A Hox Gene, Antennapedia, Regulates Expression of Multiple Major Silk Protein Genes in the Silkworm Bombyx mori.

PubMed

Tsubota, Takuya; Tomita, Shuichiro; Uchino, Keiro; Kimoto, Mai; Takiya, Shigeharu; Kajiwara, Hideyuki; Yamazaki, Toshimasa; Sezutsu, Hideki

2016-03-25

Hoxgenes play a pivotal role in the determination of anteroposterior axis specificity during bilaterian animal development. They do so by acting as a master control and regulating the expression of genes important for development. Recently, however, we showed that Hoxgenes can also function in terminally differentiated tissue of the lepidopteranBombyx mori In this species,Antennapedia(Antp) regulates expression of sericin-1, a major silk protein gene, in the silk gland. Here, we investigated whether Antpcan regulate expression of multiple genes in this tissue. By means of proteomic, RT-PCR, and in situ hybridization analyses, we demonstrate that misexpression of Antpin the posterior silk gland induced ectopic expression of major silk protein genes such assericin-3,fhxh4, and fhxh5 These genes are normally expressed specifically in the middle silk gland as is Antp Therefore, the evidence strongly suggests that Antpactivates these silk protein genes in the middle silk gland. The putativesericin-1 activator complex (middle silk gland-intermolt-specific complex) can bind to the upstream regions of these genes, suggesting that Antpdirectly activates their expression. We also found that the pattern of gene expression was well conserved between B. moriand the wild species Bombyx mandarina, indicating that the gene regulation mechanism identified here is an evolutionarily conserved mechanism and not an artifact of the domestication of B. mori We suggest that Hoxgenes have a role as a master control in terminally differentiated tissues, possibly acting as a primary regulator for a range of physiological processes. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Expression Atlas: gene and protein expression across multiple studies and organisms

PubMed Central

Tang, Y Amy; Bazant, Wojciech; Burke, Melissa; Fuentes, Alfonso Muñoz-Pomer; George, Nancy; Koskinen, Satu; Mohammed, Suhaib; Geniza, Matthew; Preece, Justin; Jarnuczak, Andrew F; Huber, Wolfgang; Stegle, Oliver; Brazma, Alvis; Petryszak, Robert

2018-01-01

Abstract Expression Atlas (http://www.ebi.ac.uk/gxa) is an added value database that provides information about gene and protein expression in different species and contexts, such as tissue, developmental stage, disease or cell type. The available public and controlled access data sets from different sources are curated and re-analysed using standardized, open source pipelines and made available for queries, download and visualization. As of August 2017, Expression Atlas holds data from 3,126 studies across 33 different species, including 731 from plants. Data from large-scale RNA sequencing studies including Blueprint, PCAWG, ENCODE, GTEx and HipSci can be visualized next to each other. In Expression Atlas, users can query genes or gene-sets of interest and explore their expression across or within species, tissues, developmental stages in a constitutive or differential context, representing the effects of diseases, conditions or experimental interventions. All processed data matrices are available for direct download in tab-delimited format or as R-data. In addition to the web interface, data sets can now be searched and downloaded through the Expression Atlas R package. Novel features and visualizations include the on-the-fly analysis of gene set overlaps and the option to view gene co-expression in experiments investigating constitutive gene expression across tissues or other conditions. PMID:29165655

Expression of Multiple Stress Response Genes by Escherichia Coli Under Modeled Reduced Gravity

NASA Astrophysics Data System (ADS)

Vukanti, Raja; Leff, Laura G.

2012-09-01

Bacteria, in response to changes in their environment, quickly regulate gene expression; hence, transcriptional profiling has been widely used to characterize bacterial responses to various environmental conditions. In this study, we used clinorotation to grow bacteria under low-sedimentation, -shear, and -turbulence conditions (referred to as modeled reduced gravity, MRG, below) which profoundly impacts bacteria including causing elevated resistance to multiple environmental stresses. To explore potential mechanisms behind the multiple stress resistance response to MRG, we assessed expression levels of E. coli genes, using reverse transcription followed by real-time-PCR, involved in specific stress and general stress responses under MRG and normal gravity (NG) in nutritionally rich and minimal media, and during exponential and stationary phases of growth. In addition, growth rates as well as physico-chemical parameters of culture media were examined. Over-expression of stress response genes (csiD, cstA, katE, otsA, treA) occurred under MRG compared to NG controls, but only during the later stages of growth in rich medium demonstrating that bacterial response to MRG varies with growth-medium and -phase. At stationary phase in rich medium under MRG and NG, E. coli had similar growth rates (based on rRNA-leader abundance) and yields (cell mass and numbers); this coupled, with observations of simultaneous induction of starvation response genes (csiD and cstA) suggests the multiple stress resistance phenotype under MRG could be attributable to microzones of nutrient unavailability around cells. Overall, in rich medium, the response resembled the general stress response (GSR) that E. coli develops during stationary phase of growth. Along these same lines, induction of genes coding for GSR was reversed by improving nutritional conditions under MRG. The reversal of GSR under MRG suggests that the multiple stress response exhibited is not specific to MRG but may result

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

PubMed

Meissner, Tobias; Seckinger, Anja; Rème, Thierry; Hielscher, Thomas; Möhler, Thomas; Neben, Kai; Goldschmidt, Hartmut; Klein, Bernard; Hose, Dirk

2011-12-01

Multiple myeloma is an incurable malignant plasma cell disease characterized by survival ranging from several months to more than 15 years. Assessment of risk and underlying molecular heterogeneity can be excellently done by gene expression profiling (GEP), but its way into clinical routine is hampered by the lack of an appropriate reporting tool and the integration with other prognostic factors into a single "meta" risk stratification. The GEP-report (GEP-R) was built as an open-source software developed in R for gene expression reporting in clinical practice using Affymetrix microarrays. GEP-R processes new samples by applying a documentation-by-value strategy to the raw data to be able to assign thresholds and grouping algorithms defined on a reference cohort of 262 patients with multiple myeloma. Furthermore, we integrated expression-based and conventional prognostic factors within one risk stratification (HM-metascore). The GEP-R comprises (i) quality control, (ii) sample identity control, (iii) biologic classification, (iv) risk stratification, and (v) assessment of target genes. The resulting HM-metascore is defined as the sum over the weighted factors gene expression-based risk-assessment (UAMS-, IFM-score), proliferation, International Staging System (ISS) stage, t(4;14), and expression of prognostic target genes (AURKA, IGF1R) for which clinical grade inhibitors exist. The HM-score delineates three significantly different groups of 13.1%, 72.1%, and 14.7% of patients with a 6-year survival rate of 89.3%, 60.6%, and 18.6%, respectively. GEP reporting allows prospective assessment of risk and target gene expression and integration of current prognostic factors in clinical routine, being customizable about novel parameters or other cancer entities. ©2011 AACR.

A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns

PubMed Central

Mollah, Mohammad Manir Hossain; Jamal, Rahman; Mokhtar, Norfilza Mohd; Harun, Roslan; Mollah, Md. Nurul Haque

2015-01-01

Background Identifying genes that are differentially expressed (DE) between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA), are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression. Results The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0) to outlying expressions and larger weights (≤ 1) to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA. Conclusion Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed) perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small

Assembly and multiple gene expression of thermophilic enzymes in Escherichia coli for in vitro metabolic engineering.

PubMed

Ninh, Pham Huynh; Honda, Kohsuke; Sakai, Takaaki; Okano, Kenji; Ohtake, Hisao

2015-01-01

In vitro reconstitution of an artificial metabolic pathway is an emerging approach for the biocatalytic production of industrial chemicals. However, several enzymes have to be separately prepared (and purified) for the construction of an in vitro metabolic pathway, thereby limiting the practical applicability of this approach. In this study, genes encoding the nine thermophilic enzymes involved in a non-ATP-forming chimeric glycolytic pathway were assembled in an artificial operon and co-expressed in a single recombinant Escherichia coli strain. Gene expression levels of the thermophilic enzymes were controlled by their sequential order in the artificial operon. The specific activities of the recombinant enzymes in the cell-free extract of the multiple-gene-expression E. coli were 5.0-1,370 times higher than those in an enzyme cocktail prepared from a mixture of single-gene-expression strains, in each of which a single one of the nine thermophilic enzymes was overproduced. Heat treatment of a crude extract of the multiple-gene-expression cells led to the denaturation of indigenous proteins and one-step preparation of an in vitro synthetic pathway comprising only a limited number of thermotolerant enzymes. Coupling this in vitro pathway with other thermophilic enzymes including the H2 O-forming NADH oxidase or the malate/lactate dehydrogenase facilitated one-pot conversion of glucose to pyruvate or lactate, respectively. © 2014 Wiley Periodicals, Inc.

Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets.

PubMed

Salem, Saeed; Ozcaglar, Cagri

2014-01-01

Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways.

EBF factors drive expression of multiple classes of target genes governing neuronal development.

PubMed

Green, Yangsook S; Vetter, Monica L

2011-04-30

Early B cell factor (EBF) family members are transcription factors known to have important roles in several aspects of vertebrate neurogenesis, including commitment, migration and differentiation. Knowledge of how EBF family members contribute to neurogenesis is limited by a lack of detailed understanding of genes that are transcriptionally regulated by these factors. We performed a microarray screen in Xenopus animal caps to search for targets of EBF transcriptional activity, and identified candidate targets with multiple roles, including transcription factors of several classes. We determined that, among the most upregulated candidate genes with expected neuronal functions, most require EBF activity for some or all of their expression, and most have overlapping expression with ebf genes. We also found that the candidate target genes that had the most strongly overlapping expression patterns with ebf genes were predicted to be direct transcriptional targets of EBF transcriptional activity. The identification of candidate targets that are transcription factor genes, including nscl-1, emx1 and aml1, improves our understanding of how EBF proteins participate in the hierarchy of transcription control during neuronal development, and suggests novel mechanisms by which EBF activity promotes migration and differentiation. Other candidate targets, including pcdh8 and kcnk5, expand our knowledge of the types of terminal differentiated neuronal functions that EBF proteins regulate.

Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets

PubMed Central

2014-01-01

Background Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. Results We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways. PMID:25221624

GENE EXPRESSION NETWORKS

EPA Science Inventory

"Gene expression network" is the term used to describe the interplay, simple or complex, between two or more gene products in performing a specific cellular function. Although the delineation of such networks is complicated by the existence of multiple and subtle types of intera...

Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2014-01-01

Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. This study illustrates that we can

GeneNetFinder2: Improved Inference of Dynamic Gene Regulatory Relations with Multiple Regulators.

PubMed

Han, Kyungsook; Lee, Jeonghoon

2016-01-01

A gene involved in complex regulatory interactions may have multiple regulators since gene expression in such interactions is often controlled by more than one gene. Another thing that makes gene regulatory interactions complicated is that regulatory interactions are not static, but change over time during the cell cycle. Most research so far has focused on identifying gene regulatory relations between individual genes in a particular stage of the cell cycle. In this study we developed a method for identifying dynamic gene regulations of several types from the time-series gene expression data. The method can find gene regulations with multiple regulators that work in combination or individually as well as those with single regulators. The method has been implemented as the second version of GeneNetFinder (hereafter called GeneNetFinder2) and tested on several gene expression datasets. Experimental results with gene expression data revealed the existence of genes that are not regulated by individual genes but rather by a combination of several genes. Such gene regulatory relations cannot be found by conventional methods. Our method finds such regulatory relations as well as those with multiple, independent regulators or single regulators, and represents gene regulatory relations as a dynamic network in which different gene regulatory relations are shown in different stages of the cell cycle. GeneNetFinder2 is available at http://bclab.inha.ac.kr/GeneNetFinder and will be useful for modeling dynamic gene regulations with multiple regulators.

Systems Biophysics of Gene Expression

PubMed Central

Vilar, Jose M.G.; Saiz, Leonor

2013-01-01

Gene expression is a process central to any form of life. It involves multiple temporal and functional scales that extend from specific protein-DNA interactions to the coordinated regulation of multiple genes in response to intracellular and extracellular changes. This diversity in scales poses fundamental challenges to the use of traditional approaches to fully understand even the simplest gene expression systems. Recent advances in computational systems biophysics have provided promising avenues to reliably integrate the molecular detail of biophysical process into the system behavior. Here, we review recent advances in the description of gene regulation as a system of biophysical processes that extend from specific protein-DNA interactions to the combinatorial assembly of nucleoprotein complexes. There is now basic mechanistic understanding on how promoters controlled by multiple, local and distal, DNA binding sites for transcription factors can actively control transcriptional noise, cell-to-cell variability, and other properties of gene regulation, including precision and flexibility of the transcriptional responses. PMID:23790365

Multiple microRNAs regulate human FOXP2 gene expression by targeting sequences in its 3' untranslated region.

PubMed

Fu, Lijuan; Shi, Zhimin; Luo, Guanzheng; Tu, Weihong; Wang, XiuJie; Fang, Zhide; Li, XiaoChing

2014-10-01

Mutations in the human FOXP2 gene cause speech and language impairments. The FOXP2 protein is a transcription factor that regulates the expression of many downstream genes, which may have important roles in nervous system development and function. An adequate amount of functional FOXP2 protein is thought to be critical for the proper development of the neural circuitry underlying speech and language. However, how FOXP2 gene expression is regulated is not clearly understood. The FOXP2 mRNA has an approximately 4-kb-long 3' untranslated region (3' UTR), twice as long as its protein coding region, indicating that FOXP2 can be regulated by microRNAs (miRNAs). We identified multiple miRNAs that regulate the expression of the human FOXP2 gene using sequence analysis and in vitro cell systems. Focusing on let-7a, miR-9, and miR-129-5p, three brain-enriched miRNAs, we show that these miRNAs regulate human FOXP2 expression in a dosage-dependent manner and target specific sequences in the FOXP2 3' UTR. We further show that these three miRNAs are expressed in the cerebellum of the human fetal brain, where FOXP2 is known to be expressed. Our results reveal novel regulatory functions of the human FOXP2 3' UTR sequence and regulatory interactions between multiple miRNAs and the human FOXP2 gene. The expression of let-7a, miR-9, and miR-129-5p in the human fetal cerebellum is consistent with their roles in regulating FOXP2 expression during early cerebellum development. These results suggest that various genetic and environmental factors may contribute to speech and language development and related neural developmental disorders via the miRNA-FOXP2 regulatory network.

The presence of p53 influences the expression of multiple human cytomegalovirus genes at early times postinfection.

PubMed

Hannemann, Holger; Rosenke, Kyle; O'Dowd, John M; Fortunato, Elizabeth A

2009-05-01

Human cytomegalovirus (HCMV) is a common cause of morbidity and mortality in immunocompromised and immunosuppressed individuals. During infection, HCMV is known to employ host transcription factors to facilitate viral gene expression. To further understand the previously observed delay in viral replication and protein expression in p53 knockout cells, we conducted microarray analyses of p53(+/+) and p53(-/-) immortalized fibroblast cell lines. At a multiplicity of infection (MOI) of 1 at 24 h postinfection (p.i.), the expression of 22 viral genes was affected by the absence of p53. Eleven of these 22 genes (group 1) were examined by real-time reverse transcriptase, or quantitative, PCR (q-PCR). Additionally, five genes previously determined to have p53 bound to their nearest p53-responsive elements (group 2) and three control genes without p53 binding sites in their upstream sequences (group 3) were also examined. At an MOI of 1, >3-fold regulation was found for five group 1 genes. The expression of group 2 and 3 genes was not changed. At an MOI of 5, all genes from group 1 and four of five genes from group 2 were found to be regulated. The expression of control genes from group 3 remained unchanged. A q-PCR time course of four genes revealed that p53 influences viral gene expression most at immediate-early and early times p.i., suggesting a mechanism for the reduced and delayed production of virions in p53(-/-) cells.

Proglucagons in vertebrates: Expression and processing of multiple genes in a bony fish.

PubMed

Busby, Ellen R; Mommsen, Thomas P

2016-09-01

In contrast to mammals, where a single proglucagon (PG) gene encodes three peptides: glucagon, glucagon-like peptide 1 and glucagon-like peptide 2 (GLP-1; GLP-2), many non-mammalian vertebrates carry multiple PG genes. Here, we investigate proglucagon mRNA sequences, their tissue expression and processing in a diploid bony fish. Copper rockfish (Sebastes caurinus) express two independent genes coding for distinct proglucagon sequences (PG I, PG II), with PG II lacking the GLP-2 sequence. These genes are differentially transcribed in the endocrine pancreas, the brain, and the gastrointestinal tract. Alternative splicing identified in rockfish is only one part of this complex regulation of the PG transcripts: the system has the potential to produce two glucagons, four GLP-1s and a single GLP-2, or any combination of these peptides. Mass spectrometric analysis of partially purified PG-derived peptides in endocrine pancreas confirms translation of both PG transcripts and differential processing of the resulting peptides. The complex differential regulation of the two PG genes and their continued presence in this extant teleostean fish strongly suggests unique and, as yet largely unidentified, roles for the peptide products encoded in each gene. Copyright © 2016 Elsevier Inc. All rights reserved.

Multiple Genes Repress Motility in Uropathogenic Escherichia coli Constitutively Expressing Type 1 Fimbriae▿ †

PubMed Central

Simms, Amy N.; Mobley, Harry L. T.

2008-01-01

Two surface organelles of uropathogenic Escherichia coli (UPEC), flagella and type 1 fimbriae, are critical for colonization of the urinary tract but mediate opposite actions. Flagella propel bacteria through urine and along mucus layers, while type 1 fimbriae allow bacteria to adhere to specific receptors present on uroepithelial cells. Constitutive expression of type 1 fimbriae leads to repression of motility and chemotaxis in UPEC strain CFT073, suggesting that UPEC may coordinately regulate motility and adherence. To identify genes involved in this regulation of motility by type 1 fimbriae, transposon mutagenesis was performed on a phase-locked type 1 fimbrial ON variant of strain CFT073 (CFT073 fim L-ON), followed by a screen for restoration of motility in soft agar. Functions of the genes identified included attachment, metabolism, transport, DNA mismatch repair, and transcriptional regulation, and a number of genes had hypothetical function. Isogenic deletion mutants of these genes were also constructed in CFT073 fim L-ON. Motility was partially restored in six of these mutants, including complementable mutations in four genes encoding known transcriptional regulators, lrhA, lrp, slyA, and papX; a mismatch repair gene, mutS; and one hypothetical gene, ydiV. Type 1 fimbrial expression in these mutants was unaltered, and the majority of these mutants expressed larger amounts of flagellin than the fim L-ON parental strain. Our results indicate that repression of motility in CFT073 fim L-ON is not solely due to the constitutive expression of type 1 fimbriae on the surfaces of the bacteria and that multiple genes may contribute to this repression. PMID:18359812

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Tabatabaei, Seyyed Mohammad; Namaki, Saeed

2016-01-01

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets. PMID:28028462

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

PubMed Central

Gong, Bin-Sheng; Zhang, Qing-Pu; Zhang, Guang-Mei; Zhang, Shao-Jun; Zhang, Wei; Lv, Hong-Chao; Zhang, Fan; Lv, Sa-Li; Li, Chuan-Xing; Rao, Shao-Qi; Li, Xia

2007-01-01

Gene expression profiles and single-nucleotide polymorphism (SNP) profiles are modern data for genetic analysis. It is possible to use the two types of information to analyze the relationships among genes by some genetical genomics approaches. In this study, gene expression profiles were used as expression traits. And relationships among the genes, which were co-linked to a common SNP(s), were identified by integrating the two types of information. Further research on the co-expressions among the co-linked genes was carried out after the gene-SNP relationships were established using the Haseman-Elston sib-pair regression. The results showed that the co-expressions among the co-linked genes were significantly higher if the number of connections between the genes and a SNP(s) was more than six. Then, the genes were interconnected via one or more SNP co-linkers to construct a gene-SNP intermixed network. The genes sharing more SNPs tended to have a stronger correlation. Finally, a gene-gene network was constructed with their intensities of relationships (the number of SNP co-linkers shared) as the weights for the edges. PMID:18466544

Global map of physical interactions among differentially expressed genes in multiple sclerosis relapses and remissions.

PubMed

Tuller, Tamir; Atar, Shimshi; Ruppin, Eytan; Gurevich, Michael; Achiron, Anat

2011-09-15

Multiple sclerosis (MS) is a central nervous system autoimmune inflammatory T-cell-mediated disease with a relapsing-remitting course in the majority of patients. In this study, we performed a high-resolution systems biology analysis of gene expression and physical interactions in MS relapse and remission. To this end, we integrated 164 large-scale measurements of gene expression in peripheral blood mononuclear cells of MS patients in relapse or remission and healthy subjects, with large-scale information about the physical interactions between these genes obtained from public databases. These data were analyzed with a variety of computational methods. We find that there is a clear and significant global network-level signal that is related to the changes in gene expression of MS patients in comparison to healthy subjects. However, despite the clear differences in the clinical symptoms of MS patients in relapse versus remission, the network level signal is weaker when comparing patients in these two stages of the disease. This result suggests that most of the genes have relatively similar expression levels in the two stages of the disease. In accordance with previous studies, we found that the pathways related to regulation of cell death, chemotaxis and inflammatory response are differentially expressed in the disease in comparison to healthy subjects, while pathways related to cell adhesion, cell migration and cell-cell signaling are activated in relapse in comparison to remission. However, the current study includes a detailed report of the exact set of genes involved in these pathways and the interactions between them. For example, we found that the genes TP53 and IL1 are 'network-hub' that interacts with many of the differentially expressed genes in MS patients versus healthy subjects, and the epidermal growth factor receptor is a 'network-hub' in the case of MS patients with relapse versus remission. The statistical approaches employed in this study enabled us

Genome multiplication as adaptation to tissue survival: evidence from gene expression in mammalian heart and liver.

PubMed

Anatskaya, Olga V; Vinogradov, Alexander E

2007-01-01

To elucidate the functional significance of genome multiplication in somatic tissues, we performed a large-scale analysis of ploidy-associated changes in expression of non-tissue-specific (i.e., broadly expressed) genes in the heart and liver of human and mouse (6585 homologous genes were analyzed). These species have inverse patterns of polyploidization in cardiomyocytes and hepatocytes. The between-species comparison of two pairs of homologous tissues with crisscross contrast in ploidy levels allows the removal of the effects of species and tissue specificity on the profile of gene activity. The different tests performed from the standpoint of modular biology revealed a consistent picture of ploidy-associated alteration in a wide range of functional gene groups. The major effects consisted of hypoxia-inducible factor-triggered changes in main cellular processes and signaling pathways, activation of defense against DNA lesions, acceleration of protein turnover and transcription, and the impairment of apoptosis, the immune response, and cytoskeleton maintenance. We also found a severe decline in aerobic respiration and stimulation of sugar and fatty acid metabolism. These metabolic rearrangements create a special type of metabolism that can be considered intermediate between aerobic and anaerobic. The metabolic and physiological changes revealed (reflected in the alteration of gene expression) help explain the unique ability of polyploid tissues to combine proliferation and differentiation, which are separated in diploid tissues. We argue that genome multiplication promotes cell survival and tissue regeneration under stressful conditions.

Digital detection of multiple minority mutants and expression levels of multiple colorectal cancer-related genes using digital-PCR coupled with bead-array.

PubMed

Huang, Huan; Li, Shuo; Sun, Lizhou; Zhou, Guohua

2015-01-01

To simultaneously analyze mutations and expression levels of multiple genes on one detection platform, we proposed a method termed "multiplex ligation-dependent probe amplification-digital amplification coupled with hydrogel bead-array" (MLPA-DABA) and applied it to diagnose colorectal cancer (CRC). CRC cells and tissues were sampled to extract nucleic acid, perform MLPA with sequence-tagged probes, perform digital emulsion polymerase chain reaction (PCR), and produce a hydrogel bead-array to immobilize beads and form a single bead layer on the array. After hybridization with fluorescent probes, the number of colored beads, which reflects the abundance of expressed genes and the mutation rate, was counted for diagnosis. Only red or green beads occurred on the chips in the mixed samples, indicating the success of single-molecule PCR. When a one-source sample was analyzed using mixed MLPA probes, beads of only one color occurred, suggesting the high specificity of the method in analyzing CRC mutation and gene expression. In gene expression analysis of a CRC tissue from one CRC patient, the mutant percentage was 3.1%, and the expression levels of CRC-related genes were much higher than those of normal tissue. The highly sensitive MLPA-DABA succeeds in the relative quantification of mutations and gene expressions of exfoliated cells in stool samples of CRC patients on the same chip platform. MLPA-DABA coupled with hydrogel bead-array is a promising method in the non-invasive diagnosis of CRC.

Digital Detection of Multiple Minority Mutants and Expression Levels of Multiple Colorectal Cancer-Related Genes Using Digital-PCR Coupled with Bead-Array

PubMed Central

Huang, Huan; Li, Shuo; Sun, Lizhou; Zhou, Guohua

2015-01-01

To simultaneously analyze mutations and expression levels of multiple genes on one detection platform, we proposed a method termed “multiplex ligation-dependent probe amplification–digital amplification coupled with hydrogel bead-array” (MLPA–DABA) and applied it to diagnose colorectal cancer (CRC). CRC cells and tissues were sampled to extract nucleic acid, perform MLPA with sequence-tagged probes, perform digital emulsion polymerase chain reaction (PCR), and produce a hydrogel bead-array to immobilize beads and form a single bead layer on the array. After hybridization with fluorescent probes, the number of colored beads, which reflects the abundance of expressed genes and the mutation rate, was counted for diagnosis. Only red or green beads occurred on the chips in the mixed samples, indicating the success of single-molecule PCR. When a one-source sample was analyzed using mixed MLPA probes, beads of only one color occurred, suggesting the high specificity of the method in analyzing CRC mutation and gene expression. In gene expression analysis of a CRC tissue from one CRC patient, the mutant percentage was 3.1%, and the expression levels of CRC-related genes were much higher than those of normal tissue. The highly sensitive MLPA–DABA succeeds in the relative quantification of mutations and gene expressions of exfoliated cells in stool samples of CRC patients on the same chip platform. MLPA–DABA coupled with hydrogel bead-array is a promising method in the non-invasive diagnosis of CRC. PMID:25880764

Rofecoxib modulates multiple gene expression pathways in a clinical model of acute inflammatory pain

PubMed Central

Wang, Xiao-Min; Wu, Tian-Xia; Hamza, May; Ramsay, Edward S.; Wahl, Sharon M.; Dionne, Raymond A.

2007-01-01

New insights into the biological properties of cyclooxygenase-2 (COX-2) and its response pathway challenge the hypothesis that COX-2 is simply pro-inflammatory and inhibition of COX-2 solely prevents the development of inflammation and ameliorates inflammatory pain. The present study performed a comprehensive analysis of gene/protein expression induced by a selective inhibitor of COX-2, rofecoxib, compared with a non-selective COX inhibitor, ibuprofen, and placebo in a clinical model of acute inflammatory pain (the surgical extraction of impacted third molars) using microarray analysis followed by quantitative RT-PCR verification and Western blotting. Inhibition of COX-2 modulated gene expression related to inflammation and pain, the arachidonic acid pathway, apoptosis/angiogenesis, cell adhesion and signal transduction. Compared to placebo, rofecoxib treatment increased the gene expression of ANXA3 (annexin 3), SOD2 (superoxide dismutase 2), SOCS3 (suppressor of cytokine signaling 3) and IL1RN (IL1 receptor antagonist) which are associated with inhibition of phospholipase A2 and suppression of cytokine signaling cascades, respectively. Both rofecoxib and ibuprofen treatment increased the gene expression of the pro-inflammatory mediators, IL6 and CCL2 (chemokine C-C motif ligand 2), following tissue injury compared to the placebo treatment. These results indicate a complex role for COX-2 in the inflammatory cascade in addition to the well-characterized COX-dependent pathway, as multiple pathways are also involved in rofecoxib-induced anti-inflammatory and analgesic effects at the gene expression level. These findings may also suggest an alternative hypothesis for the adverse effects attributed to selective inhibition of COX-2. PMID:17070997

Immune response genes receptors expression and polymorphisms in relation to multiple sclerosis susceptibility and response to INF-β therapy.

PubMed

Karam, Rehab A; Rezk, Noha A; Amer, Mona M; Fathy, Hala A

2016-09-01

Interferon (IFN)-β is one of the disease modifying drugs used in the treatment of multiple sclerosis. A predictive marker that indicates good or poor response to the treatment is highly desirable. We aimed to investigate the relation between the immune response genes receptors (IFNAR1, IFNAR2, and CCR5) expression and their polymorhic variants and multiple sclerosis (MS) susceptibility as well as the response to IFN-β therapy. The immune response genes receptors expression and genotyping were analyzed in 80 patients with MS, treated with IFN-β and in 110 healthy controls. There was a significant decrease of IFNAR1 and IFNAR2 mRNA expression and a significant increase of CCR5 mRNA expression in MS patients compared with the control group. Also, the level of IFNAR1, IFNAR2, and CCR5 mRNA expression was found to be significantly lower in the responders than nonresponders. Carriers of IFNAR1 18417 C/C genotype and C allele had an increased risk of developing MS. There was a significant relation between CCR5 Δ32 allele and IFN-β treatment response in MS patients. Our results highlighted the significance of IFNAR and CCR5 genes in multiple sclerosis risk and the response to IFN-β therapy. © 2016 IUBMB Life, 68(9):727-734, 2016. © 2016 International Union of Biochemistry and Molecular Biology.

Genes with a spike expression are clustered in chromosome (sub)bands and spike (sub)bands have a powerful prognostic value in patients with multiple myeloma

PubMed Central

Kassambara, Alboukadel; Hose, Dirk; Moreaux, Jérôme; Walker, Brian A.; Protopopov, Alexei; Reme, Thierry; Pellestor, Franck; Pantesco, Véronique; Jauch, Anna; Morgan, Gareth; Goldschmidt, Hartmut; Klein, Bernard

2012-01-01

Background Genetic abnormalities are common in patients with multiple myeloma, and may deregulate gene products involved in tumor survival, proliferation, metabolism and drug resistance. In particular, translocations may result in a high expression of targeted genes (termed spike expression) in tumor cells. We identified spike genes in multiple myeloma cells of patients with newly-diagnosed myeloma and investigated their prognostic value. Design and Methods Genes with a spike expression in multiple myeloma cells were picked up using box plot probe set signal distribution and two selection filters. Results In a cohort of 206 newly diagnosed patients with multiple myeloma, 2587 genes/expressed sequence tags with a spike expression were identified. Some spike genes were associated with some transcription factors such as MAF or MMSET and with known recurrent translocations as expected. Spike genes were not associated with increased DNA copy number and for a majority of them, involved unknown mechanisms. Of spiked genes, 36.7% clustered significantly in 149 out of 862 documented chromosome (sub)bands, of which 53 had prognostic value (35 bad, 18 good). Their prognostic value was summarized with a spike band score that delineated 23.8% of patients with a poor median overall survival (27.4 months versus not reached, P<0.001) using the training cohort of 206 patients. The spike band score was independent of other gene expression profiling-based risk scores, t(4;14), or del17p in an independent validation cohort of 345 patients. Conclusions We present a new approach to identify spike genes and their relationship to patients’ survival. PMID:22102711

Effects of Gene Orientation and Use of Multiple Promoters on the Expression of XYL1 and XYL2 in Saccharomyces cerevisiae

NASA Astrophysics Data System (ADS)

Bae, Ju Yun; Laplaza, José; Jeffries, Thomas W.

Orientation of adjacent genes has been reported to affect their expression in eukaryotic systems, and metabolic engineering also often makes repeated use of a few promoters to obtain high expression. To improve transcriptional control in heterologous expression, we examined how these factors affect gene expression and enzymatic activity in Saccharomyces cerevisiae. We assembled d-xylose reductase (XYL1) and d-xylitol dehydrogenase (XYL2) in four ways. Each pair of genes was placed in two different tandem (l→2→ or √1√2), convergent (1→√2), and divergent (√1 2→) orientations in autonomous plasmids. The TEF1 promoter was used to drive XYL1 and the TDH3 promoter to drive XYL2 in each of the constructs. The effects of gene orientation on growth, transcription, and enzyme activity were analyzed. The transcription level as measured by quantitative PCR (q-PCR) correlated with enzyme activities, but our data did not show a significant effect of gene orientation. To test the possible dilution of promoter strength due to multiple use of the same promoter, we examined the level of expression of XYL1 driven by either the TEF1 or TDH3 promoter when carried on a single copy plasmid. We then coexpressed XYL2 from either a single or multicopy plasmid, which was also driven by the same promoter. XYL2 transcript and enzyme expression increased with plasmid copy number, while the expression of XYLl was constant regardless of the number of other TEF1 or TDH3 promoters present in the cell. According to our data, there is no significant effect of gene orientation or multiple promoter use on gene transcription and translation when genes are expressed from plasmids; however, other factors could affect expression of adjacent genes in chromosomes.

A gene expression inflammatory signature specifically predicts multiple myeloma evolution and patients survival.

PubMed

Botta, C; Di Martino, M T; Ciliberto, D; Cucè, M; Correale, P; Rossi, M; Tagliaferri, P; Tassone, P

2016-12-16

Multiple myeloma (MM) is closely dependent on cross-talk between malignant plasma cells and cellular components of the inflammatory/immunosuppressive bone marrow milieu, which promotes disease progression, drug resistance, neo-angiogenesis, bone destruction and immune-impairment. We investigated the relevance of inflammatory genes in predicting disease evolution and patient survival. A bioinformatics study by Ingenuity Pathway Analysis on gene expression profiling dataset of monoclonal gammopathy of undetermined significance, smoldering and symptomatic-MM, identified inflammatory and cytokine/chemokine pathways as the most progressively affected during disease evolution. We then selected 20 candidate genes involved in B-cell inflammation and we investigated their role in predicting clinical outcome, through univariate and multivariate analyses (log-rank test, logistic regression and Cox-regression model). We defined an 8-genes signature (IL8, IL10, IL17A, CCL3, CCL5, VEGFA, EBI3 and NOS2) identifying each condition (MGUS/smoldering/symptomatic-MM) with 84% accuracy. Moreover, six genes (IFNG, IL2, LTA, CCL2, VEGFA, CCL3) were found independently correlated with patients' survival. Patients whose MM cells expressed high levels of Th1 cytokines (IFNG/LTA/IL2/CCL2) and low levels of CCL3 and VEGFA, experienced the longest survival. On these six genes, we built a prognostic risk score that was validated in three additional independent datasets. In this study, we provide proof-of-concept that inflammation has a critical role in MM patient progression and survival. The inflammatory-gene prognostic signature validated in different datasets clearly indicates novel opportunities for personalized anti-MM treatment.

Gene selection with multiple ordering criteria.

PubMed

Chen, James J; Tsai, Chen-An; Tzeng, Shengli; Chen, Chun-Houh

2007-03-05

A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two commonly known criteria to select differentially expressed genes under two experimental conditions. These two selection criteria often result in incompatible selected gene sets. Also, in a two-factor, say, treatment by time experiment, the investigator may be interested in one gene list that responds to both treatment and time effects. We propose three layer ranking algorithms, point-admissible, line-admissible (convex), and Pareto, to provide a preference gene list from multiple gene lists generated by different ranking criteria. Using the public colon data as an example, the layer ranking algorithms are applied to the three univariate ranking criteria, fold-change, p-value, and frequency of selections by the SVM-RFE classifier. A simulation experiment shows that for experiments with small or moderate sample sizes (less than 20 per group) and detecting a 4-fold change or less, the two-dimensional (p-value and fold-change) convex layer ranking selects differentially expressed genes with generally lower FDR and higher power than the standard p-value ranking. Three applications are presented. The first application illustrates a use of the layer rankings to potentially improve predictive accuracy. The second application illustrates an application to a two-factor experiment involving two dose levels and two time points. The layer rankings are applied to selecting differentially expressed genes relating to the dose and time effects. In the third application, the layer rankings are applied to a benchmark data set consisting of three dilution concentrations to provide a ranking system from a long list of differentially expressed genes generated from the three dilution concentrations. The layer ranking algorithms are useful to help investigators in selecting the most promising genes from multiple gene lists

Expression of the lef5 gene from Spodoptera exigua multiple nucleopolyhedrovirus contributes to the baculovirus stability in cell culture.

PubMed

Martínez-Solís, María; Jakubowska, Agata K; Herrero, Salvador

2017-10-01

Baculoviruses are a broad group of viruses infecting insects, predominately of the order Lepidoptera. They are used worldwide as biological insecticides and as expression vectors to produce recombinant proteins. Baculoviruses replicate in their host, although several cell lines have been developed for in vitro replication. Nevertheless, replication of baculoviruses in cell culture involves the generation of defective viruses with a decrease in productivity and virulence. Transcriptional studies of the Spodoptera exigua multiple nucleopolyhedrovirus (SeMNPV) and the Autographa californica multiple nucleopolyhedrovirus (AcMNPV) infective process revealed differences in the expression patterns when the virus replicated under in vitro (Se301 cells) or in vivo (S. exigua larvae) conditions. The late expression factor 5 (lef5) gene was found to be highly overexpressed when the virus replicates in larvae. To test the possible role of lef5 expression in viral stability, recombinant AcMNPV expressing the lef5 gene from SeMNPV (Se-lef5) was generated and its stability was monitored during successive infection passages in Sf21 cells by evaluating the loss of several essential and non-essential genes. The gfp transgene was more stable in those viruses expressing the Se-LEF5 protein and the GFP-defective viruses were accumulated at a lower level when compared to its control viruses, confirming the positive influence of lef5 in viral stability during the multiplication process. This work describes for the first time a viral factor involved in transgene stability when baculoviruses replicate in cell culture, opening new ways to facilitate the in vitro production of recombinant proteins using baculovirus.

The analysis of correlation between IL-1B gene expression and genotyping in multiple sclerosis patients.

PubMed

Heidary, Masoumeh; Rakhshi, Nahid; Pahlevan Kakhki, Majid; Behmanesh, Mehrdad; Sanati, Mohammad Hossein; Sanadgol, Nima; Kamaladini, Hossein; Nikravesh, Abbas

2014-08-15

IL-1B is released by monocytes, astrocytes and brain endothelial cells and seems to be involved in inflammatory reactions of the central nervous system (CNS) in multiple sclerosis (MS). This study aims to evaluate the expression level of IL-1B mRNA in peripheral blood mononuclear cells (PBMCs), genotype the rs16944 SNP and find out the role of this SNP on the expression level of IL-1B in MS patients. We found that the expression level of IL-1B in MS patients increased 3.336 times more than controls in PBMCs but the rs16944 SNP in the promoter region of IL-1B did not affect the expression level of this gene and there was not association of this SNP with MS in the examined population. Also, our data did not reveal any correlation between normalized expressions of IL-1B gene with age of participants, age of onset, and disease duration. Copyright © 2014 Elsevier B.V. All rights reserved.

Reference gene selection for quantitative gene expression studies during biological invasions: A test on multiple genes and tissues in a model ascidian Ciona savignyi.

PubMed

Huang, Xuena; Gao, Yangchun; Jiang, Bei; Zhou, Zunchun; Zhan, Aibin

2016-01-15

As invasive species have successfully colonized a wide range of dramatically different local environments, they offer a good opportunity to study interactions between species and rapidly changing environments. Gene expression represents one of the primary and crucial mechanisms for rapid adaptation to local environments. Here, we aim to select reference genes for quantitative gene expression analysis based on quantitative Real-Time PCR (qRT-PCR) for a model invasive ascidian, Ciona savignyi. We analyzed the stability of ten candidate reference genes in three tissues (siphon, pharynx and intestine) under two key environmental stresses (temperature and salinity) in the marine realm based on three programs (geNorm, NormFinder and delta Ct method). Our results demonstrated only minor difference for stability rankings among the three methods. The use of different single reference gene might influence the data interpretation, while multiple reference genes could minimize possible errors. Therefore, reference gene combinations were recommended for different tissues - the optimal reference gene combination for siphon was RPS15 and RPL17 under temperature stress, and RPL17, UBQ and TubA under salinity treatment; for pharynx, TubB, TubA and RPL17 were the most stable genes under temperature stress, while TubB, TubA and UBQ were the best under salinity stress; for intestine, UBQ, RPS15 and RPL17 were the most reliable reference genes under both treatments. Our results suggest that the necessity of selection and test of reference genes for different tissues under varying environmental stresses. The results obtained here are expected to reveal mechanisms of gene expression-mediated invasion success using C. savignyi as a model species. Copyright © 2015 Elsevier B.V. All rights reserved.

Validation of the Lung Subtyping Panel in Multiple Fresh-Frozen and Formalin-Fixed, Paraffin-Embedded Lung Tumor Gene Expression Data Sets.

PubMed

Faruki, Hawazin; Mayhew, Gregory M; Fan, Cheng; Wilkerson, Matthew D; Parker, Scott; Kam-Morgan, Lauren; Eisenberg, Marcia; Horten, Bruce; Hayes, D Neil; Perou, Charles M; Lai-Goldman, Myla

2016-06-01

Context .- A histologic classification of lung cancer subtypes is essential in guiding therapeutic management. Objective .- To complement morphology-based classification of lung tumors, a previously developed lung subtyping panel (LSP) of 57 genes was tested using multiple public fresh-frozen gene-expression data sets and a prospectively collected set of formalin-fixed, paraffin-embedded lung tumor samples. Design .- The LSP gene-expression signature was evaluated in multiple lung cancer gene-expression data sets totaling 2177 patients collected from 4 platforms: Illumina RNAseq (San Diego, California), Agilent (Santa Clara, California) and Affymetrix (Santa Clara) microarrays, and quantitative reverse transcription-polymerase chain reaction. Gene centroids were calculated for each of 3 genomic-defined subtypes: adenocarcinoma, squamous cell carcinoma, and neuroendocrine, the latter of which encompassed both small cell carcinoma and carcinoid. Classification by LSP into 3 subtypes was evaluated in both fresh-frozen and formalin-fixed, paraffin-embedded tumor samples, and agreement with the original morphology-based diagnosis was determined. Results .- The LSP-based classifications demonstrated overall agreement with the original clinical diagnosis ranging from 78% (251 of 322) to 91% (492 of 538 and 869 of 951) in the fresh-frozen public data sets and 84% (65 of 77) in the formalin-fixed, paraffin-embedded data set. The LSP performance was independent of tissue-preservation method and gene-expression platform. Secondary, blinded pathology review of formalin-fixed, paraffin-embedded samples demonstrated concordance of 82% (63 of 77) with the original morphology diagnosis. Conclusions .- The LSP gene-expression signature is a reproducible and objective method for classifying lung tumors and demonstrates good concordance with morphology-based classification across multiple data sets. The LSP panel can supplement morphologic assessment of lung cancers, particularly

JRmGRN: Joint reconstruction of multiple gene regulatory networks with common hub genes using data from multiple tissues or conditions.

PubMed

Deng, Wenping; Zhang, Kui; Liu, Sanzhen; Zhao, Patrick; Xu, Shizhong; Wei, Hairong

2018-04-30

Joint reconstruction of multiple gene regulatory networks (GRNs) using gene expression data from multiple tissues/conditions is very important for understanding common and tissue/condition-specific regulation. However, there are currently no computational models and methods available for directly constructing such multiple GRNs that not only share some common hub genes but also possess tissue/condition-specific regulatory edges. In this paper, we proposed a new graphic Gaussian model for joint reconstruction of multiple gene regulatory networks (JRmGRN), which highlighted hub genes, using gene expression data from several tissues/conditions. Under the framework of Gaussian graphical model, JRmGRN method constructs the GRNs through maximizing a penalized log likelihood function. We formulated it as a convex optimization problem, and then solved it with an alternating direction method of multipliers (ADMM) algorithm. The performance of JRmGRN was first evaluated with synthetic data and the results showed that JRmGRN outperformed several other methods for reconstruction of GRNs. We also applied our method to real Arabidopsis thaliana RNA-seq data from two light regime conditions in comparison with other methods, and both common hub genes and some conditions-specific hub genes were identified with higher accuracy and precision. JRmGRN is available as a R program from: https://github.com/wenpingd. hairong@mtu.edu. Proof of theorem, derivation of algorithm and supplementary data are available at Bioinformatics online.

Origins of extrinsic variability in eukaryotic gene expression

NASA Astrophysics Data System (ADS)

Volfson, Dmitri; Marciniak, Jennifer; Blake, William J.; Ostroff, Natalie; Tsimring, Lev S.; Hasty, Jeff

2006-02-01

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution, determination of cell fates and the development of genetic disease. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes simultaneously, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modelling with fluorescence data generated from multiple promoter-gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous lower limit for expression variability. A second source, which is modelled as originating from a common upstream transcription factor, exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Origins of extrinsic variability in eukaryotic gene expression

NASA Astrophysics Data System (ADS)

Volfson, Dmitri; Marciniak, Jennifer; Blake, William J.; Ostroff, Natalie; Tsimring, Lev S.; Hasty, Jeff

2006-03-01

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution, determination of cell fates and the development of genetic disease. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes in concert, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modeling with fluorescence data generated from multiple promoter-gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous noise floor in expression variability. A second source which is modeled as originating from a common upstream transcription factor exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

Spatially Restricted and Developmentally Dynamic Expression of Engrailed Genes in Multiple Cerebellar Cell Types

PubMed Central

Wilson, Sandra L.; Kalinovsky, Anna; Orvis, Grant D.

2011-01-01

The cerebellum is a highly organized structure partitioned into lobules along the anterior–posterior (A-P) axis and into striped molecular domains along the medial–lateral (M-L) axis. The Engrailed (En) homeobox genes are required for patterning the morphological and molecular domains along both axes, as well as for the establishment of the normal afferent topography required to generate a fully functional cerebellum. As a means to understand how the En genes regulate multiple levels of cerebellum construction, we characterized En1 and En2 expression around birth and at postnatal day (P)21 during the period when the cerebellum undergoes a remarkable transformation from a smooth ovoid structure to a highly foliated structure. We show that both En1 and En2 are expressed in many neuronal cell types in the cerebellum, and expression persists until at least P21. En1 and En2 expression, however, undergoes profound changes in their cellular and spatial distributions between embryonic stages and P21, and their expression domains become largely distinct. Comparison of the distribution of En-expressing Purkinje cells relative to early- and late-onset Purkinje cell M-L stripe proteins revealed that although En1- and En2-expressing Purkinje cell domains do not strictly align with those of ZEBRINII at P21, a clear pattern exists that is most evident at E17.5 by an inverse correlation between the level of En2 expression and PLCβ4 and EPHA4. PMID:21431469

Analysis of bHLH coding genes using gene co-expression network approach.

PubMed

Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

2016-07-01

Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species.

Clinical and multiple gene expression variables in survival analysis of breast cancer: Analysis with the hypertabastic survival model

PubMed Central

2012-01-01

Background We explore the benefits of applying a new proportional hazard model to analyze survival of breast cancer patients. As a parametric model, the hypertabastic survival model offers a closer fit to experimental data than Cox regression, and furthermore provides explicit survival and hazard functions which can be used as additional tools in the survival analysis. In addition, one of our main concerns is utilization of multiple gene expression variables. Our analysis treats the important issue of interaction of different gene signatures in the survival analysis. Methods The hypertabastic proportional hazards model was applied in survival analysis of breast cancer patients. This model was compared, using statistical measures of goodness of fit, with models based on the semi-parametric Cox proportional hazards model and the parametric log-logistic and Weibull models. The explicit functions for hazard and survival were then used to analyze the dynamic behavior of hazard and survival functions. Results The hypertabastic model provided the best fit among all the models considered. Use of multiple gene expression variables also provided a considerable improvement in the goodness of fit of the model, as compared to use of only one. By utilizing the explicit survival and hazard functions provided by the model, we were able to determine the magnitude of the maximum rate of increase in hazard, and the maximum rate of decrease in survival, as well as the times when these occurred. We explore the influence of each gene expression variable on these extrema. Furthermore, in the cases of continuous gene expression variables, represented by a measure of correlation, we were able to investigate the dynamics with respect to changes in gene expression. Conclusions We observed that use of three different gene signatures in the model provided a greater combined effect and allowed us to assess the relative importance of each in determination of outcome in this data set. These

Gene Expression Profiling of Multiple Sclerosis Pathology Identifies Early Patterns of Demyelination Surrounding Chronic Active Lesions

PubMed Central

Hendrickx, Debbie A. E.; van Scheppingen, Jackelien; van der Poel, Marlijn; Bossers, Koen; Schuurman, Karianne G.; van Eden, Corbert G.; Hol, Elly M.; Hamann, Jörg; Huitinga, Inge

2017-01-01

In multiple sclerosis (MS), activated microglia and infiltrating macrophages phagocytose myelin focally in (chronic) active lesions. These demyelinating sites expand in time, but at some point turn inactive into a sclerotic scar. To identify molecular mechanisms underlying lesion activity and halt, we analyzed genome-wide gene expression in rim and peri-lesional regions of chronic active and inactive MS lesions, as well as in control tissue. Gene clustering revealed patterns of gene expression specifically associated with MS and with the presumed, subsequent stages of lesion development. Next to genes involved in immune functions, we found regulation of novel genes in and around the rim of chronic active lesions, such as NPY, KANK4, NCAN, TKTL1, and ANO4. Of note, the presence of many foamy macrophages in active rims was accompanied by a congruent upregulation of genes related to lipid binding, such as MSR1, CD68, CXCL16, and OLR1, and lipid uptake, such as CHIT1, GPNMB, and CCL18. Except CCL18, these genes were already upregulated in regions around active MS lesions, showing that such lesions are indeed expanding. In vitro downregulation of the scavenger receptors MSR1 and CXCL16 reduced myelin uptake. In conclusion, this study provides the gene expression profile of different aspects of MS pathology and indicates that early demyelination, mediated by scavenger receptors, is already present in regions around active MS lesions. Genes involved in early demyelination events in regions surrounding chronic active MS lesions might be promising therapeutic targets to stop lesion expansion. PMID:29312322

Gene Expression Profiling of Multiple Sclerosis Pathology Identifies Early Patterns of Demyelination Surrounding Chronic Active Lesions.

PubMed

Hendrickx, Debbie A E; van Scheppingen, Jackelien; van der Poel, Marlijn; Bossers, Koen; Schuurman, Karianne G; van Eden, Corbert G; Hol, Elly M; Hamann, Jörg; Huitinga, Inge

2017-01-01

In multiple sclerosis (MS), activated microglia and infiltrating macrophages phagocytose myelin focally in (chronic) active lesions. These demyelinating sites expand in time, but at some point turn inactive into a sclerotic scar. To identify molecular mechanisms underlying lesion activity and halt, we analyzed genome-wide gene expression in rim and peri-lesional regions of chronic active and inactive MS lesions, as well as in control tissue. Gene clustering revealed patterns of gene expression specifically associated with MS and with the presumed, subsequent stages of lesion development. Next to genes involved in immune functions, we found regulation of novel genes in and around the rim of chronic active lesions, such as NPY, KANK4, NCAN, TKTL1 , and ANO4 . Of note, the presence of many foamy macrophages in active rims was accompanied by a congruent upregulation of genes related to lipid binding, such as MSR1, CD68, CXCL16 , and OLR1 , and lipid uptake, such as CHIT1, GPNMB , and CCL18 . Except CCL18 , these genes were already upregulated in regions around active MS lesions, showing that such lesions are indeed expanding. In vitro downregulation of the scavenger receptors MSR1 and CXCL16 reduced myelin uptake. In conclusion, this study provides the gene expression profile of different aspects of MS pathology and indicates that early demyelination, mediated by scavenger receptors, is already present in regions around active MS lesions. Genes involved in early demyelination events in regions surrounding chronic active MS lesions might be promising therapeutic targets to stop lesion expansion.

Klotho gene expression decreases in peripheral blood mononuclear cells (PBMCs) of patients with relapsing-remitting multiple sclerosis.

PubMed

Karami, Masoumeh; Mehrabi, Farzad; Allameh, Abdolamir; Pahlevan Kakhki, Majid; Amiri, Mehdi; Emami Aleagha, Mohammad Sajad

2017-10-15

we recently showed that a hypothesized anti-aging and anti-inflammatory protein, namely Klotho, may contribute to the etiology and/or pathogenesis of multiple sclerosis (MS). In addition, Klotho function and its gene expression are dependent on inflammatory pathways. Accordingly, the aim of this study was to investigate the Klotho gene expression within peripheral blood mononuclear cells (PBMCs) of patients with MS. Altogether, 30 patients with relapsing-remitting MS (RRMS) along with 30 age and sex-matched healthy individuals were enrolled in this study. Blood samples were obtained from all participants and then PBMCs were isolated. The quantitative Real-Time PCR was carried out for Klotho mRNA derived from PBMCs. The results showed that klotho gene expression in the PBMCs of patients with RRMS is nearly 2.5-fold less than healthy individuals (P=0.0006). This is the first study demonstrating a possible role of Klotho in the PBMCs of MS patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Regulatory analysis of the mouse Hoxb3 gene: multiple elements work in concert to direct temporal and spatial patterns of expression.

PubMed

Kwan, C T; Tsang, S L; Krumlauf, R; Sham, M H

2001-04-01

The expression pattern of the mouse Hoxb3 gene is exceptionally complex and dynamic compared with that of other members of the Hoxb cluster. There are multiple types of transcripts for Hoxb3 gene, and the anterior boundaries of its expression vary at different stages of development. Two enhancers flanking Hoxb3 on the 3' and 5' sides regulate Hoxb2 and Hoxb4, respectively, and these control regions define the two ends of a 28-kb interval in and around the Hoxb3 locus. To assay the regulatory potential of DNA fragments in this interval we have used transgenic analysis with a lacZ reporter gene to locate cis-elements for directing the dynamic patterns of Hoxb3 expression. Our detailed analysis has identified four new and widely spaced cis-acting regulatory regions that can together account for major aspects of the Hoxb3 expression pattern. Elements Ib, IIIa, and IVb control gene expression in neural and mesodermal tissues; element Va controls mesoderm-specific gene expression. The most anterior neural expression domain of Hoxb3 is controlled by an r5 enhancer (element IVa); element IIIa directs reporter expression in the anterior spinal cord and hindbrain up to r6, and the region A enhancer (in element I) mediates posterior neural expression. Hence, the regulation of segmental expression of Hoxb3 in the hindbrain is different from that of Hoxa3, as two separate enhancer elements contribute to expression in r5 and r6. The mesoderm-specific element (Va) directs reporter expression to prevertebra C1 at 12.5 dpc, which is the anterior limit of paraxial mesoderm expression for Hoxb3. When tested in combinations, these cis-elements appear to work as modules in an additive manner to recapitulate the major endogenous expression patterns of Hoxb3 during embryogenesis. Together our study shows that multiple control elements direct reporter gene expression in diverse tissue-, temporal-, and spatially restricted subset of the endogenous Hoxb3 expression domains and work in

Molecular profiling of multiple myeloma: from gene expression analysis to next-generation sequencing.

PubMed

Agnelli, Luca; Tassone, Pierfrancesco; Neri, Antonino

2013-06-01

Multiple myeloma is a fatal malignant proliferation of clonal bone marrow Ig-secreting plasma cells, characterized by wide clinical, biological, and molecular heterogeneity. Herein, global gene and microRNA expression, genome-wide DNA profilings, and next-generation sequencing technology used to investigate the genomic alterations underlying the bio-clinical heterogeneity in multiple myeloma are discussed. High-throughput technologies have undoubtedly allowed a better comprehension of the molecular basis of the disease, a fine stratification, and early identification of high-risk patients, and have provided insights toward targeted therapy studies. However, such technologies are at risk of being affected by laboratory- or cohort-specific biases, and are moreover influenced by high number of expected false positives. This aspect has a major weight in myeloma, which is characterized by large molecular heterogeneity. Therefore, meta-analysis as well as multiple approaches are desirable if not mandatory to validate the results obtained, in line with commonly accepted recommendation for tumor diagnostic/prognostic biomarker studies.

Alteration of Multiple Leukocyte Gene Expression Networks is Linked with Magnetic Resonance Markers of Prognosis After Acute ST-Elevation Myocardial Infarction.

PubMed

Teren, A; Kirsten, H; Beutner, F; Scholz, M; Holdt, L M; Teupser, D; Gutberlet, M; Thiery, J; Schuler, G; Eitel, I

2017-02-03

Prognostic relevant pathways of leukocyte involvement in human myocardial ischemic-reperfusion injury are largely unknown. We enrolled 136 patients with ST-elevation myocardial infarction (STEMI) after primary angioplasty within 12 h after onset of symptoms. Following reperfusion, whole blood was collected within a median time interval of 20 h (interquartile range: 15-25 h) for genome-wide gene expression analysis. Subsequent CMR scans were performed using a standard protocol to determine infarct size (IS), area at risk (AAR), myocardial salvage index (MSI) and the extent of late microvascular obstruction (lateMO). We found 398 genes associated with lateMO and two genes with IS. Neither AAR, nor MSI showed significant correlations with gene expression. Genes correlating with lateMO were strongly related to several canonical pathways, including positive regulation of T-cell activation (p = 3.44 × 10 -5 ), and regulation of inflammatory response (p = 1.86 × 10 -3 ). Network analysis of multiple gene expression alterations associated with larger lateMO identified the following functional consequences: facilitated utilisation and decreased concentration of free fatty acid, repressed cell differentiation, enhanced phagocyte movement, increased cell death, vascular disease and compensatory vasculogenesis. In conclusion, the extent of lateMO after acute, reperfused STEMI correlated with altered activation of multiple genes related to fatty acid utilisation, lymphocyte differentiation, phagocyte mobilisation, cell survival, and vascular dysfunction.

Integrating genome-wide association studies and gene expression data highlights dysregulated multiple sclerosis risk pathways.

PubMed

Liu, Guiyou; Zhang, Fang; Jiang, Yongshuai; Hu, Yang; Gong, Zhongying; Liu, Shoufeng; Chen, Xiuju; Jiang, Qinghua; Hao, Junwei

2017-02-01

Much effort has been expended on identifying the genetic determinants of multiple sclerosis (MS). Existing large-scale genome-wide association study (GWAS) datasets provide strong support for using pathway and network-based analysis methods to investigate the mechanisms underlying MS. However, no shared genetic pathways have been identified to date. We hypothesize that shared genetic pathways may indeed exist in different MS-GWAS datasets. Here, we report results from a three-stage analysis of GWAS and expression datasets. In stage 1, we conducted multiple pathway analyses of two MS-GWAS datasets. In stage 2, we performed a candidate pathway analysis of the large-scale MS-GWAS dataset. In stage 3, we performed a pathway analysis using the dysregulated MS gene list from seven human MS case-control expression datasets. In stage 1, we identified 15 shared pathways. In stage 2, we successfully replicated 14 of these 15 significant pathways. In stage 3, we found that dysregulated MS genes were significantly enriched in 10 of 15 MS risk pathways identified in stages 1 and 2. We report shared genetic pathways in different MS-GWAS datasets and highlight some new MS risk pathways. Our findings provide new insights on the genetic determinants of MS.

GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

PubMed

Ye, Ning; Yin, Hengfu; Liu, Jingjing; Dai, Xiaogang; Yin, Tongming

2015-01-01

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.

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

PubMed Central

Sanchita; Sharma, Ashok

2016-01-01

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

Estimating differential expression from multiple indicators

PubMed Central

Ilmjärv, Sten; Hundahl, Christian Ansgar; Reimets, Riin; Niitsoo, Margus; Kolde, Raivo; Vilo, Jaak; Vasar, Eero; Luuk, Hendrik

2014-01-01

Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR. PMID:24586062

A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue.

PubMed

Chen, Zhenyu; Li, Jianping; Wei, Liwei

2007-10-01

Recently, gene expression profiling using microarray techniques has been shown as a promising tool to improve the diagnosis and treatment of cancer. Gene expression data contain high level of noise and the overwhelming number of genes relative to the number of available samples. It brings out a great challenge for machine learning and statistic techniques. Support vector machine (SVM) has been successfully used to classify gene expression data of cancer tissue. In the medical field, it is crucial to deliver the user a transparent decision process. How to explain the computed solutions and present the extracted knowledge becomes a main obstacle for SVM. A multiple kernel support vector machine (MK-SVM) scheme, consisting of feature selection, rule extraction and prediction modeling is proposed to improve the explanation capacity of SVM. In this scheme, we show that the feature selection problem can be translated into an ordinary multiple parameters learning problem. And a shrinkage approach: 1-norm based linear programming is proposed to obtain the sparse parameters and the corresponding selected features. We propose a novel rule extraction approach using the information provided by the separating hyperplane and support vectors to improve the generalization capacity and comprehensibility of rules and reduce the computational complexity. Two public gene expression datasets: leukemia dataset and colon tumor dataset are used to demonstrate the performance of this approach. Using the small number of selected genes, MK-SVM achieves encouraging classification accuracy: more than 90% for both two datasets. Moreover, very simple rules with linguist labels are extracted. The rule sets have high diagnostic power because of their good classification performance.

Tensor decomposition-based and principal-component-analysis-based unsupervised feature extraction applied to the gene expression and methylation profiles in the brains of social insects with multiple castes.

PubMed

Taguchi, Y-H

2018-05-08

Even though coexistence of multiple phenotypes sharing the same genomic background is interesting, it remains incompletely understood. Epigenomic profiles may represent key factors, with unknown contributions to the development of multiple phenotypes, and social-insect castes are a good model for elucidation of the underlying mechanisms. Nonetheless, previous studies have failed to identify genes associated with aberrant gene expression and methylation profiles because of the lack of suitable methodology that can address this problem properly. A recently proposed principal component analysis (PCA)-based and tensor decomposition (TD)-based unsupervised feature extraction (FE) can solve this problem because these two approaches can deal with gene expression and methylation profiles even when a small number of samples is available. PCA-based and TD-based unsupervised FE methods were applied to the analysis of gene expression and methylation profiles in the brains of two social insects, Polistes canadensis and Dinoponera quadriceps. Genes associated with differential expression and methylation between castes were identified, and analysis of enrichment of Gene Ontology terms confirmed reliability of the obtained sets of genes from the biological standpoint. Biologically relevant genes, shown to be associated with significant differential gene expression and methylation between castes, were identified here for the first time. The identification of these genes may help understand the mechanisms underlying epigenetic control of development of multiple phenotypes under the same genomic conditions.

Discovery and validation of a glioblastoma co-expressed gene module

PubMed Central

Dunwoodie, Leland J.; Poehlman, William L.; Ficklin, Stephen P.; Feltus, Frank Alexander

2018-01-01

Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network. PMID:29541392

Discovery and validation of a glioblastoma co-expressed gene module.

PubMed

Dunwoodie, Leland J; Poehlman, William L; Ficklin, Stephen P; Feltus, Frank Alexander

2018-02-16

Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network.

Microarray expression profiling identifies genes with altered expression in HDL-deficient mice

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

Callow, Matthew J.; Dudoit, Sandrine; Gong, Elaine L.

2000-05-05

Based on the assumption that severe alterations in the expression of genes known to be involved in HDL metabolism may affect the expression of other genes we screened an array of over 5000 mouse expressed sequence tags (ESTs) for altered gene expression in the livers of two lines of mice with dramatic decreases in HDL plasma concentrations. Labeled cDNA from livers of apolipoprotein AI (apo AI) knockout mice, Scavenger Receptor BI (SR-BI) transgenic mice and control mice were co-hybridized to microarrays. Two-sample t-statistics were used to identify genes with altered expression levels in the knockout or transgenic mice compared withmore » the control mice. In the SR-BI group we found 9 array elements representing at least 5 genes to be significantly altered on the basis of an adjusted p value of less than 0.05. In the apo AI knockout group 8 array elements representing 4 genes were altered compared with the control group (p < 0.05). Several of the genes identified in the SR-BI transgenic suggest altered sterol metabolism and oxidative processes. These studies illustrate the use of multiple-testing methods for the identification of genes with altered expression in replicated microarray experiments of apo AI knockout and SR-BI transgenic mice.« less

Time-Course Gene Set Analysis for Longitudinal Gene Expression Data

PubMed Central

Hejblum, Boris P.; Skinner, Jason; Thiébaut, Rodolphe

2015-01-01

Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA) introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estimates. It allows to use all available repeated measurements while dealing with unbalanced data due to missing at random (MAR) measurements. TcGSA is a hypothesis driven method that identifies a priori defined gene sets with significant expression variations over time, taking into account the potential heterogeneity of expression within gene sets. When biological conditions are compared, the method indicates if the time patterns of gene sets significantly differ according to these conditions. The interest of the method is illustrated by its application to two real life datasets: an HIV therapeutic vaccine trial (DALIA-1 trial), and data from a recent study on influenza and pneumococcal vaccines. In the DALIA-1 trial TcGSA revealed a significant change in gene expression over time within 69 gene sets during vaccination, while a standard univariate individual gene analysis corrected for multiple testing as well as a standard a Gene Set Enrichment Analysis (GSEA) for time series both failed to detect any significant pattern change over time. When applied to the second illustrative data set, TcGSA allowed the identification of 4 gene sets finally found to be linked with the influenza vaccine too although they were found to be associated to the pneumococcal vaccine only in previous analyses. In our simulation study TcGSA exhibits good statistical properties, and an increased power compared to other approaches for analyzing time-course expression patterns of gene sets. The method is made available for the community through an R package. PMID:26111374

Evolutionary Approach for Relative Gene Expression Algorithms

PubMed Central

Czajkowski, Marcin

2014-01-01

A Relative Expression Analysis (RXA) uses ordering relationships in a small collection of genes and is successfully applied to classiffication using microarray data. As checking all possible subsets of genes is computationally infeasible, the RXA algorithms require feature selection and multiple restrictive assumptions. Our main contribution is a specialized evolutionary algorithm (EA) for top-scoring pairs called EvoTSP which allows finding more advanced gene relations. We managed to unify the major variants of relative expression algorithms through EA and introduce weights to the top-scoring pairs. Experimental validation of EvoTSP on public available microarray datasets showed that the proposed solution significantly outperforms in terms of accuracy other relative expression algorithms and allows exploring much larger solution space. PMID:24790574

Clustering cancer gene expression data by projective clustering ensemble

PubMed Central

Yu, Xianxue; Yu, Guoxian

2017-01-01

Gene expression data analysis has paramount implications for gene treatments, cancer diagnosis and other domains. Clustering is an important and promising tool to analyze gene expression data. Gene expression data is often characterized by a large amount of genes but with limited samples, thus various projective clustering techniques and ensemble techniques have been suggested to combat with these challenges. However, it is rather challenging to synergy these two kinds of techniques together to avoid the curse of dimensionality problem and to boost the performance of gene expression data clustering. In this paper, we employ a projective clustering ensemble (PCE) to integrate the advantages of projective clustering and ensemble clustering, and to avoid the dilemma of combining multiple projective clusterings. Our experimental results on publicly available cancer gene expression data show PCE can improve the quality of clustering gene expression data by at least 4.5% (on average) than other related techniques, including dimensionality reduction based single clustering and ensemble approaches. The empirical study demonstrates that, to further boost the performance of clustering cancer gene expression data, it is necessary and promising to synergy projective clustering with ensemble clustering. PCE can serve as an effective alternative technique for clustering gene expression data. PMID:28234920

Digital analysis of the expression levels of multiple colorectal cancer-related genes by multiplexed digital-PCR coupled with hydrogel bead-array.

PubMed

Qi, Zongtai; Ma, Yinjiao; Deng, Lili; Wu, Haiping; Zhou, Guohua; Kajiyama, Tomoharu; Kambara, Hideki

2011-06-07

To digitally analyze expression levels of multiple genes in one reaction, we proposed a method termed as 'MDHB' (Multiplexed Digital-PCR coupled with Hydrogel Bead-array). The template for bead-based emulsion PCR (emPCR) was prepared by reverse transcription using sequence-tagged primers. The beads recovered from emPCR were immobilized with hydrogel to form a single-bead layer on a chip, and then decoded by gene-specific probe hybridization and Cy3-dUTP based primer extension reaction. The specificity of probe hybridization was improved by using electrophoresis to remove mismatched probes on the bead's surface. The number of positive beads reflects the abundance of expressed genes; the expression levels of target genes were normalized to a housekeeping gene and expressed as the number ratio of green beads to red beads. The discrimination limit of MDHB is 0.1% (i.e., one target molecule from 1000 background molecules), and the sensitivity of the method is below 100 cells when using the β-actin gene as the detection target. We have successfully employed MDHB to detect the relative expression levels of four colorectal cancer (CRC)-related genes (c-myc, COX-2, MMP7, and DPEP1) in 8 tissue samples and 9 stool samples from CRC patients, giving the detection rates of 100% and 77%, respectively. The results suggest that MDHB could be a potential tool for early non-invasive diagnosis of CRC.

Gene duplication, silencing and expression alteration govern the molecular evolution of PRC2 genes in plants.

PubMed

Furihata, Hazuka Y; Suenaga, Kazuya; Kawanabe, Takahiro; Yoshida, Takanori; Kawabe, Akira

2016-10-13

PRC2 genes were analyzed for their number of gene duplications, d N /d S ratios and expression patterns among Brassicaceae and Gramineae species. Although both amino acid sequences and copy number of the PRC2 genes were generally well conserved in both Brassicaceae and Gramineae species, we observed that some rapidly evolving genes experienced duplications and expression pattern changes. After multiple duplication events, all but one or two of the duplicated copies tend to be silenced. Silenced copies were reactivated in the endosperm and showed ectopic expression in developing seeds. The results indicated that rapid evolution of some PRC2 genes is initially caused by a relaxation of selective constraint following the gene duplication events. Several loci could become maternally expressed imprinted genes and acquired functional roles in the endosperm.

Rat Models of Cardiovascular Disease Demonstrate Distinctive Pulmonary Gene Expressions for Vascular Response Genes: Impact of Ozone Exposure

EPA Science Inventory

Comparative gene expression profiling of multiple tissues from rat strains with genetic predisposition to diverse cardiovascular diseases (CVD) can help decode the transcriptional program that governs organ-specific functions. We examined expressions of CVD genes in the lungs of ...

Allen Brain Atlas-Driven Visualizations: a web-based gene expression energy visualization tool.

PubMed

Zaldivar, Andrew; Krichmar, Jeffrey L

2014-01-01

The Allen Brain Atlas-Driven Visualizations (ABADV) is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA) across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources.

FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data.

PubMed

Manijak, Mieszko P; Nielsen, Henrik B

2011-06-11

Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially circumvented by instead matching gene expression signatures to signatures of other experiments. To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700 Arabidopsis microarray experiments. Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/.

Mixture models for detecting differentially expressed genes in microarrays.

PubMed

Jones, Liat Ben-Tovim; Bean, Richard; McLachlan, Geoffrey J; Zhu, Justin Xi

2006-10-01

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

Large clusters of co-expressed genes in the Drosophila genome.

PubMed

Boutanaev, Alexander M; Kalmykova, Alla I; Shevelyov, Yuri Y; Nurminsky, Dmitry I

2002-12-12

Clustering of co-expressed, non-homologous genes on chromosomes implies their co-regulation. In lower eukaryotes, co-expressed genes are often found in pairs. Clustering of genes that share aspects of transcriptional regulation has also been reported in higher eukaryotes. To advance our understanding of the mode of coordinated gene regulation in multicellular organisms, we performed a genome-wide analysis of the chromosomal distribution of co-expressed genes in Drosophila. We identified a total of 1,661 testes-specific genes, one-third of which are clustered on chromosomes. The number of clusters of three or more genes is much higher than expected by chance. We observed a similar trend for genes upregulated in the embryo and in the adult head, although the expression pattern of individual genes cannot be predicted on the basis of chromosomal position alone. Our data suggest that the prevalent mechanism of transcriptional co-regulation in higher eukaryotes operates with extensive chromatin domains that comprise multiple genes.

PLEXdb: Gene expression resources for plants and plant pathogens

USDA-ARS?s Scientific Manuscript database

PLEXdb (Plant Expression Database), in partnership with community databases, supports comparisons of gene expression across multiple plant and pathogen species, promoting individuals and/or consortia to upload genome-scale data sets to contrast them to previously archived data. These analyses facili...

Multiple Sclerosis Risk Variant HLA-DRB1*1501 Associates with High Expression of DRB1 Gene in Different Human Populations

PubMed Central

Abad-Grau, María del Mar; Fedetz, María; Izquierdo, Guillermo; Lucas, Miguel; Fernández, Óscar; Ndagire, Dorothy; Catalá-Rabasa, Antonio; Ruiz, Agustín; Gayán, Javier; Delgado, Concepción; Arnal, Carmen

2012-01-01

The human leukocyte antigen (HLA) DRB1*1501 has been consistently associated with multiple sclerosis (MS) in nearly all populations tested. This points to a specific antigen presentation as the pathogenic mechanism though this does not fully explain the disease association. The identification of expression quantitative trait loci (eQTL) for genes in the HLA locus poses the question of the role of gene expression in MS susceptibility. We analyzed the eQTLs in the HLA region with respect to MS-associated HLA-variants obtained from genome-wide association studies (GWAS). We found that the Tag of DRB1*1501, rs3135388 A allele, correlated with high expression of DRB1, DRB5 and DQB1 genes in a Caucasian population. In quantitative terms, the MS-risk AA genotype carriers of rs3135388 were associated with 15.7-, 5.2- and 8.3-fold higher expression of DQB1, DRB5 and DRB1, respectively, than the non-risk GG carriers. The haplotype analysis of expression-associated variants in a Spanish MS cohort revealed that high expression of DRB1 and DQB1 alone did not contribute to the disease. However, in Caucasian, Asian and African American populations, the DRB1*1501 allele was always highly expressed. In other immune related diseases such as type 1 diabetes, inflammatory bowel disease, ulcerative colitis, asthma and IgA deficiency, the best GWAS-associated HLA SNPs were also eQTLs for different HLA Class II genes. Our data suggest that the DR/DQ expression levels, together with specific structural properties of alleles, seem to be the causal effect in MS and in other immunopathologies rather than specific antigen presentation alone. PMID:22253788

Ikaros gene expression and leukemia.

PubMed

Tonnelle, Cécile; Calmels, Boris; Maroc, Christine; Gabert, Jean; Chabannon, Christian

2002-01-01

The Ikaros (Ik) protein, or LyF1, was initially described as a protein binding to regulatory sequences of a number of genes expressed in murine lymphoid cells. Ikaros is a critical regulator of normal hematopoietic stem cell differentiation, as evidenced by dramatic defects in the lymphoid compartments, in homozygous animals with gene inactivation. Because differential splicing produces multiple isoforms with potentially different functions, Ikaros provides a unique model to study how post-transcriptional mechanisms may be involved in neoplastic processes. Indeed, several groups including ours have underlined evidences that expression of different Ikaros isoforms vary among different types of leukemias. The predominance of short isoforms in certain subsets is intriguing. Here, additional observations reinforced the hypothesis that Ikaros expression may be deregulated in human leukemias. Whether this is a cause or a consequence of the leukemic process remains speculative. Other human diseases however, provide examples of abnormal post-transcriptional regulations that have been further characterized.

Analysis of multiplex gene expression maps obtained by voxelation.

PubMed

An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

2009-04-29

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental

Neighboring Genes Show Correlated Evolution in Gene Expression

PubMed Central

Ghanbarian, Avazeh T.; Hurst, Laurence D.

2015-01-01

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

Geometry of the Gene Expression Space of Individual Cells

PubMed Central

Korem, Yael; Szekely, Pablo; Hart, Yuval; Sheftel, Hila; Hausser, Jean; Mayo, Avi; Rothenberg, Michael E.; Kalisky, Tomer; Alon, Uri

2015-01-01

There is a revolution in the ability to analyze gene expression of single cells in a tissue. To understand this data we must comprehend how cells are distributed in a high-dimensional gene expression space. One open question is whether cell types form discrete clusters or whether gene expression forms a continuum of states. If such a continuum exists, what is its geometry? Recent theory on evolutionary trade-offs suggests that cells that need to perform multiple tasks are arranged in a polygon or polyhedron (line, triangle, tetrahedron and so on, generally called polytopes) in gene expression space, whose vertices are the expression profiles optimal for each task. Here, we analyze single-cell data from human and mouse tissues profiled using a variety of single-cell technologies. We fit the data to shapes with different numbers of vertices, compute their statistical significance, and infer their tasks. We find cases in which single cells fill out a continuum of expression states within a polyhedron. This occurs in intestinal progenitor cells, which fill out a tetrahedron in gene expression space. The four vertices of this tetrahedron are each enriched with genes for a specific task related to stemness and early differentiation. A polyhedral continuum of states is also found in spleen dendritic cells, known to perform multiple immune tasks: cells fill out a tetrahedron whose vertices correspond to key tasks related to maturation, pathogen sensing and communication with lymphocytes. A mixture of continuum-like distributions and discrete clusters is found in other cell types, including bone marrow and differentiated intestinal crypt cells. This approach can be used to understand the geometry and biological tasks of a wide range of single-cell datasets. The present results suggest that the concept of cell type may be expanded. In addition to discreet clusters in gene-expression space, we suggest a new possibility: a continuum of states within a polyhedron, in which the

Neighboring Genes Show Correlated Evolution in Gene Expression.

PubMed

Ghanbarian, Avazeh T; Hurst, Laurence D

2015-07-01

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

Circadian enhancers coordinate multiple phases of rhythmic gene transcription in vivo.

PubMed

Fang, Bin; Everett, Logan J; Jager, Jennifer; Briggs, Erika; Armour, Sean M; Feng, Dan; Roy, Ankur; Gerhart-Hines, Zachary; Sun, Zheng; Lazar, Mitchell A

2014-11-20

Mammalian transcriptomes display complex circadian rhythms with multiple phases of gene expression that cannot be accounted for by current models of the molecular clock. We have determined the underlying mechanisms by measuring nascent RNA transcription around the clock in mouse liver. Unbiased examination of enhancer RNAs (eRNAs) that cluster in specific circadian phases identified functional enhancers driven by distinct transcription factors (TFs). We further identify on a global scale the components of the TF cistromes that function to orchestrate circadian gene expression. Integrated genomic analyses also revealed mechanisms by which a single circadian factor controls opposing transcriptional phases. These findings shed light on the diversity and specificity of TF function in the generation of multiple phases of circadian gene transcription in a mammalian organ.

Molecular Characteristics of High-Dose Melphalan Associated Oral Mucositis in Patients with Multiple Myeloma: A Gene Expression Study on Human Mucosa

PubMed Central

Bødker, Julie Støve; Christensen, Heidi Søgaard; Johansen, Preben; Nielsen, Søren; Christiansen, Ilse; Bergmann, Olav Jonas; Bøgsted, Martin; Dybkær, Karen; Vyberg, Mogens; Johnsen, Hans Erik

2017-01-01

Background Toxicity of the oral and gastrointestinal mucosa induced by high-dose melphalan is a clinical challenge with no documented prophylactic interventions or predictive tests. The aim of this study was to describe molecular changes in human oral mucosa and to identify biomarkers correlated with the grade of clinical mucositis. Methods and Findings Ten patients with multiple myeloma (MM) were included. For each patient, we acquired three buccal biopsies, one before, one at 2 days, and one at 20 days after high-dose melphalan administration. We also acquired buccal biopsies from 10 healthy individuals that served as controls. We analyzed the biopsies for global gene expression and performed an immunohistochemical analysis to determine HLA-DRB5 expression. We evaluated associations between clinical mucositis and gene expression profiles. Compared to gene expression levels before and 20 days after therapy, at two days after melphalan treatment, we found gene regulation in the p53 and TNF pathways (MDM2, INPPD5, TIGAR), which favored anti-apoptotic defense, and upregulation of immunoregulatory genes (TREM2, LAMP3) in mucosal dendritic cells. This upregulation was independent of clinical mucositis. HLA-DRB1 and HLA-DRB5 (surface receptors on dendritic cells) were expressed at low levels in all patients with MM, in the subgroup of patients with ulcerative mucositis (UM), and in controls; in contrast, the subgroup with low-grade mucositis (NM) displayed 5–6 fold increases in HLA-DRB1 and HLA-DRB5 expression in the first two biopsies, independent of melphalan treatment. Moreover, different splice variants of HLA-DRB1 were expressed in the UM and NM subgroups. Conclusions Our results revealed that, among patients with MM, immunoregulatory genes and genes involved in defense against apoptosis were affected immediately after melphalan administration, independent of the presence of clinical mucositis. Furthermore, our results suggested that the expression levels of HLA

Normal uniform mixture differential gene expression detection for cDNA microarrays

PubMed Central

Dean, Nema; Raftery, Adrian E

2005-01-01

Background One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the thousands of tests run make some of the more popular methods for doing this problematic. Results We propose a simple method, Normal Uniform Differential Gene Expression (NUDGE) detection for finding differentially expressed genes in cDNA microarrays. The method uses a simple univariate normal-uniform mixture model, in combination with new normalization methods for spread as well as mean that extend the lowess normalization of Dudoit, Yang, Callow and Speed (2002) [1]. It takes account of multiple testing, and gives probabilities of differential expression as part of its output. It can be applied to either single-slide or replicated experiments, and it is very fast. Three datasets are analyzed using NUDGE, and the results are compared to those given by other popular methods: unadjusted and Bonferroni-adjusted t tests, Significance Analysis of Microarrays (SAM), and Empirical Bayes for microarrays (EBarrays) with both Gamma-Gamma and Lognormal-Normal models. Conclusion The method gives a high probability of differential expression to genes known/suspected a priori to be differentially expressed and a low probability to the others. In terms of known false positives and false negatives, the method outperforms all multiple-replicate methods except for the Gamma-Gamma EBarrays method to which it offers comparable results with the added advantages of greater simplicity, speed, fewer assumptions and applicability to the single replicate case. An R package called nudge to implement the methods in this paper will be made available soon at . PMID:16011807

Multiple Multi-Copper Oxidase Gene Families in Basidiomycetes – What for?

PubMed Central

Kües, Ursula; Rühl, Martin

2011-01-01

Genome analyses revealed in various basidiomycetes the existence of multiple genes for blue multi-copper oxidases (MCOs). Whole genomes are now available from saprotrophs, white rot and brown rot species, plant and animal pathogens and ectomycorrhizal species. Total numbers (from 1 to 17) and types of mco genes differ between analyzed species with no easy to recognize connection of gene distribution to fungal life styles. Types of mco genes might be present in one and absent in another fungus. Distinct types of genes have been multiplied at speciation in different organisms. Phylogenetic analysis defined different subfamilies of laccases sensu stricto (specific to Agaricomycetes), classical Fe2+-oxidizing Fet3-like ferroxidases, potential ferroxidases/laccases exhibiting either one or both of these enzymatic functions, enzymes clustering with pigment MCOs and putative ascorbate oxidases. Biochemically best described are laccases sensu stricto due to their proposed roles in degradation of wood, straw and plant litter and due to the large interest in these enzymes in biotechnology. However, biological functions of laccases and other MCOs are generally little addressed. Functions in substrate degradation, symbiontic and pathogenic intercations, development, pigmentation and copper homeostasis have been put forward. Evidences for biological functions are in most instances rather circumstantial by correlations of expression. Multiple factors impede research on biological functions such as difficulties of defining suitable biological systems for molecular research, the broad and overlapping substrate spectrum multi-copper oxidases usually possess, the low existent knowledge on their natural substrates, difficulties imposed by low expression or expression of multiple enzymes, and difficulties in expressing enzymes heterologously. PMID:21966246

An analysis of gene expression in PTSD implicates genes involved in the glucocorticoid receptor pathway and neural responses to stress

PubMed Central

Logue, Mark W.; Smith, Alicia K.; Baldwin, Clinton; Wolf, Erika J.; Guffanti, Guia; Ratanatharathorn, Andrew; Stone, Annjanette; Schichman, Steven A.; Humphries, Donald; Binder, Elisabeth B.; Arloth, Janine; Menke, Andreas; Uddin, Monica; Wildman, Derek; Galea, Sandro; Aiello, Allison E.; Koenen, Karestan C.; Miller, Mark W.

2015-01-01

We examined the association between posttraumatic stress disorder (PTSD) and gene expression using whole blood samples from a cohort of trauma-exposed white non-Hispanic male veterans (115 cases and 28 controls). 10,264 probes of genes and gene transcripts were analyzed. We found 41 that were differentially expressed in PTSD cases versus controls (multiple-testing corrected p<0.05). The most significant was DSCAM, a neurological gene expressed widely in the developing brain and in the amygdala and hippocampus of the adult brain. We then examined the 41 differentially expressed genes in a meta-analysis using two replication cohorts and found significant associations with PTSD for 7 of the 41 (p<0.05), one of which (ATP6AP1L) survived multiple-testing correction. There was also broad evidence of overlap across the discovery and replication samples for the entire set of genes implicated in the discovery data based on the direction of effect and an enrichment of p<0.05 significant probes beyond what would be expected under the null. Finally, we found that the set of differentially expressed genes from the discovery sample was enriched for genes responsive to glucocorticoid signaling with most showing reduced expression in PTSD cases compared to controls. PMID:25867994

Multilevel regulation of gene expression by microRNAs.

PubMed

Makeyev, Eugene V; Maniatis, Tom

2008-03-28

MicroRNAs (miRNAs) are approximately 22-nucleotide-long noncoding RNAs that normally function by suppressing translation and destabilizing messenger RNAs bearing complementary target sequences. Some miRNAs are expressed in a cell- or tissue-specific manner and may contribute to the establishment and/or maintenance of cellular identity. Recent studies indicate that tissue-specific miRNAs may function at multiple hierarchical levels of gene regulatory networks, from targeting hundreds of effector genes incompatible with the differentiated state to controlling the levels of global regulators of transcription and alternative pre-mRNA splicing. This multilevel regulation may allow individual miRNAs to profoundly affect the gene expression program of differentiated cells.

Caste- and development-associated gene expression in a lower termite

PubMed Central

Scharf, Michael E; Wu-Scharf, Dancia; Pittendrigh, Barry R; Bennett, Gary W

2003-01-01

Background Social insects such as termites express dramatic polyphenism (the occurrence of multiple forms in a species on the basis of differential gene expression) both in association with caste differentiation and between castes after differentiation. We have used cDNA macroarrays to compare gene expression between polyphenic castes and intermediary developmental stages of the termite Reticulitermes flavipes. Results We identified differentially expressed genes from nine ontogenic categories. Quantitative PCR was used to quantify precise differences in gene expression between castes and between intermediary developmental stages. We found worker and nymph-biased expression of transcripts encoding termite and endosymbiont cellulases; presoldier-biased expression of transcripts encoding the storage/hormone-binding protein vitellogenin; and soldier-biased expression of gene transcripts encoding two transcription/translation factors, two signal transduction factors and four cytoskeletal/muscle proteins. The two transcription/translation factors showed significant homology to the bicaudal and bric-a-brac developmental genes of Drosophila. Conclusions Our results show differential expression of regulatory, structural and enzyme-coding genes in association with termite castes and their developmental precursor stages. They also provide the first glimpse into how insect endosymbiont cellulase gene expression can vary in association with the caste of a host. These findings shed light on molecular processes associated with termite biology, polyphenism, caste differentiation and development and highlight potentially interesting variations in developmental themes between termites, other insects, and higher animals. PMID:14519197

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

PubMed

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

2018-02-01

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

A high resolution atlas of gene expression in the domestic sheep (Ovis aries).

PubMed

Clark, Emily L; Bush, Stephen J; McCulloch, Mary E B; Farquhar, Iseabail L; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G; Wu, Chunlei; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C Bruce; Freeman, Tom C; Summers, Kim M; Archibald, Alan L; Hume, David A

2017-09-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

Partitioning of functional gene expression data using principal points.

PubMed

Kim, Jaehee; Kim, Haseong

2017-10-12

DNA microarrays offer motivation and hope for the simultaneous study of variations in multiple genes. Gene expression is a temporal process that allows variations in expression levels with a characterized gene function over a period of time. Temporal gene expression curves can be treated as functional data since they are considered as independent realizations of a stochastic process. This process requires appropriate models to identify patterns of gene functions. The partitioning of the functional data can find homogeneous subgroups of entities for the massive genes within the inherent biological networks. Therefor it can be a useful technique for the analysis of time-course gene expression data. We propose a new self-consistent partitioning method of functional coefficients for individual expression profiles based on the orthonormal basis system. A principal points based functional partitioning method is proposed for time-course gene expression data. The method explores the relationship between genes using Legendre coefficients as principal points to extract the features of gene functions. Our proposed method provides high connectivity in connectedness after clustering for simulated data and finds a significant subsets of genes with the increased connectivity. Our approach has comparative advantages that fewer coefficients are used from the functional data and self-consistency of principal points for partitioning. As real data applications, we are able to find partitioned genes through the gene expressions found in budding yeast data and Escherichia coli data. The proposed method benefitted from the use of principal points, dimension reduction, and choice of orthogonal basis system as well as provides appropriately connected genes in the resulting subsets. We illustrate our method by applying with each set of cell-cycle-regulated time-course yeast genes and E. coli genes. The proposed method is able to identify highly connected genes and to explore the complex

Methylomics of gene expression in human monocytes

PubMed Central

Liu, Yongmei; Ding, Jingzhong; Reynolds, Lindsay M.; Lohman, Kurt; Register, Thomas C.; De La Fuente, Alberto; Howard, Timothy D.; Hawkins, Greg A.; Cui, Wei; Morris, Jessica; Smith, Shelly G.; Barr, R. Graham; Kaufman, Joel D.; Burke, Gregory L.; Post, Wendy; Shea, Steven; Mccall, Charles E.; Siscovick, David; Jacobs, David R.; Tracy, Russell P.; Herrington, David M.; Hoeschele, Ina

2013-01-01

DNA methylation is one of several epigenetic mechanisms that contribute to the regulation of gene expression; however, the extent to which methylation of CpG dinucleotides correlates with gene expression at the genome-wide level is still largely unknown. Using purified primary monocytes from subjects in a large community-based cohort (n = 1264), we characterized methylation (>485 000 CpG sites) and mRNA expression (>48K transcripts) and carried out genome-wide association analyses of 8370 expression phenotypes. We identified 11 203 potential cis-acting CpG loci whose degree of methylation was associated with gene expression (eMS) at a false discovery rate threshold of 0.001. Most of the associations were consistent in effect size and direction of effect across sex and three ethnicities. Contrary to expectation, these eMS were not predominately enriched in promoter regions, or CpG islands, but rather in the 3′ UTR, gene bodies, CpG shores or ‘offshore’ sites, and both positive and negative correlations between methylation and expression were observed across all locations. eMS were enriched for regions predicted to be regulatory by ENCODE (Encyclopedia of DNA Elements) data in multiple cell types, particularly enhancers. One of the strongest association signals detected (P < 2.2 × 10−308) was a methylation probe (cg17005068) in the promoter/enhancer region of the glutathione S-transferase theta 1 gene (GSTT1, encoding the detoxification enzyme) with GSTT1 mRNA expression. Our study provides a detailed description of the epigenetic architecture in human monocytes and its relationship to gene expression. These data may help prioritize interrogation of biologically relevant methylation loci and provide new insights into the epigenetic basis of human health and diseases. PMID:23900078

Circadian Enhancers Coordinate Multiple Phases of Rhythmic Gene Transcription In Vivo

PubMed Central

Fang, Bin; Everett, Logan J.; Jager, Jennifer; Briggs, Erika; Armour, Sean M.; Feng, Dan; Roy, Ankur; Gerhart-Hines, Zachary; Sun, Zheng; Lazar, Mitchell A.

2014-01-01

SUMMARY Mammalian transcriptomes display complex circadian rhythms with multiple phases of gene expression that cannot be accounted for by current models of the molecular clock. We have determined the underlying mechanisms by measuring nascent RNA transcription around the clock in mouse liver. Unbiased examination of eRNAs that cluster in specific circadian phases identified functional enhancers driven by distinct transcription factors (TFs). We further identify on a global scale the components of the TF cistromes that function to orchestrate circadian gene expression. Integrated genomic analyses also revealed novel mechanisms by which a single circadian factor controls opposing transcriptional phases. These findings shed new light on the diversity and specificity of TF function in the generation of multiple phases of circadian gene transcription in a mammalian organ. PMID:25416951

Identifying a gene expression signature of cluster headache in blood

PubMed Central

Eising, Else; Pelzer, Nadine; Vijfhuizen, Lisanne S.; Vries, Boukje de; Ferrari, Michel D.; ‘t Hoen, Peter A. C.; Terwindt, Gisela M.; van den Maagdenberg, Arn M. J. M.

2017-01-01

Cluster headache is a relatively rare headache disorder, typically characterized by multiple daily, short-lasting attacks of excruciating, unilateral (peri-)orbital or temporal pain associated with autonomic symptoms and restlessness. To better understand the pathophysiology of cluster headache, we used RNA sequencing to identify differentially expressed genes and pathways in whole blood of patients with episodic (n = 19) or chronic (n = 20) cluster headache in comparison with headache-free controls (n = 20). Gene expression data were analysed by gene and by module of co-expressed genes with particular attention to previously implicated disease pathways including hypocretin dysregulation. Only moderate gene expression differences were identified and no associations were found with previously reported pathogenic mechanisms. At the level of functional gene sets, associations were observed for genes involved in several brain-related mechanisms such as GABA receptor function and voltage-gated channels. In addition, genes and modules of co-expressed genes showed a role for intracellular signalling cascades, mitochondria and inflammation. Although larger study samples may be required to identify the full range of involved pathways, these results indicate a role for mitochondria, intracellular signalling and inflammation in cluster headache. PMID:28074859

A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

Regulatory states in the developmental control of gene expression.

PubMed

Peter, Isabelle S

2017-09-01

A growing body of evidence shows that gene expression in multicellular organisms is controlled by the combinatorial function of multiple transcription factors. This indicates that not the individual transcription factors or signaling molecules, but the combination of expressed regulatory molecules, the regulatory state, should be viewed as the functional unit in gene regulation. Here, I discuss the concept of the regulatory state and its proposed role in the genome-wide control of gene expression. Recent analyses of regulatory gene expression in sea urchin embryos have been instrumental for solving the genomic control of cell fate specification in this system. Some of the approaches that were used to determine the expression of regulatory states during sea urchin embryogenesis are reviewed. Significant developmental changes in regulatory state expression leading to the distinct specification of cell fates are regulated by gene regulatory network circuits. How these regulatory state transitions are encoded in the genome is illuminated using the sea urchin endoderm-mesoderms cell fate decision circuit as an example. These observations highlight the importance of considering developmental gene regulation, and the function of individual transcription factors, in the context of regulatory states. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Gene expression in cerebral ischemia: a new approach for neuroprotection.

PubMed

Millán, Mónica; Arenillas, Juan

2006-01-01

Cerebral ischemia is one of the strongest stimuli for gene induction in the brain. Hundreds of genes have been found to be induced by brain ischemia. Many genes are involved in neurodestructive functions such as excitotoxicity, inflammatory response and neuronal apoptosis. However, cerebral ischemia is also a powerful reformatting and reprogramming stimulus for the brain through neuroprotective gene expression. Several genes may participate in both cellular responses. Thus, isolation of candidate genes for neuroprotection strategies and interpretation of expression changes have been proven difficult. Nevertheless, many studies are being carried out to improve the knowledge of the gene activation and protein expression following ischemic stroke, as well as in the development of new therapies that modify biochemical, molecular and genetic changes underlying cerebral ischemia. Owing to the complexity of the process involving numerous critical genes expressed differentially in time, space and concentration, ongoing therapeutic efforts should be based on multiple interventions at different levels. By modification of the acute gene expression induced by ischemia or the apoptotic gene program, gene therapy is a promising treatment but is still in a very experimental phase. Some hurdles will have to be overcome before these therapies can be introduced into human clinical stroke trials. Copyright 2006 S. Karger AG, Basel.

A gene expression system offering multiple levels of regulation: the Dual Drug Control (DDC) system.

PubMed

Sudomoina, Marina; Latypova, Ekaterina; Favorova, Olga O; Golemis, Erica A; Serebriiskii, Ilya G

2004-04-29

Whether for cell culture studies of protein function, construction of mouse models to enable in vivo analysis of disease epidemiology, or ultimately gene therapy of human diseases, a critical enabling step is the ability to achieve finely controlled regulation of gene expression. Previous efforts to achieve this goal have explored inducible drug regulation of gene expression, and construction of synthetic promoters based on two-hybrid paradigms, among others. In this report, we describe the combination of dimerizer-regulated two-hybrid and tetracycline regulatory elements in an ordered cascade, placing expression of endpoint reporters under the control of two distinct drugs. In this Dual Drug Control (DDC) system, a first plasmid expresses fusion proteins to DBD and AD, which interact only in the presence of a small molecule dimerizer; a second plasmid encodes a cassette transcriptionally responsive to the first DBD, directing expression of the Tet-OFF protein; and a third plasmid encodes a reporter gene transcriptionally responsive to binding by Tet-OFF. We evaluate the dynamic range and specificity of this system in comparison to other available systems. This study demonstrates the feasibility of combining two discrete drug-regulated expression systems in a temporally sequential cascade, without loss of dynamic range of signal induction. The efficient layering of control levels allowed by this combination of elements provides the potential for the generation of complex control circuitry that may advance ability to regulate gene expression in vivo.

A high resolution atlas of gene expression in the domestic sheep (Ovis aries)

PubMed Central

Farquhar, Iseabail L.; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G.; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C. Bruce; Freeman, Tom C.; Archibald, Alan L.; Hume, David A.

2017-01-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of ‘guilt by association’ was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages. PMID:28915238

Gene expression analysis of flax seed development

PubMed Central

2011-01-01

Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages) seed coats (globular and torpedo stages) and endosperm (pooled globular to torpedo stages) and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST) (GenBank accessions LIBEST_026995 to LIBEST_027011) were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152) had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid clones that comprise

Turning publicly available gene expression data into discoveries using gene set context analysis.

PubMed

Ji, Zhicheng; Vokes, Steven A; Dang, Chi V; Ji, Hongkai

2016-01-08

Gene Set Context Analysis (GSCA) is an open source software package to help researchers use massive amounts of publicly available gene expression data (PED) to make discoveries. Users can interactively visualize and explore gene and gene set activities in 25,000+ consistently normalized human and mouse gene expression samples representing diverse biological contexts (e.g. different cells, tissues and disease types, etc.). By providing one or multiple genes or gene sets as input and specifying a gene set activity pattern of interest, users can query the expression compendium to systematically identify biological contexts associated with the specified gene set activity pattern. In this way, researchers with new gene sets from their own experiments may discover previously unknown contexts of gene set functions and hence increase the value of their experiments. GSCA has a graphical user interface (GUI). The GUI makes the analysis convenient and customizable. Analysis results can be conveniently exported as publication quality figures and tables. GSCA is available at https://github.com/zji90/GSCA. This software significantly lowers the bar for biomedical investigators to use PED in their daily research for generating and screening hypotheses, which was previously difficult because of the complexity, heterogeneity and size of the data. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

PubMed

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

2014-07-07

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

Selection and validation of reference genes for gene expression analysis in apomictic and sexual Cenchrus ciliaris

PubMed Central

2013-01-01

Background Apomixis is a naturally occurring asexual mode of seed reproduction resulting in offspring genetically identical to the maternal plant. Identifying differential gene expression patterns between apomictic and sexual plants is valuable to help deconstruct the trait. Quantitative RT-PCR (qRT-PCR) is a popular method for analyzing gene expression. Normalizing gene expression data using proper reference genes which show stable expression under investigated conditions is critical in qRT-PCR analysis. We used qRT-PCR to validate expression and stability of six potential reference genes (EF1alpha, EIF4A, UBCE, GAPDH, ACT2 and TUBA) in vegetative and reproductive tissues of B-2S and B-12-9 accessions of C. ciliaris. Findings Among tissue types evaluated, EF1alpha showed the highest level of expression while TUBA showed the lowest. When all tissue types were evaluated and compared between genotypes, EIF4A was the most stable reference gene. Gene expression stability for specific ovary stages of B-2S and B-12-9 was also determined. Except for TUBA, all other tested reference genes could be used for any stage-specific ovary tissue normalization, irrespective of the mode of reproduction. Conclusion Our gene expression stability assay using six reference genes, in sexual and apomictic accessions of C. ciliaris, suggests that EIF4A is the most stable gene across all tissue types analyzed. All other tested reference genes, with the exception of TUBA, could be used for gene expression comparison studies between sexual and apomictic ovaries over multiple developmental stages. This reference gene validation data in C. ciliaris will serve as an important base for future apomixis-related transcriptome data validation. PMID:24083672

Gene Architectures that Minimize Cost of Gene Expression.

PubMed

Frumkin, Idan; Schirman, Dvir; Rotman, Aviv; Li, Fangfei; Zahavi, Liron; Mordret, Ernest; Asraf, Omer; Wu, Song; Levy, Sasha F; Pilpel, Yitzhak

2017-01-05

Gene expression burdens cells by consuming resources and energy. While numerous studies have investigated regulation of expression level, little is known about gene design elements that govern expression costs. Here, we ask how cells minimize production costs while maintaining a given protein expression level and whether there are gene architectures that optimize this process. We measured fitness of ∼14,000 E. coli strains, each expressing a reporter gene with a unique 5' architecture. By comparing cost-effective and ineffective architectures, we found that cost per protein molecule could be minimized by lowering transcription levels, regulating translation speeds, and utilizing amino acids that are cheap to synthesize and that are less hydrophobic. We then examined natural E. coli genes and found that highly expressed genes have evolved more forcefully to minimize costs associated with their expression. Our study thus elucidates gene design elements that improve the economy of protein expression in natural and heterologous systems. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of Gene Expression Profiles of Soft Tissue Sarcoma Using a Combination of Knowledge-Based Filtering with Integration of Multiple Statistics

PubMed Central

Doi, Ayano; Ichinohe, Risa; Ikuyo, Yoriko; Takahashi, Teruyoshi; Marui, Shigetaka; Yasuhara, Koji; Nakamura, Tetsuro; Sugita, Shintaro; Sakamoto, Hiromi; Yoshida, Teruhiko; Hasegawa, Tadashi

2014-01-01

The diagnosis and treatment of soft tissue sarcomas (STS) have been difficult. Of the diverse histological subtypes, undifferentiated pleomorphic sarcoma (UPS) is particularly difficult to diagnose accurately, and its classification per se is still controversial. Recent advances in genomic technologies provide an excellent way to address such problems. However, it is often difficult, if not impossible, to identify definitive disease-associated genes using genome-wide analysis alone, primarily because of multiple testing problems. In the present study, we analyzed microarray data from 88 STS patients using a combination method that used knowledge-based filtering and a simulation based on the integration of multiple statistics to reduce multiple testing problems. We identified 25 genes, including hypoxia-related genes (e.g., MIF, SCD1, P4HA1, ENO1, and STAT1) and cell cycle- and DNA repair-related genes (e.g., TACC3, PRDX1, PRKDC, and H2AFY). These genes showed significant differential expression among histological subtypes, including UPS, and showed associations with overall survival. STAT1 showed a strong association with overall survival in UPS patients (logrank p = 1.84×10−6 and adjusted p value 2.99×10−3 after the permutation test). According to the literature, the 25 genes selected are useful not only as markers of differential diagnosis but also as prognostic/predictive markers and/or therapeutic targets for STS. Our combination method can identify genes that are potential prognostic/predictive factors and/or therapeutic targets in STS and possibly in other cancers. These disease-associated genes deserve further preclinical and clinical validation. PMID:25188299

Gene Expression Profiling Predicts the Development of Oral Cancer

PubMed Central

Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

2011-01-01

Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635

Meta-analysis of cancer gene expression signatures reveals new cancer genes, SAGE tags and tumor associated regions of co-regulation

PubMed Central

Kavak, Erşen; Ünlü, Mustafa; Nistér, Monica; Koman, Ahmet

2010-01-01

Cancer is among the major causes of human death and its mechanism(s) are not fully understood. We applied a novel meta-analysis approach to multiple sets of merged serial analysis of gene expression and microarray cancer data in order to analyze transcriptome alterations in human cancer. Our methodology, which we denote ‘COgnate Gene Expression patterNing in tumours’ (COGENT), unmasked numerous genes that were differentially expressed in multiple cancers. COGENT detected well-known tumor-associated (TA) genes such as TP53, EGFR and VEGF, as well as many multi-cancer, but not-yet-tumor-associated genes. In addition, we identified 81 co-regulated regions on the human genome (RIDGEs) by using expression data from all cancers. Some RIDGEs (28%) consist of paralog genes while another subset (30%) are specifically dysregulated in tumors but not in normal tissues. Furthermore, a significant number of RIDGEs are associated with GC-rich regions on the genome. All assembled data is freely available online (www.oncoreveal.org) as a tool implementing COGENT analysis of multi-cancer genes and RIDGEs. These findings engender a deeper understanding of cancer biology by demonstrating the existence of a pool of under-studied multi-cancer genes and by highlighting the cancer-specificity of some TA-RIDGEs. PMID:20621981

Identification of diverse nerve growth factor-regulated genes by serial analysis of gene expression (SAGE) profiling

PubMed Central

Angelastro, James M.; Klimaschewski, Lars; Tang, Song; Vitolo, Ottavio V.; Weissman, Tamily A.; Donlin, Laura T.; Shelanski, Michael L.; Greene, Lloyd A.

2000-01-01

Neurotrophic factors such as nerve growth factor (NGF) promote a wide variety of responses in neurons, including differentiation, survival, plasticity, and repair. Such actions often require changes in gene expression. To identify the regulated genes and thereby to more fully understand the NGF mechanism, we carried out serial analysis of gene expression (SAGE) profiling of transcripts derived from rat PC12 cells before and after NGF-promoted neuronal differentiation. Multiple criteria supported the reliability of the profile. Approximately 157,000 SAGE tags were analyzed, representing at least 21,000 unique transcripts. Of these, nearly 800 were regulated by 6-fold or more in response to NGF. Approximately 150 of the regulated transcripts have been matched to named genes, the majority of which were not previously known to be NGF-responsive. Functional categorization of the regulated genes provides insight into the complex, integrated mechanism by which NGF promotes its multiple actions. It is anticipated that as genomic sequence information accrues the data derived here will continue to provide information about neurotrophic factor mechanisms. PMID:10984536

Maternal residential air pollution and placental imprinted gene expression.

PubMed

Kingsley, Samantha L; Deyssenroth, Maya A; Kelsey, Karl T; Awad, Yara Abu; Kloog, Itai; Schwartz, Joel D; Lambertini, Luca; Chen, Jia; Marsit, Carmen J; Wellenius, Gregory A

2017-11-01

Maternal exposure to air pollution is associated with reduced fetal growth, but its relationship with expression of placental imprinted genes (important regulators of fetal growth) has not yet been studied. To examine relationships between maternal residential air pollution and expression of placental imprinted genes in the Rhode Island Child Health Study (RICHS). Women-infant pairs were enrolled following delivery between 2009 and 2013. We geocoded maternal residential addresses at delivery, estimated daily levels of fine particulate matter (PM 2.5 ; n=355) and black carbon (BC; n=336) using spatial-temporal models, and estimated residential distance to nearest major roadway (n=355). Using linear regression models we investigated the associations between each exposure metric and expression of nine candidate genes previously associated with infant birthweight in RICHS, with secondary analyses of a panel of 108 imprinted genes expressed in the placenta. We also explored effect measure modification by infant sex. PM 2.5 and BC were associated with altered expression for seven and one candidate genes, respectively, previously linked with birthweight in this cohort. Adjusting for multiple comparisons, we found that PM 2.5 and BC were associated with changes in expression of 41 and 12 of 108 placental imprinted genes, respectively. Infant sex modified the association between PM 2.5 and expression of CHD7 and between proximity to major roadways and expression of ZDBF2. We found that maternal exposure to residential PM 2.5 and BC was associated with changes in placental imprinted gene expression, which suggests a plausible line of investigation of how air pollution affects fetal growth and development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Gene Expression Measurement Module (GEMM) - a fully automated, miniaturized instrument for measuring gene expression in space

NASA Astrophysics Data System (ADS)

Karouia, Fathi; Ricco, Antonio; Pohorille, Andrew; Peyvan, Kianoosh

2012-07-01

The capability to measure gene expression on board spacecrafts opens the doors to a large number of experiments on the influence of space environment on biological systems that will profoundly impact our ability to conduct safe and effective space travel, and might also shed light on terrestrial physiology or biological function and human disease and aging processes. Measurements of gene expression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, determine metabolic basis of microbial pathogenicity and drug resistance, test our ability to sustain and grow in space organisms that can be used for life support and in situ resource utilization during long-duration space exploration, and monitor both the spacecraft environment and crew health. These and other applications hold significant potential for discoveries in space biology, biotechnology and medicine. Accordingly, supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measuring microbial expression of thousands of genes from multiple samples. The instrument will be capable of (1) lysing bacterial cell walls, (2) extracting and purifying RNA released from cells, (3) hybridizing it on a microarray and (4) providing electrochemical readout, all in a microfluidics cartridge. The prototype under development is suitable for deployment on nanosatellite platforms developed by the NASA Small Spacecraft Office. The first target application is to cultivate and measure gene expression of the photosynthetic bacterium Synechococcus elongatus, i.e. a cyanobacterium known to exhibit remarkable metabolic diversity and resilience to adverse conditions

Programming gene expression with combinatorial promoters

PubMed Central

Cox, Robert Sidney; Surette, Michael G; Elowitz, Michael B

2007-01-01

Promoters control the expression of genes in response to one or more transcription factors (TFs). The architecture of a promoter is the arrangement and type of binding sites within it. To understand natural genetic circuits and to design promoters for synthetic biology, it is essential to understand the relationship between promoter function and architecture. We constructed a combinatorial library of random promoter architectures. We characterized 288 promoters in Escherichia coli, each containing up to three inputs from four different TFs. The library design allowed for multiple −10 and −35 boxes, and we observed varied promoter strength over five decades. To further analyze the functional repertoire, we defined a representation of promoter function in terms of regulatory range, logic type, and symmetry. Using these results, we identified heuristic rules for programming gene expression with combinatorial promoters. PMID:18004278

Gene expression allelic imbalance in ovine brown adipose tissue impacts energy homeostasis

PubMed Central

Ghazanfar, Shila; Vuocolo, Tony; Morrison, Janna L.; Nicholas, Lisa M.; McMillen, Isabella C.; Yang, Jean Y. H.; Buckley, Michael J.

2017-01-01

Heritable trait variation within a population of organisms is largely governed by DNA variations that impact gene transcription and protein function. Identifying genetic variants that affect complex functional traits is a primary aim of population genetics studies, especially in the context of human disease and agricultural production traits. The identification of alleles directly altering mRNA expression and thereby biological function is challenging due to difficulty in isolating direct effects of cis-acting genetic variations from indirect trans-acting genetic effects. Allele specific gene expression or allelic imbalance in gene expression (AI) occurring at heterozygous loci provides an opportunity to identify genes directly impacted by cis-acting genetic variants as indirect trans-acting effects equally impact the expression of both alleles. However, the identification of genes showing AI in the context of the expression of all genes remains a challenge due to a variety of technical and statistical issues. The current study focuses on the discovery of genes showing AI using single nucleotide polymorphisms as allelic reporters. By developing a computational and statistical process that addressed multiple analytical challenges, we ranked 5,809 genes for evidence of AI using RNA-Seq data derived from brown adipose tissue samples from a cohort of late gestation fetal lambs and then identified a conservative subgroup of 1,293 genes. Thus, AI was extensive, representing approximately 25% of the tested genes. Genes associated with AI were enriched for multiple Gene Ontology (GO) terms relating to lipid metabolism, mitochondrial function and the extracellular matrix. These functions suggest that cis-acting genetic variations causing AI in the population are preferentially impacting genes involved in energy homeostasis and tissue remodelling. These functions may contribute to production traits likely to be under genetic selection in the population. PMID:28665992

Pediatric acute myeloid leukemia with NPM1 mutations is characterized by a gene expression profile with dysregulated HOX gene expression distinct from MLL-rearranged leukemias.

PubMed

Mullighan, C G; Kennedy, A; Zhou, X; Radtke, I; Phillips, L A; Shurtleff, S A; Downing, J R

2007-09-01

Somatic mutations in nucleophosmin (NPM1) occur in approximately 35% of adult acute myeloid leukemia (AML). To assess the frequency of NPM1 mutations in pediatric AML, we sequenced NPM1 in the diagnostic blasts from 93 pediatric AML patients. Six cases harbored NPM1 mutations, with each case lacking common cytogenetic abnormalities. To explore the phenotype of the AMLs with NPM1 mutations, gene expression profiles were obtained using Affymetrix U133A microarrays. NPM1 mutations were associated with increased expression of multiple homeobox genes including HOXA9, A10, B2, B6 and MEIS1. As dysregulated homeobox gene expression is also a feature of MLL-rearranged leukemia, the gene expression signatures of NPM1-mutated and MLL-rearranged leukemias were compared. Significant differences were identified between these leukemia subtypes including the expression of different HOX genes, with NPM1-mutated AML showing higher levels of expression of HOXB2, B3, B6 and D4. These results confirm recent reports of perturbed HOX expression in NPM1-mutated adult AML, and provide the first evidence that the NPM1-mutated signature is distinct from MLL-rearranged AML. These findings suggest that mutated NPM1 leads to dysregulated HOX expression via a different mechanism than MLL rearrangement.

Msn2 Coordinates a Stoichiometric Gene Expression Program

PubMed Central

Stewart-Ornstein, Jacob; Nelson, Christopher; DeRisi, Joe; Weissman, Jonathan S.; El-Samad, Hana

2014-01-01

Summary Background Many cellular processes operate in an “analog” regime in which the magnitude of the response is precisely tailored to the intensity of the stimulus. In order to maintain the coherence of such responses, the cell must provide for proportional expression of multiple target genes across a wide dynamic range of induction states. Our understanding of the strategies used to achieve graded gene regulation is limited. Results In this work, we document a relationship between stress responsive gene expression and the transcription factor Msn2 that is graded over a large range of Msn2 cocnentrations. We use computational modeling, in vivo, and in vitro analysis to dissect the roots of this relationship. Our studies reveal a simple and general strategy based on non-cooperative low-affinity interactions between Msn2 and its cognate binding sites, as well as competition over a large number of Msn2 binding sites in the genome relative to the number of Msn2 molecules. Conclusions In addition to enabling precise tuning of gene expression to the state of the environment, this strategy ensures co-linear activation of target genes, allowing for stoichiometric expression of large groups of genes without extensive promoter tuning. Furthermore, such a strategy enables precise modulation of the activity of any given promoter by addition of binding sites without altering the qualitative relationship between different genes in a regulon. This feature renders a given regulon highly ‘evolvable’. PMID:24210615

Nipbl and mediator cooperatively regulate gene expression to control limb development.

PubMed

Muto, Akihiko; Ikeda, Shingo; Lopez-Burks, Martha E; Kikuchi, Yutaka; Calof, Anne L; Lander, Arthur D; Schilling, Thomas F

2014-09-01

Haploinsufficiency for Nipbl, a cohesin loading protein, causes Cornelia de Lange Syndrome (CdLS), the most common "cohesinopathy". It has been proposed that the effects of Nipbl-haploinsufficiency result from disruption of long-range communication between DNA elements. Here we use zebrafish and mouse models of CdLS to examine how transcriptional changes caused by Nipbl deficiency give rise to limb defects, a common condition in individuals with CdLS. In the zebrafish pectoral fin (forelimb), knockdown of Nipbl expression led to size reductions and patterning defects that were preceded by dysregulated expression of key early limb development genes, including fgfs, shha, hand2 and multiple hox genes. In limb buds of Nipbl-haploinsufficient mice, transcriptome analysis revealed many similar gene expression changes, as well as altered expression of additional classes of genes that play roles in limb development. In both species, the pattern of dysregulation of hox-gene expression depended on genomic location within the Hox clusters. In view of studies suggesting that Nipbl colocalizes with the mediator complex, which facilitates enhancer-promoter communication, we also examined zebrafish deficient for the Med12 Mediator subunit, and found they resembled Nipbl-deficient fish in both morphology and gene expression. Moreover, combined partial reduction of both Nipbl and Med12 had a strongly synergistic effect, consistent with both molecules acting in a common pathway. In addition, three-dimensional fluorescent in situ hybridization revealed that Nipbl and Med12 are required to bring regions containing long-range enhancers into close proximity with the zebrafish hoxda cluster. These data demonstrate a crucial role for Nipbl in limb development, and support the view that its actions on multiple gene pathways result from its influence, together with Mediator, on regulation of long-range chromosomal interactions.

Gene expression analysis of colorectal cancer by bioinformatics strategy.

PubMed

Cui, Meng; Yuan, Junhua; Li, Jun; Sun, Bing; Li, Tao; Li, Yuantao; Wu, Guoliang

2014-10-01

We used bioinformatics technology to analyze gene expression profiles involved in colorectal cancer tissue samples and healthy controls. In this paper, we downloaded the gene expression profile GSE4107 from Gene Expression Omnibus (GEO) database, in which a total of 22 chips were available, including normal colonic mucosa tissue from normal healthy donors (n=10), colorectal cancer tissue samples from colorectal patients (n=33). To further understand the biological functions of the screened DGEs, the KEGG pathway enrichment analysis were conducted. Then we built a transcriptome network to study differentially co-expressed links. A total of 3151 DEGs of CRC were selected. Besides, total 164 DCGs (Differentially Coexpressed Gene, DCG) and 29279 DCLs (Differentially Co-expressed Link, DCL) were obtained. Furthermore, the significantly enriched KEGG pathways were Endocytosis, Calcium signaling pathway, Vascular smooth muscle contraction, Linoleic acid metabolism, Arginine and proline metabolism, Inositol phosphate metabolism and MAPK signaling pathway. Our results show that the generation of CRC involves multiple genes, TFs and pathways. Several signal and immune pathways are linked to CRC and give us more clues in the process of CRC. Hence, our work would pave ways for novel diagnosis of CRC, and provided theoretical guidance into cancer therapy.

Gene Expression Profiling in Fish Toxicology: A Review.

PubMed

Kumar, Girish; Denslow, Nancy D

In this review, we present an overview of transcriptomic responses to chemical exposures in a variety of fish species. We have discussed the use of several molecular approaches such as northern blotting, differential display reverse transcription-polymerase chain reaction (DDRT-PCR), suppression subtractive hybridization (SSH), real time quantitative PCR (RT-qPCR), microarrays, and next-generation sequencing (NGS) for measuring gene expression. These techniques have been mainly used to measure the toxic effects of single compounds or simple mixtures in laboratory conditions. In addition, only few studies have been conducted to examine the biological significance of differentially expressed gene sets following chemical exposure. Therefore, future studies should focus more under field conditions using a multidisciplinary approach (genomics, proteomics and metabolomics) to understand the synergetic effects of multiple environmental stressors and to determine the functional significance of differentially expressed genes. Nevertheless, recent developments in NGS technologies and decreasing costs of sequencing holds the promise to uncover the complexity of anthropogenic impacts and biological effects in wild fish populations.

Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes.

PubMed

Paraboschi, Elvezia Maria; Cardamone, Giulia; Rimoldi, Valeria; Gemmati, Donato; Spreafico, Marta; Duga, Stefano; Soldà, Giulia; Asselta, Rosanna

2015-09-30

Abnormalities in RNA metabolism and alternative splicing (AS) are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS) and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls), followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p=0.0015) by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.

Hox gene expression during postlarval development of the polychaete Alitta virens.

PubMed

Bakalenko, Nadezhda I; Novikova, Elena L; Nesterenko, Alexander Y; Kulakova, Milana A

2013-05-01

Hox genes are the family of transcription factors that play a key role in the patterning of the anterior-posterior axis of all bilaterian animals. These genes display clustered organization and colinear expression. Expression boundaries of individual Hox genes usually correspond with morphological boundaries of the body. Previously, we studied Hox gene expression during larval development of the polychaete Alitta virens (formerly Nereis virens) and discovered that Hox genes are expressed in nereid larva according to the spatial colinearity principle. Adult Alitta virens consist of multiple morphologically similar segments, which are formed sequentially in the growth zone. Since the worm grows for most of its life, postlarval segments constantly change their position along the anterior-posterior axis. We studied the expression dynamics of the Hox cluster during postlarval development of the nereid Alitta virens and found that 8 out of 11 Hox genes are transcribed as wide gene-specific gradients in the ventral nerve cord, ectoderm, and mesoderm. The expression domains constantly shift in accordance with the changing proportions of the growing worm, so expression domains of most Hox genes do not have stable anterior or/and posterior boundaries.In the course of our study, we revealed long antisense RNA (asRNA) for some Hox genes. Expression patterns of two of these genes were analyzed using whole-mount in-situ hybridization. This is the first discovery of antisense RNA for Hox genes in Lophotrochozoa. Hox gene expression in juvenile A. virens differs significantly from Hox gene expression patterns both in A. virens larva and in other Bilateria.We suppose that the postlarval function of the Hox genes in this polychaete is to establish and maintain positional coordinates in a constantly growing body, as opposed to creating morphological difference between segments.

Tumor Cell Gene Expression Changes Following Short-term In vivo Exposure to Single Agent Chemotherapeutics are Related to Survival in Multiple Myeloma

PubMed Central

Burington, Bart; Barlogie, Bart; Zhan, Fenghuang; Crowley, John; Shaughnessy, John D.

2013-01-01

Changes in global gene expression patterns in tumor cells following in vivo therapy may vary by treatment and provide added or synergistic prognostic power over pretherapy gene expression profiles (GEP). This molecular readout of drug-cell interaction may also point to mechanisms of action/resistance. In newly diagnosed patients with multiple myeloma (MM), microarray data were obtained on tumor cells prior to and 48 hours after in vivo treatment using dexamethasone (n = 45) or thalidomide (n = 42); in the case of relapsed MM, microarray data were obtained prior to (n = 36) and after (n = 19) lenalidomide administration. Dexamethasone and thalidomide induced both common and unique GEP changes in tumor cells. Combined baseline and 48-hour changes in GEP in a subset of genes, many related to oxidative stress and cytoskeletal dynamics, were predictive of outcome in newly diagnosed MM patients receiving tandem transplants. Thalidomide-altered genes also changed following lenalidomide exposure and predicted event-free and overall survival in relapsed patients receiving lenalidomide as a single agent. Combined with baseline molecular features, changes in GEP following short-term single-agent exposure may help guide treatment decisions for patients with MM. Genes whose drug-altered expression were found to be related to survival may point to molecular switches related to response and/or resistance to different classes of drugs. PMID:18676754

Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules.

PubMed

Curtis, Ross E; Kim, Seyoung; Woolford, John L; Xu, Wenjie; Xing, Eric P

2013-03-21

Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL data via pairwise statistical significance tests or linear regression does not leverage the availability of the structural information of the transcriptome, such as presence of gene networks that reveal correlation and potentially regulatory relationships among the study genes. We employ a new eQTL mapping algorithm, GFlasso, which we have previously developed for sparse structured regression, to reanalyze a genome-wide yeast dataset. GFlasso fully takes into account the dependencies among expression traits to suppress false positives and to enhance the signal/noise ratio. Thus, GFlasso leverages the gene-interaction network to discover the pleiotropic effects of genetic loci that perturb the expression level of multiple (rather than individual) genes, which enables us to gain more power in detecting previously neglected signals that are marginally weak but pleiotropically significant. While eQTL hotspots in yeast have been reported previously as genomic regions controlling multiple genes, our analysis reveals additional novel eQTL hotspots and, more interestingly, uncovers groups of multiple contributing eQTL hotspots that affect the expression level of functional gene modules. To our knowledge, our study is the first to report this type of gene regulation stemming from multiple eQTL hotspots. Additionally, we report the results from in-depth bioinformatics analysis for three groups of these eQTL hotspots: ribosome biogenesis, telomere silencing, and retrotransposon biology. We suggest candidate regulators for the functional gene modules that map to each group of hotspots. Not only do we find that many of these candidate regulators contain mutations in the promoter and coding regions of the genes, in the case of the Ribi group

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

PubMed

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

2011-05-01

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

Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data.

PubMed

Ezer, Daphne; Moignard, Victoria; Göttgens, Berthold; Adryan, Boris

2016-08-01

Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete pipeline for the analysis of single cell qPCR data that uses the mathematics behind bursty expression to develop more accurate and robust algorithms for analyzing the origin of heterogeneity in experimental samples, specifically an algorithm for clustering cells by their bursting behavior (Simulated Annealing for Bursty Expression Clustering, SABEC) and a statistical tool for comparing the kinetic parameters of bursty expression across populations of cells (Estimation of Parameter changes in Kinetics, EPiK). We applied these methods to hematopoiesis, including a new single cell dataset in which transcription factors (TFs) involved in the earliest branchpoint of blood differentiation were individually up- and down-regulated. We could identify two unique sub-populations within a seemingly homogenous group of hematopoietic stem cells. In addition, we could predict regulatory mechanisms controlling the expression levels of eighteen key hematopoietic transcription factors throughout differentiation. Detailed information about gene regulatory mechanisms can therefore be obtained simply from high throughput single cell gene expression data, which should be widely applicable given the rapid expansion of single cell genomics.

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

PubMed Central

Peng, Cheng; Shiu, Shin-Han

2016-01-01

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

Changes in skeletal muscle gene expression consequent to altered weight bearing

NASA Technical Reports Server (NTRS)

Booth, F. W.; Kirby, C. R.

1992-01-01

Skeletal muscle is a dynamic organ that adapts to alterations in weight bearing. This brief review examines changes in muscle gene expression resulting from the removal of weight bearing by hindlimb suspension and from increased weight bearing due to eccentric exercise. Acute (less than or equal to 2 days) non-weight bearing of adult rat soleus muscle alters only the translational control of muscle gene expression, while chronic (greater than or equal to 7 days) removal of weight bearing appears to influence pretranslational, translational, and posttranslational mechanisms of control. Acute and chronic eccentric exercise are associated with alterations of translational and posttranslational control, while chronic eccentric training also alters the pretranslational control of muscle gene expression. Thus alterations in weight bearing influence multiple sites of gene regulation.

Annotation of gene function in citrus using gene expression information and co-expression networks

PubMed Central

2014-01-01

Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related biological processes may exhibit similar expression patterns across diverse sets of experimental conditions. While bioinformatics resources such as GCN analysis are widely available for efficient gene function prediction in model plant species including Arabidopsis, soybean and rice, in citrus these tools are not yet developed. Results We have constructed a comprehensive GCN for citrus inferred from 297 publicly available Affymetrix Genechip Citrus Genome microarray datasets, providing gene co-expression relationships at a genome-wide scale (33,000 transcripts). The comprehensive citrus GCN consists of a global GCN (condition-independent) and four condition-dependent GCNs that survey the sweet orange species only, all citrus fruit tissues, all citrus leaf tissues, or stress-exposed plants. All of these GCNs are clustered using genome-wide, gene-centric (guide) and graph clustering algorithms for flexibility of gene function prediction. For each putative cluster, gene ontology (GO) enrichment and gene expression specificity analyses were performed to enhance gene function, expression and regulation pattern prediction. The guide-gene approach was used to infer novel roles of genes involved in disease susceptibility and vitamin C metabolism, and graph-clustering approaches were used to investigate isoprenoid/phenylpropanoid metabolism in citrus peel, and citric acid catabolism via the GABA shunt in citrus fruit. Conclusions Integration of citrus gene co-expression networks

Developmental expression of "germline"- and "sex determination"-related genes in the ctenophore Mnemiopsis leidyi.

PubMed

Reitzel, Adam M; Pang, Kevin; Martindale, Mark Q

2016-01-01

An essential developmental pathway in sexually reproducing animals is the specification of germ cells and the differentiation of mature gametes, sperm and oocytes. The "germline" genes vasa, nanos and piwi are commonly identified in primordial germ cells, suggesting a molecular signature for the germline throughout animals. However, these genes are also expressed in a diverse set of somatic stem cells throughout the animal kingdom leaving open significant questions for whether they are required for germline specification. Similarly, members of the Dmrt gene family are essential components regulating sex determination and differentiation in bilaterian animals, but the functions of these transcription factors, including potential roles in sex determination, in early diverging animals remain unknown. The phylogenetic position of ctenophores and the genome sequence of the lobate Mnemiopsis leidyi motivated us to determine the compliment of these gene families in this species and determine expression patterns during development. Our phylogenetic analyses of the vasa, piwi and nanos gene families show that Mnemiopsis has multiple genes in each family with multiple lineage-specific paralogs. Expression domains of Mnemiopsis nanos, vasa and piwi, during embryogenesis from fertilization to the cydippid stage, were diverse, with little overlapping expression and no or little expression in what we think are the germ cells or gametogenic regions. piwi paralogs in Mnemiopsis had distinct expression domains in the ectoderm during development. We observed overlapping expression domains in the apical organ and tentacle apparatus of the cydippid for a subset of "germline genes," which are areas of high cell proliferation, suggesting that these genes are involved with "stem cell" specification and maintenance. Similarly, the five Dmrt genes show diverse non-overlapping expression domains, with no clear evidence for expression in future gametogenic regions of the adult. We also

Multi-targeted priming for genome-wide gene expression assays.

PubMed

Adomas, Aleksandra B; Lopez-Giraldez, Francesc; Clark, Travis A; Wang, Zheng; Townsend, Jeffrey P

2010-08-17

Complementary approaches to assaying global gene expression are needed to assess gene expression in regions that are poorly assayed by current methodologies. A key component of nearly all gene expression assays is the reverse transcription of transcribed sequences that has traditionally been performed by priming the poly-A tails on many of the transcribed genes in eukaryotes with oligo-dT, or by priming RNA indiscriminately with random hexamers. We designed an algorithm to find common sequence motifs that were present within most protein-coding genes of Saccharomyces cerevisiae and of Neurospora crassa, but that were not present within their ribosomal RNA or transfer RNA genes. We then experimentally tested whether degenerately priming these motifs with multi-targeted primers improved the accuracy and completeness of transcriptomic assays. We discovered two multi-targeted primers that would prime a preponderance of genes in the genomes of Saccharomyces cerevisiae and Neurospora crassa while avoiding priming ribosomal RNA or transfer RNA. Examining the response of Saccharomyces cerevisiae to nitrogen deficiency and profiling Neurospora crassa early sexual development, we demonstrated that using multi-targeted primers in reverse transcription led to superior performance of microarray profiling and next-generation RNA tag sequencing. Priming with multi-targeted primers in addition to oligo-dT resulted in higher sensitivity, a larger number of well-measured genes and greater power to detect differences in gene expression. Our results provide the most complete and detailed expression profiles of the yeast nitrogen starvation response and N. crassa early sexual development to date. Furthermore, our multi-targeting priming methodology for genome-wide gene expression assays provides selective targeting of multiple sequences and counter-selection against undesirable sequences, facilitating a more complete and precise assay of the transcribed sequences within the genome.

Genome-Level Longitudinal Expression of Signaling Pathways and Gene Networks in Pediatric Septic Shock

PubMed Central

Shanley, Thomas P; Cvijanovich, Natalie; Lin, Richard; Allen, Geoffrey L; Thomas, Neal J; Doctor, Allan; Kalyanaraman, Meena; Tofil, Nancy M; Penfil, Scott; Monaco, Marie; Odoms, Kelli; Barnes, Michael; Sakthivel, Bhuvaneswari; Aronow, Bruce J; Wong, Hector R

2007-01-01

We have conducted longitudinal studies focused on the expression profiles of signaling pathways and gene networks in children with septic shock. Genome-level expression profiles were generated from whole blood-derived RNA of children with septic shock (n = 30) corresponding to day one and day three of septic shock, respectively. Based on sequential statistical and expression filters, day one and day three of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to controls (n = 15). Venn analysis demonstrated 239 unique genes in the day one dataset, 598 unique genes in the day three dataset, and 1,906 genes common to both datasets. Functional analyses demonstrated time-dependent, differential regulation of genes involved in multiple signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biology were persistently downregulated on both day one and day three. Further analyses demonstrated large scale, persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock subjected to longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses. PMID:17932561

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

PubMed

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

2016-09-01

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

Positive Selection Underlies Faster-Z Evolution of Gene Expression in Birds.

PubMed

Dean, Rebecca; Harrison, Peter W; Wright, Alison E; Zimmer, Fabian; Mank, Judith E

2015-10-01

The elevated rate of evolution for genes on sex chromosomes compared with autosomes (Fast-X or Fast-Z evolution) can result either from positive selection in the heterogametic sex or from nonadaptive consequences of reduced relative effective population size. Recent work in birds suggests that Fast-Z of coding sequence is primarily due to relaxed purifying selection resulting from reduced relative effective population size. However, gene sequence and gene expression are often subject to distinct evolutionary pressures; therefore, we tested for Fast-Z in gene expression using next-generation RNA-sequencing data from multiple avian species. Similar to studies of Fast-Z in coding sequence, we recover clear signatures of Fast-Z in gene expression; however, in contrast to coding sequence, our data indicate that Fast-Z in expression is due to positive selection acting primarily in females. In the soma, where gene expression is highly correlated between the sexes, we detected Fast-Z in both sexes, although at a higher rate in females, suggesting that many positively selected expression changes in females are also expressed in males. In the gonad, where intersexual correlations in expression are much lower, we detected Fast-Z for female gene expression, but crucially, not males. This suggests that a large amount of expression variation is sex-specific in its effects within the gonad. Taken together, our results indicate that Fast-Z evolution of gene expression is the product of positive selection acting on recessive beneficial alleles in the heterogametic sex. More broadly, our analysis suggests that the adaptive potential of Z chromosome gene expression may be much greater than that of gene sequence, results which have important implications for the role of sex chromosomes in speciation and sexual selection. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Positive Selection Underlies Faster-Z Evolution of Gene Expression in Birds

PubMed Central

Dean, Rebecca; Harrison, Peter W.; Wright, Alison E.; Zimmer, Fabian; Mank, Judith E.

2015-01-01

The elevated rate of evolution for genes on sex chromosomes compared with autosomes (Fast-X or Fast-Z evolution) can result either from positive selection in the heterogametic sex or from nonadaptive consequences of reduced relative effective population size. Recent work in birds suggests that Fast-Z of coding sequence is primarily due to relaxed purifying selection resulting from reduced relative effective population size. However, gene sequence and gene expression are often subject to distinct evolutionary pressures; therefore, we tested for Fast-Z in gene expression using next-generation RNA-sequencing data from multiple avian species. Similar to studies of Fast-Z in coding sequence, we recover clear signatures of Fast-Z in gene expression; however, in contrast to coding sequence, our data indicate that Fast-Z in expression is due to positive selection acting primarily in females. In the soma, where gene expression is highly correlated between the sexes, we detected Fast-Z in both sexes, although at a higher rate in females, suggesting that many positively selected expression changes in females are also expressed in males. In the gonad, where intersexual correlations in expression are much lower, we detected Fast-Z for female gene expression, but crucially, not males. This suggests that a large amount of expression variation is sex-specific in its effects within the gonad. Taken together, our results indicate that Fast-Z evolution of gene expression is the product of positive selection acting on recessive beneficial alleles in the heterogametic sex. More broadly, our analysis suggests that the adaptive potential of Z chromosome gene expression may be much greater than that of gene sequence, results which have important implications for the role of sex chromosomes in speciation and sexual selection. PMID:26067773

Creating and validating cis-regulatory maps of tissue-specific gene expression regulation

PubMed Central

O'Connor, Timothy R.; Bailey, Timothy L.

2014-01-01

Predicting which genomic regions control the transcription of a given gene is a challenge. We present a novel computational approach for creating and validating maps that associate genomic regions (cis-regulatory modules–CRMs) with genes. The method infers regulatory relationships that explain gene expression observed in a test tissue using widely available genomic data for ‘other’ tissues. To predict the regulatory targets of a CRM, we use cross-tissue correlation between histone modifications present at the CRM and expression at genes within 1 Mbp of it. To validate cis-regulatory maps, we show that they yield more accurate models of gene expression than carefully constructed control maps. These gene expression models predict observed gene expression from transcription factor binding in the CRMs linked to that gene. We show that our maps are able to identify long-range regulatory interactions and improve substantially over maps linking genes and CRMs based on either the control maps or a ‘nearest neighbor’ heuristic. Our results also show that it is essential to include CRMs predicted in multiple tissues during map-building, that H3K27ac is the most informative histone modification, and that CAGE is the most informative measure of gene expression for creating cis-regulatory maps. PMID:25200088

Hormone-induced protection against mammary tumorigenesis is conserved in multiple rat strains and identifies a core gene expression signature induced by pregnancy.

PubMed

Blakely, Collin M; Stoddard, Alexander J; Belka, George K; Dugan, Katherine D; Notarfrancesco, Kathleen L; Moody, Susan E; D'Cruz, Celina M; Chodosh, Lewis A

2006-06-15

Women who have their first child early in life have a substantially lower lifetime risk of breast cancer. The mechanism for this is unknown. Similar to humans, rats exhibit parity-induced protection against mammary tumorigenesis. To explore the basis for this phenomenon, we identified persistent pregnancy-induced changes in mammary gene expression that are tightly associated with protection against tumorigenesis in multiple inbred rat strains. Four inbred rat strains that exhibit marked differences in their intrinsic susceptibilities to carcinogen-induced mammary tumorigenesis were each shown to display significant protection against methylnitrosourea-induced mammary tumorigenesis following treatment with pregnancy levels of estradiol and progesterone. Microarray expression profiling of parous and nulliparous mammary tissue from these four strains yielded a common 70-gene signature. Examination of the genes constituting this signature implicated alterations in transforming growth factor-beta signaling, the extracellular matrix, amphiregulin expression, and the growth hormone/insulin-like growth factor I axis in pregnancy-induced alterations in breast cancer risk. Notably, related molecular changes have been associated with decreased mammographic density, which itself is strongly associated with decreased breast cancer risk. Our findings show that hormone-induced protection against mammary tumorigenesis is widely conserved among divergent rat strains and define a gene expression signature that is tightly correlated with reduced mammary tumor susceptibility as a consequence of a normal developmental event. Given the conservation of this signature, these pathways may contribute to pregnancy-induced protection against breast cancer.

Differential gene expression in the siphonophore Nanomia bijuga (Cnidaria) assessed with multiple next-generation sequencing workflows.

PubMed

Siebert, Stefan; Robinson, Mark D; Tintori, Sophia C; Goetz, Freya; Helm, Rebecca R; Smith, Stephen A; Shaner, Nathan; Haddock, Steven H D; Dunn, Casey W

2011-01-01

We investigated differential gene expression between functionally specialized feeding polyps and swimming medusae in the siphonophore Nanomia bijuga (Cnidaria) with a hybrid long-read/short-read sequencing strategy. We assembled a set of partial gene reference sequences from long-read data (Roche 454), and generated short-read sequences from replicated tissue samples that were mapped to the references to quantify expression. We collected and compared expression data with three short-read expression workflows that differ in sample preparation, sequencing technology, and mapping tools. These workflows were Illumina mRNA-Seq, which generates sequence reads from random locations along each transcript, and two tag-based approaches, SOLiD SAGE and Helicos DGE, which generate reads from particular tag sites. Differences in expression results across workflows were mostly due to the differential impact of missing data in the partial reference sequences. When all 454-derived gene reference sequences were considered, Illumina mRNA-Seq detected more than twice as many differentially expressed (DE) reference sequences as the tag-based workflows. This discrepancy was largely due to missing tag sites in the partial reference that led to false negatives in the tag-based workflows. When only the subset of reference sequences that unambiguously have tag sites was considered, we found broad congruence across workflows, and they all identified a similar set of DE sequences. Our results are promising in several regards for gene expression studies in non-model organisms. First, we demonstrate that a hybrid long-read/short-read sequencing strategy is an effective way to collect gene expression data when an annotated genome sequence is not available. Second, our replicated sampling indicates that expression profiles are highly consistent across field-collected animals in this case. Third, the impacts of partial reference sequences on the ability to detect DE can be mitigated through

Differential Gene Expression in the Siphonophore Nanomia bijuga (Cnidaria) Assessed with Multiple Next-Generation Sequencing Workflows

PubMed Central

Siebert, Stefan; Robinson, Mark D.; Tintori, Sophia C.; Goetz, Freya; Helm, Rebecca R.; Smith, Stephen A.; Shaner, Nathan; Haddock, Steven H. D.; Dunn, Casey W.

2011-01-01

We investigated differential gene expression between functionally specialized feeding polyps and swimming medusae in the siphonophore Nanomia bijuga (Cnidaria) with a hybrid long-read/short-read sequencing strategy. We assembled a set of partial gene reference sequences from long-read data (Roche 454), and generated short-read sequences from replicated tissue samples that were mapped to the references to quantify expression. We collected and compared expression data with three short-read expression workflows that differ in sample preparation, sequencing technology, and mapping tools. These workflows were Illumina mRNA-Seq, which generates sequence reads from random locations along each transcript, and two tag-based approaches, SOLiD SAGE and Helicos DGE, which generate reads from particular tag sites. Differences in expression results across workflows were mostly due to the differential impact of missing data in the partial reference sequences. When all 454-derived gene reference sequences were considered, Illumina mRNA-Seq detected more than twice as many differentially expressed (DE) reference sequences as the tag-based workflows. This discrepancy was largely due to missing tag sites in the partial reference that led to false negatives in the tag-based workflows. When only the subset of reference sequences that unambiguously have tag sites was considered, we found broad congruence across workflows, and they all identified a similar set of DE sequences. Our results are promising in several regards for gene expression studies in non-model organisms. First, we demonstrate that a hybrid long-read/short-read sequencing strategy is an effective way to collect gene expression data when an annotated genome sequence is not available. Second, our replicated sampling indicates that expression profiles are highly consistent across field-collected animals in this case. Third, the impacts of partial reference sequences on the ability to detect DE can be mitigated through

PiiL: visualization of DNA methylation and gene expression data in gene pathways.

PubMed

Moghadam, Behrooz Torabi; Zamani, Neda; Komorowski, Jan; Grabherr, Manfred

2017-08-02

DNA methylation is a major mechanism involved in the epigenetic state of a cell. It has been observed that the methylation status of certain CpG sites close to or within a gene can directly affect its expression, either by silencing or, in some cases, up-regulating transcription. However, a vertebrate genome contains millions of CpG sites, all of which are potential targets for methylation, and the specific effects of most sites have not been characterized to date. To study the complex interplay between methylation status, cellular programs, and the resulting phenotypes, we present PiiL, an interactive gene expression pathway browser, facilitating analyses through an integrated view of methylation and expression on multiple levels. PiiL allows for specific hypothesis testing by quickly assessing pathways or gene networks, where the data is projected onto pathways that can be downloaded directly from the online KEGG database. PiiL provides a comprehensive set of analysis features that allow for quick and specific pattern searches. Individual CpG sites and their impact on host gene expression, as well as the impact on other genes present in the regulatory network, can be examined. To exemplify the power of this approach, we analyzed two types of brain tumors, Glioblastoma multiform and lower grade gliomas. At a glance, we could confirm earlier findings that the predominant methylation and expression patterns separate perfectly by mutations in the IDH genes, rather than by histology. We could also infer the IDH mutation status for samples for which the genotype was not known. By applying different filtering methods, we show that a subset of CpG sites exhibits consistent methylation patterns, and that the status of sites affect the expression of key regulator genes, as well as other genes located downstream in the same pathways. PiiL is implemented in Java with focus on a user-friendly graphical interface. The source code is available under the GPL license from https://github.com/behroozt/PiiL.git .

Digital gene expression analysis of gene expression differences within Brassica diploids and allopolyploids.

PubMed

Jiang, Jinjin; Wang, Yue; Zhu, Bao; Fang, Tingting; Fang, Yujie; Wang, Youping

2015-01-27

Brassica includes many successfully cultivated crop species of polyploid origin, either by ancestral genome triplication or by hybridization between two diploid progenitors, displaying complex repetitive sequences and transposons. The U's triangle, which consists of three diploids and three amphidiploids, is optimal for the analysis of complicated genomes after polyploidization. Next-generation sequencing enables the transcriptome profiling of polyploids on a global scale. We examined the gene expression patterns of three diploids (Brassica rapa, B. nigra, and B. oleracea) and three amphidiploids (B. napus, B. juncea, and B. carinata) via digital gene expression analysis. In total, the libraries generated between 5.7 and 6.1 million raw reads, and the clean tags of each library were mapped to 18547-21995 genes of B. rapa genome. The unambiguous tag-mapped genes in the libraries were compared. Moreover, the majority of differentially expressed genes (DEGs) were explored among diploids as well as between diploids and amphidiploids. Gene ontological analysis was performed to functionally categorize these DEGs into different classes. The Kyoto Encyclopedia of Genes and Genomes analysis was performed to assign these DEGs into approximately 120 pathways, among which the metabolic pathway, biosynthesis of secondary metabolites, and peroxisomal pathway were enriched. The non-additive genes in Brassica amphidiploids were analyzed, and the results indicated that orthologous genes in polyploids are frequently expressed in a non-additive pattern. Methyltransferase genes showed differential expression pattern in Brassica species. Our results provided an understanding of the transcriptome complexity of natural Brassica species. The gene expression changes in diploids and allopolyploids may help elucidate the morphological and physiological differences among Brassica species.

Aberrant Gene Expression in Humans

PubMed Central

Yang, Ence; Ji, Guoli; Brinkmeyer-Langford, Candice L.; Cai, James J.

2015-01-01

Gene expression as an intermediate molecular phenotype has been a focus of research interest. In particular, studies of expression quantitative trait loci (eQTL) have offered promise for understanding gene regulation through the discovery of genetic variants that explain variation in gene expression levels. Existing eQTL methods are designed for assessing the effects of common variants, but not rare variants. Here, we address the problem by establishing a novel analytical framework for evaluating the effects of rare or private variants on gene expression. Our method starts from the identification of outlier individuals that show markedly different gene expression from the majority of a population, and then reveals the contributions of private SNPs to the aberrant gene expression in these outliers. Using population-scale mRNA sequencing data, we identify outlier individuals using a multivariate approach. We find that outlier individuals are more readily detected with respect to gene sets that include genes involved in cellular regulation and signal transduction, and less likely to be detected with respect to the gene sets with genes involved in metabolic pathways and other fundamental molecular functions. Analysis of polymorphic data suggests that private SNPs of outlier individuals are enriched in the enhancer and promoter regions of corresponding aberrantly-expressed genes, suggesting a specific regulatory role of private SNPs, while the commonly-occurring regulatory genetic variants (i.e., eQTL SNPs) show little evidence of involvement. Additional data suggest that non-genetic factors may also underlie aberrant gene expression. Taken together, our findings advance a novel viewpoint relevant to situations wherein common eQTLs fail to predict gene expression when heritable, rare inter-individual variation exists. The analytical framework we describe, taking into consideration the reality of differential phenotypic robustness, may be valuable for investigating

iGC-an integrated analysis package of gene expression and copy number alteration.

PubMed

Lai, Yi-Pin; Wang, Liang-Bo; Wang, Wei-An; Lai, Liang-Chuan; Tsai, Mong-Hsun; Lu, Tzu-Pin; Chuang, Eric Y

2017-01-14

With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual. We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance. The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .

Multiclass cancer diagnosis using tumor gene expression signatures

DOE PAGES

Ramaswamy, S.; Tamayo, P.; Rifkin, R.; ...

2001-12-11

The optimal treatment of patients with cancer depends on establishing accurate diagnoses by using a complex combination of clinical and histopathological data. In some instances, this task is difficult or impossible because of atypical clinical presentation or histopathology. To determine whether the diagnosis of multiple common adult malignancies could be achieved purely by molecular classification, we subjected 218 tumor samples, spanning 14 common tumor types, and 90 normal tissue samples to oligonucleotide microarray gene expression analysis. The expression levels of 16,063 genes and expressed sequence tags were used to evaluate the accuracy of a multiclass classifier based on a supportmore » vector machine algorithm. Overall classification accuracy was 78%, far exceeding the accuracy of random classification (9%). Poorly differentiated cancers resulted in low-confidence predictions and could not be accurately classified according to their tissue of origin, indicating that they are molecularly distinct entities with dramatically different gene expression patterns compared with their well differentiated counterparts. Taken together, these results demonstrate the feasibility of accurate, multiclass molecular cancer classification and suggest a strategy for future clinical implementation of molecular cancer diagnostics.« less

Organ-specific gene expression: the bHLH protein Sage provides tissue specificity to Drosophila FoxA.

PubMed

Fox, Rebecca M; Vaishnavi, Aria; Maruyama, Rika; Andrew, Deborah J

2013-05-01

FoxA transcription factors play major roles in organ-specific gene expression, regulating, for example, glucagon expression in the pancreas, GLUT2 expression in the liver, and tyrosine hydroxylase expression in dopaminergic neurons. Organ-specific gene regulation by FoxA proteins is achieved through cooperative regulation with a broad array of transcription factors with more limited expression domains. Fork head (Fkh), the sole Drosophila FoxA family member, is required for the development of multiple distinct organs, yet little is known regarding how Fkh regulates tissue-specific gene expression. Here, we characterize Sage, a bHLH transcription factor expressed exclusively in the Drosophila salivary gland (SG). We show that Sage is required for late SG survival and normal tube morphology. We find that many Sage targets, identified by microarray analysis, encode SG-specific secreted cargo, transmembrane proteins, and the enzymes that modify these proteins. We show that both Sage and Fkh are required for the expression of Sage target genes, and that co-expression of Sage and Fkh is sufficient to drive target gene expression in multiple cell types. Sage and Fkh drive expression of the bZip transcription factor Senseless (Sens), which boosts expression of Sage-Fkh targets, and Sage, Fkh and Sens colocalize on SG chromosomes. Importantly, expression of Sage-Fkh target genes appears to simply add to the tissue-specific gene expression programs already established in other cell types, and Sage and Fkh cannot alter the fate of most embryonic cell types even when expressed early and continuously.

Organ-specific gene expression: the bHLH protein Sage provides tissue specificity to Drosophila FoxA

PubMed Central

Fox, Rebecca M.; Vaishnavi, Aria; Maruyama, Rika; Andrew, Deborah J.

2013-01-01

FoxA transcription factors play major roles in organ-specific gene expression, regulating, for example, glucagon expression in the pancreas, GLUT2 expression in the liver, and tyrosine hydroxylase expression in dopaminergic neurons. Organ-specific gene regulation by FoxA proteins is achieved through cooperative regulation with a broad array of transcription factors with more limited expression domains. Fork head (Fkh), the sole Drosophila FoxA family member, is required for the development of multiple distinct organs, yet little is known regarding how Fkh regulates tissue-specific gene expression. Here, we characterize Sage, a bHLH transcription factor expressed exclusively in the Drosophila salivary gland (SG). We show that Sage is required for late SG survival and normal tube morphology. We find that many Sage targets, identified by microarray analysis, encode SG-specific secreted cargo, transmembrane proteins, and the enzymes that modify these proteins. We show that both Sage and Fkh are required for the expression of Sage target genes, and that co-expression of Sage and Fkh is sufficient to drive target gene expression in multiple cell types. Sage and Fkh drive expression of the bZip transcription factor Senseless (Sens), which boosts expression of Sage-Fkh targets, and Sage, Fkh and Sens colocalize on SG chromosomes. Importantly, expression of Sage-Fkh target genes appears to simply add to the tissue-specific gene expression programs already established in other cell types, and Sage and Fkh cannot alter the fate of most embryonic cell types even when expressed early and continuously. PMID:23578928

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

PubMed

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

2015-09-01

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

Synergistic interactions of biotic and abiotic environmental stressors on gene expression.

PubMed

Altshuler, Ianina; McLeod, Anne M; Colbourne, John K; Yan, Norman D; Cristescu, Melania E

2015-03-01

Understanding the response of organisms to multiple stressors is critical for predicting if populations can adapt to rapid environmental change. Natural and anthropogenic stressors often interact, complicating general predictions. In this study, we examined the interactive and cumulative effects of two common environmental stressors, lowered calcium concentration, an anthropogenic stressor, and predator presence, a natural stressor, on the water flea Daphnia pulex. We analyzed expression changes of five genes involved in calcium homeostasis - cuticle proteins (Cutie, Icp2), calbindin (Calb), and calcium pump and channel (Serca and Ip3R) - using real-time quantitative PCR (RT-qPCR) in a full factorial experiment. We observed strong synergistic interactions between low calcium concentration and predator presence. While the Ip3R gene was not affected by the stressors, the other four genes were affected in their transcriptional levels by the combination of the stressors. Transcriptional patterns of genes that code for cuticle proteins (Cutie and Icp2) and a sarcoplasmic calcium pump (Serca) only responded to the combination of stressors, changing their relative expression levels in a synergistic response, while a calcium-binding protein (Calb) responded to low calcium stress and the combination of both stressors. The expression pattern of these genes (Cutie, Icp2, and Serca) were nonlinear, yet they were dose dependent across the calcium gradient. Multiple stressors can have complex, often unexpected effects on ecosystems. This study demonstrates that the dominant interaction for the set of tested genes appears to be synergism. We argue that gene expression patterns can be used to understand and predict the type of interaction expected when organisms are exposed simultaneously to natural and anthropogenic stressors.

The α‐synuclein gene in multiple system atrophy

PubMed Central

Ozawa, T; Healy, D G; Abou‐Sleiman, P M; Ahmadi, K R; Quinn, N; Lees, A J; Shaw, K; Wullner, U; Berciano, J; Moller, J C; Kamm, C; Burk, K; Josephs, K A; Barone, P; Tolosa, E; Goldstein, D B; Wenning, G; Geser, F; Holton, J L; Gasser, T; Revesz, T; Wood, N W

2006-01-01

Background The formation of α‐synuclein aggregates may be a critical event in the pathogenesis of multiple system atrophy (MSA). However, the role of this gene in the aetiology of MSA is unknown and untested. Method The linkage disequilibrium (LD) structure of the α‐synuclein gene was established and LD patterns were used to identify a set of tagging single nucleotide polymorphisms (SNPs) that represent 95% of the haplotype diversity across the entire gene. The effect of polymorphisms on the pathological expression of MSA in pathologically confirmed cases was also evaluated. Results and conclusion In 253 Gilman probable or definite MSA patients, 457 possible, probable, and definite MSA cases and 1472 controls, a frequency difference for the individual tagging SNPs or tag‐defined haplotypes was not detected. No effect was observed of polymorphisms on the pathological expression of MSA in pathologically confirmed cases. PMID:16543523

Bayesian approach to transforming public gene expression repositories into disease diagnosis databases.

PubMed

Huang, Haiyan; Liu, Chun-Chi; Zhou, Xianghong Jasmine

2010-04-13

The rapid accumulation of gene expression data has offered unprecedented opportunities to study human diseases. The National Center for Biotechnology Information Gene Expression Omnibus is currently the largest database that systematically documents the genome-wide molecular basis of diseases. However, thus far, this resource has been far from fully utilized. This paper describes the first study to transform public gene expression repositories into an automated disease diagnosis database. Particularly, we have developed a systematic framework, including a two-stage Bayesian learning approach, to achieve the diagnosis of one or multiple diseases for a query expression profile along a hierarchical disease taxonomy. Our approach, including standardizing cross-platform gene expression data and heterogeneous disease annotations, allows analyzing both sources of information in a unified probabilistic system. A high level of overall diagnostic accuracy was shown by cross validation. It was also demonstrated that the power of our method can increase significantly with the continued growth of public gene expression repositories. Finally, we showed how our disease diagnosis system can be used to characterize complex phenotypes and to construct a disease-drug connectivity map.

Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification.

PubMed

Shimoni, Yishai

2018-02-01

One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes.

Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification

PubMed Central

2018-01-01

One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes. PMID:29470520

Multiple glutathione S-transferase genes: identification and expression in oriental fruit fly, Bactrocera dorsalis.

PubMed

Hu, Fei; Dou, Wei; Wang, Jing-Jing; Jia, Fu-Xian; Wang, Jin-Jun

2014-02-01

The oriental fruit fly, Bactrocera dorsalis (Hendel), is widely distributed in Asia-Pacific regions, where it is a serious pest of a wide range of tropical and subtropical fruit and vegetable crops. In this study, 17 cDNA encoding glutathione S-transferases (GSTs) in B. dorsalis were sequenced and characterised. Phylogenetic analysis revealed that 16 GSTs belonged to five different cytosolic classes, including four in delta, eight in epsilon, two in omega, one in theta, and one in zeta. The remaining GST (BdGSTu1) was unclassified. RT-qPCR assay showed that the relative expression levels of five GST genes were significantly higher in larval stages than in adulthood. Tissue-specific expression analysis found that BdGSTe3, BdGSTe9 and BdGSTd5 were expressed highly in the midgut, BdGSTe4, BdGSTe6, BdGSTd6 and BdGSTz2 were higher in the fat body, and six GSTs were higher in Malpighian tubules. RT-qPCR confirmed that the expressions of nine GST genes were increased by malathion exposure at various times and doses, while BdGSTe4, BdGSTe9 and BdGSTt1 were increased by β-cypermethrin exposure. The increases in GST gene expression levels after malathion and β-cypermethrin exposure in B. dorsalis might increase the ability of this species to detoxify other insecticides and xenobiotics. © 2013 Society of Chemical Industry.

Microgravity and immunity: Changes in lymphocyte gene expression.

NASA Astrophysics Data System (ADS)

Risin, D.; Ward, N. E.; Risin, S. A.; Pellis, N. R.

Earlier studies had shown that modeled and true microgravity MG cause multiple direct effects on human lymphocytes MG inhibits lymphocyte locomotion suppresses polyclonal and antigen-specific activation affects signal transduction mechanisms as well as activation-induced apoptosis In this study we assessed changes in gene expression associated with lymphocyte exposure to microgravity in an attempt to identify microgravity-sensitive genes MGSG in general and specifically those genes that might be responsible for the functional and structural changes observed earlier Two sets of experiments targeting different goals were conducted In the first set T-lymphocytes from normal donors were activated with anti-CD3 and IL2 and then cultured in 1g static and modeled MG MMG conditions Rotating Wall Vessel bioreactor for 24 hours This setting allowed searching for MGSG by comparison of gene expression patterns in zero and 1 g gravity In the second set - activated T-cells after culturing for 24 hours in 1g and MMG were exposed three hours before harvesting to a secondary activation stimulus PHA thus triggering the apoptotic pathway Total RNA was extracted using the RNeasy isolation kit Qiagen Valencia CA Affymetrix Gene Chips U133A allowing testing for 18 400 human genes were used for microarray analysis The experiments were performed in triplicates with T-cells obtained from different blood donors to minimize the possible input of biological variation in gene expression and discriminate changes that are associated with the

Pediatric Multiple Sclerosis: Genes, Environment, and a Comprehensive Therapeutic Approach.

PubMed

Cappa, Ryan; Theroux, Liana; Brenton, J Nicholas

2017-10-01

Pediatric multiple sclerosis is an increasingly recognized and studied disorder that accounts for 3% to 10% of all patients with multiple sclerosis. The risk for pediatric multiple sclerosis is thought to reflect a complex interplay between environmental and genetic risk factors. Environmental exposures, including sunlight (ultraviolet radiation, vitamin D levels), infections (Epstein-Barr virus), passive smoking, and obesity, have been identified as potential risk factors in youth. Genetic predisposition contributes to the risk of multiple sclerosis, and the major histocompatibility complex on chromosome 6 makes the single largest contribution to susceptibility to multiple sclerosis. With the use of large-scale genome-wide association studies, other non-major histocompatibility complex alleles have been identified as independent risk factors for the disease. The bridge between environment and genes likely lies in the study of epigenetic processes, which are environmentally-influenced mechanisms through which gene expression may be modified. This article will review these topics to provide a framework for discussion of a comprehensive approach to counseling and ultimately treating the pediatric patient with multiple sclerosis. Copyright © 2017 Elsevier Inc. All rights reserved.

FOXP3, CBLB and ITCH gene expression and cytotoxic T lymphocyte antigen 4 expression on CD4+CD25high T cells in multiple sclerosis

PubMed Central

Sellebjerg, F; Krakauer, M; Khademi, M; Olsson, T; Sørensen, P S

2012-01-01

Expression of the forkhead box protein 3 (FoxP3) transcription factor is regulated by the E3 ubiquitin ligases Itch and Cbl-b and induces regulatory activity CD4+CD25high T cells. Treatment with interferon (IFN)-β enhances regulatory T cell activity in multiple sclerosis (MS). We studied the phenotype of CD4+CD25high T cells in MS by flow cytometry and its relationship with expression of the FOXP3, ITCH and CBLB genes. We found that untreated MS patients had lower cell surface expression of cytotoxic T lymphocyte antigen 4 (CTLA-4) on CD4+CD25high T cells and higher intracellular CTLA-4 expression than healthy controls. Cell surface expression of CTLA-4 on CD4+CD25high T cells correlated with expression of FOXP3 mRNA in untreated patients and increased significantly with time from most recent injection in patients treated with IFN-β. FOXP3 mRNA expression correlated with CBLB and ITCH and T helper type 2 cytokine mRNA expression in MS patients. These data link expression of FOXP3, CBLB and ITCH mRNA and CTLA-4 expression on the surface of CD4+CD25high T cell in MS. We hypothesize that this may reflect alterations in the inhibitory effect of CTLA-4 or in regulatory T cell function. PMID:23039885

Clustered metallothionein genes are co-regulated in rice and ectopic expression of OsMT1e-P confers multiple abiotic stress tolerance in tobacco via ROS scavenging

PubMed Central

2012-01-01

Background Metallothioneins (MT) are low molecular weight, cysteine rich metal binding proteins, found across genera and species, but their function(s) in abiotic stress tolerance are not well documented. Results We have characterized a rice MT gene, OsMT1e-P, isolated from a subtractive library generated from a stressed salinity tolerant rice genotype, Pokkali. Bioinformatics analysis of the rice genome sequence revealed that this gene belongs to a multigenic family, which consists of 13 genes with 15 protein products. OsMT1e-P is located on chromosome XI, away from the majority of other type I genes that are clustered on chromosome XII. Various members of this MT gene cluster showed a tight co-regulation pattern under several abiotic stresses. Sequence analysis revealed the presence of conserved cysteine residues in OsMT1e-P protein. Salinity stress was found to regulate the transcript abundance of OsMT1e-P in a developmental and organ specific manner. Using transgenic approach, we found a positive correlation between ectopic expression of OsMT1e-P and stress tolerance. Our experiments further suggest ROS scavenging to be the possible mechanism for multiple stress tolerance conferred by OsMT1e-P. Conclusion We present an overview of MTs, describing their gene structure, genome localization and expression patterns under salinity and development in rice. We have found that ectopic expression of OsMT1e-P enhances tolerance towards multiple abiotic stresses in transgenic tobacco and the resultant plants could survive and set viable seeds under saline conditions. Taken together, the experiments presented here have indicated that ectopic expression of OsMT1e-P protects against oxidative stress primarily through efficient scavenging of reactive oxygen species. PMID:22780875

Clustered metallothionein genes are co-regulated in rice and ectopic expression of OsMT1e-P confers multiple abiotic stress tolerance in tobacco via ROS scavenging.

PubMed

Kumar, Gautam; Kushwaha, Hemant Ritturaj; Panjabi-Sabharwal, Vaishali; Kumari, Sumita; Joshi, Rohit; Karan, Ratna; Mittal, Shweta; Pareek, Sneh L Singla; Pareek, Ashwani

2012-07-10

Metallothioneins (MT) are low molecular weight, cysteine rich metal binding proteins, found across genera and species, but their function(s) in abiotic stress tolerance are not well documented. We have characterized a rice MT gene, OsMT1e-P, isolated from a subtractive library generated from a stressed salinity tolerant rice genotype, Pokkali. Bioinformatics analysis of the rice genome sequence revealed that this gene belongs to a multigenic family, which consists of 13 genes with 15 protein products. OsMT1e-P is located on chromosome XI, away from the majority of other type I genes that are clustered on chromosome XII. Various members of this MT gene cluster showed a tight co-regulation pattern under several abiotic stresses. Sequence analysis revealed the presence of conserved cysteine residues in OsMT1e-P protein. Salinity stress was found to regulate the transcript abundance of OsMT1e-P in a developmental and organ specific manner. Using transgenic approach, we found a positive correlation between ectopic expression of OsMT1e-P and stress tolerance. Our experiments further suggest ROS scavenging to be the possible mechanism for multiple stress tolerance conferred by OsMT1e-P. We present an overview of MTs, describing their gene structure, genome localization and expression patterns under salinity and development in rice. We have found that ectopic expression of OsMT1e-P enhances tolerance towards multiple abiotic stresses in transgenic tobacco and the resultant plants could survive and set viable seeds under saline conditions. Taken together, the experiments presented here have indicated that ectopic expression of OsMT1e-P protects against oxidative stress primarily through efficient scavenging of reactive oxygen species.

Increased Resistance to Multiple Antimicrobials and Altered Resistance Gene Expression in CMY-2-Positive Salmonella enterica following a Simulated Patient Treatment with Ceftriaxone

PubMed Central

Hamilton, Russell D.; Hulsebus, Holly J.; Akbar, Samina

2012-01-01

Salmonellosis is one of the most common causes of food-borne disease in the United States. Increasing antimicrobial resistance and corresponding increases in virulence present serious challenges. Currently, empirical therapy for invasive Salmonella enterica infection includes either ceftriaxone or ciprofloxacin (E. L. Hohmann, Clin. Infect. Dis. 32:263–269, 2001). The blaCMY-2 gene confers resistance to ceftriaxone, the antimicrobial of choice for pediatric patients with invasive Salmonella enterica infections, making these infections especially dangerous (J. M. Whichard et al., Emerg. Infect. Dis. 11:1464–1466, 2005). We hypothesized that blaCMY-2-positive Salmonella enterica would exhibit increased MICs to multiple antimicrobial agents and increased resistance gene expression following exposure to ceftriaxone using a protocol that simulated a patient treatment in vitro. Seven Salmonella enterica strains survived a simulated patient treatment in vitro and, following treatment, exhibited a significantly increased ceftriaxone MIC. Not only would these isolates be less responsive to further ceftriaxone treatment, but because the blaCMY-2 genes are commonly located on large, multidrug-resistant plasmids, increased expression of the blaCMY-2 gene may be associated with increased expression of other drug resistance genes located on the plasmid (N. D. Hanson and C. C. Sanders, Curr. Pharm. Des. 5:881–894, 1999). The results of this study demonstrate that a simulated patient treatment with ceftriaxone can alter the expression of antimicrobial resistance genes, including blaCMY-2 and floR in S. enterica serovar Typhimurium and S. enterica serovar Newport. Additionally, we have shown increased MICs following a simulated patient treatment with ceftriaxone for tetracycline, amikacin, ceftriaxone, and cefepime, all of which have resistance genes commonly located on CMY-2 plasmids. The increases in resistance observed are significant and may have a negative impact on both

Investigation of Reference Genes in Vibrio parahaemolyticus for Gene Expression Analysis Using Quantitative RT-PCR.

PubMed

Ma, Yue-Jiao; Sun, Xiao-Hong; Xu, Xiao-Yan; Zhao, Yong; Pan, Ying-Jie; Hwang, Cheng-An; Wu, Vivian C H

2015-01-01

Vibrio parahaemolyticus is a significant human pathogen capable of causing foodborne gastroenteritis associated with the consumption of contaminated raw or undercooked seafood. Quantitative RT-PCR (qRT-PCR) is a useful tool for studying gene expression in V. parahaemolyticus to characterize its virulence factors and understand the effect of environmental conditions on its pathogenicity. However, there is not a stable gene in V. parahaemolyticus that has been identified for use as a reference gene for qRT-PCR. This study evaluated the stability of 6 reference genes (16S rRNA, recA, rpoS, pvsA, pvuA, and gapdh) in 5 V. parahaemolyticus strains (O3:K6-clinical strain-tdh+, ATCC33846-tdh+, ATCC33847-tdh+, ATCC17802-trh+, and F13-environmental strain-tdh+) cultured at 4 different temperatures (15, 25, 37 and 42°C). Stability values were calculated using GeNorm, NormFinder, BestKeeper, and Delta CT algorithms. The results indicated that recA was the most stably expressed gene in the V. parahaemolyticus strains cultured at different temperatures. This study examined multiple V. parahaemolyticus strains and growth temperatures, hence the finding provided stronger evidence that recA can be used as a reference gene for gene expression studies in V. parahaemolyticus.

Differential expression of multiple glutamine synthetase genes in air-breathing magur catfish, Clarias magur and their induction under hyper-ammonia stress.

PubMed

Banerjee, Bodhisattwa; Koner, Debaprasad; Bhuyan, Gitalee; Saha, Nirmalendu

2018-06-01

The present study demonstrates the unique presence of three different gs genes (cmgs01, cmgs02, and cmgs03) in air-breathing ureogenic magur catfish (Clarias magur), which is otherwise reported to be encoded by a single gene in higher vertebrates. Of these three genes, two (cmgs01and cmgs03) were identified as 'liver' form, predominantly expressed in liver cells, and the third one as 'brain' form (cmgs02), expressed chiefly in brain cells. Molecular characterization studies have revealed conservation of homologous active site residues in all the three gs genes. In silico analysis, accompanied by GS enzyme assay and Western blot analysis of different GS isoforms in different subcellular fractions indicated the mitochondrial localization of cmGS01 and cmGS03 in liver and kidney cells and cytosolic localization of cmGS02 in brain cells. Further, exposure of magur catfish to high external ammonia (HEA; 25 mM NH 4 Cl) led to a significant induction of multiple gs genes as evidenced by higher expression of different gs mRNAs at variable levels in different tissues. The cmgs01 and cmgs03 mRNA levels elevated significantly in liver, kidney, muscle, and gills, whereas the cmgs02 mRNA level increased considerably in the brain after 14 days of exposure to HEA. These increases in mRNA levels were associated with a significant rise in cmGS01 and cmGS03 proteins in liver, kidney, muscle, and gills, and the cmGS02 protein in the brain after 14 days of exposure to HEA. Therefore, it can be concluded that the unique differential expression of three gs genes and their induction under high ammonia level probably helps in detoxification of ammonia to glutamine and further to urea via the ornithine-urea cycle in ureogenic as well as non-ureogenic tissues of these magur catfish. Copyright © 2017. Published by Elsevier B.V.

Aberrant DNA methylation associated with silencing BNIP3 gene expression in haematopoietic tumours

PubMed Central

Murai, M; Toyota, M; Satoh, A; Suzuki, H; Akino, K; Mita, H; Sasaki, Y; Ishida, T; Shen, L; Garcia-Manero, G; Issa, J-P J; Hinoda, Y; Tokino, T; Imai, K

2005-01-01

Hypoxia is a key factor contributing to the progression of human neoplasias and to the development of resistance to chemotherapy. BNIP3 is a proapoptotic member of the Bcl-2 protein family involved in hypoxia-induced cell death. We evaluated the expression and methylation status of BNIP3 gene to better understand the role of epigenetic alteration of its expression in haematopoietic tumours. Methylation of the region around the BNIP3 transcription start site was detected in four acute lymphocytic leukaemia, one multiple myeloma and one Burkitt lymphoma cell lines, and was closely associated with silencing the gene. That expression of BNIP3 was restored by treatment with 5-aza2′-deoxycytidine (5-aza-dC), a methyltransferase inhibitor, which confirmed the gene to be epigenetically inactivated by methylation. Notably, re-expression of BNIP3 using 5-aza2-dC also restored hypoxia-mediated cell death in methylated cell lines. Acetylation of histone H3 in the 5′ region of the gene, which was assessed using chromatin immunoprecipitation assays, correlated directly with gene expression and inversely with DNA methylation. Among primary tumours, methylation of BNIP3 was detected in five of 34 (15%) acute lymphocytic leukaemias, six of 35 (17%) acute myelogenous leukaemias and three of 14 (21%) multiple myelomas. These results suggest that aberrant DNA methylation of the 5′ CpG island and histone deacetylation play key roles in silencing BNIP3 expression in haematopoietic tumours. PMID:15756280

GEOGLE: context mining tool for the correlation between gene expression and the phenotypic distinction.

PubMed

Yu, Yao; Tu, Kang; Zheng, Siyuan; Li, Yun; Ding, Guohui; Ping, Jie; Hao, Pei; Li, Yixue

2009-08-25

In the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches. In our work, we integrated gene expression information from Gene Expression Omnibus (GEO), biomedical ontology from Medical Subject Headings (MeSH) and signaling pathway knowledge from sigPathway entries to develop a context mining tool for gene expression analysis - GEOGLE. GEOGLE offers a rapid and convenient way for searching relevant experimental datasets, pathways and biological terms according to multiple types of queries: including biomedical vocabularies, GDS IDs, gene IDs, pathway names and signature list. Moreover, GEOGLE summarizes the signature genes from a subset of GDSes and estimates the correlation between gene expression and the phenotypic distinction with an integrated p value. This approach performing global searching of expression data may expand the traditional way of collecting heterogeneous gene expression experiment data. GEOGLE is a novel tool that provides researchers a quantitative way to understand the correlation between gene expression and phenotypic distinction through meta-analysis of gene expression datasets from different experiments, as well as the biological meaning behind. The web site and user guide of GEOGLE are available at: http://omics.biosino.org:14000/kweb/workflow.jsp?id=00020.

Combining Evidence of Preferential Gene-Tissue Relationships from Multiple Sources

PubMed Central

Guo, Jing; Hammar, Mårten; Öberg, Lisa; Padmanabhuni, Shanmukha S.; Bjäreland, Marcus; Dalevi, Daniel

2013-01-01

An important challenge in drug discovery and disease prognosis is to predict genes that are preferentially expressed in one or a few tissues, i.e. showing a considerably higher expression in one tissue(s) compared to the others. Although several data sources and methods have been published explicitly for this purpose, they often disagree and it is not evident how to retrieve these genes and how to distinguish true biological findings from those that are due to choice-of-method and/or experimental settings. In this work we have developed a computational approach that combines results from multiple methods and datasets with the aim to eliminate method/study-specific biases and to improve the predictability of preferentially expressed human genes. A rule-based score is used to merge and assign support to the results. Five sets of genes with known tissue specificity were used for parameter pruning and cross-validation. In total we identify 3434 tissue-specific genes. We compare the genes of highest scores with the public databases: PaGenBase (microarray), TiGER (EST) and HPA (protein expression data). The results have 85% overlap to PaGenBase, 71% to TiGER and only 28% to HPA. 99% of our predictions have support from at least one of these databases. Our approach also performs better than any of the databases on identifying drug targets and biomarkers with known tissue-specificity. PMID:23950964

SET1A/COMPASS and shadow enhancers in the regulation of homeotic gene expression

PubMed Central

Cao, Kaixiang; Collings, Clayton K.; Marshall, Stacy A.; Morgan, Marc A.; Rendleman, Emily J.; Wang, Lu; Sze, Christie C.; Sun, Tianjiao; Bartom, Elizabeth T.; Shilatifard, Ali

2017-01-01

The homeotic (Hox) genes are highly conserved in metazoans, where they are required for various processes in development, and misregulation of their expression is associated with human cancer. In the developing embryo, Hox genes are activated sequentially in time and space according to their genomic position within Hox gene clusters. Accumulating evidence implicates both enhancer elements and noncoding RNAs in controlling this spatiotemporal expression of Hox genes, but disentangling their relative contributions is challenging. Here, we identify two cis-regulatory elements (E1 and E2) functioning as shadow enhancers to regulate the early expression of the HoxA genes. Simultaneous deletion of these shadow enhancers in embryonic stem cells leads to impaired activation of HoxA genes upon differentiation, while knockdown of a long noncoding RNA overlapping E1 has no detectable effect on their expression. Although MLL/COMPASS (complex of proteins associated with Set1) family of histone methyltransferases is known to activate transcription of Hox genes in other contexts, we found that individual inactivation of the MLL1-4/COMPASS family members has little effect on early Hox gene activation. Instead, we demonstrate that SET1A/COMPASS is required for full transcriptional activation of multiple Hox genes but functions independently of the E1 and E2 cis-regulatory elements. Our results reveal multiple regulatory layers for Hox genes to fine-tune transcriptional programs essential for development. PMID:28487406

Allopatric integrations selectively change host transcriptomes, leading to varied expression efficiencies of exotic genes in Myxococcus xanthus.

PubMed

Zhu, Li-Ping; Yue, Xin-Jing; Han, Kui; Li, Zhi-Feng; Zheng, Lian-Shuai; Yi, Xiu-Nan; Wang, Hai-Long; Zhang, You-Ming; Li, Yue-Zhong

2015-07-22

Exotic genes, especially clustered multiple-genes for a complex pathway, are normally integrated into chromosome for heterologous expression. The influences of insertion sites on heterologous expression and allotropic expressions of exotic genes on host remain mostly unclear. We compared the integration and expression efficiencies of single and multiple exotic genes that were inserted into Myxococcus xanthus genome by transposition and attB-site-directed recombination. While the site-directed integration had a rather stable chloramphenicol acetyl transferase (CAT) activity, the transposition produced varied CAT enzyme activities. We attempted to integrate the 56-kb gene cluster for the biosynthesis of antitumor polyketides epothilones into M. xanthus genome by site-direction but failed, which was determined to be due to the insertion size limitation at the attB site. The transposition technique produced many recombinants with varied production capabilities of epothilones, which, however, were not paralleled to the transcriptional characteristics of the local sites where the genes were integrated. Comparative transcriptomics analysis demonstrated that the allopatric integrations caused selective changes of host transcriptomes, leading to varied expressions of epothilone genes in different mutants. With the increase of insertion fragment size, transposition is a more practicable integration method for the expression of exotic genes. Allopatric integrations selectively change host transcriptomes, which lead to varied expression efficiencies of exotic genes.

A highly tunable system for the simultaneous expression of multiple enzymes in Saccharomyces cerevisiae.

PubMed

Ito, Yoichiro; Yamanishi, Mamoru; Ikeuchi, Akinori; Matsuyama, Takashi

2015-01-16

Control of the expression levels of multiple enzymes in transgenic yeasts is essential for the effective production of complex molecules through fermentation. Here, we propose a tunable strategy for the control of expression levels based on the design of terminator regions and other gene-expression control elements in Saccharomyces cerevisiae. Our genome-integrated system, which is capable of producing high expression levels over a wide dynamic range, will broadly enable metabolic engineering and synthetic biology. We demonstrated that the activities of multiple cellulases and the production of ethanol were doubled in a transgenic yeast constructed with our system compared with those achieved with a standard expression system.

Microgravity and Immunity: Changes in Lymphocyte Gene Expression

NASA Technical Reports Server (NTRS)

Risin, D.; Pellis, N. R.; Ward, N. E.; Risin, S. A.

2006-01-01

Earlier studies had shown that modeled and true microgravity (MG) cause multiple direct effects on human lymphocytes. MG inhibits lymphocyte locomotion, suppresses polyclonal and antigen-specific activation, affects signal transduction mechanisms, as well as activation-induced apoptosis. In this study we assessed changes in gene expression associated with lymphocyte exposure to microgravity in an attempt to identify microgravity-sensitive genes (MGSG) in general and specifically those genes that might be responsible for the functional and structural changes observed earlier. Two sets of experiments targeting different goals were conducted. In the first set, T-lymphocytes from normal donors were activated with antiCD3 and IL2 and then cultured in 1g (static) and modeled MG (MMG) conditions (Rotating Wall Vessel bioreactor) for 24 hours. This setting allowed searching for MGSG by comparison of gene expression patterns in zero and 1 g gravity. In the second set - activated T-cells after culturing for 24 hours in 1g and MMG were exposed three hours before harvesting to a secondary activation stimulus (PHA) thus triggering the apoptotic pathway. Total RNA was extracted using the RNeasy isolation kit (Qiagen, Valencia, CA). Affymetrix Gene Chips (U133A), allowing testing for 18,400 human genes, were used for microarray analysis. In the first set of experiments MMG exposure resulted in altered expression of 89 genes, 10 of them were up-regulated and 79 down-regulated. In the second set, changes in expression were revealed in 85 genes, 20 were up-regulated and 65 were down-regulated. The analysis revealed that significant numbers of MGS genes are associated with signal transduction and apoptotic pathways. Interestingly, the majority of genes that responded by up- or down-regulation in the alternative sets of experiments were not the same, possibly reflecting different functional states of the examined T-lymphocyte populations. The responder genes (MGSG) might play an

Stochastic and epigenetic changes of gene expression in Arabidopsis polyploids.

PubMed

Wang, Jianlin; Tian, Lu; Madlung, Andreas; Lee, Hyeon-Se; Chen, Meng; Lee, Jinsuk J; Watson, Brian; Kagochi, Trevor; Comai, Luca; Chen, Z Jeffrey

2004-08-01

Polyploidization is an abrupt speciation mechanism for eukaryotes and is especially common in plants. However, little is known about patterns and mechanisms of gene regulation during early stages of polyploid formation. Here we analyzed differential expression patterns of the progenitors' genes among successive selfing generations and independent lineages. The synthetic Arabidopsis allotetraploid lines were produced by a genetic cross between A. thaliana and A. arenosa autotetraploids. We found that some progenitors' genes are differentially expressed in early generations, whereas other genes are silenced in late generations or among different siblings within a selfing generation, suggesting that the silencing of progenitors' genes is rapidly and/or stochastically established. Moreover, a subset of genes is affected in autotetraploid and multiple independent allotetraploid lines and in A. suecica, a natural allotetraploid derived from A. thaliana and A. arenosa, indicating locus-specific susceptibility to ploidy-dependent gene regulation. The role of DNA methylation in silencing progenitors' genes is tested in DNA-hypomethylation transgenic lines of A. suecica using RNA interference (RNAi). Two silenced genes are reactivated in both ddm1- and met1-RNAi lines, consistent with the demethylation of centromeric repeats and gene-specific regions in the genome. A rapid and stochastic process of differential gene expression is reinforced by epigenetic regulation during polyploid formation and evolution. Copyright 2004 Genetics Society of America

A multiplex branched DNA assay for parallel quantitative gene expression profiling.

PubMed

Flagella, Michael; Bui, Son; Zheng, Zhi; Nguyen, Cung Tuong; Zhang, Aiguo; Pastor, Larry; Ma, Yunqing; Yang, Wen; Crawford, Kimberly L; McMaster, Gary K; Witney, Frank; Luo, Yuling

2006-05-01

We describe a novel method to quantitatively measure messenger RNA (mRNA) expression of multiple genes directly from crude cell lysates and tissue homogenates without the need for RNA purification or target amplification. The multiplex branched DNA (bDNA) assay adapts the bDNA technology to the Luminex fluorescent bead-based platform through the use of cooperative hybridization, which ensures an exceptionally high degree of assay specificity. Using in vitro transcribed RNA as reference standards, we demonstrated that the assay is highly specific, with cross-reactivity less than 0.2%. We also determined that the assay detection sensitivity is 25,000 RNA transcripts with intra- and interplate coefficients of variance of less than 10% and less than 15%, respectively. Using three 10-gene panels designed to measure proinflammatory and apoptosis responses, we demonstrated sensitive and specific multiplex gene expression profiling directly from cell lysates. The gene expression change data demonstrate a high correlation coefficient (R(2)=0.94) compared with measurements obtained using the single-plex bDNA assay. Thus, the multiplex bDNA assay provides a powerful means to quantify the gene expression profile of a defined set of target genes in large sample populations.

Reduced opsin gene expression in a cave-dwelling fish

PubMed Central

Tobler, Michael; Coleman, Seth W.; Perkins, Brian D.; Rosenthal, Gil G.

2010-01-01

Regressive evolution of structures associated with vision in cave-dwelling organisms is the focus of intense research. Most work has focused on differences between extreme visual phenotypes: sighted, surface animals and their completely blind, cave-dwelling counterparts. We suggest that troglodytic systems, comprising multiple populations that vary along a gradient of visual function, may prove critical in understanding the mechanisms underlying initial regression in visual pathways. Gene expression assays of natural and laboratory-reared populations of the Atlantic molly (Poecilia mexicana) revealed reduced opsin expression in cave-dwelling populations compared with surface-dwelling conspecifics. Our results suggest that the reduction in opsin expression in cave-dwelling populations is not phenotypically plastic but reflects a hardwired system not rescued by exposure to light during retinal ontogeny. Changes in opsin gene expression may consequently represent a first evolutionary step in the regression of eyes in cave organisms. PMID:19740890

Polycistronic gene expression in Aspergillus niger.

PubMed

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

Transcriptome-Level Signatures in Gene Expression and Gene Expression Variability during Bacterial Adaptive Evolution.

PubMed

Erickson, Keesha E; Otoupal, Peter B; Chatterjee, Anushree

2017-01-01

Antibiotic-resistant bacteria are an increasingly serious public health concern, as strains emerge that demonstrate resistance to almost all available treatments. One factor that contributes to the crisis is the adaptive ability of bacteria, which exhibit remarkable phenotypic and gene expression heterogeneity in order to gain a survival advantage in damaging environments. This high degree of variability in gene expression across biological populations makes it a challenging task to identify key regulators of bacterial adaptation. Here, we research the regulation of adaptive resistance by investigating transcriptome profiles of Escherichia coli upon adaptation to disparate toxins, including antibiotics and biofuels. We locate potential target genes via conventional gene expression analysis as well as using a new analysis technique examining differential gene expression variability. By investigating trends across the diverse adaptation conditions, we identify a focused set of genes with conserved behavior, including those involved in cell motility, metabolism, membrane structure, and transport, and several genes of unknown function. To validate the biological relevance of the observed changes, we synthetically perturb gene expression using clustered regularly interspaced short palindromic repeat (CRISPR)-dCas9. Manipulation of select genes in combination with antibiotic treatment promotes adaptive resistance as demonstrated by an increased degree of antibiotic tolerance and heterogeneity in MICs. We study the mechanisms by which identified genes influence adaptation and find that select differentially variable genes have the potential to impact metabolic rates, mutation rates, and motility. Overall, this work provides evidence for a complex nongenetic response, encompassing shifts in gene expression and gene expression variability, which underlies adaptive resistance. IMPORTANCE Even initially sensitive bacteria can rapidly thwart antibiotic treatment through stress

A powerful approach reveals numerous expression quantitative trait haplotypes in multiple tissues.

PubMed

Ying, Dingge; Li, Mulin Jun; Sham, Pak Chung; Li, Miaoxin

2018-04-26

Recently many studies showed single nucleotide polymorphisms (SNPs) affect gene expression and contribute to development of complex traits/diseases in a tissue context-dependent manner. However, little is known about haplotype's influence on gene expression and complex traits, which reflects the interaction effect between SNPs. In the present study, we firstly proposed a regulatory region guided eQTL haplotype association analysis approach, and then systematically investigate the expression quantitative trait loci (eQTL) haplotypes in 20 different tissues by the approach. The approach has a powerful design of reducing computational burden by the utilization of regulatory predictions for candidate SNP selection and multiple testing corrections on non-independent haplotypes. The application results in multiple tissues showed that haplotype-based eQTLs not only increased the number of eQTL genes in a tissue specific manner, but were also enriched in loci that associated with complex traits in a tissue-matched manner. In addition, we found that tag SNPs of eQTL haplotypes from whole blood were selectively enriched in certain combination of regulatory elements (e.g. promoters and enhancers) according to predicted chromatin states. In summary, this eQTL haplotype detection approach, together with the application results, shed insights into synergistic effect of sequence variants on gene expression and their susceptibility to complex diseases. The executable application "eHaplo" is implemented in Java and is publicly available at http://grass.cgs.hku.hk/limx/ehaplo/. jonsonfox@gmail.com, limiaoxin@mail.sysu.edu.cn. Supplementary data are available at Bioinformatics online.

Integrated analysis of microRNAs, transcription factors and target genes expression discloses a specific molecular architecture of hyperdiploid multiple myeloma

PubMed Central

Caracciolo, Daniele; Agnelli, Luca; Neri, Antonino; Walker, Brian A.; Morgan, Gareth J.; Cannataro, Mario

2015-01-01

Multiple Myeloma (MM) is a malignancy characterized by the hyperdiploid (HD-MM) and the non-hyperdiploid (nHD-MM) subtypes. To shed light within the molecular architecture of these subtypes, we used a novel integromics approach. By annotated MM patient mRNA/microRNA (miRNA) datasets, we investigated mRNAs and miRNAs profiles with relation to changes in transcriptional regulators expression. We found that HD-MM displays specific gene and miRNA expression profiles, involving the Signal Transducer and Activator of Transcription (STAT)3 pathway as well as the Transforming Growth Factor–beta (TGFβ) and the transcription regulator Nuclear Protein-1 (NUPR1). Our data define specific molecular features of HD-MM that may translate in the identification of novel relevant druggable targets. PMID:26056083

Regulatory Architecture of Gene Expression Variation in the Threespine Stickleback Gasterosteus aculeatus

PubMed Central

Pritchard, Victoria L.; Viitaniemi, Heidi M.; McCairns, R. J. Scott; Merilä, Juha; Nikinmaa, Mikko; Primmer, Craig R.; Leder, Erica H.

2016-01-01

Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL) underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats. PMID:27836907

Global gene expression associated with hepatocarcinogenesis in adult male mice induced by in utero arsenic exposure.

PubMed

Liu, Jie; Xie, Yaxiong; Ducharme, Danica M K; Shen, Jun; Diwan, Bhalchandra A; Merrick, B Alex; Grissom, Sherry F; Tucker, Charles J; Paules, Richard S; Tennant, Raymond; Waalkes, Michael P

2006-03-01

Our previous work has shown that exposure to inorganic arsenic in utero produces hepatocellular carcinoma (HCC) in adult male mice. To explore further the molecular mechanisms of transplacental arsenic hepatocarcinogenesis, we conducted a second arsenic transplacental carcinogenesis study and used a genomewide microarray to profile arsenic-induced aberrant gene expression more extensively. Briefly, pregnant C3H mice were given drinking water containing 85 ppm arsenic as sodium arsenite or unaltered water from days 8 to 18 of gestation. The incidence of HCC in adult male offspring was increased 4-fold and tumor multiplicity 3-fold after transplacental arsenic exposure. Samples of normal liver and liver tumors were taken at autopsy for genomic analysis. Arsenic exposure in utero resulted in significant alterations (p < 0.001) in the expression of 2,010 genes in arsenic-exposed liver samples and in the expression of 2,540 genes in arsenic-induced HCC. Ingenuity Pathway Analysis revealed that significant alterations in gene expression occurred in a number of biological networks, and Myc plays a critical role in one of the primary networks. Real-time reverse transcriptase-polymerase chain reaction and Western blot analysis of selected genes/proteins showed > 90% concordance. Arsenic-altered gene expression included activation of oncogenes and HCC biomarkers, and increased expression of cell proliferation-related genes, stress proteins, and insulin-like growth factors and genes involved in cell-cell communications. Liver feminization was evidenced by increased expression of estrogen-linked genes and altered expression of genes that encode gender-related metabolic enzymes. These novel findings are in agreement with the biology and histology of arsenic-induced HCC, thereby indicating that multiple genetic events are associated with transplacental arsenic hepatocarcinogenesis.

Identification, Classification and Differential Expression of Oleosin Genes in Tung Tree (Vernicia fordii)

PubMed Central

Cao, Heping; Zhang, Lin; Tan, Xiaofeng; Long, Hongxu; Shockey, Jay M.

2014-01-01

Triacylglycerols (TAG) are the major molecules of energy storage in eukaryotes. TAG are packed in subcellular structures called oil bodies or lipid droplets. Oleosins (OLE) are the major proteins in plant oil bodies. Multiple isoforms of OLE are present in plants such as tung tree (Vernicia fordii), whose seeds are rich in novel TAG with a wide range of industrial applications. The objectives of this study were to identify OLE genes, classify OLE proteins and analyze OLE gene expression in tung trees. We identified five tung tree OLE genes coding for small hydrophobic proteins. Genome-wide phylogenetic analysis and multiple sequence alignment demonstrated that the five tung OLE genes represented the five OLE subfamilies and all contained the “proline knot” motif (PX5SPX3P) shared among 65 OLE from 19 tree species, including the sequenced genomes of Prunus persica (peach), Populus trichocarpa (poplar), Ricinus communis (castor bean), Theobroma cacao (cacao) and Vitis vinifera (grapevine). Tung OLE1, OLE2 and OLE3 belong to the S type and OLE4 and OLE5 belong to the SM type of Arabidopsis OLE. TaqMan and SYBR Green qPCR methods were used to study the differential expression of OLE genes in tung tree tissues. Expression results demonstrated that 1) All five OLE genes were expressed in developing tung seeds, leaves and flowers; 2) OLE mRNA levels were much higher in seeds than leaves or flowers; 3) OLE1, OLE2 and OLE3 genes were expressed in tung seeds at much higher levels than OLE4 and OLE5 genes; 4) OLE mRNA levels rapidly increased during seed development; and 5) OLE gene expression was well-coordinated with tung oil accumulation in the seeds. These results suggest that tung OLE genes 1–3 probably play major roles in tung oil accumulation and/or oil body development. Therefore, they might be preferred targets for tung oil engineering in transgenic plants. PMID:24516650

Identification, classification and differential expression of oleosin genes in tung tree (Vernicia fordii).

PubMed

Cao, Heping; Zhang, Lin; Tan, Xiaofeng; Long, Hongxu; Shockey, Jay M

2014-01-01

Triacylglycerols (TAG) are the major molecules of energy storage in eukaryotes. TAG are packed in subcellular structures called oil bodies or lipid droplets. Oleosins (OLE) are the major proteins in plant oil bodies. Multiple isoforms of OLE are present in plants such as tung tree (Vernicia fordii), whose seeds are rich in novel TAG with a wide range of industrial applications. The objectives of this study were to identify OLE genes, classify OLE proteins and analyze OLE gene expression in tung trees. We identified five tung tree OLE genes coding for small hydrophobic proteins. Genome-wide phylogenetic analysis and multiple sequence alignment demonstrated that the five tung OLE genes represented the five OLE subfamilies and all contained the "proline knot" motif (PX5SPX3P) shared among 65 OLE from 19 tree species, including the sequenced genomes of Prunus persica (peach), Populus trichocarpa (poplar), Ricinus communis (castor bean), Theobroma cacao (cacao) and Vitis vinifera (grapevine). Tung OLE1, OLE2 and OLE3 belong to the S type and OLE4 and OLE5 belong to the SM type of Arabidopsis OLE. TaqMan and SYBR Green qPCR methods were used to study the differential expression of OLE genes in tung tree tissues. Expression results demonstrated that 1) All five OLE genes were expressed in developing tung seeds, leaves and flowers; 2) OLE mRNA levels were much higher in seeds than leaves or flowers; 3) OLE1, OLE2 and OLE3 genes were expressed in tung seeds at much higher levels than OLE4 and OLE5 genes; 4) OLE mRNA levels rapidly increased during seed development; and 5) OLE gene expression was well-coordinated with tung oil accumulation in the seeds. These results suggest that tung OLE genes 1-3 probably play major roles in tung oil accumulation and/or oil body development. Therefore, they might be preferred targets for tung oil engineering in transgenic plants.

Genetics of Sputum Gene Expression in Chronic Obstructive Pulmonary Disease

PubMed Central

Qiu, Weiliang; Cho, Michael H.; Riley, John H.; Anderson, Wayne H.; Singh, Dave; Bakke, Per; Gulsvik, Amund; Litonjua, Augusto A.; Lomas, David A.; Crapo, James D.; Beaty, Terri H.; Celli, Bartolome R.; Rennard, Stephen; Tal-Singer, Ruth; Fox, Steven M.; Silverman, Edwin K.; Hersh, Craig P.

2011-01-01

Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus. PMID:21949713

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

Emerging Use of Gene Expression Microarrays in Plant Physiology

DOE PAGES

Wullschleger, Stan D.; Difazio, Stephen P.

2003-01-01

Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology weremore » selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.« less

Gene expression inference with deep learning

PubMed Central

Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

2016-01-01

Motivation: Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. Results: We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. Availability and implementation: D-GEX is available at https://github.com/uci-cbcl/D-GEX. Contact: xhx@ics.uci.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26873929

Gene expression inference with deep learning.

PubMed

Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

2016-06-15

Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Novel method to load multiple genes onto a mammalian artificial chromosome.

PubMed

Tóth, Anna; Fodor, Katalin; Praznovszky, Tünde; Tubak, Vilmos; Udvardy, Andor; Hadlaczky, Gyula; Katona, Robert L

2014-01-01

Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs) was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS) cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

Predicting features of breast cancer with gene expression patterns.

PubMed

Lu, Xuesong; Lu, Xin; Wang, Zhigang C; Iglehart, J Dirk; Zhang, Xuegong; Richardson, Andrea L

2008-03-01

Data from gene expression arrays hold an enormous amount of biological information. We sought to determine if global gene expression in primary breast cancers contained information about biologic, histologic, and anatomic features of the disease in individual patients. Microarray data from the tumors of 129 patients were analyzed for the ability to predict biomarkers [estrogen receptor (ER) and HER2], histologic features [grade and lymphatic-vascular invasion (LVI)], and stage parameters (tumor size and lymph node metastasis). Multiple statistical predictors were used and the prediction accuracy was determined by cross-validation error rate; multidimensional scaling (MDS) allowed visualization of the predicted states under study. Models built from gene expression data accurately predict ER and HER2 status, and divide tumor grade into high-grade and low-grade clusters; intermediate-grade tumors are not a unique group. In contrast, gene expression data is inaccurate at predicting tumor size, lymph node status or LVI. The best model for prediction of nodal status included tumor size, LVI status and pathologically defined tumor subtype (based on combinations of ER, HER2, and grade); the addition of microarray-based prediction to this model failed to improve the prediction accuracy. Global gene expression supports a binary division of ER, HER2, and grade, clearly separating tumors into two categories; intermediate values for these bio-indicators do not define intermediate tumor subsets. Results are consistent with a model of regional metastasis that depends on inherent biologic differences in metastatic propensity between breast cancer subtypes, upon which time and chance then operate.

From wild wolf to domestic dog: gene expression changes in the brain.

PubMed

Saetre, Peter; Lindberg, Julia; Leonard, Jennifer A; Olsson, Kerstin; Pettersson, Ulf; Ellegren, Hans; Bergström, Tomas F; Vilà, Carles; Jazin, Elena

2004-07-26

Despite the relatively recent divergence time between domestic dogs (Canis familiaris) and gray wolves (Canis lupus), the two species show remarkable behavioral differences. Since dogs and wolves are nearly identical at the level of DNA sequence, we hypothesize that the two species may differ in patterns of gene expression. We compare gene expression patterns in dogs, wolves and a close relative, the coyote (Canis latrans), in three parts of the brain: hypothalamus, amygdala and frontal cortex, with microarray technology. Additionally, we identify genes with region-specific expression patterns in all three species. Among the wild canids, the hypothalamus has a highly conserved expression profile. This contrasts with a marked divergence in domestic dogs. Real-time PCR experiments confirm the altered expression of two neuropeptides, CALCB and NPY. Our results suggest that strong selection on dogs for behavior during domestication may have resulted in modifications of mRNA expression patterns in a few hypothalamic genes with multiple functions. This study indicates that rapid changes in brain gene expression may not be exclusive to the development of human brains. Instead, they may provide a common mechanism for rapid adaptive changes during speciation, particularly in cases that present strong selective pressures on behavioral characters.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data.

PubMed

Cha, Kihoon; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

2015-01-01

It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

PubMed Central

2015-01-01

Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation. PMID:26043779

Photoperiod regulates multiple gene expression in the suprachiasmatic nuclei and pars tuberalis of the Siberian hamster (Phodopus sungorus).

PubMed

Johnston, Jonathan D; Ebling, Francis J P; Hazlerigg, David G

2005-06-01

Photoperiod regulates the seasonal physiology of many mammals living in temperate latitudes. Photoperiodic information is decoded by the master circadian clock in the suprachiasmatic nuclei (SCN) of the hypothalamus and then transduced via pineal melatonin secretion. This neurochemical signal is interpreted by tissues expressing melatonin receptors (e.g. the pituitary pars tuberalis, PT) to drive physiological changes. In this study we analysed the photoperiodic regulation of the circadian clockwork in the SCN and PT of the Siberian hamster. Female hamsters were exposed to either long or short photoperiod for 8 weeks and sampled at 2-h intervals across the 24-h cycle. In the SCN, rhythmic expression of the clock genes Per1, Per2, Cry1, Rev-erbalpha, and the clock-controlled genes arginine vasopressin (AVP) and d-element binding protein (DBP) was modulated by photoperiod. All of these E-box-containing genes tracked dawn, with earlier peak mRNA expression in long, compared to short, photoperiod. This response occurred irrespective of the presence of additional regulatory cis-elements, suggesting photoperiodic regulation of SCN gene expression through a common E-box-related mechanism. In long photoperiod, expression of Cry1 and Per1 in the PT tracked the onset and offset of melatonin secretion, respectively. However, whereas Cry1 tracked melatonin onset in short period, Per1 expression was not detectably rhythmic. We therefore propose that, in the SCN, photoperiodic regulation of clock gene expression primarily occurs via E-boxes, whereas melatonin-driven signal transduction drives the phasing of a subset of clock genes in the PT, independently of the E-box.

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

PubMed

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

2006-09-15

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

Distinct regulation of alternative polyadenylation and gene expression by nuclear poly(A) polymerases

PubMed Central

Li, Wencheng; Laishram, Rakesh S.; Hoque, Mainul; Ji, Zhe

2017-01-01

Abstract Polyadenylation of nascent RNA by poly(A) polymerase (PAP) is important for 3′ end maturation of almost all eukaryotic mRNAs. Most mammalian genes harbor multiple polyadenylation sites (PASs), leading to expression of alternative polyadenylation (APA) isoforms with distinct functions. How poly(A) polymerases may regulate PAS usage and hence gene expression is poorly understood. Here, we show that the nuclear canonical (PAPα and PAPγ) and non-canonical (Star-PAP) PAPs play diverse roles in PAS selection and gene expression. Deficiencies in the PAPs resulted in perturbations of gene expression, with Star-PAP impacting lowly expressed mRNAs and long-noncoding RNAs to the greatest extent. Importantly, different PASs of a gene are distinctly regulated by different PAPs, leading to widespread relative expression changes of APA isoforms. The location and surrounding sequence motifs of a PAS appear to differentiate its regulation by the PAPs. We show Star-PAP-specific PAS usage regulates the expression of the eukaryotic translation initiation factor EIF4A1, the tumor suppressor gene PTEN and the long non-coding RNA NEAT1. The Star-PAP-mediated APA of PTEN is essential for DNA damage-induced increase of PTEN protein levels. Together, our results reveal a PAS-guided and PAP-mediated paradigm for gene expression in response to cellular signaling cues. PMID:28911096

Defining global neuroendocrine gene expression patterns associated with reproductive seasonality in fish.

PubMed

Zhang, Dapeng; Xiong, Huiling; Mennigen, Jan A; Popesku, Jason T; Marlatt, Vicki L; Martyniuk, Christopher J; Crump, Kate; Cossins, Andrew R; Xia, Xuhua; Trudeau, Vance L

2009-06-05

Many vertebrates, including the goldfish, exhibit seasonal reproductive rhythms, which are a result of interactions between external environmental stimuli and internal endocrine systems in the hypothalamo-pituitary-gonadal axis. While it is long believed that differential expression of neuroendocrine genes contributes to establishing seasonal reproductive rhythms, no systems-level investigation has yet been conducted. In the present study, by analyzing multiple female goldfish brain microarray datasets, we have characterized global gene expression patterns for a seasonal cycle. A core set of genes (873 genes) in the hypothalamus were identified to be differentially expressed between May, August and December, which correspond to physiologically distinct stages that are sexually mature (prespawning), sexual regression, and early gonadal redevelopment, respectively. Expression changes of these genes are also shared by another brain region, the telencephalon, as revealed by multivariate analysis. More importantly, by examining one dataset obtained from fish in October who were kept under long-daylength photoperiod (16 h) typical of the springtime breeding season (May), we observed that the expression of identified genes appears regulated by photoperiod, a major factor controlling vertebrate reproductive cyclicity. Gene ontology analysis revealed that hormone genes and genes functionally involved in G-protein coupled receptor signaling pathway and transmission of nerve impulses are significantly enriched in an expression pattern, whose transition is located between prespawning and sexually regressed stages. The existence of seasonal expression patterns was verified for several genes including isotocin, ependymin II, GABA(A) gamma2 receptor, calmodulin, and aromatase b by independent samplings of goldfish brains from six seasonal time points and real-time PCR assays. Using both theoretical and experimental strategies, we report for the first time global gene expression

Defining Global Neuroendocrine Gene Expression Patterns Associated with Reproductive Seasonality in Fish

PubMed Central

Mennigen, Jan A.; Popesku, Jason T.; Marlatt, Vicki L.; Martyniuk, Christopher J.; Crump, Kate; Cossins, Andrew R.; Xia, Xuhua; Trudeau, Vance L.

2009-01-01

Background Many vertebrates, including the goldfish, exhibit seasonal reproductive rhythms, which are a result of interactions between external environmental stimuli and internal endocrine systems in the hypothalamo-pituitary-gonadal axis. While it is long believed that differential expression of neuroendocrine genes contributes to establishing seasonal reproductive rhythms, no systems-level investigation has yet been conducted. Methodology/Principal Findings In the present study, by analyzing multiple female goldfish brain microarray datasets, we have characterized global gene expression patterns for a seasonal cycle. A core set of genes (873 genes) in the hypothalamus were identified to be differentially expressed between May, August and December, which correspond to physiologically distinct stages that are sexually mature (prespawning), sexual regression, and early gonadal redevelopment, respectively. Expression changes of these genes are also shared by another brain region, the telencephalon, as revealed by multivariate analysis. More importantly, by examining one dataset obtained from fish in October who were kept under long-daylength photoperiod (16 h) typical of the springtime breeding season (May), we observed that the expression of identified genes appears regulated by photoperiod, a major factor controlling vertebrate reproductive cyclicity. Gene ontology analysis revealed that hormone genes and genes functionally involved in G-protein coupled receptor signaling pathway and transmission of nerve impulses are significantly enriched in an expression pattern, whose transition is located between prespawning and sexually regressed stages. The existence of seasonal expression patterns was verified for several genes including isotocin, ependymin II, GABAA gamma2 receptor, calmodulin, and aromatase b by independent samplings of goldfish brains from six seasonal time points and real-time PCR assays. Conclusions/Significance Using both theoretical and experimental

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

PubMed Central

2012-01-01

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods. Reviewers This article was reviewed by Arcady Mushegian, Byung-Soo Kim and Joel Bader. PMID:23227854

Methods to increase reproducibility in differential gene expression via meta-analysis

PubMed Central

Sweeney, Timothy E.; Haynes, Winston A.; Vallania, Francesco; Ioannidis, John P.; Khatri, Purvesh

2017-01-01

Findings from clinical and biological studies are often not reproducible when tested in independent cohorts. Due to the testing of a large number of hypotheses and relatively small sample sizes, results from whole-genome expression studies in particular are often not reproducible. Compared to single-study analysis, gene expression meta-analysis can improve reproducibility by integrating data from multiple studies. However, there are multiple choices in designing and carrying out a meta-analysis. Yet, clear guidelines on best practices are scarce. Here, we hypothesized that studying subsets of very large meta-analyses would allow for systematic identification of best practices to improve reproducibility. We therefore constructed three very large gene expression meta-analyses from clinical samples, and then examined meta-analyses of subsets of the datasets (all combinations of datasets with up to N/2 samples and K/2 datasets) compared to a ‘silver standard’ of differentially expressed genes found in the entire cohort. We tested three random-effects meta-analysis models using this procedure. We showed relatively greater reproducibility with more-stringent effect size thresholds with relaxed significance thresholds; relatively lower reproducibility when imposing extraneous constraints on residual heterogeneity; and an underestimation of actual false positive rate by Benjamini–Hochberg correction. In addition, multivariate regression showed that the accuracy of a meta-analysis increased significantly with more included datasets even when controlling for sample size. PMID:27634930

Using a periclinal chimera to unravel layer-specific gene expression in plants

PubMed Central

Filippis, Ioannis; Lopez-Cobollo, Rosa; Abbott, James; Butcher, Sarah; Bishop, Gerard J

2013-01-01

Plant organs are made from multiple cell types, and defining the expression level of a gene in any one cell or group of cells from a complex mixture is difficult. Dicotyledonous plants normally have three distinct layers of cells, L1, L2 and L3. Layer L1 is the single layer of cells making up the epidermis, layer L2 the single cell sub-epidermal layer and layer L3 constitutes the rest of the internal cells. Here we show how it is possible to harvest an organ and characterise the level of layer-specific expression by using a periclinal chimera that has its L1 layer from Solanum pennellii and its L2 and L3 layers from Solanum lycopersicum. This is possible by measuring the level of the frequency of species-specific transcripts. RNA-seq analysis enabled the genome-wide assessment of whether a gene is expressed in the L1 or L2/L3 layers. From 13 277 genes that are expressed in both the chimera and the parental lines and with at least one polymorphism between the parental alleles, we identified 382 genes that are preferentially expressed in L1 in contrast to 1159 genes in L2/L3. Gene ontology analysis shows that many genes preferentially expressed in L1 are involved in cutin and wax biosynthesis, whereas numerous genes that are preferentially expressed in L2/L3 tissue are associated with chloroplastic processes. These data indicate the use of such chimeras and provide detailed information on the level of layer-specific expression of genes. PMID:23725542

Systematic comparison of co-expression of multiple recombinant thermophilic enzymes in Escherichia coli BL21(DE3).

PubMed

Chen, Hui; Huang, Rui; Zhang, Y-H Percival

2017-06-01

The precise control of multiple heterologous enzyme expression levels in one Escherichia coli strain is important for cascade biocatalysis, metabolic engineering, synthetic biology, natural product synthesis, and studies of complexed proteins. We systematically investigated the co-expression of up to four thermophilic enzymes (i.e., α-glucan phosphorylase (αGP), phosphoglucomutase (PGM), glucose 6-phosphate dehydrogenase (G6PDH), and 6-phosphogluconate dehydrogenase (6PGDH)) in E. coli BL21(DE3) by adding T7 promoter or T7 terminator of each gene for multiple genes in tandem, changing gene alignment, and comparing one or two plasmid systems. It was found that the addition of T7 terminator after each gene was useful to decrease the influence of the upstream gene. The co-expression of the four enzymes in E. coli BL21(DE3) was demonstrated to generate two NADPH molecules from one glucose unit of maltodextrin, where NADPH was oxidized to convert xylose to xylitol. The best four-gene co-expression system was based on two plasmids (pET and pACYC) which harbored two genes. As a result, apparent enzymatic activities of the four enzymes were regulated to be at similar levels and the overall four-enzyme activity was the highest based on the formation of xylitol. This study provides useful information for the precise control of multi-enzyme-coordinated expression in E. coli BL21(DE3).

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

PubMed Central

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

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

PubMed

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

Association of abnormal morphology and altered gene expression in human preimplantation embryos.

PubMed

Wells, Dagan; Bermúdez, Mercedes G; Steuerwald, Nury; Malter, Henry E; Thornhill, Alan R; Cohen, Jacques

2005-08-01

We set out to characterize the expression of nine genes in human preimplantation embryos and determine whether abnormal morphology is associated with altered gene activity. Reverse transcription and real-time polymerase chain reaction were used to quantify the expression of multiple genes in each embryo. The genes studied have various important cellular roles (e.g., cell cycle regulation, DNA repair, and apoptosis). Research laboratory working closely with a clinical IVF practice. Over 50 embryos were donated by infertile patients (various etiologies). Among these, all major stages of preimplantation development and a variety of common morphologic abnormalities were represented. None. Quantification of mRNA transcripts. We detected an association between certain forms of abnormal morphology and disturbances of gene activity. Cellular fragmentation was associated with altered expression of several genes, including TP53, suggesting that fragmenting blastomeres are suffering stress of a type monitored by p53, possibly as a consequence of suboptimal culture conditions. Appropriate gene expression is vital for the regulation of metabolic pathways and key developmental events. Our data indicates a possible causal relationship between changes in gene expression and the formation of clinically relevant abnormal embryo morphologies. We hypothesize that embryos with expression profiles characteristic of good morphology and appropriate for their developmental stage have the greatest potential for implantation. If confirmed, this could lead to a new generation of preimplantation genetic diagnosis (PGD) tests for assessing embryo viability and predicting implantation potential.

Regulatory Architecture of Gene Expression Variation in the Threespine Stickleback Gasterosteus aculeatus.

PubMed

Pritchard, Victoria L; Viitaniemi, Heidi M; McCairns, R J Scott; Merilä, Juha; Nikinmaa, Mikko; Primmer, Craig R; Leder, Erica H

2017-01-05

Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL) underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats. Copyright © 2017 Pritchard et al.

Gene Expression Profiling of Gastric Cancer

PubMed Central

Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

2015-01-01

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

The biofilm-specific antibiotic resistance gene ndvB is important for expression of ethanol oxidation genes in Pseudomonas aeruginosa biofilms.

PubMed

Beaudoin, Trevor; Zhang, Li; Hinz, Aaron J; Parr, Christopher J; Mah, Thien-Fah

2012-06-01

Bacteria growing in biofilms are responsible for a large number of persistent infections and are often more resistant to antibiotics than are free-floating bacteria. In a previous study, we identified a Pseudomonas aeruginosa gene, ndvB, which is important for the formation of periplasmic glucans. We established that these glucans function in biofilm-specific antibiotic resistance by sequestering antibiotic molecules away from their cellular targets. In this study, we investigate another function of ndvB in biofilm-specific antibiotic resistance. DNA microarray analysis identified 24 genes that were responsive to the presence of ndvB. A subset of 20 genes, including 8 ethanol oxidation genes (ercS', erbR, exaA, exaB, eraR, pqqB, pqqC, and pqqE), was highly expressed in wild-type biofilm cells but not in ΔndvB biofilms, while 4 genes displayed the reciprocal expression pattern. Using quantitative real-time PCR, we confirmed the ndvB-dependent expression of the ethanol oxidation genes and additionally demonstrated that these genes were more highly expressed in biofilms than in planktonic cultures. Expression of erbR in ΔndvB biofilms was restored after the treatment of the biofilm with periplasmic extracts derived from wild-type biofilm cells. Inactivation of ethanol oxidation genes increased the sensitivity of biofilms to tobramycin. Together, these results reveal that ndvB affects the expression of multiple genes in biofilms and that ethanol oxidation genes are linked to biofilm-specific antibiotic resistance.

Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages.

PubMed

Reddy, Anupama; Growney, Joseph D; Wilson, Nick S; Emery, Caroline M; Johnson, Jennifer A; Ward, Rebecca; Monaco, Kelli A; Korn, Joshua; Monahan, John E; Stump, Mark D; Mapa, Felipa A; Wilson, Christopher J; Steiger, Janine; Ledell, Jebediah; Rickles, Richard J; Myer, Vic E; Ettenberg, Seth A; Schlegel, Robert; Sellers, William R; Huet, Heather A; Lehár, Joseph

2015-01-01

Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response.

Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages

PubMed Central

Reddy, Anupama; Growney, Joseph D.; Wilson, Nick S.; Emery, Caroline M.; Johnson, Jennifer A.; Ward, Rebecca; Monaco, Kelli A.; Korn, Joshua; Monahan, John E.; Stump, Mark D.; Mapa, Felipa A.; Wilson, Christopher J.; Steiger, Janine; Ledell, Jebediah; Rickles, Richard J.; Myer, Vic E.; Ettenberg, Seth A.; Schlegel, Robert; Sellers, William R.

2015-01-01

Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response. PMID:26378449

Genome-wide gene phylogeny of CIPK family in cassava and expression analysis of partial drought-induced genes

PubMed Central

Hu, Wei; Xia, Zhiqiang; Yan, Yan; Ding, Zehong; Tie, Weiwei; Wang, Lianzhe; Zou, Meiling; Wei, Yunxie; Lu, Cheng; Hou, Xiaowan; Wang, Wenquan; Peng, Ming

2015-01-01

Cassava is an important food and potential biofuel crop that is tolerant to multiple abiotic stressors. The mechanisms underlying these tolerances are currently less known. CBL-interacting protein kinases (CIPKs) have been shown to play crucial roles in plant developmental processes, hormone signaling transduction, and in the response to abiotic stress. However, no data is currently available about the CPK family in cassava. In this study, a total of 25 CIPK genes were identified from cassava genome based on our previous genome sequencing data. Phylogenetic analysis suggested that 25 MeCIPKs could be classified into four subfamilies, which was supported by exon-intron organizations and the architectures of conserved protein motifs. Transcriptomic analysis of a wild subspecies and two cultivated varieties showed that most MeCIPKs had different expression patterns between wild subspecies and cultivatars in different tissues or in response to drought stress. Some orthologous genes involved in CIPK interaction networks were identified between Arabidopsis and cassava. The interaction networks and co-expression patterns of these orthologous genes revealed that the crucial pathways controlled by CIPK networks may be involved in the differential response to drought stress in different accessions of cassava. Nine MeCIPK genes were selected to investigate their transcriptional response to various stimuli and the results showed the comprehensive response of the tested MeCIPK genes to osmotic, salt, cold, oxidative stressors, and ABA signaling. The identification and expression analysis of CIPK family suggested that CIPK genes are important components of development and multiple signal transduction pathways in cassava. The findings of this study will help lay a foundation for the functional characterization of the CIPK gene family and provide an improved understanding of abiotic stress responses and signaling transduction in cassava. PMID:26579161

Impact of angiogenesis-related gene expression on the tracer kinetics of 18F-FDG in colorectal tumors.

PubMed

Strauss, Ludwig G; Koczan, Dirk; Klippel, Sven; Pan, Leyun; Cheng, Caixia; Willis, Stefan; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2008-08-01

18F-FDG kinetics are primarily dependent on the expression of genes associated with glucose transporters and hexokinases but may be modulated by other genes. The dependency of 18F-FDG kinetics on angiogenesis-related gene expression was evaluated in this study. Patients with primary colorectal tumors (n = 25) were examined with PET and 18F-FDG within 2 days before surgery. Tissue specimens were obtained from the tumor and the normal colon during surgery, and gene expression was assessed using gene arrays. Overall, 23 angiogenesis-related genes were identified with a tumor-to-normal ratio exceeding 1.50. Analysis revealed a significant correlation between k1 and vascular endothelial growth factor (VEGF-A, r = 0.51) and between fractal dimension and angiopoietin-2 (r = 0.48). k3 was negatively correlated with VEGF-B (r = -0.46), and a positive correlation was noted for angiopoietin-like 4 gene (r = 0.42). A multiple linear regression analysis was used for the PET parameters to predict the gene expression, and a correlation coefficient of r = 0.75 was obtained for VEGF-A and of r = 0.76 for the angiopoietin-2 expression. Thus, on the basis of these multiple correlation coefficients, angiogenesis-related gene expression contributes to about 50% of the variance of the 18F-FDG kinetic data. The global 18F-FDG uptake, as measured by the standardized uptake value and influx, was not significantly correlated with angiogenesis-associated genes. 18F-FDG kinetics are modulated by angiogenesis-related genes. The transport rate for 18F-FDG (k1) is higher in tumors with a higher expression of VEGF-A and angiopoietin-2. The regression functions for the PET parameters provide the possibility to predict the gene expression of VEGF-A and angiopoietin-2.

Genome-wide co-localization of Polycomb orthologs and their effects on gene expression in human fibroblasts

PubMed Central

2014-01-01

Background Polycomb group proteins form multicomponent complexes that are important for establishing lineage-specific patterns of gene expression. Mammalian cells encode multiple permutations of the prototypic Polycomb repressive complex 1 (PRC1) with little evidence for functional specialization. An aim of this study is to determine whether the multiple orthologs that are co-expressed in human fibroblasts act on different target genes and whether their genomic location changes during cellular senescence. Results Deep sequencing of chromatin immunoprecipitated with antibodies against CBX6, CBX7, CBX8, RING1 and RING2 reveals that the orthologs co-localize at multiple sites. PCR-based validation at representative loci suggests that a further six PRC1 proteins have similar binding patterns. Importantly, sequential chromatin immunoprecipitation with antibodies against different orthologs implies that multiple variants of PRC1 associate with the same DNA. At many loci, the binding profiles have a distinctive architecture that is preserved in two different types of fibroblast. Conversely, there are several hundred loci at which PRC1 binding is cell type-specific and, contrary to expectations, the presence of PRC1 does not necessarily equate with transcriptional silencing. Interestingly, the PRC1 binding profiles are preserved in senescent cells despite changes in gene expression. Conclusions The multiple permutations of PRC1 in human fibroblasts congregate at common rather than specific sites in the genome and with overlapping but distinctive binding profiles in different fibroblasts. The data imply that the effects of PRC1 complexes on gene expression are more subtle than simply repressing the loci at which they bind. PMID:24485159

Glucocorticoid Receptor Related Genes: Genotype And Brain Gene Expression Relationships To Suicide And Major Depressive Disorder

PubMed Central

Pantazatos, Spiro P.; Huang, Yung-yu; Rosoklija, Gorazd B.; Dwork, Andrew J.; Burke, Ainsley; Arango, Victoria; Oquendo, Maria A.; Mann, J. John

2016-01-01

Introduction We tested the relationship between genotype, gene expression and suicidal behavior and MDD in live subjects and postmortem samples for three genes, associated with the hypothalamic-pituitary-adrenal axis, suicidal behavior and major depressive disorder (MDD); FK506 binding protein 5 (FKBP5), Spindle and kinetochore-associated protein 2 (SKA2) and Glucocorticoid Receptor (NR3C1). Materials and Methods Single-nucleotide polymorphisms (SNPs) and haplotypes were tested for association with suicidal behavior and MDD in a live (N=277) and a postmortem sample (N=209). RNA-seq was used to examine gene and isoform-level brain expression postmortem (Brodmann Area 9) (N=59). Expression quantitative trait loci (eQTL) relationships were examined using a public database (UK Brain Expression Consortium). Results We identified a haplotype within the FKBP5 gene, present in 47% of the live subjects, that was associated with increased risk of suicide attempt (OR=1.58, t=6.03, p=0.014). Six SNPs on this gene, three SNPs on SKA2 and one near NR3C1 showed before-adjustment association with attempted suicide, and two SNPs of SKA2 with suicide death, but none stayed significant after adjustment for multiple testing. Only the SKA2 SNPs were related to expression in the prefrontal cortex. One NR3C1 transcript had lower expression in suicide relative to non-suicide sudden death cases (b=-0.48, SE=0.12, t=-4.02, adjusted p=0.004). Conclusion We have identified an association of FKBP5 haplotype with risk of suicide attempt and found an association between suicide and altered NR3C1 gene expression in the prefrontal cortex. Our findings further implicate hypothalamic pituitary axis dysfunction in suicidal behavior. PMID:27030168

GLUCOCORTICOID RECEPTOR-RELATED GENES: GENOTYPE AND BRAIN GENE EXPRESSION RELATIONSHIPS TO SUICIDE AND MAJOR DEPRESSIVE DISORDER.

PubMed

Yin, Honglei; Galfalvy, Hanga; Pantazatos, Spiro P; Huang, Yung-Yu; Rosoklija, Gorazd B; Dwork, Andrew J; Burke, Ainsley; Arango, Victoria; Oquendo, Maria A; Mann, J John

2016-06-01

We tested the relationship between genotype, gene expression and suicidal behavior and major depressive disorder (MDD) in live subjects and postmortem samples for three genes, associated with the hypothalamic-pituitary-adrenal axis, suicidal behavior, and MDD; FK506-binding protein 5 (FKBP5), Spindle and kinetochore-associated protein 2 (SKA2), and Glucocorticoid Receptor (NR3C1). Single-nucleotide polymorphisms (SNPs) and haplotypes were tested for association with suicidal behavior and MDD in a live (N = 277) and a postmortem sample (N = 209). RNA-seq was used to examine gene and isoform-level brain expression postmortem (Brodmann Area 9; N = 59). Expression quantitative trait loci (eQTL) relationships were examined using a public database (UK Brain Expression Consortium). We identified a haplotype within the FKBP5 gene, present in 47% of the live subjects, which was associated with increased risk of suicide attempt (OR = 1.58, t = 6.03, P = .014). Six SNPs on this gene, three SNPs on SKA2, and one near NR3C1 showed before-adjustment association with attempted suicide, and two SNPs of SKA2 with suicide death, but none stayed significant after adjustment for multiple testing. Only the SKA2 SNPs were related to expression in the prefrontal cortex (pFCTX). One NR3C1 transcript had lower expression in suicide relative to nonsuicide sudden death cases (b = -0.48, SE = 0.12, t = -4.02, adjusted P = .004). We have identified an association of FKBP5 haplotype with risk of suicide attempt and found an association between suicide and altered NR3C1 gene expression in the pFCTX. Our findings further implicate hypothalamic pituitary axis dysfunction in suicidal behavior. © 2016 Wiley Periodicals, Inc.

T-cell lymphomas associated gene expression signature: Bioinformatics analysis based on gene expression Omnibus.

PubMed

Zhou, Lei-Lei; Xu, Xiao-Yue; Ni, Jie; Zhao, Xia; Zhou, Jian-Wei; Feng, Ji-Feng

2018-06-01

Due to the low incidence and the heterogeneity of subtypes, the biological process of T-cell lymphomas is largely unknown. Although many genes have been detected in T-cell lymphomas, the role of these genes in biological process of T-cell lymphomas was not further analyzed. Two qualified datasets were downloaded from Gene Expression Omnibus database. The biological functions of differentially expressed genes were evaluated by gene ontology enrichment and KEGG pathway analysis. The network for intersection genes was constructed by the cytoscape v3.0 software. Kaplan-Meier survival curves and log-rank test were employed to assess the association between differentially expressed genes and clinical characters. The intersection mRNAs were proved to be associated with fundamental processes of T-cell lymphoma cells. These intersection mRNAs were involved in the activation of some cancer-related pathways, including PI3K/AKT, Ras, JAK-STAT, and NF-kappa B signaling pathway. PDGFRA, CXCL12, and CCL19 were the most significant central genes in the signal-net analysis. The results of survival analysis are not entirely credible. Our findings uncovered aberrantly expressed genes and a complex RNA signal network in T-cell lymphomas and indicated cancer-related pathways involved in disease initiation and progression, providing a new insight for biotargeted therapy in T-cell lymphomas. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Gene Expression Measurement Module (GEMM) - A Fully Automated, Miniaturized Instrument for Measuring Gene Expression in Space

NASA Technical Reports Server (NTRS)

Pohorille, Andrew; Peyvan, Kia; Karouia, Fathi; Ricco, Antonio

2012-01-01

The capability to measure gene expression on board spacecraft opens the door to a large number of high-value experiments on the influence of the space environment on biological systems. For example, measurements of gene expression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, and determine the metabolic bases of microbial pathogenicity and drug resistance. These and other applications hold significant potential for discoveries in space biology, biotechnology, and medicine. Supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measurement of expression of several hundreds of microbial genes from multiple samples. The instrument will be capable of (1) lysing cell walls of bacteria sampled from cultures grown in space, (2) extracting and purifying RNA released from cells, (3) hybridizing the RNA on a microarray and (4) providing readout of the microarray signal, all in a single microfluidics cartridge. The device is suitable for deployment on nanosatellite platforms developed by NASA Ames' Small Spacecraft Division. To meet space and other technical constraints imposed by these platforms, a number of technical innovations are being implemented. The integration and end-to-end technological and biological validation of the instrument are carried out using as a model the photosynthetic bacterium Synechococcus elongatus, known for its remarkable metabolic diversity and resilience to adverse conditions. Each step in the measurement process-lysis, nucleic acid extraction, purification, and hybridization to an array-is assessed through comparison of the results obtained using the instrument with

Nur77 coordinately regulates expression of genes linked to glucose metabolism in skeletal muscle.

PubMed

Chao, Lily C; Zhang, Zidong; Pei, Liming; Saito, Tsugumichi; Tontonoz, Peter; Pilch, Paul F

2007-09-01

Innervation is important for normal metabolism in skeletal muscle, including insulin-sensitive glucose uptake. However, the transcription factors that transduce signals from the neuromuscular junction to the nucleus and affect changes in metabolic gene expression are not well defined. We demonstrate here that the orphan nuclear receptor Nur77 is a regulator of gene expression linked to glucose utilization in muscle. In vivo, Nur77 is preferentially expressed in glycolytic compared with oxidative muscle and is responsive to beta-adrenergic stimulation. Denervation of rat muscle compromises expression of Nur77 in parallel with that of numerous genes linked to glucose metabolism, including glucose transporter 4 and genes involved in glycolysis, glycogenolysis, and the glycerophosphate shuttle. Ectopic expression of Nur77, either in rat muscle or in C2C12 muscle cells, induces expression of a highly overlapping set of genes, including glucose transporter 4, muscle phosphofructokinase, and glycogen phosphorylase. Furthermore, selective knockdown of Nur77 in rat muscle by small hairpin RNA or genetic deletion of Nur77 in mice reduces the expression of a battery of genes involved in skeletal muscle glucose utilization in vivo. Finally, we show that Nur77 binds the promoter regions of multiple genes involved in glucose metabolism in muscle. These results identify Nur77 as a potential mediator of neuromuscular signaling in the control of metabolic gene expression.

Nur77 coordinately regulates expression of genes linked to glucose metabolism in skeletal muscle

PubMed Central

Chao, Lily C.; Zhang, Zidong; Pei, Liming; Saito, Tsugumichi; Tontonoz, Peter; Pilch, Paul F.

2008-01-01

Innervation is important for normal metabolism in skeletal muscle, including insulin-sensitive glucose uptake. However, the transcription factors that transduce signals from the neuromuscular junction to the nucleus and affect changes in metabolic gene expression are not well defined. We demonstrate here that the orphan nuclear receptor Nur77 is a regulator of gene expression linked to glucose utilization in muscle. In vivo, Nur77 is preferentially expressed in glycolytic compared to oxidative muscle and is responsive to β-adrenergic stimulation. Denervation of rat muscle compromises expression of Nur77 in parallel with that of numerous genes linked to glucose metabolism, including GLUT4 and genes involved in glycolysis, glycogenolysis, and the glycerophosphate shuttle. Ectopic expression of Nur77, either in rat muscle or in C2C12 muscle cells, induces expression of a highly overlapping set of genes, including GLUT4, muscle phosphofructokinase, and glycogen phosphorylase. Furthermore, selective knockdown of Nur77 in rat muscle by shRNA or genetic deletion of Nur77 in mice reduces the expression of a battery of genes involved in skeletal muscle glucose utilization in vivo. Finally, we show that Nur77 binds the promoter regions of multiple innervation-dependent genes in muscle. These results identify Nur77 as a potential mediator of neuromuscular signaling in the control of metabolic gene expression. PMID:17550977

Multilevel Regulation of Bacterial Gene Expression with the Combined STAR and Antisense RNA System.

PubMed

Lee, Young Je; Kim, Soo-Jung; Moon, Tae Seok

2018-03-16

Synthetic small RNA regulators have emerged as a versatile tool to predictably control bacterial gene expression. Owing to their simple design principles, small size, and highly orthogonal behavior, these engineered genetic parts have been incorporated into genetic circuits. However, efforts to achieve more sophisticated cellular functions using RNA regulators have been hindered by our limited ability to integrate different RNA regulators into complex circuits. Here, we present a combined RNA regulatory system in Escherichia coli that uses small transcription activating RNA (STAR) and antisense RNA (asRNA) to activate or deactivate target gene expression in a programmable manner. Specifically, we demonstrated that the activated target output by the STAR system can be deactivated by expressing two different types of asRNAs: one binds to and sequesters the STAR regulator, affecting the transcription process, while the other binds to the target mRNA, affecting the translation process. We improved deactivation efficiencies (up to 96%) by optimizing each type of asRNA and then integrating the two optimized asRNAs into a single circuit. Furthermore, we demonstrated that the combined STAR and asRNA system can control gene expression in a reversible way and can regulate expression of a gene in the genome. Lastly, we constructed and simultaneously tested two A AND NOT B logic gates in the same cell to show sophisticated multigene regulation by the combined system. Our approach establishes a methodology for integrating multiple RNA regulators to rationally control multiple genes.

Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

PubMed Central

Li, Xia; Rao, Shaoqi; Jiang, Wei; Li, Chuanxing; Xiao, Yun; Guo, Zheng; Zhang, Qingpu; Wang, Lihong; Du, Lei; Li, Jing; Li, Li; Zhang, Tianwen; Wang, Qing K

2006-01-01

Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network) to address the underlying regulations of genes that can span any unit(s) of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex gene regulations related to

Altered Gene Expressions and Cytogenetic Repair Efficiency in Cells with Suppressed Expression of XPA after Proton Exposure

NASA Technical Reports Server (NTRS)

Zhang, Ye; Rohde, Larry H.; Gridley, Daila S.; Mehta, Satish K.; Pierson, Duane L.; Wu, Honglu

2009-01-01

Cellular responses to damages from ionizing radiation (IR) exposure are influenced not only by the genes involved in DNA double strand break (DSB) repair, but also by non- DSB repair genes. We demonstrated previously that suppressed expression of several non-DSB repair genes, such as XPA, elevated IR-induced cytogenetic damages. In the present study, we exposed human fibroblasts that were treated with control or XPA targeting siRNA to 250 MeV protons (0 to 4 Gy), and analyzed chromosome aberrations and expressions of genes involved in DNA repair. As expected, after proton irradiation, cells with suppressed expression of XPA showed a significantly elevated frequency of chromosome aberrations compared with control siRNA treated (CS) cells. Protons caused more severe DNA damages in XPA knock-down cells, as 36% cells contained multiple aberrations compared to 25% in CS cells after 4Gy proton irradiation. Comparison of gene expressions using the real-time PCR array technique revealed that expressions of p53 and its regulated genes in irradiated XPA suppressed cells were altered similarly as in CS cells, suggesting that the impairment of IR induced DNA repair in XPA suppressed cells is p53-independent. Except for XPA, which was more than 2 fold down regulated in XPA suppressed cells, several other DNA damage sensing and repair genes (GTSE1, RBBP8, RAD51, UNG and XRCC2) were shown a more than 1.5 fold difference between XPA knock-down cells and CS cells after proton exposure. The possible involvement of these genes in the impairment of DNA repair in XPA suppressed cells will be further investigated.

Identification of genes expressed in the hermaphrodite germ line of C. elegans using SAGE

PubMed Central

Wang, Xin; Zhao, Yongjun; Wong, Kim; Ehlers, Peter; Kohara, Yuji; Jones, Steven J; Marra, Marco A; Holt, Robert A; Moerman, Donald G; Hansen, Dave

2009-01-01

Background Germ cells must progress through elaborate developmental stages from an undifferentiated germ cell to a fully differentiated gamete. Some of these stages include exiting mitosis and entering meiosis, progressing through the various stages of meiotic prophase, adopting either a male (sperm) or female (oocyte) fate, and completing meiosis. Additionally, many of the factors needed to drive embryogenesis are synthesized in the germ line. To increase our understanding of the genes that might be necessary for the formation and function of the germ line, we have constructed a SAGE library from hand dissected C. elegans hermaphrodite gonads. Results We found that 4699 genes, roughly 21% of all known C. elegans genes, are expressed in the adult hermaphrodite germ line. Ribosomal genes are highly expressed in the germ line; roughly four fold above their expression levels in the soma. We further found that 1063 of the germline-expressed genes have enriched expression in the germ line as compared to the soma. A comparison of these 1063 germline-enriched genes with a similar list of genes prepared using microarrays revealed an overlap of 460 genes, mutually reinforcing the two lists. Additionally, we identified 603 germline-enriched genes, supported by in situ expression data, which were not previously identified. We also found >4 fold enrichment for RNA binding proteins in the germ line as compared to the soma. Conclusion Using multiple technological platforms provides a more complete picture of global gene expression patterns. Genes involved in RNA metabolism are expressed at a significantly higher level in the germ line than the soma, suggesting a stronger reliance on RNA metabolism for control of the expression of genes in the germ line. Additionally, the number and expression level of germ line expressed genes on the X chromosome is lower than expected based on a random distribution. PMID:19426519

De novo Transcriptome Assembly of Chinese Kale and Global Expression Analysis of Genes Involved in Glucosinolate Metabolism in Multiple Tissues

PubMed Central

Wu, Shuanghua; Lei, Jianjun; Chen, Guoju; Chen, Hancai; Cao, Bihao; Chen, Changming

2017-01-01

Chinese kale, a vegetable of the cruciferous family, is a popular crop in southern China and Southeast Asia due to its high glucosinolate content and nutritional qualities. However, there is little research on the molecular genetics and genes involved in glucosinolate metabolism and its regulation in Chinese kale. In this study, we sequenced and characterized the transcriptomes and expression profiles of genes expressed in 11 tissues of Chinese kale. A total of 216 million 150-bp clean reads were generated using RNA-sequencing technology. From the sequences, 98,180 unigenes were assembled for the whole plant, and 49,582~98,423 unigenes were assembled for each tissue. Blast analysis indicated that a total of 80,688 (82.18%) unigenes exhibited similarity to known proteins. The functional annotation and classification tools used in this study suggested that genes principally expressed in Chinese kale, were mostly involved in fundamental processes, such as cellular and molecular functions, the signal transduction, and biosynthesis of secondary metabolites. The expression levels of all unigenes were analyzed in various tissues of Chinese kale. A large number of candidate genes involved in glucosinolate metabolism and its regulation were identified, and the expression patterns of these genes were analyzed. We found that most of the genes involved in glucosinolate biosynthesis were highly expressed in the root, petiole, and in senescent leaves. The expression patterns of ten glucosinolate biosynthetic genes from RNA-seq were validated by quantitative RT-PCR in different tissues. These results provided an initial and global overview of Chinese kale gene functions and expression activities in different tissues. PMID:28228764

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

PubMed

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

2014-09-01

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

Using a periclinal chimera to unravel layer-specific gene expression in plants.

PubMed

Filippis, Ioannis; Lopez-Cobollo, Rosa; Abbott, James; Butcher, Sarah; Bishop, Gerard J

2013-09-01

Plant organs are made from multiple cell types, and defining the expression level of a gene in any one cell or group of cells from a complex mixture is difficult. Dicotyledonous plants normally have three distinct layers of cells, L1, L2 and L3. Layer L1 is the single layer of cells making up the epidermis, layer L2 the single cell sub-epidermal layer and layer L3 constitutes the rest of the internal cells. Here we show how it is possible to harvest an organ and characterise the level of layer-specific expression by using a periclinal chimera that has its L1 layer from Solanum pennellii and its L2 and L3 layers from Solanum lycopersicum. This is possible by measuring the level of the frequency of species-specific transcripts. RNA-seq analysis enabled the genome-wide assessment of whether a gene is expressed in the L1 or L2/L3 layers. From 13 277 genes that are expressed in both the chimera and the parental lines and with at least one polymorphism between the parental alleles, we identified 382 genes that are preferentially expressed in L1 in contrast to 1159 genes in L2/L3. Gene ontology analysis shows that many genes preferentially expressed in L1 are involved in cutin and wax biosynthesis, whereas numerous genes that are preferentially expressed in L2/L3 tissue are associated with chloroplastic processes. These data indicate the use of such chimeras and provide detailed information on the level of layer-specific expression of genes. © 2013 East Malling Research The Plant Journal © 2013 John Wiley & Sons Ltd.

Reconstructing directed gene regulatory network by only gene expression data.

PubMed

Zhang, Lu; Feng, Xi Kang; Ng, Yen Kaow; Li, Shuai Cheng

2016-08-18

Accurately identifying gene regulatory network is an important task in understanding in vivo biological activities. The inference of such networks is often accomplished through the use of gene expression data. Many methods have been developed to evaluate gene expression dependencies between transcription factor and its target genes, and some methods also eliminate transitive interactions. The regulatory (or edge) direction is undetermined if the target gene is also a transcription factor. Some methods predict the regulatory directions in the gene regulatory networks by locating the eQTL single nucleotide polymorphism, or by observing the gene expression changes when knocking out/down the candidate transcript factors; regrettably, these additional data are usually unavailable, especially for the samples deriving from human tissues. In this study, we propose the Context Based Dependency Network (CBDN), a method that is able to infer gene regulatory networks with the regulatory directions from gene expression data only. To determine the regulatory direction, CBDN computes the influence of source to target by evaluating the magnitude changes of expression dependencies between the target gene and the others with conditioning on the source gene. CBDN extends the data processing inequality by involving the dependency direction to distinguish between direct and transitive relationship between genes. We also define two types of important regulators which can influence a majority of the genes in the network directly or indirectly. CBDN can detect both of these two types of important regulators by averaging the influence functions of candidate regulator to the other genes. In our experiments with simulated and real data, even with the regulatory direction taken into account, CBDN outperforms the state-of-the-art approaches for inferring gene regulatory network. CBDN identifies the important regulators in the predicted network: 1. TYROBP influences a batch of genes that are

Monoallelic Gene Expression in Mammals.

PubMed

Chess, Andrew

2016-11-23

Monoallelic expression not due to cis-regulatory sequence polymorphism poses an intriguing problem in epigenetics because it requires the unequal treatment of two segments of DNA that are present in the same nucleus and that can indeed have absolutely identical sequences. Here, I focus on a few recent developments in the field of monoallelic expression that are of particular interest and raise interesting questions for future work. One development is regarding analyses of imprinted genes, in which recent work suggests the possibility that intriguing networks of imprinted genes exist and are important for genetic and physiological studies. Another issue that has been raised in recent years by a number of publications is the question of how skewed allelic expression should be for it to be designated as monoallelic expression and, further, what methods are appropriate or inappropriate for analyzing genomic data to examine allele-specific expression. Perhaps the most exciting recent development in mammalian monoallelic expression is a clever and carefully executed analysis of genetic diversity of autosomal genes subject to random monoallelic expression (RMAE), which provides compelling evidence for distinct evolutionary forces acting on random monoallelically expressed genes.

An Integrative Genetics Approach to Identify Candidate Genes Regulating BMD: Combining Linkage, Gene Expression, and Association

PubMed Central

Farber, Charles R; van Nas, Atila; Ghazalpour, Anatole; Aten, Jason E; Doss, Sudheer; Sos, Brandon; Schadt, Eric E; Ingram-Drake, Leslie; Davis, Richard C; Horvath, Steve; Smith, Desmond J; Drake, Thomas A; Lusis, Aldons J

2009-01-01

Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification. PMID:18767929

Non-coding RNAs as regulators of gene expression and epigenetics

PubMed Central

Kaikkonen, Minna U.; Lam, Michael T.Y.; Glass, Christopher K.

2011-01-01

Genome-wide studies have revealed that mammalian genomes are pervasively transcribed. This has led to the identification and isolation of novel classes of non-coding RNAs (ncRNAs) that influence gene expression by a variety of mechanisms. Here we review the characteristics and functions of regulatory ncRNAs in chromatin remodelling and at multiple levels of transcriptional and post-transcriptional regulation. We also describe the potential roles of ncRNAs in vascular biology and in mediating epigenetic modifications that might play roles in cardiovascular disease susceptibility. The emerging recognition of the diverse functions of ncRNAs in regulation of gene expression suggests that they may represent new targets for therapeutic intervention. PMID:21558279

Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae

PubMed Central

Teste, Marie-Ange; Duquenne, Manon; François, Jean M; Parrou, Jean-Luc

2009-01-01

Background Real-time RT-PCR is the recommended method for quantitative gene expression analysis. A compulsory step is the selection of good reference genes for normalization. A few genes often referred to as HouseKeeping Genes (HSK), such as ACT1, RDN18 or PDA1 are among the most commonly used, as their expression is assumed to remain unchanged over a wide range of conditions. Since this assumption is very unlikely, a geometric averaging of multiple, carefully selected internal control genes is now strongly recommended for normalization to avoid this problem of expression variation of single reference genes. The aim of this work was to search for a set of reference genes for reliable gene expression analysis in Saccharomyces cerevisiae. Results From public microarray datasets, we selected potential reference genes whose expression remained apparently invariable during long-term growth on glucose. Using the algorithm geNorm, ALG9, TAF10, TFC1 and UBC6 turned out to be genes whose expression remained stable, independent of the growth conditions and the strain backgrounds tested in this study. We then showed that the geometric averaging of any subset of three genes among the six most stable genes resulted in very similar normalized data, which contrasted with inconsistent results among various biological samples when the normalization was performed with ACT1. Normalization with multiple selected genes was therefore applied to transcriptional analysis of genes involved in glycogen metabolism. We determined an induction ratio of 100-fold for GPH1 and 20-fold for GSY2 between the exponential phase and the diauxic shift on glucose. There was no induction of these two genes at this transition phase on galactose, although in both cases, the kinetics of glycogen accumulation was similar. In contrast, SGA1 expression was independent of the carbon source and increased by 3-fold in stationary phase. Conclusion In this work, we provided a set of genes that are suitable reference

Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae.

PubMed

Teste, Marie-Ange; Duquenne, Manon; François, Jean M; Parrou, Jean-Luc

2009-10-30

Real-time RT-PCR is the recommended method for quantitative gene expression analysis. A compulsory step is the selection of good reference genes for normalization. A few genes often referred to as HouseKeeping Genes (HSK), such as ACT1, RDN18 or PDA1 are among the most commonly used, as their expression is assumed to remain unchanged over a wide range of conditions. Since this assumption is very unlikely, a geometric averaging of multiple, carefully selected internal control genes is now strongly recommended for normalization to avoid this problem of expression variation of single reference genes. The aim of this work was to search for a set of reference genes for reliable gene expression analysis in Saccharomyces cerevisiae. From public microarray datasets, we selected potential reference genes whose expression remained apparently invariable during long-term growth on glucose. Using the algorithm geNorm, ALG9, TAF10, TFC1 and UBC6 turned out to be genes whose expression remained stable, independent of the growth conditions and the strain backgrounds tested in this study. We then showed that the geometric averaging of any subset of three genes among the six most stable genes resulted in very similar normalized data, which contrasted with inconsistent results among various biological samples when the normalization was performed with ACT1. Normalization with multiple selected genes was therefore applied to transcriptional analysis of genes involved in glycogen metabolism. We determined an induction ratio of 100-fold for GPH1 and 20-fold for GSY2 between the exponential phase and the diauxic shift on glucose. There was no induction of these two genes at this transition phase on galactose, although in both cases, the kinetics of glycogen accumulation was similar. In contrast, SGA1 expression was independent of the carbon source and increased by 3-fold in stationary phase. In this work, we provided a set of genes that are suitable reference genes for quantitative gene

NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms.

PubMed

Ruyssinck, Joeri; Huynh-Thu, Vân Anh; Geurts, Pierre; Dhaene, Tom; Demeester, Piet; Saeys, Yvan

2014-01-01

One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms) and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made publicly available.

NIMEFI: Gene Regulatory Network Inference using Multiple Ensemble Feature Importance Algorithms

PubMed Central

Ruyssinck, Joeri; Huynh-Thu, Vân Anh; Geurts, Pierre; Dhaene, Tom; Demeester, Piet; Saeys, Yvan

2014-01-01

One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms) and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made publicly available

Expressing genes do not forget their LINEs: transposable elements and gene expression

PubMed Central

Kines, Kristine J.; Belancio, Victoria P.

2012-01-01

1. ABSTRACT Historically the accumulated mass of mammalian transposable elements (TEs), particularly those located within gene boundaries, was viewed as a genetic burden potentially detrimental to the genomic landscape. This notion has been strengthened by the discovery that transposable sequences can alter the architecture of the transcriptome, not only through insertion, but also long after the integration process is completed. Insertions previously considered harmless are now known to impact the expression of host genes via modification of the transcript quality or quantity, transcriptional interference, or by the control of pathways that affect the mRNA life-cycle. Conversely, several examples of the evolutionary advantageous impact of TEs on the host gene structure that diversified the cellular transcriptome are reported. TE-induced changes in gene expression can be tissue-or disease-specific, raising the possibility that the impact of TE sequences may vary during development, among normal cell types, and between normal and disease-affected tissues. The understanding of the rules and abundance of TE-interference with gene expression is in its infancy, and its contribution to human disease and/or evolution remains largely unexplored. PMID:22201807

Permethrin induction of multiple cytochrome P450 genes in insecticide resistant mosquitoes, Culex quinquefasciatus.

PubMed

Gong, Youhui; Li, Ting; Zhang, Lee; Gao, Xiwu; Liu, Nannan

2013-01-01

The expression of some insect P450 genes can be induced by both exogenous and endogenous compounds and there is evidence to suggest that multiple constitutively overexpressed P450 genes are co-responsible for the development of resistance to permethrin in resistant mosquitoes. This study characterized the permethrin induction profiles of P450 genes known to be constitutively overexpressed in resistant mosquitoes, Culex quinquefasciatus. The gene expression in 7 of the 19 P450 genes CYP325K3v1, CYP4D42v2, CYP9J45, (CYP) CPIJ000926, CYP325G4, CYP4C38, CYP4H40 in the HAmCqG8 strain, increased more than 2-fold after exposure to permethrin at an LC50 concentration (10 ppm) compared to their acetone treated counterpart; no significant differences in the expression of these P450 genes in susceptible S-Lab mosquitoes were observed after permethrin treatment. Eleven of the fourteen P450 genes overexpressed in the MAmCqG6 strain, CYP9M10, CYP6Z12, CYP9J33, CYP9J43, CYP9J34, CYP306A1, CYP6Z15, CYP9J45, CYPPAL1, CYP4C52v1, CYP9J39, were also induced more than doubled after exposure to an LC50 (0.7 ppm) dose of permethrin. No significant induction in P450 gene expression was observed in the susceptible S-Lab mosquitoes after permethrin treatment except for CYP6Z15 and CYP9J39, suggesting that permethrin induction of these two P450 genes are common to both susceptible and resistant mosquitoes while the induction of the others are specific to insecticide resistant mosquitoes. These results demonstrate that multiple P450 genes are co-up-regulated in insecticide resistant mosquitoes through both constitutive overexpression and induction mechanisms, providing additional support for their involvement in the detoxification of insecticides and the development of insecticide resistance.

Discrete domains of gene expression in germinal layers distinguish the development of gyrencephaly

PubMed Central

de Juan Romero, Camino; Bruder, Carl; Tomasello, Ugo; Sanz-Anquela, José Miguel; Borrell, Víctor

2015-01-01

Gyrencephalic species develop folds in the cerebral cortex in a stereotypic manner, but the genetic mechanisms underlying this patterning process are unknown. We present a large-scale transcriptomic analysis of individual germinal layers in the developing cortex of the gyrencephalic ferret, comparing between regions prospective of fold and fissure. We find unique transcriptional signatures in each germinal compartment, where thousands of genes are differentially expressed between regions, including ∼80% of genes mutated in human cortical malformations. These regional differences emerge from the existence of discrete domains of gene expression, which occur at multiple locations across the developing cortex of ferret and human, but not the lissencephalic mouse. Complex expression patterns emerge late during development and map the eventual location of folds or fissures. Protomaps of gene expression within germinal layers may contribute to define cortical folds or functional areas, but our findings demonstrate that they distinguish the development of gyrencephalic cortices. PMID:25916825

Multiple Taf subunits of TFIID interact with Ino2 activation domains and contribute to expression of genes required for yeast phospholipid biosynthesis.

PubMed

Hintze, Stefan; Engelhardt, Maike; van Diepen, Laura; Witt, Eric; Schüller, Hans-Joachim

2017-12-01

Expression of phospholipid biosynthetic genes in yeast requires activator protein Ino2 which can bind to the UAS element inositol/choline-responsive element (ICRE) and trigger activation of target genes, using two separate transcriptional activation domains, TAD1 and TAD2. However, it is still unknown which cofactors mediate activation by TADs of Ino2. Here, we show that multiple subunits of basal transcription factor TFIID (TBP-associated factors Taf1, Taf4, Taf6, Taf10 and Taf12) are able to interact in vitro with activation domains of Ino2. Interaction was no longer observed with activation-defective variants of TAD1. We were able to identify two nonoverlapping regions in the N-terminus of Taf1 (aa 1-100 and aa 182-250) each of which could interact with TAD1 of Ino2 as well as with TAD4 of activator Adr1. Specific missense mutations within Taf1 domain aa 182-250 affecting basic and hydrophobic residues prevented interaction with wild-type TAD1 and caused reduced expression of INO1. Using chromatin immunoprecipitation we demonstrated Ino2-dependent recruitment of Taf1 and Taf6 to ICRE-containing promoters INO1 and CHO2. Transcriptional derepression of INO1 was no longer possible with temperature-sensitive taf1 and taf6 mutants cultivated under nonpermissive conditions. This result supports the hypothesis of Taf-dependent expression of structural genes activated by Ino2. © 2017 John Wiley & Sons Ltd.

Calcisponges have a ParaHox gene and dynamic expression of dispersed NK homeobox genes.

PubMed

Fortunato, Sofia A V; Adamski, Marcin; Ramos, Olivia Mendivil; Leininger, Sven; Liu, Jing; Ferrier, David E K; Adamska, Maja

2014-10-30

Sponges are simple animals with few cell types, but their genomes paradoxically contain a wide variety of developmental transcription factors, including homeobox genes belonging to the Antennapedia (ANTP) class, which in bilaterians encompass Hox, ParaHox and NK genes. In the genome of the demosponge Amphimedon queenslandica, no Hox or ParaHox genes are present, but NK genes are linked in a tight cluster similar to the NK clusters of bilaterians. It has been proposed that Hox and ParaHox genes originated from NK cluster genes after divergence of sponges from the lineage leading to cnidarians and bilaterians. On the other hand, synteny analysis lends support to the notion that the absence of Hox and ParaHox genes in Amphimedon is a result of secondary loss (the ghost locus hypothesis). Here we analysed complete suites of ANTP-class homeoboxes in two calcareous sponges, Sycon ciliatum and Leucosolenia complicata. Our phylogenetic analyses demonstrate that these calcisponges possess orthologues of bilaterian NK genes (Hex, Hmx and Msx), a varying number of additional NK genes and one ParaHox gene, Cdx. Despite the generation of scaffolds spanning multiple genes, we find no evidence of clustering of Sycon NK genes. All Sycon ANTP-class genes are developmentally expressed, with patterns suggesting their involvement in cell type specification in embryos and adults, metamorphosis and body plan patterning. These results demonstrate that ParaHox genes predate the origin of sponges, thus confirming the ghost locus hypothesis, and highlight the need to analyse the genomes of multiple sponge lineages to obtain a complete picture of the ancestral composition of the first animal genome.

Common inversion polymorphism at 17q21.31 affects expression of multiple genes in tissue-specific manner.

PubMed

de Jong, Simone; Chepelev, Iouri; Janson, Esther; Strengman, Eric; van den Berg, Leonard H; Veldink, Jan H; Ophoff, Roel A

2012-09-06

Chromosome 17q21.31 contains a common inversion polymorphism of approximately 900 kb in populations with European ancestry. Two divergent MAPT haplotypes, H1 and H2 are described with distinct linkage disequilibrium patterns across the region reflecting the inversion status at this locus. The MAPT H1 haplotype has been associated with progressive supranuclear palsy, corticobasal degeneration, Parkinson's disease and Alzheimer's disease, while the H2 is linked to recurrent deletion events associated with the 17q21.31 microdeletion syndrome, a disease characterized by developmental delay and learning disability. In this study, we investigate the effect of the inversion on the expression of genes in the 17q21.31 region. We find the expression of several genes in and at the borders of the inversion to be affected; specific either to whole blood or different regions of the human brain. The H1 haplotype was found to be associated with an increased expression of LRRC37A4, PLEKH1M and MAPT. In contrast, a decreased expression of MGC57346, LRRC37A and CRHR1 was associated with H1. Studies thus far have focused on the expression of MAPT in the inversion region. However, our results show that the inversion status affects expression of other genes in the 17q21.31 region as well. Given the link between the inversion status and different neurological diseases, these genes may also be involved in disease pathology, possibly in a tissue-specific manner.

Blockage of hemichannels alters gene expression in osteocytes in a high magneto-gravitational environment

PubMed Central

Xu, Huiyun; Ning, Dandan; Zhao, Dezhi; Chen, Yunhe; Zhao, Dongdong; Gu, Sumin; Jiang, Jean X.; Shang, Peng

2017-01-01

Osteocytes, the most abundant cells in bone, are highly responsive to external environmental changes. We tested how Cx43 hemichannels which mediate the exchange of small molecules between cells and extracellular environment impact genome wide gene expression under conditions of abnormal gravity and magnetic field. To this end, we subjected osteocytic MLO-Y4 cells to a high magneto-gravitational environment and used microarray to examine global gene expression and a specific blocking antibody was used to assess the role of Cx43 hemichannels. While 3 hr exposure to abnormal gravity and magnetic field had relatively minor effects on global gene expression, blocking hemichannels significantly impacted the expression of a number of genes which are involved in cell viability, apoptosis, mineral absorption, protein absorption and digestion, and focal adhesion. Also, blocking of hemichannels enriched genes in multiple signaling pathways which are enaged by TGF-beta, Jak-STAT and VEGF. These results show the role of connexin hemichannels in bone cells in high magneto-gravitational environments. PMID:27814646

aGEM: an integrative system for analyzing spatial-temporal gene-expression information

PubMed Central

Jiménez-Lozano, Natalia; Segura, Joan; Macías, José Ramón; Vega, Juanjo; Carazo, José María

2009-01-01

Motivation: The work presented here describes the ‘anatomical Gene-Expression Mapping (aGEM)’ Platform, a development conceived to integrate phenotypic information with the spatial and temporal distributions of genes expressed in the mouse. The aGEM Platform has been built by extending the Distributed Annotation System (DAS) protocol, which was originally designed to share genome annotations over the WWW. DAS is a client-server system in which a single client integrates information from multiple distributed servers. Results: The aGEM Platform provides information to answer three main questions. (i) Which genes are expressed in a given mouse anatomical component? (ii) In which mouse anatomical structures are a given gene or set of genes expressed? And (iii) is there any correlation among these findings? Currently, this Platform includes several well-known mouse resources (EMAGE, GXD and GENSAT), hosting gene-expression data mostly obtained from in situ techniques together with a broad set of image-derived annotations. Availability: The Platform is optimized for Firefox 3.0 and it is accessed through a friendly and intuitive display: http://agem.cnb.csic.es Contact: natalia@cnb.csic.es Supplementary information: Supplementary data are available at http://bioweb.cnb.csic.es/VisualOmics/aGEM/home.html and http://bioweb.cnb.csic.es/VisualOmics/index_VO.html and Bioinformatics online. PMID:19592395

PW1 gene/paternally expressed gene 3 (PW1/Peg3) identifies multiple adult stem and progenitor cell populations

PubMed Central

Besson, Vanessa; Smeriglio, Piera; Wegener, Amélie; Relaix, Frédéric; Nait Oumesmar, Brahim; Sassoon, David A.; Marazzi, Giovanna

2011-01-01

A variety of markers are invaluable for identifying and purifying stem/progenitor cells. Here we report the generation of a murine reporter line driven by Pw1 that reveals cycling and quiescent progenitor/stem cells in all adult tissues thus far examined, including the intestine, blood, testis, central nervous system, bone, skeletal muscle, and skin. Neurospheres generated from the adult PW1-reporter mouse show near 100% reporter-gene expression following a single passage. Furthermore, epidermal stem cells can be purified solely on the basis of reporter-gene expression. These cells are clonogenic, repopulate the epidermal stem-cell niches, and give rise to new hair follicles. Finally, we demonstrate that only PW1 reporter-expressing epidermal cells give rise to follicles that are capable of self-renewal following injury. Our data demonstrate that PW1 serves as an invaluable marker for competent self-renewing stem cells in a wide array of adult tissues, and the PW1-reporter mouse serves as a tool for rapid stem cell isolation and characterization. PMID:21709251

Long genes and genes with multiple splice variants are enriched in pathways linked to cancer and other multigenic diseases.

PubMed

Sahakyan, Aleksandr B; Balasubramanian, Shankar

2016-03-12

The role of random mutations and genetic errors in defining the etiology of cancer and other multigenic diseases has recently received much attention. With the view that complex genes should be particularly vulnerable to such events, here we explore the link between the simple properties of the human genes, such as transcript length, number of splice variants, exon/intron composition, and their involvement in the pathways linked to cancer and other multigenic diseases. We reveal a substantial enrichment of cancer pathways with long genes and genes that have multiple splice variants. Although the latter two factors are interdependent, we show that the overall gene length and splicing complexity increase in cancer pathways in a partially decoupled manner. Our systematic survey for the pathways enriched with top lengthy genes and with genes that have multiple splice variants reveal, along with cancer pathways, the pathways involved in various neuronal processes, cardiomyopathies and type II diabetes. We outline a correlation between the gene length and the number of somatic mutations. Our work is a step forward in the assessment of the role of simple gene characteristics in cancer and a wider range of multigenic diseases. We demonstrate a significant accumulation of long genes and genes with multiple splice variants in pathways of multigenic diseases that have already been associated with de novo mutations. Unlike the cancer pathways, we note that the pathways of neuronal processes, cardiomyopathies and type II diabetes contain genes long enough for topoisomerase-dependent gene expression to also be a potential contributing factor in the emergence of pathologies, should topoisomerases become impaired.

CRISPR Perturbation of Gene Expression Alters Bacterial Fitness under Stress and Reveals Underlying Epistatic Constraints.

PubMed

Otoupal, Peter B; Erickson, Keesha E; Escalas-Bordoy, Antoni; Chatterjee, Anushree

2017-01-20

The evolution of antibiotic resistance has engendered an impending global health crisis that necessitates a greater understanding of how resistance emerges. The impact of nongenetic factors and how they influence the evolution of resistance is a largely unexplored area of research. Here we present a novel application of CRISPR-Cas9 technology for investigating how gene expression governs the adaptive pathways available to bacteria during the evolution of resistance. We examine the impact of gene expression changes on bacterial adaptation by constructing a library of deactivated CRISPR-Cas9 synthetic devices to tune the expression of a set of stress-response genes in Escherichia coli. We show that artificially inducing perturbations in gene expression imparts significant synthetic control over fitness and growth during stress exposure. We present evidence that these impacts are reversible; strains with synthetically perturbed gene expression regained wild-type growth phenotypes upon stress removal, while maintaining divergent growth characteristics under stress. Furthermore, we demonstrate a prevailing trend toward negative epistatic interactions when multiple gene perturbations are combined simultaneously, thereby posing an intrinsic constraint on gene expression underlying adaptive trajectories. Together, these results emphasize how CRISPR-Cas9 can be employed to engineer gene expression changes that shape bacterial adaptation, and present a novel approach to synthetically control the evolution of antimicrobial resistance.

LNDriver: identifying driver genes by integrating mutation and expression data based on gene-gene interaction network.

PubMed

Wei, Pi-Jing; Zhang, Di; Xia, Junfeng; Zheng, Chun-Hou

2016-12-23

Cancer is a complex disease which is characterized by the accumulation of genetic alterations during the patient's lifetime. With the development of the next-generation sequencing technology, multiple omics data, such as cancer genomic, epigenomic and transcriptomic data etc., can be measured from each individual. Correspondingly, one of the key challenges is to pinpoint functional driver mutations or pathways, which contributes to tumorigenesis, from millions of functional neutral passenger mutations. In this paper, in order to identify driver genes effectively, we applied a generalized additive model to mutation profiles to filter genes with long length and constructed a new gene-gene interaction network. Then we integrated the mutation data and expression data into the gene-gene interaction network. Lastly, greedy algorithm was used to prioritize candidate driver genes from the integrated data. We named the proposed method Length-Net-Driver (LNDriver). Experiments on three TCGA datasets, i.e., head and neck squamous cell carcinoma, kidney renal clear cell carcinoma and thyroid carcinoma, demonstrated that the proposed method was effective. Also, it can identify not only frequently mutated drivers, but also rare candidate driver genes.

SOURCES OF VARIATION IN BASELINE GENE EXPRESSION LEVELS FROM TOXICOGENOMIC STUDY CONTROL ANIMALS ACROSS MULTIPLE LABORATORIES

EPA Science Inventory

Variations in study design are typical for toxicogenomic studies, but their impact on gene expression in control animals has not been well characterized. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Scienc...

Time-Course Analysis of Gene Expression During the Saccharomyces cerevisiae Hypoxic Response.

PubMed

Bendjilali, Nasrine; MacLeon, Samuel; Kalra, Gurmannat; Willis, Stephen D; Hossian, A K M Nawshad; Avery, Erica; Wojtowicz, Olivia; Hickman, Mark J

2017-01-05

Many cells experience hypoxia, or low oxygen, and respond by dramatically altering gene expression. In the yeast Saccharomyces cerevisiae, genes that respond are required for many oxygen-dependent cellular processes, such as respiration, biosynthesis, and redox regulation. To more fully characterize the global response to hypoxia, we exposed yeast to hypoxic conditions, extracted RNA at different times, and performed RNA sequencing (RNA-seq) analysis. Time-course statistical analysis revealed hundreds of genes that changed expression by up to 550-fold. The genes responded with varying kinetics suggesting that multiple regulatory pathways are involved. We identified most known oxygen-regulated genes and also uncovered new regulated genes. Reverse transcription-quantitative PCR (RT-qPCR) analysis confirmed that the lysine methyltransferase EFM6 and the recombinase DMC1, both conserved in humans, are indeed oxygen-responsive. Looking more broadly, oxygen-regulated genes participate in expected processes like respiration and lipid metabolism, but also in unexpected processes like amino acid and vitamin metabolism. Using principle component analysis, we discovered that the hypoxic response largely occurs during the first 2 hr and then a new steady-state expression state is achieved. Moreover, we show that the oxygen-dependent genes are not part of the previously described environmental stress response (ESR) consisting of genes that respond to diverse types of stress. While hypoxia appears to cause a transient stress, the hypoxic response is mostly characterized by a transition to a new state of gene expression. In summary, our results reveal that hypoxia causes widespread and complex changes in gene expression to prepare the cell to function with little or no oxygen. Copyright © 2017 Bendjilali et al.

Arabidopsis gene expression patterns during spaceflight

NASA Astrophysics Data System (ADS)

Paul, A.-L.; Ferl, R. J.

The exposure of Arabidopsis thaliana (Arabidopsis) plants to spaceflight environments resulted in the differential expression of hundreds of genes. A 5 day mission on orbiter Columbia in 1999 (STS-93) carried transgenic Arabidopsis plants engineered with a transgene composed of the alcohol dehydrogenase (Adh) gene promoter linked to the β -Glucuronidase (GUS) reporter gene. The plants were used to evaluate the effects of spaceflight on two fronts. First, expression patterns visualized with the Adh/GUS transgene were used to address specifically the possibility that spaceflight induces a hypoxic stress response, and to assess whether any spaceflight response was similar to control terrestrial hypoxia-induced gene expression patterns. (Paul et al., Plant Physiol. 2001, 126:613). Second, genome-wide patterns of native gene expression were evaluated utilizing the Affymetrix ATH1 GeneChip? array of 8,000 Arabidopsis genes. As a control for the veracity of the array analyses, a selection of genes identified with the arrays was further characterized with quantitative Real-Time RT PCR (ABI - TaqmanTM). Comparison of the patterns of expression for arrays of hybridized with RNA isolated from plants exposed to spaceflight compared to the control arrays revealed hundreds of genes that were differentially expressed in response to spaceflight, yet most genes that are hallmarks of hypoxic stress were unaffected. These results will be discussed in light of current models for plant responses to the spaceflight environment, and with regard to potential future flight opportunities.

Structure, Expression, Chromosomal Location and Product of the Gene Encoding Adh2 in Petunia

PubMed Central

Gregerson, R. G.; Cameron, L.; McLean, M.; Dennis, P.; Strommer, J.

1993-01-01

In most higher plants the genes encoding alcohol dehydrogenase comprise a small gene family, usually with two members. The Adh1 gene of Petunia has been cloned and analyzed, but a second identifiable gene was not recovered from any of three genomic libraries. We have therefore employed the polymerase chain reaction to obtain the major portion of a second Adh gene. From sequence, mapping and northern data we conclude this gene encodes ADH2, the major anaerobically inducible Adh gene of Petunia. The availability of both Adh1 and Adh2 from Petunia has permitted us to compare their structures and patterns of expression to those of the well-studied Adh genes of maize, of which one is highly expressed developmentally, while both are induced in response to hypoxia. Despite their evolutionary distance, evidenced by deduced amino acid sequence as well as taxonomic classification, the pairs of genes are regulated in strikingly similar ways in maize and Petunia. Our findings suggest a significant biological basis for the regulatory strategy employed by these distant species for differential expression of multiple Adh genes. PMID:8096485

Regulation of Chlamydia Gene Expression by Tandem Promoters with Different Temporal Patterns.

PubMed

Rosario, Christopher J; Tan, Ming

2016-01-15

Chlamydia is a genus of pathogenic bacteria with an unusual intracellular developmental cycle marked by temporal waves of gene expression. The three main temporal groups of chlamydial genes are proposed to be controlled by separate mechanisms of transcriptional regulation. However, we have noted genes with discrepancies, such as the early gene dnaK and the midcycle genes bioY and pgk, which have promoters controlled by the late transcriptional regulators EUO and σ(28). To resolve this issue, we analyzed the promoters of these three genes in vitro and in Chlamydia trachomatis bacteria grown in cell culture. Transcripts from the σ(28)-dependent promoter of each gene were detected only at late times in the intracellular infection, bolstering the role of σ(28) RNA polymerase in late gene expression. In each case, however, expression prior to late times was due to a second promoter that was transcribed by σ(66) RNA polymerase, which is the major form of chlamydial polymerase. These results demonstrate that chlamydial genes can be transcribed from tandem promoters with different temporal profiles, leading to a composite expression pattern that differs from the expression profile of a single promoter. In addition, tandem promoters allow a gene to be regulated by multiple mechanisms of transcriptional regulation, such as DNA supercoiling or late regulation by EUO and σ(28). We discuss how tandem promoters broaden the repertoire of temporal gene expression patterns in the chlamydial developmental cycle and can be used to fine-tune the expression of specific genes. Chlamydia is a pathogenic bacterium that is responsible for the majority of infectious disease cases reported to the CDC each year. It causes an intracellular infection that is characterized by coordinated expression of chlamydial genes in temporal waves. Chlamydial transcription has been shown to be regulated by DNA supercoiling, alternative forms of RNA polymerase, and transcription factors, but the number

The mouse Gtl2 gene is differentially expressed during embryonic development, encodes multiple alternatively spliced transcripts, and may act as an RNA.

PubMed

Schuster-Gossler, K; Bilinski, P; Sado, T; Ferguson-Smith, A; Gossler, A

1998-06-01

We have isolated a novel mouse gene (Gtl2) from the site of a gene trap integration (Gtl2lacZ) that gave rise to developmentally regulated lacZ expression, and a dominant parental-origin-dependent phenotype. Heterozygous Gtl2lacZ mice that inherited the transgene from the father showed a proportionate dwarfism phenotype, whereas the penetrance and expressivity of the phenotype was strongly reduced in Gtl2lacZ mice that inherited the transgene from the mother. Gtl2 expression is highly similar to the beta-galactosidase staining pattern, and is down-regulated but not abolished in mice carrying the Gtl2lacZ insertion. In early postimplantation embryos, Gtl2 is expressed in the visceral yolk sac and embryonic ectoderm. During subsequent development and organogenesis, Gtl2 transcripts are abundant in the paraxial mesoderm closely correlated with myogenic differentiation, in parts of the central nervous system, and in the epithelial ducts of developing excretory organs. The Gtl2 gene gives rise to various differentially spliced transcripts, which contain multiple small open reading frames (ORF). However, none of the ATG codons of these ORFs is in the context of a strong Kozak consensus sequence for initiation of translation, suggesting that Gtl2 might function as an RNA. Nuclear Gtl2 RNA was detected in a temporally and spatially regulated manner, and partially processed Gtl2 transcripts were readily detected in Northern blot hybridizations of polyadenylated RNA, suggesting that primary Gtl2 transcripts are differently processed in various cell types during development. Gtl2 transcript levels are present in parthenogenic embryos but may be reduced, consistent with the pattern of inheritance of the Gtl2lacZ phenotype.

Selection of housekeeping genes for gene expression studies in the adult rat submandibular gland under normal, inflamed, atrophic and regenerative states

PubMed Central

Silver, Nicholas; Cotroneo, Emanuele; Proctor, Gordon; Osailan, Samira; Paterson, Katherine L; Carpenter, Guy H

2008-01-01

Background Real-time PCR is a reliable tool with which to measure mRNA transcripts, and provides valuable information on gene expression profiles. Endogenous controls such as housekeeping genes are used to normalise mRNA levels between samples for sensitive comparisons of mRNA transcription. Selection of the most stable control gene(s) is therefore critical for the reliable interpretation of gene expression data. For the purpose of this study, 7 commonly used housekeeping genes were investigated in salivary submandibular glands under normal, inflamed, atrophic and regenerative states. Results The program NormFinder identified the suitability of HPRT to use as a single gene for normalisation within the normal, inflamed and regenerative states, and GAPDH in the atrophic state. For normalisation to multiple housekeeping genes, for each individual state, the optimal number of housekeeping genes as given by geNorm was: ACTB/UBC in the normal, ACTB/YWHAZ in the inflamed, ACTB/HPRT in the atrophic and ACTB/GAPDH in the regenerative state. The most stable housekeeping gene identified between states (compared to normal) was UBC. However, ACTB, identified as one of the most stably expressed genes within states, was found to be one of the most variable between states. Furthermore we demonstrated that normalising between states to ACTB, rather than UBC, introduced an approximately 3 fold magnitude of error. Conclusion Using NormFinder, our studies demonstrated the suitability of HPRT to use as a single gene for normalisation within the normal, inflamed and regenerative groups and GAPDH in the atrophic group. However, if normalising to multiple housekeeping genes, we recommend normalising to those identified by geNorm. For normalisation across the physiological states, we recommend the use of UBC. PMID:18637167

Discovery of error-tolerant biclusters from noisy gene expression data.

PubMed

Gupta, Rohit; Rao, Navneet; Kumar, Vipin

2011-11-24

An important analysis performed on microarray gene-expression data is to discover biclusters, which denote groups of genes that are coherently expressed for a subset of conditions. Various biclustering algorithms have been proposed to find different types of biclusters from these real-valued gene-expression data sets. However, these algorithms suffer from several limitations such as inability to explicitly handle errors/noise in the data; difficulty in discovering small bicliusters due to their top-down approach; inability of some of the approaches to find overlapping biclusters, which is crucial as many genes participate in multiple biological processes. Association pattern mining also produce biclusters as their result and can naturally address some of these limitations. However, traditional association mining only finds exact biclusters, which limits its applicability in real-life data sets where the biclusters may be fragmented due to random noise/errors. Moreover, as they only work with binary or boolean attributes, their application on gene-expression data require transforming real-valued attributes to binary attributes, which often results in loss of information. Many past approaches have tried to address the issue of noise and handling real-valued attributes independently but there is no systematic approach that addresses both of these issues together. In this paper, we first propose a novel error-tolerant biclustering model, 'ET-bicluster', and then propose a bottom-up heuristic-based mining algorithm to sequentially discover error-tolerant biclusters directly from real-valued gene-expression data. The efficacy of our proposed approach is illustrated by comparing it with a recent approach RAP in the context of two biological problems: discovery of functional modules and discovery of biomarkers. For the first problem, two real-valued S.Cerevisiae microarray gene-expression data sets are used to demonstrate that the biclusters obtained from ET

A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays

PubMed Central

Zuckerman, Neta S.; Noam, Yair; Goldsmith, Andrea J.; Lee, Peter P.

2013-01-01

Gene expression analysis is generally performed on heterogeneous tissue samples consisting of multiple cell types. Current methods developed to separate heterogeneous gene expression rely on prior knowledge of the cell-type composition and/or signatures - these are not available in most public datasets. We present a novel method to identify the cell-type composition, signatures and proportions per sample without need for a-priori information. The method was successfully tested on controlled and semi-controlled datasets and performed as accurately as current methods that do require additional information. As such, this method enables the analysis of cell-type specific gene expression using existing large pools of publically available microarray datasets. PMID:23990767

Evolution of Daily Gene Co-expression Patterns from Algae to Plants

PubMed Central

de los Reyes, Pedro; Romero-Campero, Francisco J.; Ruiz, M. Teresa; Romero, José M.; Valverde, Federico

2017-01-01

Daily rhythms play a key role in transcriptome regulation in plants and microalgae orchestrating responses that, among other processes, anticipate light transitions that are essential for their metabolism and development. The recent accumulation of genome-wide transcriptomic data generated under alternating light:dark periods from plants and microalgae has made possible integrative and comparative analysis that could contribute to shed light on the evolution of daily rhythms in the green lineage. In this work, RNA-seq and microarray data generated over 24 h periods in different light regimes from the eudicot Arabidopsis thaliana and the microalgae Chlamydomonas reinhardtii and Ostreococcus tauri have been integrated and analyzed using gene co-expression networks. This analysis revealed a reduction in the size of the daily rhythmic transcriptome from around 90% in Ostreococcus, being heavily influenced by light transitions, to around 40% in Arabidopsis, where a certain independence from light transitions can be observed. A novel Multiple Bidirectional Best Hit (MBBH) algorithm was applied to associate single genes with a family of potential orthologues from evolutionary distant species. Gene duplication, amplification and divergence of rhythmic expression profiles seems to have played a central role in the evolution of gene families in the green lineage such as Pseudo Response Regulators (PRRs), CONSTANS-Likes (COLs), and DNA-binding with One Finger (DOFs). Gene clustering and functional enrichment have been used to identify groups of genes with similar rhythmic gene expression patterns. The comparison of gene clusters between species based on potential orthologous relationships has unveiled a low to moderate level of conservation of daily rhythmic expression patterns. However, a strikingly high conservation was found for the gene clusters exhibiting their highest and/or lowest expression value during the light transitions. PMID:28751903

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis.

PubMed

Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu

2003-11-07

To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s).

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis

PubMed Central

Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu

2003-01-01

Background To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. Results We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. Conclusion PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s). PMID:14604444

MeSH key terms for validation and annotation of gene expression clusters

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

Rechtsteiner, A.; Rocha, L. M.

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 whomore » 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

Gene Expression Analyses of Subchondral Bone in Early Experimental Osteoarthritis by Microarray

PubMed Central

Chen, YuXian; Shen, Jun; Lu, HuaDing; Zeng, Chun; Ren, JianHua; Zeng, Hua; Li, ZhiFu; Chen, ShaoMing; Cai, DaoZhang; Zhao, Qing

2012-01-01

Osteoarthritis (OA) is a degenerative joint disease that affects both cartilage and bone. A better understanding of the early molecular changes in subchondral bone may help elucidate the pathogenesis of OA. We used microarray technology to investigate the time course of molecular changes in the subchondral bone in the early stages of experimental osteoarthritis in a rat model. We identified 2,234 differentially expressed (DE) genes at 1 week, 1,944 at 2 weeks and 1,517 at 4 weeks post-surgery. Further analyses of the dysregulated genes indicated that the events underlying subchondral bone remodeling occurred sequentially and in a time-dependent manner at the gene expression level. Some of the identified dysregulated genes that were identified have suspected roles in bone development or remodeling; these genes include Alp, Igf1, Tgf β1, Postn, Mmp3, Tnfsf11, Acp5, Bmp5, Aspn and Ihh. The differences in the expression of these genes were confirmed by real-time PCR, and the results indicated that our microarray data accurately reflected gene expression patterns characteristic of early OA. To validate the results of our microarray analysis at the protein level, immunohistochemistry staining was used to investigate the expression of Mmp3 and Aspn protein in tissue sections. These analyses indicate that Mmp3 protein expression completely matched the results of both the microarray and real-time PCR analyses; however, Aspn protein expression was not observed to differ at any time. In summary, our study demonstrated a simple method of separation of subchondral bone sample from the knee joint of rat, which can effectively avoid bone RNA degradation. These findings also revealed the gene expression profiles of subchondral bone in the rat OA model at multiple time points post-surgery and identified important DE genes with known or suspected roles in bone development or remodeling. These genes may be novel diagnostic markers or therapeutic targets for OA. PMID:22384228

A BAC-bacterial recombination method to generate physically linked multiple gene reporter DNA constructs.

PubMed

Maye, Peter; Stover, Mary Louise; Liu, Yaling; Rowe, David W; Gong, Shiaochin; Lichtler, Alexander C

2009-03-13

Reporter gene mice are valuable animal models for biological research providing a gene expression readout that can contribute to cellular characterization within the context of a developmental process. With the advancement of bacterial recombination techniques to engineer reporter gene constructs from BAC genomic clones and the generation of optically distinguishable fluorescent protein reporter genes, there is an unprecedented capability to engineer more informative transgenic reporter mouse models relative to what has been traditionally available. We demonstrate here our first effort on the development of a three stage bacterial recombination strategy to physically link multiple genes together with their respective fluorescent protein (FP) reporters in one DNA fragment. This strategy uses bacterial recombination techniques to: (1) subclone genes of interest into BAC linking vectors, (2) insert desired reporter genes into respective genes and (3) link different gene-reporters together. As proof of concept, we have generated a single DNA fragment containing the genes Trap, Dmp1, and Ibsp driving the expression of ECFP, mCherry, and Topaz FP reporter genes, respectively. Using this DNA construct, we have successfully generated transgenic reporter mice that retain two to three gene readouts. The three stage methodology to link multiple genes with their respective fluorescent protein reporter works with reasonable efficiency. Moreover, gene linkage allows for their common chromosomal integration into a single locus. However, the testing of this multi-reporter DNA construct by transgenesis does suggest that the linkage of two different genes together, despite their large size, can still create a positional effect. We believe that gene choice, genomic DNA fragment size and the presence of endogenous insulator elements are critical variables.

Alterations in gene expression and DNA methylation during murine and human lung alveolar septation.

PubMed

Cuna, Alain; Halloran, Brian; Faye-Petersen, Ona; Kelly, David; Crossman, David K; Cui, Xiangqin; Pandit, Kusum; Kaminski, Naftali; Bhattacharya, Soumyaroop; Ahmad, Ausaf; Mariani, Thomas J; Ambalavanan, Namasivayam

2015-07-01

DNA methylation, a major epigenetic mechanism, may regulate coordinated expression of multiple genes at specific time points during alveolar septation in lung development. The objective of this study was to identify genes regulated by methylation during normal septation in mice and during disordered septation in bronchopulmonary dysplasia. In mice, newborn lungs (preseptation) and adult lungs (postseptation) were evaluated by microarray analysis of gene expression and immunoprecipitation of methylated DNA followed by sequencing (MeDIP-Seq). In humans, microarray gene expression data were integrated with genome-wide DNA methylation data from bronchopulmonary dysplasia versus preterm and term lung. Genes with reciprocal changes in expression and methylation, suggesting regulation by DNA methylation, were identified. In mice, 95 genes with inverse correlation between expression and methylation during normal septation were identified. In addition to genes known to be important in lung development (Wnt signaling, Angpt2, Sox9, etc.) and its extracellular matrix (Tnc, Eln, etc.), genes involved with immune and antioxidant defense (Stat4, Sod3, Prdx6, etc.) were also observed. In humans, 23 genes were differentially methylated with reciprocal changes in expression in bronchopulmonary dysplasia compared with preterm or term lung. Genes of interest included those involved with detoxifying enzymes (Gstm3) and transforming growth factor-β signaling (bone morphogenetic protein 7 [Bmp7]). In terms of overlap, 20 genes and three pathways methylated during mouse lung development also demonstrated changes in methylation between preterm and term human lung. Changes in methylation correspond to altered expression of a number of genes associated with lung development, suggesting that DNA methylation of these genes may regulate normal and abnormal alveolar septation.

Cross-Study Homogeneity of Psoriasis Gene Expression in Skin across a Large Expression Range

PubMed Central

Kerkof, Keith; Timour, Martin; Russell, Christopher B.

2013-01-01

Background In psoriasis, only limited overlap between sets of genes identified as differentially expressed (psoriatic lesional vs. psoriatic non-lesional) was found using statistical and fold-change cut-offs. To provide a framework for utilizing prior psoriasis data sets we sought to understand the consistency of those sets. Methodology/Principal Findings Microarray expression profiling and qRT-PCR were used to characterize gene expression in PP and PN skin from psoriasis patients. cDNA (three new data sets) and cRNA hybridization (four existing data sets) data were compared using a common analysis pipeline. Agreement between data sets was assessed using varying qualitative and quantitative cut-offs to generate a DEG list in a source data set and then using other data sets to validate the list. Concordance increased from 67% across all probe sets to over 99% across more than 10,000 probe sets when statistical filters were employed. The fold-change behavior of individual genes tended to be consistent across the multiple data sets. We found that genes with <2-fold change values were quantitatively reproducible between pairs of data-sets. In a subset of transcripts with a role in inflammation changes detected by microarray were confirmed by qRT-PCR with high concordance. For transcripts with both PN and PP levels within the microarray dynamic range, microarray and qRT-PCR were quantitatively reproducible, including minimal fold-changes in IL13, TNFSF11, and TNFRSF11B and genes with >10-fold changes in either direction such as CHRM3, IL12B and IFNG. Conclusions/Significance Gene expression changes in psoriatic lesions were consistent across different studies, despite differences in patient selection, sample handling, and microarray platforms but between-study comparisons showed stronger agreement within than between platforms. We could use cut-offs as low as log10(ratio) = 0.1 (fold-change = 1.26), generating larger gene lists that validate on independent data

Candidate genes for panhypopituitarism identified by gene expression profiling

PubMed Central

Mortensen, Amanda H.; MacDonald, James W.; Ghosh, Debashis

2011-01-01

Mutations in the transcription factors PROP1 and PIT1 (POU1F1) lead to pituitary hormone deficiency and hypopituitarism in mice and humans. The dysmorphology of developing Prop1 mutant pituitaries readily distinguishes them from those of Pit1 mutants and normal mice. This and other features suggest that Prop1 controls the expression of genes besides Pit1 that are important for pituitary cell migration, survival, and differentiation. To identify genes involved in these processes we used microarray analysis of gene expression to compare pituitary RNA from newborn Prop1 and Pit1 mutants and wild-type littermates. Significant differences in gene expression were noted between each mutant and their normal littermates, as well as between Prop1 and Pit1 mutants. Otx2, a gene critical for normal eye and pituitary development in humans and mice, exhibited elevated expression specifically in Prop1 mutant pituitaries. We report the spatial and temporal regulation of Otx2 in normal mice and Prop1 mutants, and the results suggest Otx2 could influence pituitary development by affecting signaling from the ventral diencephalon and regulation of gene expression in Rathke's pouch. The discovery that Otx2 expression is affected by Prop1 deficiency provides support for our hypothesis that identifying molecular differences in mutants will contribute to understanding the molecular mechanisms that control pituitary organogenesis and lead to human pituitary disease. PMID:21828248

FastGCN: A GPU Accelerated Tool for Fast Gene Co-Expression Networks

PubMed Central

Liang, Meimei; Zhang, Futao; Jin, Gulei; Zhu, Jun

2015-01-01

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. PMID:25602758

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

PubMed

Liang, Meimei; Zhang, Futao; Jin, Gulei; Zhu, Jun

2015-01-01

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.

Gene expression profile of steroid-induced necrosis of femoral head of rats.

PubMed

Tong, Peijian; Wu, Chengliang; Jin, Hongting; Mao, Qiang; Yu, Nanze; Holz, Jonathan D; Shan, Letian; Liu, Hui; Xiao, Luwei

2011-10-01

The key to treating steroid-induced necrosis of femoral heads (SINFH) is early diagnosis. Dramatic improvements in diagnosis could be made if the pathogenesis of SINFH was more fully understood; however, the underlying mechanism of this disease is currently unknown. To explore the potential mechanism of SINFH, we performed gene array analysis on a rat model of the disease and compare the expression profile with that of normal rats. A quantitative RT-PCR and immunohistochemistry (IHC) assays were used to confirm the microarray results. Compared to the control group, 190 genes in the experimental group were differentially expressed, with 52 up-regulated and 138 down-regulated. Of these genes, 102 are known (deposited in GenBank), while 88 of them are unknown. The known genes can be divided into several families according to their biological functions, such as oxidative stress, apoptosis, signal transduction, angiogenesis, extracellular matrix, lipid metabolism, and transcription related genes. The results of quantitative RT-PCR and IHC were consistent with gene chip results. Our findings indicate that many genes involved in diverse signaling pathways were differentially expressed between SINFH rats and normal rats. Furthermore, our findings suggest that the development of SINFH is a complicated and dynamic process affected by multiple factors and signaling pathways and regulated by various genes.

Alternative-splicing-mediated gene expression

NASA Astrophysics Data System (ADS)

Wang, Qianliang; Zhou, Tianshou

2014-01-01

Alternative splicing (AS) is a fundamental process during gene expression and has been found to be ubiquitous in eukaryotes. However, how AS impacts gene expression levels both quantitatively and qualitatively remains to be fully explored. Here, we analyze two common models of gene expression, each incorporating a simple splice mechanism that a pre-mRNA is spliced into two mature mRNA isoforms in a probabilistic manner. In the constitutive expression case, we show that the steady-state molecular numbers of two mature mRNA isoforms follow mutually independent Poisson distributions. In the bursting expression case, we demonstrate that the tail decay of the steady-state distribution for both mature mRNA isoforms that in general are not mutually independent can be characterized by the product of mean burst size and splicing probability. In both cases, we find that AS can efficiently modulate both the variability (measured by variance) and the noise level of the total mature mRNA, and in particular, the latter is always lower than the noise level of the pre-mRNA, implying that AS always reduces the noise. These results altogether reveal that AS is a mechanism of efficiently controlling the gene expression noise.

Evolution and expression analysis of the grape (Vitis vinifera L.) WRKY gene family.

PubMed

Guo, Chunlei; Guo, Rongrong; Xu, Xiaozhao; Gao, Min; Li, Xiaoqin; Song, Junyang; Zheng, Yi; Wang, Xiping

2014-04-01

WRKY proteins comprise a large family of transcription factors that play important roles in plant defence regulatory networks, including responses to various biotic and abiotic stresses. To date, no large-scale study of WRKY genes has been undertaken in grape (Vitis vinifera L.). In this study, a total of 59 putative grape WRKY genes (VvWRKY) were identified and renamed on the basis of their respective chromosome distribution. A multiple sequence alignment analysis using all predicted grape WRKY genes coding sequences, together with those from Arabidopsis thaliana and tomato (Solanum lycopersicum), indicated that the 59 VvWRKY genes can be classified into three main groups (I-III). An evaluation of the duplication events suggested that several WRKY genes arose before the divergence of the grape and Arabidopsis lineages. Moreover, expression profiles derived from semiquantitative PCR and real-time quantitative PCR analyses showed distinct expression patterns in various tissues and in response to different treatments. Four VvWRKY genes showed a significantly higher expression in roots or leaves, 55 responded to varying degrees to at least one abiotic stress treatment, and the expression of 38 were altered following powdery mildew (Erysiphe necator) infection. Most VvWRKY genes were downregulated in response to abscisic acid or salicylic acid treatments, while the expression of a subset was upregulated by methyl jasmonate or ethylene treatments.

Evolution and expression analysis of the grape (Vitis vinifera L.) WRKY gene family

PubMed Central

Guo, Chunlei; Guo, Rongrong; Wang, Xiping

2014-01-01

WRKY proteins comprise a large family of transcription factors that play important roles in plant defence regulatory networks, including responses to various biotic and abiotic stresses. To date, no large-scale study of WRKY genes has been undertaken in grape (Vitis vinifera L.). In this study, a total of 59 putative grape WRKY genes (VvWRKY) were identified and renamed on the basis of their respective chromosome distribution. A multiple sequence alignment analysis using all predicted grape WRKY genes coding sequences, together with those from Arabidopsis thaliana and tomato (Solanum lycopersicum), indicated that the 59 VvWRKY genes can be classified into three main groups (I–III). An evaluation of the duplication events suggested that several WRKY genes arose before the divergence of the grape and Arabidopsis lineages. Moreover, expression profiles derived from semiquantitative PCR and real-time quantitative PCR analyses showed distinct expression patterns in various tissues and in response to different treatments. Four VvWRKY genes showed a significantly higher expression in roots or leaves, 55 responded to varying degrees to at least one abiotic stress treatment, and the expression of 38 were altered following powdery mildew (Erysiphe necator) infection. Most VvWRKY genes were downregulated in response to abscisic acid or salicylic acid treatments, while the expression of a subset was upregulated by methyl jasmonate or ethylene treatments. PMID:24510937

Haplotypes and gene expression implicate the MAPT region for Parkinson disease

PubMed Central

Tobin, J.E.; Latourelle, J.C.; Lew, M.F.; Klein, C.; Suchowersky, O.; Shill, H.A.; Golbe, L.I.; Mark, M.H.; Growdon, J.H.; Wooten, G.F.; Racette, B.A.; Perlmutter, J.S.; Watts, R.; Guttman, M.; Baker, K.B.; Goldwurm, S.; Pezzoli, G.; Singer, C.; Saint-Hilaire, M.H.; Hendricks, A.E.; Williamson, S.; Nagle, M.W.; Wilk, J.B.; Massood, T.; Laramie, J.M.; DeStefano, A.L.; Litvan, I.; Nicholson, G.; Corbett, A.; Isaacson, S.; Burn, D.J.; Chinnery, P.F.; Pramstaller, P.P.; Sherman, S.; Al-hinti, J.; Drasby, E.; Nance, M.; Moller, A.T.; Ostergaard, K.; Roxburgh, R.; Snow, B.; Slevin, J.T.; Cambi, F.; Gusella, J.F.; Myers, R.H.

2009-01-01

Background Microtubule-associated protein tau (MAPT) has been associated with several neurodegenerative disorders including forms of parkinsonism and Parkinson disease (PD). We evaluated the association of the MAPT region with PD in a large cohort of familial PD cases recruited by the GenePD Study. In addition, postmortem brain samples from patients with PD and neurologically normal controls were used to evaluate whether the expression of the 3-repeat and 4-repeat isoforms of MAPT, and neighboring genes Saitohin (STH) and KIAA1267, are altered in PD cerebellum. Methods Twenty-one single-nucleotide polymorphisms (SNPs) in the region of MAPT on chromosome 17q21 were genotyped in the GenePD Study. Single SNPs and haplotypes, including the H1 haplotype, were evaluated for association to PD. Relative quantification of gene expression was performed using real-time RT-PCR. Results After adjusting for multiple comparisons, SNP rs1800547 was significantly associated with PD affection. While the H1 haplotype was associated with a significantly increased risk for PD, a novel H1 subhaplotype was identified that predicted a greater increased risk for PD. The expression of 4-repeat MAPT, STH, and KIAA1267 was significantly increased in PD brains relative to controls. No difference in expression was observed for 3-repeat MAPT. Conclusions This study supports a role for MAPT in the pathogenesis of familial and idiopathic Parkinson disease (PD). Interestingly, the results of the gene expression studies suggest that other genes in the vicinity of MAPT, specifically STH and KIAA1267, may also have a role in PD and suggest complex effects for the genes in this region on PD risk. PMID:18509094

Mapping of Gene Expression Reveals CYP27A1 as a Susceptibility Gene for Sporadic ALS

PubMed Central

van Rheenen, Wouter; Franke, Lude; Jansen, Ritsert C.; van Es, Michael A.; van Vught, Paul W. J.; Blauw, Hylke M.; Groen, Ewout J. N.; Horvath, Steve; Estrada, Karol; Rivadeneira, Fernando; Hofman, Albert; Uitterlinden, Andre G.; Robberecht, Wim; Andersen, Peter M.; Melki, Judith; Meininger, Vincent; Hardiman, Orla; Landers, John E.; Brown, Robert H.; Shatunov, Aleksey; Shaw, Christopher E.; Leigh, P. Nigel; Al-Chalabi, Ammar; Ophoff, Roel A.

2012-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive, neurodegenerative disease characterized by loss of upper and lower motor neurons. ALS is considered to be a complex trait and genome-wide association studies (GWAS) have implicated a few susceptibility loci. However, many more causal loci remain to be discovered. Since it has been shown that genetic variants associated with complex traits are more likely to be eQTLs than frequency-matched variants from GWAS platforms, we conducted a two-stage genome-wide screening for eQTLs associated with ALS. In addition, we applied an eQTL analysis to finemap association loci. Expression profiles using peripheral blood of 323 sporadic ALS patients and 413 controls were mapped to genome-wide genotyping data. Subsequently, data from a two-stage GWAS (3,568 patients and 10,163 controls) were used to prioritize eQTLs identified in the first stage (162 ALS, 207 controls). These prioritized eQTLs were carried forward to the second sample with both gene-expression and genotyping data (161 ALS, 206 controls). Replicated eQTL SNPs were then tested for association in the second-stage GWAS data to find SNPs associated with disease, that survived correction for multiple testing. We thus identified twelve cis eQTLs with nominally significant associations in the second-stage GWAS data. Eight SNP-transcript pairs of highest significance (lowest p = 1.27×10−51) withstood multiple-testing correction in the second stage and modulated CYP27A1 gene expression. Additionally, we show that C9orf72 appears to be the only gene in the 9p21.2 locus that is regulated in cis, showing the potential of this approach in identifying causative genes in association loci in ALS. This study has identified candidate genes for sporadic ALS, most notably CYP27A1. Mutations in CYP27A1 are causal to cerebrotendinous xanthomatosis which can present as a clinical mimic of ALS with progressive upper motor neuron loss, making it a plausible susceptibility gene for

Transient GFP expression in Nicotiana plumbaginifolia suspension cells: the role of gene silencing, cell death and T-DNA loss.

PubMed

Weld, R; Heinemann, J; Eady, C

2001-03-01

The transient nature of T-DNA expression was studied with a gfp reporter gene transferred to Nicotiana plumbaginifolia suspension cells from Agrobacterium tumefaciens. Individual GFP-expressing protoplasts were isolated after 4 days' co-cultivation. The protoplasts were cultured without selection and 4 weeks later the surviving proto-calluses were again screened for GFP expression. Of the proto-calluses initially expressing GFP, 50% had lost detectable GFP activity during the first 4 weeks of culture. Multiple T-DNA copies of the gfp gene were detected in 10 of 17 proto-calluses lacking visible GFP activity. The remaining 7 cell lines contained no gfp sequences. Our results confirm that transiently expressed T-DNAs can be lost during growth of somatic cells and demonstrate that transiently expressing cells frequently integrate multiple T-DNAs that become silenced. In cells competent for DNA uptake, cell death and gene silencing were more important barriers to the recovery of stably expressing transformants than lack of T-DNA integration.

Dose-dense and less dose-intense Total Therapy 5 for gene expression profiling-defined high-risk multiple myeloma.

PubMed

Jethava, Y; Mitchell, A; Zangari, M; Waheed, S; Schinke, C; Thanendrarajan, S; Sawyer, J; Alapat, D; Tian, E; Stein, C; Khan, R; Heuck, C J; Petty, N; Avery, D; Steward, D; Smith, R; Bailey, C; Epstein, J; Yaccoby, S; Hoering, A; Crowley, J; Morgan, G; Barlogie, B; van Rhee, F

2016-07-29

Multiple myeloma (MM) is a heterogeneous disease with high-risk patients progressing rapidly despite treatment. Various definitions of high-risk MM are used and we reported that gene expression profile (GEP)-defined high risk was a major predictor of relapse. In spite of our best efforts, the majority of GEP70 high-risk patients relapse and we have noted higher relapse rates during drug-free intervals. This prompted us to explore the concept of less intense drug dosing with shorter intervals between courses with the aim of preventing inter-course relapse. Here we report the outcome of the Total Therapy 5 trial, where this concept was tested. This regimen effectively reduced early mortality and relapse but failed to improve progression-free survival and overall survival due to relapse early during maintenance.

A two-step hierarchical hypothesis set testing framework, with applications to gene expression data on ordered categories

PubMed Central

2014-01-01

Background In complex large-scale experiments, in addition to simultaneously considering a large number of features, multiple hypotheses are often being tested for each feature. This leads to a problem of multi-dimensional multiple testing. For example, in gene expression studies over ordered categories (such as time-course or dose-response experiments), interest is often in testing differential expression across several categories for each gene. In this paper, we consider a framework for testing multiple sets of hypothesis, which can be applied to a wide range of problems. Results We adopt the concept of the overall false discovery rate (OFDR) for controlling false discoveries on the hypothesis set level. Based on an existing procedure for identifying differentially expressed gene sets, we discuss a general two-step hierarchical hypothesis set testing procedure, which controls the overall false discovery rate under independence across hypothesis sets. In addition, we discuss the concept of the mixed-directional false discovery rate (mdFDR), and extend the general procedure to enable directional decisions for two-sided alternatives. We applied the framework to the case of microarray time-course/dose-response experiments, and proposed three procedures for testing differential expression and making multiple directional decisions for each gene. Simulation studies confirm the control of the OFDR and mdFDR by the proposed procedures under independence and positive correlations across genes. Simulation results also show that two of our new procedures achieve higher power than previous methods. Finally, the proposed methodology is applied to a microarray dose-response study, to identify 17 β-estradiol sensitive genes in breast cancer cells that are induced at low concentrations. Conclusions The framework we discuss provides a platform for multiple testing procedures covering situations involving two (or potentially more) sources of multiplicity. The framework is easy to

Gene Expression Profiles from Disease Discordant Twins Suggest Shared Antiviral Pathways and Viral Exposures among Multiple Systemic Autoimmune Diseases.

PubMed

Gan, Lu; O'Hanlon, Terrance P; Lai, Zhennan; Fannin, Rick; Weller, Melodie L; Rider, Lisa G; Chiorini, John A; Miller, Frederick W

2015-01-01

Viral agents are of interest as possible autoimmune triggers due to prior reported associations and widely studied molecular mechanisms of antiviral immune responses in autoimmunity. Here we examined new viral candidates for the initiation and/or promotion of systemic autoimmune diseases (SAID), as well as possible related signaling pathways shared in the pathogenesis of those disorders. RNA isolated from peripheral blood samples from 33 twins discordant for SAID and 33 matched, unrelated healthy controls was analyzed using a custom viral-human gene microarray. Paired comparisons were made among three study groups-probands with SAID, their unaffected twins, and matched, unrelated healthy controls-using statistical and molecular pathway analyses. Probands and unaffected twins differed significantly in the expression of 537 human genes, and 107 of those were associated with viral infections. These 537 differentially expressed human genes participate in overlapping networks of several canonical, biologic pathways relating to antiviral responses and inflammation. Moreover, certain viral genes were expressed at higher levels in probands compared to either unaffected twins or unrelated, healthy controls. Interestingly, viral gene expression levels in unaffected twins appeared intermediate between those of probands and the matched, unrelated healthy controls. Of the viruses with overexpressed viral genes, herpes simplex virus-2 (HSV-2) was the only human viral pathogen identified using four distinct oligonucleotide probes corresponding to three HSV-2 genes associated with different stages of viral infection. Although the effects from immunosuppressive therapy on viral gene expression remain unclear, this exploratory study suggests a new approach to evaluate shared viral agents and antiviral immune responses that may be involved in the development of SAID.

Gene Expression Profiles from Disease Discordant Twins Suggest Shared Antiviral Pathways and Viral Exposures among Multiple Systemic Autoimmune Diseases

PubMed Central

Gan, Lu; O’Hanlon, Terrance P.; Lai, Zhennan; Fannin, Rick; Weller, Melodie L.; Rider, Lisa G.; Chiorini, John A.; Miller, Frederick W.

2015-01-01

Viral agents are of interest as possible autoimmune triggers due to prior reported associations and widely studied molecular mechanisms of antiviral immune responses in autoimmunity. Here we examined new viral candidates for the initiation and/or promotion of systemic autoimmune diseases (SAID), as well as possible related signaling pathways shared in the pathogenesis of those disorders. RNA isolated from peripheral blood samples from 33 twins discordant for SAID and 33 matched, unrelated healthy controls was analyzed using a custom viral-human gene microarray. Paired comparisons were made among three study groups—probands with SAID, their unaffected twins, and matched, unrelated healthy controls—using statistical and molecular pathway analyses. Probands and unaffected twins differed significantly in the expression of 537 human genes, and 107 of those were associated with viral infections. These 537 differentially expressed human genes participate in overlapping networks of several canonical, biologic pathways relating to antiviral responses and inflammation. Moreover, certain viral genes were expressed at higher levels in probands compared to either unaffected twins or unrelated, healthy controls. Interestingly, viral gene expression levels in unaffected twins appeared intermediate between those of probands and the matched, unrelated healthy controls. Of the viruses with overexpressed viral genes, herpes simplex virus-2 (HSV-2) was the only human viral pathogen identified using four distinct oligonucleotide probes corresponding to three HSV-2 genes associated with different stages of viral infection. Although the effects from immunosuppressive therapy on viral gene expression remain unclear, this exploratory study suggests a new approach to evaluate shared viral agents and antiviral immune responses that may be involved in the development of SAID. PMID:26556803

Gene Expression Noise, Fitness Landscapes, and Evolution

NASA Astrophysics Data System (ADS)

Charlebois, Daniel

The stochastic (or noisy) process of gene expression can have fitness consequences for living organisms. For example, gene expression noise facilitates the development of drug resistance by increasing the time scale at which beneficial phenotypic states can be maintained. The present work investigates the relationship between gene expression noise and the fitness landscape. By incorporating the costs and benefits of gene expression, we track how the fluctuation magnitude and timescale of expression noise evolve in simulations of cell populations under stress. We find that properties of expression noise evolve to maximize fitness on the fitness landscape, and that low levels of expression noise emerge when the fitness benefits of gene expression exceed the fitness costs (and that high levels of noise emerge when the costs of expression exceed the benefits). The findings from our theoretical/computational work offer new hypotheses on the development of drug resistance, some of which are now being investigated in evolution experiments in our laboratory using well-characterized synthetic gene regulatory networks in budding yeast. Nserc Postdoctoral Fellowship (Grant No. PDF-453977-2014).

Validation of miRNA genes suitable as reference genes in qPCR analyses of miRNA gene expression in Atlantic salmon (Salmo salar).

PubMed

Johansen, Ilona; Andreassen, Rune

2014-12-23

MicroRNAs (miRNAs) are an abundant class of endogenous small RNA molecules that downregulate gene expression at the post-transcriptional level. They play important roles by regulating genes that control multiple biological processes, and recent years there has been an increased interest in studying miRNA genes and miRNA gene expression. The most common method applied to study gene expression of single genes is quantitative PCR (qPCR). However, before expression of mature miRNAs can be studied robust qPCR methods (miRNA-qPCR) must be developed. This includes identification and validation of suitable reference genes. We are particularly interested in Atlantic salmon (Salmo salar). This is an economically important aquaculture species, but no reference genes dedicated for use in miRNA-qPCR methods has been validated for this species. Our aim was, therefore, to identify suitable reference genes for miRNA-qPCR methods in Salmo salar. We used a systematic approach where we utilized similar studies in other species, some biological criteria, results from deep sequencing of small RNAs and, finally, experimental validation of candidate reference genes by qPCR to identify the most suitable reference genes. Ssa-miR-25-3p was identified as most suitable single reference gene. The best combinations of two reference genes were ssa-miR-25-3p and ssa-miR-455-5p. These two genes were constitutively and stably expressed across many different tissues. Furthermore, infectious salmon anaemia did not seem to affect their expression levels. These genes were amplified with high specificity, good efficiency and the qPCR assays showed a good linearity when applying a simple cybergreen miRNA-PCR method using miRNA gene specific forward primers. We have identified suitable reference genes for miRNA-qPCR in Atlantic salmon. These results will greatly facilitate further studies on miRNA genes in this species. The reference genes identified are conserved genes that are identical in their mature

Using the 2A Protein Coexpression System: Multicistronic 2A Vectors Expressing Gene(s) of Interest and Reporter Proteins.

PubMed

Luke, Garry A; Ryan, Martin D

2018-01-01

To date, a huge range of different proteins-many with cotranslational and posttranslational subcellular localization signals-have been coexpressed together with various reporter proteins in vitro and in vivo using 2A peptides. The pros and cons of 2A co-expression technology are considered below, followed by a simple example of a "how to" protocol to concatenate multiple genes of interest, together with a reporter gene, into a single gene linked via 2As for easy identification or selection of transduced cells.

Deciphering the associations between gene expression and copy number alteration using a sparse double Laplacian shrinkage approach

PubMed Central

Shi, Xingjie; Zhao, Qing; Huang, Jian; Xie, Yang; Ma, Shuangge

2015-01-01

Motivation: Both gene expression levels (GEs) and copy number alterations (CNAs) have important biological implications. GEs are partly regulated by CNAs, and much effort has been devoted to understanding their relations. The regulation analysis is challenging with one gene expression possibly regulated by multiple CNAs and one CNA potentially regulating the expressions of multiple genes. The correlations among GEs and among CNAs make the analysis even more complicated. The existing methods have limitations and cannot comprehensively describe the regulation. Results: A sparse double Laplacian shrinkage method is developed. It jointly models the effects of multiple CNAs on multiple GEs. Penalization is adopted to achieve sparsity and identify the regulation relationships. Network adjacency is computed to describe the interconnections among GEs and among CNAs. Two Laplacian shrinkage penalties are imposed to accommodate the network adjacency measures. Simulation shows that the proposed method outperforms the competing alternatives with more accurate marker identification. The Cancer Genome Atlas data are analysed to further demonstrate advantages of the proposed method. Availability and implementation: R code is available at http://works.bepress.com/shuangge/49/ Contact: shuangge.ma@yale.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26342102

Strategies for comparing gene expression profiles from different microarray platforms: application to a case-control experiment.

PubMed

Severgnini, Marco; Bicciato, Silvio; Mangano, Eleonora; Scarlatti, Francesca; Mezzelani, Alessandra; Mattioli, Michela; Ghidoni, Riccardo; Peano, Clelia; Bonnal, Raoul; Viti, Federica; Milanesi, Luciano; De Bellis, Gianluca; Battaglia, Cristina

2006-06-01

Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.

Familial aggregation analysis of gene expressions

PubMed Central

Rao, Shao-Qi; Xu, Liang-De; Zhang, Guang-Mei; Li, Xia; Li, Lin; Shen, Gong-Qing; Jiang, Yang; Yang, Yue-Ying; Gong, Bin-Sheng; Jiang, Wei; Zhang, Fan; Xiao, Yun; Wang, Qing K

2007-01-01

Traditional studies of familial aggregation are aimed at defining the genetic (and non-genetic) causes of a disease from physiological or clinical traits. However, there has been little attempt to use genome-wide gene expressions, the direct phenotypic measures of genes, as the traits to investigate several extended issues regarding the distributions of familially aggregated genes on chromosomes or in functions. In this study we conducted a genome-wide familial aggregation analysis by using the in vitro cell gene expressions of 3300 human autosome genes (Problem 1 data provided to Genetic Analysis Workshop 15) in order to answer three basic genetics questions. First, we investigated how gene expressions aggregate among different types (degrees) of relative pairs. Second, we conducted a bioinformatics analysis of highly familially aggregated genes to see how they are distributed on chromosomes. Third, we performed a gene ontology enrichment test of familially aggregated genes to find evidence to support their functional consensus. The results indicated that 1) gene expressions did aggregate in families, especially between sibs. Of 3300 human genes analyzed, there were a total of 1105 genes with one or more significant (empirical p < 0.05) familial correlation; 2) there were several genomic hot spots where highly familially aggregated genes (e.g., the chromosome 6 HLA genes cluster) were clustered; 3) as we expected, gene ontology enrichment tests revealed that the 1105 genes were aggregating not only in families but also in functional categories. PMID:18466548

A whole blood gene expression-based signature for smoking status

PubMed Central

2012-01-01

Background Smoking is the leading cause of preventable death worldwide and has been shown to increase the risk of multiple diseases including coronary artery disease (CAD). We sought to identify genes whose levels of expression in whole blood correlate with self-reported smoking status. Methods Microarrays were used to identify gene expression changes in whole blood which correlated with self-reported smoking status; a set of significant genes from the microarray analysis were validated by qRT-PCR in an independent set of subjects. Stepwise forward logistic regression was performed using the qRT-PCR data to create a predictive model whose performance was validated in an independent set of subjects and compared to cotinine, a nicotine metabolite. Results Microarray analysis of whole blood RNA from 209 PREDICT subjects (41 current smokers, 4 quit ≤ 2 months, 64 quit > 2 months, 100 never smoked; NCT00500617) identified 4214 genes significantly correlated with self-reported smoking status. qRT-PCR was performed on 1,071 PREDICT subjects across 256 microarray genes significantly correlated with smoking or CAD. A five gene (CLDND1, LRRN3, MUC1, GOPC, LEF1) predictive model, derived from the qRT-PCR data using stepwise forward logistic regression, had a cross-validated mean AUC of 0.93 (sensitivity=0.78; specificity=0.95), and was validated using 180 independent PREDICT subjects (AUC=0.82, CI 0.69-0.94; sensitivity=0.63; specificity=0.94). Plasma from the 180 validation subjects was used to assess levels of cotinine; a model using a threshold of 10 ng/ml cotinine resulted in an AUC of 0.89 (CI 0.81-0.97; sensitivity=0.81; specificity=0.97; kappa with expression model = 0.53). Conclusion We have constructed and validated a whole blood gene expression score for the evaluation of smoking status, demonstrating that clinical and environmental factors contributing to cardiovascular disease risk can be assessed by gene expression. PMID:23210427

HOXB homeobox gene expression in cervical carcinoma.