salinity and drought stress, with 20 paralogous pairs showing nearly identical expression patterns and three paralogous pairs diversifying significantly under drought stress. Quantitative real-time RT-PCR (qRT-PCR) analysis of six paralogous pairs of 12 selected soybean HD-Zip genes under both drought and salinity stress confirmed their stress-inducible expression patterns. This study presents a thorough overview of the soybean HD-Zip gene family and provides a new perspective on the evolution of this gene family. The results indicate that HD-Zip family genes may be involved in many plant responses to stress conditions. Additionally, this study provides a solid foundation for uncovering the biological roles of HD-Zip genes in soybean growth and development.

eXpression2Kinases (X2K) Web: linking expression signatures to upstream cell signaling networks.

PubMed

Clarke, Daniel J B; Kuleshov, Maxim V; Schilder, Brian M; Torre, Denis; Duffy, Mary E; Keenan, Alexandra B; Lachmann, Alexander; Feldmann, Axel S; Gundersen, Gregory W; Silverstein, Moshe C; Wang, Zichen; Ma'ayan, Avi

2018-05-25

While gene expression data at the mRNA level can be globally and accurately measured, profiling the activity of cell signaling pathways is currently much more difficult. eXpression2Kinases (X2K) computationally predicts involvement of upstream cell signaling pathways, given a signature of differentially expressed genes. X2K first computes enrichment for transcription factors likely to regulate the expression of the differentially expressed genes. The next step of X2K connects these enriched transcription factors through known protein-protein interactions (PPIs) to construct a subnetwork. The final step performs kinase enrichment analysis on the members of the subnetwork. X2K Web is a new implementation of the original eXpression2Kinases algorithm with important enhancements. X2K Web includes many new transcription factor and kinase libraries, and PPI networks. For demonstration, thousands of gene expression signatures induced by kinase inhibitors, applied to six breast cancer cell lines, are provided for fetching directly into X2K Web. The results are displayed as interactive downloadable vector graphic network images and bar graphs. Benchmarking various settings via random permutations enabled the identification of an optimal set of parameters to be used as the default settings in X2K Web. X2K Web is freely available from http://X2K.cloud.

Network-Induced Classification Kernels for Gene Expression Profile Analysis

PubMed Central

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

ExprAlign - the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles

PubMed Central

2009-01-01

Background Sequence identification of ESTs from non-model species offers distinct challenges particularly when these species have duplicated genomes and when they are phylogenetically distant from sequenced model organisms. For the common carp, an environmental model of aquacultural interest, large numbers of ESTs remained unidentified using BLAST sequence alignment. We have used the expression profiles from large-scale microarray experiments to suggest gene identities. Results Expression profiles from ~700 cDNA microarrays describing responses of 7 major tissues to multiple environmental stressors were used to define a co-expression landscape. This was based on the Pearsons correlation coefficient relating each gene with all other genes, from which a network description provided clusters of highly correlated genes as 'mountains'. We show that these contain genes with known identities and genes with unknown identities, and that the correlation constitutes evidence of identity in the latter. This procedure has suggested identities to 522 of 2701 unknown carp ESTs sequences. We also discriminate several common carp genes and gene isoforms that were not discriminated by BLAST sequence alignment alone. Precision in identification was substantially improved by use of data from multiple tissues and treatments. Conclusion The detailed analysis of co-expression landscapes is a sensitive technique for suggesting an identity for the large number of BLAST unidentified cDNAs generated in EST projects. It is capable of detecting even subtle changes in expression profiles, and thereby of distinguishing genes with a common BLAST identity into different identities. It benefits from the use of multiple treatments or contrasts, and from the large-scale microarray data. PMID:19939286

Rat Models of Cardiovascular Disease Demonstrate Distinctive Pulmonary Gene Expressions for Vascular Response Genes: Impact of Ozone Exposure

EPA Science Inventory

Comparative gene expression profiling of multiple tissues from rat strains with genetic predisposition to diverse cardiovascular diseases (CVD) can help decode the transcriptional program that governs organ-specific functions. We examined expressions of CVD genes in the lungs of ...

GENE EXPRESSION PROFILING OF ACCESSIBLE SURROGATE TISSUES TO MONITOR MOLECULAR CHANGES IN INACCESSIBLE TARGET TISSUES FOLLOWING TOXICANT EXPOSURE

EPA Science Inventory

Gene Expression Profiling Of Accessible Surrogate Tissues To Monitor Molecular Changes In Inaccessible Target Tissues Following Toxicant Exposure
John C. Rockett, Chad R. Blystone, Amber K. Goetz, Rachel N. Murrell, Judith E. Schmid and David J. Dix
Reproductive Toxicology ...

21 CFR 866.6040 - Gene expression profiling test system for breast cancer prognosis.

Code of Federal Regulations, 2010 CFR

2010-04-01

... cancer prognosis. 866.6040 Section 866.6040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... cancer prognosis. (a) Identification. A gene expression profiling test system for breast cancer prognosis... previously diagnosed breast cancer. (b) Classification. Class II (special controls). The special control is...

21 CFR 866.6040 - Gene expression profiling test system for breast cancer prognosis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... cancer prognosis. 866.6040 Section 866.6040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... cancer prognosis. (a) Identification. A gene expression profiling test system for breast cancer prognosis... previously diagnosed breast cancer. (b) Classification. Class II (special controls). The special control is...

Bioinforrnatics of Gene Expression Profiling Data Provide Mechanistic Understanding of Acute Ozone-Induced Lung injury

EPA Science Inventory

Acute ozone-induced pulmonary injury and inflammation are well characterized. A few studies have used gene expression profiling to determine the types of changes induced by ozone; however the mechanisms or the pathways involved are less well understood. We presumed that robust bi...

Comparison of Non-Human Primate and Human Whole Blood Tissue Gene Expression Profiles

DTIC Science & Technology

2005-03-01

studies have used rhesus, chimpanzee, gorilla, or orangutan RNA, but to date no gene expression profiling studies are available that use AGM or cynomologus...previous work has been published using human genechips to study NHPs, particularly rhesus, chimpanzee, gorilla, and orangutan (Uddin et al., 2004; Kayo

21 CFR 866.6040 - Gene expression profiling test system for breast cancer prognosis.

Code of Federal Regulations, 2013 CFR

2013-04-01

... cancer prognosis. 866.6040 Section 866.6040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... cancer prognosis. (a) Identification. A gene expression profiling test system for breast cancer prognosis... previously diagnosed breast cancer. (b) Classification. Class II (special controls). The special control is...

21 CFR 866.6040 - Gene expression profiling test system for breast cancer prognosis.

Code of Federal Regulations, 2012 CFR

2012-04-01

... cancer prognosis. 866.6040 Section 866.6040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... cancer prognosis. (a) Identification. A gene expression profiling test system for breast cancer prognosis... previously diagnosed breast cancer. (b) Classification. Class II (special controls). The special control is...

21 CFR 866.6040 - Gene expression profiling test system for breast cancer prognosis.

Code of Federal Regulations, 2014 CFR

2014-04-01

... cancer prognosis. 866.6040 Section 866.6040 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... cancer prognosis. (a) Identification. A gene expression profiling test system for breast cancer prognosis... previously diagnosed breast cancer. (b) Classification. Class II (special controls). The special control is...

RESIDUAL OIL FLY ASH (ROFA) AND VANADIUM-INDUCED GENE EXPRESSION PROFILES IN HUMAN VASCULAR ENDOTHELIAL CELLS

EPA Science Inventory

Residual oil fly ash (ROFA) and vanadium-induced gene expression profiles in human vascular endothelial cells.
Srikanth S. Nadadur, Urmila P. Kodavanti, Mary Jane Selgrade and Daniel L. Costa, Pulmonary Toxicology Branch, ETD, NHEERL, ORD, US EPA, Research Triangle Park, N...

Digital gene expression profiling analysis and its application in the identification of genes associated with improved response to neoadjuvant chemotherapy in breast cancer.

PubMed

Liu, Xiaozhen; Jin, Gan; Qian, Jiacheng; Yang, Hongjian; Tang, Hongchao; Meng, Xuli; Li, Yongfeng

2018-04-23

This study aimed to screen sensitive biomarkers for the efficacy evaluation of neoadjuvant chemotherapy in breast cancer. In this study, Illumina digital gene expression sequencing technology was applied and differentially expressed genes (DEGs) between patients presenting pathological complete response (pCR) and non-pathological complete response (NpCR) were identified. Further, gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were then performed. The genes in significant enriched pathways were finally quantified by quantitative real-time PCR (qRT-PCR) to confirm that they were differentially expressed. Additionally, GSE23988 from Gene Expression Omnibus database was used as the validation dataset to confirm the DEGs. After removing the low-quality reads, 715 DEGs were finally detected. After mapping to KEGG pathways, 10 DEGs belonging to the ubiquitin proteasome pathway (HECTD3, PSMB10, UBD, UBE2C, and UBE2S) and cytokine-cytokine receptor interactions (CCL2, CCR1, CXCL10, CXCL11, and IL2RG) were selected for further analysis. These 10 genes were finally quantified by qRT-PCR to confirm that they were differentially expressed (the log 2 fold changes of selected genes were - 5.34, 7.81, 6.88, 5.74, 3.11, 19.58, 8.73, 8.88, 7.42, and 34.61 for HECTD3, PSMB10, UBD, UBE2C, UBE2S, CCL2, CCR1, CXCL10, CXCL11, and IL2RG, respectively). Moreover, 53 common genes were confirmed by the validation dataset, including downregulated UBE2C and UBE2S. Our results suggested that these 10 genes belonging to these two pathways might be useful as sensitive biomarkers for the efficacy evaluation of neoadjuvant chemotherapy in breast cancer.

Changes in Gene Expression Predicting Local Control in Cervical Cancer: Results from Radiation Therapy Oncology Group 0128

PubMed Central

Weidhaas, Joanne B.; Li, Shu-Xia; Winter, Kathryn; Ryu, Janice; Jhingran, Anuja; Miller, Bridgette; Dicker, Adam P.; Gaffney, David

2009-01-01

Purpose To evaluate the potential of gene expression signatures to predict response to treatment in locally advanced cervical cancer treated with definitive chemotherapy and radiation. Experimental Design Tissue biopsies were collected from patients participating in Radiation Therapy Oncology Group (RTOG) 0128, a phase II trial evaluating the benefit of celecoxib in addition to cisplatin chemotherapy and radiation for locally advanced cervical cancer. Gene expression profiling was done and signatures of pretreatment, mid-treatment (before the first implant), and “changed” gene expression patterns between pre- and mid-treatment samples were determined. The ability of the gene signatures to predict local control versus local failure was evaluated. Two-group t test was done to identify the initial gene set separating these end points. Supervised classification methods were used to enrich the gene sets. The results were further validated by leave-one-out and 2-fold cross-validation. Results Twenty-two patients had suitable material from pretreatment samples for analysis, and 13 paired pre- and mid-treatment samples were obtained. The changed gene expression signatures between the pre- and mid-treatment biopsies predicted response to treatment, separating patients with local failures from those who achieved local control with a seven-gene signature. The in-sample prediction rate, leave-one-out prediction rate, and 2-fold prediction rate are 100% for this seven-gene signature. This signature was enriched for cell cycle genes. Conclusions Changed gene expression signatures during therapy in cervical cancer can predict outcome as measured by local control. After further validation, such findings could be applied to direct additional therapy for cervical cancer patients treated with chemotherapy and radiation. PMID:19509178

Multiple biomarkers in molecular oncology. II. Molecular diagnostics applications in breast cancer management.

PubMed

Malinowski, Douglas P

2007-05-01

In recent years, the application of genomic and proteomic technologies to the problem of breast cancer prognosis and the prediction of therapy response have begun to yield encouraging results. Independent studies employing transcriptional profiling of primary breast cancer specimens using DNA microarrays have identified gene expression profiles that correlate with clinical outcome in primary breast biopsy specimens. Recent advances in microarray technology have demonstrated reproducibility, making clinical applications more achievable. In this regard, one such DNA microarray device based upon a 70-gene expression signature was recently cleared by the US FDA for application to breast cancer prognosis. These DNA microarrays often employ at least 70 gene targets for transcriptional profiling and prognostic assessment in breast cancer. The use of PCR-based methods utilizing a small subset of genes has recently demonstrated the ability to predict the clinical outcome in early-stage breast cancer. Furthermore, protein-based immunohistochemistry methods have progressed from using gene clusters and gene expression profiling to smaller subsets of expressed proteins to predict prognosis in early-stage breast cancer. Beyond prognostic applications, DNA microarray-based transcriptional profiling has demonstrated the ability to predict response to chemotherapy in early-stage breast cancer patients. In this review, recent advances in the use of multiple markers for prognosis of disease recurrence in early-stage breast cancer and the prediction of therapy response will be discussed.

Integrated genome-wide Alu methylation and transcriptome profiling analyses reveal novel epigenetic regulatory networks associated with autism spectrum disorder.

PubMed

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.

Abnormal gene expression profiles in human ovaries from polycystic ovary syndrome patients.

PubMed

Jansen, Erik; Laven, Joop S E; Dommerholt, Henri B R; Polman, Jan; van Rijt, Cindy; van den Hurk, Caroline; Westland, Jolanda; Mosselman, Sietse; Fauser, Bart C J M

2004-12-01

Polycystic ovary syndrome (PCOS) represents the most common cause of anovulatory infertility and affects 5-10% of women of reproductive age. The etiology of PCOS is still unknown. The current study is the first to describe consistent differences in gene expression profiles in human ovaries comparing PCOS patients vs. healthy normoovulatory individuals. The microarray analysis of PCOS vs. normal ovaries identifies dysregulated expression of genes encoding components of several biological pathways or systems such as Wnt signaling, extracellular matrix components, and immunological factors. Resulting data may provide novel clues for ovarian dysfunction in PCOS. Intriguingly, the gene expression profiles of ovaries from (long-term) androgen-treated female-to-male transsexuals (TSX) show considerable overlap with PCOS. This observation provides supportive evidence that androgens play a key role in the pathogenesis of PCOS. Presented data may contribute to a better understanding of dysregulated pathways in PCOS, which might ultimately reveal novel leads for therapeutic intervention.

Expression profiles of key phenylpropanoid genes during Vanilla planifolia pod development reveal a positive correlation between PAL gene expression and vanillin biosynthesis.

PubMed

Fock-Bastide, Isabelle; Palama, Tony Lionel; Bory, Séverine; Lécolier, Aurélie; Noirot, Michel; Joët, Thierry

2014-01-01

In Vanilla planifolia pods, development of flavor precursors is dependent on the phenylpropanoid pathway. The distinctive vanilla aroma is produced by numerous phenolic compounds of which vanillin is the most important. Because of the economic importance of vanilla, vanillin biosynthetic pathways have been extensively studied but agreement has not yet been reached on the processes leading to its accumulation. In order to explore the transcriptional control exerted on these pathways, five key phenylpropanoid genes expressed during pod development were identified and their mRNA accumulation profiles were evaluated during pod development and maturation using quantitative real-time PCR. As a prerequisite for expression analysis using qRT-PCR, five potential reference genes were tested, and two genes encoding Actin and EF1 were shown to be the most stable reference genes for accurate normalization during pod development. For the first time, genes encoding a phenylalanine ammonia-lyase (VpPAL1) and a cinnamate 4-hydroxylase (VpC4H1) were identified in vanilla pods and studied during maturation. Among phenylpropanoid genes, differential regulation was observed from 3 to 8 months after pollination. VpPAL1 was gradually up-regulated, reaching the maximum expression level at maturity. In contrast, genes encoding 4HBS, C4H, OMT2 and OMT3 did not show significant increase in expression levels after the fourth month post-pollination. Expression profiling of these key phenylpropanoid genes is also discussed in light of accumulation patterns for key phenolic compounds. Interestingly, VpPAL1 gene expression was shown to be positively correlated to maturation and vanillin accumulation. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Gene Expression Profile of NF-κB, Nrf2, Glycolytic, and p53 Pathways During the SH-SY5Y Neuronal Differentiation Mediated by Retinoic Acid.

PubMed

de Bittencourt Pasquali, Matheus Augusto; de Ramos, Vitor Miranda; Albanus, Ricardo D Oliveira; Kunzler, Alice; de Souza, Luis Henrinque Trentin; Dalmolin, Rodrigo Juliani Siqueira; Gelain, Daniel Pens; Ribeiro, Leila; Carro, Luigi; Moreira, José Cláudio Fonseca

2016-01-01

SH-SY5Y cells, a neuroblastoma cell line that is a well-established model system to study the initial phases of neuronal differentiation, have been used in studies to elucidate the mechanisms of neuronal differentiation. In the present study, we investigated alterations of gene expression in SH-SY5Y cells during neuronal differentiation mediated by retinoic acid (RA) treatment. We evaluated important pathways involving nuclear factor kappa B (NF-κB), nuclear E2-related factor 2 (Nrf2), glycolytic, and p53 during neuronal differentiation. We also investigated the involvement of reactive oxygen species (ROS) in modulating the gene expression profile of those pathways by antioxidant co-treatment with Trolox®, a hydrophilic analogue of α-tocopherol. We found that RA treatment increases levels of gene expression of NF-κB, glycolytic, and antioxidant pathway genes during neuronal differentiation of SH-SY5Y cells. We also found that ROS production induced by RA treatment in SH-SY5Y cells is involved in gene expression profile alterations, chiefly in NF-κB, and glycolytic pathways. Antioxidant co-treatment with Trolox® reversed the effects mediated by RA NF-κB, and glycolytic pathways gene expression. Interestingly, co-treatment with Trolox® did not reverse the effects in antioxidant gene expression mediated by RA in SH-SY5Y. To confirm neuronal differentiation, we quantified endogenous levels of tyrosine hydroxylase, a recognized marker of neuronal differentiation. Our data suggest that during neuronal differentiation mediated by RA, changes in profile gene expression of important pathways occur. These alterations are in part mediated by ROS production. Therefore, our results reinforce the importance in understanding the mechanism by which RA induces neuronal differentiation in SH-SY5Y cells, principally due this model being commonly used as a neuronal cell model in studies of neuronal pathologies.

In Planta Stage-Specific Fungal Gene Profiling Elucidates the Molecular Strategies of Fusarium graminearum Growing inside Wheat Coleoptiles[W][OA

PubMed Central

Zhang, Xiao-Wei; Jia, Lei-Jie; Zhang, Yan; Jiang, Gang; Li, Xuan; Zhang, Dong; Tang, Wei-Hua

2012-01-01

The ascomycete Fusarium graminearum is a destructive fungal pathogen of wheat (Triticum aestivum). To better understand how this pathogen proliferates within the host plant, we tracked pathogen growth inside wheat coleoptiles and then examined pathogen gene expression inside wheat coleoptiles at 16, 40, and 64 h after inoculation (HAI) using laser capture microdissection and microarray analysis. We identified 344 genes that were preferentially expressed during invasive growth in planta. Gene expression profiles for 134 putative plant cell wall–degrading enzyme genes suggest that there was limited cell wall degradation at 16 HAI and extensive degradation at 64 HAI. Expression profiles for genes encoding reactive oxygen species (ROS)–related enzymes suggest that F. graminearum primarily scavenges extracellular ROS before a later burst of extracellular ROS is produced by F. graminearum enzymes. Expression patterns of genes involved in primary metabolic pathways suggest that F. graminearum relies on the glyoxylate cycle at an early stage of plant infection. A secondary metabolite biosynthesis gene cluster was specifically induced at 64 HAI and was required for virulence. Our results indicate that F. graminearum initiates infection of coleoptiles using covert penetration strategies and switches to overt cellular destruction of tissues at an advanced stage of infection. PMID:23266949

A PCR primer bank for quantitative gene expression analysis.

PubMed

Wang, Xiaowei; Seed, Brian

2003-12-15

Although gene expression profiling by microarray analysis is a useful tool for assessing global levels of transcriptional activity, variability associated with the data sets usually requires that observed differences be validated by some other method, such as real-time quantitative polymerase chain reaction (real-time PCR). However, non-specific amplification of non-target genes is frequently observed in the latter, confounding the analysis in approximately 40% of real-time PCR attempts when primer-specific labels are not used. Here we present an experimentally validated algorithm for the identification of transcript-specific PCR primers on a genomic scale that can be applied to real-time PCR with sequence-independent detection methods. An online database, PrimerBank, has been created for researchers to retrieve primer information for their genes of interest. PrimerBank currently contains 147 404 primers encompassing most known human and mouse genes. The primer design algorithm has been tested by conventional and real-time PCR for a subset of 112 primer pairs with a success rate of 98.2%.

Differential gene expression profiling of endometrium during the mid-luteal phase of the estrous cycle between a repeat breeder (RB) and non-RB cows.

PubMed

Hayashi, Ken-Go; Hosoe, Misa; Kizaki, Keiichiro; Fujii, Shiori; Kanahara, Hiroko; Takahashi, Toru; Sakumoto, Ryosuke

2017-03-23

Repeat breeding directly affects reproductive efficiency in cattle due to an increase in services per conception and calving interval. This study aimed to investigate whether changes in endometrial gene expression profile are involved in repeat breeding in cows. Differential gene expression profiles of the endometrium were investigated during the mid-luteal phase of the estrous cycle between repeat breeder (RB) and non-RB cows using microarray analysis. The caruncular (CAR) and intercaruncular (ICAR) endometrium of both ipsilateral and contralateral uterine horns to the corpus luteum were collected from RB (inseminated at least three times but not pregnant) and non-RB cows on Day 15 of the estrous cycle (4 cows/group). Global gene expression profiles of these endometrial samples were analyzed with a 15 K custom-made oligo-microarray for cattle. Immunohistochemistry was performed to investigate the cellular localization of proteins of three identified transcripts in the endometrium. Microarray analysis revealed that 405 and 397 genes were differentially expressed in the CAR and ICAR of the ipsilateral uterine horn of RB, respectively when compared with non-RB cows. In the contralateral uterine horn, 443 and 257 differentially expressed genes were identified in the CAR and ICAR of RB, respectively when compared with non-RB cows. Gene ontology analysis revealed that genes involved in development and morphogenesis were mainly up-regulated in the CAR of RB cows. In the ICAR of both the ipsilateral and contralateral uterine horns, genes related to the metabolic process were predominantly enriched in the RB cows when compared with non-RB cows. In the analysis of the whole uterus (combining the data above four endometrial compartments), RB cows showed up-regulation of 37 genes including PRSS2, GSTA3 and PIPOX and down-regulation of 39 genes including CHGA, KRT35 and THBS4 when compared with non-RB cows. Immunohistochemistry revealed that CHGA, GSTA3 and PRSS2 proteins were localized in luminal and glandular epithelial cells and stroma of the endometrium. The present study showed that endometrial gene expression profiles are different between RB and non-RB cows. The identified candidate endometrial genes and functions in each endometrial compartment may contribute to bovine reproductive performance.

Multiway real-time PCR gene expression profiling in yeast Saccharomyces cerevisiae reveals altered transcriptional response of ADH-genes to glucose stimuli.

PubMed

Ståhlberg, Anders; Elbing, Karin; Andrade-Garda, José Manuel; Sjögreen, Björn; Forootan, Amin; Kubista, Mikael

2008-04-16

The large sensitivity, high reproducibility and essentially unlimited dynamic range of real-time PCR to measure gene expression in complex samples provides the opportunity for powerful multivariate and multiway studies of biological phenomena. In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc. Here we perform a multiway study of the temporal response of four yeast Saccharomyces cerevisiae strains with different glucose uptake rates upon altered metabolic conditions. We measured the expression of 18 genes as function of time after addition of glucose to four strains of yeast grown in ethanol. The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map. Our approach identifies gene groups that respond similarly to the change of nutrient, and genes that behave differently in mutant strains. Of particular interest is our finding that ADH4 and ADH6 show a behavior typical of glucose-induced genes, while ADH3 and ADH5 are repressed after glucose addition. Multiway real-time PCR gene expression profiling is a powerful technique which can be utilized to characterize functions of new genes by, for example, comparing their temporal response after perturbation in different genetic variants of the studied subject. The technique also identifies genes that show perturbed expression in specific strains.

Multiway real-time PCR gene expression profiling in yeast Saccharomyces cerevisiae reveals altered transcriptional response of ADH-genes to glucose stimuli

PubMed Central

Ståhlberg, Anders; Elbing, Karin; Andrade-Garda, José Manuel; Sjögreen, Björn; Forootan, Amin; Kubista, Mikael

2008-01-01

Background The large sensitivity, high reproducibility and essentially unlimited dynamic range of real-time PCR to measure gene expression in complex samples provides the opportunity for powerful multivariate and multiway studies of biological phenomena. In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc. Here we perform a multiway study of the temporal response of four yeast Saccharomyces cerevisiae strains with different glucose uptake rates upon altered metabolic conditions. Results We measured the expression of 18 genes as function of time after addition of glucose to four strains of yeast grown in ethanol. The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map. Our approach identifies gene groups that respond similarly to the change of nutrient, and genes that behave differently in mutant strains. Of particular interest is our finding that ADH4 and ADH6 show a behavior typical of glucose-induced genes, while ADH3 and ADH5 are repressed after glucose addition. Conclusion Multiway real-time PCR gene expression profiling is a powerful technique which can be utilized to characterize functions of new genes by, for example, comparing their temporal response after perturbation in different genetic variants of the studied subject. The technique also identifies genes that show perturbed expression in specific strains. PMID:18412983

Impact of Profiling Technologies in the Understanding of Recombinant Protein Production

NASA Astrophysics Data System (ADS)

Vijayendran, Chandran; Flaschel, Erwin

Since expression profiling methods have been available in a high throughput fashion, the implication of these technologies in the field of biotechnology has increased dramatically. Microarray technology is one such unique and efficient methodology for simultaneous exploration of expression levels of numerous genes. Likewise, two-dimensional gel electrophoresis or multidimensional liquid chromatography coupled with mass spectrometry are extensively utilised for studying expression levels of numerous proteins. In the field of biotechnology these highly parallel analytical methods have paved the way to study and understand various biological phenomena depending on expression patterns. The next phenomenological level is represented by the metabolome and the (metabolic) fluxome. However, this chapter reviews gene and protein profiling and their impact on understanding recombinant protein production. We focus on the computational methods utilised for the analyses of data obtained from these profiling technologies as well as prominent results focusing on recombinant protein expression with Escherichia coli. Owing to the knowledge accumulated with respect to cellular signals triggered during recombinant protein production, this field is on the way to design strategies for developing improved processes. Both gene and protein profiling have exhibited a handful of functional categories to concentrate on in order to identify target genes and proteins, respectively, involved in the signalling network with major impact on recombinant protein production.

mRNA Expression Profiling of Laser Microbeam Microdissected Cells from Slender Embryonic Structures

PubMed Central

Scheidl, Stefan J.; Nilsson, Sven; Kalén, Mattias; Hellström, Mats; Takemoto, Minoru; Håkansson, Joakim; Lindahl, Per

2002-01-01

Microarray hybridization has rapidly evolved as an important tool for genomic studies and studies of gene regulation at the transcriptome level. Expression profiles from homogenous samples such as yeast and mammalian cell cultures are currently extending our understanding of biology, whereas analyses of multicellular organisms are more difficult because of tissue complexity. The combination of laser microdissection, RNA amplification, and microarray hybridization has the potential to provide expression profiles from selected populations of cells in vivo. In this article, we present and evaluate an experimental procedure for global gene expression analysis of slender embryonic structures using laser microbeam microdissection and laser pressure catapulting. As a proof of principle, expression profiles from 1000 cells in the mouse embryonic (E9.5) dorsal aorta were generated and compared with profiles for captured mesenchymal cells located one cell diameter further away from the aortic lumen. A number of genes were overexpressed in the aorta, including 11 previously known markers for blood vessels. Among the blood vessel markers were endoglin, tie-2, PDGFB, and integrin-β1, that are important regulators of blood vessel formation. This demonstrates that microarray analysis of laser microbeam micro-dissected cells is sufficiently sensitive for identifying genes with regulative functions. PMID:11891179

Expression of pathogenicity-related genes of Xylella fastidiosa in vitro and in planta.

PubMed

de Souza, Alessandra A; Takita, Marco A; Pereira, Eridan O; Coletta-Filho, Helvécio D; Machado, Marcos A

2005-04-01

Xylella fastidiosa is responsible for several economically important plant diseases. It is currently assumed that the symptoms are caused by vascular occlusion due to biofilm formation. Microarray technology was previously used to examine the global gene expression profile of X. fastidiosa freshly isolated from symptomatic plants or after several passages by axenic culture medium, and different pathogenicity profiles have been obtained. In the present study the expression of some pathogenicity-related genes was evaluated in vitro and in planta by RT-PCR. The results suggest that adhesion is important at the beginning of biofilm formation, while the genes related to adaptation are essential for the organism's maintenance in planta. Similar results were observed in vitro mainly for the adhesion genes. The pattern of expression observed suggests that adhesion modulates biofilm formation whereas the expression of some adaptation genes may be related to the environment in which the organism is living.

Analysis of gene expression profile induced by EMP-1 in esophageal cancer cells using cDNA Microarray

PubMed Central

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

Analysis of gene expression profile induced by EMP-1 in esophageal cancer cells using cDNA Microarray.

PubMed

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.

Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling

PubMed Central

Fang, H; Tong, W; Perkins, R; Shi, L; Hong, H; Cao, X; Xie, Q; Yim, SH; Ward, JM; Pitot, HC; Dragan, YP

2005-01-01

Background The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in animal models. These types of studies have the potential to greatly enhance our understanding of diseases such as liver cancer in humans. Genes co-expressed across multiple species are most likely to have conserved functions. We have used various bioinformatics approaches to examine microarray expression profiles from liver neoplasms that arise in albumin-SV40 transgenic rats to elucidate genes, chromosome aberrations and pathways that might be associated with human liver cancer. Results In this study, we first identified 2223 differentially expressed genes by comparing gene expression profiles for two control, two adenoma and two carcinoma samples using an F-test. These genes were subsequently mapped to the rat chromosomes using a novel visualization tool, the Chromosome Plot. Using the same plot, we further mapped the significant genes to orthologous chromosomal locations in human and mouse. Many genes expressed in rat 1q that are amplified in rat liver cancer map to the human chromosomes 10, 11 and 19 and to the mouse chromosomes 7, 17 and 19, which have been implicated in studies of human and mouse liver cancer. Using Comparative Genomics Microarray Analysis (CGMA), we identified regions of potential aberrations in human. Lastly, a pathway analysis was conducted to predict altered human pathways based on statistical analysis and extrapolation from the rat data. All of the identified pathways have been known to be important in the etiology of human liver cancer, including cell cycle control, cell growth and differentiation, apoptosis, transcriptional regulation, and protein metabolism. Conclusion The study demonstrates that the hepatic gene expression profiles from the albumin-SV40 transgenic rat model revealed genes, pathways and chromosome alterations consistent with experimental and clinical research in human liver cancer. The bioinformatics tools presented in this paper are essential for cross species extrapolation and mapping of microarray data, its analysis and interpretation. PMID:16026603

PROSPECT improves cis-acting regulatory element prediction by integrating expression profile data with consensus pattern searches

PubMed Central

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

From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.

PubMed

Chen, Yunshun; Lun, Aaron T L; Smyth, Gordon K

2016-01-01

In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims of RNA-seq profiling is to identify genes or molecular pathways that are differentially expressed (DE) between two or more biological conditions. This article demonstrates a computational workflow for the detection of DE genes and pathways from RNA-seq data by providing a complete analysis of an RNA-seq experiment profiling epithelial cell subsets in the mouse mammary gland. The workflow uses R software packages from the open-source Bioconductor project and covers all steps of the analysis pipeline, including alignment of read sequences, data exploration, differential expression analysis, visualization and pathway analysis. Read alignment and count quantification is conducted using the Rsubread package and the statistical analyses are performed using the edgeR package. The differential expression analysis uses the quasi-likelihood functionality of edgeR.

Mining the archives: a cross-platform analysis of gene ...

EPA Pesticide Factsheets

Formalin-fixed paraffin-embedded (FFPE) tissue samples represent a potentially invaluable resource for genomic research into the molecular basis of disease. However, use of FFPE samples in gene expression studies has been limited by technical challenges resulting from degradation of nucleic acids. Here we evaluated gene expression profiles derived from fresh-frozen (FRO) and FFPE mouse liver tissues using two DNA microarray protocols and two whole transcriptome sequencing (RNA-seq) library preparation methodologies. The ribo-depletion protocol outperformed the other three methods by having the highest correlations of differentially expressed genes (DEGs) and best overlap of pathways between FRO and FFPE groups. We next tested the effect of sample time in formalin (18 hours or 3 weeks) on gene expression profiles. Hierarchical clustering of the datasets indicated that test article treatment, and not preservation method, was the main driver of gene expression profiles. Meta- and pathway analyses indicated that biological responses were generally consistent for 18-hour and 3-week FFPE samples compared to FRO samples. However, clear erosion of signal intensity with time in formalin was evident, and DEG numbers differed by platform and preservation method. Lastly, we investigated the effect of age in FFPE block on genomic profiles. RNA-seq analysis of 8-, 19-, and 26-year-old control blocks using the ribo-depletion protocol resulted in comparable quality metrics, inc

Reciprocal changes in gene expression profiles of cocultured breast epithelial cells and primary fibroblasts.

PubMed

Rozenchan, Patricia Bortman; Carraro, Dirce Maria; Brentani, Helena; de Carvalho Mota, Louise Danielle; Bastos, Elen Pereira; e Ferreira, Elisa Napolitano; Torres, Cesar H; Katayama, Maria Lúcia Hirata; Roela, Rosimeire Aparecida; Lyra, Eduardo C; Soares, Fernando Augusto; Folgueira, Maria Aparecida Azevedo Koike; Góes, João Carlos Guedes Sampaio; Brentani, Maria Mitzi

2009-12-15

The importance of epithelial-stroma interaction in normal breast development and tumor progression has been recognized. To identify genes that were regulated by these reciprocal interactions, we cocultured a nonmalignant (MCF10A) and a breast cancer derived (MDA-MB231) basal cell lines, with fibroblasts isolated from breast benign-disease adjacent tissues (NAF) or with carcinoma-associated fibroblasts (CAF), in a transwell system. Gene expression profiles of each coculture pair were compared with the correspondent monocultures, using a customized microarray. Contrariwise to large alterations in epithelial cells genomic profiles, fibroblasts were less affected. In MDA-MB231 highly represented genes downregulated by CAF derived factors coded for proteins important for the specificity of vectorial transport between ER and golgi, possibly affecting cell polarity whereas the response of MCF10A comprised an induction of genes coding for stress responsive proteins, representing a prosurvival effect. While NAF downregulated genes encoding proteins associated to glycolipid and fatty acid biosynthesis in MDA-MB231, potentially affecting membrane biogenesis, in MCF10A, genes critical for growth control and adhesion were altered. NAFs responded to coculture with MDA-MB231 by a decrease in the expression of genes induced by TGFbeta1 and associated to motility. However, there was little change in NAFs gene expression profile influenced by MCF10A. CAFs responded to the presence of both epithelial cells inducing genes implicated in cell proliferation. Our data indicate that interactions between breast fibroblasts and basal epithelial cells resulted in alterations in the genomic profiles of both cell types which may help to clarify some aspects of this heterotypic signaling. Copyright (c) 2009 UICC.

Development and validation of a gene profile predicting benefit of postmastectomy radiotherapy in patients with high-risk breast cancer: a study of gene expression in the DBCG82bc cohort.

PubMed

Tramm, Trine; Mohammed, Hayat; Myhre, Simen; Kyndi, Marianne; Alsner, Jan; Børresen-Dale, Anne-Lise; Sørlie, Therese; Frigessi, Arnoldo; Overgaard, Jens

2014-10-15

To identify genes predicting benefit of radiotherapy in patients with high-risk breast cancer treated with systemic therapy and randomized to receive or not receive postmastectomy radiotherapy (PMRT). The study was based on the Danish Breast Cancer Cooperative Group (DBCG82bc) cohort. Gene-expression analysis was performed in a training set of frozen tumor tissue from 191 patients. Genes were identified through the Lasso method with the endpoint being locoregional recurrence (LRR). A weighted gene-expression index (DBCG-RT profile) was calculated and transferred to quantitative real-time PCR (qRT-PCR) in corresponding formalin-fixed, paraffin-embedded (FFPE) samples, before validation in FFPE from 112 additional patients. Seven genes were identified, and the derived DBCG-RT profile divided the 191 patients into "high LRR risk" and "low LRR risk" groups. PMRT significantly reduced risk of LRR in "high LRR risk" patients, whereas "low LRR risk" patients showed no additional reduction in LRR rate. Technical transfer of the DBCG-RT profile to FFPE/qRT-PCR was successful, and the predictive impact was successfully validated in another 112 patients. A DBCG-RT gene profile was identified and validated, identifying patients with very low risk of LRR and no benefit from PMRT. The profile may provide a method to individualize treatment with PMRT. ©2014 American Association for Cancer Research.

Identification of key microRNAs and genes in preeclampsia by bioinformatics analysis

PubMed Central

Luo, Shouling; Cao, Nannan; Tang, Yao; Gu, Weirong

2017-01-01

Preeclampsia is a leading cause of perinatal maternal–foetal mortality and morbidity. The aim of this study is to identify the key microRNAs and genes in preeclampsia and uncover their potential functions. We downloaded the miRNA expression profile of GSE84260 and the gene expression profile of GSE73374 from the Gene Expression Omnibus database. Differentially expressed miRNAs and genes were identified and compared to miRNA-target information from MiRWalk 2.0, and a total of 65 differentially expressed miRNAs (DEMIs), including 32 up-regulated miRNAs and 33 down-regulated miRNAs, and 91 differentially expressed genes (DEGs), including 83 up-regulated genes and 8 down-regulated genes, were identified. The pathway enrichment analyses of the DEMIs showed that the up-regulated DEMIs were enriched in the Hippo signalling pathway and MAPK signalling pathway, and the down-regulated DEMIs were enriched in HTLV-I infection and miRNAs in cancers. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses of the DEGs were performed using Multifaceted Analysis Tool for Human Transcriptome. The up-regulated DEGs were enriched in biological processes (BPs), including the response to cAMP, response to hydrogen peroxide and cell-cell adhesion mediated by integrin; no enrichment of down-regulated DEGs was identified. KEGG analysis showed that the up-regulated DEGs were enriched in the Hippo signalling pathway and pathways in cancer. A PPI network of the DEGs was constructed by using Cytoscape software, and FOS, STAT1, MMP14, ITGB1, VCAN, DUSP1, LDHA, MCL1, MET, and ZFP36 were identified as the hub genes. The current study illustrates a characteristic microRNA profile and gene profile in preeclampsia, which may contribute to the interpretation of the progression of preeclampsia and provide novel biomarkers and therapeutic targets for preeclampsia. PMID:28594854

Identification of Reference Genes for Quantitative Gene Expression Studies in a Non-Model Tree Pistachio (Pistacia vera L.)

PubMed Central

Moazzam Jazi, Maryam; Ghadirzadeh Khorzoghi, Effat; Botanga, Christopher; Seyedi, Seyed Mahdi

2016-01-01

The tree species, Pistacia vera (P. vera) is an important commercial product that is salt-tolerant and long-lived, with a possible lifespan of over one thousand years. Gene expression analysis is an efficient method to explore the possible regulatory mechanisms underlying these characteristics. Therefore, having the most suitable set of reference genes is required for transcript level normalization under different conditions in P. vera. In the present study, we selected eight widely used reference genes, ACT, EF1α, α-TUB, β-TUB, GAPDH, CYP2, UBQ10, and 18S rRNA. Using qRT-PCR their expression was assessed in 54 different samples of three cultivars of P. vera. The samples were collected from different organs under various abiotic treatments (cold, drought, and salt) across three time points. Several statistical programs (geNorm, NormFinder, and BestKeeper) were applied to estimate the expression stability of candidate reference genes. Results obtained from the statistical analysis were then exposed to Rank aggregation package to generate a consensus gene rank. Based on our results, EF1α was found to be the superior reference gene in all samples under all abiotic treatments. In addition to EF1α, ACT and β-TUB were the second best reference genes for gene expression analysis in leaf and root. We recommended β-TUB as the second most stable gene for samples under the cold and drought treatments, while ACT holds the same position in samples analyzed under salt treatment. This report will benefit future research on the expression profiling of P. vera and other members of the Anacardiaceae family. PMID:27308855

Identification of Reference Genes for Quantitative Gene Expression Studies in a Non-Model Tree Pistachio (Pistacia vera L.).

PubMed

Moazzam Jazi, Maryam; Ghadirzadeh Khorzoghi, Effat; Botanga, Christopher; Seyedi, Seyed Mahdi

2016-01-01

The tree species, Pistacia vera (P. vera) is an important commercial product that is salt-tolerant and long-lived, with a possible lifespan of over one thousand years. Gene expression analysis is an efficient method to explore the possible regulatory mechanisms underlying these characteristics. Therefore, having the most suitable set of reference genes is required for transcript level normalization under different conditions in P. vera. In the present study, we selected eight widely used reference genes, ACT, EF1α, α-TUB, β-TUB, GAPDH, CYP2, UBQ10, and 18S rRNA. Using qRT-PCR their expression was assessed in 54 different samples of three cultivars of P. vera. The samples were collected from different organs under various abiotic treatments (cold, drought, and salt) across three time points. Several statistical programs (geNorm, NormFinder, and BestKeeper) were applied to estimate the expression stability of candidate reference genes. Results obtained from the statistical analysis were then exposed to Rank aggregation package to generate a consensus gene rank. Based on our results, EF1α was found to be the superior reference gene in all samples under all abiotic treatments. In addition to EF1α, ACT and β-TUB were the second best reference genes for gene expression analysis in leaf and root. We recommended β-TUB as the second most stable gene for samples under the cold and drought treatments, while ACT holds the same position in samples analyzed under salt treatment. This report will benefit future research on the expression profiling of P. vera and other members of the Anacardiaceae family.

dbMDEGA: a database for meta-analysis of differentially expressed genes in autism spectrum disorder.

PubMed

Zhang, Shuyun; Deng, Libin; Jia, Qiyue; Huang, Shaoting; Gu, Junwang; Zhou, Fankun; Gao, Meng; Sun, Xinyi; Feng, Chang; Fan, Guangqin

2017-11-16

Autism spectrum disorders (ASD) are hereditary, heterogeneous and biologically complex neurodevelopmental disorders. Individual studies on gene expression in ASD cannot provide clear consensus conclusions. Therefore, a systematic review to synthesize the current findings from brain tissues and a search tool to share the meta-analysis results are urgently needed. Here, we conducted a meta-analysis of brain gene expression profiles in the current reported human ASD expression datasets (with 84 frozen male cortex samples, 17 female cortex samples, 32 cerebellum samples and 4 formalin fixed samples) and knock-out mouse ASD model expression datasets (with 80 collective brain samples). Then, we applied R language software and developed an interactive shared and updated database (dbMDEGA) displaying the results of meta-analysis of data from ASD studies regarding differentially expressed genes (DEGs) in the brain. This database, dbMDEGA ( https://dbmdega.shinyapps.io/dbMDEGA/ ), is a publicly available web-portal for manual annotation and visualization of DEGs in the brain from data from ASD studies. This database uniquely presents meta-analysis values and homologous forest plots of DEGs in brain tissues. Gene entries are annotated with meta-values, statistical values and forest plots of DEGs in brain samples. This database aims to provide searchable meta-analysis results based on the current reported brain gene expression datasets of ASD to help detect candidate genes underlying this disorder. This new analytical tool may provide valuable assistance in the discovery of DEGs and the elucidation of the molecular pathogenicity of ASD. This database model may be replicated to study other disorders.

Effects of Simulated Microgravity on the Expression Profile of Microrna in Human Lymphoblastoid Cells

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.

Comparative Transcriptional Profiling of the Axolotl Limb Identifies a Tripartite Regeneration-Specific Gene Program

PubMed Central

Knapp, Dunja; Schulz, Herbert; Rascon, Cynthia Alexander; Volkmer, Michael; Scholz, Juliane; Nacu, Eugen; Le, Mu; Novozhilov, Sergey; Tazaki, Akira; Protze, Stephanie; Jacob, Tina; Hubner, Norbert; Habermann, Bianca; Tanaka, Elly M.

2013-01-01

Understanding how the limb blastema is established after the initial wound healing response is an important aspect of regeneration research. Here we performed parallel expression profile time courses of healing lateral wounds versus amputated limbs in axolotl. This comparison between wound healing and regeneration allowed us to identify amputation-specific genes. By clustering the expression profiles of these samples, we could detect three distinguishable phases of gene expression – early wound healing followed by a transition-phase leading to establishment of the limb development program, which correspond to the three phases of limb regeneration that had been defined by morphological criteria. By focusing on the transition-phase, we identified 93 strictly amputation-associated genes many of which are implicated in oxidative-stress response, chromatin modification, epithelial development or limb development. We further classified the genes based on whether they were or were not significantly expressed in the developing limb bud. The specific localization of 53 selected candidates within the blastema was investigated by in situ hybridization. In summary, we identified a set of genes that are expressed specifically during regeneration and are therefore, likely candidates for the regulation of blastema formation. PMID:23658691

Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis.

PubMed

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.

Xenopus microRNA genes are predominantly located within introns and are differentially expressed in adult frog tissues via post-transcriptional regulation

PubMed Central

Tang, Guo-Qing; Maxwell, E. Stuart

2008-01-01

The amphibian Xenopus provides a model organism for investigating microRNA expression during vertebrate embryogenesis and development. Searching available Xenopus genome databases using known human pre-miRNAs as query sequences, more than 300 genes encoding 142 Xenopus tropicalis miRNAs were identified. Analysis of Xenopus tropicalis miRNA genes revealed a predominate positioning within introns of protein-coding and nonprotein-coding RNA Pol II-transcribed genes. MiRNA genes were also located in pre-mRNA exons and positioned intergenically between known protein-coding genes. Many miRNA species were found in multiple locations and in more than one genomic context. MiRNA genes were also clustered throughout the genome, indicating the potential for the cotranscription and coordinate expression of miRNAs located in a given cluster. Northern blot analysis confirmed the expression of many identified miRNAs in both X. tropicalis and X. laevis. Comparison of X. tropicalis and X. laevis blots revealed comparable expression profiles, although several miRNAs exhibited species-specific expression in different tissues. More detailed analysis revealed that for some miRNAs, the tissue-specific expression profile of the pri-miRNA precursor was distinctly different from that of the mature miRNA profile. Differential miRNA precursor processing in both the nucleus and cytoplasm was implicated in the observed tissue-specific differences. These observations indicated that post-transcriptional processing plays an important role in regulating miRNA expression in the amphibian Xenopus. PMID:18032731

Transcriptional maturation of the mouse auditory forebrain.

PubMed

Hackett, Troy A; Guo, Yan; Clause, Amanda; Hackett, Nicholas J; Garbett, Krassimira; Zhang, Pan; Polley, Daniel B; Mirnics, Karoly

2015-08-14

The maturation of the brain involves the coordinated expression of thousands of genes, proteins and regulatory elements over time. In sensory pathways, gene expression profiles are modified by age and sensory experience in a manner that differs between brain regions and cell types. In the auditory system of altricial animals, neuronal activity increases markedly after the opening of the ear canals, initiating events that culminate in the maturation of auditory circuitry in the brain. This window provides a unique opportunity to study how gene expression patterns are modified by the onset of sensory experience through maturity. As a tool for capturing these features, next-generation sequencing of total RNA (RNAseq) has tremendous utility, because the entire transcriptome can be screened to index expression of any gene. To date, whole transcriptome profiles have not been generated for any central auditory structure in any species at any age. In the present study, RNAseq was used to profile two regions of the mouse auditory forebrain (A1, primary auditory cortex; MG, medial geniculate) at key stages of postnatal development (P7, P14, P21, adult) before and after the onset of hearing (~P12). Hierarchical clustering, differential expression, and functional geneset enrichment analyses (GSEA) were used to profile the expression patterns of all genes. Selected genesets related to neurotransmission, developmental plasticity, critical periods and brain structure were highlighted. An accessible repository of the entire dataset was also constructed that permits extraction and screening of all data from the global through single-gene levels. To our knowledge, this is the first whole transcriptome sequencing study of the forebrain of any mammalian sensory system. Although the data are most relevant for the auditory system, they are generally applicable to forebrain structures in the visual and somatosensory systems, as well. The main findings were: (1) Global gene expression patterns were tightly clustered by postnatal age and brain region; (2) comparing A1 and MG, the total numbers of differentially expressed genes were comparable from P7 to P21, then dropped to nearly half by adulthood; (3) comparing successive age groups, the greatest numbers of differentially expressed genes were found between P7 and P14 in both regions, followed by a steady decline in numbers with age; (4) maturational trajectories in expression levels varied at the single gene level (increasing, decreasing, static, other); (5) between regions, the profiles of single genes were often asymmetric; (6) GSEA revealed that genesets related to neural activity and plasticity were typically upregulated from P7 to adult, while those related to structure tended to be downregulated; (7) GSEA and pathways analysis of selected functional networks were not predictive of expression patterns in the auditory forebrain for all genes, reflecting regional specificity at the single gene level. Gene expression in the auditory forebrain during postnatal development is in constant flux and becomes increasingly stable with age. Maturational changes are evident at the global through single gene levels. Transcriptome profiles in A1 and MG are distinct at all ages, and differ from other brain regions. The database generated by this study provides a rich foundation for the identification of novel developmental biomarkers, functional gene pathways, and targeted studies of postnatal maturation in the auditory forebrain.

The DNA methylation profile of liver tumors in C3H mice and identification of differentially methylated regions involved in the regulation of tumorigenic genes.

PubMed

Matsushita, Junya; Okamura, Kazuyuki; Nakabayashi, Kazuhiko; Suzuki, Takehiro; Horibe, Yu; Kawai, Tomoko; Sakurai, Toshihiro; Yamashita, Satoshi; Higami, Yoshikazu; Ichihara, Gaku; Hata, Kenichiro; Nohara, Keiko

2018-03-22

C3H mice have been frequently used in cancer studies as animal models of spontaneous liver tumors and chemically induced hepatocellular carcinoma (HCC). Epigenetic modifications, including DNA methylation, are among pivotal control mechanisms of gene expression leading to carcinogenesis. Although information on somatic mutations in liver tumors of C3H mice is available, epigenetic aspects are yet to be clarified. We performed next generation sequencing-based analysis of DNA methylation and microarray analysis of gene expression to explore genes regulated by DNA methylation in spontaneous liver tumors of C3H mice. Overlaying these data, we selected cancer-related genes whose expressions are inversely correlated with DNA methylation levels in the associated differentially methylated regions (DMRs) located around transcription start sites (TSSs) (promoter DMRs). We further assessed mutuality of the selected genes for expression and DNA methylation in human HCC using the Cancer Genome Atlas (TCGA) database. We obtained data on genome-wide DNA methylation profiles in the normal and tumor livers of C3H mice. We identified promoter DMRs of genes which are reported to be related to cancer and whose expressions are inversely correlated with the DNA methylation, including Mst1r, Slpi and Extl1. The association between DNA methylation and gene expression was confirmed using a DNA methylation inhibitor 5-aza-2'-deoxycytidine (5-aza-dC) in Hepa1c1c7 cells and Hepa1-6 cells. Overexpression of Mst1r in Hepa1c1c7 cells illuminated a novel downstream pathway via IL-33 upregulation. Database search indicated that gene expressions of Mst1r and Slpi are upregulated and the TSS upstream regions are hypomethylated also in human HCC. These results suggest that DMRs, including those of Mst1r and Slpi, are involved in liver tumorigenesis in C3H mice, and also possibly in human HCC. Our study clarified genome wide DNA methylation landscape of C3H mice. The data provide useful information for further epigenetic studies of mice models of HCC. The present study particularly proposed novel DNA methylation-regulated pathways for Mst1r and Slpi, which may be applied not only to mouse HCC but also to human HCC.

Murine Hyperglycemic Vasculopathy and Cardiomyopathy: Whole-Genome Gene Expression Analysis Predicts Cellular Targets and Regulatory Networks Influenced by Mannose Binding Lectin

PubMed Central

Zou, Chenhui; La Bonte, Laura R.; Pavlov, Vasile I.; Stahl, Gregory L.

2012-01-01

Hyperglycemia, in the absence of type 1 or 2 diabetes, is an independent risk factor for cardiovascular disease. We have previously demonstrated a central role for mannose binding lectin (MBL)-mediated cardiac dysfunction in acute hyperglycemic mice. In this study, we applied whole-genome microarray data analysis to investigate MBL’s role in systematic gene expression changes. The data predict possible intracellular events taking place in multiple cellular compartments such as enhanced insulin signaling pathway sensitivity, promoted mitochondrial respiratory function, improved cellular energy expenditure and protein quality control, improved cytoskeleton structure, and facilitated intracellular trafficking, all of which may contribute to the organismal health of MBL null mice against acute hyperglycemia. Our data show a tight association between gene expression profile and tissue function which might be a very useful tool in predicting cellular targets and regulatory networks connected with in vivo observations, providing clues for further mechanistic studies. PMID:22375142

A Dynamic Bronchial Airway Gene Expression Signature of Chronic Obstructive Pulmonary Disease and Lung Function Impairment

PubMed Central

Steiling, Katrina; van den Berge, Maarten; Hijazi, Kahkeshan; Florido, Roberta; Campbell, Joshua; Liu, Gang; Xiao, Ji; Zhang, Xiaohui; Duclos, Grant; Drizik, Eduard; Si, Huiqing; Perdomo, Catalina; Dumont, Charles; Coxson, Harvey O.; Alekseyev, Yuriy O.; Sin, Don; Pare, Peter; Hogg, James C.; McWilliams, Annette; Hiemstra, Pieter S.; Sterk, Peter J.; Timens, Wim; Chang, Jeffrey T.; Sebastiani, Paola; O’Connor, George T.; Bild, Andrea H.; Postma, Dirkje S.; Lam, Stephen

2013-01-01

Rationale: Molecular phenotyping of chronic obstructive pulmonary disease (COPD) has been impeded in part by the difficulty in obtaining lung tissue samples from individuals with impaired lung function. Objectives: We sought to determine whether COPD-associated processes are reflected in gene expression profiles of bronchial airway epithelial cells obtained by bronchoscopy. Methods: Gene expression profiling of bronchial brushings obtained from 238 current and former smokers with and without COPD was performed using Affymetrix Human Gene 1.0 ST Arrays. Measurements and Main Results: We identified 98 genes whose expression levels were associated with COPD status, FEV1% predicted, and FEV1/FVC. In silico analysis identified activating transcription factor 4 (ATF4) as a potential transcriptional regulator of genes with COPD-associated airway expression, and ATF4 overexpression in airway epithelial cells in vitro recapitulates COPD-associated gene expression changes. Genes with COPD-associated expression in the bronchial airway epithelium had similarly altered expression profiles in prior studies performed on small-airway epithelium and lung parenchyma, suggesting that transcriptomic alterations in the bronchial airway epithelium reflect molecular events found at more distal sites of disease activity. Many of the airway COPD-associated gene expression changes revert toward baseline after therapy with the inhaled corticosteroid fluticasone in independent cohorts. Conclusions: Our findings demonstrate a molecular field of injury throughout the bronchial airway of active and former smokers with COPD that may be driven in part by ATF4 and is modifiable with therapy. Bronchial airway epithelium may ultimately serve as a relatively accessible tissue in which to measure biomarkers of disease activity for guiding clinical management of COPD. PMID:23471465

Transcriptome analysis and gene expression profiling of abortive and developing ovules during fruit development in hazelnut.

PubMed

Cheng, Yunqing; Liu, Jianfeng; Zhang, Huidi; Wang, Ju; Zhao, Yixin; Geng, Wanting

2015-01-01

A high ratio of blank fruit in hazelnut (Corylus heterophylla Fisch) is a very common phenomenon that causes serious yield losses in northeast China. The development of blank fruit in the Corylus genus is known to be associated with embryo abortion. However, little is known about the molecular mechanisms responsible for embryo abortion during the nut development stage. Genomic information for C. heterophylla Fisch is not available; therefore, data related to transcriptome and gene expression profiling of developing and abortive ovules are needed. In this study, de novo transcriptome sequencing and RNA-seq analysis were conducted using short-read sequencing technology (Illumina HiSeq 2000). The results of the transcriptome assembly analysis revealed genetic information that was associated with the fruit development stage. Two digital gene expression libraries were constructed, one for a full (normally developing) ovule and one for an empty (abortive) ovule. Transcriptome sequencing and assembly results revealed 55,353 unigenes, including 18,751 clusters and 36,602 singletons. These results were annotated using the public databases NR, NT, Swiss-Prot, KEGG, COG, and GO. Using digital gene expression profiling, gene expression differences in developing and abortive ovules were identified. A total of 1,637 and 715 unigenes were significantly upregulated and downregulated, respectively, in abortive ovules, compared with developing ovules. Quantitative real-time polymerase chain reaction analysis was used in order to verify the differential expression of some genes. The transcriptome and digital gene expression profiling data of normally developing and abortive ovules in hazelnut provide exhaustive information that will improve our understanding of the molecular mechanisms of abortive ovule formation in hazelnut.

Transient gene and microRNA expression profile changes of confluent human fibroblast cells in space

NASA Astrophysics Data System (ADS)

Wu, Honglu; Story, Michael; Karouia, Fathi; Stodieck, Louis; Zhang, Ye; Lu, Tao

2016-07-01

Microgravity, or an altered gravity environment from the Earth1g, has been shown to influence global gene expression patterns and protein levels in cultured cells. However, most of the reported studies conducted in space or using simulated microgravity on the ground have focused on the growth or differentiation of these cells. Whether non-proliferating cultured cells will sense the presence of microgravity in space has not been specifically addressed. In an experiment conducted onboard the International Space Station (ISS), confluent human fibroblast cells were fixed after being cultured in space for 3 and 14 days, respectively, for investigations of gene and miRNA expression profile changes in these cells. Results of the experiment showed that on Day 3, both the flown and ground cells were still proliferating slowly, as measured by the percentage of Ki-67 positive cells. Gene and miRNA expression data indicated activation of NFkB and other growth related pathways involving HGF and Vegf along with down regulation of the Let-7 miRNA family. On Day 14 when the cells were mostly non-proliferating, the gene and miRNA expression profiles between the flight and ground samples were indistinguishable. Comparison of gene and miRNA expressions in the Day 3 samples with respect to Day 14 revealed that most of the changes observed on Day 3 were related to cell growth for both the flown and ground cells. Analysis of cytoskeletal changes via immunohistochemistry staining of the cells with antibodies for αa-tubulin and fibronectin showed no difference between flown and ground samples. Taken together, our study suggests that in true non-dividing human fibroblast cells in culture, microgravity experienced in space has little effect on the gene and miRNA expression profiles.

Fundamental limits on dynamic inference from single-cell snapshots

PubMed Central

Weinreb, Caleb; Tusi, Betsabeh K.; Socolovsky, Merav

2018-01-01

Single-cell expression profiling reveals the molecular states of individual cells with unprecedented detail. Because these methods destroy cells in the process of analysis, they cannot measure how gene expression changes over time. However, some information on dynamics is present in the data: the continuum of molecular states in the population can reflect the trajectory of a typical cell. Many methods for extracting single-cell dynamics from population data have been proposed. However, all such attempts face a common limitation: for any measured distribution of cell states, there are multiple dynamics that could give rise to it, and by extension, multiple possibilities for underlying mechanisms of gene regulation. Here, we describe the aspects of gene expression dynamics that cannot be inferred from a static snapshot alone and identify assumptions necessary to constrain a unique solution for cell dynamics from static snapshots. We translate these constraints into a practical algorithmic approach, population balance analysis (PBA), which makes use of a method from spectral graph theory to solve a class of high-dimensional differential equations. We use simulations to show the strengths and limitations of PBA, and then apply it to single-cell profiles of hematopoietic progenitor cells (HPCs). Cell state predictions from this analysis agree with HPC fate assays reported in several papers over the past two decades. By highlighting the fundamental limits on dynamic inference faced by any method, our framework provides a rigorous basis for dynamic interpretation of a gene expression continuum and clarifies best experimental designs for trajectory reconstruction from static snapshot measurements. PMID:29463712