miRvestigator: web application to identify miRNAs responsible for co-regulated gene expression patterns discovered through transcriptome profiling.

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Plaisier, Christopher L; Bare, J Christopher; Baliga, Nitin S

2011-07-01

Transcriptome profiling studies have produced staggering numbers of gene co-expression signatures for a variety of biological systems. A significant fraction of these signatures will be partially or fully explained by miRNA-mediated targeted transcript degradation. miRvestigator takes as input lists of co-expressed genes from Caenorhabditis elegans, Drosophila melanogaster, G. gallus, Homo sapiens, Mus musculus or Rattus norvegicus and identifies the specific miRNAs that are likely to bind to 3' un-translated region (UTR) sequences to mediate the observed co-regulation. The novelty of our approach is the miRvestigator hidden Markov model (HMM) algorithm which systematically computes a similarity P-value for each unique miRNA seed sequence from the miRNA database miRBase to an overrepresented sequence motif identified within the 3'-UTR of the query genes. We have made this miRNA discovery tool accessible to the community by integrating our HMM algorithm with a proven algorithm for de novo discovery of miRNA seed sequences and wrapping these algorithms into a user-friendly interface. Additionally, the miRvestigator web server also produces a list of putative miRNA binding sites within 3'-UTRs of the query transcripts to facilitate the design of validation experiments. The miRvestigator is freely available at http://mirvestigator.systemsbiology.net.

Array2BIO: from microarray expression data to functional annotation of co-regulated genes

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Rasley Amy

2006-06-01

Full Text Available Abstract Background There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. Results Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1 comparative analysis of signal versus control and (2 clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Crème allows prediction of gene regulatory elements that underlie observed expression patterns. Conclusion We have developed Array2BIO – a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to Dcode.org comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available at http://array2bio.dcode.org.

Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

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Borlawsky Tara B

2010-10-01

Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgVH mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgVH status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgVH mutational status which can accurately predict the survival outcome are yet to be discovered. Results In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgVH mutation status from the ZAP70 co-expression network. Conclusions We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgVH mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.

Co-expression network analysis of duplicate genes in maize (Zea mays L.) reveals no subgenome bias.

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Li, Lin; Briskine, Roman; Schaefer, Robert; Schnable, Patrick S; Myers, Chad L; Flagel, Lex E; Springer, Nathan M; Muehlbauer, Gary J

2016-11-04

Gene duplication is prevalent in many species and can result in coding and regulatory divergence. Gene duplications can be classified as whole genome duplication (WGD), tandem and inserted (non-syntenic). In maize, WGD resulted in the subgenomes maize1 and maize2, of which maize1 is considered the dominant subgenome. However, the landscape of co-expression network divergence of duplicate genes in maize is still largely uncharacterized. To address the consequence of gene duplication on co-expression network divergence, we developed a gene co-expression network from RNA-seq data derived from 64 different tissues/stages of the maize reference inbred-B73. WGD, tandem and inserted gene duplications exhibited distinct regulatory divergence. Inserted duplicate genes were more likely to be singletons in the co-expression networks, while WGD duplicate genes were likely to be co-expressed with other genes. Tandem duplicate genes were enriched in the co-expression pattern where co-expressed genes were nearly identical for the duplicates in the network. Older gene duplications exhibit more extensive co-expression variation than younger duplications. Overall, non-syntenic genes primarily from inserted duplications show more co-expression divergence. Also, such enlarged co-expression divergence is significantly related to duplication age. Moreover, subgenome dominance was not observed in the co-expression networks - maize1 and maize2 exhibit similar levels of intra subgenome correlations. Intriguingly, the level of inter subgenome co-expression was similar to the level of intra subgenome correlations, and genes from specific subgenomes were not likely to be the enriched in co-expression network modules and the hub genes were not predominantly from any specific subgenomes in maize. Our work provides a comprehensive analysis of maize co-expression network divergence for three different types of gene duplications and identifies potential relationships between duplication types

GeneCAT--novel webtools that combine BLAST and co-expression analyses

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Mutwil, Marek; Obro, Jens; Willats, William G T

2008-01-01

The gene co-expression analysis toolbox (GeneCAT) introduces several novel microarray data analyzing tools. First, the multigene co-expression analysis, combined with co-expressed gene networks, provides a more powerful data mining technique than standard, single-gene co-expression analysis. Second...... orthologs in the plant model organisms Arabidopsis thaliana and Hordeum vulgare (Barley). GeneCAT is equipped with expression data for the model plant A. thaliana, and first to introduce co-expression mining tools for the monocot Barley. GeneCAT is available at http://genecat.mpg.de....

Elucidating gene function and function evolution through comparison of co-expression networks in plants

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Marek eMutwil

2014-08-01

Full Text Available The analysis of gene expression data has shown that transcriptionally coordinated (co-expressed genes are often functionally related, enabling scientists to use expression data in gene function prediction. This Focused Review discusses our original paper (Large-scale co-expression approach to dissect secondary cell wall formation across plant species, Frontiers in Plant Science 2:23. In this paper we applied cross-species analysis to co-expression networks of genes involved in cellulose biosynthesis. We show that the co-expression networks from different species are highly similar, indicating that whole biological pathways are conserved across species. This finding has two important implications. First, the analysis can transfer gene function annotation from well-studied plants, such as Arabidopsis, to other, uncharacterized plant species. As the analysis finds genes that have similar sequence and similar expression pattern across different organisms, functionally equivalent genes can be identified. Second, since co-expression analyses are often noisy, a comparative analysis should have higher performance, as parts of co-expression networks that are conserved are more likely to be functionally relevant. In this Focused Review, we outline the comparative analysis done in the original paper and comment on the recent advances and approaches that allow comparative analyses of co-function networks. We hypothesize that, in comparison to simple co-expression analysis, comparative analysis would yield more accurate gene function predictions. Finally, by combining comparative analysis with genomic information of green plants, we propose a possible composition of cellulose biosynthesis machinery during earlier stages of plant evolution.

Expression profiling identifies genes involved in emphysema severity

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Bowman Rayleen V

2009-09-01

Full Text Available Abstract Chronic obstructive pulmonary disease (COPD is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients. Gene expression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressed genes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples. Class comparison identified 98 differentially expressed genes (p p Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3.

Co-expression analysis identifies CRC and AP1 the regulator of Arabidopsis fatty acid biosynthesis.

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Han, Xinxin; Yin, Linlin; Xue, Hongwei

2012-07-01

Fatty acids (FAs) play crucial rules in signal transduction and plant development, however, the regulation of FA metabolism is still poorly understood. To study the relevant regulatory network, fifty-eight FA biosynthesis genes including de novo synthases, desaturases and elongases were selected as "guide genes" to construct the co-expression network. Calculation of the correlation between all Arabidopsis thaliana (L.) genes with each guide gene by Arabidopsis co-expression dating mining tools (ACT) identifies 797 candidate FA-correlated genes. Gene ontology (GO) analysis of these co-expressed genes showed they are tightly correlated to photosynthesis and carbohydrate metabolism, and function in many processes. Interestingly, 63 transcription factors (TFs) were identified as candidate FA biosynthesis regulators and 8 TF families are enriched. Two TF genes, CRC and AP1, both correlating with 8 FA guide genes, were further characterized. Analyses of the ap1 and crc mutant showed the altered total FA composition of mature seeds. The contents of palmitoleic acid, stearic acid, arachidic acid and eicosadienoic acid are decreased, whereas that of oleic acid is increased in ap1 and crc seeds, which is consistent with the qRT-PCR analysis revealing the suppressed expression of the corresponding guide genes. In addition, yeast one-hybrid analysis and electrophoretic mobility shift assay (EMSA) revealed that CRC can bind to the promoter regions of KCS7 and KCS15, indicating that CRC may directly regulate FA biosynthesis. © 2012 Institute of Botany, Chinese Academy of Sciences.

A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes

DEFF Research Database (Denmark)

de Jong, Simone; Boks, Marco P M; Fuller, Tova F

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......, 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...

Disease gene characterization through large-scale co-expression analysis.

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Allen Day

2009-12-01

Full Text Available In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET.Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2 and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis.

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

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Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M

2013-12-16

Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis

Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysis

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Zhou X

2018-05-01

characterize the results of WGCNA.Results: Two gene modules (Gmagenta and Ggreen and one miRNA module were associated with the pathological stage. Six hub genes (COL1A2, THBS2, BGN, COL1A1, TAGLN and DACT3 were related to prognosis and validated to be associated with the pathological stage. Five hub miRNAs were identified to be related to prognosis (hsa-miR-125b-5p, hsa-miR-145-5p, hsa-let-7c-5p, hsa-miR-218-5p and hsa-miR-125b-2-3p. A total of 18 hub genes and seven hub miRNAs were predominantly expressed in tumor stroma. Proteoglycans in cancer, focal adhesion, extracellular matrix (ECM–receptor interaction and so on were common pathways of the three modules. Hsa-let-7c-5p was located at the core of miRNA–gene network.Conclusion: These findings help to advance the understanding of tumor stroma in the progression of CAC and provide prognostic biomarkers as well as therapeutic targets. Keywords: colon adenocarcinoma, weighted gene co-expression network analysis, differentially expressed genes, differentially expressed miRNA, tumor stroma

Co-Expression of Neighboring Genes in the Zebrafish (Danio rerio Genome

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Daryi Wang

2009-08-01

Full Text Available Neighboring genes in the eukaryotic genome have a tendency to express concurrently, and the proximity of two adjacent genes is often considered a possible explanation for their co-expression behavior. However, the actual contribution of the physical distance between two genes to their co-expression behavior has yet to be defined. To further investigate this issue, we studied the co-expression of neighboring genes in zebrafish, which has a compact genome and has experienced a whole genome duplication event. Our analysis shows that the proportion of highly co-expressed neighboring pairs (Pearson’s correlation coefficient R>0.7 is low (0.24% ~ 0.67%; however, it is still significantly higher than that of random pairs. In particular, the statistical result implies that the co-expression tendency of neighboring pairs is negatively correlated with their physical distance. Our findings therefore suggest that physical distance may play an important role in the co-expression of neighboring genes. Possible mechanisms related to the neighboring genes’ co-expression are also discussed.

Low pH induces co-ordinate regulation of gene expression in oesophageal cells.

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Duggan, Shane P; Gallagher, William M; Fox, Edward J P; Abdel-Latif, Mohammed M; Reynolds, John V; Kelleher, Dermot

2006-02-01

The development of gastro-oesophageal reflux disease (GORD) is known to be a causative risk factor in the evolution of adenocarcinoma of the oesophagus. The major component of this reflux is gastric acid. However, the impact of low pH on gene expression has not been extensively studied in oesophageal cells. This study utilizes a transcriptomic and bioinformatic approach to assess regulation of gene expression in response to low pH. In more detail, oesophageal adenocarcinoma cell lines were exposed to a range of pH environments. Affymetrix microarrays were used for gene-expression analysis and results were validated using cycle limitation and real-time RT-PCR analysis, as well as northern and western blotting. Comparative promoter transcription factor binding site (TFBS) analysis (MatInspector) of hierarchically clustered gene-expression data was employed to identify the elements which may co-ordinately regulate individual gene clusters. Initial experiments demonstrated maximal induction of EGR1 gene expression at pH 6.5. Subsequent array experimentation revealed significant induction of gene expression from such functional categories as DNA damage response (EGR1-4, ATF3) and cell-cycle control (GADD34, GADD45, p57). Changes in expression of EGR1, EGR3, ATF3, MKP-1, FOSB, CTGF and CYR61 were verified in separate experiments and in a variety of oesophageal cell lines. TFBS analysis of promoters identified transcription factors that may co-ordinately regulate gene-expression clusters, Cluster 1: Oct-1, AP4R; Cluster 2: NF-kB, EGRF; Cluster 3: IKRS, AP-1F. Low pH has the ability to induce genes and pathways which can provide an environment suitable for the progression of malignancy. Further functional analysis of the genes and clusters identified in this low pH study is likely to lead to new insights into the pathogenesis and therapeutics of GORD and oesophageal cancer.

Genes associated with thermosensitive genic male sterility in rice identified by comparative expression profiling.

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Pan, Yufang; Li, Qiaofeng; Wang, Zhizheng; Wang, Yang; Ma, Rui; Zhu, Lili; He, Guangcun; Chen, Rongzhi

2014-12-16

development, low temperature responses or TGMS was validated by quantitative RT-PCR (qRT-PCR). Temperature strongly affects global gene expression and may be the common regulator of fertility in PGMS/TGMS rice lines. The identified expression changes reflect perturbations in the transcriptomic regulation of pollen development networks in TGMS-Co27. Findings from this and previous studies indicate that sets of genes involved in post-transcriptional and translation processes are involved in thermosensitive male sterility transitions in TGMS-Co27.

Uncovering co-expression gene network modules regulating fruit acidity in diverse apples.

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Bai, Yang; Dougherty, Laura; Cheng, Lailiang; Zhong, Gan-Yuan; Xu, Kenong

2015-08-16

Acidity is a major contributor to fruit quality. Several organic acids are present in apple fruit, but malic acid is predominant and determines fruit acidity. The trait is largely controlled by the Malic acid (Ma) locus, underpinning which Ma1 that putatively encodes a vacuolar aluminum-activated malate transporter1 (ALMT1)-like protein is a strong candidate gene. We hypothesize that fruit acidity is governed by a gene network in which Ma1 is key member. The goal of this study is to identify the gene network and the potential mechanisms through which the network operates. Guided by Ma1, we analyzed the transcriptomes of mature fruit of contrasting acidity from six apple accessions of genotype Ma_ (MaMa or Mama) and four of mama using RNA-seq and identified 1301 fruit acidity associated genes, among which 18 were most significant acidity genes (MSAGs). Network inferring using weighted gene co-expression network analysis (WGCNA) revealed five co-expression gene network modules of significant (P acidity. Overall, this study provides important insight into the Ma1-mediated gene network controlling acidity in mature apple fruit of diverse genetic background.

Gene Co-expression Analysis to Characterize Genes Related to Marbling Trait in Hanwoo (Korean) Cattle.

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Lim, Dajeong; Lee, Seung-Hwan; Kim, Nam-Kuk; Cho, Yong-Min; Chai, Han-Ha; Seong, Hwan-Hoo; Kim, Heebal

2013-01-01

Marbling (intramuscular fat) is an important trait that affects meat quality and is a casual factor determining the price of beef in the Korean beef market. It is a complex trait and has many biological pathways related to muscle and fat. There is a need to identify functional modules or genes related to marbling traits and investigate their relationships through a weighted gene co-expression network analysis based on the system level. Therefore, we investigated the co-expression relationships of genes related to the 'marbling score' trait and systemically analyzed the network topology in Hanwoo (Korean cattle). As a result, we determined 3 modules (gene groups) that showed statistically significant results for marbling score. In particular, one module (denoted as red) has a statistically significant result for marbling score (p = 0.008) and intramuscular fat (p = 0.02) and water capacity (p = 0.006). From functional enrichment and relationship analysis of the red module, the pathway hub genes (IL6, CHRNE, RB1, INHBA and NPPA) have a direct interaction relationship and share the biological functions related to fat or muscle, such as adipogenesis or muscle growth. This is the first gene network study with m.logissimus in Hanwoo to observe co-expression patterns in divergent marbling phenotypes. It may provide insights into the functional mechanisms of the marbling trait.

Gene Co-expression Analysis to Characterize Genes Related to Marbling Trait in Hanwoo (Korean Cattle

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Dajeong Lim

2013-01-01

Full Text Available Marbling (intramuscular fat is an important trait that affects meat quality and is a casual factor determining the price of beef in the Korean beef market. It is a complex trait and has many biological pathways related to muscle and fat. There is a need to identify functional modules or genes related to marbling traits and investigate their relationships through a weighted gene co-expression network analysis based on the system level. Therefore, we investigated the co-expression relationships of genes related to the ‘marbling score’ trait and systemically analyzed the network topology in Hanwoo (Korean cattle. As a result, we determined 3 modules (gene groups that showed statistically significant results for marbling score. In particular, one module (denoted as red has a statistically significant result for marbling score (p = 0.008 and intramuscular fat (p = 0.02 and water capacity (p = 0.006. From functional enrichment and relationship analysis of the red module, the pathway hub genes (IL6, CHRNE, RB1, INHBA and NPPA have a direct interaction relationship and share the biological functions related to fat or muscle, such as adipogenesis or muscle growth. This is the first gene network study with m.logissimus in Hanwoo to observe co-expression patterns in divergent marbling phenotypes. It may provide insights into the functional mechanisms of the marbling trait.

In-silico gene co-expression network analysis in Paracoccidioides brasiliensis with reference to haloacid dehalogenase superfamily hydrolase gene

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Raghunath Satpathy

2015-01-01

Full Text Available Context: Paracoccidioides brasiliensis, a dimorphic fungus is the causative agent of paracoccidioidomycosis, a disease globally affecting millions of people. The haloacid dehalogenase (HAD superfamily hydrolases enzyme in the fungi, in particular, is known to be responsible in the pathogenesis by adhering to the tissue. Hence, identification of novel drug targets is essential. Aims: In-silico based identification of co-expressed genes along with HAD superfamily hydrolase in P. brasiliensis during the morphogenesis from mycelium to yeast to identify possible genes as drug targets. Materials and Methods: In total, four datasets were retrieved from the NCBI-gene expression omnibus (GEO database, each containing 4340 genes, followed by gene filtration expression of the data set. Further co-expression (CE study was performed individually and then a combination these genes were visualized in the Cytoscape 2. 8.3. Statistical Analysis Used: Mean and standard deviation value of the HAD superfamily hydrolase gene was obtained from the expression data and this value was subsequently used for the CE calculation purpose by selecting specific correlation power and filtering threshold. Results: The 23 genes that were thus obtained are common with respect to the HAD superfamily hydrolase gene. A significant network was selected from the Cytoscape network visualization that contains total 7 genes out of which 5 genes, which do not have significant protein hits, obtained from gene annotation of the expressed sequence tags by BLAST X. For all the protein PSI-BLAST was performed against human genome to find the homology. Conclusions: The gene co-expression network was obtained with respect to HAD superfamily dehalogenase gene in P. Brasiliensis.

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

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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

A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes.

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Simone de Jong

Full Text Available 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.

Gene co-expression networks shed light into diseases of brain iron accumulation.

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Bettencourt, Conceição; Forabosco, Paola; Wiethoff, Sarah; Heidari, Moones; Johnstone, Daniel M; Botía, Juan A; Collingwood, Joanna F; Hardy, John; Milward, Elizabeth A; Ryten, Mina; Houlden, Henry

2016-03-01

Aberrant brain iron deposition is observed in both common and rare neurodegenerative disorders, including those categorized as Neurodegeneration with Brain Iron Accumulation (NBIA), which are characterized by focal iron accumulation in the basal ganglia. Two NBIA genes are directly involved in iron metabolism, but whether other NBIA-related genes also regulate iron homeostasis in the human brain, and whether aberrant iron deposition contributes to neurodegenerative processes remains largely unknown. This study aims to expand our understanding of these iron overload diseases and identify relationships between known NBIA genes and their main interacting partners by using a systems biology approach. We used whole-transcriptome gene expression data from human brain samples originating from 101 neuropathologically normal individuals (10 brain regions) to generate weighted gene co-expression networks and cluster the 10 known NBIA genes in an unsupervised manner. We investigated NBIA-enriched networks for relevant cell types and pathways, and whether they are disrupted by iron loading in NBIA diseased tissue and in an in vivo mouse model. We identified two basal ganglia gene co-expression modules significantly enriched for NBIA genes, which resemble neuronal and oligodendrocytic signatures. These NBIA gene networks are enriched for iron-related genes, and implicate synapse and lipid metabolism related pathways. Our data also indicates that these networks are disrupted by excessive brain iron loading. We identified multiple cell types in the origin of NBIA disorders. We also found unforeseen links between NBIA networks and iron-related processes, and demonstrate convergent pathways connecting NBIAs and phenotypically overlapping diseases. Our results are of further relevance for these diseases by providing candidates for new causative genes and possible points for therapeutic intervention. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Weighted gene co-expression network analysis reveals potential genes involved in early metamorphosis process in sea cucumber Apostichopus japonicus.

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Li, Yongxin; Kikuchi, Mani; Li, Xueyan; Gao, Qionghua; Xiong, Zijun; Ren, Yandong; Zhao, Ruoping; Mao, Bingyu; Kondo, Mariko; Irie, Naoki; Wang, Wen

2018-01-01

Sea cucumbers, one main class of Echinoderms, have a very fast and drastic metamorphosis process during their development. However, the molecular basis under this process remains largely unknown. Here we systematically examined the gene expression profiles of Japanese common sea cucumber (Apostichopus japonicus) for the first time by RNA sequencing across 16 developmental time points from fertilized egg to juvenile stage. Based on the weighted gene co-expression network analysis (WGCNA), we identified 21 modules. Among them, MEdarkmagenta was highly expressed and correlated with the early metamorphosis process from late auricularia to doliolaria larva. Furthermore, gene enrichment and differentially expressed gene analysis identified several genes in the module that may play key roles in the metamorphosis process. Our results not only provide a molecular basis for experimentally studying the development and morphological complexity of sea cucumber, but also lay a foundation for improving its emergence rate. Copyright © 2017 Elsevier Inc. All rights reserved.

Genes and co-expression modules common to drought and bacterial stress responses in Arabidopsis and rice.

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Rafi Shaik

Full Text Available Plants are simultaneously exposed to multiple stresses resulting in enormous changes in the molecular landscape within the cell. Identification and characterization of the synergistic and antagonistic components of stress response mechanisms contributing to the cross talk between stresses is of high priority to explore and enhance multiple stress responses. To this end, we performed meta-analysis of drought (abiotic, bacterial (biotic stress response in rice and Arabidopsis by analyzing a total of 386 microarray samples belonging to 20 microarray studies and identified approximately 3100 and 900 DEGs in rice and Arabidopsis, respectively. About 38.5% (1214 and 28.7% (272 DEGs were common to drought and bacterial stresses in rice and Arabidopsis, respectively. A majority of these common DEGs showed conserved expression status in both stresses. Gene ontology enrichment analysis clearly demarcated the response and regulation of various plant hormones and related biological processes. Fatty acid metabolism and biosynthesis of alkaloids were upregulated and, nitrogen metabolism and photosynthesis was downregulated in both stress conditions. WRKY transcription family genes were highly enriched in all upregulated gene sets while 'CO-like' TF family showed inverse relationship of expression between drought and bacterial stresses. Weighted gene co-expression network analysis divided DEG sets into multiple modules that show high co-expression and identified stress specific hub genes with high connectivity. Detection of consensus modules based on DEGs common to drought and bacterial stress revealed 9 and 4 modules in rice and Arabidopsis, respectively, with conserved and reversed co-expression patterns.

Genetic architecture of gene expression in the chicken

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Stanley Dragana

2013-01-01

Full Text Available Abstract Background The annotation of many genomes is limited, with a large proportion of identified genes lacking functional assignments. The construction of gene co-expression networks is a powerful approach that presents a way of integrating information from diverse gene expression datasets into a unified analysis which allows inferences to be drawn about the role of previously uncharacterised genes. Using this approach, we generated a condition-free gene co-expression network for the chicken using data from 1,043 publically available Affymetrix GeneChip Chicken Genome Arrays. This data was generated from a diverse range of experiments, including different tissues and experimental conditions. Our aim was to identify gene co-expression modules and generate a tool to facilitate exploration of the functional chicken genome. Results Fifteen modules, containing between 24 and 473 genes, were identified in the condition-free network. Most of the modules showed strong functional enrichment for particular Gene Ontology categories. However, a few showed no enrichment. Transcription factor binding site enrichment was also noted. Conclusions We have demonstrated that this chicken gene co-expression network is a useful tool in gene function prediction and the identification of putative novel transcription factors and binding sites. This work highlights the relevance of this methodology for functional prediction in poorly annotated genomes such as the chicken.

Suppression subtractive hybridization and comparative expression analysis to identify developmentally regulated genes in filamentous fungi.

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Gesing, Stefan; Schindler, Daniel; Nowrousian, Minou

2013-09-01

Ascomycetes differentiate four major morphological types of fruiting bodies (apothecia, perithecia, pseudothecia and cleistothecia) that are derived from an ancestral fruiting body. Thus, fruiting body differentiation is most likely controlled by a set of common core genes. One way to identify such genes is to search for genes with evolutionary conserved expression patterns. Using suppression subtractive hybridization (SSH), we selected differentially expressed transcripts in Pyronema confluens (Pezizales) by comparing two cDNA libraries specific for sexual and for vegetative development, respectively. The expression patterns of selected genes from both libraries were verified by quantitative real time PCR. Expression of several corresponding homologous genes was found to be conserved in two members of the Sordariales (Sordaria macrospora and Neurospora crassa), a derived group of ascomycetes that is only distantly related to the Pezizales. Knockout studies with N. crassa orthologues of differentially regulated genes revealed a functional role during fruiting body development for the gene NCU05079, encoding a putative MFS peptide transporter. These data indicate conserved gene expression patterns and a functional role of the corresponding genes during fruiting body development; such genes are candidates of choice for further functional analysis. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

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Bing Jiang

2017-01-01

Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

FastGCN: a GPU accelerated tool for fast gene co-expression networks.

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Meimei Liang

Full Text Available Gene co-expression networks comprise one type of valuable biological networks. Many methods and tools have been published to construct gene co-expression networks; however, most of these tools and methods are inconvenient and time consuming for large datasets. We have developed a user-friendly, accelerated and optimized tool for constructing gene co-expression networks that can fully harness the parallel nature of GPU (Graphic Processing Unit architectures. Genetic entropies were exploited to filter out genes with no or small expression changes in the raw data preprocessing step. Pearson correlation coefficients were then calculated. After that, we normalized these coefficients and employed the False Discovery Rate to control the multiple tests. At last, modules identification was conducted to construct the co-expression networks. All of these calculations were implemented on a GPU. We also compressed the coefficient matrix to save space. We compared the performance of the GPU implementation with those of multi-core CPU implementations with 16 CPU threads, single-thread C/C++ implementation and single-thread R implementation. Our results show that GPU implementation largely outperforms single-thread C/C++ implementation and single-thread R implementation, and GPU implementation outperforms multi-core CPU implementation when the number of genes increases. With the test dataset containing 16,000 genes and 590 individuals, we can achieve greater than 63 times the speed using a GPU implementation compared with a single-thread R implementation when 50 percent of genes were filtered out and about 80 times the speed when no genes were filtered out.

Building gene co-expression networks using transcriptomics data for systems biology investigations

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Kadarmideen, Haja; Watson-Haigh, Nathan S.

2012-01-01

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four......) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT...... (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended....

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI

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Wang, Weijing; Jiang, Wenjie; Hou, Lin

2017-01-01

BACKGROUND: The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis......) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database...

Gene expression analysis identifies global gene dosage sensitivity in cancer

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Fehrmann, Rudolf S. N.; Karjalainen, Juha M.; Krajewska, Malgorzata

2015-01-01

Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gen...

GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

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Ning Ye

2015-01-01

Full Text Available The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

Identification of a 251 gene expression signature that can accurately detect M. tuberculosis in patients with and without HIV co-infection.

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Noor Dawany

Full Text Available BACKGROUND: Co-infection with tuberculosis (TB is the leading cause of death in HIV-infected individuals. However, diagnosis of TB, especially in the presence of an HIV co-infection, can be limiting due to the high inaccuracy associated with the use of conventional diagnostic methods. Here we report a gene signature that can identify a tuberculosis infection in patients co-infected with HIV as well as in the absence of HIV. METHODS: We analyzed global gene expression data from peripheral blood mononuclear cell (PBMC samples of patients that were either mono-infected with HIV or co-infected with HIV/TB and used support vector machines to identify a gene signature that can distinguish between the two classes. We then validated our results using publically available gene expression data from patients mono-infected with TB. RESULTS: Our analysis successfully identified a 251-gene signature that accurately distinguishes patients co-infected with HIV/TB from those infected with HIV only, with an overall accuracy of 81.4% (sensitivity = 76.2%, specificity = 86.4%. Furthermore, we show that our 251-gene signature can also accurately distinguish patients with active TB in the absence of an HIV infection from both patients with a latent TB infection and healthy controls (88.9-94.7% accuracy; 69.2-90% sensitivity and 90.3-100% specificity. We also demonstrate that the expression levels of the 251-gene signature diminish as a correlate of the length of TB treatment. CONCLUSIONS: A 251-gene signature is described to (a detect TB in the presence or absence of an HIV co-infection, and (b assess response to treatment following anti-TB therapy.

Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies

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2014-01-01

Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods. PMID:24708878

Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules.

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Xiaolin Xiao

2014-01-01

Full Text Available Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states. Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based and humans (mRNA-sequencing-based and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi

Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules.

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Xiao, Xiaolin; Moreno-Moral, Aida; Rotival, Maxime; Bottolo, Leonardo; Petretto, Enrico

2014-01-01

Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states). Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks) that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted) networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based) and humans (mRNA-sequencing-based) and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi-tissue subnetwork of co-expressed

Differential gene expression in human fibroblasts after alpha-particle emitter (211)At compared with (60)Co irradiation

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Danielsson, Anna; Claesson, Kristina; Parris, Toshima Z

2013-01-01

trastuzumab monoclonal antibody (0.25, 0.5, and 1 Gy) and (60)Co (1, 2, and 3 Gy). Results: We report gene expression profiles that distinguish the effect different radiation qualities and absorbed doses have on cellular functions in human fibroblasts. In addition, we identified commonly expressed transcripts...

Cartilage-selective genes identified in genome-scale analysis of non-cartilage and cartilage gene expression

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Cohn Zachary A

2007-06-01

Full Text Available Abstract Background Cartilage plays a fundamental role in the development of the human skeleton. Early in embryogenesis, mesenchymal cells condense and differentiate into chondrocytes to shape the early skeleton. Subsequently, the cartilage anlagen differentiate to form the growth plates, which are responsible for linear bone growth, and the articular chondrocytes, which facilitate joint function. However, despite the multiplicity of roles of cartilage during human fetal life, surprisingly little is known about its transcriptome. To address this, a whole genome microarray expression profile was generated using RNA isolated from 18–22 week human distal femur fetal cartilage and compared with a database of control normal human tissues aggregated at UCLA, termed Celsius. Results 161 cartilage-selective genes were identified, defined as genes significantly expressed in cartilage with low expression and little variation across a panel of 34 non-cartilage tissues. Among these 161 genes were cartilage-specific genes such as cartilage collagen genes and 25 genes which have been associated with skeletal phenotypes in humans and/or mice. Many of the other cartilage-selective genes do not have established roles in cartilage or are novel, unannotated genes. Quantitative RT-PCR confirmed the unique pattern of gene expression observed by microarray analysis. Conclusion Defining the gene expression pattern for cartilage has identified new genes that may contribute to human skeletogenesis as well as provided further candidate genes for skeletal dysplasias. The data suggest that fetal cartilage is a complex and transcriptionally active tissue and demonstrate that the set of genes selectively expressed in the tissue has been greatly underestimated.

Analysis of Temporal-spatial Co-variation within Gene Expression Microarray Data in an Organogenesis Model

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Ehler, Martin; Rajapakse, Vinodh; Zeeberg, Barry; Brooks, Brian; Brown, Jacob; Czaja, Wojciech; Bonner, Robert F.

The gene networks underlying closure of the optic fissure during vertebrate eye development are poorly understood. We used a novel clustering method based on Laplacian Eigenmaps, a nonlinear dimension reduction method, to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our new method provided greater biological specificity than classical clustering algorithms in terms of identifying more biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates. This new methodology builds on the advantages of LCM to isolate pure phenotypic populations within complex tissues and allows improved ability to identify critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and extracting spatial and temporal co-variations appear to be a powerful approach to understanding the gene regulatory networks that specify mammalian organogenesis.

Network statistics of genetically-driven gene co-expression modules in mouse crosses

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Marie-Pier eScott-Boyer

2013-12-01

Full Text Available In biology, networks are used in different contexts as ways to represent relationships between entities, such as for instance interactions between genes, proteins or metabolites. Despite progress in the analysis of such networks and their potential to better understand the collective impact of genes on complex traits, one remaining challenge is to establish the biologic validity of gene co-expression networks and to determine what governs their organization. We used WGCNA to construct and analyze seven gene expression datasets from several tissues of mouse recombinant inbred strains (RIS. For six out of the 7 networks, we found that linkage to module QTLs (mQTLs could be established for 29.3% of gene co-expression modules detected in the several mouse RIS. For about 74.6% of such genetically-linked modules, the mQTL was on the same chromosome as the one contributing most genes to the module, with genes originating from that chromosome showing higher connectivity than other genes in the modules. Such modules (that we considered as genetically-driven had network statistic properties (density, centralization and heterogeneity that set them apart from other modules in the network. Altogether, a sizeable portion of gene co-expression modules detected in mouse RIS panels had genetic determinants as their main organizing principle. In addition to providing a biologic interpretation validation for these modules, these genetic determinants imparted on them particular properties that set them apart from other modules in the network, to the point that they can be predicted to a large extent on the basis of their network statistics.

Integrating mean and variance heterogeneities to identify differentially expressed genes.

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Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

2016-12-06

In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

Cogena, a novel tool for co-expressed gene-set enrichment analysis, applied to drug repositioning and drug mode of action discovery.

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Jia, Zhilong; Liu, Ying; Guan, Naiyang; Bo, Xiaochen; Luo, Zhigang; Barnes, Michael R

2016-05-27

Drug repositioning, finding new indications for existing drugs, has gained much recent attention as a potentially efficient and economical strategy for accelerating new therapies into the clinic. Although improvement in the sensitivity of computational drug repositioning methods has identified numerous credible repositioning opportunities, few have been progressed. Arguably the "black box" nature of drug action in a new indication is one of the main blocks to progression, highlighting the need for methods that inform on the broader target mechanism in the disease context. We demonstrate that the analysis of co-expressed genes may be a critical first step towards illumination of both disease pathology and mode of drug action. We achieve this using a novel framework, co-expressed gene-set enrichment analysis (cogena) for co-expression analysis of gene expression signatures and gene set enrichment analysis of co-expressed genes. The cogena framework enables simultaneous, pathway driven, disease and drug repositioning analysis. Cogena can be used to illuminate coordinated changes within disease transcriptomes and identify drugs acting mechanistically within this framework. We illustrate this using a psoriatic skin transcriptome, as an exemplar, and recover two widely used Psoriasis drugs (Methotrexate and Ciclosporin) with distinct modes of action. Cogena out-performs the results of Connectivity Map and NFFinder webservers in similar disease transcriptome analyses. Furthermore, we investigated the literature support for the other top-ranked compounds to treat psoriasis and showed how the outputs of cogena analysis can contribute new insight to support the progression of drugs into the clinic. We have made cogena freely available within Bioconductor or https://github.com/zhilongjia/cogena . In conclusion, by targeting co-expressed genes within disease transcriptomes, cogena offers novel biological insight, which can be effectively harnessed for drug discovery and

Gene expression profile identifies potential biomarkers for human intervertebral disc degeneration.

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Guo, Wei; Zhang, Bin; Li, Yan; Duan, Hui-Quan; Sun, Chao; Xu, Yun-Qiang; Feng, Shi-Qing

2017-12-01

The present study aimed to reveal the potential genes associated with the pathogenesis of intervertebral disc degeneration (IDD) by analyzing microarray data using bioinformatics. Gene expression profiles of two regions of the intervertebral disc were compared between patients with IDD and controls. GSE70362 containing two groups of gene expression profiles, 16 nucleus pulposus (NP) samples from patients with IDD and 8 from controls, and 16 annulus fibrosus (AF) samples from patients with IDD and 8 from controls, was downloaded from the Gene Expression Omnibus database. A total of 93 and 114 differentially expressed genes (DEGs) were identified in NP and AF samples, respectively, using a limma software package for the R programming environment. Gene Ontology (GO) function enrichment analysis was performed to identify the associated biological functions of DEGs in IDD, which indicated that the DEGs may be involved in various processes, including cell adhesion, biological adhesion and extracellular matrix organization. Pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated that the identified DEGs were potentially involved in focal adhesion and the p53 signaling pathway. Further analysis revealed that there were 35 common DEGs observed between the two regions (NP and AF), which may be further regulated by 6 clusters of microRNAs (miRNAs) retrieved with WebGestalt. The genes in the DEG‑miRNA regulatory network were annotated using GO function and KEGG pathway enrichment analysis, among which extracellular matrix organization was the most significant disrupted biological process and focal adhesion was the most significant dysregulated pathway. In addition, the result of protein‑protein interaction network modules demonstrated the involvement of inflammatory cytokine interferon signaling in IDD. These findings may not only advance the understanding of the pathogenesis of IDD, but also identify novel potential

Integration of liver gene co-expression networks and eGWAs analyses highlighted candidate regulators implicated in lipid metabolism in pigs.

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Ballester, Maria; Ramayo-Caldas, Yuliaxis; Revilla, Manuel; Corominas, Jordi; Castelló, Anna; Estellé, Jordi; Fernández, Ana I; Folch, Josep M

2017-04-19

In the present study, liver co-expression networks and expression Genome Wide Association Study (eGWAS) were performed to identify DNA variants and molecular pathways implicated in the functional regulatory mechanisms of meat quality traits in pigs. With this purpose, the liver mRNA expression of 44 candidates genes related with lipid metabolism was analysed in 111 Iberian x Landrace backcross animals. The eGWAS identified 92 eSNPs located in seven chromosomal regions and associated with eight genes: CROT, CYP2U1, DGAT1, EGF, FABP1, FABP5, PLA2G12A, and PPARA. Remarkably, cis-eSNPs associated with FABP1 gene expression which may be determining the C18:2(n-6)/C18:3(n-3) ratio in backfat through the multiple interaction of DNA variants and genes were identified. Furthermore, a hotspot on SSC8 associated with the gene expression of eight genes was identified and the TBCK gene was pointed out as candidate gene regulating it. Our results also suggested that the PI3K-Akt-mTOR pathway plays an important role in the control of the analysed genes highlighting nuclear receptors as the NR3C1 or PPARA. Finally, sex-dimorphism associated with hepatic lipid metabolism was identified with over-representation of female-biased genes. These results increase our knowledge of the genetic architecture underlying fat composition traits.

A co-expression gene network associated with developmental regulation of apple fruit acidity.

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Bai, Yang; Dougherty, Laura; Cheng, Lailiang; Xu, Kenong

2015-08-01

Apple fruit acidity, which affects the fruit's overall taste and flavor to a large extent, is primarily determined by the concentration of malic acid. Previous studies demonstrated that the major QTL malic acid (Ma) on chromosome 16 is largely responsible for fruit acidity variations in apple. Recent advances suggested that a natural mutation that gives rise to a premature stop codon in one of the two aluminum-activated malate transporter (ALMT)-like genes (called Ma1) is the genetic causal element underlying Ma. However, the natural mutation does not explain the developmental changes of fruit malate levels in a given genotype. Using RNA-seq data from the fruit of 'Golden Delicious' taken at 14 developmental stages from 1 week after full-bloom (WAF01) to harvest (WAF20), we characterized their transcriptomes in groups of high (12.2 ± 1.6 mg/g fw, WAF03-WAF08), mid (7.4 ± 0.5 mg/g fw, WAF01-WAF02 and WAF10-WAF14) and low (5.4 ± 0.4 mg/g fw, WAF16-WAF20) malate concentrations. Detailed analyses showed that a set of 3,066 genes (including Ma1) were expressed not only differentially (P FDR < 0.05) between the high and low malate groups (or between the early and late developmental stages) but also in significant (P < 0.05) correlation with malate concentrations. The 3,066 genes fell in 648 MapMan (sub-) bins or functional classes, and 19 of them were significantly (P FDR < 0.05) co-enriched or co-suppressed in a malate dependent manner. Network inferring using the 363 genes encompassed in the 19 (sub-) bins, identified a major co-expression network of 239 genes. Since the 239 genes were also differentially expressed between the early (WAF03-WAF08) and late (WAF16-WAF20) developmental stages, the major network was considered to be associated with developmental regulation of apple fruit acidity in 'Golden Delicious'.

ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis

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Saurav Mallik

2017-12-01

Full Text Available For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures—weighted rank-based Jaccard and Cosine measures—and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm—RANWAR—was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.

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Mallik, Saurav; Zhao, Zhongming

2017-12-28

For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

A comprehensive analysis on preservation patterns of gene co-expression networks during Alzheimer's disease progression.

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Ray, Sumanta; Hossain, Sk Md Mosaddek; Khatun, Lutfunnesa; Mukhopadhyay, Anirban

2017-12-20

Alzheimer's disease (AD) is a chronic neuro-degenerative disruption of the brain which involves in large scale transcriptomic variation. The disease does not impact every regions of the brain at the same time, instead it progresses slowly involving somewhat sequential interaction with different regions. Analysis of the expression patterns of the genes in different regions of the brain influenced in AD surely contribute for a enhanced comprehension of AD pathogenesis and shed light on the early characterization of the disease. Here, we have proposed a framework to identify perturbation and preservation characteristics of gene expression patterns across six distinct regions of the brain ("EC", "HIP", "PC", "MTG", "SFG", and "VCX") affected in AD. Co-expression modules were discovered considering a couple of regions at once. These are then analyzed to know the preservation and perturbation characteristics. Different module preservation statistics and a rank aggregation mechanism have been adopted to detect the changes of expression patterns across brain regions. Gene ontology (GO) and pathway based analysis were also carried out to know the biological meaning of preserved and perturbed modules. In this article, we have extensively studied the preservation patterns of co-expressed modules in six distinct brain regions affected in AD. Some modules are emerged as the most preserved while some others are detected as perturbed between a pair of brain regions. Further investigation on the topological properties of preserved and non-preserved modules reveals a substantial association amongst "betweenness centrality" and "degree" of the involved genes. Our findings may render a deeper realization of the preservation characteristics of gene expression patterns in discrete brain regions affected by AD.

Evaluation of endogenous control gene(s) for gene expression studies in human blood exposed to 60Co γ-rays ex vivo

International Nuclear Information System (INIS)

Vaiphei, S. Thangminlal; Keppen, Joshua; Nongrum, Saibadaiahun; Sharan, R.N.; Chaubey, R.C.; Kma, L.

2015-01-01

In gene expression studies, it is critical to normalize data using a stably expressed endogenous control gene in order to obtain accurate and reliable results. However, we currently do not have a universally applied endogenous control gene for normalization of data for gene expression studies, particularly those involving 60 Co γ-ray-exposed human blood samples. In this study, a comparative assessment of the gene expression of six widely used housekeeping endogenous control genes, namely 18S, ACTB, B2M, GAPDH, MT-ATP6 and CDKN1A, was undertaken for a range of 60 Co γ-ray doses (0.5, 1.0, 2.0 and 4.0 Gy) at 8.4 Gy min -1 at 0 and 24 h post-irradiation time intervals. Using the NormFinder algorithm, real-time PCR data obtained from six individuals (three males and three females) were analyzed with respect to the threshold cycle (Ct) value and abundance, ΔCt pair-wise comparison, intra- and inter-group variability assessments, etc. GAPDH, either alone or in combination with 18S, was found to be the most suitable endogenous control gene and should be used in gene expression studies, especially those involving qPCR of γ-ray-exposed human blood samples. (author)

A powerful nonparametric method for detecting differentially co-expressed genes: distance correlation screening and edge-count test.

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Zhang, Qingyang

2018-05-16

Differential co-expression analysis, as a complement of differential expression analysis, offers significant insights into the changes in molecular mechanism of different phenotypes. A prevailing approach to detecting differentially co-expressed genes is to compare Pearson's correlation coefficients in two phenotypes. However, due to the limitations of Pearson's correlation measure, this approach lacks the power to detect nonlinear changes in gene co-expression which is common in gene regulatory networks. In this work, a new nonparametric procedure is proposed to search differentially co-expressed gene pairs in different phenotypes from large-scale data. Our computational pipeline consisted of two main steps, a screening step and a testing step. The screening step is to reduce the search space by filtering out all the independent gene pairs using distance correlation measure. In the testing step, we compare the gene co-expression patterns in different phenotypes by a recently developed edge-count test. Both steps are distribution-free and targeting nonlinear relations. We illustrate the promise of the new approach by analyzing the Cancer Genome Atlas data and the METABRIC data for breast cancer subtypes. Compared with some existing methods, the new method is more powerful in detecting nonlinear type of differential co-expressions. The distance correlation screening can greatly improve computational efficiency, facilitating its application to large data sets.

Evaluation of endogenous control gene(s) for gene expression studies in human blood exposed to 60Co γ-rays ex vivo.

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Vaiphei, S Thangminlal; Keppen, Joshua; Nongrum, Saibadaiahun; Chaubey, R C; Kma, L; Sharan, R N

2015-01-01

In gene expression studies, it is critical to normalize data using a stably expressed endogenous control gene in order to obtain accurate and reliable results. However, we currently do not have a universally applied endogenous control gene for normalization of data for gene expression studies, particularly those involving (60)Co γ-ray-exposed human blood samples. In this study, a comparative assessment of the gene expression of six widely used housekeeping endogenous control genes, namely 18S, ACTB, B2M, GAPDH, MT-ATP6 and CDKN1A, was undertaken for a range of (60)Co γ-ray doses (0.5, 1.0, 2.0 and 4.0 Gy) at 8.4 Gy min(-1) at 0 and 24 h post-irradiation time intervals. Using the NormFinder algorithm, real-time PCR data obtained from six individuals (three males and three females) were analyzed with respect to the threshold cycle (Ct) value and abundance, ΔCt pair-wise comparison, intra- and inter-group variability assessments, etc. GAPDH, either alone or in combination with 18S, was found to be the most suitable endogenous control gene and should be used in gene expression studies, especially those involving qPCR of γ-ray-exposed human blood samples. © The Author 2014. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Gene dosage, expression, and ontology analysis identifies driver genes in the carcinogenesis and chemoradioresistance of cervical cancer.

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Malin Lando

2009-11-01

Full Text Available Integrative analysis of gene dosage, expression, and ontology (GO data was performed to discover driver genes in the carcinogenesis and chemoradioresistance of cervical cancers. Gene dosage and expression profiles of 102 locally advanced cervical cancers were generated by microarray techniques. Fifty-two of these patients were also analyzed with the Illumina expression method to confirm the gene expression results. An independent cohort of 41 patients was used for validation of gene expressions associated with clinical outcome. Statistical analysis identified 29 recurrent gains and losses and 3 losses (on 3p, 13q, 21q associated with poor outcome after chemoradiotherapy. The intratumor heterogeneity, assessed from the gene dosage profiles, was low for these alterations, showing that they had emerged prior to many other alterations and probably were early events in carcinogenesis. Integration of the alterations with gene expression and GO data identified genes that were regulated by the alterations and revealed five biological processes that were significantly overrepresented among the affected genes: apoptosis, metabolism, macromolecule localization, translation, and transcription. Four genes on 3p (RYBP, GBE1 and 13q (FAM48A, MED4 correlated with outcome at both the gene dosage and expression level and were satisfactorily validated in the independent cohort. These integrated analyses yielded 57 candidate drivers of 24 genetic events, including novel loci responsible for chemoradioresistance. Further mapping of the connections among genetic events, drivers, and biological processes suggested that each individual event stimulates specific processes in carcinogenesis through the coordinated control of multiple genes. The present results may provide novel therapeutic opportunities of both early and advanced stage cervical cancers.

Gene expression profiling of brakeless mutant Drosophila embryos.

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Crona, Filip; Singla, Bhumica; Mannervik, Mattias

2015-12-01

The transcriptional co-regulator Brakeless performs many important functions during Drosophila development, but few target genes have been identified. Here we use Affymetrix microarrays to identify Brakeless-regulated genes in 2-4 h old Drosophila embryos. Robust multi-array analysis (RMA) and statistical tests revealed 240 genes that changed their expression more than 1.5 fold. We find that up- and down-regulated genes fall into distinct gene ontology categories. In our associated study [2] we demonstrate that both up- and down-regulated genes can be direct Brakeless targets. Our results indicate that the co-repressor and co-activator activities of Brakeless may result in distinct biological responses. The microarray data complies with MIAME guidelines and is deposited in GEO under accession number GSE60048.

In silico identification of miRNAs and their target genes and analysis of gene co-expression network in saffron (Crocus sativus L.) stigma

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Zinati, Zahra; Shamloo-Dashtpagerdi, Roohollah; Behpouri, Ali

2016-01-01

As an aromatic and colorful plant of substantive taste, saffron (Crocus sativus L.) owes such properties of matter to growing class of the secondary metabolites derived from the carotenoids, apocarotenoids. Regarding the critical role of microRNAs in secondary metabolic synthesis and the limited number of identified miRNAs in C. sativus, on the other hand, one may see the point how the characterization of miRNAs along with the corresponding target genes in C. sativus might expand our perspectives on the roles of miRNAs in carotenoid/apocarotenoid biosynthetic pathway. A computational analysis was used to identify miRNAs and their targets using EST (Expressed Sequence Tag) library from mature saffron stigmas. Then, a gene co- expression network was constructed to identify genes which are potentially involved in carotenoid/apocarotenoid biosynthetic pathways. EST analysis led to the identification of two putative miRNAs (miR414 and miR837-5p) along with the corresponding stem- looped precursors. To our knowledge, this is the first report on miR414 and miR837-5p in C. sativus. Co-expression network analysis indicated that miR414 and miR837-5p may play roles in C. sativus metabolic pathways and led to identification of candidate genes including six transcription factors and one protein kinase probably involved in carotenoid/apocarotenoid biosynthetic pathway. Presence of transcription factors, miRNAs and protein kinase in the network indicated multiple layers of regulation in saffron stigma. The candidate genes from this study may help unraveling regulatory networks underlying the carotenoid/apocarotenoid biosynthesis in saffron and designing metabolic engineering for enhanced secondary metabolites. PMID:28261627

Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

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Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash

2016-01-01

Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499

Gene expression responses of paper birch (Betula papyrifera) to elevated CO2 and O3 during leaf maturation and senescence

International Nuclear Information System (INIS)

Kontunen-Soppela, Sari; Parviainen, Juha; Ruhanen, Hanna; Brosche, Mikael; Keinaenen, Markku; Thakur, Ramesh C.; Kolehmainen, Mikko; Kangasjaervi, Jaakko; Oksanen, Elina; Karnosky, David F.; Vapaavuori, Elina

2010-01-01

Gene expression responses of paper birch (Betula papyrifera) leaves to elevated concentrations of CO 2 and O 3 were studied with microarray analyses from three time points during the summer of 2004 at Aspen FACE. Microarray data were analyzed with clustering techniques, self-organizing maps, K-means clustering and Sammon's mappings, to detect similar gene expression patterns within sampling times and treatments. Most of the alterations in gene expression were caused by O 3 , alone or in combination with CO 2 . O 3 induced defensive reactions to oxidative stress and earlier leaf senescence, seen as decreased expression of photosynthesis- and carbon fixation-related genes, and increased expression of senescence-associated genes. The effects of elevated CO 2 reflected surplus of carbon that was directed to synthesis of secondary compounds. The combined CO 2 + O 3 treatment resulted in differential gene expression than with individual gas treatments or in changes similar to O 3 treatment, indicating that CO 2 cannot totally alleviate the harmful effects of O 3 . - Clustering analysis of birch leaf gene expression data reveals differential responses to O 3 and CO 2 .

Integrative Analysis of Hippocampus Gene Expression Profiles Identifies Network Alterations in Aging and Alzheimer’s Disease

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Vinay Lanke

2018-05-01

Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder contributing to rapid decline in cognitive function and ultimately dementia. Most cases of AD occur in elderly and later years. There is a growing need for understanding the relationship between aging and AD to identify shared and unique hallmarks associated with the disease in a region and cell-type specific manner. Although genomic studies on AD have been performed extensively, the molecular mechanism of disease progression is still not clear. The major objective of our study is to obtain a higher-order network-level understanding of aging and AD, and their relationship using the hippocampal gene expression profiles of young (20–50 years, aging (70–99 years, and AD (70–99 years. The hippocampus is vulnerable to damage at early stages of AD and altered neurogenesis in the hippocampus is linked to the onset of AD. We combined the weighted gene co-expression network and weighted protein–protein interaction network-level approaches to study the transition from young to aging to AD. The network analysis revealed the organization of co-expression network into functional modules that are cell-type specific in aging and AD. We found that modules associated with astrocytes, endothelial cells and microglial cells are upregulated and significantly correlate with both aging and AD. The modules associated with neurons, mitochondria and endoplasmic reticulum are downregulated and significantly correlate with AD than aging. The oligodendrocytes module does not show significant correlation with neither aging nor disease. Further, we identified aging- and AD-specific interactions/subnetworks by integrating the gene expression with a human protein–protein interaction network. We found dysregulation of genes encoding protein kinases (FYN, SYK, SRC, PKC, MAPK1, ephrin receptors and transcription factors (FOS, STAT3, CEBPB, MYC, NFKβ, and EGR1 in AD. Further, we found genes that encode proteins

A comparative genomics screen identifies a Sinorhizobium meliloti 1021 sodM-like gene strongly expressed within host plant nodules

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Queiroux Clothilde

2012-05-01

Full Text Available Abstract Background We have used the genomic data in the Integrated Microbial Genomes system of the Department of Energy’s Joint Genome Institute to make predictions about rhizobial open reading frames that play a role in nodulation of host plants. The genomic data was screened by searching for ORFs conserved in α-proteobacterial rhizobia, but not conserved in closely-related non-nitrogen-fixing α-proteobacteria. Results Using this approach, we identified many genes known to be involved in nodulation or nitrogen fixation, as well as several new candidate genes. We knocked out selected new genes and assayed for the presence of nodulation phenotypes and/or nodule-specific expression. One of these genes, SMc00911, is strongly expressed by bacterial cells within host plant nodules, but is expressed minimally by free-living bacterial cells. A strain carrying an insertion mutation in SMc00911 is not defective in the symbiosis with host plants, but in contrast to expectations, this mutant strain is able to out-compete the S. meliloti 1021 wild type strain for nodule occupancy in co-inoculation experiments. The SMc00911 ORF is predicted to encode a “SodM-like” (superoxide dismutase-like protein containing a rhodanese sulfurtransferase domain at the N-terminus and a chromate-resistance superfamily domain at the C-terminus. Several other ORFs (SMb20360, SMc01562, SMc01266, SMc03964, and the SMc01424-22 operon identified in the screen are expressed at a moderate level by bacteria within nodules, but not by free-living bacteria. Conclusions Based on the analysis of ORFs identified in this study, we conclude that this comparative genomics approach can identify rhizobial genes involved in the nitrogen-fixing symbiosis with host plants, although none of the newly identified genes were found to be essential for this process.

Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model.

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Omony, Jimmy; de Jong, Anne; Krawczyk, Antonina O; Eijlander, Robyn T; Kuipers, Oscar P

2018-02-09

Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes.

Identification of a cis-regulatory element by transient analysis of co-ordinately regulated genes

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Allan Andrew C

2008-07-01

Full Text Available Abstract Background Transcription factors (TFs co-ordinately regulate target genes that are dispersed throughout the genome. This co-ordinate regulation is achieved, in part, through the interaction of transcription factors with conserved cis-regulatory motifs that are in close proximity to the target genes. While much is known about the families of transcription factors that regulate gene expression in plants, there are few well characterised cis-regulatory motifs. In Arabidopsis, over-expression of the MYB transcription factor PAP1 (PRODUCTION OF ANTHOCYANIN PIGMENT 1 leads to transgenic plants with elevated anthocyanin levels due to the co-ordinated up-regulation of genes in the anthocyanin biosynthetic pathway. In addition to the anthocyanin biosynthetic genes, there are a number of un-associated genes that also change in expression level. This may be a direct or indirect consequence of the over-expression of PAP1. Results Oligo array analysis of PAP1 over-expression Arabidopsis plants identified genes co-ordinately up-regulated in response to the elevated expression of this transcription factor. Transient assays on the promoter regions of 33 of these up-regulated genes identified eight promoter fragments that were transactivated by PAP1. Bioinformatic analysis on these promoters revealed a common cis-regulatory motif that we showed is required for PAP1 dependent transactivation. Conclusion Co-ordinated gene regulation by individual transcription factors is a complex collection of both direct and indirect effects. Transient transactivation assays provide a rapid method to identify direct target genes from indirect target genes. Bioinformatic analysis of the promoters of these direct target genes is able to locate motifs that are common to this sub-set of promoters, which is impossible to identify with the larger set of direct and indirect target genes. While this type of analysis does not prove a direct interaction between protein and DNA

Gene expression signature analysis identifies vorinostat as a candidate therapy for gastric cancer.

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Sofie Claerhout

Full Text Available Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future.Using microarray technology, we generated a gene expression profile of human gastric cancer-specific genes from human gastric cancer tissue samples. We used this profile in the Broad Institute's Connectivity Map analysis to identify candidate therapeutic compounds for gastric cancer. We found the histone deacetylase inhibitor vorinostat as the lead compound and thus a potential therapeutic drug for gastric cancer. Vorinostat induced both apoptosis and autophagy in gastric cancer cell lines. Pharmacological and genetic inhibition of autophagy however, increased the therapeutic efficacy of vorinostat, indicating that a combination of vorinostat with autophagy inhibitors may therapeutically be more beneficial. Moreover, gene expression analysis of gastric cancer identified a collection of genes (ITGB5, TYMS, MYB, APOC1, CBX5, PLA2G2A, and KIF20A whose expression was elevated in gastric tumor tissue and downregulated more than 2-fold by vorinostat treatment in gastric cancer cell lines. In contrast, SCGB2A1, TCN1, CFD, APLP1, and NQO1 manifested a reversed pattern.We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment.

Characterization of novel tumor stroma markers identified by gene expression profiling of human cancer tissues and 3D co-culture models

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Rupp, C.

2010-01-01

The tumor stroma plays an important role in tumorigenesis. During cancer progression it undergoes changes in architecture, gene expression and secretion of proteolytic enzymes that are essential for the invasive and metastatic phenotype of malignant tumors. Cancer associated fibroblasts (Cafes) represent the major cellular component of the stroma and recent studies demonstrated the prognostic and therapeutic significance of CaF-related molecular signatures. The identification and characterization of genes and signaling pathways involved in the molecular interactions between tumor and stromal cells has been the focus of this study. For that purpose we have used two complementary approaches: the identification of novel tumor stroma targets in human colon cancer samples using whole genome Affymetrix GeneChip analysis and the validation of theses targets in a newly established of 3D co-culture model that mimics the cellular and molecular heterogeneity of human cancers. We have demonstrated increased expression of gene sets related to hypoxia, epithelial-to-mesenchymal transition (EMT) and TGFβ pathway activation in CAFs vs their normal counterparts in both systems. The putative TGFβ target IGFBP7 (insulin-like growth factor binding protein 7) was identified as a tumor stroma marker of epithelial cancers and as a tumor antigen in mesenchyme-derived sarcomas. IGFPB7 was shown to promote anchorage-independent growth in malignant mesenchymal cells and malignant epithelial cells with an EMT-phenotype, whereas a tumor suppressor function was observed in tumor epithelial cells. In summary, we have demonstrated that a number of important signaling pathways involved in cancer progression and metastasis are specifically dysregulated in the tumor stroma both in our in vivo screen and in the in vitro 3D model, illustrating the value of these approaches for the identification and characterization of novel stromal markers. (author) [de

Comparative modular analysis of gene expression in vertebrate organs

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Piasecka Barbara

2012-03-01

Full Text Available Abstract Background The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. Results Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. Conclusions Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

Comparative modular analysis of gene expression in vertebrate organs.

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Piasecka, Barbara; Kutalik, Zoltán; Roux, Julien; Bergmann, Sven; Robinson-Rechavi, Marc

2012-03-29

The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

Matrix factorization reveals aging-specific co-expression gene modules in the fat and muscle tissues in nonhuman primates

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Wang, Yongcui; Zhao, Weiling; Zhou, Xiaobo

2016-10-01

Accurate identification of coherent transcriptional modules (subnetworks) in adipose and muscle tissues is important for revealing the related mechanisms and co-regulated pathways involved in the development of aging-related diseases. Here, we proposed a systematically computational approach, called ICEGM, to Identify the Co-Expression Gene Modules through a novel mathematical framework of Higher-Order Generalized Singular Value Decomposition (HO-GSVD). ICEGM was applied on the adipose, and heart and skeletal muscle tissues in old and young female African green vervet monkeys. The genes associated with the development of inflammation, cardiovascular and skeletal disorder diseases, and cancer were revealed by the ICEGM. Meanwhile, genes in the ICEGM modules were also enriched in the adipocytes, smooth muscle cells, cardiac myocytes, and immune cells. Comprehensive disease annotation and canonical pathway analysis indicated that immune cells, adipocytes, cardiomyocytes, and smooth muscle cells played a synergistic role in cardiac and physical functions in the aged monkeys by regulation of the biological processes associated with metabolism, inflammation, and atherosclerosis. In conclusion, the ICEGM provides an efficiently systematic framework for decoding the co-expression gene modules in multiple tissues. Analysis of genes in the ICEGM module yielded important insights on the cooperative role of multiple tissues in the development of diseases.

Lignin, mitochondrial family and photorespiratory transporter classification as case studies in using co-expression, co-response and protein locations to aid in identifying transport functions

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Takayuki eTohge

2014-03-01

Full Text Available Whole genome sequencing and the relative ease of transcript profiling have facilitated the collection and data warehousing of immense quantities of expression data. However, a substantial proportion of genes are not yet functionally annotated a problem which is particularly acute for transport proteins. In Arabidopsis, for example, only a minor fraction of the estimated 700 intracellular transporters have been identified at the molecular genetic level. Furthermore it is only within the last couple of years that critical genes such as those encoding the final transport step required for the long distance transport of sucrose and the first transporter of the core photorespiratory pathway have been identified. Here we will describe how transcriptional coordination between genes of known function and non-annotated genes allows the identification of putative transporters on the premise that such co-expressed genes tend to be functionally related. We will additionally extend this to include the expansion of this approach to include phenotypic information from other levels of cellular organization such as proteomic and metabolomic data and provide case studies wherein this approach has successfully been used to fill knowledge gaps in important metabolic pathways and physiological processes.

Sparse canonical correlation analysis for identifying, connecting and completing gene-expression networks

NARCIS (Netherlands)

Waaijenborg, S.; Zwinderman, A.H.

2009-01-01

ABSTRACT: BACKGROUND: We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway. We used Wold's method for calculation of the

Gene Expression Signature Analysis Identifies Vorinostat as a Candidate Therapy for Gastric Cancer

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Choi, Woonyoung; Park, Yun-Yong; Kim, KyoungHyun; Kim, Sang-Bae; Lee, Ju-Seog; Mills, Gordon B.; Cho, Jae Yong

2011-01-01

Background Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future. Methodology/Principal Findings Using microarray technology, we generated a gene expression profile of human gastric cancer–specific genes from human gastric cancer tissue samples. We used this profile in the Broad Institute's Connectivity Map analysis to identify candidate therapeutic compounds for gastric cancer. We found the histone deacetylase inhibitor vorinostat as the lead compound and thus a potential therapeutic drug for gastric cancer. Vorinostat induced both apoptosis and autophagy in gastric cancer cell lines. Pharmacological and genetic inhibition of autophagy however, increased the therapeutic efficacy of vorinostat, indicating that a combination of vorinostat with autophagy inhibitors may therapeutically be more beneficial. Moreover, gene expression analysis of gastric cancer identified a collection of genes (ITGB5, TYMS, MYB, APOC1, CBX5, PLA2G2A, and KIF20A) whose expression was elevated in gastric tumor tissue and downregulated more than 2-fold by vorinostat treatment in gastric cancer cell lines. In contrast, SCGB2A1, TCN1, CFD, APLP1, and NQO1 manifested a reversed pattern. Conclusions/Significance We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment. PMID:21931799

Consistent Differential Expression Pattern (CDEP) on microarray to identify genes related to metastatic behavior.

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Tsoi, Lam C; Qin, Tingting; Slate, Elizabeth H; Zheng, W Jim

2011-11-11

To utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP), to identify genes with common differential expression patterns across different datasets. We combined False Discovery Rate (FDR) estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as AMIGO2, Gem, and CXCL11 that have not been shown to associate with, but may play roles in, metastasis. CDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and insensitivity to data variation commonly associated with microarray

Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients

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DeYoung Joseph

2009-08-01

Full Text Available Abstract Background Amyotrophic Lateral Sclerosis (ALS is a lethal disorder characterized by progressive degeneration of motor neurons in the brain and spinal cord. Diagnosis is mainly based on clinical symptoms, and there is currently no therapy to stop the disease or slow its progression. Since access to spinal cord tissue is not possible at disease onset, we investigated changes in gene expression profiles in whole blood of ALS patients. Results Our transcriptional study showed dramatic changes in blood of ALS patients; 2,300 probes (9.4% showed significant differential expression in a discovery dataset consisting of 30 ALS patients and 30 healthy controls. Weighted gene co-expression network analysis (WGCNA was used to find disease-related networks (modules and disease related hub genes. Two large co-expression modules were found to be associated with ALS. Our findings were replicated in a second (30 patients and 30 controls and third dataset (63 patients and 63 controls, thereby demonstrating a highly significant and consistent association of two large co-expression modules with ALS disease status. Ingenuity Pathway Analysis of the ALS related module genes implicates enrichment of functional categories related to genetic disorders, neurodegeneration of the nervous system and inflammatory disease. The ALS related modules contain a number of candidate genes possibly involved in pathogenesis of ALS. Conclusion This first large-scale blood gene expression study in ALS observed distinct patterns between cases and controls which may provide opportunities for biomarker development as well as new insights into the molecular mechanisms of the disease.

Cross-study analysis of gene expression data for intermediate neuroblastoma identifies two biological subtypes

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Warnat, Patrick; Oberthuer, André; Fischer, Matthias; Westermann, Frank; Eils, Roland; Brors, Benedikt

2007-01-01

Neuroblastoma patients show heterogeneous clinical courses ranging from life-threatening progression to spontaneous regression. Recently, gene expression profiles of neuroblastoma tumours were associated with clinically different phenotypes. However, such data is still rare for important patient subgroups, such as patients with MYCN non-amplified advanced stage disease. Prediction of the individual course of disease and optimal therapy selection in this cohort is challenging. Additional research effort is needed to describe the patterns of gene expression in this cohort and to identify reliable prognostic markers for this subset of patients. We combined gene expression data from two studies in a meta-analysis in order to investigate differences in gene expression of advanced stage (3 or 4) tumours without MYCN amplification that show contrasting outcomes (alive or dead) at five years after initial diagnosis. In addition, a predictive model for outcome was generated. Gene expression profiles from 66 patients were included from two studies using different microarray platforms. In the combined data set, 72 genes were identified as differentially expressed by meta-analysis at a false discovery rate (FDR) of 8.33%. Meta-analysis detected 34 differentially expressed genes that were not found as significant in either single study. Outcome prediction based on data of both studies resulted in a predictive accuracy of 77%. Moreover, the genes that were differentially expressed in subgroups of advanced stage patients without MYCN amplification accurately separated MYCN amplified tumours from low stage tumours without MYCN amplification. Our findings support the hypothesis that neuroblastoma consists of two biologically distinct subgroups that differ by characteristic gene expression patterns, which are associated with divergent clinical outcome

Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

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Thomassen, Mads; Tan, Qihua; Kruse, Torben A

2008-01-01

Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets. We have analyzed 8 publicly available gene expression data sets. A global approach, 'gene set enrichment analysis' as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis. By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may

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

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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

A search engine to identify pathway genes from expression data on multiple organisms

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Zambon Alexander C

2007-05-01

Full Text Available Abstract Background The completion of several genome projects showed that most genes have not yet been characterized, especially in multicellular organisms. Although most genes have unknown functions, a large collection of data is available describing their transcriptional activities under many different experimental conditions. In many cases, the coregulatation of a set of genes across a set of conditions can be used to infer roles for genes of unknown function. Results We developed a search engine, the Multiple-Species Gene Recommender (MSGR, which scans gene expression datasets from multiple organisms to identify genes that participate in a genetic pathway. The MSGR takes a query consisting of a list of genes that function together in a genetic pathway from one of six organisms: Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Arabidopsis thaliana, and Helicobacter pylori. Using a probabilistic method to merge searches, the MSGR identifies genes that are significantly coregulated with the query genes in one or more of those organisms. The MSGR achieves its highest accuracy for many human pathways when searches are combined across species. We describe specific examples in which new genes were identified to be involved in a neuromuscular signaling pathway and a cell-adhesion pathway. Conclusion The search engine can scan large collections of gene expression data for new genes that are significantly coregulated with a pathway of interest. By integrating searches across organisms, the MSGR can identify pathway members whose coregulation is either ancient or newly evolved.

Effects of threshold on the topology of gene co-expression networks.

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Couto, Cynthia Martins Villar; Comin, César Henrique; Costa, Luciano da Fontoura

2017-09-26

Several developments regarding the analysis of gene co-expression profiles using complex network theory have been reported recently. Such approaches usually start with the construction of an unweighted gene co-expression network, therefore requiring the selection of a suitable threshold defining which pairs of vertices will be connected. We aimed at addressing such an important problem by suggesting and comparing five different approaches for threshold selection. Each of the methods considers a respective biologically-motivated criterion for electing a potentially suitable threshold. A set of 21 microarray experiments from different biological groups was used to investigate the effect of applying the five proposed criteria to several biological situations. For each experiment, we used the Pearson correlation coefficient to measure the relationship between each gene pair, and the resulting weight matrices were thresholded considering several values, generating respective adjacency matrices (co-expression networks). Each of the five proposed criteria was then applied in order to select the respective threshold value. The effects of these thresholding approaches on the topology of the resulting networks were compared by using several measurements, and we verified that, depending on the database, the impact on the topological properties can be large. However, a group of databases was verified to be similarly affected by most of the considered criteria. Based on such results, it can be suggested that when the generated networks present similar measurements, the thresholding method can be chosen with greater freedom. If the generated networks are markedly different, the thresholding method that better suits the interests of each specific research study represents a reasonable choice.

Co-expression Network Approach to Studying the Effects of Botulinum Neurotoxin-A.

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Mukund, Kavitha; Ward, Samuel R; Lieber, Richard L; Subramaniam, Shankar

2017-10-16

Botulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications.The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into 5 groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes- Dclk1 and Ostalpha within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous workBotulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications.The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules

The duplicated genes database: identification and functional annotation of co-localised duplicated genes across genomes.

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Marion Ouedraogo

Full Text Available BACKGROUND: There has been a surge in studies linking genome structure and gene expression, with special focus on duplicated genes. Although initially duplicated from the same sequence, duplicated genes can diverge strongly over evolution and take on different functions or regulated expression. However, information on the function and expression of duplicated genes remains sparse. Identifying groups of duplicated genes in different genomes and characterizing their expression and function would therefore be of great interest to the research community. The 'Duplicated Genes Database' (DGD was developed for this purpose. METHODOLOGY: Nine species were included in the DGD. For each species, BLAST analyses were conducted on peptide sequences corresponding to the genes mapped on a same chromosome. Groups of duplicated genes were defined based on these pairwise BLAST comparisons and the genomic location of the genes. For each group, Pearson correlations between gene expression data and semantic similarities between functional GO annotations were also computed when the relevant information was available. CONCLUSIONS: The Duplicated Gene Database provides a list of co-localised and duplicated genes for several species with the available gene co-expression level and semantic similarity value of functional annotation. Adding these data to the groups of duplicated genes provides biological information that can prove useful to gene expression analyses. The Duplicated Gene Database can be freely accessed through the DGD website at http://dgd.genouest.org.

Different gene expression of Normal lymphobloastoid cells which exposure to different dose of 60Co γ-ray

International Nuclear Information System (INIS)

Xiao Yao; Yang Jian; Gao Xian; Qin Yanghua; Sun Ding; Hai Ling

2008-01-01

Objective: To study on the gene expression of normal lymphoblastoid cells(AHH-1) which exposure to difference dose of 60 Co γ-ray, analyses the essential different biological effect.. Methods Human AHH-1 normal line was irradiated by 60 Co γ-rays. Used human cDNA microarray to develop the transcriptional levels of the genes by hybridizing the mRNA of cells 8 h after exposured in different dose and the control cells. Cluster analysis, discrimination and bolting were used to filter the effective genes of differential expression. Results The results of data analysis showed 23 genes of differential expression closely related to biological effect of 2.0 Gy radiation, 5 genes express changed only by 0.5 Gy radiation, 5 genes express apparently both in 2.0 Gy and 0.5 Gy radiation. Conclusion: The different dose γ-rays radiation-induced significant changes in gene expression, such as PAPLN, TP53INP1, PTENP1, FOS and TPR seem to be some important components of cellular radioresponse. (authors)

High-Throughput Screening to Identify Regulators of Meiosis-Specific Gene Expression in Saccharomyces cerevisiae.

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Kassir, Yona

2017-01-01

Meiosis and gamete formation are processes that are essential for sexual reproduction in all eukaryotic organisms. Multiple intracellular and extracellular signals feed into pathways that converge on transcription factors that induce the expression of meiosis-specific genes. Once triggered the meiosis-specific gene expression program proceeds in a cascade that drives progress through the events of meiosis and gamete formation. Meiosis-specific gene expression is tightly controlled by a balance of positive and negative regulatory factors that respond to a plethora of signaling pathways. The budding yeast Saccharomyces cerevisiae has proven to be an outstanding model for the dissection of gametogenesis owing to the sophisticated genetic manipulations that can be performed with the cells. It is possible to use a variety selection and screening methods to identify genes and their functions. High-throughput screening technology has been developed to allow an array of all viable yeast gene deletion mutants to be screened for phenotypes and for regulators of gene expression. This chapter describes a protocol that has been used to screen a library of homozygous diploid yeast deletion strains to identify regulators of the meiosis-specific IME1 gene.

Cross-species global and subset gene expression profiling identifies genes involved in prostate cancer response to selenium

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Dhir Rajiv

2004-08-01

Full Text Available Abstract Background Gene expression technologies have the ability to generate vast amounts of data, yet there often resides only limited resources for subsequent validation studies. This necessitates the ability to perform sorting and prioritization of the output data. Previously described methodologies have used functional pathways or transcriptional regulatory grouping to sort genes for further study. In this paper we demonstrate a comparative genomics based method to leverage data from animal models to prioritize genes for validation. This approach allows one to develop a disease-based focus for the prioritization of gene data, a process that is essential for systems that lack significant functional pathway data yet have defined animal models. This method is made possible through the use of highly controlled spotted cDNA slide production and the use of comparative bioinformatics databases without the use of cross-species slide hybridizations. Results Using gene expression profiling we have demonstrated a similar whole transcriptome gene expression patterns in prostate cancer cells from human and rat prostate cancer cell lines both at baseline expression levels and after treatment with physiologic concentrations of the proposed chemopreventive agent Selenium. Using both the human PC3 and rat PAII prostate cancer cell lines have gone on to identify a subset of one hundred and fifty-four genes that demonstrate a similar level of differential expression to Selenium treatment in both species. Further analysis and data mining for two genes, the Insulin like Growth Factor Binding protein 3, and Retinoic X Receptor alpha, demonstrates an association with prostate cancer, functional pathway links, and protein-protein interactions that make these genes prime candidates for explaining the mechanism of Selenium's chemopreventive effect in prostate cancer. These genes are subsequently validated by western blots showing Selenium based induction and using

Co-Cultures of Pseudomonas aeruginosa and Roseobacter denitrificans Reveal Shifts in Gene Expression Levels Compared to Solo Cultures

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Crystal A. Conway

2012-01-01

Full Text Available Consistent biosynthesis of desired secondary metabolites (SMs from pure microbial cultures is often unreliable. In a proof-of-principle study to induce SM gene expression and production, we describe mixed “co-culturing” conditions and monitoring of messages via quantitative real-time PCR (qPCR. Gene expression of model bacterial strains (Pseudomonas aeruginosa PAO1 and Roseobacter denitrificans Och114 was analyzed in pure solo and mixed cocultures to infer the effects of interspecies interactions on gene expression in vitro, Two P. aeruginosa genes (PhzH coding for portions of the phenazine antibiotic pathway leading to pyocyanin (PCN and the RhdA gene for thiosulfate: cyanide sulfurtransferase (Rhodanese and two R. denitrificans genes (BetaLact for metallo-beta-lactamase and the DMSP gene for dimethylpropiothetin dethiomethylase were assessed for differential expression. Results showed that R. denitrificans DMSP and BetaLact gene expression became elevated in a mixed culture. In contrast, P. aeruginosa co-cultures with R. denitrificans or a third species did not increase target gene expression above control levels. This paper provides insight for better control of target SM gene expression in vitro and bypass complex genetic engineering manipulations.

Previously unidentified changes in renal cell carcinoma gene expression identified by parametric analysis of microarray data

International Nuclear Information System (INIS)

Lenburg, Marc E; Liou, Louis S; Gerry, Norman P; Frampton, Garrett M; Cohen, Herbert T; Christman, Michael F

2003-01-01

Renal cell carcinoma is a common malignancy that often presents as a metastatic-disease for which there are no effective treatments. To gain insights into the mechanism of renal cell carcinogenesis, a number of genome-wide expression profiling studies have been performed. Surprisingly, there is very poor agreement among these studies as to which genes are differentially regulated. To better understand this lack of agreement we profiled renal cell tumor gene expression using genome-wide microarrays (45,000 probe sets) and compare our analysis to previous microarray studies. We hybridized total RNA isolated from renal cell tumors and adjacent normal tissue to Affymetrix U133A and U133B arrays. We removed samples with technical defects and removed probesets that failed to exhibit sequence-specific hybridization in any of the samples. We detected differential gene expression in the resulting dataset with parametric methods and identified keywords that are overrepresented in the differentially expressed genes with the Fisher-exact test. We identify 1,234 genes that are more than three-fold changed in renal tumors by t-test, 800 of which have not been previously reported to be altered in renal cell tumors. Of the only 37 genes that have been identified as being differentially expressed in three or more of five previous microarray studies of renal tumor gene expression, our analysis finds 33 of these genes (89%). A key to the sensitivity and power of our analysis is filtering out defective samples and genes that are not reliably detected. The widespread use of sample-wise voting schemes for detecting differential expression that do not control for false positives likely account for the poor overlap among previous studies. Among the many genes we identified using parametric methods that were not previously reported as being differentially expressed in renal cell tumors are several oncogenes and tumor suppressor genes that likely play important roles in renal cell

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis

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Akira Ishikawa

2017-11-01

Full Text Available Large numbers of quantitative trait loci (QTL affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

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Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number

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Cooper James B

2010-03-01

Full Text Available Abstract Background Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the underlying structure of these natural datasets is often fuzzy, and the computational identification of data clusters generally requires knowledge about cluster number and geometry. Results We integrated strategies from machine learning, cartography, and graph theory into a new informatics method for automatically clustering self-organizing map ensembles of high-dimensional data. Our new method, called AutoSOME, readily identifies discrete and fuzzy data clusters without prior knowledge of cluster number or structure in diverse datasets including whole genome microarray data. Visualization of AutoSOME output using network diagrams and differential heat maps reveals unexpected variation among well-characterized cancer cell lines. Co-expression analysis of data from human embryonic and induced pluripotent stem cells using AutoSOME identifies >3400 up-regulated genes associated with pluripotency, and indicates that a recently identified protein-protein interaction network characterizing pluripotency was underestimated by a factor of four. Conclusions By effectively extracting important information from high-dimensional microarray data without prior knowledge or the need for data filtration, AutoSOME can yield systems-level insights from whole genome microarray expression studies. Due to its generality, this new method should also have practical utility for a variety of data-intensive applications, including the results of deep sequencing experiments. AutoSOME is available for download at http://jimcooperlab.mcdb.ucsb.edu/autosome.

Robust Nonnegative Matrix Factorization via Joint Graph Laplacian and Discriminative Information for Identifying Differentially Expressed Genes

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Ling-Yun Dai

2017-01-01

Full Text Available Differential expression plays an important role in cancer diagnosis and classification. In recent years, many methods have been used to identify differentially expressed genes. However, the recognition rate and reliability of gene selection still need to be improved. In this paper, a novel constrained method named robust nonnegative matrix factorization via joint graph Laplacian and discriminative information (GLD-RNMF is proposed for identifying differentially expressed genes, in which manifold learning and the discriminative label information are incorporated into the traditional nonnegative matrix factorization model to train the objective matrix. Specifically, L2,1-norm minimization is enforced on both the error function and the regularization term which is robust to outliers and noise in gene data. Furthermore, the multiplicative update rules and the details of convergence proof are shown for the new model. The experimental results on two publicly available cancer datasets demonstrate that GLD-RNMF is an effective method for identifying differentially expressed genes.

Gene Expression and the Diversity of Identified Neurons

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Buck, L.; Stein, R.; Palazzolo, M.; Anderson, D. J.; Axel, R.

1983-01-01

Nervous systems consist of diverse populations of neurons that are anatomically and functionally distinct. The diversity of neurons and the precision with which they are interconnected suggest that specific genes or sets of genes are activated in some neurons but not expressed in others. Experimentally, this problem may be considered at two levels. First, what is the total number of genes expressed in the brain, and how are they distributed among the different populations of neurons? Second, ...

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

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Uddin, Raihan; Singh, Shiva M

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they

Promotion of growth by Coenzyme Q10 is linked to gene expression in C. elegans.

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Fischer, Alexandra; Niklowitz, Petra; Menke, Thomas; Döring, Frank

2014-10-03

Coenzyme Q (CoQ, ubiquinone) is an essential component of the respiratory chain, a cofactor of pyrimidine biosynthesis and acts as an antioxidant in extra mitochondrial membranes. More recently CoQ has been identified as a modulator of apoptosis, inflammation and gene expression. CoQ deficient Caenorhabditis elegans clk-1 mutants show several phenotypes including a delayed postembryonic growth. Using wild type and two clk-1 mutants, here we established an experimental set-up to study the consequences of endogenous CoQ deficiency or exogenous CoQ supply on gene expression and growth. We found that a deficiency of endogenous CoQ synthesis down-regulates a cluster of genes that are important for growth (i.e., RNA polymerase II, eukaryotic initiation factor) and up-regulates oxidation reactions (i.e., cytochrome P450, superoxide dismutase) and protein interactions (i.e., F-Box proteins). Exogenous CoQ supply partially restores the expression of these genes as well as the growth retardation of CoQ deficient clk-1 mutants. On the other hand exogenous CoQ supply does not alter the expression of a further sub-set of genes. These genes are involved in metabolism (i.e., succinate dehydrogenase complex), cell signalling or synthesis of lectins. Thus, our work provides a comprehensive overview of genes which can be modulated in their expression by endogenous or exogenous CoQ. As growth retardation in CoQ deficiency is linked to the gene expression profile we suggest that CoQ promotes growth via gene expression. Copyright © 2014 Elsevier Inc. All rights reserved.

The functional landscape of mouse gene expression

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Zhang Wen

2004-12-01

Full Text Available Abstract Background Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. Results We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. Conclusions We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.

An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.

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Botía, Juan A; Vandrovcova, Jana; Forabosco, Paola; Guelfi, Sebastian; D'Sa, Karishma; Hardy, John; Lewis, Cathryn M; Ryten, Mina; Weale, Michael E

2017-04-12

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github.com/juanbot/km2gcn ). We assessed our method on networks created from UKBEC data (10 different human brain tissues), on networks created from GTEx data (42 human tissues, including 13 brain tissues), and on simulated networks derived from GTEx data. We observed substantially improved module properties, including: (1) few or zero misplaced genes; (2) increased counts of replicable clusters in alternate tissues (x3.1 on average); (3) improved enrichment of Gene Ontology terms (seen in 48/52 GCNs) (4) improved cell type enrichment signals (seen in 21/23 brain GCNs); and (5) more accurate partitions in simulated data according to a range of similarity indices. The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful.

Digital gene expression profiling of flax (Linum usitatissimum L.) stem peel identifies genes enriched in fiber-bearing phloem tissue.

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Guo, Yuan; Qiu, Caisheng; Long, Songhua; Chen, Ping; Hao, Dongmei; Preisner, Marta; Wang, Hui; Wang, Yufu

2017-08-30

To better understand the molecular mechanisms and gene expression characteristics associated with development of bast fiber cell within flax stem phloem, the gene expression profiling of flax stem peels and leaves were screened, using Illumina's Digital Gene Expression (DGE) analysis. Four DGE libraries (2 for stem peel and 2 for leaf), ranging from 6.7 to 9.2 million clean reads were obtained, which produced 7.0 million and 6.8 million mapped reads for flax stem peel and leave, respectively. By differential gene expression analysis, a total of 975 genes, of which 708 (73%) genes have protein-coding annotation, were identified as phloem enriched genes putatively involved in the processes of polysaccharide and cell wall metabolism. Differential expression genes (DEGs) was validated using quantitative RT-PCR, the expression pattern of all nine genes determined by qRT-PCR fitted in well with that obtained by sequencing analysis. Cluster and Gene Ontology (GO) analysis revealed that a large number of genes related to metabolic process, catalytic activity and binding category were expressed predominantly in the stem peels. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the phloem enriched genes suggested approximately 111 biological pathways. The large number of genes and pathways produced from DGE sequencing will expand our understanding of the complex molecular and cellular events in flax bast fiber development and provide a foundation for future studies on fiber development in other bast fiber crops. Copyright © 2017 Elsevier B.V. All rights reserved.

Gene Expression Analysis in Tubule Interstitial Compartments Reveals Candidate Agents for IgA Nephropathy

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Jinling Wang

2014-09-01

Full Text Available Background/Aims: Our aim was to explore the molecular mechanism underlying development of IgA nephropathy and discover candidate agents for IgA nephropathy. Methods: The differentially expressed genes (DEGs between patients with IgA nephropathy and normal controls were identified by the data of GSE35488 downloaded from GEO (Gene Expression Omnibus database. The co-expressed gene pairs among DEGs were screened to construct the gene-gene interaction network. Gene Ontology (GO enrichment analysis was performed to analyze the functions of DEGs. The biologically active small molecules capable of targeting IgA nephropathy were identified using the Connectivity Map (cMap database. Results: A total of 55 genes involved in response to organic substance, transcription factor activity and response to steroid hormone stimulus were identified to be differentially expressed in IgA nephropathy patients compared to healthy individuals. A network with 45 co-expressed gene pairs was constructed. DEGs in the network were significantly enriched in response to organic substance. Additionally, a group of small molecules were identified, such as doxorubicin and thapsigargin. Conclusion: Our work provided a systematic insight in understanding the mechanism of IgA nephropathy. Small molecules such as thapsigargin might be potential candidate agents for the treatment of IgA nephropathy.

MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer.

LENUS (Irish Health Repository)

Chang, Kah Hoong

2010-01-01

BACKGROUND: Advances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to quantify gene expression. Appropriate normalisation of RT-qPCR data using stably expressed reference genes is critical to ensure accurate and reliable results. Mi(cro)RNA expression profiles have been shown to be more accurate in disease classification than mRNA expression profiles. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in miRNA RT-qPCR studies. METHODS: We adopt and report a systematic approach to identify the most stable reference genes for miRNA expression studies by RT-qPCR in colorectal cancer (CRC). High-throughput miRNA profiling was performed on ten pairs of CRC and normal tissues. By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation. As such the stability of a panel of miRNAs was examined on 35 tumour and 39 normal tissues. The effects of normalisers on the relative quantity of established oncogenic (miR-21 and miR-31) and tumour suppressor (miR-143 and miR-145) target miRNAs were assessed. RESULTS: In the array experiment, miR-26a, miR-345, miR-425 and miR-454 were identified as having expression profiles closest to the global mean. From a panel of six miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) and two small nucleolar RNA genes (RNU48 and Z30), miR-16 and miR-345 were identified as the most stably expressed reference genes. The combined use of miR-16 and miR-345 to normalise expression data enabled detection of a significant dysregulation of all four target miRNAs between tumour and normal colorectal tissue. CONCLUSIONS: Our study demonstrates that the top six most

MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer

LENUS (Irish Health Repository)

Chang, Kah Hoong

2010-04-29

Abstract Background Advances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to quantify gene expression. Appropriate normalisation of RT-qPCR data using stably expressed reference genes is critical to ensure accurate and reliable results. Mi(cro)RNA expression profiles have been shown to be more accurate in disease classification than mRNA expression profiles. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in miRNA RT-qPCR studies. Methods We adopt and report a systematic approach to identify the most stable reference genes for miRNA expression studies by RT-qPCR in colorectal cancer (CRC). High-throughput miRNA profiling was performed on ten pairs of CRC and normal tissues. By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation. As such the stability of a panel of miRNAs was examined on 35 tumour and 39 normal tissues. The effects of normalisers on the relative quantity of established oncogenic (miR-21 and miR-31) and tumour suppressor (miR-143 and miR-145) target miRNAs were assessed. Results In the array experiment, miR-26a, miR-345, miR-425 and miR-454 were identified as having expression profiles closest to the global mean. From a panel of six miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) and two small nucleolar RNA genes (RNU48 and Z30), miR-16 and miR-345 were identified as the most stably expressed reference genes. The combined use of miR-16 and miR-345 to normalise expression data enabled detection of a significant dysregulation of all four target miRNAs between tumour and normal colorectal tissue. Conclusions Our study demonstrates that the top six most

Expression profiling identifies genes involved in neoplastic transformation of serous ovarian cancer

International Nuclear Information System (INIS)

Merritt, Melissa A; Parsons, Peter G; Newton, Tanya R; Martyn, Adam C; Webb, Penelope M; Green, Adèle C; Papadimos, David J; Boyle, Glen M

2009-01-01

The malignant potential of serous ovarian tumors, the most common ovarian tumor subtype, varies from benign to low malignant potential (LMP) tumors to frankly invasive cancers. Given the uncertainty about the relationship between these different forms, we compared their patterns of gene expression. Expression profiling was carried out on samples of 7 benign, 7 LMP and 28 invasive (moderate and poorly differentiated) serous tumors and four whole normal ovaries using oligonucleotide microarrays representing over 21,000 genes. We identified 311 transcripts that distinguished invasive from benign tumors, and 20 transcripts that were significantly differentially expressed between invasive and LMP tumors at p < 0.01 (with multiple testing correction). Five genes that were differentially expressed between invasive and either benign or normal tissues were validated by real time PCR in an independent panel of 46 serous tumors (4 benign, 7 LMP, 35 invasive). Overexpression of SLPI and WNT7A and down-regulation of C6orf31, PDGFRA and GLTSCR2 were measured in invasive and LMP compared with benign and normal tissues. Over-expression of WNT7A in an ovarian cancer cell line led to increased migration and invasive capacity. These results highlight several genes that may play an important role across the spectrum of serous ovarian tumorigenesis

Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

Science.gov (United States)

Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

2012-07-15

Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of EOperon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

DEFF Research Database (Denmark)

Kogelman, Lisette; Cirera Salicio, Susanna; Zhernakova, Daria V.

2014-01-01

interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model...... (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. Results WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P ... the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using...

Ethylene-Related Gene Expression Networks in Wood Formation

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Carolin Seyfferth

2018-03-01

Full Text Available Thickening of tree stems is the result of secondary growth, accomplished by the meristematic activity of the vascular cambium. Secondary growth of the stem entails developmental cascades resulting in the formation of secondary phloem outwards and secondary xylem (i.e., wood inwards of the stem. Signaling and transcriptional reprogramming by the phytohormone ethylene modifies cambial growth and cell differentiation, but the molecular link between ethylene and secondary growth remains unknown. We addressed this shortcoming by analyzing expression profiles and co-expression networks of ethylene pathway genes using the AspWood transcriptome database which covers all stages of secondary growth in aspen (Populus tremula stems. ACC synthase expression suggests that the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC is synthesized during xylem expansion and xylem cell maturation. Ethylene-mediated transcriptional reprogramming occurs during all stages of secondary growth, as deduced from AspWood expression profiles of ethylene-responsive genes. A network centrality analysis of the AspWood dataset identified EIN3D and 11 ERFs as hubs. No overlap was found between the co-expressed genes of the EIN3 and ERF hubs, suggesting target diversification and hence independent roles for these transcription factor families during normal wood formation. The EIN3D hub was part of a large co-expression gene module, which contained 16 transcription factors, among them several new candidates that have not been earlier connected to wood formation and a VND-INTERACTING 2 (VNI2 homolog. We experimentally demonstrated Populus EIN3D function in ethylene signaling in Arabidopsis thaliana. The ERF hubs ERF118 and ERF119 were connected on the basis of their expression pattern and gene co-expression module composition to xylem cell expansion and secondary cell wall formation, respectively. We hereby establish data resources for ethylene-responsive genes and

Global Gene-Expression Analysis to Identify Differentially Expressed Genes Critical for the Heat Stress Response in Brassica rapa.

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Xiangshu Dong

Full Text Available Genome-wide dissection of the heat stress response (HSR is necessary to overcome problems in crop production caused by global warming. To identify HSR genes, we profiled gene expression in two Chinese cabbage inbred lines with different thermotolerances, Chiifu and Kenshin. Many genes exhibited >2-fold changes in expression upon exposure to 0.5- 4 h at 45°C (high temperature, HT: 5.2% (2,142 genes in Chiifu and 3.7% (1,535 genes in Kenshin. The most enriched GO (Gene Ontology items included 'response to heat', 'response to reactive oxygen species (ROS', 'response to temperature stimulus', 'response to abiotic stimulus', and 'MAPKKK cascade'. In both lines, the genes most highly induced by HT encoded small heat shock proteins (Hsps and heat shock factor (Hsf-like proteins such as HsfB2A (Bra029292, whereas high-molecular weight Hsps were constitutively expressed. Other upstream HSR components were also up-regulated: ROS-scavenging genes like glutathione peroxidase 2 (BrGPX2, Bra022853, protein kinases, and phosphatases. Among heat stress (HS marker genes in Arabidopsis, only exportin 1A (XPO1A (Bra008580, Bra006382 can be applied to B. rapa for basal thermotolerance (BT and short-term acquired thermotolerance (SAT gene. CYP707A3 (Bra025083, Bra021965, which is involved in the dehydration response in Arabidopsis, was associated with membrane leakage in both lines following HS. Although many transcription factors (TF genes, including DREB2A (Bra005852, were involved in HS tolerance in both lines, Bra024224 (MYB41 and Bra021735 (a bZIP/AIR1 [Anthocyanin-Impaired-Response-1] were specific to Kenshin. Several candidate TFs involved in thermotolerance were confirmed as HSR genes by real-time PCR, and these assignments were further supported by promoter analysis. Although some of our findings are similar to those obtained using other plant species, clear differences in Brassica rapa reveal a distinct HSR in this species. Our data could also provide a

Effect of co-culture with enterocinogenic E. faecium on L. monocytogenes key virulence gene expression

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Eleftherios H. Drosinos

2016-08-01

Full Text Available The aim of the present study was to assess the expression of key virulence genes during co-culture of L. monocytogenes with a bacteriocinogenic E. faecium strain in liquid growth medium. For that purpose, BHI broth was inoculated with 7 log CFU·mL–1 L. monocytogenes and 4, 5 or 6 log CFU·mL–1 E. faecium. Sampling took place after 8 and 24 h of incubation, corresponding to the maximum and minimum of enterocin production, respectively. The RNA was extracted, stabilized and expression of prfA, sigB, hly, plcA, plcB, inlA, inlB, inlC and inlJ, was assessed by RT-qPCR. Most of the genes were downregulated during co-culture at 5 °C. Moreover, a statistically significant effect of the inoculum level was evident in most of the cases. On the contrary, no effect on the transcription level of most of the genes was observed during co-culture at 37 °C.

GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets.

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John Patrick Mpindi

Full Text Available BACKGROUND: Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type ('outlier genes', a hallmark of potential oncogenes. METHODOLOGY: A new statistical method (the gene tissue index, GTI was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29 of these genes, and 17 of these 19 genes (90% showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target. CONCLUSIONS/SIGNIFICANCE: Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is

Transcriptional profiling identifies differentially expressed genes in developing turkey skeletal muscle

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Velleman Sandra G

2011-03-01

Full Text Available Abstract Background Skeletal muscle growth and development from embryo to adult consists of a series of carefully regulated changes in gene expression. Understanding these developmental changes in agriculturally important species is essential to the production of high quality meat products. For example, consumer demand for lean, inexpensive meat products has driven the turkey industry to unprecedented production through intensive genetic selection. However, achievements of increased body weight and muscle mass have been countered by an increased incidence of myopathies and meat quality defects. In a previous study, we developed and validated a turkey skeletal muscle-specific microarray as a tool for functional genomics studies. The goals of the current study were to utilize this microarray to elucidate functional pathways of genes responsible for key events in turkey skeletal muscle development and to compare differences in gene expression between two genetic lines of turkeys. To achieve these goals, skeletal muscle samples were collected at three critical stages in muscle development: 18d embryo (hyperplasia, 1d post-hatch (shift from myoblast-mediated growth to satellite cell-modulated growth by hypertrophy, and 16wk (market age from two genetic lines: a randombred control line (RBC2 maintained without selection pressure, and a line (F selected from the RBC2 line for increased 16wk body weight. Array hybridizations were performed in two experiments: Experiment 1 directly compared the developmental stages within genetic line, while Experiment 2 directly compared the two lines within each developmental stage. Results A total of 3474 genes were differentially expressed (false discovery rate; FDR Conclusions The current study identified gene pathways and uncovered novel genes important in turkey muscle growth and development. Future experiments will focus further on several of these candidate genes and the expression and mechanism of action of

Detecting microRNA activity from gene expression data

LENUS (Irish Health Repository)

Madden, Stephen F

2010-05-18

Abstract Background MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. Results Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. Conclusions We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

Detecting microRNA activity from gene expression data.

LENUS (Irish Health Repository)

Madden, Stephen F

2010-01-01

BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. CONCLUSIONS: We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

Cloning and expression analysis of cinnamoyl-CoA reductase (CCR) genes in sorghum.

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Li, Jieqin; Fan, Feifei; Wang, Lihua; Zhan, Qiuwen; Wu, Peijin; Du, Junli; Yang, Xiaocui; Liu, Yanlong

2016-01-01

Cinnamoyl-CoA reductase (CCR) is the first enzyme in the monolignol-specific branch of the lignin biosynthetic pathway. In this research, three sorghum CCR genes including SbCCR1, SbCCR2-1 and SbCCR2-2 were cloned and characterized. Analyses of the structure and phylogeny of the three CCR genes showed evolutionary conservation of the functional domains and divergence of function. Transient expression assays in Nicotiana benthamiana leaves demonstrated that the three CCR proteins were localized in the cytoplasm. The expression analysis showed that the three CCR genes were induced by drought. But in 48 h, the expression levels of SbCCR1 and SbCCR2-2 did not differ between CK and the drought treatment; while the expression level of SbCCR2-1 in the drought treatment was higher than in CK. The expression of the SbCCR1 and SbCCR2-1 genes was not induced by sorghum aphid [Melanaphis sacchari (Zehntner)] attack, but SbCCR2-2 was significantly induced by sorghum aphid attack. It is suggested that SbCCR2-2 is involved in the process of pest defense. Absolute quantitative real-time PCR revealed that the three CCR genes were mainly expressed in lignin deposition organs. The gene copy number of SbCCR1 was significantly higher than those of SbCCR2-1 and SbCCR2-2 in the tested tissues, especially in stem. The results provide new insight into the functions of the three CCR genes in sorghum.

Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases.

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Kai Wang

2009-12-01

Full Text Available Co-expression networks are routinely used to study human diseases like obesity and diabetes. Systematic comparison of these networks between species has the potential to elucidate common mechanisms that are conserved between human and rodent species, as well as those that are species-specific characterizing evolutionary plasticity. We developed a semi-parametric meta-analysis approach for combining gene-gene co-expression relationships across expression profile datasets from multiple species. The simulation results showed that the semi-parametric method is robust against noise. When applied to human, mouse, and rat liver co-expression networks, our method out-performed existing methods in identifying gene pairs with coherent biological functions. We identified a network conserved across species that highlighted cell-cell signaling, cell-adhesion and sterol biosynthesis as main biological processes represented in genome-wide association study candidate gene sets for blood lipid levels. We further developed a heterogeneity statistic to test for network differences among multiple datasets, and demonstrated that genes with species-specific interactions tend to be under positive selection throughout evolution. Finally, we identified a human-specific sub-network regulated by RXRG, which has been validated to play a different role in hyperlipidemia and Type 2 diabetes between human and mouse. Taken together, our approach represents a novel step forward in integrating gene co-expression networks from multiple large scale datasets to leverage not only common information but also differences that are dataset-specific.

Gene expression profiling reveals multiple toxicity endpoints induced by hepatotoxicants

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Huang Qihong; Jin Xidong; Gaillard, Elias T.; Knight, Brian L.; Pack, Franklin D.; Stoltz, James H.; Jayadev, Supriya; Blanchard, Kerry T

2004-05-18

Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate gene expression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1 mg/kg per day for 1, 7 and 14 days), methapyrilene (100 mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic gene expression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of gene expression data was able to provide a clear distinction of each compound, suggesting that gene expression data can be used to discern different hepatotoxic agents and toxicity endpoints. Gene expression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and

A Genome-Wide Association Study for Culm Cellulose Content in Barley Reveals Candidate Genes Co-Expressed with Members of the CELLULOSE SYNTHASE A Gene Family

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Houston, Kelly; Burton, Rachel A.; Sznajder, Beata; Rafalski, Antoni J.; Dhugga, Kanwarpal S.; Mather, Diane E.; Taylor, Jillian; Steffenson, Brian J.; Waugh, Robbie; Fincher, Geoffrey B.

2015-01-01

Cellulose is a fundamentally important component of cell walls of higher plants. It provides a scaffold that allows the development and growth of the plant to occur in an ordered fashion. Cellulose also provides mechanical strength, which is crucial for both normal development and to enable the plant to withstand both abiotic and biotic stresses. We quantified the cellulose concentration in the culm of 288 two – rowed and 288 six – rowed spring type barley accessions that were part of the USDA funded barley Coordinated Agricultural Project (CAP) program in the USA. When the population structure of these accessions was analysed we identified six distinct populations, four of which we considered to be comprised of a sufficient number of accessions to be suitable for genome-wide association studies (GWAS). These lines had been genotyped with 3072 SNPs so we combined the trait and genetic data to carry out GWAS. The analysis allowed us to identify regions of the genome containing significant associations between molecular markers and cellulose concentration data, including one region cross-validated in multiple populations. To identify candidate genes we assembled the gene content of these regions and used these to query a comprehensive RNA-seq based gene expression atlas. This provided us with gene annotations and associated expression data across multiple tissues, which allowed us to formulate a supported list of candidate genes that regulate cellulose biosynthesis. Several regions identified by our analysis contain genes that are co-expressed with CELLULOSE SYNTHASE A (HvCesA) across a range of tissues and developmental stages. These genes are involved in both primary and secondary cell wall development. In addition, genes that have been previously linked with cellulose synthesis by biochemical methods, such as HvCOBRA, a gene of unknown function, were also associated with cellulose levels in the association panel. Our analyses provide new insights into the

Expression and functional assessment of candidate type 2 diabetes susceptibility genes identify four new genes contributing to human insulin secretion

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Fatou K. Ndiaye

2017-06-01

Full Text Available Objectives: Genome-wide association studies (GWAS have identified >100 loci independently contributing to type 2 diabetes (T2D risk. However, translational implications for precision medicine and for the development of novel treatments have been disappointing, due to poor knowledge of how these loci impact T2D pathophysiology. Here, we aimed to measure the expression of genes located nearby T2D associated signals and to assess their effect on insulin secretion from pancreatic beta cells. Methods: The expression of 104 candidate T2D susceptibility genes was measured in a human multi-tissue panel, through PCR-free expression assay. The effects of the knockdown of beta-cell enriched genes were next investigated on insulin secretion from the human EndoC-βH1 beta-cell line. Finally, we performed RNA-sequencing (RNA-seq so as to assess the pathways affected by the knockdown of the new genes impacting insulin secretion from EndoC-βH1, and we analyzed the expression of the new genes in mouse models with altered pancreatic beta-cell function. Results: We found that the candidate T2D susceptibility genes' expression is significantly enriched in pancreatic beta cells obtained by laser capture microdissection or sorted by flow cytometry and in EndoC-βH1 cells, but not in insulin sensitive tissues. Furthermore, the knockdown of seven T2D-susceptibility genes (CDKN2A, GCK, HNF4A, KCNK16, SLC30A8, TBC1D4, and TCF19 with already known expression and/or function in beta cells changed insulin secretion, supporting our functional approach. We showed first evidence for a role in insulin secretion of four candidate T2D-susceptibility genes (PRC1, SRR, ZFAND3, and ZFAND6 with no previous knowledge of presence and function in beta cells. RNA-seq in EndoC-βH1 cells with decreased expression of PRC1, SRR, ZFAND6, or ZFAND3 identified specific gene networks related to T2D pathophysiology. Finally, a positive correlation between the expression of Ins2 and the

Gene expression meta-analysis identifies chromosomal regions involved in ovarian cancer survival

DEFF Research Database (Denmark)

Thomassen, Mads; Jochumsen, Kirsten M; Mogensen, Ole

2009-01-01

the relation of gene expression and chromosomal position to identify chromosomal regions of importance for early recurrence of ovarian cancer. By use of *Gene Set Enrichment Analysis*, we have ranked chromosomal regions according to their association to survival. Over-representation analysis including 1...... using death (P = 0.015) and recurrence (P = 0.002) as outcome. The combined mutation score is strongly associated to upregulation of several growth factor pathways....

, , , , , and Gene Expression in Single- and Co-cultured Bovine Satellite Cells and Intramuscular Preadipocytes Treated with Palmitic, Stearic, Oleic, and Linoleic Acid

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S. H. Choi

2015-03-01

Full Text Available We previously demonstrated that bovine subcutaneous preadipocytes promote adipogenic gene expression in muscle satellite cells in a co-culture system. Herein we hypothesize that saturated fatty acids would promote adipogenic/lipogenic gene expression, whereas mono- and polyunsaturated fatty acids would have the opposite effect. Bovine semimembranosus satellite cells (BSC and intramuscular preadipocytes (IPA were isolated from crossbred steers and cultured with 10% fetal bovine serum (FBS/Dulbecco’s Modified Eagle Medium (DMEM and 1% antibiotics during the 3-d proliferation period. After proliferation, cells were treated for 3 d with 3% horse serum/DMEM (BSC or 5% FBS/DMEM (IPA with antibiotics. Media also contained 10 μg/mL insulin and 10 μg/mL pioglitazone. Subsequently, differentiating BSC and IPA were cultured in their respective media with 40 μM palmitic, stearic, oleic, or linoleic acid for 4 d. Finally, BSC and IPA were single- or co-cultured for an additional 2 h. All fatty acid treatments increased (p = 0.001 carnitine palmitoyltransferase-1 beta (CPT1β gene expression, but the increase in CPT1β gene expression was especially pronounced in IPA incubated with palmitic and stearic acid (6- to 17- fold increases. Oleic and linoleic acid decreased (p = 0.001 stearoyl-CoA desaturase (SCD gene expression over 80% in both BSC and IPA. Conversely, palmitic and stearic acid increased SCD gene expression three fold in co-cultured in IPA, and stearic acid increased AMPKα gene expression in single- and co-cultured BSC and IPA. Consistent with our hypothesis, saturated fatty acids, especially stearic acid, promoted adipogenic and lipogenic gene expression, whereas unsaturated fatty acids decreased expression of those genes associated with fatty acid metabolism.

Network-Based Method for Identifying Co- Regeneration Genes in Bone, Dentin, Nerve and Vessel Tissues.

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Chen, Lei; Pan, Hongying; Zhang, Yu-Hang; Feng, Kaiyan; Kong, XiangYin; Huang, Tao; Cai, Yu-Dong

2017-10-02

Bone and dental diseases are serious public health problems. Most current clinical treatments for these diseases can produce side effects. Regeneration is a promising therapy for bone and dental diseases, yielding natural tissue recovery with few side effects. Because soft tissues inside the bone and dentin are densely populated with nerves and vessels, the study of bone and dentin regeneration should also consider the co-regeneration of nerves and vessels. In this study, a network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein-protein interactions. Three procedures were applied in the network-based method. The first procedure, searching, sought the shortest paths connecting regeneration genes of one tissue type with regeneration genes of other tissues, thereby extracting possible co-regeneration genes. The second procedure, testing, employed a permutation test to evaluate whether possible genes were false discoveries; these genes were excluded by the testing procedure. The last procedure, screening, employed two rules, the betweenness ratio rule and interaction score rule, to select the most essential genes. A total of seventeen genes were inferred by the method, which were deemed to contribute to co-regeneration of at least two tissues. All these seventeen genes were extensively discussed to validate the utility of the method.

A contribution to the study of plant development evolution based on gene co-expression networks

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Francisco J. Romero-Campero

2013-08-01

Full Text Available Phototrophic eukaryotes are among the most successful organisms on Earth due to their unparalleled efficiency at capturing light energy and fixing carbon dioxide to produce organic molecules. A conserved and efficient network of light-dependent regulatory modules could be at the bases of this success. This regulatory system conferred early advantages to phototrophic eukaryotes that allowed for specialization, complex developmental processes and modern plant characteristics. We have studied light-dependent gene regulatory modules from algae to plants employing integrative-omics approaches based on gene co-expression networks. Our study reveals some remarkably conserved ways in which eukaryotic phototrophs deal with day length and light signaling. Here we describe how a family of Arabidopsis transcription factors involved in photoperiod response has evolved from a single algal gene according to the innovation, amplification and divergence theory of gene evolution by duplication. These modifications of the gene co-expression networks from the ancient unicellular green algae Chlamydomonas reinhardtii to the modern brassica Arabidopsis thaliana may hint on the evolution and specialization of plants and other organisms.

Suppression subtractive hybridization identified differentially expressed genes in lung adenocarcinoma: ERGIC3 as a novel lung cancer-related gene

International Nuclear Information System (INIS)

Wu, Mingsong; Tu, Tao; Huang, Yunchao; Cao, Yi

2013-01-01

To understand the carcinogenesis caused by accumulated genetic and epigenetic alterations and seek novel biomarkers for various cancers, studying differentially expressed genes between cancerous and normal tissues is crucial. In the study, two cDNA libraries of lung cancer were constructed and screened for identification of differentially expressed genes. Two cDNA libraries of differentially expressed genes were constructed using lung adenocarcinoma tissue and adjacent nonmalignant lung tissue by suppression subtractive hybridization. The data of the cDNA libraries were then analyzed and compared using bioinformatics analysis. Levels of mRNA and protein were measured by quantitative real-time polymerase chain reaction (q-RT-PCR) and western blot respectively, as well as expression and localization of proteins were determined by immunostaining. Gene functions were investigated using proliferation and migration assays after gene silencing and gene over-expression. Two libraries of differentially expressed genes were obtained. The forward-subtracted library (FSL) and the reverse-subtracted library (RSL) contained 177 and 59 genes, respectively. Bioinformatic analysis demonstrated that these genes were involved in a wide range of cellular functions. The vast majority of these genes were newly identified to be abnormally expressed in lung cancer. In the first stage of the screening for 16 genes, we compared lung cancer tissues with their adjacent non-malignant tissues at the mRNA level, and found six genes (ERGIC3, DDR1, HSP90B1, SDC1, RPSA, and LPCAT1) from the FSL were significantly up-regulated while two genes (GPX3 and TIMP3) from the RSL were significantly down-regulated (P < 0.05). The ERGIC3 protein was also over-expressed in lung cancer tissues and cultured cells, and expression of ERGIC3 was correlated with the differentiated degree and histological type of lung cancer. The up-regulation of ERGIC3 could promote cellular migration and proliferation in vitro. The

Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences.

Science.gov (United States)

Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki

2010-06-01

Tests of differentially expressed genes (DEGs) from microarray experiments are based on the null hypothesis that genes that are irrelevant to the phenotype/stimulus are expressed equally in the target and control samples. However, this strict hypothesis is not always true, as there can be several transcriptomic background differences between target and control samples, including different cell/tissue types, different cell cycle stages and different biological donors. These differences lead to increased false positives, which have little biological/medical significance. In this article, we propose a statistical framework to identify DEGs between target and control samples from expression microarray data allowing transcriptomic background differences between these samples by introducing a modified null hypothesis that the gene expression background difference is normally distributed. We use an iterative procedure to perform robust estimation of the null hypothesis and identify DEGs as outliers. We evaluated our method using our own triplicate microarray experiment, followed by validations with reverse transcription-polymerase chain reaction (RT-PCR) and on the MicroArray Quality Control dataset. The evaluations suggest that our technique (i) results in less false positive and false negative results, as measured by the degree of agreement with RT-PCR of the same samples, (ii) can be applied to different microarray platforms and results in better reproducibility as measured by the degree of DEG identification concordance both intra- and inter-platforms and (iii) can be applied efficiently with only a few microarray replicates. Based on these evaluations, we propose that this method not only identifies more reliable and biologically/medically significant DEG, but also reduces the power-cost tradeoff problem in the microarray field. Source code and binaries freely available for download at http://comonca.org.cn/fdca/resources/softwares/deg.zip.

APRIL is a novel clinical chemo-resistance biomarker in colorectal adenocarcinoma identified by gene expression profiling

International Nuclear Information System (INIS)

Petty, Russell D; Wang, Weiguang; Gilbert, Fiona; Semple, Scot; Collie-Duguid, Elaina SR; Samuel, Leslie M; Murray, Graeme I; MacDonald, Graham; O'Kelly, Terrence; Loudon, Malcolm; Binnie, Norman; Aly, Emad; McKinlay, Aileen

2009-01-01

5-Fluorouracil(5FU) and oral analogues, such as capecitabine, remain one of the most useful agents for the treatment of colorectal adenocarcinoma. Low toxicity and convenience of administration facilitate use, however clinical resistance is a major limitation. Investigation has failed to fully explain the molecular mechanisms of resistance and no clinically useful predictive biomarkers for 5FU resistance have been identified. We investigated the molecular mechanisms of clinical 5FU resistance in colorectal adenocarcinoma patients in a prospective biomarker discovery project utilising gene expression profiling. The aim was to identify novel 5FU resistance mechanisms and qualify these as candidate biomarkers and therapeutic targets. Putative treatment specific gene expression changes were identified in a transcriptomics study of rectal adenocarcinomas, biopsied and profiled before and after pre-operative short-course radiotherapy or 5FU based chemo-radiotherapy, using microarrays. Tumour from untreated controls at diagnosis and resection identified treatment-independent gene expression changes. Candidate 5FU chemo-resistant genes were identified by comparison of gene expression data sets from these clinical specimens with gene expression signatures from our previous studies of colorectal cancer cell lines, where parental and daughter lines resistant to 5FU were compared. A colorectal adenocarcinoma tissue microarray (n = 234, resected tumours) was used as an independent set to qualify candidates thus identified. APRIL/TNFSF13 mRNA was significantly upregulated following 5FU based concurrent chemo-radiotherapy and in 5FU resistant colorectal adenocarcinoma cell lines but not in radiotherapy alone treated colorectal adenocarcinomas. Consistent withAPRIL's known function as an autocrine or paracrine secreted molecule, stromal but not tumour cell protein expression by immunohistochemistry was correlated with poor prognosis (p = 0.019) in the independent set

Identifying Stable Reference Genes for qRT-PCR Normalisation in Gene Expression Studies of Narrow-Leafed Lupin (Lupinus angustifolius L..

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Candy M Taylor

Full Text Available Quantitative Reverse Transcription PCR (qRT-PCR is currently one of the most popular, high-throughput and sensitive technologies available for quantifying gene expression. Its accurate application depends heavily upon normalisation of gene-of-interest data with reference genes that are uniformly expressed under experimental conditions. The aim of this study was to provide the first validation of reference genes for Lupinus angustifolius (narrow-leafed lupin, a significant grain legume crop using a selection of seven genes previously trialed as reference genes for the model legume, Medicago truncatula. In a preliminary evaluation, the seven candidate reference genes were assessed on the basis of primer specificity for their respective targeted region, PCR amplification efficiency, and ability to discriminate between cDNA and gDNA. Following this assessment, expression of the three most promising candidates [Ubiquitin C (UBC, Helicase (HEL, and Polypyrimidine tract-binding protein (PTB] was evaluated using the NormFinder and RefFinder statistical algorithms in two narrow-leafed lupin lines, both with and without vernalisation treatment, and across seven organ types (cotyledons, stem, leaves, shoot apical meristem, flowers, pods and roots encompassing three developmental stages. UBC was consistently identified as the most stable candidate and has sufficiently uniform expression that it may be used as a sole reference gene under the experimental conditions tested here. However, as organ type and developmental stage were associated with greater variability in relative expression, it is recommended using UBC and HEL as a pair to achieve optimal normalisation. These results highlight the importance of rigorously assessing candidate reference genes for each species across a diverse range of organs and developmental stages. With emerging technologies, such as RNAseq, and the completion of valuable transcriptome data sets, it is possible that other

Extensive co-operation between the Epstein-Barr virus EBNA3 proteins in the manipulation of host gene expression and epigenetic chromatin modification.

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Robert E White

2010-11-01

Full Text Available Epstein-Barr virus (EBV is able to drive the transformation of B-cells, resulting in the generation of lymphoblastoid cell lines (LCLs in vitro. EBV nuclear proteins EBNA3A and EBNA3C are necessary for efficient transformation, while EBNA3B is dispensable. We describe a transcriptome analysis of BL31 cells infected with a series of EBNA3-knockout EBVs, including one deleted for all three EBNA3 genes. Using Affymetrix Exon 1.0 ST microarrays analysed with the MMBGX algorithm, we have identified over 1000 genes whose regulation by EBV requires one of the EBNA3s. Remarkably, a third of the genes identified require more than one EBNA3 for their regulation, predominantly EBNA3C co-operating with either EBNA3B, EBNA3A or both. The microarray was validated by real-time PCR, while ChIP analysis of a selection of co-operatively repressed promoters indicates a role for polycomb group complexes. Targets include genes involved in apoptosis, cell migration and B-cell differentiation, and show a highly significant but subtle alteration in genes involved in mitosis. In order to assess the relevance of the BL31 system to LCLs, we analysed the transcriptome of a set of EBNA3B knockout (3BKO LCLs. Around a third of the genes whose expression level in LCLs was altered in the absence of EBNA3B were also altered in 3BKO-BL31 cell lines.Among these are TERT and TCL1A, implying that EBV-induced changes in the expression of these genes are not required for B-cell transformation. We also identify 26 genes that require both EBNA3A and EBNA3B for their regulation in LCLs. Together, this shows the complexity of the interaction between EBV and its host, whereby multiple EBNA3 proteins co-operate to modulate the behaviour of the host cell.

Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

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Karacali Bilge

2007-10-01

Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

Individual co-variation between viral RNA load and gene expression reveals novel host factors during early dengue virus infection of the Aedes aegypti midgut.

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Vincent Raquin

2017-12-01

Full Text Available Dengue virus (DENV causes more human infections than any other mosquito-borne virus. The current lack of antiviral strategies has prompted genome-wide screens for host genes that are required for DENV infectivity. Earlier transcriptomic studies that identified DENV host factors in the primary vector Aedes aegypti used inbred laboratory colonies and/or pools of mosquitoes that erase individual variation. Here, we performed transcriptome sequencing on individual midguts in a field-derived Ae. aegypti population to identify new candidate host factors modulating DENV replication. We analyzed the transcriptomic data using an approach that accounts for individual co-variation between viral RNA load and gene expression. This approach generates a prediction about the agonist or antagonist effect of candidate genes on DENV replication based on the sign of the correlation between gene expression and viral RNA load. Using this method, we identified 39 candidate genes that went undetected by conventional pairwise comparison of gene expression levels between DENV-infected midguts and uninfected controls. Only four candidate genes were detected by both methods, emphasizing their complementarity. We demonstrated the value of our approach by functional validation of a candidate agonist gene encoding a sterol regulatory element-binding protein (SREBP, which was identified by correlation analysis but not by pairwise comparison. We confirmed that SREBP promotes DENV infection in the midgut by RNAi-mediated gene knockdown in vivo. We suggest that our approach for transcriptomic analysis can empower genome-wide screens for potential agonist or antagonist factors by leveraging inter-individual variation in gene expression. More generally, this method is applicable to a wide range of phenotypic traits displaying inter-individual variation.

Phylogenomic analysis of UDP glycosyltransferase 1 multigene family in Linum usitatissimum identified genes with varied expression patterns

Science.gov (United States)

2012-01-01

Background The glycosylation process, catalyzed by ubiquitous glycosyltransferase (GT) family enzymes, is a prevalent modification of plant secondary metabolites that regulates various functions such as hormone homeostasis, detoxification of xenobiotics and biosynthesis and storage of secondary metabolites. Flax (Linum usitatissimum L.) is a commercially grown oilseed crop, important because of its essential fatty acids and health promoting lignans. Identification and characterization of UDP glycosyltransferase (UGT) genes from flax could provide valuable basic information about this important gene family and help to explain the seed specific glycosylated metabolite accumulation and other processes in plants. Plant genome sequencing projects are useful to discover complexity within this gene family and also pave way for the development of functional genomics approaches. Results Taking advantage of the newly assembled draft genome sequence of flax, we identified 137 UDP glycosyltransferase (UGT) genes from flax using a conserved signature motif. Phylogenetic analysis of these protein sequences clustered them into 14 major groups (A-N). Expression patterns of these genes were investigated using publicly available expressed sequence tag (EST), microarray data and reverse transcription quantitative real time PCR (RT-qPCR). Seventy-three per cent of these genes (100 out of 137) showed expression evidence in 15 tissues examined and indicated varied expression profiles. The RT-qPCR results of 10 selected genes were also coherent with the digital expression analysis. Interestingly, five duplicated UGT genes were identified, which showed differential expression in various tissues. Of the seven intron loss/gain positions detected, two intron positions were conserved among most of the UGTs, although a clear relationship about the evolution of these genes could not be established. Comparison of the flax UGTs with orthologs from four other sequenced dicot genomes indicated that

Phylogenomic analysis of UDP glycosyltransferase 1 multigene family in Linum usitatissimum identified genes with varied expression patterns

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Barvkar Vitthal T

2012-05-01

Full Text Available Abstract Background The glycosylation process, catalyzed by ubiquitous glycosyltransferase (GT family enzymes, is a prevalent modification of plant secondary metabolites that regulates various functions such as hormone homeostasis, detoxification of xenobiotics and biosynthesis and storage of secondary metabolites. Flax (Linum usitatissimum L. is a commercially grown oilseed crop, important because of its essential fatty acids and health promoting lignans. Identification and characterization of UDP glycosyltransferase (UGT genes from flax could provide valuable basic information about this important gene family and help to explain the seed specific glycosylated metabolite accumulation and other processes in plants. Plant genome sequencing projects are useful to discover complexity within this gene family and also pave way for the development of functional genomics approaches. Results Taking advantage of the newly assembled draft genome sequence of flax, we identified 137 UDP glycosyltransferase (UGT genes from flax using a conserved signature motif. Phylogenetic analysis of these protein sequences clustered them into 14 major groups (A-N. Expression patterns of these genes were investigated using publicly available expressed sequence tag (EST, microarray data and reverse transcription quantitative real time PCR (RT-qPCR. Seventy-three per cent of these genes (100 out of 137 showed expression evidence in 15 tissues examined and indicated varied expression profiles. The RT-qPCR results of 10 selected genes were also coherent with the digital expression analysis. Interestingly, five duplicated UGT genes were identified, which showed differential expression in various tissues. Of the seven intron loss/gain positions detected, two intron positions were conserved among most of the UGTs, although a clear relationship about the evolution of these genes could not be established. Comparison of the flax UGTs with orthologs from four other sequenced dicot

Genome-wide gene expression array identifies novel genes related to disease severity and excessive daytime sleepiness in patients with obstructive sleep apnea.

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Yung-Che Chen

Full Text Available We aimed to identify novel molecular associations between chronic intermittent hypoxia with re-oxygenation and adverse consequences in obstructive sleep apnea (OSA. We analyzed gene expression profiles of peripheral blood mononuclear cells from 48 patients with sleep-disordered breathing stratified into four groups: primary snoring (PS, moderate to severe OSA (MSO, very severe OSA (VSO, and very severe OSA patients on long-term continuous positive airway pressure treatment (VSOC. Comparisons of the microarray gene expression data identified eight genes up-regulated with OSA and down-regulated with CPAP treatment, and five genes down-regulated with OSA and up-regulated with CPAP treatment. Protein expression levels of two genes related to endothelial tight junction (AMOT P130, and PLEKHH3, and three genes related to anti-or pro-apoptosis (BIRC3, ADAR1 P150, and LGALS3 were all increased in the VSO group, while AMOT P130 was further increased, and PLEKHH3, BIRC3, and ADAR1 P150 were all decreased in the VSOC group. Subgroup analyses revealed that AMOT P130 protein expression was increased in OSA patients with excessive daytime sleepiness, BIRC3 protein expression was decreased in OSA patients with hypertension, and LGALS3 protein expression was increased in OSA patients with chronic kidney disease. In vitro short-term intermittent hypoxia with re-oxygenation experiment showed immediate over-expression of ADAR1 P150. In conclusion, we identified a novel association between AMOT/PLEKHH3/BIRC3/ADAR1/LGALS3 over-expressions and high severity index in OSA patients. AMOT and GALIG may constitute an important determinant for the development of hypersomnia and kidney injury, respectively, while BIRC3 may play a protective role in the development of hypertension.

Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles

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Lee Yun-Shien

2008-03-01

Full Text Available Abstract Background The hierarchical clustering tree (HCT with a dendrogram 1 and the singular value decomposition (SVD with a dimension-reduced representative map 2 are popular methods for two-way sorting the gene-by-array matrix map employed in gene expression profiling. While HCT dendrograms tend to optimize local coherent clustering patterns, SVD leading eigenvectors usually identify better global grouping and transitional structures. Results This study proposes a flipping mechanism for a conventional agglomerative HCT using a rank-two ellipse (R2E, an improved SVD algorithm for sorting purpose seriation by Chen 3 as an external reference. While HCTs always produce permutations with good local behaviour, the rank-two ellipse seriation gives the best global grouping patterns and smooth transitional trends. The resulting algorithm automatically integrates the desirable properties of each method so that users have access to a clustering and visualization environment for gene expression profiles that preserves coherent local clusters and identifies global grouping trends. Conclusion We demonstrate, through four examples, that the proposed method not only possesses better numerical and statistical properties, it also provides more meaningful biomedical insights than other sorting algorithms. We suggest that sorted proximity matrices for genes and arrays, in addition to the gene-by-array expression matrix, can greatly aid in the search for comprehensive understanding of gene expression structures. Software for the proposed methods can be obtained at http://gap.stat.sinica.edu.tw/Software/GAP.

Application of biclustering of gene expression data and gene set enrichment analysis methods to identify potentially disease causing nanomaterials

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Andrew Williams

2015-12-01

Full Text Available Background: The presence of diverse types of nanomaterials (NMs in commerce is growing at an exponential pace. As a result, human exposure to these materials in the environment is inevitable, necessitating the need for rapid and reliable toxicity testing methods to accurately assess the potential hazards associated with NMs. In this study, we applied biclustering and gene set enrichment analysis methods to derive essential features of altered lung transcriptome following exposure to NMs that are associated with lung-specific diseases. Several datasets from public microarray repositories describing pulmonary diseases in mouse models following exposure to a variety of substances were examined and functionally related biclusters of genes showing similar expression profiles were identified. The identified biclusters were then used to conduct a gene set enrichment analysis on pulmonary gene expression profiles derived from mice exposed to nano-titanium dioxide (nano-TiO2, carbon black (CB or carbon nanotubes (CNTs to determine the disease significance of these data-driven gene sets.Results: Biclusters representing inflammation (chemokine activity, DNA binding, cell cycle, apoptosis, reactive oxygen species (ROS and fibrosis processes were identified. All of the NM studies were significant with respect to the bicluster related to chemokine activity (DAVID; FDR p-value = 0.032. The bicluster related to pulmonary fibrosis was enriched in studies where toxicity induced by CNT and CB studies was investigated, suggesting the potential for these materials to induce lung fibrosis. The pro-fibrogenic potential of CNTs is well established. Although CB has not been shown to induce fibrosis, it induces stronger inflammatory, oxidative stress and DNA damage responses than nano-TiO2 particles.Conclusion: The results of the analysis correctly identified all NMs to be inflammogenic and only CB and CNTs as potentially fibrogenic. In addition to identifying several

Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

KAUST Repository

Othoum, Ghofran K

2013-05-01

Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

KAUST Repository

Othoum, Ghofran K

2013-01-01

Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

The Relationship Between Transcript Expression Levels of Nuclear Encoded (TFAM, NRF1 and Mitochondrial Encoded (MT-CO1 Genes in Single Human Oocytes During Oocyte Maturation

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Ghaffari Novin M.

2015-06-01

Full Text Available In some cases of infertility in women, human oocytes fail to mature when they reach the metaphase II (MII stage. Mitochondria plays an important role in oocyte maturation. A large number of mitochondrial DNA (mtDNA, copied in oocytes, is essential for providing adenosine triphosphate (ATP during oocyte maturation. The purpose of this study was to identify the relationship between transcript expression levels of the mitochondrial encoded gene (MT-CO1 and two nuclear encoded genes, nuclear respiratory factor 1 (NRF1 and mitochondrial transcription factor A (TFAM in various stages of human oocyte maturation. Nine consenting patients, age 21-35 years old, with male factors were selected for ovarian stimulation and intracytoplasmic sperm injection (ICSI procedures. mRNA levels of mitochondrial- related genes were performed by singlecell TaqMan® quantitative real-time polymerase chain reaction (qRT-PCR. There was no significant relationship between the relative expression levels in germinal vesicle (GV stage oocytes (p = 0.62. On the contrary, a significant relationship was seen between the relative expression levels of TFAM and NRF1 and the MT-CO1 genes at the stages of metaphase I (MI and MII (p = 0.03 and p = 0.002. A relationship exists between the transcript expression levels of TFAM and NRF1, and MT-CO1 genes in various stages of human oocyte maturation.

Regulation of gene expression is associated with tolerance of the Arctic copepod Calanus glacialis to CO2-acidified sea water.

Science.gov (United States)

Bailey, Allison; De Wit, Pierre; Thor, Peter; Browman, Howard I; Bjelland, Reidun; Shema, Steven; Fields, David M; Runge, Jeffrey A; Thompson, Cameron; Hop, Haakon

2017-09-01

Ocean acidification is the increase in seawater p CO 2 due to the uptake of atmospheric anthropogenic CO 2 , with the largest changes predicted to occur in the Arctic seas. For some marine organisms, this change in p CO 2 , and associated decrease in pH, represents a climate change-related stressor. In this study, we investigated the gene expression patterns of nauplii of the Arctic copepod Calanus glacialis cultured at low pH levels. We have previously shown that organismal-level performance (development, growth, respiration) of C. glacialis nauplii is unaffected by low pH. Here, we investigated the molecular-level response to lowered pH in order to elucidate the physiological processes involved in this tolerance. Nauplii from wild-caught C. glacialis were cultured at four pH levels (8.05, 7.9, 7.7, 7.5). At stage N6, mRNA was extracted and sequenced using RNA-seq. The physiological functionality of the proteins identified was categorized using Gene Ontology and KEGG pathways. We found that the expression of 151 contigs varied significantly with pH on a continuous scale (93% downregulated with decreasing pH). Gene set enrichment analysis revealed that, of the processes downregulated, many were components of the universal cellular stress response, including DNA repair, redox regulation, protein folding, and proteolysis. Sodium:proton antiporters were among the processes significantly upregulated, indicating that these ion pumps were involved in maintaining cellular pH homeostasis. C. glacialis significantly alters its gene expression at low pH, although they maintain normal larval development. Understanding what confers tolerance to some species will support our ability to predict the effects of future ocean acidification on marine organisms.

[Weighted gene co-expression network analysis in biomedicine research].

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Liu, Wei; Li, Li; Ye, Hua; Tu, Wei

2017-11-25

High-throughput biological technologies are now widely applied in biology and medicine, allowing scientists to monitor thousands of parameters simultaneously in a specific sample. However, it is still an enormous challenge to mine useful information from high-throughput data. The emergence of network biology provides deeper insights into complex bio-system and reveals the modularity in tissue/cellular networks. Correlation networks are increasingly used in bioinformatics applications. Weighted gene co-expression network analysis (WGCNA) tool can detect clusters of highly correlated genes. Therefore, we systematically reviewed the application of WGCNA in the study of disease diagnosis, pathogenesis and other related fields. First, we introduced principle, workflow, advantages and disadvantages of WGCNA. Second, we presented the application of WGCNA in disease, physiology, drug, evolution and genome annotation. Then, we indicated the application of WGCNA in newly developed high-throughput methods. We hope this review will help to promote the application of WGCNA in biomedicine research.

Gene co-expression networks and profiles reveal potential biomarkers of boar taint in pigs

DEFF Research Database (Denmark)

Drag, Markus; Skinkyté-Juskiené, R.; Do, Duy Ngoc

synthesis. In testis, >80 DE genes were functionally classified by the PANTHER tool to “Gonadotropin releasing hormone receptor” and “Wnt signaling” pathways which play a role in reproductive maturation and proliferation of spermatogonia, respectively. WGCNA was used to build co-expression modules...

Gene expression analysis identifies new candidate genes associated with the development of black skin spots in Corriedale sheep.

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Peñagaricano, Francisco; Zorrilla, Pilar; Naya, Hugo; Robello, Carlos; Urioste, Jorge I

2012-02-01

The white coat colour of sheep is an important economic trait. For unknown reasons, some animals are born with, and others develop with time, black skin spots that can also produce pigmented fibres. The presence of pigmented fibres in the white wool significantly decreases the fibre quality. The aim of this work was to study gene expression in black spots (with and without pigmented fibres) and white skin by microarray techniques, in order to identify the possible genes involved in the development of this trait. Five unrelated Corriedale sheep were used and, for each animal, the three possible comparisons (three different hybridisations) between the three samples of interest were performed. Differential gene expression patterns were analysed using different t-test approaches. Most of the major genes with well-known roles in skin pigmentation, e.g. ASIP, MC1R and C-KIT, showed no significant difference in the gene expression between white skin and black spots. On the other hand, many of the differentially expressed genes (raw P-value spots. The gene expression of C-FOS and KLF4, transcription factors involved in the cellular response to external factors such as ultraviolet light, was validated by quantitative polymerase chain reaction (PCR). This exploratory study provides a list of candidate genes that could be associated with the development of black skin spots that should be studied in more detail. Characterisation of these genes will enable us to discern the molecular mechanisms involved in the development of this feature and, hence, increase our understanding of melanocyte biology and skin pigmentation. In sheep, understanding this phenomenon is a first step towards developing molecular tools to assist in the selection against the presence of pigmented fibres in white wool.

Comprehensive analysis of coding-lncRNA gene co-expression network uncovers conserved functional lncRNAs in zebrafish.

Science.gov (United States)

Chen, Wen; Zhang, Xuan; Li, Jing; Huang, Shulan; Xiang, Shuanglin; Hu, Xiang; Liu, Changning

2018-05-09

Zebrafish is a full-developed model system for studying development processes and human disease. Recent studies of deep sequencing had discovered a large number of long non-coding RNAs (lncRNAs) in zebrafish. However, only few of them had been functionally characterized. Therefore, how to take advantage of the mature zebrafish system to deeply investigate the lncRNAs' function and conservation is really intriguing. We systematically collected and analyzed a series of zebrafish RNA-seq data, then combined them with resources from known database and literatures. As a result, we obtained by far the most complete dataset of zebrafish lncRNAs, containing 13,604 lncRNA genes (21,128 transcripts) in total. Based on that, a co-expression network upon zebrafish coding and lncRNA genes was constructed and analyzed, and used to predict the Gene Ontology (GO) and the KEGG annotation of lncRNA. Meanwhile, we made a conservation analysis on zebrafish lncRNA, identifying 1828 conserved zebrafish lncRNA genes (1890 transcripts) that have their putative mammalian orthologs. We also found that zebrafish lncRNAs play important roles in regulation of the development and function of nervous system; these conserved lncRNAs present a significant sequential and functional conservation, with their mammalian counterparts. By integrative data analysis and construction of coding-lncRNA gene co-expression network, we gained the most comprehensive dataset of zebrafish lncRNAs up to present, as well as their systematic annotations and comprehensive analyses on function and conservation. Our study provides a reliable zebrafish-based platform to deeply explore lncRNA function and mechanism, as well as the lncRNA commonality between zebrafish and human.

Comparison of gene co-networks reveals the molecular mechanisms of the rice (Oryza sativa L.) response to Rhizoctonia solani AG1 IA infection.

Science.gov (United States)

Zhang, Jinfeng; Zhao, Wenjuan; Fu, Rong; Fu, Chenglin; Wang, Lingxia; Liu, Huainian; Li, Shuangcheng; Deng, Qiming; Wang, Shiquan; Zhu, Jun; Liang, Yueyang; Li, Ping; Zheng, Aiping

2018-05-05

Rhizoctonia solani causes rice sheath blight, an important disease affecting the growth of rice (Oryza sativa L.). Attempts to control the disease have met with little success. Based on transcriptional profiling, we previously identified more than 11,947 common differentially expressed genes (TPM > 10) between the rice genotypes TeQing and Lemont. In the current study, we extended these findings by focusing on an analysis of gene co-expression in response to R. solani AG1 IA and identified gene modules within the networks through weighted gene co-expression network analysis (WGCNA). We compared the different genes assigned to each module and the biological interpretations of gene co-expression networks at early and later modules in the two rice genotypes to reveal differential responses to AG1 IA. Our results show that different changes occurred in the two rice genotypes and that the modules in the two groups contain a number of candidate genes possibly involved in pathogenesis, such as the VQ protein. Furthermore, these gene co-expression networks provide comprehensive transcriptional information regarding gene expression in rice in response to AG1 IA. The co-expression networks derived from our data offer ideas for follow-up experimentation that will help advance our understanding of the translational regulation of rice gene expression changes in response to AG1 IA.

Gene co-expression networks in liver and muscle transcriptome reveal sex-specific gene expression in lambs fed with a mix of essential oils

DEFF Research Database (Denmark)

Sabino, Marcella; Carmelo, Victor Adriano Okstoft; Mazzoni, Gianluca

2018-01-01

the potential of RNA-Sequencing data in order to evaluate the effect of an EO supplementary diet on gene expression in both lamb liver and muscle. Using a treatment and sex interaction model, 13 and 4 differentially expressed genes were identified in liver and muscle respectively. Sex-specific differentially...... on the expression profile of both liver and muscle tissues. We hypothesize that the presence of EOs could have beneficial effects on wellness of male lamb and further analyses are needed to understand the biological mechanisms behind the different effect of EO metabolites based on sex. Using lamb as a model...

xSyn: A Software Tool for Identifying Sophisticated 3-Way Interactions From Cancer Expression Data

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Baishali Bandyopadhyay

2017-08-01

Full Text Available Background: Constructing gene co-expression networks from cancer expression data is important for investigating the genetic mechanisms underlying cancer. However, correlation coefficients or linear regression models are not able to model sophisticated relationships among gene expression profiles. Here, we address the 3-way interaction that 2 genes’ expression levels are clustered in different space locations under the control of a third gene’s expression levels. Results: We present xSyn, a software tool for identifying such 3-way interactions from cancer gene expression data based on an optimization procedure involving the usage of UPGMA (Unweighted Pair Group Method with Arithmetic Mean and synergy. The effectiveness is demonstrated by application to 2 real gene expression data sets. Conclusions: xSyn is a useful tool for decoding the complex relationships among gene expression profiles. xSyn is available at http://www.bdxconsult.com/xSyn.html .

ESR1 Is Co-Expressed with Closely Adjacent Uncharacterised Genes Spanning a Breast Cancer Susceptibility Locus at 6q25.1

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Dunbier, Anita K.; Anderson, Helen; Ghazoui, Zara; Lopez-Knowles, Elena; Pancholi, Sunil; Ribas, Ricardo; Drury, Suzanne; Sidhu, Kally; Leary, Alexandra; Martin, Lesley-Ann; Dowsett, Mitch

2011-01-01

Approximately 80% of human breast carcinomas present as oestrogen receptor α-positive (ER+ve) disease, and ER status is a critical factor in treatment decision-making. Recently, single nucleotide polymorphisms (SNPs) in the region immediately upstream of the ER gene (ESR1) on 6q25.1 have been associated with breast cancer risk. Our investigation of factors associated with the level of expression of ESR1 in ER+ve tumours has revealed unexpected associations between genes in this region and ESR1 expression that are important to consider in studies of the genetic causes of breast cancer risk. RNA from tumour biopsies taken from 104 postmenopausal women before and after 2 weeks treatment with an aromatase (oestrogen synthase) inhibitor was analyzed on Illumina 48K microarrays. Multiple-testing corrected Spearman correlation revealed that three previously uncharacterized open reading frames (ORFs) located immediately upstream of ESR1, C6ORF96, C6ORF97, and C6ORF211 were highly correlated with ESR1 (Rs = 0.67, 0.64, and 0.55 respectively, FDRaccount for the correlations. The correlations were maintained in cultured cells. An ERα antagonist did not affect the ORFs' expression or their correlation with ESR1, suggesting their transcriptional co-activation is not directly mediated by ERα. siRNA inhibition of C6ORF211 suppressed proliferation in MCF7 cells, and C6ORF211 positively correlated with a proliferation metagene in tumours. In contrast, C6ORF97 expression correlated negatively with the metagene and predicted for improved disease-free survival in a tamoxifen-treated published dataset, independently of ESR1. Our observations suggest that some of the biological effects previously attributed to ER could be mediated and/or modified by these co-expressed genes. The co-expression and function of these genes may be important influences on the recently identified relationship between SNPs in this region and breast cancer risk. PMID:21552322

Biotin augments acetyl CoA carboxylase 2 gene expression in the hypothalamus, leading to the suppression of food intake in mice.

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Sone, Hideyuki; Kamiyama, Shin; Higuchi, Mutsumi; Fujino, Kaho; Kubo, Shizuka; Miyazawa, Masami; Shirato, Saya; Hiroi, Yuka; Shiozawa, Kota

2016-07-29

It is known that biotin prevents the development of diabetes by increasing the functions of pancreatic beta-cells and improving insulin sensitivity in the periphery. However, its anti-obesity effects such as anorectic effects remain to be clarified. Acetyl CoA carboxylase (ACC), a biotin-dependent enzyme, has two isoforms (ACC1 and ACC2) and serves to catalyze the reaction of acetyl CoA to malonyl CoA. In the hypothalamus, ACC2 increases the production of malonyl CoA, which acts as a satiety signal. In this study, we investigated whether biotin increases the gene expression of ACC2 in the hypothalamus and suppresses food intake in mice administered excessive biotin. Food intake was significantly decreased by biotin, but plasma regulators of appetite, including glucose, ghrelin, and leptin, were not affected. On the other hand, biotin notably accumulated in the hypothalamus and enhanced ACC2 gene expression there, but it did not change the gene expression of ACC1, malonyl CoA decarboxylase (a malonyl CoA-degrading enzyme), and AMP-activated protein kinase α-2 (an ACC-inhibitory enzyme). These findings strongly suggest that biotin potentiates the suppression of appetite by upregulating ACC2 gene expression in the hypothalamus. This effect of biotin may contribute to the prevention of diabetes by biotin treatment. Copyright © 2016 Elsevier Inc. All rights reserved.

Nine co-localized cytochrome P450 genes of the CYP2N, CYP2AD, and CYP2P gene families in the mangrove killifish Kryptolebias marmoratus genome: Identification and expression in response to B[α]P, BPA, OP, and NP.

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Puthumana, Jayesh; Kim, Bo-Mi; Jeong, Chang-Bum; Kim, Duck-Hyun; Kang, Hye-Min; Jung, Jee-Hyun; Kim, Il-Chan; Hwang, Un-Ki; Lee, Jae-Seong

2017-06-01

The CYP2 genes are the largest and most diverse cytochrome P450 (CYP) subfamily in vertebrates. We have identified nine co-localized CYP2 genes (∼55kb) in a new cluster in the genome of the highly resilient ecotoxicological fish model Kryptolebias marmoratus. Molecular characterization, temporal and tissue-specific expression pattern, and response to xenobiotics of these genes were examined. The CYP2 gene clusters were characterized and designated CYP2N22-23, CYP2AD12, and CYP2P16-20. Gene synteny analysis confirmed that the cluster in K. marmoratus is similar to that found in other teleost fishes, including zebrafish. A gene duplication event with diverged catalytic function was observed in CYP2AD12. Moreover, a high level of divergence in expression was observed among the co-localized genes. Phylogeny of the cluster suggested an orthologous relationship with similar genes in zebrafish and Japanese medaka. Gene expression analysis showed that CYP2P19 and CYP2N20 were consecutively expressed throughout embryonic development, whereas CYP2P18 was expressed in all adult tissues, suggesting that members of each CYP2 gene family have different physiological roles even though they are located in the same cluster. Among endocrine-disrupting chemicals (EDCs), benzo[α]pyrene (B[α]P) induced expression of CYP2N23, bisphenol A (BPA) induced CYP2P18 and CYP2P19, and 4-octylphenol (OP) induced CYP2AD12, but there was no significant response to 4-nonylphenol (NP), implying differential catalytic roles of the enzyme. In this paper, we identify and characterize a CYP2 gene cluster in the mangrove killifish K. marmoratus with differing catalytic roles toward EDCs. Our findings provide insights on the roles of nine co-localized CYP2 genes and their catalytic functions for better understanding of chemical-biological interactions in fish. Copyright © 2017 Elsevier B.V. All rights reserved.

Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data.

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Ren, Zhonglu; Wang, Wenhui; Li, Jinming

2016-02-01

Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristics of each subtype. Clustering analysis and discriminant analysis were utilized to discover the subtypes in two different molecular levels on 153 colon cancer samples from The Cancer Genome Atlas (TCGA) Data Portal. At gene expression level, we identified two major subtypes, ECL1 (expression cluster 1) and ECL2 (expression cluster 2) and a list of signature genes. Due to the heterogeneity of colon cancer, the subtype ECL1 can be further subdivided into three nested subclasses, and HOTAIR were found upregulated in subclass 2. At DNA methylation level, we uncovered three major subtypes, MCL1 (methylation cluster 1), MCL2 (methylation cluster 2) and MCL3 (methylation cluster 3). We found only three subtypes of CpG island methylator phenotype (CIMP) in colon cancer instead of the four subtypes in the previous reports, and we found no sufficient evidence to subdivide MCL3 into two distinct subgroups.

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways

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Musungu, Bryan M.; Bhatnagar, Deepak; Brown, Robert L.; Payne, Gary A.; OBrian, Greg; Fakhoury, Ahmad M.; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus, a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays, and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays, there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus. Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus. PMID:27917194

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways.

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Musungu, Bryan M; Bhatnagar, Deepak; Brown, Robert L; Payne, Gary A; OBrian, Greg; Fakhoury, Ahmad M; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus , a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays , and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays , there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus . Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus .

Use of an activated beta-catenin to identify Wnt pathway target genes in caenorhabditis elegans, including a subset of collagen genes expressed in late larval development.

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Jackson, Belinda M; Abete-Luzi, Patricia; Krause, Michael W; Eisenmann, David M

2014-04-16

The Wnt signaling pathway plays a fundamental role during metazoan development, where it regulates diverse processes, including cell fate specification, cell migration, and stem cell renewal. Activation of the beta-catenin-dependent/canonical Wnt pathway up-regulates expression of Wnt target genes to mediate a cellular response. In the nematode Caenorhabditis elegans, a canonical Wnt signaling pathway regulates several processes during larval development; however, few target genes of this pathway have been identified. To address this deficit, we used a novel approach of conditionally activated Wnt signaling during a defined stage of larval life by overexpressing an activated beta-catenin protein, then used microarray analysis to identify genes showing altered expression compared with control animals. We identified 166 differentially expressed genes, of which 104 were up-regulated. A subset of the up-regulated genes was shown to have altered expression in mutants with decreased or increased Wnt signaling; we consider these genes to be bona fide C. elegans Wnt pathway targets. Among these was a group of six genes, including the cuticular collagen genes, bli-1 col-38, col-49, and col-71. These genes show a peak of expression in the mid L4 stage during normal development, suggesting a role in adult cuticle formation. Consistent with this finding, reduction of function for several of the genes causes phenotypes suggestive of defects in cuticle function or integrity. Therefore, this work has identified a large number of putative Wnt pathway target genes during larval life, including a small subset of Wnt-regulated collagen genes that may function in synthesis of the adult cuticle.

Identifying candidate driver genes by integrative ovarian cancer genomics data

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Lu, Xinguo; Lu, Jibo

2017-08-01

Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.

Polycistronic gene expression in Aspergillus niger.

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Schuetze, Tabea; Meyer, Vera

2017-09-25

Genome mining approaches predict dozens of biosynthetic gene clusters in each of the filamentous fungal genomes sequenced so far. However, the majority of these gene clusters still remain cryptic because they are not expressed in their natural host. Simultaneous expression of all genes belonging to a biosynthetic pathway in a heterologous host is one approach to activate biosynthetic gene clusters and to screen the metabolites produced for bioactivities. Polycistronic expression of all pathway genes under control of a single and tunable promoter would be the method of choice, as this does not only simplify cloning procedures, but also offers control on timing and strength of expression. However, polycistronic gene expression is a feature not commonly found in eukaryotic host systems, such as Aspergillus niger. In this study, we tested the suitability of the viral P2A peptide for co-expression of three genes in A. niger. Two genes descend from Fusarium oxysporum and are essential to produce the secondary metabolite enniatin (esyn1, ekivR). The third gene (luc) encodes the reporter luciferase which was included to study position effects. Expression of the polycistronic gene cassette was put under control of the Tet-On system to ensure tunable gene expression in A. niger. In total, three polycistronic expression cassettes which differed in the position of luc were constructed and targeted to the pyrG locus in A. niger. This allowed direct comparison of the luciferase activity based on the position of the luciferase gene. Doxycycline-mediated induction of the Tet-On expression cassettes resulted in the production of one long polycistronic mRNA as proven by Northern analyses, and ensured comparable production of enniatin in all three strains. Notably, gene position within the polycistronic expression cassette matters, as, luciferase activity was lowest at position one and had a comparable activity at positions two and three. The P2A peptide can be used to express at

Changes in the gene expression of co-cultured human fibroblast cells and osteosarcoma cells: the role of microenvironment.

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Salvatore, Viviana; Focaroli, Stefano; Teti, Gabriella; Mazzotti, Antonio; Falconi, Mirella

2015-10-06

The progression of malignant tumors does not depend exclusively on the autonomous properties of cancer cells; it is also influenced by tumor stroma reactivity and is under strict microenvironmental control. By themselves, stromal cells are not malignant, and they maintain normal tissue structure and function. However, through intercellular interactions or by paracrine secretions from cancer cells, normal stromal cells acquire abnormal phenotypes that sustain cancer cell growth and tumor progression. In their dysfunctional state, fibroblast and immune cells produce chemokines and growth factors that stimulate cancer cell growth and invasion. In our previous work, we established an in vitro model based on a monolayer co-culture system of healthy human fibroblasts (HFs) and human osteosarcoma cells (the MG-63 cell line) that simulates the microenvironment of tumor cells and healthy cells. The coexistence between MG-63 cells and HFs allowed us to identify the YKL-40 protein as the main marker for verifying the influence of tumor cells grown in contact with healthy cells. In this study, we evaluated the interactions of HFs and MG-63 cells in a transwell co-culture system over 24 h, 48 h, 72 h, and 96 h. We analyzed the contributions of these populations to the tumor microenvironment during cancer progression, as measured by multiple markers. We examined the effect of siRNA knockdown of YKL-40 by tracking the subsequent changes in gene expression within the co-culture. We validated the expression of several genes, focusing on those involved in cancer cell invasion, inflammatory responses, and angiogenesis: TNF alpha, IL-6, MMP-1, MMP-9, and VEGF. We compared the results to those from a transwell co-culture without the YKL-40 knockdown. In a pro-inflammatory environment promoted by TNF alpha and IL-6, siRNA knockdown of YKL-40 caused a down-regulation of VEGF and MMP-1 expression in HFs. These findings demonstrated that the tumor microenvironment has an influence on the

Domestication rewired gene expression and nucleotide diversity patterns in tomato.

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Sauvage, Christopher; Rau, Andrea; Aichholz, Charlotte; Chadoeuf, Joël; Sarah, Gautier; Ruiz, Manuel; Santoni, Sylvain; Causse, Mathilde; David, Jacques; Glémin, Sylvain

2017-08-01

Plant domestication has led to considerable phenotypic modifications from wild species to modern varieties. However, although changes in key traits have been well documented, less is known about the underlying molecular mechanisms, such as the reduction of molecular diversity or global gene co-expression patterns. In this study, we used a combination of gene expression and population genetics in wild and crop tomato to decipher the footprints of domestication. We found a set of 1729 differentially expressed genes (DEG) between the two genetic groups, belonging to 17 clusters of co-expressed DEG, suggesting that domestication affected not only individual genes but also regulatory networks. Five co-expression clusters were enriched in functional terms involving carbohydrate metabolism or epigenetic regulation of gene expression. We detected differences in nucleotide diversity between the crop and wild groups specific to DEG. Our study provides an extensive profiling of the rewiring of gene co-expression induced by the domestication syndrome in one of the main crop species. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Dissection of regulatory networks that are altered in disease via differential co-expression.

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David Amar

Full Text Available Comparing the gene-expression profiles of sick and healthy individuals can help in understanding disease. Such differential expression analysis is a well-established way to find gene sets whose expression is altered in the disease. Recent approaches to gene-expression analysis go a step further and seek differential co-expression patterns, wherein the level of co-expression of a set of genes differs markedly between disease and control samples. Such patterns can arise from a disease-related change in the regulatory mechanism governing that set of genes, and pinpoint dysfunctional regulatory networks. Here we present DICER, a new method for detecting differentially co-expressed gene sets using a novel probabilistic score for differential correlation. DICER goes beyond standard differential co-expression and detects pairs of modules showing differential co-expression. The expression profiles of genes within each module of the pair are correlated across all samples. The correlation between the two modules, however, differs markedly between the disease and normal samples. We show that DICER outperforms the state of the art in terms of significance and interpretability of the detected gene sets. Moreover, the gene sets discovered by DICER manifest regulation by disease-specific microRNA families. In a case study on Alzheimer's disease, DICER dissected biological processes and protein complexes into functional subunits that are differentially co-expressed, thereby revealing inner structures in disease regulatory networks.

The gene expression profiles of canine mammary cancer cells grown with carcinoma-associated fibroblasts (CAFs as a co-culture in vitro

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Król Magdalena

2012-03-01

Full Text Available Abstract Background It is supposed that fibroblasts present in tumour microenvironment increase cancer invasiveness and its ability to metastasize but the mechanisms have not been clearly defined yet. Thus, the current study was designed to assess changes in gene expression in five various cancer cell lines grown as a co-culture with the carcinoma-associated fibroblasts (CAFs in vitro. Results A carcinoma-associated fibroblast cell line was isolated from a canine mammary cancer. Then, a co-culture of cancer cells with the CAFs was established and maintained for 72 hrs. Having sorted the cells, a global gene expression in cancer cells using DNA microarrays was examined. The analysis revealed an up-regulation of 100 genes and a down-regulation of 106 genes in the cancer cells grown as a co-culture with the CAFs in comparison to control conditions. The PANTHER binomial statistics tool was applied to determine statistically over-manifested pathways (p Conclusion The results of the current study showed that the co-culturing of cancer cells and the CAFs caused significant changes to the cancer gene expression. The presence of the CAFs in a microenvironment of cancer cells promotes adhesion, angiogenesis and EMT.

Kinase Gene Expression Profiling of Metastatic Clear Cell Renal Cell Carcinoma Tissue Identifies Potential New Therapeutic Targets.

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Pooja Ghatalia

Full Text Available Kinases are therapeutically actionable targets. Kinase inhibitors targeting vascular endothelial growth factor receptors (VEGFR and mammalian target of rapamycin (mTOR improve outcomes in metastatic clear cell renal cell carcinoma (ccRCC, but are not curative. Metastatic tumor tissue has not been comprehensively studied for kinase gene expression. Paired intra-patient kinase gene expression analysis in primary tumor (T, matched normal kidney (N and metastatic tumor tissue (M may assist in identifying drivers of metastasis and prioritizing therapeutic targets. We compared the expression of 519 kinase genes using NanoString in T, N and M in 35 patients to discover genes over-expressed in M compared to T and N tissue. RNA-seq data derived from ccRCC tumors in The Cancer Genome Atlas (TCGA were used to demonstrate differential expression of genes in primary tumor tissue from patients that had metastasis at baseline (n = 79 compared to those that did not develop metastasis for at least 2 years (n = 187. Functional analysis was conducted to identify key signaling pathways by using Ingenuity Pathway Analysis. Of 10 kinase genes overexpressed in metastases compared to primary tumor in the discovery cohort, 9 genes were also differentially expressed in TCGA primary tumors with metastasis at baseline compared to primary tumors without metastasis for at least 2 years: EPHB2, AURKA, GSG2, IKBKE, MELK, CSK, CHEK2, CDC7 and MAP3K8; p<0.001. The top pathways overexpressed in M tissue were pyridoxal 5'-phosphate salvage, salvage pathways of pyrimidine ribonucleotides, NF-kB signaling, NGF signaling and cell cycle control of chromosomal replication. The 9 kinase genes validated to be over-expressed in metastatic ccRCC may represent currently unrecognized but potentially actionable therapeutic targets that warrant functional validation.

Transcriptomic meta-analysis identifies gene expression characteristics in various samples of HIV-infected patients with nonprogressive disease.

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Zhang, Le-Le; Zhang, Zi-Ning; Wu, Xian; Jiang, Yong-Jun; Fu, Ya-Jing; Shang, Hong

2017-09-12

A small proportion of HIV-infected patients remain clinically and/or immunologically stable for years, including elite controllers (ECs) who have undetectable viremia (10 years). However, the mechanism of nonprogression needs to be further resolved. In this study, a transcriptome meta-analysis was performed on nonprogressor and progressor microarray data to identify differential transcriptome pathways and potential biomarkers. Using the INMEX (integrative meta-analysis of expression data) program, we performed the meta-analysis to identify consistently differentially expressed genes (DEGs) in nonprogressors and further performed functional interpretation (gene ontology analysis and pathway analysis) of the DEGs identified in the meta-analysis. Five microarray datasets (81 cases and 98 controls in total), including whole blood, CD4 + and CD8 + T cells, were collected for meta-analysis. We determined that nonprogressors have reduced expression of important interferon-stimulated genes (ISGs), CD38, lymphocyte activation gene 3 (LAG-3) in whole blood, CD4 + and CD8 + T cells. Gene ontology (GO) analysis showed a significant enrichment in DEGs that function in the type I interferon signaling pathway. Upregulated pathways, including the PI3K-Akt signaling pathway in whole blood, cytokine-cytokine receptor interaction in CD4 + T cells and the MAPK signaling pathway in CD8 + T cells, were identified in nonprogressors compared with progressors. In each metabolic functional category, the number of downregulated DEGs was more than the upregulated DEGs, and almost all genes were downregulated DEGs in the oxidative phosphorylation (OXPHOS) and tricarboxylic acid (TCA) cycle in the three types of samples. Our transcriptomic meta-analysis provides a comprehensive evaluation of the gene expression profiles in major blood types of nonprogressors, providing new insights in the understanding of HIV pathogenesis and developing strategies to delay HIV disease progression.

Co-regulation analysis of closely linked genes identifies a highly recurrent gain on chromosome 17q25.3 in prostate cancer

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Bermudo, Raquel; Martínez-A, Carlos; Ortiz, Ángel R; Fernández, Pedro L; Thomson, Timothy M; Abia, David; Ferrer, Berta; Nayach, Iracema; Benguria, Alberto; Zaballos, Ángel; Rey, Javier del; Miró, Rosa; Campo, Elías

2008-01-01

Transcriptional profiling of prostate cancer (PC) has unveiled new markers of neoplasia and allowed insights into mechanisms underlying this disease. Genomewide analyses have also identified new chromosomal abnormalities associated with PC. The combination of both classes of data for the same sample cohort might provide better criteria for identifying relevant factors involved in neoplasia. Here we describe transcriptional signatures identifying distinct normal and tumoral prostate tissue compartments, and the inference and demonstration of a new, highly recurrent copy number gain on chromosome 17q25.3. We have applied transcriptional profiling to tumoral and non-tumoral prostate samples with relatively homogeneous epithelial representations as well as pure stromal tissue from peripheral prostate and cultured cell lines, followed by quantitative RT-PCR validations and immunohistochemical analysis. In addition, we have performed in silico colocalization analysis of co-regulated genes and validation by fluorescent in situ hybridization (FISH). The transcriptomic analysis has allowed us to identify signatures corresponding to non-tumoral luminal and tumoral epithelium, basal epithelial cells, and prostate stromal tissue. In addition, in silico analysis of co-regulated expression of physically linked genes has allowed us to predict the occurrence of a copy number gain at chromosomal region 17q25.3. This computational inference was validated by fluorescent in situ hybridization, which showed gains in this region in over 65% of primary and metastatic tumoral samples. Our approach permits to directly link gene copy number variations with transcript co-regulation in association with neoplastic states. Therefore, transcriptomic studies of carefully selected samples can unveil new diagnostic markers and transcriptional signatures highly specific of PC, and lead to the discovery of novel genomic abnormalities that may provide additional insights into the causes and mechanisms

MeSH key terms for validation and annotation of gene expression clusters

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Rechtsteiner, A. (Andreas); Rocha, L. M. (Luis Mateus)

2004-01-01

Integration of different sources of information is a great challenge for the analysis of gene expression data, and for the field of Functional Genomics in general. As the availability of numerical data from high-throughput methods increases, so does the need for technologies that assist in the validation and evaluation of the biological significance of results extracted from these data. In mRNA assaying with microarrays, for example, numerical analysis often attempts to identify clusters of co-expressed genes. The important task to find the biological significance of the results and validate them has so far mostly fallen to the biological expert who had to perform this task manually. One of the most promising avenues to develop automated and integrative technology for such tasks lies in the application of modern Information Retrieval (IR) and Knowledge Management (KM) algorithms to databases with biomedical publications and data. Examples of databases available for the field are bibliographic databases c ntaining scientific publications (e.g. MEDLINE/PUBMED), databases containing sequence data (e.g. GenBank) and databases of semantic annotations (e.g. the Gene Ontology Consortium and Medical Subject Headings (MeSH)). We present here an approach that uses the MeSH terms and their concept hierarchies to validate and obtain functional information for gene expression clusters. The controlled and hierarchical MeSH vocabulary is used by the National Library of Medicine (NLM) to index all the articles cited in MEDLINE. Such indexing with a controlled vocabulary eliminates some of the ambiguity due to polysemy (terms that have multiple meanings) and synonymy (multiple terms have similar meaning) that would be encountered if terms would be extracted directly from the articles due to differing article contexts or author preferences and background. Further, the hierarchical organization of the MeSH terms can illustrate the conceptuallfunctional relationships of genes

In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

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Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-01

Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723

Weighted Gene Co-expression Network Analysis of the Dioscin Rich Medicinal Plant Dioscorea nipponica

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Wei Sun

2017-06-01

Full Text Available Dioscorea contains critically important species which can be used as staple foods or sources of bioactive substances, including Dioscorea nipponica, which has been used to develop highly successful drugs to treat cardiovascular disease. Its major active ingredients are thought to be sterol compounds such as diosgenin, which has been called “medicinal gold” because of its valuable properties. However, reliance on naturally growing plants as a production system limits the potential use of D. nipponica, raising interest in engineering metabolic pathways to enhance the production of secondary metabolites. However, the biosynthetic pathway of diosgenin is still poorly understood, and D. nipponica is poorly characterized at a molecular level, hindering in-depth investigation. In the present work, the RNAs from five organs and seven methyl jasmonate treated D. nipponica rhizomes were sequenced using the Illumina high-throughput sequencing platform, yielding 52 gigabases of data, which were pooled and assembled into a reference transcriptome. Four hundred and eighty two genes were found to be highly expressed in the rhizomes, and these genes are mainly involved in stress response and transcriptional regulation. Based on their expression patterns, 36 genes were selected for further investigation as candidate genes involved in dioscin biosynthesis. Constructing co-expression networks based on significant changes in gene expression revealed 15 gene modules. Of these, four modules with properties correlating to dioscin regulation and biosynthesis, consisting of 4,665 genes in total, were selected for further functional investigation. These results improve our understanding of dioscin biosynthesis in this important medicinal plant and will help guide more intensive investigations.

Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments.

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Regier, Mary C; Maccoux, Lindsey J; Weinberger, Emma M; Regehr, Keil J; Berry, Scott M; Beebe, David J; Alarid, Elaine T

2016-08-01

Heterotypic interactions in cancer microenvironments play important roles in disease initiation, progression, and spread. Co-culture is the predominant approach used in dissecting paracrine interactions between tumor and stromal cells, but functional results from simple co-cultures frequently fail to correlate to in vivo conditions. Though complex heterotypic in vitro models have improved functional relevance, there is little systematic knowledge of how multi-culture parameters influence this recapitulation. We therefore have employed a more iterative approach to investigate the influence of increasing model complexity; increased heterotypic complexity specifically. Here we describe how the compartmentalized and microscale elements of our multi-culture device allowed us to obtain gene expression data from one cell type at a time in a heterotypic culture where cells communicated through paracrine interactions. With our device we generated a large dataset comprised of cell type specific gene-expression patterns for cultures of increasing complexity (three cell types in mono-, co-, or tri-culture) not readily accessible in other systems. Principal component analysis indicated that gene expression was changed in co-culture but was often more strongly altered in tri-culture as compared to mono-culture. Our analysis revealed that cell type identity and the complexity around it (mono-, co-, or tri-culture) influence gene regulation. We also observed evidence of complementary regulation between cell types in the same heterotypic culture. Here we demonstrate the utility of our platform in providing insight into how tumor and stromal cells respond to microenvironments of varying complexities highlighting the expanding importance of heterotypic cultures that go beyond conventional co-culture.

Identification of PEG-induced water stress responsive transcripts using co-expression network in Eucalyptus grandis.

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Ghosh Dasgupta, Modhumita; Dharanishanthi, Veeramuthu

2017-09-05

Ecophysiological studies in Eucalyptus have shown that water is the principal factor limiting stem growth. Effect of water deficit conditions on physiological and biochemical parameters has been extensively reported in Eucalyptus. The present study was conducted to identify major polyethylene glycol induced water stress responsive transcripts in Eucalyptus grandis using gene co-expression network. A customized array representing 3359 water stress responsive genes was designed to document their expression in leaves of E. grandis cuttings subjected to -0.225MPa of PEG treatment. The differentially expressed transcripts were documented and significantly co-expressed transcripts were used for construction of network. The co-expression network was constructed with 915 nodes and 3454 edges with degree ranging from 2 to 45. Ninety four GO categories and 117 functional pathways were identified in the network. MCODE analysis generated 27 modules and module 6 with 479 nodes and 1005 edges was identified as the biologically relevant network. The major water responsive transcripts represented in the module included dehydrin, osmotin, LEA protein, expansin, arabinogalactans, heat shock proteins, major facilitator proteins, ARM repeat proteins, raffinose synthase, tonoplast intrinsic protein and transcription factors like DREB2A, ARF9, AGL24, UNE12, WLIM1 and MYB66, MYB70, MYB 55, MYB 16 and MYB 103. The coordinated analysis of gene expression patterns and coexpression networks developed in this study identified an array of transcripts that may regulate PEG induced water stress responses in E. grandis. Copyright © 2017 Elsevier B.V. All rights reserved.

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

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Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Integration of molecular biology tools for identifying promoters and genes abundantly expressed in flowers of Oncidium Gower Ramsey

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Tung Shu-Yun

2011-04-01

Full Text Available Abstract Background Orchids comprise one of the largest families of flowering plants and generate commercially important flowers. However, model plants, such as Arabidopsis thaliana do not contain all plant genes, and agronomic and horticulturally important genera and species must be individually studied. Results Several molecular biology tools were used to isolate flower-specific gene promoters from Oncidium 'Gower Ramsey' (Onc. GR. A cDNA library of reproductive tissues was used to construct a microarray in order to compare gene expression in flowers and leaves. Five genes were highly expressed in flower tissues, and the subcellular locations of the corresponding proteins were identified using lip transient transformation with fluorescent protein-fusion constructs. BAC clones of the 5 genes, together with 7 previously published flower- and reproductive growth-specific genes in Onc. GR, were identified for cloning of their promoter regions. Interestingly, 3 of the 5 novel flower-abundant genes were putative trypsin inhibitor (TI genes (OnTI1, OnTI2 and OnTI3, which were tandemly duplicated in the same BAC clone. Their promoters were identified using transient GUS reporter gene transformation and stable A. thaliana transformation analyses. Conclusions By combining cDNA microarray, BAC library, and bombardment assay techniques, we successfully identified flower-directed orchid genes and promoters.

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

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Rapin, Nicolas; Bagger, Frederik Otzen; Jendholm, Johan

2014-01-01

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 iden......-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....

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

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Hulsman, Marc; Lelieveldt, Boudewijn P. F.; de Ridder, Jeroen; Reinders, Marcel

2015-01-01

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale). PMID:25965262

MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

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Gonzalez-Dominguez, Jorge; Martin, Maria J

2017-10-10

In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

Identifying optimal reference genes for the normalization of microRNA expression in cucumber under viral stress

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Liang, Chaoqiong; Hao, Jianjun; Meng, Yan; Luo, Laixin; Li, Jianqiang

2018-01-01

Cucumber green mottle mosaic virus (CGMMV) is an economically important pathogen and causes significant reduction of both yield and quality of cucumber (Cucumis sativus). Currently, there were no satisfied strategies for controlling the disease. A better understanding of microRNA (miRNA) expression related to the regulation of plant-virus interactions and virus resistance would be of great assistance when developing control strategies for CGMMV. However, accurate expression analysis is highly dependent on robust and reliable reference gene used as an internal control for normalization of miRNA expression. Most commonly used reference genes involved in CGMMV-infected cucumber are not universally expressed depending on tissue types and stages of plant development. It is therefore crucial to identify suitable reference genes in investigating the role of miRNA expression. In this study, seven reference genes, including Actin, Tubulin, EF-1α, 18S rRNA, Ubiquitin, GAPDH and Cyclophilin, were evaluated for the most accurate results in analyses using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Gene expression was assayed on cucumber leaves, stems and roots that were collected at different days post inoculation with CGMMV. The expression data were analyzed using algorithms including delta-Ct, geNorm, NormFinder, and BestKeeper as well as the comparative tool RefFinder. The reference genes were subsequently validated using miR159. The results showed that EF-1α and GAPDH were the most reliable reference genes for normalizing miRNA expression in leaf, root and stem samples, while Ubiquitin and EF-1α were the most suitable combination overall. PMID:29543906

Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design.

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Li, Jianqiang; Zhou, Doudou; Qiu, Weiliang; Shi, Yuliang; Yang, Ji-Jiang; Chen, Shi; Wang, Qing; Pan, Hui

2018-01-12

Investigating how genes jointly affect complex human diseases is important, yet challenging. The network approach (e.g., weighted gene co-expression network analysis (WGCNA)) is a powerful tool. However, genomic data usually contain substantial batch effects, which could mask true genomic signals. Paired design is a powerful tool that can reduce batch effects. However, it is currently unclear how to appropriately apply WGCNA to genomic data from paired design. In this paper, we modified the current WGCNA pipeline to analyse high-throughput genomic data from paired design. We illustrated the modified WGCNA pipeline by analysing the miRNA dataset provided by Shiah et al. (2014), which contains forty oral squamous cell carcinoma (OSCC) specimens and their matched non-tumourous epithelial counterparts. OSCC is the sixth most common cancer worldwide. The modified WGCNA pipeline identified two sets of novel miRNAs associated with OSCC, in addition to the existing miRNAs reported by Shiah et al. (2014). Thus, this work will be of great interest to readers of various scientific disciplines, in particular, genetic and genomic scientists as well as medical scientists working on cancer.

Cis-Natural Antisense Transcripts Are Mainly Co-expressed with Their Sense Transcripts and Primarily Related to Energy Metabolic Pathways during Muscle Development.

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Zhao, Yunxia; Hou, Ye; Zhao, Changzhi; Liu, Fei; Luan, Yu; Jing, Lu; Li, Xinyun; Zhu, Mengjin; Zhao, Shuhong

2016-01-01

Cis-natural antisense transcripts (cis-NATs) are a new class of RNAs identified in various species. However, the biological functions of cis-NATs are largely unknown. In this study, we investigated the transcriptional characteristics and functions of cis-NATs in the muscle tissue of lean Landrace and indigenous fatty Lantang pigs. In total, 3,306 cis-NATs of 2,469 annotated genes were identified in the muscle tissue of pigs. More than 1,300 cis-NATs correlated with their sense genes at the transcriptional level, and approximately 80% of them were co-expressed in the two breeds. Furthermore, over 1,200 differentially expressed cis-NATs were identified during muscle development. Function annotation showed that the cis-NATs participated in muscle development mainly by co-expressing with genes involved in energy metabolic pathways, including citrate cycle (TCA cycle), glycolysis or gluconeogenesis, mitochondrial activation and so on. Moreover, these cis-NATs and their sense genes abruptly increased at the transition from the late fetal stages to the early postnatal stages and then decreased along with muscle development. In conclusion, the cis-NATs in the muscle tissue of pigs were identified and determined to be mainly co-expressed with their sense genes. The co-expressed cis-NATs and their sense gene were primarily related to energy metabolic pathways during muscle development in pigs. Our results offered novel evidence on the roles of cis-NATs during the muscle development of pigs.

Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

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Jesús Lascorz

2011-01-01

Full Text Available Background: A large number of gene expression profiling (GEP studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-regulated in colorectal carcinogenesis. Materials and Methods: We started the analysis with 242 unique annotated genes that had been reported by any of three recent meta-analyses covering GEP studies on genes differentially expressed in carcinoma vs normal mucosa. Most of these genes (218, 91.9% had been reported in at least three GEP studies. These 242 genes were submitted to bioinformatic analysis using a total of nine tools to detect enrichment of Gene Ontology (GO categories or Kyoto Encyclopedia of Genes and Genomes (KEGG pathways. As a final consistency criterion the pathway categories had to be enriched by several tools to be taken into consideration. Results: Our pathway-based enrichment analysis identified the categories of ribosomal protein constituents, extracellular matrix receptor interaction, carbonic anhydrase isozymes, and a general category related to inflammation and cellular response as significantly and consistently overrepresented entities. Conclusions: We triaged the genes covered by the published GEP literature on colorectal carcinogenesis and subjected them to multiple enrichment tools in order to identify the consistently enriched gene categories. These turned out to have known functional relationships to cancer development and thus deserve further investigation.

Transcriptomic variation among six Arabidopsis thaliana accessions identified several novel genes controlling aluminium tolerance.

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Kusunoki, Kazutaka; Nakano, Yuki; Tanaka, Keisuke; Sakata, Yoichi; Koyama, Hiroyuki; Kobayashi, Yuriko

2017-02-01

Differences in the expression levels of aluminium (Al) tolerance genes are a known determinant of Al tolerance among plant varieties. We combined transcriptomic analysis of six Arabidopsis thaliana accessions with contrasting Al tolerance and a reverse genetic approach to identify Al-tolerance genes responsible for differences in Al tolerance between accession groups. Gene expression variation increased in the signal transduction process under Al stress and in growth-related processes in the absence of stress. Co-expression analysis and promoter single nucleotide polymorphism searching suggested that both trans-acting polymorphisms of Al signal transduction pathway and cis-acting polymorphisms in the promoter sequences caused the variations in gene expression associated with Al tolerance. Compared with the wild type, Al sensitivity increased in T-DNA knockout (KO) lines for five genes, including TARGET OF AVRB OPERATION1 (TAO1) and an unannotated gene (At5g22530). These were identified from 53 Al-inducible genes showing significantly higher expression in tolerant accessions than in sensitive accessions. These results indicate that the difference in transcriptional signalling is partly associated with the natural variation in Al tolerance in Arabidopsis. Our study also demonstrates the feasibility of comparative transcriptome analysis by using natural genetic variation for the identification of genes responsible for Al stress tolerance. © 2016 John Wiley & Sons Ltd.

Integrated genomic and gene expression profiling identifies two major genomic circuits in urothelial carcinoma.

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David Lindgren

Full Text Available Similar to other malignancies, urothelial carcinoma (UC is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21, and BCL2L1 (20q11. We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.

Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers.

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Irigoyen, Antonio; Jimenez-Luna, Cristina; Benavides, Manuel; Caba, Octavio; Gallego, Javier; Ortuño, Francisco Manuel; Guillen-Ponce, Carmen; Rojas, Ignacio; Aranda, Enrique; Torres, Carolina; Prados, Jose

2018-01-01

Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

Genome-wide targeted prediction of ABA responsive genes in rice based on over-represented cis-motif in co-expressed genes.

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Lenka, Sangram K; Lohia, Bikash; Kumar, Abhay; Chinnusamy, Viswanathan; Bansal, Kailash C

2009-02-01

Abscisic acid (ABA), the popular plant stress hormone, plays a key role in regulation of sub-set of stress responsive genes. These genes respond to ABA through specific transcription factors which bind to cis-regulatory elements present in their promoters. We discovered the ABA Responsive Element (ABRE) core (ACGT) containing CGMCACGTGB motif as over-represented motif among the promoters of ABA responsive co-expressed genes in rice. Targeted gene prediction strategy using this motif led to the identification of 402 protein coding genes potentially regulated by ABA-dependent molecular genetic network. RT-PCR analysis of arbitrarily chosen 45 genes from the predicted 402 genes confirmed 80% accuracy of our prediction. Plant Gene Ontology (GO) analysis of ABA responsive genes showed enrichment of signal transduction and stress related genes among diverse functional categories.

Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.

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Gruben, Birgit S; Mäkelä, Miia R; Kowalczyk, Joanna E; Zhou, Miaomiao; Benoit-Gelber, Isabelle; De Vries, Ronald P

2017-11-23

The Aspergillus niger genome contains a large repertoire of genes encoding carbohydrate active enzymes (CAZymes) that are targeted to plant polysaccharide degradation enabling A. niger to grow on a wide range of plant biomass substrates. Which genes need to be activated in certain environmental conditions depends on the composition of the available substrate. Previous studies have demonstrated the involvement of a number of transcriptional regulators in plant biomass degradation and have identified sets of target genes for each regulator. In this study, a broad transcriptional analysis was performed of the A. niger genes encoding (putative) plant polysaccharide degrading enzymes. Microarray data focusing on the initial response of A. niger to the presence of plant biomass related carbon sources were analyzed of a wild-type strain N402 that was grown on a large range of carbon sources and of the regulatory mutant strains ΔxlnR, ΔaraR, ΔamyR, ΔrhaR and ΔgalX that were grown on their specific inducing compounds. The cluster analysis of the expression data revealed several groups of co-regulated genes, which goes beyond the traditionally described co-regulated gene sets. Additional putative target genes of the selected regulators were identified, based on their expression profile. Notably, in several cases the expression profile puts questions on the function assignment of uncharacterized genes that was based on homology searches, highlighting the need for more extensive biochemical studies into the substrate specificity of enzymes encoded by these non-characterized genes. The data also revealed sets of genes that were upregulated in the regulatory mutants, suggesting interaction between the regulatory systems and a therefore even more complex overall regulatory network than has been reported so far. Expression profiling on a large number of substrates provides better insight in the complex regulatory systems that drive the conversion of plant biomass by fungi. In

Co-ordinate regulation of Salmonella typhimurium invasion genes by environmental and regulatory factors is mediated by control of hilA expression.

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Bajaj, V; Lucas, R L; Hwang, C; Lee, C A

1996-11-01

During infection of their hosts, salmonellae enter intestinal epithelial cells. It has been proposed that when Salmonella typhimurium is present in the intestinal lumen, several environmental and regulatory conditions modulate the expression of invasion factors required for bacterial entry into host cells. We report here that the expression of six different S. typhimurium invasion genes encoded on SPI1 (Salmonella pathogenicity island 1) is co-ordinately regulated by oxygen, osmolarity, pH, PhoPQ, and HilA. HilA is a transcriptional activator of the OmpR/ToxR family that is also encoded on SPI1. We have found that HilA plays a central role in the co-ordinated regulation of invasion genes by environmental and regulatory conditions. HilA can activate the expression of two invasion gene-lacZY fusions on reporter plasmids in Escherichia coll, suggesting that HilA acts directly at invasion-gene promoters in S. typhimurium. We have found that the regulation of invasion genes by oxygen, osmolarity, pH, and PhoPQ is indirect and is mediated by regulation of hilA expression by these environmental and regulatory factors. We hypothesize that the complex and co-ordinate regulation of Invasion genes by HilA is an important feature of salmonella pathogenesis and allows salmonellae to enter intestinal epithelial cells.

Identifying Tmem59 related gene regulatory network of mouse neural stem cell from a compendium of expression profiles

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Guo Xiuyun

2011-09-01

Full Text Available Abstract Background Neural stem cells offer potential treatment for neurodegenerative disorders, such like Alzheimer's disease (AD. While much progress has been made in understanding neural stem cell function, a precise description of the molecular mechanisms regulating neural stem cells is not yet established. This lack of knowledge is a major barrier holding back the discovery of therapeutic uses of neural stem cells. In this paper, the regulatory mechanism of mouse neural stem cell (NSC differentiation by tmem59 is explored on the genome-level. Results We identified regulators of tmem59 during the differentiation of mouse NSCs from a compendium of expression profiles. Based on the microarray experiment, we developed the parallelized SWNI algorithm to reconstruct gene regulatory networks of mouse neural stem cells. From the inferred tmem59 related gene network including 36 genes, pou6f1 was identified to regulate tmem59 significantly and might play an important role in the differentiation of NSCs in mouse brain. There are four pathways shown in the gene network, indicating that tmem59 locates in the downstream of the signalling pathway. The real-time RT-PCR results shown that the over-expression of pou6f1 could significantly up-regulate tmem59 expression in C17.2 NSC line. 16 out of 36 predicted genes in our constructed network have been reported to be AD-related, including Ace, aqp1, arrdc3, cd14, cd59a, cds1, cldn1, cox8b, defb11, folr1, gdi2, mmp3, mgp, myrip, Ripk4, rnd3, and sncg. The localization of tmem59 related genes and functional-related gene groups based on the Gene Ontology (GO annotation was also identified. Conclusions Our findings suggest that the expression of tmem59 is an important factor contributing to AD. The parallelized SWNI algorithm increased the efficiency of network reconstruction significantly. This study enables us to highlight novel genes that may be involved in NSC differentiation and provides a shortcut to

ESR1 is co-expressed with closely adjacent uncharacterised genes spanning a breast cancer susceptibility locus at 6q25.1.

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Anita K Dunbier

2011-04-01

Full Text Available Approximately 80% of human breast carcinomas present as oestrogen receptor α-positive (ER+ve disease, and ER status is a critical factor in treatment decision-making. Recently, single nucleotide polymorphisms (SNPs in the region immediately upstream of the ER gene (ESR1 on 6q25.1 have been associated with breast cancer risk. Our investigation of factors associated with the level of expression of ESR1 in ER+ve tumours has revealed unexpected associations between genes in this region and ESR1 expression that are important to consider in studies of the genetic causes of breast cancer risk. RNA from tumour biopsies taken from 104 postmenopausal women before and after 2 weeks treatment with an aromatase (oestrogen synthase inhibitor was analyzed on Illumina 48K microarrays. Multiple-testing corrected Spearman correlation revealed that three previously uncharacterized open reading frames (ORFs located immediately upstream of ESR1, C6ORF96, C6ORF97, and C6ORF211 were highly correlated with ESR1 (Rs =  0.67, 0.64, and 0.55 respectively, FDR<1 × 10(-7. Publicly available datasets confirmed this relationship in other groups of ER+ve tumours. DNA copy number changes did not account for the correlations. The correlations were maintained in cultured cells. An ERα antagonist did not affect the ORFs' expression or their correlation with ESR1, suggesting their transcriptional co-activation is not directly mediated by ERα. siRNA inhibition of C6ORF211 suppressed proliferation in MCF7 cells, and C6ORF211 positively correlated with a proliferation metagene in tumours. In contrast, C6ORF97 expression correlated negatively with the metagene and predicted for improved disease-free survival in a tamoxifen-treated published dataset, independently of ESR1. Our observations suggest that some of the biological effects previously attributed to ER could be mediated and/or modified by these co-expressed genes. The co-expression and function of these genes may be

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

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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.

Step-by-Step Construction of Gene Co-expression Networks from High-Throughput Arabidopsis RNA Sequencing Data.

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Contreras-López, Orlando; Moyano, Tomás C; Soto, Daniela C; Gutiérrez, Rodrigo A

2018-01-01

The rapid increase in the availability of transcriptomics data generated by RNA sequencing represents both a challenge and an opportunity for biologists without bioinformatics training. The challenge is handling, integrating, and interpreting these data sets. The opportunity is to use this information to generate testable hypothesis to understand molecular mechanisms controlling gene expression and biological processes (Fig. 1). A successful strategy to generate tractable hypotheses from transcriptomics data has been to build undirected network graphs based on patterns of gene co-expression. Many examples of new hypothesis derived from network analyses can be found in the literature, spanning different organisms including plants and specific fields such as root developmental biology.In order to make the process of constructing a gene co-expression network more accessible to biologists, here we provide step-by-step instructions using published RNA-seq experimental data obtained from a public database. Similar strategies have been used in previous studies to advance root developmental biology. This guide includes basic instructions for the operation of widely used open source platforms such as Bio-Linux, R, and Cytoscape. Even though the data we used in this example was obtained from Arabidopsis thaliana, the workflow developed in this guide can be easily adapted to work with RNA-seq data from any organism.

Bioinformatic analysis of patient-derived ASPS gene expressions and ASPL-TFE3 fusion transcript levels identify potential therapeutic targets.

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David G Covell

Full Text Available Gene expression data, collected from ASPS tumors of seven different patients and from one immortalized ASPS cell line (ASPS-1, was analyzed jointly with patient ASPL-TFE3 (t(X;17(p11;q25 fusion transcript data to identify disease-specific pathways and their component genes. Data analysis of the pooled patient and ASPS-1 gene expression data, using conventional clustering methods, revealed a relatively small set of pathways and genes characterizing the biology of ASPS. These results could be largely recapitulated using only the gene expression data collected from patient tumor samples. The concordance between expression measures derived from ASPS-1 and both pooled and individual patient tumor data provided a rationale for extending the analysis to include patient ASPL-TFE3 fusion transcript data. A novel linear model was exploited to link gene expressions to fusion transcript data and used to identify a small set of ASPS-specific pathways and their gene expression. Cellular pathways that appear aberrantly regulated in response to the t(X;17(p11;q25 translocation include the cell cycle and cell adhesion. The identification of pathways and gene subsets characteristic of ASPS support current therapeutic strategies that target the FLT1 and MET, while also proposing additional targeting of genes found in pathways involved in the cell cycle (CHK1, cell adhesion (ARHGD1A, cell division (CDC6, control of meiosis (RAD51L3 and mitosis (BIRC5, and chemokine-related protein tyrosine kinase activity (CCL4.

A framework to identify gene expression profiles in a model of inflammation induced by lipopolysaccharide after treatment with thalidomide

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Paiva Renata T

2012-06-01

Full Text Available Abstract Background Thalidomide is an anti-inflammatory and anti-angiogenic drug currently used for the treatment of several diseases, including erythema nodosum leprosum, which occurs in patients with lepromatous leprosy. In this research, we use DNA microarray analysis to identify the impact of thalidomide on gene expression responses in human cells after lipopolysaccharide (LPS stimulation. We employed a two-stage framework. Initially, we identified 1584 altered genes in response to LPS. Modulation of this set of genes was then analyzed in the LPS stimulated cells treated with thalidomide. Results We identified 64 genes with altered expression induced by thalidomide using the rank product method. In addition, the lists of up-regulated and down-regulated genes were investigated by means of bioinformatics functional analysis, which allowed for the identification of biological processes affected by thalidomide. Confirmatory analysis was done in five of the identified genes using real time PCR. Conclusions The results showed some genes that can further our understanding of the biological mechanisms in the action of thalidomide. Of the five genes evaluated with real time PCR, three were down regulated and two were up regulated confirming the initial results of the microarray analysis.

Transcriptional Profiling Identifies Location-Specific and Breed-Specific Differentially Expressed Genes in Embryonic Myogenesis in Anas Platyrhynchos.

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Rong-Ping Zhang

Full Text Available Skeletal muscle growth and development are highly orchestrated processes involving significant changes in gene expressions. Differences in the location-specific and breed-specific genes and pathways involved have important implications for meat productions and meat quality. Here, RNA-Seq was performed to identify differences in the muscle deposition between two muscle locations and two duck breeds for functional genomics studies. To achieve those goals, skeletal muscle samples were collected from the leg muscle (LM and the pectoral muscle (PM of two genetically different duck breeds, Heiwu duck (H and Peking duck (P, at embryonic 15 days. Functional genomics studies were performed in two experiments: Experiment 1 directly compared the location-specific genes between PM and LM, and Experiment 2 compared the two breeds (H and P at the same developmental stage (embryonic 15 days. Almost 13 million clean reads were generated using Illumina technology (Novogene, Beijing, China on each library, and more than 70% of the reads mapped to the Peking duck (Anas platyrhynchos genome. A total of 168 genes were differentially expressed between the two locations analyzed in Experiment 1, whereas only 8 genes were differentially expressed when comparing the same location between two breeds in Experiment 2. Gene Ontology (GO and the Kyoto Encyclopedia of Genes and Genomes pathways (KEGG were used to functionally annotate DEGs (differentially expression genes. The DEGs identified in Experiment 1 were mainly involved in focal adhesion, the PI3K-Akt signaling pathway and ECM-receptor interaction pathways (corrected P-value<0.05. In Experiment 2, the DEGs were associated with only the ribosome signaling pathway (corrected P-value<0.05. In addition, quantitative real-time PCR was used to confirm 15 of the differentially expressed genes originally detected by RNA-Seq. A comparative transcript analysis of the leg and pectoral muscles of two duck breeds not only

Genome-Wide Temporal Expression Profiling in Caenorhabditis elegans Identifies a Core Gene Set Related to Long-Term Memory.

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Freytag, Virginie; Probst, Sabine; Hadziselimovic, Nils; Boglari, Csaba; Hauser, Yannick; Peter, Fabian; Gabor Fenyves, Bank; Milnik, Annette; Demougin, Philippe; Vukojevic, Vanja; de Quervain, Dominique J-F; Papassotiropoulos, Andreas; Stetak, Attila

2017-07-12

The identification of genes related to encoding, storage, and retrieval of memories is a major interest in neuroscience. In the current study, we analyzed the temporal gene expression changes in a neuronal mRNA pool during an olfactory long-term associative memory (LTAM) in Caenorhabditis elegans hermaphrodites. Here, we identified a core set of 712 (538 upregulated and 174 downregulated) genes that follows three distinct temporal peaks demonstrating multiple gene regulation waves in LTAM. Compared with the previously published positive LTAM gene set (Lakhina et al., 2015), 50% of the identified upregulated genes here overlap with the previous dataset, possibly representing stimulus-independent memory-related genes. On the other hand, the remaining genes were not previously identified in positive associative memory and may specifically regulate aversive LTAM. Our results suggest a multistep gene activation process during the formation and retrieval of long-term memory and define general memory-implicated genes as well as conditioning-type-dependent gene sets. SIGNIFICANCE STATEMENT The identification of genes regulating different steps of memory is of major interest in neuroscience. Identification of common memory genes across different learning paradigms and the temporal activation of the genes are poorly studied. Here, we investigated the temporal aspects of Caenorhabditis elegans gene expression changes using aversive olfactory associative long-term memory (LTAM) and identified three major gene activation waves. Like in previous studies, aversive LTAM is also CREB dependent, and CREB activity is necessary immediately after training. Finally, we define a list of memory paradigm-independent core gene sets as well as conditioning-dependent genes. Copyright © 2017 the authors 0270-6474/17/376661-12$15.00/0.

An extensive (co-expression analysis tool for the cytochrome P450 superfamily in Arabidopsis thaliana

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Provart Nicholas J

2008-04-01

Full Text Available Abstract Background Sequencing of the first plant genomes has revealed that cytochromes P450 have evolved to become the largest family of enzymes in secondary metabolism. The proportion of P450 enzymes with characterized biochemical function(s is however very small. If P450 diversification mirrors evolution of chemical diversity, this points to an unexpectedly poor understanding of plant metabolism. We assumed that extensive analysis of gene expression might guide towards the function of P450 enzymes, and highlight overlooked aspects of plant metabolism. Results We have created a comprehensive database, 'CYPedia', describing P450 gene expression in four data sets: organs and tissues, stress response, hormone response, and mutants of Arabidopsis thaliana, based on public Affymetrix ATH1 microarray expression data. P450 expression was then combined with the expression of 4,130 re-annotated genes, predicted to act in plant metabolism, for co-expression analyses. Based on the annotation of co-expressed genes from diverse pathway annotation databases, co-expressed pathways were identified. Predictions were validated for most P450s with known functions. As examples, co-expression results for P450s related to plastidial functions/photosynthesis, and to phenylpropanoid, triterpenoid and jasmonate metabolism are highlighted here. Conclusion The large scale hypothesis generation tools presented here provide leads to new pathways, unexpected functions, and regulatory networks for many P450s in plant metabolism. These can now be exploited by the community to validate the proposed functions experimentally using reverse genetics, biochemistry, and metabolic profiling.

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

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Klopfleisch, Robert; Lenze, Dido; Hummel, Michael; Gruber, Achim D

2010-01-01

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. 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. 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. 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

TAF6delta controls apoptosis and gene expression in the absence of p53.

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Emmanuelle Wilhelm

Full Text Available BACKGROUND: Life and death decisions of metazoan cells hinge on the balance between the expression of pro- versus anti-apoptotic gene products. The general RNA polymerase II transcription factor, TFIID, plays a central role in the regulation of gene expression through its core promoter recognition and co-activator functions. The core TFIID subunit TAF6 acts in vitro as an essential co-activator of transcription for the p53 tumor suppressor protein. We previously identified a splice variant of TAF6, termed TAF6delta that can be induced during apoptosis. METHODOLOGY/PRINCIPAL FINDINGS: To elucidate the impact of TAF6delta on cell death and gene expression, we have employed modified antisense oligonucleotides to enforce expression of endogenous TAF6delta. The induction of endogenous TAF6delta triggered apoptosis in tumor cell lines, including cells devoid of p53. Microarray experiments revealed that TAF6delta activates gene expression independently of cellular p53 status. CONCLUSIONS: Our data define TAF6delta as a pivotal node in a signaling pathway that controls gene expression programs and apoptosis in the absence of p53.

Co-expression of G2-EPSPS and glyphosate acetyltransferase GAT genes conferring high tolerance to glyphosate in soybean

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Bingfu eGuo

2015-10-01

Full Text Available Glyphosate is a widely used non-selective herbicide with broad spectrum of weed control around the world. At present, most of the commercial glyphosate tolerant soybeans utilize glyphosate tolerant gene CP4-EPSPS or glyphosate acetyltransferase gene GAT separately. In this study, both glyphosate tolerant gene G2-EPSPS and glyphosate degraded gene GAT were co-transferred into soybean and transgenic plants showed high tolerance to glyphosate. Molecular analysis including PCR, Sothern blot, qRT-PCR and Western blot revealed that target genes have been integrated into genome and expressed effectively at both mRNA and protein levels. Furthermore, the glyphosate tolerance analysis showed that no typical symptom was observed when compared with a glyphosate tolerant line HJ06-698 derived from GR1 transgenic soybean even at four-fold labeled rate of Roundup. Chlorophyll and shikimic acid content analysis of transgenic plant also revealed that these two indexes were not significantly altered after glyphosate application. These results indicated that co-expression of G2-EPSPS and GAT conferred high tolerance to the herbicide glyphosate in soybean. Therefore, combination of tolerant and degraded genes provides a new strategy for developing glyphosate tolerant transgenic crops.

Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

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Fowles, Jared S; Brown, Kristen C; Hess, Ann M; Duval, Dawn L; Gustafson, Daniel L

2016-02-19

Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

Genome-Wide Identification and Expression Analysis of the Biotin Carboxyl Carrier Subunits of Heteromeric Acetyl-CoA Carboxylase in Gossypium

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Jinping Hua

2017-05-01

Full Text Available Acetyl-CoA carboxylase is an important enzyme, which catalyzes acetyl-CoA’s carboxylation to produce malonyl-CoA and to serve as a committed step for de novo fatty acid biosynthesis in plastids. In this study, 24 putative cotton BCCP genes were identified based on the lately published genome data in Gossypium. Among them, 4, 4, 8, and 8 BCCP homologs were identified in Gossypium raimondii, G. arboreum, G. hirsutum, and G. barbadense, respectively. These genes were divided into two classes based on a phylogenetic analysis. In each class, these homologs were relatively conserved in gene structure and motifs. The chromosomal distribution pattern revealed that all the BCCP genes were distributed equally on corresponding chromosomes or scaffold in the four cotton species. Segmental duplication was a predominant duplication event in both of G. hirsutum and G. barbadense. The analysis of the expression profile showed that 8 GhBCCP genes expressed in all the tested tissues with changed expression levels, and GhBCCP genes belonging to class II were predominantly expressed in developing ovules. Meanwhile, the expression analysis for the 16 cotton BCCP genes from G. raimondii, G. arboreum and G. hirsutum showed that they were induced or suppressed by cold or salt stress, and their expression patterns varied among different tissues. These findings will help to determine the functional and evolutionary characteristics of the BCCP genes in Gossypium species.

Gene expression analysis to identify molecular correlates of pre- and post-conditioning derived neuroprotection.

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Prasad, Shiv S; Russell, Marsha; Nowakowska, Margeryta; Williams, Andrew; Yauk, Carole

2012-06-01

Mild ischaemic exposures before or after severe injurious ischaemia that elicit neuroprotective responses are referred to as preconditioning and post-conditioning. The corresponding molecular mechanisms of neuroprotection are not completely understood. Identification of the genes and associated pathways of corresponding neuroprotection would provide insight into neuronal survival, potential therapeutic approaches and assessments of therapies for stroke. The objectives of this study were to use global gene expression approach to infer the molecular mechanisms in pre- and post-conditioning-derived neuroprotection in cortical neurons following oxygen and glucose deprivation (OGD) in vitro and then to apply these findings to predict corresponding functional pathways. To this end, microarray analysis was applied to rat cortical neurons with or without the pre- and post-conditioning treatments at 3-h post-reperfusion, and differentially expressed transcripts were subjected to statistical, hierarchical clustering and pathway analyses. The expression patterns of 3,431 genes altered under all conditions of ischaemia (with and without pre- or post-conditioning). We identified 1,595 genes that were commonly regulated within both the pre- and post-conditioning treatments. Cluster analysis revealed that transcription profiles clustered tightly within controls, non-conditioned OGD and neuroprotected groups. Two clusters defining neuroprotective conditions associated with up- and downregulated genes were evident. The five most upregulated genes within the neuroprotective clusters were Tagln, Nes, Ptrf, Vim and Adamts9, and the five most downregulated genes were Slc7a3, Bex1, Brunol4, Nrxn3 and Cpne4. Pathway analysis revealed that the intracellular and second messenger signalling pathways in addition to cell death were predominantly associated with downregulated pre- and post-conditioning associated genes, suggesting that modulation of cell death and signal transduction pathways

Identifying essential genes in bacterial metabolic networks with machine learning methods

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2010-01-01

Background Identifying essential genes in bacteria supports to identify potential drug targets and an understanding of minimal requirements for a synthetic cell. However, experimentally assaying the essentiality of their coding genes is resource intensive and not feasible for all bacterial organisms, in particular if they are infective. Results We developed a machine learning technique to identify essential genes using the experimental data of genome-wide knock-out screens from one bacterial organism to infer essential genes of another related bacterial organism. We used a broad variety of topological features, sequence characteristics and co-expression properties potentially associated with essentiality, such as flux deviations, centrality, codon frequencies of the sequences, co-regulation and phyletic retention. An organism-wise cross-validation on bacterial species yielded reliable results with good accuracies (area under the receiver-operator-curve of 75% - 81%). Finally, it was applied to drug target predictions for Salmonella typhimurium. We compared our predictions to the viability of experimental knock-outs of S. typhimurium and identified 35 enzymes, which are highly relevant to be considered as potential drug targets. Specifically, we detected promising drug targets in the non-mevalonate pathway. Conclusions Using elaborated features characterizing network topology, sequence information and microarray data enables to predict essential genes from a bacterial reference organism to a related query organism without any knowledge about the essentiality of genes of the query organism. In general, such a method is beneficial for inferring drug targets when experimental data about genome-wide knockout screens is not available for the investigated organism. PMID:20438628

Signature pathways identified from gene expression profiles in the human uterine cervix before and after spontaneous term parturition

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HASSAN, Sonia S.; ROMERO, Roberto; TARCA, Adi L.; DRAGHICI, Sorin; PINELES, Beth; BUGRIM, Andrej; KHALEK, Nahla; CAMACHO, Natalia; MITTAL, Pooja; YOON, Bo Hyun; ESPINOZA, Jimmy; KIM, Chong Jai; SOROKIN, Yoram; MALONE, John

2008-01-01

Objective This study aimed to discover ‘signature pathways’ characterizing biological processes based on genes differentially expressed in the uterine cervix before and after spontaneous labor. Study Design The cervical transcriptome was previously characterized from biopsies taken before and after term labor. Pathway analysis was used to study the differentially expressed genes based on two gene-to-pathway annotation databases (KEGG and Metacore™). Over-represented and highly impacted pathways and connectivity nodes were identified. Results Fifty-two pathways in the Metacore™ database were significantly enriched in differentially expressed genes. Three of the top 5 pathways were known to be involved in cervical remodeling.Two novel pathways were: plasmin signaling and plasminogen activator urokinase (PLAU) signaling. The same analysis in the KEGG database identified 4 significant pathways, of which impact analysis confirmed. Multiple nodes providing connectivity within the plasmin and PLAU signaling pathways were identified.. Conclusions Three strategies for pathway analysis were consistent in their identification of novel, unexpected as well as expected networks, suggesting that this approach is both valid and effective for the elucidation of biological mechanisms involved in cervical dilation and remodeling. PMID:17826407

Expression of gentisate 1,2-dioxygenase (gdoA) genes involved in aromatic degradation in two haloarchaeal genera.

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Fairley, D J; Wang, G; Rensing, C; Pepper, I L; Larkin, M J

2006-12-01

Gentisate-1,2-dioxygenase genes (gdoA), with homology to a number of bacterial dioxygenases, and genes encoding a putative coenzyme A (CoA)-synthetase subunit (acdB) and a CoA-thioesterase (tieA) were identified in two haloarchaeal isolates. In Haloarcula sp. D1, gdoA was expressed during growth on 4-hydroxybenzoate but not benzoate, and acdB and tieA were not expressed during growth on any of the aromatic substrates tested. In contrast, gdoA was expressed in Haloferax sp. D1227 during growth on benzoate, 3-hydroxybenzoate, cinnamate and phenylpropionate, and both acdB and tieA were expressed during growth on benzoate, cinnamate and phenylpropionate, but not on 3-hydroxybenzoate. This pattern of induction is consistent with these genes encoding steps in a CoA-mediated benzoate pathway in this strain.

Gene Expression Profiling Identifies Important Genes Affected by R2 Compound Disrupting FAK and P53 Complex

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Golubovskaya, Vita M.; Ho, Baotran; Conroy, Jeffrey; Liu, Song; Wang, Dan; Cance, William G.

2014-01-01

Focal Adhesion Kinase (FAK) is a non-receptor kinase that plays an important role in many cellular processes: adhesion, proliferation, invasion, angiogenesis, metastasis and survival. Recently, we have shown that Roslin 2 or R2 (1-benzyl-15,3,5,7-tetraazatricyclo[3.3.1.1~3,7~]decane) compound disrupts FAK and p53 proteins, activates p53 transcriptional activity, and blocks tumor growth. In this report we performed a microarray gene expression analysis of R2-treated HCT116 p53 +/+ and p53 −/− cells and detected 1484 genes that were significantly up- or down-regulated (p < 0.05) in HCT116 p53 +/+ cells but not in p53 −/− cells. Among up-regulated genes in HCT p53 +/+ cells we detected critical p53 targets: Mdm-2, Noxa-1, and RIP1. Among down-regulated genes, Met, PLK2, KIF14, BIRC2 and other genes were identified. In addition, a combination of R2 compound with M13 compound that disrupts FAK and Mmd-2 complex or R2 and Nutlin-1 that disrupts Mdm-2 and p53 decreased clonogenicity of HCT116 p53 +/+ colon cancer cells more significantly than each agent alone in a p53-dependent manner. Thus, the report detects gene expression profile in response to R2 treatment and demonstrates that the combination of drugs targeting FAK, Mdm-2, and p53 can be a novel therapy approach

Diametrical clustering for identifying anti-correlated gene clusters.

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Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

2003-09-01

Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

Comprehensive Analysis of Gene Expression Profiles of Sepsis-Induced Multiorgan Failure Identified Its Valuable Biomarkers.

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Wang, Yumei; Yin, Xiaoling; Yang, Fang

2018-02-01

Sepsis is an inflammatory-related disease, and severe sepsis would induce multiorgan dysfunction, which is the most common cause of death of patients in noncoronary intensive care units. Progression of novel therapeutic strategies has proven to be of little impact on the mortality of severe sepsis, and unfortunately, its mechanisms still remain poorly understood. In this study, we analyzed gene expression profiles of severe sepsis with failure of lung, kidney, and liver for the identification of potential biomarkers. We first downloaded the gene expression profiles from the Gene Expression Omnibus and performed preprocessing of raw microarray data sets and identification of differential expression genes (DEGs) through the R programming software; then, significantly enriched functions of DEGs in lung, kidney, and liver failure sepsis samples were obtained from the Database for Annotation, Visualization, and Integrated Discovery; finally, protein-protein interaction network was constructed for DEGs based on the STRING database, and network modules were also obtained through the MCODE cluster method. As a result, lung failure sepsis has the highest number of DEGs of 859, whereas the number of DEGs in kidney and liver failure sepsis samples is 178 and 175, respectively. In addition, 17 overlaps were obtained among the three lists of DEGs. Biological processes related to immune and inflammatory response were found to be significantly enriched in DEGs. Network and module analysis identified four gene clusters in which all or most of genes were upregulated. The expression changes of Icam1 and Socs3 were further validated through quantitative PCR analysis. This study should shed light on the development of sepsis and provide potential therapeutic targets for sepsis-induced multiorgan failure.

Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans.

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Maxime Rotival

2011-12-01

Full Text Available One major expectation from the transcriptome in humans is to characterize the biological basis of associations identified by genome-wide association studies. So far, few cis expression quantitative trait loci (eQTLs have been reliably related to disease susceptibility. Trans-regulating mechanisms may play a more prominent role in disease susceptibility. We analyzed 12,808 genes detected in at least 5% of circulating monocyte samples from a population-based sample of 1,490 European unrelated subjects. We applied a method of extraction of expression patterns-independent component analysis-to identify sets of co-regulated genes. These patterns were then related to 675,350 SNPs to identify major trans-acting regulators. We detected three genomic regions significantly associated with co-regulated gene modules. Association of these loci with multiple expression traits was replicated in Cardiogenics, an independent study in which expression profiles of monocytes were available in 758 subjects. The locus 12q13 (lead SNP rs11171739, previously identified as a type 1 diabetes locus, was associated with a pattern including two cis eQTLs, RPS26 and SUOX, and 5 trans eQTLs, one of which (MADCAM1 is a potential candidate for mediating T1D susceptibility. The locus 12q24 (lead SNP rs653178, which has demonstrated extensive disease pleiotropy, including type 1 diabetes, hypertension, and celiac disease, was associated to a pattern strongly correlating to blood pressure level. The strongest trans eQTL in this pattern was CRIP1, a known marker of cellular proliferation in cancer. The locus 12q15 (lead SNP rs11177644 was associated with a pattern driven by two cis eQTLs, LYZ and YEATS4, and including 34 trans eQTLs, several of them tumor-related genes. This study shows that a method exploiting the structure of co-expressions among genes can help identify genomic regions involved in trans regulation of sets of genes and can provide clues for understanding the

Identification of a set of genes showing regionally enriched expression in the mouse brain

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Marra Marco A

2008-07-01

Full Text Available Abstract Background The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters ( Results We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Conclusion Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression.

Genetic architecture of wood properties based on association analysis and co-expression networks in white spruce.

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Lamara, Mebarek; Raherison, Elie; Lenz, Patrick; Beaulieu, Jean; Bousquet, Jean; MacKay, John

2016-04-01

Association studies are widely utilized to analyze complex traits but their ability to disclose genetic architectures is often limited by statistical constraints, and functional insights are usually minimal in nonmodel organisms like forest trees. We developed an approach to integrate association mapping results with co-expression networks. We tested single nucleotide polymorphisms (SNPs) in 2652 candidate genes for statistical associations with wood density, stiffness, microfibril angle and ring width in a population of 1694 white spruce trees (Picea glauca). Associations mapping identified 229-292 genes per wood trait using a statistical significance level of P wood associated genes and several known MYB and NAC regulators were identified as network hubs. The network revealed a link between the gene PgNAC8, wood stiffness and microfibril angle, as well as considerable within-season variation for both genetic control of wood traits and gene expression. Trait associations were distributed throughout the network suggesting complex interactions and pleiotropic effects. Our findings indicate that integration of association mapping and co-expression networks enhances our understanding of complex wood traits. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Comparative gene expression between two yeast species

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Guan Yuanfang

2013-01-01

Full Text Available Abstract Background Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository. Results In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species gene expression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences. Conclusions Taken together, these analyses provide a global view of gene expression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.

Early bovine embryos regulate oviduct epithelial cell gene expression during in vitro co-culture.

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Schmaltz-Panneau, Barbara; Cordova, Amanda; Dhorne-Pollet, Sophie; Hennequet-Antier, Christelle; Uzbekova, Sveltlana; Martinot, Emmanuelle; Doret, Sarah; Martin, Patrice; Mermillod, Pascal; Locatelli, Yann

2014-10-01

In mammals, the oviduct may participate to the regulation of early embryo development. In vitro co-culture of early bovine embryos with bovine oviduct epithelial cells (BOEC) has been largely used to mimic the maternal environment. However, the mechanisms of BOEC action have not been clearly elucidated yet. The aim of this study was to determine the response of BOEC cultures to the presence of developing bovine embryos. A 21,581-element bovine oligonucleotide array was used compare the gene expression profiles of confluent BOEC cultured for 8 days with or without embryos. This study revealed 34 differentially expressed genes (DEG). Of these 34 genes, IFI6, ISG15, MX1, IFI27, IFI44, RSAD2, IFITM1, EPSTI1, USP18, IFIT5, and STAT1 expression increased to the greatest extent due to the presence of embryos with a major impact on antiviral and immune response. Among the mRNAs at least 25 are already described as induced by interferons. In addition, transcript levels of new candidate genes involved in the regulation of transcription, modulation of the maternal immune system and endometrial remodeling were found to be increased. We selected 7 genes and confirmed their differential expression by quantitative RT-PCR. The immunofluorescence imaging of cellular localization of STAT1 protein in BOEC showed a nuclear translocation in the presence of embryos, suggesting the activation of interferon signaling pathway. This first systematic study of BOEC transcriptome changes in response to the presence of embryos in cattle provides some evidences that these cells are able to adapt their transcriptomic profile in response to embryo signaling. Copyright © 2014 Elsevier B.V. All rights reserved.

Tumor SHB gene expression affects disease characteristics in human acute myeloid leukemia.

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Jamalpour, Maria; Li, Xiujuan; Cavelier, Lucia; Gustafsson, Karin; Mostoslavsky, Gustavo; Höglund, Martin; Welsh, Michael

2017-10-01

The mouse Shb gene coding for the Src Homology 2-domain containing adapter protein B has recently been placed in context of BCRABL1-induced myeloid leukemia in mice and the current study was performed in order to relate SHB to human acute myeloid leukemia (AML). Publicly available AML databases were mined for SHB gene expression and patient survival. SHB gene expression was determined in the Uppsala cohort of AML patients by qPCR. Cell proliferation was determined after SHB gene knockdown in leukemic cell lines. Despite a low frequency of SHB gene mutations, many tumors overexpressed SHB mRNA compared with normal myeloid blood cells. AML patients with tumors expressing low SHB mRNA displayed longer survival times. A subgroup of AML exhibiting a favorable prognosis, acute promyelocytic leukemia (APL) with a PMLRARA translocation, expressed less SHB mRNA than AML tumors in general. When examining genes co-expressed with SHB in AML tumors, four other genes ( PAX5, HDAC7, BCORL1, TET1) related to leukemia were identified. A network consisting of these genes plus SHB was identified that relates to certain phenotypic characteristics, such as immune cell, vascular and apoptotic features. SHB knockdown in the APL PMLRARA cell line NB4 and the monocyte/macrophage cell line MM6 adversely affected proliferation, linking SHB gene expression to tumor cell expansion and consequently to patient survival. It is concluded that tumor SHB gene expression relates to AML survival and its subgroup APL. Moreover, this gene is included in a network of genes that plays a role for an AML phenotype exhibiting certain immune cell, vascular and apoptotic characteristics.

Rhythmic diel pattern of gene expression in juvenile maize leaf.

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Maciej Jończyk

Full Text Available BACKGROUND: Numerous biochemical and physiological parameters of living organisms follow a circadian rhythm. Although such rhythmic behavior is particularly pronounced in plants, which are strictly dependent on the daily photoperiod, data on the molecular aspects of the diurnal cycle in plants is scarce and mostly concerns the model species Arabidopsis thaliana. Here we studied the leaf transcriptome in seedlings of maize, an important C4 crop only distantly related to A. thaliana, throughout a cycle of 10 h darkness and 14 h light to look for rhythmic patterns of gene expression. RESULTS: Using DNA microarrays comprising ca. 43,000 maize-specific probes we found that ca. 12% of all genes showed clear-cut diel rhythms of expression. Cluster analysis identified 35 groups containing from four to ca. 1,000 genes, each comprising genes of similar expression patterns. Perhaps unexpectedly, the most pronounced and most common (concerning the highest number of genes expression maxima were observed towards and during the dark phase. Using Gene Ontology classification several meaningful functional associations were found among genes showing similar diel expression patterns, including massive induction of expression of genes related to gene expression, translation, protein modification and folding at dusk and night. Additionally, we found a clear-cut tendency among genes belonging to individual clusters to share defined transcription factor-binding sequences. CONCLUSIONS: Co-expressed genes belonging to individual clusters are likely to be regulated by common mechanisms. The nocturnal phase of the diurnal cycle involves gross induction of fundamental biochemical processes and should be studied more thoroughly than was appreciated in most earlier physiological studies. Although some general mechanisms responsible for the diel regulation of gene expression might be shared among plants, details of the diurnal regulation of gene expression seem to differ

Lack of co-ordinate expression of the alpha1(I) and alpha1(III) procollagen genes in fibroblast clonal cultures.

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Yamaguchi, Y; Crane, S; Zhou, L; Ochoa, S M; Falanga, V

2000-12-01

Several extracellular matrix genes, most notably alpha1(I) and alpha1(III) procollagen, are reported to be co-ordinately expressed in cultures of dermal fibroblasts. However, it remains unclear whether the expression of these genes is truly co-ordinate or whether it may be the result of averaging the phenotypic expression of different fibroblast subpopulations present within each culture. Objectives To determine by Northern analysis the correlation between alpha1(I) and alpha1(III) procollagen mRNA levels in clonal populations of human dermal fibroblasts. As previously described, clonal cultures were derived from parent strains of human dermal fibroblasts by a microscopically controlled dilution technique and by stimulation of single cells with low oxygen tension in the early phases of clonal growth. In agreement with previous reports, we found that baseline steady-state levels of alpha1(I) procollagen mRNA were co-ordinately regulated with the alpha1(III) procollagen mRNA in 26 parent strains (r = 0. 9003; P ordinate regulation observed in non-clonal cultures, suggesting that these two genes operate under different sets of regulatory controls. This clonal heterogeneity may provide additional flexibility to the process of tissue repair and fibroblast clonal expansion.

Social Regulation of Gene Expression in Threespine Sticklebacks.

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Anna K Greenwood

Full Text Available Identifying genes that are differentially expressed in response to social interactions is informative for understanding the molecular basis of social behavior. To address this question, we described changes in gene expression as a result of differences in the extent of social interactions. We housed threespine stickleback (Gasterosteus aculeatus females in either group conditions or individually for one week, then measured levels of gene expression in three brain regions using RNA-sequencing. We found that numerous genes in the hindbrain/cerebellum had altered expression in response to group or individual housing. However, relatively few genes were differentially expressed in either the diencephalon or telencephalon. The list of genes upregulated in fish from social groups included many genes related to neural development and cell adhesion as well as genes with functions in sensory signaling, stress, and social and reproductive behavior. The list of genes expressed at higher levels in individually-housed fish included several genes previously identified as regulated by social interactions in other animals. The identified genes are interesting targets for future research on the molecular mechanisms of normal social interactions.

Network-based differential gene expression analysis suggests cell cycle related genes regulated by E2F1 underlie the molecular difference between smoker and non-smoker lung adenocarcinoma

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2013-01-01

Background Differential gene expression (DGE) analysis is commonly used to reveal the deregulated molecular mechanisms of complex diseases. However, traditional DGE analysis (e.g., the t test or the rank sum test) tests each gene independently without considering interactions between them. Top-ranked differentially regulated genes prioritized by the analysis may not directly relate to the coherent molecular changes underlying complex diseases. Joint analyses of co-expression and DGE have been applied to reveal the deregulated molecular modules underlying complex diseases. Most of these methods consist of separate steps: first to identify gene-gene relationships under the studied phenotype then to integrate them with gene expression changes for prioritizing signature genes, or vice versa. It is warrant a method that can simultaneously consider gene-gene co-expression strength and corresponding expression level changes so that both types of information can be leveraged optimally. Results In this paper, we develop a gene module based method for differential gene expression analysis, named network-based differential gene expression (nDGE) analysis, a one-step integrative process for prioritizing deregulated genes and grouping them into gene modules. We demonstrate that nDGE outperforms existing methods in prioritizing deregulated genes and discovering deregulated gene modules using simulated data sets. When tested on a series of smoker and non-smoker lung adenocarcinoma data sets, we show that top differentially regulated genes identified by the rank sum test in different sets are not consistent while top ranked genes defined by nDGE in different data sets significantly overlap. nDGE results suggest that a differentially regulated gene module, which is enriched for cell cycle related genes and E2F1 targeted genes, plays a role in the molecular differences between smoker and non-smoker lung adenocarcinoma. Conclusions In this paper, we develop nDGE to prioritize

A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders.

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Jiang, Peng; Scarpa, Joseph R; Fitzpatrick, Karrie; Losic, Bojan; Gao, Vance D; Hao, Ke; Summa, Keith C; Yang, He S; Zhang, Bin; Allada, Ravi; Vitaterna, Martha H; Turek, Fred W; Kasarskis, Andrew

2015-05-05

Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

POSSIBLE RELATED FUNCTIONS OF THE NON-HOMOLOGOUS CO-REGULATED GENE PAIR PDCD10 AND SERPINI1

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Concetta Scimone

2017-04-01

Full Text Available Gene expression in mammalians is a very finely controlled mechanism, and bidirectional promoters can be considered one of the most compelling examples of the accuracy of genic expression coordination. As recently reported, a bidirectional promoter regulates the expression of the PDCD10(whose mutations cause familial Cerebral Cavernous Malformations (CCMs and SERPINI1 gene pair, even though they are non-homologous genes. The aim of this study was to identify any potential common roles of these two coregulated genes. An in-silico approach was used to identify functional correlations, using the BioGraph, IPA® and Cytoscape tools and the KEGG pathway database. The results obtained show that PDCD10 and SERPINI1 may co-regulate some cellular processes, particularly those related to focal adhesion maintenance. All common pathways identified for PDCD10 and SERPINI1 are closely associated with the pathogenic characteristics of CCMs; we thus hypothesize that genes involved in these networks may contribute to the development of CCMs.

Construction and comparison of gene co-expression networks shows complex plant immune responses

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Luis Guillermo Leal

2014-10-01

Full Text Available Gene co-expression networks (GCNs are graphic representations that depict the coordinated transcription of genes in response to certain stimuli. GCNs provide functional annotations of genes whose function is unknown and are further used in studies of translational functional genomics among species. In this work, a methodology for the reconstruction and comparison of GCNs is presented. This approach was applied using gene expression data that were obtained from immunity experiments in Arabidopsis thaliana, rice, soybean, tomato and cassava. After the evaluation of diverse similarity metrics for the GCN reconstruction, we recommended the mutual information coefficient measurement and a clustering coefficient-based method for similarity threshold selection. To compare GCNs, we proposed a multivariate approach based on the Principal Component Analysis (PCA. Branches of plant immunity that were exemplified by each experiment were analyzed in conjunction with the PCA results, suggesting both the robustness and the dynamic nature of the cellular responses. The dynamic of molecular plant responses produced networks with different characteristics that are differentiable using our methodology. The comparison of GCNs from plant pathosystems, showed that in response to similar pathogens plants could activate conserved signaling pathways. The results confirmed that the closeness of GCNs projected on the principal component space is an indicative of similarity among GCNs. This also can be used to understand global patterns of events triggered during plant immune responses.

The arabidopsis wall associated kinase-like 10 gene encodes a functional guanylyl cyclase and is co-expressed with pathogen defense related genes

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Meier, Stuart; Ruzvidzo, Oziniel; Morse, Monique; Donaldson, Lara; Kwezi, Lusisizwe; Gehring, Christoph A

2010-01-01

Background: Second messengers have a key role in linking environmental stimuli to physiological responses. One such messenger, guanosine 3?,5?-cyclic monophosphate (cGMP), has long been known to be an essential signaling molecule in many different physiological processes in higher plants, including biotic stress responses. To date, however, the guanylyl cyclase (GC) enzymes that catalyze the formation of cGMP from GTP have largely remained elusive in higher plants. Principal Findings: We have identified an Arabidopsis receptor type wall associated kinase-like molecule (AtWAKL10) as a candidate GC and provide experimental evidence to show that the intracellular domain of AtWAKL10431-700 can generate cGMP in vitro. Further, we also demonstrate that the molecule has kinase activity indicating that AtWAKL10 is a twin-domain catalytic protein. A co-expression and stimulus-specific expression analysis revealed that AtWAKL10 is consistently coexpressed with well characterized pathogen defense related genes and along with these genes is induced early and sharply in response to a range of pathogens and their elicitors. Conclusions: We demonstrate that AtWAKL10 is a twin-domain, kinase-GC signaling molecule that may function in biotic stress responses that are critically dependent on the second messenger cGMP. © 2010 Meier et al.

The arabidopsis wall associated kinase-like 10 gene encodes a functional guanylyl cyclase and is co-expressed with pathogen defense related genes

KAUST Repository

Meier, Stuart

2010-01-26

Background: Second messengers have a key role in linking environmental stimuli to physiological responses. One such messenger, guanosine 3?,5?-cyclic monophosphate (cGMP), has long been known to be an essential signaling molecule in many different physiological processes in higher plants, including biotic stress responses. To date, however, the guanylyl cyclase (GC) enzymes that catalyze the formation of cGMP from GTP have largely remained elusive in higher plants. Principal Findings: We have identified an Arabidopsis receptor type wall associated kinase-like molecule (AtWAKL10) as a candidate GC and provide experimental evidence to show that the intracellular domain of AtWAKL10431-700 can generate cGMP in vitro. Further, we also demonstrate that the molecule has kinase activity indicating that AtWAKL10 is a twin-domain catalytic protein. A co-expression and stimulus-specific expression analysis revealed that AtWAKL10 is consistently coexpressed with well characterized pathogen defense related genes and along with these genes is induced early and sharply in response to a range of pathogens and their elicitors. Conclusions: We demonstrate that AtWAKL10 is a twin-domain, kinase-GC signaling molecule that may function in biotic stress responses that are critically dependent on the second messenger cGMP. © 2010 Meier et al.

GOBO: gene expression-based outcome for breast cancer online.

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Markus Ringnér

Full Text Available Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo, allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1 rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2 identification of co-expressed genes for creation of potential metagenes, 3 association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

Early and long-standing rheumatoid arthritis: distinct molecular signatures identified by gene-expression profiling in synovia

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Lequerré, Thierry; Bansard, Carine; Vittecoq, Olivier; Derambure, Céline; Hiron, Martine; Daveau, Maryvonne; Tron, François; Ayral, Xavier; Biga, Norman; Auquit-Auckbur, Isabelle; Chiocchia, Gilles; Le Loët, Xavier; Salier, Jean-Philippe

2009-01-01

Introduction Rheumatoid arthritis (RA) is a heterogeneous disease and its underlying molecular mechanisms are still poorly understood. Because previous microarray studies have only focused on long-standing (LS) RA compared to osteoarthritis, we aimed to compare the molecular profiles of early and LS RA versus control synovia. Methods Synovial biopsies were obtained by arthroscopy from 15 patients (4 early untreated RA, 4 treated LS RA and 7 controls, who had traumatic or mechanical lesions). Extracted mRNAs were used for large-scale gene-expression profiling. The different gene-expression combinations identified by comparison of profiles of early, LS RA and healthy synovia were linked to the biological processes involved in each situation. Results Three combinations of 719, 116 and 52 transcripts discriminated, respectively, early from LS RA, and early or LS RA from healthy synovia. We identified several gene clusters and distinct molecular signatures specifically expressed during early or LS RA, thereby suggesting the involvement of different pathophysiological mechanisms during the course of RA. Conclusions Early and LS RA have distinct molecular signatures with different biological processes participating at different times during the course of the disease. These results suggest that better knowledge of the main biological processes involved at a given RA stage might help to choose the most appropriate treatment. PMID:19563633

Chromium downregulates the expression of Acetyl CoA Carboxylase 1 gene in lipogenic tissues of domestic goats: a potential strategy for meat quality improvement.

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Najafpanah, Mohammad Javad; Sadeghi, Mostafa; Zali, Abolfazl; Moradi-Shahrebabak, Hossein; Mousapour, Hojatollah

2014-06-15

Acetyl CoA Carboxylase 1 (ACC1) is a biotin-dependent enzyme that catalyzes the carboxylation of Acetyl CoA to form Malonyl CoA, the key intermediate metabolite in fatty acid synthesis. In this study, the mRNA expression of the ACC1 gene was evaluated in four different tissues (liver, visceral fat, subcutaneous fat, and longissimus muscle) of the domestic goat (Capra hircus) kids feeding on four different levels of trivalent chromium (0, 0.5, 1, and 1.5mg/day) as food supplementation. RT-qPCR technique was used for expression analyses and heat shock protein 90 gene (HSP-90) was considered as reference gene for data normalization. Our results revealed that 1.5mg/day chromium significantly reduced the expression of the ACC1 gene in liver, visceral fat, and subcutaneous fat tissues, but not in longissimus muscles (Pmeat quality in domestic animals. Copyright © 2014 Elsevier B.V. All rights reserved.

GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response.

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Zaag, Rim; Tamby, Jean Philippe; Guichard, Cécile; Tariq, Zakia; Rigaill, Guillem; Delannoy, Etienne; Renou, Jean-Pierre; Balzergue, Sandrine; Mary-Huard, Tristan; Aubourg, Sébastien; Martin-Magniette, Marie-Laure; Brunaud, Véronique

2015-01-01

CATdb (http://urgv.evry.inra.fr/CATdb) is a database providing a public access to a large collection of transcriptomic data, mainly for Arabidopsis but also for other plants. This resource has the rare advantage to contain several thousands of microarray experiments obtained with the same technical protocol and analyzed by the same statistical pipelines. In this paper, we present GEM2Net, a new module of CATdb that takes advantage of this homogeneous dataset to mine co-expression units and decipher Arabidopsis gene functions. GEM2Net explores 387 stress conditions organized into 18 biotic and abiotic stress categories. For each one, a model-based clustering is applied on expression differences to identify clusters of co-expressed genes. To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications. Exploiting protein-protein interactions and transcription factors-targets interactions enables to display gene networks. GEM2Net presents the analysis of the 18 stress categories, in which 17,264 genes are involved and organized within 681 co-expression clusters. The meta-data analyses were stored and organized to compose a dynamic Web resource. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Transient Co-Expression of Post-Transcriptional Gene Silencing Suppressors for Increased in Planta Expression of a Recombinant Anthrax Receptor Fusion Protein

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Kittipong Rattanaporn

2011-08-01

Full Text Available Potential epidemics of infectious diseases and the constant threat of bioterrorism demand rapid, scalable, and cost-efficient manufacturing of therapeutic proteins. Molecular farming of tobacco plants provides an alternative for the recombinant production of therapeutics. We have developed a transient production platform that uses Agrobacterium infiltration of Nicotiana benthamiana plants to express a novel anthrax receptor decoy protein (immunoadhesin, CMG2-Fc. This chimeric fusion protein, designed to protect against the deadly anthrax toxins, is composed of the von Willebrand factor A (VWA domain of human capillary morphogenesis 2 (CMG2, an effective anthrax toxin receptor, and the Fc region of human immunoglobulin G (IgG. We evaluated, in N. benthamiana intact plants and detached leaves, the expression of CMG2-Fc under the control of the constitutive CaMV 35S promoter, and the co-expression of CMG2-Fc with nine different viral suppressors of post-transcriptional gene silencing (PTGS: p1, p10, p19, p21, p24, p25, p38, 2b, and HCPro. Overall, transient CMG2-Fc expression was higher on intact plants than detached leaves. Maximum expression was observed with p1 co-expression at 3.5 days post-infiltration (DPI, with a level of 0.56 g CMG2-Fc per kg of leaf fresh weight and 1.5% of the total soluble protein, a ten-fold increase in expression when compared to absence of suppression. Co-expression with the p25 PTGS suppressor also significantly increased the CMG2-Fc expression level after just 3.5 DPI.

Transient co-expression of post-transcriptional gene silencing suppressors for increased in planta expression of a recombinant anthrax receptor fusion protein.

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Arzola, Lucas; Chen, Junxing; Rattanaporn, Kittipong; Maclean, James M; McDonald, Karen A

2011-01-01

Potential epidemics of infectious diseases and the constant threat of bioterrorism demand rapid, scalable, and cost-efficient manufacturing of therapeutic proteins. Molecular farming of tobacco plants provides an alternative for the recombinant production of therapeutics. We have developed a transient production platform that uses Agrobacterium infiltration of Nicotiana benthamiana plants to express a novel anthrax receptor decoy protein (immunoadhesin), CMG2-Fc. This chimeric fusion protein, designed to protect against the deadly anthrax toxins, is composed of the von Willebrand factor A (VWA) domain of human capillary morphogenesis 2 (CMG2), an effective anthrax toxin receptor, and the Fc region of human immunoglobulin G (IgG). We evaluated, in N. benthamiana intact plants and detached leaves, the expression of CMG2-Fc under the control of the constitutive CaMV 35S promoter, and the co-expression of CMG2-Fc with nine different viral suppressors of post-transcriptional gene silencing (PTGS): p1, p10, p19, p21, p24, p25, p38, 2b, and HCPro. Overall, transient CMG2-Fc expression was higher on intact plants than detached leaves. Maximum expression was observed with p1 co-expression at 3.5 days post-infiltration (DPI), with a level of 0.56 g CMG2-Fc per kg of leaf fresh weight and 1.5% of the total soluble protein, a ten-fold increase in expression when compared to absence of suppression. Co-expression with the p25 PTGS suppressor also significantly increased the CMG2-Fc expression level after just 3.5 DPI.

Deletion and Gene Expression Analyses Define the Paxilline Biosynthetic Gene Cluster in Penicillium paxilli

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Emily J. Parker

2013-08-01

Full Text Available The indole-diterpene paxilline is an abundant secondary metabolite synthesized by Penicillium paxilli. In total, 21 genes have been identified at the PAX locus of which six have been previously confirmed to have a functional role in paxilline biosynthesis. A combination of bioinformatics, gene expression and targeted gene replacement analyses were used to define the boundaries of the PAX gene cluster. Targeted gene replacement identified seven genes, paxG, paxA, paxM, paxB, paxC, paxP and paxQ that were all required for paxilline production, with one additional gene, paxD, required for regular prenylation of the indole ring post paxilline synthesis. The two putative transcription factors, PP104 and PP105, were not co-regulated with the pax genes and based on targeted gene replacement, including the double knockout, did not have a role in paxilline production. The relationship of indole dimethylallyl transferases involved in prenylation of indole-diterpenes such as paxilline or lolitrem B, can be found as two disparate clades, not supported by prenylation type (e.g., regular or reverse. This paper provides insight into the P. paxilli indole-diterpene locus and reviews the recent advances identified in paxilline biosynthesis.

Expression microarray identifies the unliganded glucocorticoid receptor as a regulator of gene expression in mammary epithelial cells

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Ritter, Heather D; Mueller, Christopher R

2014-01-01

While glucocorticoids and the liganded glucocorticoid receptor (GR) have a well-established role in the maintenance of differentiation and suppression of apoptosis in breast tissue, the involvement of unliganded GR in cellular processes is less clear. Our previous studies implicated unliganded GR as a positive regulator of the BRCA1 tumour suppressor gene in the absence of glucocorticoid hormone, which suggested it could play a similar role in the regulation of other genes. An shRNA vector directed against GR was used to create mouse mammary cell lines with depleted endogenous levels of this receptor in order to further characterize the role of GR in breast cells. An expression microarray screen for targets of unliganded GR was performed using our GR-depleted cell lines maintained in the absence of glucocorticoids. Candidate genes positively regulated by unliganded GR were identified, classified by Gene Ontology and Ingenuity Pathway Analysis, and validated using quantitative real-time reverse transcriptase PCR. Chromatin immunoprecipitation and dual luciferase expression assays were conducted to further investigate the mechanism through which unliganded GR regulates these genes. Expression microarray analysis revealed 260 targets negatively regulated and 343 targets positively regulated by unliganded GR. A number of the positively regulated targets were involved in pro-apoptotic networks, possibly opposing the activity of liganded GR targets. Validation and further analysis of five candidates from the microarray indicated that two of these, Hsd11b1 and Ch25h, were regulated by unliganded GR in a manner similar to Brca1 during glucocorticoid treatment. Furthermore, GR was shown to interact directly with and upregulate the Ch25h promoter in the absence, but not the presence, of hydrocortisone (HC), confirming our previously described model of gene regulation by unliganded GR. This work presents the first identification of targets of unliganded GR. We propose that

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

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Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

Combined Gene Expression and RNAi Screening to Identify Alkylation Damage Survival Pathways from Fly to Human.

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Zanotto-Filho, Alfeu; Dashnamoorthy, Ravi; Loranc, Eva; de Souza, Luis H T; Moreira, José C F; Suresh, Uthra; Chen, Yidong; Bishop, Alexander J R

2016-01-01

Alkylating agents are a key component of cancer chemotherapy. Several cellular mechanisms are known to be important for its survival, particularly DNA repair and xenobiotic detoxification, yet genomic screens indicate that additional cellular components may be involved. Elucidating these components has value in either identifying key processes that can be modulated to improve chemotherapeutic efficacy or may be altered in some cancers to confer chemoresistance. We therefore set out to reevaluate our prior Drosophila RNAi screening data by comparison to gene expression arrays in order to determine if we could identify any novel processes in alkylation damage survival. We noted a consistent conservation of alkylation survival pathways across platforms and species when the analysis was conducted on a pathway/process level rather than at an individual gene level. Better results were obtained when combining gene lists from two datasets (RNAi screen plus microarray) prior to analysis. In addition to previously identified DNA damage responses (p53 signaling and Nucleotide Excision Repair), DNA-mRNA-protein metabolism (transcription/translation) and proteasome machinery, we also noted a highly conserved cross-species requirement for NRF2, glutathione (GSH)-mediated drug detoxification and Endoplasmic Reticulum stress (ER stress)/Unfolded Protein Responses (UPR) in cells exposed to alkylation. The requirement for GSH, NRF2 and UPR in alkylation survival was validated by metabolomics, protein studies and functional cell assays. From this we conclude that RNAi/gene expression fusion is a valid strategy to rapidly identify key processes that may be extendable to other contexts beyond damage survival.

Combined Gene Expression and RNAi Screening to Identify Alkylation Damage Survival Pathways from Fly to Human.

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Alfeu Zanotto-Filho

Full Text Available Alkylating agents are a key component of cancer chemotherapy. Several cellular mechanisms are known to be important for its survival, particularly DNA repair and xenobiotic detoxification, yet genomic screens indicate that additional cellular components may be involved. Elucidating these components has value in either identifying key processes that can be modulated to improve chemotherapeutic efficacy or may be altered in some cancers to confer chemoresistance. We therefore set out to reevaluate our prior Drosophila RNAi screening data by comparison to gene expression arrays in order to determine if we could identify any novel processes in alkylation damage survival. We noted a consistent conservation of alkylation survival pathways across platforms and species when the analysis was conducted on a pathway/process level rather than at an individual gene level. Better results were obtained when combining gene lists from two datasets (RNAi screen plus microarray prior to analysis. In addition to previously identified DNA damage responses (p53 signaling and Nucleotide Excision Repair, DNA-mRNA-protein metabolism (transcription/translation and proteasome machinery, we also noted a highly conserved cross-species requirement for NRF2, glutathione (GSH-mediated drug detoxification and Endoplasmic Reticulum stress (ER stress/Unfolded Protein Responses (UPR in cells exposed to alkylation. The requirement for GSH, NRF2 and UPR in alkylation survival was validated by metabolomics, protein studies and functional cell assays. From this we conclude that RNAi/gene expression fusion is a valid strategy to rapidly identify key processes that may be extendable to other contexts beyond damage survival.

Differential gene expression and Hog1 interaction with osmoresponsive genes in the extremely halotolerant black yeast Hortaea werneckii

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Plemenitaš Ana

2007-08-01

Full Text Available Abstract Background Fluctuations in external salinity force eukaryotic cells to respond by changes in the gene expression of proteins acting in protective biochemical processes, thus counteracting the changing osmotic pressure. The high-osmolarity glycerol (HOG signaling pathway is essential for the efficient up-regulation of the osmoresponsive genes. In this study, the differential gene expression of the extremely halotolerant black yeast Hortaea werneckii was explored. Furthermore, the interaction of mitogen-activated protein kinase HwHog1 and RNA polymerase II with the chromatin in cells adapted to an extremely hypersaline environment was analyzed. Results A cDNA subtraction library was constructed for H. werneckii, adapted to moderate salinity or an extremely hypersaline environment of 4.5 M NaCl. An uncommon osmoresponsive set of 95 differentially expressed genes was identified. The majority of these had not previously been connected with the adaptation of salt-sensitive S. cerevisiae to hypersaline conditions. The transcriptional response in hypersaline-adapted and hypersaline-stressed cells showed that only a subset of the identified genes responded to acute salt-stress, whereas all were differentially expressed in adapted cells. Interaction with HwHog1 was shown for 36 of the 95 differentially expressed genes. The majority of the identified osmoresponsive and HwHog1-dependent genes in H. werneckii have not been previously reported as Hog1-dependent genes in the salt-sensitive S. cerevisiae. The study further demonstrated the co-occupancy of HwHog1 and RNA polymerase II on the chromatin of 17 up-regulated and 2 down-regulated genes in 4.5 M NaCl-adapted H. werneckii cells. Conclusion Extremely halotolerant H. werneckii represents a suitable and highly relevant organism to study cellular responses to environmental salinity. In comparison with the salt-sensitive S. cerevisiae, this yeast shows a different set of genes being expressed at

Gene expression profiling of prostate tissue identifies chromatin regulation as a potential link between obesity and lethal prostate cancer.

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Ebot, Ericka M; Gerke, Travis; Labbé, David P; Sinnott, Jennifer A; Zadra, Giorgia; Rider, Jennifer R; Tyekucheva, Svitlana; Wilson, Kathryn M; Kelly, Rachel S; Shui, Irene M; Loda, Massimo; Kantoff, Philip W; Finn, Stephen; Vander Heiden, Matthew G; Brown, Myles; Giovannucci, Edward L; Mucci, Lorelei A

2017-11-01

Obese men are at higher risk of advanced prostate cancer and cancer-specific mortality; however, the biology underlying this association remains unclear. This study examined gene expression profiles of prostate tissue to identify biological processes differentially expressed by obesity status and lethal prostate cancer. Gene expression profiling was performed on tumor (n = 402) and adjacent normal (n = 200) prostate tissue from participants in 2 prospective cohorts who had been diagnosed with prostate cancer from 1982 to 2005. Body mass index (BMI) was calculated from the questionnaire immediately preceding cancer diagnosis. Men were followed for metastases or prostate cancer-specific death (lethal disease) through 2011. Gene Ontology biological processes differentially expressed by BMI were identified using gene set enrichment analysis. Pathway scores were computed by averaging the signal intensities of member genes. Odds ratios (ORs) for lethal prostate cancer were estimated with logistic regression. Among 402 men, 48% were healthy weight, 31% were overweight, and 21% were very overweight/obese. Fifteen gene sets were enriched in tumor tissue, but not normal tissue, of very overweight/obese men versus healthy-weight men; 5 of these were related to chromatin modification and remodeling (false-discovery rate 7, 41% vs 17%; P = 2 × 10 -4 ) and an increased risk of lethal disease that was independent of grade and stage (OR, 5.26; 95% confidence interval, 2.37-12.25). This study improves our understanding of the biology of aggressive prostate cancer and identifies a potential mechanistic link between obesity and prostate cancer death that warrants further study. Cancer 2017;123:4130-4138. © 2017 American Cancer Society. © 2017 American Cancer Society.

Genome-wide identification of physically clustered genes suggests chromatin-level co-regulation in male reproductive development in Arabidopsis thaliana.

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Reimegård, Johan; Kundu, Snehangshu; Pendle, Ali; Irish, Vivian F; Shaw, Peter; Nakayama, Naomi; Sundström, Jens F; Emanuelsson, Olof

2017-04-07

Co-expression of physically linked genes occurs surprisingly frequently in eukaryotes. Such chromosomal clustering may confer a selective advantage as it enables coordinated gene regulation at the chromatin level. We studied the chromosomal organization of genes involved in male reproductive development in Arabidopsis thaliana. We developed an in-silico tool to identify physical clusters of co-regulated genes from gene expression data. We identified 17 clusters (96 genes) involved in stamen development and acting downstream of the transcriptional activator MS1 (MALE STERILITY 1), which contains a PHD domain associated with chromatin re-organization. The clusters exhibited little gene homology or promoter element similarity, and largely overlapped with reported repressive histone marks. Experiments on a subset of the clusters suggested a link between expression activation and chromatin conformation: qRT-PCR and mRNA in situ hybridization showed that the clustered genes were up-regulated within 48 h after MS1 induction; out of 14 chromatin-remodeling mutants studied, expression of clustered genes was consistently down-regulated only in hta9/hta11, previously associated with metabolic cluster activation; DNA fluorescence in situ hybridization confirmed that transcriptional activation of the clustered genes was correlated with open chromatin conformation. Stamen development thus appears to involve transcriptional activation of physically clustered genes through chromatin de-condensation. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identifying key genes associated with acute myocardial infarction.

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Cheng, Ming; An, Shoukuan; Li, Junquan

2017-10-01

This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data. Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes. A total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21-5p and hsa-miR-30c-5p were obviously decreased in AMI. A total of 41 DEGs, such as SOCS3, VAPA, and COL5A2, are speculated to have roles in the pathogenesis of AMI; 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p may be involved in the regulation of the expression of these DEGs.

Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data

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REN, ZHONGLU; WANG, WENHUI; LI, JINMING

2015-01-01

Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristi...

The gsdf gene locus harbors evolutionary conserved and clustered genes preferentially expressed in fish previtellogenic oocytes.

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Gautier, Aude; Le Gac, Florence; Lareyre, Jean-Jacques

2011-02-01

display a different cellular localization compared to that of the gsdf gene indicating that the later gene is not co-regulated. Interestingly, our study identifies new clustered genes that are specifically expressed in previtellogenic oocytes (nup54, aff1, klhl8, sdad1). Copyright © 2010 Elsevier B.V. All rights reserved.

Transcriptome analysis reveals key differentially expressed genes involved in wheat grain development

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Yonglong Yu

2016-04-01

Full Text Available Wheat seed development is an important physiological process of seed maturation and directly affects wheat yield and quality. In this study, we performed dynamic transcriptome microarray analysis of an elite Chinese bread wheat cultivar (Jimai 20 during grain development using the GeneChip Wheat Genome Array. Grain morphology and scanning electron microscope observations showed that the period of 11–15 days post-anthesis (DPA was a key stage for the synthesis and accumulation of seed starch. Genome-wide transcriptional profiling and significance analysis of microarrays revealed that the period from 11 to 15 DPA was more important than the 15–20 DPA stage for the synthesis and accumulation of nutritive reserves. Series test of cluster analysis of differential genes revealed five statistically significant gene expression profiles. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes, and MapMan analysis revealed expression changes within functional groups during seed development. Metabolic pathway network analysis showed that major and minor metabolic pathways regulate one another to ensure regular seed development and nutritive reserve accumulation. We performed gene co-expression network analysis to identify genes that play vital roles in seed development and identified several key genes involved in important metabolic pathways. The transcriptional expression of eight key genes involved in starch and protein synthesis and stress defense was further validated by qRT-PCR. Our results provide new insight into the molecular mechanisms of wheat seed development and the determinants of yield and quality.

Evidence of inflammatory immune signaling in chronic fatigue syndrome: A pilot study of gene expression in peripheral blood

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Vernon Suzanne D

2008-09-01

Full Text Available Abstract Background Genomic profiling of peripheral blood reveals altered immunity in chronic fatigue syndrome (CFS however interpretation remains challenging without immune demographic context. The object of this work is to identify modulation of specific immune functional components and restructuring of co-expression networks characteristic of CFS using the quantitative genomics of peripheral blood. Methods Gene sets were constructed a priori for CD4+ T cells, CD8+ T cells, CD19+ B cells, CD14+ monocytes and CD16+ neutrophils from published data. A group of 111 women were classified using empiric case definition (U.S. Centers for Disease Control and Prevention and unsupervised latent cluster analysis (LCA. Microarray profiles of peripheral blood were analyzed for expression of leukocyte-specific gene sets and characteristic changes in co-expression identified from topological evaluation of linear correlation networks. Results Median expression for a set of 6 genes preferentially up-regulated in CD19+ B cells was significantly lower in CFS (p = 0.01 due mainly to PTPRK and TSPAN3 expression. Although no other gene set was differentially expressed at p Conclusion Dissection of blood microarray profiles points to B cell dysfunction with coordinated immune activation supporting persistent inflammation and antibody-mediated NK cell modulation of T cell activity. This has clinical implications as the CD19+ genes identified could provide robust and biologically meaningful basis for the early detection and unambiguous phenotyping of CFS.

Radiation-modulated gene expression in C. elegans

International Nuclear Information System (INIS)

Nelson, G.A.; Bayeta, E.; Perez, C.; Lloyd, E.; Jones, T.; Smith, A.; Tian, J.

2003-01-01

Full text: We use the nematode C. elegans to characterize the genotoxic and cytotoxic effects of ionizing radiation with emphasis effects of charged particle radiation and have described the fluence vs. response relationships for mutation, chromosome aberration and certain developmental errors. These endpoints quantify the biological after repair and compensation pathways have completed their work. In order to address the control of these reactions we have turned to gene expression profiling to identify genes that uniquely respond to high LET species or respond differentially as a function of radiation properties. We have employed whole genome microarray methods to map gene expression following exposure to gamma rays, protons and accelerated iron ions. We found that 599 of 17871 genes analyzed showed differential expression 3 hrs after exposure to 3 Gy of at least one radiation types. 193 were up-regulated, 406 were down-regulated, and 90% were affected by only one species of radiation. Genes whose transcription levels responded significantly mapped to definite statistical clusters that were unique for each radiation type. We are now trying to establish the functional relationships of the genes their relevance to mitigation of radiation-induced damage. Three approaches are being used. First, bioinformatics tools are being used to determine the roles of genes in co-regulated gene sets. Second, we are applying the technique of RNA interference to determine whether our radiation-induced genes affect cell survival (measured in terms of embryo survival) and chromosome aberration (intestinal anaphase bridges). Finally we are focussing on the response of the most strongly-regulated gene in our data set. This is the autosomal gene, F36D3.9, whose predicted structure is that of a cysteine protease resembling cathepsin B. An enzymological approach is being used to characterize this gene at the protein level. This work was supported by NASA Cooperative Agreement NCC9-149

The Medicago truncatula gene expression atlas web server

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Tang Yuhong

2009-12-01

Full Text Available Abstract Background Legumes (Leguminosae or Fabaceae play a major role in agriculture. Transcriptomics studies in the model legume species, Medicago truncatula, are instrumental in helping to formulate hypotheses about the role of legume genes. With the rapid growth of publically available Affymetrix GeneChip Medicago Genome Array GeneChip data from a great range of tissues, cell types, growth conditions, and stress treatments, the legume research community desires an effective bioinformatics system to aid efforts to interpret the Medicago genome through functional genomics. We developed the Medicago truncatula Gene Expression Atlas (MtGEA web server for this purpose. Description The Medicago truncatula Gene Expression Atlas (MtGEA web server is a centralized platform for analyzing the Medicago transcriptome. Currently, the web server hosts gene expression data from 156 Affymetrix GeneChip® Medicago genome arrays in 64 different experiments, covering a broad range of developmental and environmental conditions. The server enables flexible, multifaceted analyses of transcript data and provides a range of additional information about genes, including different types of annotation and links to the genome sequence, which help users formulate hypotheses about gene function. Transcript data can be accessed using Affymetrix probe identification number, DNA sequence, gene name, functional description in natural language, GO and KEGG annotation terms, and InterPro domain number. Transcripts can also be discovered through co-expression or differential expression analysis. Flexible tools to select a subset of experiments and to visualize and compare expression profiles of multiple genes have been implemented. Data can be downloaded, in part or full, in a tabular form compatible with common analytical and visualization software. The web server will be updated on a regular basis to incorporate new gene expression data and genome annotation, and is accessible

Comprehensive analysis of the flowering genes in Chinese cabbage and examination of evolutionary pattern of CO-like genes in plant kingdom

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Song, Xiaoming; Duan, Weike; Huang, Zhinan; Liu, Gaofeng; Wu, Peng; Liu, Tongkun; Li, Ying; Hou, Xilin

2015-09-01

In plants, flowering is the most important transition from vegetative to reproductive growth. The flowering patterns of monocots and eudicots are distinctly different, but few studies have described the evolutionary patterns of the flowering genes in them. In this study, we analysed the evolutionary pattern, duplication and expression level of these genes. The main results were as follows: (i) characterization of flowering genes in monocots and eudicots, including the identification of family-specific, orthologous and collinear genes; (ii) full characterization of CONSTANS-like genes in Brassica rapa (BraCOL genes), the key flowering genes; (iii) exploration of the evolution of COL genes in plant kingdom and construction of the evolutionary pattern of COL genes; (iv) comparative analysis of CO and FT genes between Brassicaceae and Grass, which identified several family-specific amino acids, and revealed that CO and FT protein structures were similar in B. rapa and Arabidopsis but different in rice; and (v) expression analysis of photoperiod pathway-related genes in B. rapa under different photoperiod treatments by RT-qPCR. This analysis will provide resources for understanding the flowering mechanisms and evolutionary pattern of COL genes. In addition, this genome-wide comparative study of COL genes may also provide clues for evolution of other flowering genes.

Bioremediation of trace cobalt from simulated spent decontamination solutions of nuclear power reactors using E. coli expressing NiCoT genes

International Nuclear Information System (INIS)

Raghu, G.; Maruthi Mohan, P.; Balaji, V.; Venkateswaran, G.; Rodrigue, A.; Lyon 1 Univ., 69

2008-01-01

Removal of radioactive cobalt at trace levels (∼nM) in the presence of large excess (10 6 -fold) of corrosion product ions of complexed Fe, Cr, and Ni in spent chemical decontamination formulations (simulated effluent) of nuclear reactors is currently done by using synthetic organic ion exchangers. A large volume of solid waste is generated due to the nonspecific nature of ion sorption. Our earlier work using various fungi and bacteria, with the aim of nuclear waste volume reduction, realized up to 30% of Co removal with specific capacities calculated up to 1 μg/g in 6-24 h. In the present study using engineered Escherichia coli expressing NiCoT genes from Rhodopseudomonas palustris CGA009 (RP) and Novosphingobium aromaticivorans F-199 (NA), we report a significant increase in the specific capacity for Co removal (12 μg/g) in 1-h exposure to simulated effluent. About 85% of Co removal was achieved in a two-cycle treatment with the cloned bacteria. Expression of NiCoT genes in the E. coli knockout mutant of NiCoT efflux gene (rcnA) was more efficient as compared to expression in wild-type E. coli MC4100, JM109 and BL21 (DE3) hosts. The viability of the E. coli strains in the formulation as well as at different doses of gamma rays exposure and the effect of gamma dose on their cobalt removal capacity are determined. The potential application scheme of the above process of bioremediation of cobalt from nuclear power reactor chemical decontamination effluents is discussed. (orig.)

Differential effects of Pseudomonas mendocina and Glomus intraradices on lettuce plants physiological response and aquaporin PIP2 gene expression under elevated atmospheric CO2 and drought.

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Alguacil, Maria Del Mar; Kohler, Josef; Caravaca, Fuensanta; Roldán, Antonio

2009-11-01

Arbuscular mycorrhizal (AM) symbiosis and plant-growth-promoting rhizobacterium (PGPR) can alleviate the effects of water stress in plants, but it is unknown whether these benefits can be maintained at elevated CO2. Therefore, we carried out a study where seedlings of Lactuca sativa were inoculated with the AM fungus (AMF) Glomus intraradices N.C. Schenk & G.S. Sm. or the PGPR Pseudomonas mendocina Palleroni and subjected to two levels of watering and two levels of atmospheric CO2 to ascertain their effects on plant physiological parameters and gene expression of one PIP aquaporin in roots. The inoculation with PGPR produced the greatest growth in lettuce plants under all assayed treatments as well as the highest foliar potassium concentration and leaf relative water content under elevated [CO2] and drought. However, under such conditions, the PIP2 gene expression remained almost unchanged. G. intraradices increased significantly the AMF colonization, foliar phosphorus concentration and leaf relative water content in plants grown under drought and elevated [CO2]. Under drought and elevated [CO2], the plants inoculated with G. intraradices showed enhanced expression of the PIP2 gene as compared to P. mendocina or control plants. Our results suggest that both microbial inoculation treatments could help to alleviate drought at elevated [CO2]. However, the PIP2 gene expression was increased only by the AMF but not by the PGPR under these conditions.

Comprehensive analysis of differential co-expression patterns reveal transcriptional dysregulation mechanism and identify novel prognostic lncRNAs in esophageal squamous cell carcinoma

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Li Z

2017-06-01

Full Text Available Zhen Li,1 Qianlan Yao,1 Songjian Zhao,1 Yin Wang,2,3 Yixue Li,1,4 Zhen Wang4 1School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 2Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, 3Collaborative Innovation Center for Genetics and Development, Fudan University, 4Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People’s Republic of China Abstract: Esophageal squamous cell carcinoma (ESCC is one of the most common malignancies worldwide and occurs at a relatively high frequency in People’s Republic of China. However, the molecular mechanism underlying ESCC is still unclear. In this study, the mRNA and long non-coding RNA (lncRNA expression profiles of ESCC were downloaded from the Gene Expression Omnibus database, and then differential co-expression analysis was used to reveal the altered co-expression relationship of gene pairs in ESCC tumors. A total of 3,709 mRNAs and 923 lncRNAs were differentially co-expressed between normal and tumor tissues, and we found that most of the gene pairs lost associations in the tumor tissues. The differential regulatory networking approach deciphered that transcriptional dysregulation was ubiquitous in ESCC, and most of the differentially regulated links were modulated by 37 TFs. Our study also found that two novel lncRNAs (ADAMTS9-AS1 and AP000696.2 might be essential in the development of ectoderm and epithelial cells, which could significantly stratify ESCC patients into high-risk and low-risk groups, and were much better than traditional clinical tumor markers. Further inspection of two risk groups showed that the changes in TF-target regulation in the high-risk patients were significantly higher than those in the low-risk patients. In addition, four signal transduction-related DCmRNAs (ERBB3, ENSA, KCNK7, MFSD5

Gene expression profiling and candidate gene resequencing identifies pathways and mutations important for malignant transformation caused by leukemogenic fusion genes.

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Novak, Rachel L; Harper, David P; Caudell, David; Slape, Christopher; Beachy, Sarah H; Aplan, Peter D

2012-12-01

NUP98-HOXD13 (NHD13) and CALM-AF10 (CA10) are oncogenic fusion proteins produced by recurrent chromosomal translocations in patients with acute myeloid leukemia (AML). Transgenic mice that express these fusions develop AML with a long latency and incomplete penetrance, suggesting that collaborating genetic events are required for leukemic transformation. We employed genetic techniques to identify both preleukemic abnormalities in healthy transgenic mice as well as collaborating events leading to leukemic transformation. Candidate gene resequencing revealed that 6 of 27 (22%) CA10 AMLs spontaneously acquired a Ras pathway mutation and 8 of 27 (30%) acquired an Flt3 mutation. Two CA10 AMLs acquired an Flt3 internal-tandem duplication, demonstrating that these mutations can be acquired in murine as well as human AML. Gene expression profiles revealed a marked upregulation of Hox genes, particularly Hoxa5, Hoxa9, and Hoxa10 in both NHD13 and CA10 mice. Furthermore, mir196b, which is embedded within the Hoxa locus, was overexpressed in both CA10 and NHD13 samples. In contrast, the Hox cofactors Meis1 and Pbx3 were differentially expressed; Meis1 was increased in CA10 AMLs but not NHD13 AMLs, whereas Pbx3 was consistently increased in NHD13 but not CA10 AMLs. Silencing of Pbx3 in NHD13 cells led to decreased proliferation, increased apoptosis, and decreased colony formation in vitro, suggesting a previously unexpected role for Pbx3 in leukemic transformation. Published by Elsevier Inc.

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

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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.

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

Science.gov (United States)

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

Identifying Differentially Expressed Genes in Pollen from Self-Incompatible “Wuzishatangju” and Self-Compatible “Shatangju” Mandarins

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Guibing Hu

2013-04-01

Full Text Available Self-incompatibility (SI is one of the important factors that can result in seedless fruit in Citrus. However, the molecular mechanism of SI in Citrus is not yet clear. In this study, two suppression subtractive hybridization (SSH libraries (forward, F and reverse, R were constructed to isolate differentially expressed genes in pollen from “Wuzishatangju” (SI and “Shatangju” (self-compatibility, SC mandarins. Four hundred and sixty-eight differentially expressed cDNA clones from 2077 positive clones were sequenced and identified. Differentially expressed ESTs are possibly involved in the SI reaction of “Wuzishatangju” by regulating pollen development, kinase activity, ubiquitin pathway, pollen-pistil interaction, and calcium ion binding. Twenty five SI candidate genes were obtained, six of which displayed specific expression patterns in various organs and stages after self- and cross-pollination. The expression level of the F-box gene (H304 and S1 (F78 in the pollen of “Wuzishatangju” was 5-fold higher than that in “Shatangju” pollen. The F-box gene, S1, UBE2, UBE3, RNaseHII, and PCP were obviously up-regulated in pistils at 3 d after self-pollination of “Wuzishatangju”, approximately 3-, 2-, 10-, 5-, 5-, and 2-fold higher, respectively than that at the same stage after cross-pollination of “Wuzishatangju” × “Shatangju” pistils. The potential involvement of these genes in the pollen SI reaction of “Wuzishatangju” is discussed.

GR and ER co-activation alters the expression of differentiation genes and associates with improved ER+ breast cancer outcome

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West, Diana C.; Pan, Deng; Tonsing-Carter, Eva Y.; Hernandez, Kyle M.; Pierce, Charles F.; Styke, Sarah C.; Bowie, Kathleen R.; Garcia, Tzintzuni I.; Kocherginsky, Masha; Conzen, Suzanne D.

2016-01-01

In estrogen receptor (ER)-negative breast cancer (BC), high tumor glucocorticoid receptor (GR) expression has been associated with a relatively poor outcome. In contrast, using a meta-analysis of several genomic datasets, here we find that tumor GR mRNA expression is associated with improved ER+ relapse-free survival (RFS) (independently of progesterone receptor (PR) expression). To understand the mechanism by which GR expression is associated with a better ER+ BC outcome, the global effect of GR-mediated transcriptional activation in ER+ BC cells was studied. Analysis of GR chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) in ER+/GR+ MCF-7 cells revealed that upon co-activation of GR and ER, GR chromatin association became enriched at proximal promoter regions. Furthermore, following ER activation, increased GR chromatin association was observed at ER, FOXO, and AP1 response elements. In addition, ER associated with GR response elements, suggesting that ER and GR interact in a complex. Co-activation of GR and ER resulted in increased expression (relative to ER activation alone) of transcripts that encode proteins promoting cellular differentiation (e.g. KDM4B, VDR) and inhibiting the Wnt-signaling pathway (IGFBP4). Finally, expression of these individual pro-differentiation genes was associated with significantly improved RFS in ER+ BC patients. Together, these data suggest that the co-expression and subsequent activity of tumor cell GR and ER contribute to the less aggressive natural history of early-stage BC by coordinating the altered expression of genes favoring differentiation. Implications The interaction between estrogen and glucocorticoid receptor activity highlights the importance of context-dependent nuclear receptor function in cancer. PMID:27141101

Complex nature of SNP genotype effects on gene expression in primary human leucocytes

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Dinesen Lotte C

2009-01-01

Full Text Available Abstract Background Genome wide association studies have been hugely successful in identifying disease risk variants, yet most variants do not lead to coding changes and how variants influence biological function is usually unknown. Methods We correlated gene expression and genetic variation in untouched primary leucocytes (n = 110 from individuals with celiac disease – a common condition with multiple risk variants identified. We compared our observations with an EBV-transformed HapMap B cell line dataset (n = 90, and performed a meta-analysis to increase power to detect non-tissue specific effects. Results In celiac peripheral blood, 2,315 SNP variants influenced gene expression at 765 different transcripts (cis expression quantitative trait loci, eQTLs. 135 of the detected SNP-probe effects (reflecting 51 unique probes were also detected in a HapMap B cell line published dataset, all with effects in the same allelic direction. Overall gene expression differences within the two datasets predominantly explain the limited overlap in observed cis-eQTLs. Celiac associated risk variants from two regions, containing genes IL18RAP and CCR3, showed significant cis genotype-expression correlations in the peripheral blood but not in the B cell line datasets. We identified 14 genes where a SNP affected the expression of different probes within the same gene, but in opposite allelic directions. By incorporating genetic variation in co-expression analyses, functional relationships between genes can be more significantly detected. Conclusion In conclusion, the complex nature of genotypic effects in human populations makes the use of a relevant tissue, large datasets, and analysis of different exons essential to enable the identification of the function for many genetic risk variants in common diseases.

Comparison of Expression Profiles in Ovarian Epithelium In Vivo and Ovarian Cancer Identifies Novel Candidate Genes Involved in Disease Pathogenesis

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Emmanuel, Catherine; Gava, Natalie; Kennedy, Catherine; Balleine, Rosemary L.; Sharma, Raghwa; Wain, Gerard; Brand, Alison; Hogg, Russell; Etemadmoghadam, Dariush; George, Joshy; Birrer, Michael J.; Clarke, Christine L.; Chenevix-Trench, Georgia; Bowtell, David D. L.; Harnett, Paul R.; deFazio, Anna

2011-01-01

Molecular events leading to epithelial ovarian cancer are poorly understood but ovulatory hormones and a high number of life-time ovulations with concomitant proliferation, apoptosis, and inflammation, increases risk. We identified genes that are regulated during the estrous cycle in murine ovarian surface epithelium and analysed these profiles to identify genes dysregulated in human ovarian cancer, using publically available datasets. We identified 338 genes that are regulated in murine ovarian surface epithelium during the estrous cycle and dysregulated in ovarian cancer. Six of seven candidates selected for immunohistochemical validation were expressed in serous ovarian cancer, inclusion cysts, ovarian surface epithelium and in fallopian tube epithelium. Most were overexpressed in ovarian cancer compared with ovarian surface epithelium and/or inclusion cysts (EpCAM, EZH2, BIRC5) although BIRC5 and EZH2 were expressed as highly in fallopian tube epithelium as in ovarian cancer. We prioritised the 338 genes for those likely to be important for ovarian cancer development by in silico analyses of copy number aberration and mutation using publically available datasets and identified genes with established roles in ovarian cancer as well as novel genes for which we have evidence for involvement in ovarian cancer. Chromosome segregation emerged as an important process in which genes from our list of 338 were over-represented including two (BUB1, NCAPD2) for which there is evidence of amplification and mutation. NUAK2, upregulated in ovarian surface epithelium in proestrus and predicted to have a driver mutation in ovarian cancer, was examined in a larger cohort of serous ovarian cancer where patients with lower NUAK2 expression had shorter overall survival. In conclusion, defining genes that are activated in normal epithelium in the course of ovulation that are also dysregulated in cancer has identified a number of pathways and novel candidate genes that may contribute

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus

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Chaoqun Li

2018-01-01

Full Text Available Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice. Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus.

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Li, Chaoqun; Cao, Feifei; Li, Shengli; Huang, Shenglin; Li, Wei; Abumaria, Nashat

2017-01-01

Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA) has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice). Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to stress

Functional modules by relating protein interaction networks and gene expression.

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Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia.

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Badea, Liviu; Herlea, Vlad; Dima, Simona Olimpia; Dumitrascu, Traian; Popescu, Irinel

2008-01-01

The precise details of pancreatic ductal adenocarcinoma (PDAC) pathogenesis are still insufficiently known, requiring the use of high-throughput methods. However, PDAC is especially difficult to study using microarrays due to its strong desmoplastic reaction, which involves a hyperproliferating stroma that effectively "masks" the contribution of the minoritary neoplastic epithelial cells. Thus it is not clear which of the genes that have been found differentially expressed between normal and whole tumor tissues are due to the tumor epithelia and which simply reflect the differences in cellular composition. To address this problem, laser microdissection studies have been performed, but these have to deal with much smaller tissue sample quantities and therefore have significantly higher experimental noise. In this paper we combine our own large sample whole-tissue study with a previously published smaller sample microdissection study by Grützmann et al. to identify the genes that are specifically overexpressed in PDAC tumor epithelia. The overlap of this list of genes with other microarray studies of pancreatic cancer as well as with the published literature is impressive. Moreover, we find a number of genes whose over-expression appears to be inversely correlated with patient survival: keratin 7, laminin gamma 2, stratifin, platelet phosphofructokinase, annexin A2, MAP4K4 and OACT2 (MBOAT2), which are all specifically upregulated in the neoplastic epithelia, rather than the tumor stroma. We improve on other microarray studies of PDAC by putting together the higher statistical power due to a larger number of samples with information about cell-type specific expression and patient survival.

Co-Expression and Co-Localization of Cartilage Glycoproteins CHI3L1 and Lubricin in Osteoarthritic Cartilage: Morphological, Immunohistochemical and Gene Expression Profiles

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Marta Anna Szychlinska

2016-03-01

Full Text Available Osteoarthritis is the most common human arthritis characterized by degeneration of articular cartilage. Several studies reported that levels of human cartilage glycoprotein chitinase 3-like-1 (CHI3L1 are known as a potential marker for the activation of chondrocytes and the progression of Osteoarthritis (OA, whereas lubricin appears to be chondroprotective. The aim of this study was to investigate the co-expression and co-localization of CHI3L1 and lubricin in normal and osteoarthritic rat articular cartilage to correlate their modified expression to a specific grade of OA. Samples of normal and osteoarthritic rat articular cartilage were analyzed by the Kellgren–Lawrence OA severity scores, the Kraus’ modified Mankin score and the Histopathology Osteoarthritis Research Society International (OARSI system for histomorphometric evaluations, and through CHI3L1 and lubricin gene expression, immunohistochemistry and double immuno-staining analysis. The immunoexpression and the mRNA levels of lubricin increased in normal cartilage and decreased in OA cartilage (normal vs. OA, p < 0.01. By contrast, the immunoexpression and the mRNA levels of CHI3L1 increased in OA cartilage and decreased in normal cartilage (normal vs. OA, p < 0.01. Our findings are consistent with reports suggesting that these two glycoproteins are functionally associated with the development of OA and in particular with grade 2/3 of OA, suggesting that in the future they could be helpful to stage the severity and progression of the disease.

Analyses of expressed sequence tags from the maize foliar pathogen Cercospora zeae-maydis identify novel genes expressed during vegetative, infectious, and reproductive growth

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Kema Gert HJ

2008-11-01

Full Text Available Abstract Background The ascomycete fungus Cercospora zeae-maydis is an aggressive foliar pathogen of maize that causes substantial losses annually throughout the Western Hemisphere. Despite its impact on maize production, little is known about the regulation of pathogenesis in C. zeae-maydis at the molecular level. The objectives of this study were to generate a collection of expressed sequence tags (ESTs from C. zeae-maydis and evaluate their expression during vegetative, infectious, and reproductive growth. Results A total of 27,551 ESTs was obtained from five cDNA libraries constructed from vegetative and sporulating cultures of C. zeae-maydis. The ESTs, grouped into 4088 clusters and 531 singlets, represented 4619 putative unique genes. Of these, 36% encoded proteins similar (E value ≤ 10-05 to characterized or annotated proteins from the NCBI non-redundant database representing diverse molecular functions and biological processes based on Gene Ontology (GO classification. We identified numerous, previously undescribed genes with potential roles in photoreception, pathogenesis, and the regulation of development as well as Zephyr, a novel, actively transcribed transposable element. Differential expression of selected genes was demonstrated by real-time PCR, supporting their proposed roles in vegetative, infectious, and reproductive growth. Conclusion Novel genes that are potentially involved in regulating growth, development, and pathogenesis were identified in C. zeae-maydis, providing specific targets for characterization by molecular genetics and functional genomics. The EST data establish a foundation for future studies in evolutionary and comparative genomics among species of Cercospora and other groups of plant pathogenic fungi.

RNA-seq methods for identifying differentially expressed gene in human pancreatic islet cells treated with pro-inflammatory cytokines.

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Li, Bo; Bi, Chang Long; Lang, Ning; Li, Yu Ze; Xu, Chao; Zhang, Ying Qi; Zhai, Ai Xia; Cheng, Zhi Feng

2014-01-01

Type 1 diabetes is a chronic autoimmune disease in which pancreatic beta cells are killed by the infiltrating immune cells as well as the cytokines released by these cells. Many studies indicate that inflammatory mediators have an essential role in this disease. In the present study, we profiled the transcriptome in human islets of langerhans under control conditions or following exposure to the pro-inflammatory cytokines based on the RNA sequencing dataset downloaded from SRA database. After filtered the low-quality ones, the RNA readers was aligned to human genome hg19 by TopHat and then assembled by Cufflinks. The expression value of each transcript was calculated and consequently differentially expressed genes were screened out. Finally, a total of 63 differentially expressed genes were identified including 60 up-regulated and three down-regulated genes. GBP5 and CXCL9 stood out as the top two most up-regulated genes in cytokines treated samples with the log2 fold change of 12.208 and 10.901, respectively. Meanwhile, PTF1A and REG3G were identified as the top two most down-regulated genes with the log2 fold change of -3.759 and -3.606, respectively. Of note, we also found 262 lncRNAs (long non-coding RNA), 177 of which were inferred as novel lncRNAs. Further in-depth follow-up analysis of the transcriptional regulation reported in this study may shed light on the specific function of these lncRNA.

Co-expression networks reveal the tissue-specific regulation of transcription and splicing.

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Saha, Ashis; Kim, Yungil; Gewirtz, Ariel D H; Jo, Brian; Gao, Chuan; McDowell, Ian C; Engelhardt, Barbara E; Battle, Alexis

2017-11-01

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues. © 2017 Saha et al.; Published by Cold Spring Harbor Laboratory Press.

Transcriptional Profiling of Cholinergic Neurons From Basal Forebrain Identifies Changes in Expression of Genes Between Sleep and Wake.

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Nikonova, Elena V; Gilliland, Jason DA; Tanis, Keith Q; Podtelezhnikov, Alexei A; Rigby, Alison M; Galante, Raymond J; Finney, Eva M; Stone, David J; Renger, John J; Pack, Allan I; Winrow, Christopher J

2017-06-01

To assess differences in gene expression in cholinergic basal forebrain cells between sleeping and sleep-deprived mice sacrificed at the same time of day. Tg(ChAT-eGFP)86Gsat mice expressing enhanced green fluorescent protein (eGFP) under control of the choline acetyltransferase (Chat) promoter were utilized to guide laser capture of cholinergic cells in basal forebrain. Messenger RNA expression levels in these cells were profiled using microarrays. Gene expression in eGFP(+) neurons was compared (1) to that in eGFP(-) neurons and to adjacent white matter, (2) between 7:00 am (lights on) and 7:00 pm (lights off), (3) between sleep-deprived and sleeping animals at 0, 3, 6, and 9 hours from lights on. There was a marked enrichment of ChAT and other markers of cholinergic neurons in eGFP(+) cells. Comparison of gene expression in these eGFP(+) neurons between 7:00 am and 7:00 pm revealed expected differences in the expression of clock genes (Arntl2, Per1, Per2, Dbp, Nr1d1) as well as mGluR3. Comparison of expression between spontaneous sleep and sleep-deprived groups sacrificed at the same time of day revealed a number of transcripts (n = 55) that had higher expression in sleep deprivation compared to sleep. Genes upregulated in sleep deprivation predominantly were from the protein folding pathway (25 transcripts, including chaperones). Among 42 transcripts upregulated in sleep was the cold-inducible RNA-binding protein. Cholinergic cell signatures were characterized. Whether the identified genes are changing as a consequence of differences in behavioral state or as part of the molecular regulatory mechanism remains to be determined. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Differentially expressed genes in iron-induced prion protein conversion

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Kim, Minsun; Kim, Eun-hee; Choi, Bo-Ran; Woo, Hee-Jong

2016-01-01

The conversion of the cellular prion protein (PrP C ) to the protease-resistant isoform is the key event in chronic neurodegenerative diseases, including transmissible spongiform encephalopathies (TSEs). Increased iron in prion-related disease has been observed due to the prion protein-ferritin complex. Additionally, the accumulation and conversion of recombinant PrP (rPrP) is specifically derived from Fe(III) but not Fe(II). Fe(III)-mediated PK-resistant PrP (PrP res ) conversion occurs within a complex cellular environment rather than via direct contact between rPrP and Fe(III). In this study, differentially expressed genes correlated with prion degeneration by Fe(III) were identified using Affymetrix microarrays. Following Fe(III) treatment, 97 genes were differentially expressed, including 85 upregulated genes and 12 downregulated genes (≥1.5-fold change in expression). However, Fe(II) treatment produced moderate alterations in gene expression without inducing dramatic alterations in gene expression profiles. Moreover, functional grouping of identified genes indicated that the differentially regulated genes were highly associated with cell growth, cell maintenance, and intra- and extracellular transport. These findings showed that Fe(III) may influence the expression of genes involved in PrP folding by redox mechanisms. The identification of genes with altered expression patterns in neural cells may provide insights into PrP conversion mechanisms during the development and progression of prion-related diseases. - Highlights: • Differential genes correlated with prion degeneration by Fe(III) were identified. • Genes were identified in cell proliferation and intra- and extracellular transport. • In PrP degeneration, redox related genes were suggested. • Cbr2, Rsad2, Slc40a1, Amph and Mvd were expressed significantly.

Small-molecule screen identifies modulators of EWS/FLI1 target gene expression and cell survival in Ewing's sarcoma.

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Boro, Aleksandar; Prêtre, Kathya; Rechfeld, Florian; Thalhammer, Verena; Oesch, Susanne; Wachtel, Marco; Schäfer, Beat W; Niggli, Felix K

2012-11-01

Ewing's sarcoma family of tumors (EFT) is characterized by the presence of chromosomal translocations leading to the expression of oncogenic transcription factors such as, in the majority of cases, EWS/FLI1. Because of its key role in Ewing's sarcoma development and maintenance, EWS/FLI1 represents an attractive therapeutic target. Here, we characterize PHLDA1 as a novel direct target gene whose expression is repressed by EWS/FLI1. Using this gene and additional specific well-characterized target genes such as NROB1, NKX2.2 and CAV1, all activated by EWS/FLI1, as a read-out system, we screened a small-molecule compound library enriched for FDA-approved drugs that modulated the expression of EWS/FLI1 target genes. Among a hit-list of nine well-known drugs such as camptothecin, fenretinide, etoposide and doxorubicin, we also identified the kinase inhibitor midostaurin (PKC412). Subsequent experiments demonstrated that midostaurin is able to induce apoptosis in a panel of six Ewing's sarcoma cell lines in vitro and can significantly suppress xenograft tumor growth in vivo. These results suggest that midostaurin might be a novel drug that is active against Ewing's cells, which might act by modulating the expression of EWS/FLI1 target genes. Copyright © 2012 UICC.

Gene expression analysis reveals new possible mechanisms of vancomycin-induced nephrotoxicity and identifies gene markers candidates.

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Dieterich, Christine; Puey, Angela; Lin, Sylvia; Lyn, Sylvia; Swezey, Robert; Furimsky, Anna; Fairchild, David; Mirsalis, Jon C; Ng, Hanna H

2009-01-01

Vancomycin, one of few effective treatments against methicillin-resistant Staphylococcus aureus, is nephrotoxic. The goals of this study were to (1) gain insights into molecular mechanisms of nephrotoxicity at the genomic level, (2) evaluate gene markers of vancomycin-induced kidney injury, and (3) compare gene expression responses after iv and ip administration. Groups of six female BALB/c mice were treated with seven daily iv or ip doses of vancomycin (50, 200, and 400 mg/kg) or saline, and sacrificed on day 8. Clinical chemistry and histopathology demonstrated kidney injury at 400 mg/kg only. Hierarchical clustering analysis revealed that kidney gene expression profiles of all mice treated at 400 mg/kg clustered with those of mice administered 200 mg/kg iv. Transcriptional profiling might thus be more sensitive than current clinical markers for detecting kidney damage, though the profiles can differ with the route of administration. Analysis of transcripts whose expression was changed by at least twofold compared with vehicle saline after high iv and ip doses of vancomycin suggested the possibility of oxidative stress and mitochondrial damage in vancomycin-induced toxicity. In addition, our data showed changes in expression of several transcripts from the complement and inflammatory pathways. Such expression changes were confirmed by relative real-time reverse transcription-polymerase chain reaction. Finally, our results further substantiate the use of gene markers of kidney toxicity such as KIM-1/Havcr1, as indicators of renal injury.

Increasing Power by Sharing Information from Genetic Background and Treatment in Clustering of Gene Expression Time Series

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Sura Zaki Alrashid

2018-02-01

Full Text Available Clustering of gene expression time series gives insight into which genes may be co-regulated, allowing us to discern the activity of pathways in a given microarray experiment. Of particular interest is how a given group of genes varies with different conditions or genetic background. This paper develops
a new clustering method that allows each cluster to be parameterised according to whether the behaviour of the genes across conditions is correlated or anti-correlated. By specifying correlation between such genes,more information is gain within the cluster about how the genes interrelate. Amyotrophic lateral sclerosis (ALS is an irreversible neurodegenerative disorder that kills the motor neurons and results in death within 2 to 3 years from the symptom onset. Speed of progression for different patients are heterogeneous with significant variability. The SOD1G93A transgenic mice from different backgrounds (129Sv and C57 showed consistent phenotypic differences for disease progression. A hierarchy of Gaussian isused processes to model condition-specific and gene-specific temporal co-variances. This study demonstrated about finding some significant gene expression profiles and clusters of associated or co-regulated gene expressions together from four groups of data (SOD1G93A and Ntg from 129Sv and C57 backgrounds. Our study shows the effectiveness of sharing information between replicates and different model conditions when modelling gene expression time series. Further gene enrichment score analysis and ontology pathway analysis of some specified clusters for a particular group may lead toward identifying features underlying the differential speed of disease progression.

Characterization of differentially expressed genes involved in pathways associated with gastric cancer.

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Hao Li

Full Text Available To explore the patterns of gene expression in gastric cancer, a total of 26 paired gastric cancer and noncancerous tissues from patients were enrolled for gene expression microarray analyses. Limma methods were applied to analyze the data, and genes were considered to be significantly differentially expressed if the False Discovery Rate (FDR value was 2. Subsequently, Gene Ontology (GO categories were used to analyze the main functions of the differentially expressed genes. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG database, we found pathways significantly associated with the differential genes. Gene-Act network and co-expression network were built respectively based on the relationships among the genes, proteins and compounds in the database. 2371 mRNAs and 350 lncRNAs considered as significantly differentially expressed genes were selected for the further analysis. The GO categories, pathway analyses and the Gene-Act network showed a consistent result that up-regulated genes were responsible for tumorigenesis, migration, angiogenesis and microenvironment formation, while down-regulated genes were involved in metabolism. These results of this study provide some novel findings on coding RNAs, lncRNAs, pathways and the co-expression network in gastric cancer which will be useful to guide further investigation and target therapy for this disease.

A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series

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Madeira Sara C

2009-06-01

the art methods that require exact matching of gene expression time series. Discussion The identification of co-regulated genes, involved in specific biological processes, remains one of the main avenues open to researchers studying gene regulatory networks. The ability of the proposed methodology to efficiently identify sets of genes with similar expression patterns is shown to be instrumental in the discovery of relevant biological phenomena, leading to more convincing evidence of specific regulatory mechanisms. Availability A prototype implementation of the algorithm coded in Java together with the dataset and examples used in the paper is available in http://kdbio.inesc-id.pt/software/e-ccc-biclustering.

LCGbase: A Comprehensive Database for Lineage-Based Co-regulated Genes.

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Wang, Dapeng; Zhang, Yubin; Fan, Zhonghua; Liu, Guiming; Yu, Jun

2012-01-01

ontology (GO) annotation, promoter identification, gene expression (co-expression), and evolutionary analysis. This database not only provides a way to define lineage-specific and species-specific gene clusters but also facilitates future studies on gene co-regulation, epigenetic control of gene expression (DNA methylation and histone marks), and chromosomal structures in a context of gene clusters and species evolution. LCGbase is freely available at http://lcgbase.big.ac.cn/LCGbase.

Acyl-CoA-binding protein/diazepam-binding inhibitor gene and pseudogenes

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Mandrup, S; Hummel, R; Ravn, S

1992-01-01

Acyl-CoA-binding protein (ACBP) is a 10 kDa protein isolated from bovine liver by virtue of its ability to bind and induce the synthesis of medium-chain acyl-CoA esters. Surprisingly, it turned out to be identical to a protein named diazepam-binding Inhibitor (DBI) claimed to be an endogenous mod...... have molecularly cloned and characterized the ACBP/DBI gene family in rat. The rat ACBP/DBI gene family comprises one expressed gene and four processed pseudogenes of which one was shown to exist in two allelic forms. The expressed gene is organized into four exons and three introns...

Carbon monoxide induced PPARγ SUMOylation and UCP2 block inflammatory gene expression in macrophages.

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Arvand Haschemi

Full Text Available Carbon monoxide (CO dampens pro-inflammatory responses in a peroxisome proliferator-activated receptor-γ (PPARγ and p38 mitogen-activated protein kinase (MAPK dependent manner. Previously, we demonstrated that CO inhibits lipopolysaccharide (LPS-induced expression of the proinflammatory early growth response-1 (Egr-1 transcription factor in macrophages via activation of PPARγ. Here, we further characterize the molecular mechanisms by which CO modulates the activity of PPARγ and Egr-1 repression. We demonstrate that CO enhances SUMOylation of PPARγ which we find was attributed to mitochondrial ROS generation. Ectopic expression of a SUMOylation-defective PPARγ-K365R mutant partially abolished CO-mediated suppression of LPS-induced Egr-1 promoter activity. Expression of a PPARγ-K77R mutant did not impair the effect of CO. In addition to PPARγ SUMOylation, CO-activated p38 MAPK was responsible for Egr-1 repression. Blocking both CO-induced PPARγ SUMOylation and p38 activation, completely reversed the effects of CO on inflammatory gene expression. In primary macrophages isolated form C57/BL6 male mice, we identify mitochondrial ROS formation by CO as the upstream trigger for the observed effects on Egr-1 in part through uncoupling protein 2 (UCP2. Macrophages derived from bone marrow isolated from Ucp2 gene Knock-Out C57/BL6 mice (Ucp2(-/-, produced significantly less ROS with CO exposure versus wild-type macrophages. Moreover, absence of UCP2 resulted in a complete loss of CO mediated Egr-1 repression. Collectively, these results indentify p38 activation, PPARγ-SUMOylation and ROS formation via UCP2 as a cooperative system by which CO impacts the inflammatory response.

Screening key genes for abdominal aortic aneurysm based on gene expression omnibus dataset.

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Wan, Li; Huang, Jingyong; Ni, Haizhen; Yu, Guanfeng

2018-02-13

Abdominal aortic aneurysm (AAA) is a common cardiovascular system disease with high mortality. The aim of this study was to identify potential genes for diagnosis and therapy in AAA. We searched and downloaded mRNA expression data from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) from AAA and normal individuals. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, transcriptional factors (TFs) network and protein-protein interaction (PPI) network were used to explore the function of genes. Additionally, immunohistochemical (IHC) staining was used to validate the expression of identified genes. Finally, the diagnostic value of identified genes was accessed by receiver operating characteristic (ROC) analysis in GEO database. A total of 1199 DEGs (188 up-regulated and 1011 down-regulated) were identified between AAA and normal individual. KEGG pathway analysis displayed that vascular smooth muscle contraction and pathways in cancer were significantly enriched signal pathway. The top 10 up-regulated and top 10 down-regulated DEGs were used to construct TFs and PPI networks. Some genes with high degrees such as NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16 and FOXO1 were identified to be related to AAA. The consequences of IHC staining showed that CCR7 and PDGFA were up-regulated in tissue samples of AAA. ROC analysis showed that NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA had the potential diagnostic value for AAA. The identified genes including NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA might be involved in the pathology of AAA.

Expression microarray meta-analysis identifies genes associated with Ras/MAPK and related pathways in progression of muscle-invasive bladder transition cell carcinoma.

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Jonathan A Ewald

Full Text Available The effective detection and management of muscle-invasive bladder Transition Cell Carcinoma (TCC continues to be an urgent clinical challenge. While some differences of gene expression and function in papillary (Ta, superficial (T1 and muscle-invasive (≥T2 bladder cancers have been investigated, the understanding of mechanisms involved in the progression of bladder tumors remains incomplete. Statistical methods of pathway-enrichment, cluster analysis and text-mining can extract and help interpret functional information about gene expression patterns in large sets of genomic data. The public availability of patient-derived expression microarray data allows open access and analysis of large amounts of clinical data. Using these resources, we investigated gene expression differences associated with tumor progression and muscle-invasive TCC. Gene expression was calculated relative to Ta tumors to assess progression-associated differences, revealing a network of genes related to Ras/MAPK and PI3K signaling pathways with increased expression. Further, we identified genes within this network that are similarly expressed in superficial Ta and T1 stages but altered in muscle-invasive T2 tumors, finding 7 genes (COL3A1, COL5A1, COL11A1, FN1, ErbB3, MAPK10 and CDC25C whose expression patterns in muscle-invasive tumors are consistent in 5 to 7 independent outside microarray studies. Further, we found increased expression of the fibrillar collagen proteins COL3A1 and COL5A1 in muscle-invasive tumor samples and metastatic T24 cells. Our results suggest that increased expression of genes involved in mitogenic signaling may support the progression of muscle-invasive bladder tumors that generally lack activating mutations in these pathways, while expression changes of fibrillar collagens, fibronectin and specific signaling proteins are associated with muscle-invasive disease. These results identify potential biomarkers and targets for TCC treatments, and

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

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Tholouli, Eleni [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); MacDermott, Sarah [The Medical School, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Hoyland, Judith [School of Biomedicine, Faculty of Medical and Human Sciences, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Yin, John Liu [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); Byers, Richard, E-mail: richard.byers@cmft.nhs.uk [School of Cancer and Enabling Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, M13 9PT Manchester (United Kingdom)

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

Large scale gene expression meta-analysis reveals tissue-specific, sex-biased gene expression in humans

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Benjamin Mayne

2016-10-01

Full Text Available The severity and prevalence of many diseases are known to differ between the sexes. Organ specific sex-biased gene expression may underpin these and other sexually dimorphic traits. To further our understanding of sex differences in transcriptional regulation, we performed meta-analyses of sex biased gene expression in multiple human tissues. We analysed 22 publicly available human gene expression microarray data sets including over 2500 samples from 15 different tissues and 9 different organs. Briefly, by using an inverse-variance method we determined the effect size difference of gene expression between males and females. We found the greatest sex differences in gene expression in the brain, specifically in the anterior cingulate cortex, (1818 genes, followed by the heart (375 genes, kidney (224 genes, colon (218 genes and thyroid (163 genes. More interestingly, we found different parts of the brain with varying numbers and identity of sex-biased genes, indicating that specific cortical regions may influence sexually dimorphic traits. The majority of sex-biased genes in other tissues such as the bladder, liver, lungs and pancreas were on the sex chromosomes or involved in sex hormone production. On average in each tissue, 32% of autosomal genes that were expressed in a sex-biased fashion contained androgen or estrogen hormone response elements. Interestingly, across all tissues, we found approximately two-thirds of autosomal genes that were sex-biased were not under direct influence of sex hormones. To our knowledge this is the largest analysis of sex-biased gene expression in human tissues to date. We identified many sex-biased genes that were not under the direct influence of sex chromosome genes or sex hormones. These may provide targets for future development of sex-specific treatments for diseases.

Expressed sequences tags of the anther smut fungus, Microbotryum violaceum, identify mating and pathogenicity genes

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Devier Benjamin

2007-08-01

Full Text Available Abstract Background The basidiomycete fungus Microbotryum violaceum is responsible for the anther-smut disease in many plants of the Caryophyllaceae family and is a model in genetics and evolutionary biology. Infection is initiated by dikaryotic hyphae produced after the conjugation of two haploid sporidia of opposite mating type. This study describes M. violaceum ESTs corresponding to nuclear genes expressed during conjugation and early hyphal production. Results A normalized cDNA library generated 24,128 sequences, which were assembled into 7,765 unique genes; 25.2% of them displayed significant similarity to annotated proteins from other organisms, 74.3% a weak similarity to the same set of known proteins, and 0.5% were orphans. We identified putative pheromone receptors and genes that in other fungi are involved in the mating process. We also identified many sequences similar to genes known to be involved in pathogenicity in other fungi. The M. violaceum EST database, MICROBASE, is available on the Web and provides access to the sequences, assembled contigs, annotations and programs to compare similarities against MICROBASE. Conclusion This study provides a basis for cloning the mating type locus, for further investigation of pathogenicity genes in the anther smut fungi, and for comparative genomics.

Analysis of genomic aberrations and gene expression profiling identifies novel lesions and pathways in myeloproliferative neoplasms

International Nuclear Information System (INIS)

Rice, K L; Lin, X; Wolniak, K; Ebert, B L; Berkofsky-Fessler, W; Buzzai, M; Sun, Y; Xi, C; Elkin, P; Levine, R; Golub, T; Gilliland, D G; Crispino, J D; Licht, J D; Zhang, W

2011-01-01

Polycythemia vera (PV), essential thrombocythemia and primary myelofibrosis, are myeloproliferative neoplasms (MPNs) with distinct clinical features and are associated with the JAK2V617F mutation. To identify genomic anomalies involved in the pathogenesis of these disorders, we profiled 87 MPN patients using Affymetrix 250K single-nucleotide polymorphism (SNP) arrays. Aberrations affecting chr9 were the most frequently observed and included 9pLOH (n=16), trisomy 9 (n=6) and amplifications of 9p13.3–23.3 (n=1), 9q33.1–34.13 (n=1) and 9q34.13 (n=6). Patients with trisomy 9 were associated with elevated JAK2V617F mutant allele burden, suggesting that gain of chr9 represents an alternative mechanism for increasing JAK2V617F dosage. Gene expression profiling of patients with and without chr9 abnormalities (+9, 9pLOH), identified genes potentially involved in disease pathogenesis including JAK2, STAT5B and MAPK14. We also observed recurrent gains of 1p36.31–36.33 (n=6), 17q21.2–q21.31 (n=5) and 17q25.1–25.3 (n=5) and deletions affecting 18p11.31–11.32 (n=8). Combined SNP and gene expression analysis identified aberrations affecting components of a non-canonical PRC2 complex (EZH1, SUZ12 and JARID2) and genes comprising a ‘HSC signature' (MLLT3, SMARCA2 and PBX1). We show that NFIB, which is amplified in 7/87 MPN patients and upregulated in PV CD34+ cells, protects cells from apoptosis induced by cytokine withdrawal

Characterization, expression and complex formation of the murine Fanconi anaemia gene product Fancg.

Science.gov (United States)

van de Vrugt, Henri J; Koomen, Mireille; Berns, Mariska A D; de Vries, Yne; Rooimans, Martin A; van der Weel, Laura; Blom, Eric; de Groot, Jan; Schepers, Rik J; Stone, Stacie; Hoatlin, Maureen E; Cheng, Ngan Ching; Joenje, Hans; Arwert, Fré

2002-03-01

Fanconi anaemia (FA) is an autosomal recessive chromosomal instability disorder. Six distinct FA disease genes have been identified, the products of which function in an integrated pathway that is thought to support a nuclear caretaker function. Comparison of FA gene characteristics in different species may help to unravel the molecular function of the FA pathway. We have cloned the murine homologue of the Fanconi anaemia complementation group G gene, FANCG/XRCC9. The murine Fancg protein shows an 83% similarity to the human protein sequence, and has a predicted molecular weight of 68.5 kDa. Expression of mouse Fancg in human FA-G lymphoblasts fully corrects their cross-linker hypersensitivity. At mRNA and protein levels we detected the co-expression of Fancg and Fanca in murine tissues. In addition, mouse Fancg and Fanca proteins co-purify by immunoprecipitation. Upon transfection into Fanca-deficient mouse embryonic fibroblasts EGFP-Fancg chimeric protein was detectable in the nucleus. We identified a murine cDNA, Fancg, which cross-complements the cellular defect of human FA-G cells and thus represents a true homologue of human FANCG. Spleen, thymus and testis showed the highest Fancg expression levels. Although Fancg and Fanca are able to form a complex, this interaction is not required for Fancg to accumulate in the nuclear compartment.

Age-dependent changes in mean and variance of gene expression across tissues in a twin cohort.

Science.gov (United States)

Viñuela, Ana; Brown, Andrew A; Buil, Alfonso; Tsai, Pei-Chien; Davies, Matthew N; Bell, Jordana T; Dermitzakis, Emmanouil T; Spector, Timothy D; Small, Kerrin S

2018-02-15

Changes in the mean and variance of gene expression with age have consequences for healthy aging and disease development. Age-dependent changes in phenotypic variance have been associated with a decline in regulatory functions leading to increase in disease risk. Here, we investigate age-related mean and variance changes in gene expression measured by RNA-seq of fat, skin, whole blood and derived lymphoblastoid cell lines (LCLs) expression from 855 adult female twins. We see evidence of up to 60% of age effects on transcription levels shared across tissues, and 47% of those on splicing. Using gene expression variance and discordance between genetically identical MZ twin pairs, we identify 137 genes with age-related changes in variance and 42 genes with age-related discordance between co-twins; implying the latter are driven by environmental effects. We identify four eQTLs whose effect on expression is age-dependent (FDR 5%). Combined, these results show a complicated mix of environmental and genetically driven changes in expression with age. Using the twin structure in our data, we show that additive genetic effects explain considerably more of the variance in gene expression than aging, but less that other environmental factors, potentially explaining why reliable expression-derived biomarkers for healthy-aging have proved elusive compared with those derived from methylation. © The Author(s) 2017. Published by Oxford University Press.