Sample records for accurate gene expression

  1. Recommendations for Accurate Resolution of Gene and Isoform Allele-Specific Expression in RNA-Seq Data

    PubMed Central

    Wood, David L. A.; Nones, Katia; Steptoe, Anita; Christ, Angelika; Harliwong, Ivon; Newell, Felicity; Bruxner, Timothy J. C.; Miller, David; Cloonan, Nicole; Grimmond, Sean M.

    2015-01-01

    Genetic variation modulates gene expression transcriptionally or post-transcriptionally, and can profoundly alter an individual’s phenotype. Measuring allelic differential expression at heterozygous loci within an individual, a phenomenon called allele-specific expression (ASE), can assist in identifying such factors. Massively parallel DNA and RNA sequencing and advances in bioinformatic methodologies provide an outstanding opportunity to measure ASE genome-wide. In this study, matched DNA and RNA sequencing, genotyping arrays and computationally phased haplotypes were integrated to comprehensively and conservatively quantify ASE in a single human brain and liver tissue sample. We describe a methodological evaluation and assessment of common bioinformatic steps for ASE quantification, and recommend a robust approach to accurately measure SNP, gene and isoform ASE through the use of personalized haplotype genome alignment, strict alignment quality control and intragenic SNP aggregation. Our results indicate that accurate ASE quantification requires careful bioinformatic analyses and is adversely affected by sample specific alignment confounders and random sampling even at moderate sequence depths. We identified multiple known and several novel ASE genes in liver, including WDR72, DSP and UBD, as well as genes that contained ASE SNPs with imbalance direction discordant with haplotype phase, explainable by annotated transcript structure, suggesting isoform derived ASE. The methods evaluated in this study will be of use to researchers performing highly conservative quantification of ASE, and the genes and isoforms identified as ASE of interest to researchers studying those loci. PMID:25965996

  2. Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

    PubMed Central

    Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher

    2016-01-01

    Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

  3. Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium.

    PubMed

    Ryan, Natalia; Chorley, Brian; Tice, Raymond R; Judson, Richard; Corton, J Christopher

    2016-05-01

    Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

  4. A gene expression biomarker accurately predicts estrogen ...

    EPA Pesticide Factsheets

    The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1 screening tests. The ToxCast program currently includes 18 HTS in vitro assays that evaluate the ability of chemicals to modulate estrogen receptor α (ERα), an important endocrine target. We propose microarray-based gene expression profiling as a complementary approach to predict ERα modulation and have developed computational methods to identify ERα modulators in an existing database of whole-genome microarray data. The ERα biomarker consisted of 46 ERα-regulated genes with consistent expression patterns across 7 known ER agonists and 3 known ER antagonists. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments in MCF-7 cells. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% or 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) OECD ER reference chemicals including “very weak” agonists and replicated predictions based on 18 in vitro ER-associated HTS assays. For 114 chemicals present in both the HTS data and the MCF-7 c

  5. A highly sensitive and accurate gene expression analysis by sequencing ("bead-seq") for a single cell.

    PubMed

    Matsunaga, Hiroko; Goto, Mari; Arikawa, Koji; Shirai, Masataka; Tsunoda, Hiroyuki; Huang, Huan; Kambara, Hideki

    2015-02-15

    Analyses of gene expressions in single cells are important for understanding detailed biological phenomena. Here, a highly sensitive and accurate method by sequencing (called "bead-seq") to obtain a whole gene expression profile for a single cell is proposed. A key feature of the method is to use a complementary DNA (cDNA) library on magnetic beads, which enables adding washing steps to remove residual reagents in a sample preparation process. By adding the washing steps, the next steps can be carried out under the optimal conditions without losing cDNAs. Error sources were carefully evaluated to conclude that the first several steps were the key steps. It is demonstrated that bead-seq is superior to the conventional methods for single-cell gene expression analyses in terms of reproducibility, quantitative accuracy, and biases caused during sample preparation and sequencing processes. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

    PubMed Central

    Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K.; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G.; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H.

    2017-01-01

    The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. PMID:27899623

  7. A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression

    PubMed Central

    Nguyen, Nha; Vo, An; Choi, Inchan

    2015-01-01

    Abstract Studying epigenetic landscapes is important to understand the condition for gene regulation. Clustering is a useful approach to study epigenetic landscapes by grouping genes based on their epigenetic conditions. However, classical clustering approaches that often use a representative value of the signals in a fixed-sized window do not fully use the information written in the epigenetic landscapes. Clustering approaches to maximize the information of the epigenetic signals are necessary for better understanding gene regulatory environments. For effective clustering of multidimensional epigenetic signals, we developed a method called Dewer, which uses the entropy of stationary wavelet of epigenetic signals inside enriched regions for gene clustering. Interestingly, the gene expression levels were highly correlated with the entropy levels of epigenetic signals. Dewer separates genes better than a window-based approach in the assessment using gene expression and achieved a correlation coefficient above 0.9 without using any training procedure. Our results show that the changes of the epigenetic signals are useful to study gene regulation. PMID:25383910

  8. A Machine Learned Classifier That Uses Gene Expression Data to Accurately Predict Estrogen Receptor Status

    PubMed Central

    Bastani, Meysam; Vos, Larissa; Asgarian, Nasimeh; Deschenes, Jean; Graham, Kathryn; Mackey, John; Greiner, Russell

    2013-01-01

    Background Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER) status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. Methods To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. Results This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. Conclusions Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions. PMID:24312637

  9. Validation of reference genes for quantitative gene expression analysis in experimental epilepsy.

    PubMed

    Sadangi, Chinmaya; Rosenow, Felix; Norwood, Braxton A

    2017-12-01

    To grasp the molecular mechanisms and pathophysiology underlying epilepsy development (epileptogenesis) and epilepsy itself, it is important to understand the gene expression changes that occur during these phases. Quantitative real-time polymerase chain reaction (qPCR) is a technique that rapidly and accurately determines gene expression changes. It is crucial, however, that stable reference genes are selected for each experimental condition to ensure that accurate values are obtained for genes of interest. If reference genes are unstably expressed, this can lead to inaccurate data and erroneous conclusions. To date, epilepsy studies have used mostly single, nonvalidated reference genes. This is the first study to systematically evaluate reference genes in male Sprague-Dawley rat models of epilepsy. We assessed 15 potential reference genes in hippocampal tissue obtained from 2 different models during epileptogenesis, 1 model during chronic epilepsy, and a model of noninjurious seizures. Reference gene ranking varied between models and also differed between epileptogenesis and chronic epilepsy time points. There was also some variance between the four mathematical models used to rank reference genes. Notably, we found novel reference genes to be more stably expressed than those most often used in experimental epilepsy studies. The consequence of these findings is that reference genes suitable for one epilepsy model may not be appropriate for others and that reference genes can change over time. It is, therefore, critically important to validate potential reference genes before using them as normalizing factors in expression analysis in order to ensure accurate, valid results. © 2017 Wiley Periodicals, Inc.

  10. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

    PubMed

    Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H

    2017-01-09

    The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Validation of reference genes for accurate normalization of gene expression for real time-quantitative PCR in strawberry fruits using different cultivars and osmotic stresses.

    PubMed

    Galli, Vanessa; Borowski, Joyce Moura; Perin, Ellen Cristina; Messias, Rafael da Silva; Labonde, Julia; Pereira, Ivan dos Santos; Silva, Sérgio Delmar Dos Anjos; Rombaldi, Cesar Valmor

    2015-01-10

    The increasing demand of strawberry (Fragaria×ananassa Duch) fruits is associated mainly with their sensorial characteristics and the content of antioxidant compounds. Nevertheless, the strawberry production has been hampered due to its sensitivity to abiotic stresses. Therefore, to understand the molecular mechanisms highlighting stress response is of great importance to enable genetic engineering approaches aiming to improve strawberry tolerance. However, the study of expression of genes in strawberry requires the use of suitable reference genes. In the present study, seven traditional and novel candidate reference genes were evaluated for transcript normalization in fruits of ten strawberry cultivars and two abiotic stresses, using RefFinder, which integrates the four major currently available software programs: geNorm, NormFinder, BestKeeper and the comparative delta-Ct method. The results indicate that the expression stability is dependent on the experimental conditions. The candidate reference gene DBP (DNA binding protein) was considered the most suitable to normalize expression data in samples of strawberry cultivars and under drought stress condition, and the candidate reference gene HISTH4 (histone H4) was the most stable under osmotic stresses and salt stress. The traditional genes GAPDH (glyceraldehyde-3-phosphate dehydrogenase) and 18S (18S ribosomal RNA) were considered the most unstable genes in all conditions. The expression of phenylalanine ammonia lyase (PAL) and 9-cis epoxycarotenoid dioxygenase (NCED1) genes were used to further confirm the validated candidate reference genes, showing that the use of an inappropriate reference gene may induce erroneous results. This study is the first survey on the stability of reference genes in strawberry cultivars and osmotic stresses and provides guidelines to obtain more accurate RT-qPCR results for future breeding efforts. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Suitable Reference Genes for Accurate Gene Expression Analysis in Parsley (Petroselinum crispum) for Abiotic Stresses and Hormone Stimuli

    PubMed Central

    Li, Meng-Yao; Song, Xiong; Wang, Feng; Xiong, Ai-Sheng

    2016-01-01

    Parsley, one of the most important vegetables in the Apiaceae family, is widely used in the food, medicinal, and cosmetic industries. Recent studies on parsley mainly focus on its chemical composition, and further research involving the analysis of the plant's gene functions and expressions is required. qPCR is a powerful method for detecting very low quantities of target transcript levels and is widely used to study gene expression. To ensure the accuracy of results, a suitable reference gene is necessary for expression normalization. In this study, four software, namely geNorm, NormFinder, BestKeeper, and RefFinder were used to evaluate the expression stabilities of eight candidate reference genes of parsley (GAPDH, ACTIN, eIF-4α, SAND, UBC, TIP41, EF-1α, and TUB) under various conditions, including abiotic stresses (heat, cold, salt, and drought) and hormone stimuli treatments (GA, SA, MeJA, and ABA). Results showed that EF-1α and TUB were the most stable genes for abiotic stresses, whereas EF-1α, GAPDH, and TUB were the top three choices for hormone stimuli treatments. Moreover, EF-1α and TUB were the most stable reference genes among all tested samples, and UBC was the least stable one. Expression analysis of PcDREB1 and PcDREB2 further verified that the selected stable reference genes were suitable for gene expression normalization. This study can guide the selection of suitable reference genes in gene expression in parsley. PMID:27746803

  13. Suitable Reference Genes for Accurate Gene Expression Analysis in Parsley (Petroselinum crispum) for Abiotic Stresses and Hormone Stimuli.

    PubMed

    Li, Meng-Yao; Song, Xiong; Wang, Feng; Xiong, Ai-Sheng

    2016-01-01

    Parsley, one of the most important vegetables in the Apiaceae family, is widely used in the food, medicinal, and cosmetic industries. Recent studies on parsley mainly focus on its chemical composition, and further research involving the analysis of the plant's gene functions and expressions is required. qPCR is a powerful method for detecting very low quantities of target transcript levels and is widely used to study gene expression. To ensure the accuracy of results, a suitable reference gene is necessary for expression normalization. In this study, four software, namely geNorm, NormFinder, BestKeeper, and RefFinder were used to evaluate the expression stabilities of eight candidate reference genes of parsley ( GAPDH, ACTIN, eIF-4 α, SAND, UBC, TIP41, EF-1 α, and TUB ) under various conditions, including abiotic stresses (heat, cold, salt, and drought) and hormone stimuli treatments (GA, SA, MeJA, and ABA). Results showed that EF-1 α and TUB were the most stable genes for abiotic stresses, whereas EF-1 α, GAPDH , and TUB were the top three choices for hormone stimuli treatments. Moreover, EF-1 α and TUB were the most stable reference genes among all tested samples, and UBC was the least stable one. Expression analysis of PcDREB1 and PcDREB2 further verified that the selected stable reference genes were suitable for gene expression normalization. This study can guide the selection of suitable reference genes in gene expression in parsley.

  14. Machine-learning approach identifies a pattern of gene expression in peripheral blood that can accurately detect ischaemic stroke

    PubMed Central

    O’Connell, Grant C; Petrone, Ashley B; Treadway, Madison B; Tennant, Connie S; Lucke-Wold, Noelle; Chantler, Paul D; Barr, Taura L

    2016-01-01

    Early and accurate diagnosis of stroke improves the probability of positive outcome. The objective of this study was to identify a pattern of gene expression in peripheral blood that could potentially be optimised to expedite the diagnosis of acute ischaemic stroke (AIS). A discovery cohort was recruited consisting of 39 AIS patients and 24 neurologically asymptomatic controls. Peripheral blood was sampled at emergency department admission, and genome-wide expression profiling was performed via microarray. A machine-learning technique known as genetic algorithm k-nearest neighbours (GA/kNN) was then used to identify a pattern of gene expression that could optimally discriminate between groups. This pattern of expression was then assessed via qRT-PCR in an independent validation cohort, where it was evaluated for its ability to discriminate between an additional 39 AIS patients and 30 neurologically asymptomatic controls, as well as 20 acute stroke mimics. GA/kNN identified 10 genes (ANTXR2, STK3, PDK4, CD163, MAL, GRAP, ID3, CTSZ, KIF1B and PLXDC2) whose coordinate pattern of expression was able to identify 98.4% of discovery cohort subjects correctly (97.4% sensitive, 100% specific). In the validation cohort, the expression levels of the same 10 genes were able to identify 95.6% of subjects correctly when comparing AIS patients to asymptomatic controls (92.3% sensitive, 100% specific), and 94.9% of subjects correctly when comparing AIS patients with stroke mimics (97.4% sensitive, 90.0% specific). The transcriptional pattern identified in this study shows strong diagnostic potential, and warrants further evaluation to determine its true clinical efficacy. PMID:29263821

  15. Novel gene sets improve set-level classification of prokaryotic gene expression data.

    PubMed

    Holec, Matěj; Kuželka, Ondřej; Železný, Filip

    2015-10-28

    Set-level classification of gene expression data has received significant attention recently. In this setting, high-dimensional vectors of features corresponding to genes are converted into lower-dimensional vectors of features corresponding to biologically interpretable gene sets. The dimensionality reduction brings the promise of a decreased risk of overfitting, potentially resulting in improved accuracy of the learned classifiers. However, recent empirical research has not confirmed this expectation. Here we hypothesize that the reported unfavorable classification results in the set-level framework were due to the adoption of unsuitable gene sets defined typically on the basis of the Gene ontology and the KEGG database of metabolic networks. We explore an alternative approach to defining gene sets, based on regulatory interactions, which we expect to collect genes with more correlated expression. We hypothesize that such more correlated gene sets will enable to learn more accurate classifiers. We define two families of gene sets using information on regulatory interactions, and evaluate them on phenotype-classification tasks using public prokaryotic gene expression data sets. From each of the two gene-set families, we first select the best-performing subtype. The two selected subtypes are then evaluated on independent (testing) data sets against state-of-the-art gene sets and against the conventional gene-level approach. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. Novel gene sets defined on the basis of regulatory interactions improve set-level classification of gene expression data. The experimental scripts and other material needed to reproduce the experiments are available at http://ida.felk.cvut.cz/novelgenesets.tar.gz.

  16. 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.

  17. How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population.

    PubMed

    De Keyser, Ellen; Desmet, Laurence; Van Bockstaele, Erik; De Riek, Jan

    2013-06-24

    Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population. An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H. Currently in plant

  18. How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population

    PubMed Central

    2013-01-01

    Background Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population. Results An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H

  19. 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

  20. Selection of reliable reference genes for quantitative real-time PCR gene expression analysis in Jute (Corchorus capsularis) under stress treatments

    PubMed Central

    Niu, Xiaoping; Qi, Jianmin; Zhang, Gaoyang; Xu, Jiantang; Tao, Aifen; Fang, Pingping; Su, Jianguang

    2015-01-01

    To accurately measure gene expression using quantitative reverse transcription PCR (qRT-PCR), reliable reference gene(s) are required for data normalization. Corchorus capsularis, an annual herbaceous fiber crop with predominant biodegradability and renewability, has not been investigated for the stability of reference genes with qRT-PCR. In this study, 11 candidate reference genes were selected and their expression levels were assessed using qRT-PCR. To account for the influence of experimental approach and tissue type, 22 different jute samples were selected from abiotic and biotic stress conditions as well as three different tissue types. The stability of the candidate reference genes was evaluated using geNorm, NormFinder, and BestKeeper programs, and the comprehensive rankings of gene stability were generated by aggregate analysis. For the biotic stress and NaCl stress subsets, ACT7 and RAN were suitable as stable reference genes for gene expression normalization. For the PEG stress subset, UBC, and DnaJ were sufficient for accurate normalization. For the tissues subset, four reference genes TUBβ, UBI, EF1α, and RAN were sufficient for accurate normalization. The selected genes were further validated by comparing expression profiles of WRKY15 in various samples, and two stable reference genes were recommended for accurate normalization of qRT-PCR data. Our results provide researchers with appropriate reference genes for qRT-PCR in C. capsularis, and will facilitate gene expression study under these conditions. PMID:26528312

  1. Evaluation of New Reference Genes in Papaya for Accurate Transcript Normalization under Different Experimental Conditions

    PubMed Central

    Chen, Weixin; Chen, Jianye; Lu, Wangjin; Chen, Lei; Fu, Danwen

    2012-01-01

    Real-time reverse transcription PCR (RT-qPCR) is a preferred method for rapid and accurate quantification of gene expression studies. Appropriate application of RT-qPCR requires accurate normalization though the use of reference genes. As no single reference gene is universally suitable for all experiments, thus reference gene(s) validation under different experimental conditions is crucial for RT-qPCR analysis. To date, only a few studies on reference genes have been done in other plants but none in papaya. In the present work, we selected 21 candidate reference genes, and evaluated their expression stability in 246 papaya fruit samples using three algorithms, geNorm, NormFinder and RefFinder. The samples consisted of 13 sets collected under different experimental conditions, including various tissues, different storage temperatures, different cultivars, developmental stages, postharvest ripening, modified atmosphere packaging, 1-methylcyclopropene (1-MCP) treatment, hot water treatment, biotic stress and hormone treatment. Our results demonstrated that expression stability varied greatly between reference genes and that different suitable reference gene(s) or combination of reference genes for normalization should be validated according to the experimental conditions. In general, the internal reference genes EIF (Eukaryotic initiation factor 4A), TBP1 (TATA binding protein 1) and TBP2 (TATA binding protein 2) genes had a good performance under most experimental conditions, whereas the most widely present used reference genes, ACTIN (Actin 2), 18S rRNA (18S ribosomal RNA) and GAPDH (Glyceraldehyde-3-phosphate dehydrogenase) were not suitable in many experimental conditions. In addition, two commonly used programs, geNorm and Normfinder, were proved sufficient for the validation. This work provides the first systematic analysis for the selection of superior reference genes for accurate transcript normalization in papaya under different experimental conditions. PMID

  2. Validation of reference genes aiming accurate normalization of qRT-PCR data in Dendrocalamus latiflorus Munro.

    PubMed

    Liu, Mingying; Jiang, Jing; Han, Xiaojiao; Qiao, Guirong; Zhuo, Renying

    2014-01-01

    Dendrocalamus latiflorus Munro distributes widely in subtropical areas and plays vital roles as valuable natural resources. The transcriptome sequencing for D. latiflorus Munro has been performed and numerous genes especially those predicted to be unique to D. latiflorus Munro were revealed. qRT-PCR has become a feasible approach to uncover gene expression profiling, and the accuracy and reliability of the results obtained depends upon the proper selection of stable reference genes for accurate normalization. Therefore, a set of suitable internal controls should be validated for D. latiflorus Munro. In this report, twelve candidate reference genes were selected and the assessment of gene expression stability was performed in ten tissue samples and four leaf samples from seedlings and anther-regenerated plants of different ploidy. The PCR amplification efficiency was estimated, and the candidate genes were ranked according to their expression stability using three software packages: geNorm, NormFinder and Bestkeeper. GAPDH and EF1α were characterized to be the most stable genes among different tissues or in all the sample pools, while CYP showed low expression stability. RPL3 had the optimal performance among four leaf samples. The application of verified reference genes was illustrated by analyzing ferritin and laccase expression profiles among different experimental sets. The analysis revealed the biological variation in ferritin and laccase transcript expression among the tissues studied and the individual plants. geNorm, NormFinder, and BestKeeper analyses recommended different suitable reference gene(s) for normalization according to the experimental sets. GAPDH and EF1α had the highest expression stability across different tissues and RPL3 for the other sample set. This study emphasizes the importance of validating superior reference genes for qRT-PCR analysis to accurately normalize gene expression of D. latiflorus Munro.

  3. Lung tumor diagnosis and subtype discovery by gene expression profiling.

    PubMed

    Wang, Lu-yong; Tu, Zhuowen

    2006-01-01

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

  4. Accurate prediction of secondary metabolite gene clusters in filamentous fungi.

    PubMed

    Andersen, Mikael R; Nielsen, Jakob B; Klitgaard, Andreas; Petersen, Lene M; Zachariasen, Mia; Hansen, Tilde J; Blicher, Lene H; Gotfredsen, Charlotte H; Larsen, Thomas O; Nielsen, Kristian F; Mortensen, Uffe H

    2013-01-02

    Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify supporting enzymes for key synthases one cluster at a time. In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 of 16 known clusters and nearly accurate for the remaining 3 clusters. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (superclusters), and validate this both with legacy data and experimentally by prediction and verification of a supercluster consisting of the synthase AN1242 and the prenyltransferase AN11080, as well as identification of the product compound nidulanin A. We have used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom.

  5. Selection of low-variance expressed Malus x domestica (apple) genes for use as quantitative PCR reference genes (housekeepers)

    USDA-ARS?s Scientific Manuscript database

    To accurately measure gene expression using PCR-based approaches, there is the need for reference genes that have low variance in expression (housekeeping genes) to normalise the data for RNA quantity and quality. For non-model species such as Malus x domestica (apples), previously, the selection of...

  6. An atlas of gene expression and gene co-regulation in the human retina.

    PubMed

    Pinelli, Michele; Carissimo, Annamaria; Cutillo, Luisa; Lai, Ching-Hung; Mutarelli, Margherita; Moretti, Maria Nicoletta; Singh, Marwah Veer; Karali, Marianthi; Carrella, Diego; Pizzo, Mariateresa; Russo, Francesco; Ferrari, Stefano; Ponzin, Diego; Angelini, Claudia; Banfi, Sandro; di Bernardo, Diego

    2016-07-08

    The human retina is a specialized tissue involved in light stimulus transduction. Despite its unique biology, an accurate reference transcriptome is still missing. Here, we performed gene expression analysis (RNA-seq) of 50 retinal samples from non-visually impaired post-mortem donors. We identified novel transcripts with high confidence (Observed Transcriptome (ObsT)) and quantified the expression level of known transcripts (Reference Transcriptome (RefT)). The ObsT included 77 623 transcripts (23 960 genes) covering 137 Mb (35 Mb new transcribed genome). Most of the transcripts (92%) were multi-exonic: 81% with known isoforms, 16% with new isoforms and 3% belonging to new genes. The RefT included 13 792 genes across 94 521 known transcripts. Mitochondrial genes were among the most highly expressed, accounting for about 10% of the reads. Of all the protein-coding genes in Gencode, 65% are expressed in the retina. We exploited inter-individual variability in gene expression to infer a gene co-expression network and to identify genes specifically expressed in photoreceptor cells. We experimentally validated the photoreceptors localization of three genes in human retina that had not been previously reported. RNA-seq data and the gene co-expression network are available online (http://retina.tigem.it). © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. Biased Gene Fractionation and Dominant Gene Expression among the Subgenomes of Brassica rapa

    PubMed Central

    Cheng, Feng; Wu, Jian; Fang, Lu; Sun, Silong; Liu, Bo; Lin, Ke; Bonnema, Guusje; Wang, Xiaowu

    2012-01-01

    Polyploidization, both ancient and recent, is frequent among plants. A “two-step theory" was proposed to explain the meso-triplication of the Brassica “A" genome: Brassica rapa. By accurately partitioning of this genome, we observed that genes in the less fractioned subgenome (LF) were dominantly expressed over the genes in more fractioned subgenomes (MFs: MF1 and MF2), while the genes in MF1 were slightly dominantly expressed over the genes in MF2. The results indicated that the dominantly expressed genes tended to be resistant against gene fractionation. By re-sequencing two B. rapa accessions: a vegetable turnip (VT117) and a Rapid Cycling line (L144), we found that genes in LF had less non-synonymous or frameshift mutations than genes in MFs; however mutation rates were not significantly different between MF1 and MF2. The differences in gene expression patterns and on-going gene death among the three subgenomes suggest that “two-step" genome triplication and differential subgenome methylation played important roles in the genome evolution of B. rapa. PMID:22567157

  8. Biased gene fractionation and dominant gene expression among the subgenomes of Brassica rapa.

    PubMed

    Cheng, Feng; Wu, Jian; Fang, Lu; Sun, Silong; Liu, Bo; Lin, Ke; Bonnema, Guusje; Wang, Xiaowu

    2012-01-01

    Polyploidization, both ancient and recent, is frequent among plants. A "two-step theory" was proposed to explain the meso-triplication of the Brassica "A" genome: Brassica rapa. By accurately partitioning of this genome, we observed that genes in the less fractioned subgenome (LF) were dominantly expressed over the genes in more fractioned subgenomes (MFs: MF1 and MF2), while the genes in MF1 were slightly dominantly expressed over the genes in MF2. The results indicated that the dominantly expressed genes tended to be resistant against gene fractionation. By re-sequencing two B. rapa accessions: a vegetable turnip (VT117) and a Rapid Cycling line (L144), we found that genes in LF had less non-synonymous or frameshift mutations than genes in MFs; however mutation rates were not significantly different between MF1 and MF2. The differences in gene expression patterns and on-going gene death among the three subgenomes suggest that "two-step" genome triplication and differential subgenome methylation played important roles in the genome evolution of B. rapa.

  9. Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

    PubMed Central

    2013-01-01

    Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression. PMID:23369200

  10. Reference Genes for Accurate Transcript Normalization in Citrus Genotypes under Different Experimental Conditions

    PubMed Central

    Mafra, Valéria; Kubo, Karen S.; Alves-Ferreira, Marcio; Ribeiro-Alves, Marcelo; Stuart, Rodrigo M.; Boava, Leonardo P.; Rodrigues, Carolina M.; Machado, Marcos A.

    2012-01-01

    Real-time reverse transcription PCR (RT-qPCR) has emerged as an accurate and widely used technique for expression profiling of selected genes. However, obtaining reliable measurements depends on the selection of appropriate reference genes for gene expression normalization. The aim of this work was to assess the expression stability of 15 candidate genes to determine which set of reference genes is best suited for transcript normalization in citrus in different tissues and organs and leaves challenged with five pathogens (Alternaria alternata, Phytophthora parasitica, Xylella fastidiosa and Candidatus Liberibacter asiaticus). We tested traditional genes used for transcript normalization in citrus and orthologs of Arabidopsis thaliana genes described as superior reference genes based on transcriptome data. geNorm and NormFinder algorithms were used to find the best reference genes to normalize all samples and conditions tested. Additionally, each biotic stress was individually analyzed by geNorm. In general, FBOX (encoding a member of the F-box family) and GAPC2 (GAPDH) was the most stable candidate gene set assessed under the different conditions and subsets tested, while CYP (cyclophilin), TUB (tubulin) and CtP (cathepsin) were the least stably expressed genes found. Validation of the best suitable reference genes for normalizing the expression level of the WRKY70 transcription factor in leaves infected with Candidatus Liberibacter asiaticus showed that arbitrary use of reference genes without previous testing could lead to misinterpretation of data. Our results revealed FBOX, SAND (a SAND family protein), GAPC2 and UPL7 (ubiquitin protein ligase 7) to be superior reference genes, and we recommend their use in studies of gene expression in citrus species and relatives. This work constitutes the first systematic analysis for the selection of superior reference genes for transcript normalization in different citrus organs and under biotic stress. PMID:22347455

  11. Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.).

    PubMed

    Huis, Rudy; Hawkins, Simon; Neutelings, Godfrey

    2010-04-19

    Quantitative real-time PCR (qRT-PCR) is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs). Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L). Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs) and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH) as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups.qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59). LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both geNorm-designated- and Norm

  12. 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

  13. Unstable Expression of Commonly Used Reference Genes in Rat Pancreatic Islets Early after Isolation Affects Results of Gene Expression Studies.

    PubMed

    Kosinová, Lucie; Cahová, Monika; Fábryová, Eva; Týcová, Irena; Koblas, Tomáš; Leontovyč, Ivan; Saudek, František; Kříž, Jan

    2016-01-01

    The use of RT-qPCR provides a powerful tool for gene expression studies; however, the proper interpretation of the obtained data is crucially dependent on accurate normalization based on stable reference genes. Recently, strong evidence has been shown indicating that the expression of many commonly used reference genes may vary significantly due to diverse experimental conditions. The isolation of pancreatic islets is a complicated procedure which creates severe mechanical and metabolic stress leading possibly to cellular damage and alteration of gene expression. Despite of this, freshly isolated islets frequently serve as a control in various gene expression and intervention studies. The aim of our study was to determine expression of 16 candidate reference genes and one gene of interest (F3) in isolated rat pancreatic islets during short-term cultivation in order to find a suitable endogenous control for gene expression studies. We compared the expression stability of the most commonly used reference genes and evaluated the reliability of relative and absolute quantification using RT-qPCR during 0-120 hrs after isolation. In freshly isolated islets, the expression of all tested genes was markedly depressed and it increased several times throughout the first 48 hrs of cultivation. We observed significant variability among samples at 0 and 24 hrs but substantial stabilization from 48 hrs onwards. During the first 48 hrs, relative quantification failed to reflect the real changes in respective mRNA concentrations while in the interval 48-120 hrs, the relative expression generally paralleled the results determined by absolute quantification. Thus, our data call into question the suitability of relative quantification for gene expression analysis in pancreatic islets during the first 48 hrs of cultivation, as the results may be significantly affected by unstable expression of reference genes. However, this method could provide reliable information from 48 hrs onwards.

  14. Stability evaluation of reference genes for gene expression analysis by RT-qPCR in soybean under different conditions.

    PubMed

    Wan, Qiao; Chen, Shuilian; Shan, Zhihui; Yang, Zhonglu; Chen, Limiao; Zhang, Chanjuan; Yuan, Songli; Hao, Qinnan; Zhang, Xiaojuan; Qiu, Dezhen; Chen, Haifeng; Zhou, Xinan

    2017-01-01

    Real-time quantitative reverse transcription PCR is a sensitive and widely used technique to quantify gene expression. To achieve a reliable result, appropriate reference genes are highly required for normalization of transcripts in different samples. In this study, 9 previously published reference genes (60S, Fbox, ELF1A, ELF1B, ACT11, TUA5, UBC4, G6PD, CYP2) of soybean [Glycine max (L.) Merr.] were selected. The expression stability of the 9 genes was evaluated under conditions of biotic stress caused by infection with soybean mosaic virus, nitrogen stress, across different cultivars and developmental stages. ΔCt and geNorm algorithms were used to evaluate and rank the expression stability of the 9 reference genes. Results obtained from two algorithms showed high consistency. Moreover, results of pairwise variation showed that two reference genes were sufficient to normalize the expression levels of target genes under each experimental setting. For virus infection, ELF1A and ELF1B were the most stable reference genes for accurate normalization. For different developmental stages, Fbox and G6PD had the highest expression stability between two soybean cultivars (Tanlong No. 1 and Tanlong No. 2). ELF1B and ACT11 were identified as the most stably expressed reference genes both under nitrogen stress and among different cultivars. The results showed that none of the candidate reference genes were uniformly expressed at different conditions, and selecting appropriate reference genes was pivotal for gene expression studies with particular condition and tissue. The most stable combination of genes identified in this study will help to achieve more accurate and reliable results in a wide variety of samples in soybean.

  15. Validating internal controls for quantitative plant gene expression studies

    PubMed Central

    Brunner, Amy M; Yakovlev, Igor A; Strauss, Steven H

    2004-01-01

    Background Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed. Results Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied. Conclusion Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments. PMID:15317655

  16. Validating internal controls for quantitative plant gene expression studies.

    PubMed

    Brunner, Amy M; Yakovlev, Igor A; Strauss, Steven H

    2004-08-18

    Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed. Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied. Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments.

  17. Adaptation of video game UVW mapping to 3D visualization of gene expression patterns

    NASA Astrophysics Data System (ADS)

    Vize, Peter D.; Gerth, Victor E.

    2007-01-01

    Analysis of gene expression patterns within an organism plays a critical role in associating genes with biological processes in both health and disease. During embryonic development the analysis and comparison of different gene expression patterns allows biologists to identify candidate genes that may regulate the formation of normal tissues and organs and to search for genes associated with congenital diseases. No two individual embryos, or organs, are exactly the same shape or size so comparing spatial gene expression in one embryo to that in another is difficult. We will present our efforts in comparing gene expression data collected using both volumetric and projection approaches. Volumetric data is highly accurate but difficult to process and compare. Projection methods use UV mapping to align texture maps to standardized spatial frameworks. This approach is less accurate but is very rapid and requires very little processing. We have built a database of over 180 3D models depicting gene expression patterns mapped onto the surface of spline based embryo models. Gene expression data in different models can easily be compared to determine common regions of activity. Visualization software, both Java and OpenGL optimized for viewing 3D gene expression data will also be demonstrated.

  18. Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series.

    PubMed

    Rubiolo, Mariano; Milone, Diego H; Stegmayer, Georgina

    2015-01-01

    Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel method based on a pool of neural networks for obtaining a gene regulatory network from a gene expression dataset. They are used for modeling each possible interaction between pairs of genes in the dataset, and a set of mining rules is applied to accurately detect the subjacent relations among genes. The results obtained on artificial and real datasets confirm the method effectiveness for discovering regulatory networks from a proper modeling of the temporal dynamics of gene expression profiles.

  19. Selection of suitable reference genes for gene expression studies in Staphylococcus capitis during growth under erythromycin stress.

    PubMed

    Cui, Bintao; Smooker, Peter M; Rouch, Duncan A; Deighton, Margaret A

    2016-08-01

    Accurate and reproducible measurement of gene transcription requires appropriate reference genes, which are stably expressed under different experimental conditions to provide normalization. Staphylococcus capitis is a human pathogen that produces biofilm under stress, such as imposed by antimicrobial agents. In this study, a set of five commonly used staphylococcal reference genes (gyrB, sodA, recA, tuf and rpoB) were systematically evaluated in two clinical isolates of Staphylococcus capitis (S. capitis subspecies urealyticus and capitis, respectively) under erythromycin stress in mid-log and stationary phases. Two public software programs (geNorm and NormFinder) and two manual calculation methods, reference residue normalization (RRN) and relative quantitative (RQ), were applied. The potential reference genes selected by the four algorithms were further validated by comparing the expression of a well-studied biofilm gene (icaA) with phenotypic biofilm formation in S. capitis under four different experimental conditions. The four methods differed considerably in their ability to predict the most suitable reference gene or gene combination for comparing icaA expression under different conditions. Under the conditions used here, the RQ method provided better selection of reference genes than the other three algorithms; however, this finding needs to be confirmed with a larger number of isolates. This study reinforces the need to assess the stability of reference genes for analysis of target gene expression under different conditions and the use of more than one algorithm in such studies. Although this work was conducted using a specific human pathogen, it emphasizes the importance of selecting suitable reference genes for accurate normalization of gene expression more generally.

  20. Identification of Importin 8 (IPO8) as the most accurate reference gene for the clinicopathological analysis of lung specimens

    PubMed Central

    Nguewa, Paul A; Agorreta, Jackeline; Blanco, David; Lozano, Maria Dolores; Gomez-Roman, Javier; Sanchez, Blas A; Valles, Iñaki; Pajares, Maria J; Pio, Ruben; Rodriguez, Maria Jose; Montuenga, Luis M; Calvo, Alfonso

    2008-01-01

    Background The accurate normalization of differentially expressed genes in lung cancer is essential for the identification of novel therapeutic targets and biomarkers by real time RT-PCR and microarrays. Although classical "housekeeping" genes, such as GAPDH, HPRT1, and beta-actin have been widely used in the past, their accuracy as reference genes for lung tissues has not been proven. Results We have conducted a thorough analysis of a panel of 16 candidate reference genes for lung specimens and lung cell lines. Gene expression was measured by quantitative real time RT-PCR and expression stability was analyzed with the softwares GeNorm and NormFinder, mean of |ΔCt| (= |Ct Normal-Ct tumor|) ± SEM, and correlation coefficients among genes. Systematic comparison between candidates led us to the identification of a subset of suitable reference genes for clinical samples: IPO8, ACTB, POLR2A, 18S, and PPIA. Further analysis showed that IPO8 had a very low mean of |ΔCt| (0.70 ± 0.09), with no statistically significant differences between normal and malignant samples and with excellent expression stability. Conclusion Our data show that IPO8 is the most accurate reference gene for clinical lung specimens. In addition, we demonstrate that the commonly used genes GAPDH and HPRT1 are inappropriate to normalize data derived from lung biopsies, although they are suitable as reference genes for lung cell lines. We thus propose IPO8 as a novel reference gene for lung cancer samples. PMID:19014639

  1. Constrained clusters of gene expression profiles with pathological features.

    PubMed

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

    2004-11-22

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

  2. Identification and evaluation of new reference genes in Gossypium hirsutum for accurate normalization of real-time quantitative RT-PCR data.

    PubMed

    Artico, Sinara; Nardeli, Sarah M; Brilhante, Osmundo; Grossi-de-Sa, Maria Fátima; Alves-Ferreira, Marcio

    2010-03-21

    Normalizing through reference genes, or housekeeping genes, can make more accurate and reliable results from reverse transcription real-time quantitative polymerase chain reaction (qPCR). Recent studies have shown that no single housekeeping gene is universal for all experiments. Thus, suitable reference genes should be the first step of any qPCR analysis. Only a few studies on the identification of housekeeping gene have been carried on plants. Therefore qPCR studies on important crops such as cotton has been hampered by the lack of suitable reference genes. By the use of two distinct algorithms, implemented by geNorm and NormFinder, we have assessed the gene expression of nine candidate reference genes in cotton: GhACT4, GhEF1alpha5, GhFBX6, GhPP2A1, GhMZA, GhPTB, GhGAPC2, GhbetaTUB3 and GhUBQ14. The candidate reference genes were evaluated in 23 experimental samples consisting of six distinct plant organs, eight stages of flower development, four stages of fruit development and in flower verticils. The expression of GhPP2A1 and GhUBQ14 genes were the most stable across all samples and also when distinct plants organs are examined. GhACT4 and GhUBQ14 present more stable expression during flower development, GhACT4 and GhFBX6 in the floral verticils and GhMZA and GhPTB during fruit development. Our analysis provided the most suitable combination of reference genes for each experimental set tested as internal control for reliable qPCR data normalization. In addition, to illustrate the use of cotton reference genes we checked the expression of two cotton MADS-box genes in distinct plant and floral organs and also during flower development. We have tested the expression stabilities of nine candidate genes in a set of 23 tissue samples from cotton plants divided into five different experimental sets. As a result of this evaluation, we recommend the use of GhUBQ14 and GhPP2A1 housekeeping genes as superior references for normalization of gene expression measures in

  3. Identification and evaluation of new reference genes in Gossypium hirsutum for accurate normalization of real-time quantitative RT-PCR data

    PubMed Central

    2010-01-01

    Background Normalizing through reference genes, or housekeeping genes, can make more accurate and reliable results from reverse transcription real-time quantitative polymerase chain reaction (qPCR). Recent studies have shown that no single housekeeping gene is universal for all experiments. Thus, suitable reference genes should be the first step of any qPCR analysis. Only a few studies on the identification of housekeeping gene have been carried on plants. Therefore qPCR studies on important crops such as cotton has been hampered by the lack of suitable reference genes. Results By the use of two distinct algorithms, implemented by geNorm and NormFinder, we have assessed the gene expression of nine candidate reference genes in cotton: GhACT4, GhEF1α5, GhFBX6, GhPP2A1, GhMZA, GhPTB, GhGAPC2, GhβTUB3 and GhUBQ14. The candidate reference genes were evaluated in 23 experimental samples consisting of six distinct plant organs, eight stages of flower development, four stages of fruit development and in flower verticils. The expression of GhPP2A1 and GhUBQ14 genes were the most stable across all samples and also when distinct plants organs are examined. GhACT4 and GhUBQ14 present more stable expression during flower development, GhACT4 and GhFBX6 in the floral verticils and GhMZA and GhPTB during fruit development. Our analysis provided the most suitable combination of reference genes for each experimental set tested as internal control for reliable qPCR data normalization. In addition, to illustrate the use of cotton reference genes we checked the expression of two cotton MADS-box genes in distinct plant and floral organs and also during flower development. Conclusion We have tested the expression stabilities of nine candidate genes in a set of 23 tissue samples from cotton plants divided into five different experimental sets. As a result of this evaluation, we recommend the use of GhUBQ14 and GhPP2A1 housekeeping genes as superior references for normalization of gene

  4. Interdependence of cell growth and gene expression: origins and consequences.

    PubMed

    Scott, Matthew; Gunderson, Carl W; Mateescu, Eduard M; Zhang, Zhongge; Hwa, Terence

    2010-11-19

    In bacteria, the rate of cell proliferation and the level of gene expression are intimately intertwined. Elucidating these relations is important both for understanding the physiological functions of endogenous genetic circuits and for designing robust synthetic systems. We describe a phenomenological study that reveals intrinsic constraints governing the allocation of resources toward protein synthesis and other aspects of cell growth. A theory incorporating these constraints can accurately predict how cell proliferation and gene expression affect one another, quantitatively accounting for the effect of translation-inhibiting antibiotics on gene expression and the effect of gratuitous protein expression on cell growth. The use of such empirical relations, analogous to phenomenological laws, may facilitate our understanding and manipulation of complex biological systems before underlying regulatory circuits are elucidated.

  5. 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.

  6. 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

  7. Turning the gene tap off; implications of regulating gene expression for cancer therapeutics

    PubMed Central

    Curtin, James F.; Candolfi, Marianela; Xiong, Weidong; Lowenstein, Pedro R.; Castro, Maria G.

    2008-01-01

    Cancer poses a tremendous therapeutic challenge worldwide, highlighting the critical need for developing novel therapeutics. A promising cancer treatment modality is gene therapy, which is a form of molecular medicine designed to introduce into target cells genetic material with therapeutic intent. Anticancer gene therapy strategies currently used in preclinical models, and in some cases in the clinic, include proapoptotic genes, oncolytic/replicative vectors, conditional cytotoxic approaches, inhibition of angiogenesis, inhibition of growth factor signaling, inactivation of oncogenes, inhibition of tumor invasion and stimulation of the immune system. The translation of these novel therapeutic modalities from the preclinical setting to the clinic has been driven by encouraging preclinical efficacy data and advances in gene delivery technologies. One area of intense research involves the ability to accurately regulate the levels of therapeutic gene expression to achieve enhanced efficacy and provide the capability to switch gene expression off completely if adverse side effects should arise. This feature could also be implemented to switch gene expression off when a successful therapeutic outcome ensues. Here, we will review recent developments related to the engineering of transcriptional switches within gene delivery systems, which could be implemented in clinical gene therapy applications directed at the treatment of cancer. PMID:18347132

  8. Effect of carbon monoxide on gene expression in cerebrocortical astrocytes: Validation of reference genes for quantitative real-time PCR.

    PubMed

    Oliveira, Sara R; Vieira, Helena L A; Duarte, Carlos B

    2015-09-15

    Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is a widely used technique to characterize changes in gene expression in complex cellular and tissue processes, such as cytoprotection or inflammation. The accurate assessment of changes in gene expression depends on the selection of adequate internal reference gene(s). Carbon monoxide (CO) affects several metabolic pathways and de novo protein synthesis is crucial in the cellular responses to this gasotransmitter. Herein a selection of commonly used reference genes was analyzed to identify the most suitable internal control genes to evaluate the effect of CO on gene expression in cultured cerebrocortical astrocytes. The cells were exposed to CO by treatment with CORM-A1 (CO releasing molecule A1) and four different algorithms (geNorm, NormFinder, Delta Ct and BestKeeper) were applied to evaluate the stability of eight putative reference genes. Our results indicate that Gapdh (glyceraldehyde-3-phosphate dehydrogenase) together with Ppia (peptidylpropyl isomerase A) is the most suitable gene pair for normalization of qRT-PCR results under the experimental conditions used. Pgk1 (phosphoglycerate kinase 1), Hprt1 (hypoxanthine guanine phosphoribosyl transferase I), Sdha (Succinate Dehydrogenase Complex, Subunit A), Tbp (TATA box binding protein), Actg1 (actin gamma 1) and Rn18s (18S rRNA) genes presented less stable expression profiles in cultured cortical astrocytes exposed to CORM-A1 for up to 60 min. For validation, we analyzed the effect of CO on the expression of Bdnf and bcl-2. Different results were obtained, depending on the reference genes used. A significant increase in the expression of both genes was found when the results were normalized with Gapdh and Ppia, in contrast with the results obtained when the other genes were used as reference. These findings highlight the need for a proper and accurate selection of the reference genes used in the quantification of qRT-PCR results

  9. Dynamic association rules for gene expression data analysis.

    PubMed

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

    2015-10-14

    DAR algorithm not only was able to identify a set of differentially expressed genes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to gene expression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.

  10. 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/.

  11. Identification and Validation of Reference Genes and Their Impact on Normalized Gene Expression Studies across Cultivated and Wild Cicer Species

    PubMed Central

    Reddy, Palakolanu Sudhakar; Sri Cindhuri, Katamreddy; Sivaji Ganesh, Adusumalli; Sharma, Kiran Kumar

    2016-01-01

    Quantitative Real-Time PCR (qPCR) is a preferred and reliable method for accurate quantification of gene expression to understand precise gene functions. A total of 25 candidate reference genes including traditional and new generation reference genes were selected and evaluated in a diverse set of chickpea samples. The samples used in this study included nine chickpea genotypes (Cicer spp.) comprising of cultivated and wild species, six abiotic stress treatments (drought, salinity, high vapor pressure deficit, abscisic acid, cold and heat shock), and five diverse tissues (leaf, root, flower, seedlings and seed). The geNorm, NormFinder and RefFinder algorithms used to identify stably expressed genes in four sample sets revealed stable expression of UCP and G6PD genes across genotypes, while TIP41 and CAC were highly stable under abiotic stress conditions. While PP2A and ABCT genes were ranked as best for different tissues, ABCT, UCP and CAC were most stable across all samples. This study demonstrated the usefulness of new generation reference genes for more accurate qPCR based gene expression quantification in cultivated as well as wild chickpea species. Validation of the best reference genes was carried out by studying their impact on normalization of aquaporin genes PIP1;4 and TIP3;1, in three contrasting chickpea genotypes under high vapor pressure deficit (VPD) treatment. The chickpea TIP3;1 gene got significantly up regulated under high VPD conditions with higher relative expression in the drought susceptible genotype, confirming the suitability of the selected reference genes for expression analysis. This is the first comprehensive study on the stability of the new generation reference genes for qPCR studies in chickpea across species, different tissues and abiotic stresses. PMID:26863232

  12. Identification and Validation of Reference Genes and Their Impact on Normalized Gene Expression Studies across Cultivated and Wild Cicer Species.

    PubMed

    Reddy, Dumbala Srinivas; Bhatnagar-Mathur, Pooja; Reddy, Palakolanu Sudhakar; Sri Cindhuri, Katamreddy; Sivaji Ganesh, Adusumalli; Sharma, Kiran Kumar

    2016-01-01

    Quantitative Real-Time PCR (qPCR) is a preferred and reliable method for accurate quantification of gene expression to understand precise gene functions. A total of 25 candidate reference genes including traditional and new generation reference genes were selected and evaluated in a diverse set of chickpea samples. The samples used in this study included nine chickpea genotypes (Cicer spp.) comprising of cultivated and wild species, six abiotic stress treatments (drought, salinity, high vapor pressure deficit, abscisic acid, cold and heat shock), and five diverse tissues (leaf, root, flower, seedlings and seed). The geNorm, NormFinder and RefFinder algorithms used to identify stably expressed genes in four sample sets revealed stable expression of UCP and G6PD genes across genotypes, while TIP41 and CAC were highly stable under abiotic stress conditions. While PP2A and ABCT genes were ranked as best for different tissues, ABCT, UCP and CAC were most stable across all samples. This study demonstrated the usefulness of new generation reference genes for more accurate qPCR based gene expression quantification in cultivated as well as wild chickpea species. Validation of the best reference genes was carried out by studying their impact on normalization of aquaporin genes PIP1;4 and TIP3;1, in three contrasting chickpea genotypes under high vapor pressure deficit (VPD) treatment. The chickpea TIP3;1 gene got significantly up regulated under high VPD conditions with higher relative expression in the drought susceptible genotype, confirming the suitability of the selected reference genes for expression analysis. This is the first comprehensive study on the stability of the new generation reference genes for qPCR studies in chickpea across species, different tissues and abiotic stresses.

  13. Reference genes for gene expression studies in wheat flag leaves grown under different farming conditions

    PubMed Central

    2011-01-01

    Background Internal control genes with highly uniform expression throughout the experimental conditions are required for accurate gene expression analysis as no universal reference genes exists. In this study, the expression stability of 24 candidate genes from Triticum aestivum cv. Cubus flag leaves grown under organic and conventional farming systems was evaluated in two locations in order to select suitable genes that can be used for normalization of real-time quantitative reverse-transcription PCR (RT-qPCR) reactions. The genes were selected among the most common used reference genes as well as genes encoding proteins involved in several metabolic pathways. Findings Individual genes displayed different expression rates across all samples assayed. Applying geNorm, a set of three potential reference genes were suitable for normalization of RT-qPCR reactions in winter wheat flag leaves cv. Cubus: TaFNRII (ferredoxin-NADP(H) oxidoreductase; AJ457980.1), ACT2 (actin 2; TC234027), and rrn26 (a putative homologue to RNA 26S gene; AL827977.1). In addition of these three genes that were also top-ranked by NormFinder, two extra genes: CYP18-2 (Cyclophilin A, AY456122.1) and TaWIN1 (14-3-3 like protein, AB042193) were most consistently stably expressed. Furthermore, we showed that TaFNRII, ACT2, and CYP18-2 are suitable for gene expression normalization in other two winter wheat varieties (Tommi and Centenaire) grown under three treatments (organic, conventional and no nitrogen) and a different environment than the one tested with cv. Cubus. Conclusions This study provides a new set of reference genes which should improve the accuracy of gene expression analyses when using wheat flag leaves as those related to the improvement of nitrogen use efficiency for cereal production. PMID:21951810

  14. Identification and evaluation of reference genes for accurate gene expression normalization of fresh and frozen-thawed spermatozoa of water buffalo (Bubalus bubalis).

    PubMed

    Ashish, Shende; Bhure, S K; Harikrishna, Pillai; Ramteke, S S; Muhammed Kutty, V H; Shruthi, N; Ravi Kumar, G V P P S; Manish, Mahawar; Ghosh, S K; Mihir, Sarkar

    2017-04-01

    The quantitative real time PCR (qRT-PCR) has become an important tool for gene-expression analysis for a selected number of genes in life science. Although large dynamic range, sensitivity and reproducibility of qRT-PCR is good, the reliability majorly depend on the selection of proper reference genes (RGs) employed for normalization. Although, RGs expression has been reported to vary considerably within same cell type with different experimental treatments. No systematic study has been conducted to identify and evaluate the appropriate RGs in spermatozoa of domestic animals. Therefore, this study was conducted to analyze suitable stable RGs in fresh and frozen-thawed spermatozoa. We have assessed 13 candidate RGs (BACT, RPS18s, RPS15A, ATP5F1, HMBS, ATP2B4, RPL13, EEF2, TBP, EIF2B2, MDH1, B2M and GLUT5) of different functions and pathways using five algorithms. Regardless of the approach, the ranking of the most and the least candidate RGs remained almost same. The comprehensive ranking by RefFinder showed GLUT5, ATP2B4 and B2M, MDH1 as the top two stable and least stable RGs, respectively. The expression levels of four heat shock proteins (HSP) were employed as a target gene to evaluate RGs efficiency for normalization. The results demonstrated an exponential difference in expression levels of the four HSP genes upon normalization of the data with the most stable and the least stable RGs. Our study, provides a convenient RGs for normalization of gene-expression of key metabolic pathways effected during freezing and thawing of spermatozoa of buffalo and other closely related bovines. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Validation of Reference Genes for Gene Expression Studies in Virus-Infected Nicotiana benthamiana Using Quantitative Real-Time PCR

    PubMed Central

    Han, Chenggui; Yu, Jialin; Li, Dawei; Zhang, Yongliang

    2012-01-01

    Nicotiana benthamiana is the most widely-used experimental host in plant virology. The recent release of the draft genome sequence for N. benthamiana consolidates its role as a model for plant–pathogen interactions. Quantitative real-time PCR (qPCR) is commonly employed for quantitative gene expression analysis. For valid qPCR analysis, accurate normalisation of gene expression against an appropriate internal control is required. Yet there has been little systematic investigation of reference gene stability in N. benthamiana under conditions of viral infections. In this study, the expression profiles of 16 commonly used housekeeping genes (GAPDH, 18S, EF1α, SAMD, L23, UK, PP2A, APR, UBI3, SAND, ACT, TUB, GBP, F-BOX, PPR and TIP41) were determined in N. benthamiana and those with acceptable expression levels were further selected for transcript stability analysis by qPCR of complementary DNA prepared from N. benthamiana leaf tissue infected with one of five RNA plant viruses (Tobacco necrosis virus A, Beet black scorch virus, Beet necrotic yellow vein virus, Barley stripe mosaic virus and Potato virus X). Gene stability was analysed in parallel by three commonly-used dedicated algorithms: geNorm, NormFinder and BestKeeper. Statistical analysis revealed that the PP2A, F-BOX and L23 genes were the most stable overall, and that the combination of these three genes was sufficient for accurate normalisation. In addition, the suitability of PP2A, F-BOX and L23 as reference genes was illustrated by expression-level analysis of AGO2 and RdR6 in virus-infected N. benthamiana leaves. This is the first study to systematically examine and evaluate the stability of different reference genes in N. benthamiana. Our results not only provide researchers studying these viruses a shortlist of potential housekeeping genes to use as normalisers for qPCR experiments, but should also guide the selection of appropriate reference genes for gene expression studies of N. benthamiana under

  16. Robust TLR4-induced gene expression patterns are not an accurate indicator of human immunity

    PubMed Central

    2010-01-01

    Background Activation of Toll-like receptors (TLRs) is widely accepted as an essential event for defence against infection. Many TLRs utilize a common signalling pathway that relies on activation of the kinase IRAK4 and the transcription factor NFκB for the rapid expression of immunity genes. Methods 21 K DNA microarray technology was used to evaluate LPS-induced (TLR4) gene responses in blood monocytes from a child with an IRAK4-deficiency. In vitro responsiveness to LPS was confirmed by real-time PCR and ELISA and compared to the clinical predisposition of the child and IRAK4-deficient mice to Gram negative infection. Results We demonstrated that the vast majority of LPS-responsive genes in IRAK4-deficient monocytes were greatly suppressed, an observation that is consistent with the described role for IRAK4 as an essential component of TLR4 signalling. The severely impaired response to LPS, however, is inconsistent with a remarkably low incidence of Gram negative infections observed in this child and other children with IRAK4-deficiency. This unpredicted clinical phenotype was validated by demonstrating that IRAK4-deficient mice had a similar resistance to infection with Gram negative S. typhimurium as wildtype mice. A number of immunity genes, such as chemokines, were expressed at normal levels in human IRAK4-deficient monocytes, indicating that particular IRAK4-independent elements within the repertoire of TLR4-induced responses are expressed. Conclusions Sufficient defence to Gram negative immunity does not require IRAK4 or a robust, 'classic' inflammatory and immune response. PMID:20105294

  17. 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

  18. 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.

  19. Expression profiles of key phenylpropanoid genes during Vanilla planifolia pod development reveal a positive correlation between PAL gene expression and vanillin biosynthesis.

    PubMed

    Fock-Bastide, Isabelle; Palama, Tony Lionel; Bory, Séverine; Lécolier, Aurélie; Noirot, Michel; Joët, Thierry

    2014-01-01

    In Vanilla planifolia pods, development of flavor precursors is dependent on the phenylpropanoid pathway. The distinctive vanilla aroma is produced by numerous phenolic compounds of which vanillin is the most important. Because of the economic importance of vanilla, vanillin biosynthetic pathways have been extensively studied but agreement has not yet been reached on the processes leading to its accumulation. In order to explore the transcriptional control exerted on these pathways, five key phenylpropanoid genes expressed during pod development were identified and their mRNA accumulation profiles were evaluated during pod development and maturation using quantitative real-time PCR. As a prerequisite for expression analysis using qRT-PCR, five potential reference genes were tested, and two genes encoding Actin and EF1 were shown to be the most stable reference genes for accurate normalization during pod development. For the first time, genes encoding a phenylalanine ammonia-lyase (VpPAL1) and a cinnamate 4-hydroxylase (VpC4H1) were identified in vanilla pods and studied during maturation. Among phenylpropanoid genes, differential regulation was observed from 3 to 8 months after pollination. VpPAL1 was gradually up-regulated, reaching the maximum expression level at maturity. In contrast, genes encoding 4HBS, C4H, OMT2 and OMT3 did not show significant increase in expression levels after the fourth month post-pollination. Expression profiling of these key phenylpropanoid genes is also discussed in light of accumulation patterns for key phenolic compounds. Interestingly, VpPAL1 gene expression was shown to be positively correlated to maturation and vanillin accumulation. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  20. Evaluation of Suitable Reference Genes for Normalization of qPCR Gene Expression Studies in Brinjal (Solanum melongena L.) During Fruit Developmental Stages.

    PubMed

    Kanakachari, Mogilicherla; Solanke, Amolkumar U; Prabhakaran, Narayanasamy; Ahmad, Israr; Dhandapani, Gurusamy; Jayabalan, Narayanasamy; Kumar, Polumetla Ananda

    2016-02-01

    Brinjal/eggplant/aubergine is one of the major solanaceous vegetable crops. Recent availability of genome information greatly facilitates the fundamental research on brinjal. Gene expression patterns during different stages of fruit development can provide clues towards the understanding of its biological functions. Quantitative real-time PCR (qPCR) has become one of the most widely used methods for rapid and accurate quantification of gene expression. However, its success depends on the use of a suitable reference gene for data normalization. For qPCR analysis, a single reference gene is not universally suitable for all experiments. Therefore, reference gene validation is a crucial step. Suitable reference genes for qPCR analysis of brinjal fruit development have not been investigated so far. In this study, we have selected 21 candidate reference genes from the Brinjal (Solanum melongena) Plant Gene Indices database (compbio.dfci.harvard.edu/tgi/plant.html) and studied their expression profiles by qPCR during six different fruit developmental stages (0, 5, 10, 20, 30, and 50 days post anthesis) along with leaf samples of the Pusa Purple Long (PPL) variety. To evaluate the stability of gene expression, geNorm and NormFinder analytical softwares were used. geNorm identified SAND (SAND family protein) and TBP (TATA binding protein) as the best pairs of reference genes in brinjal fruit development. The results showed that for brinjal fruit development, individual or a combination of reference genes should be selected for data normalization. NormFinder identified Expressed gene (expressed sequence) as the best single reference gene in brinjal fruit development. In this study, we have identified and validated for the first time reference genes to provide accurate transcript normalization and quantification at various fruit developmental stages of brinjal which can also be useful for gene expression studies in other Solanaceae plant species.

  1. 1NON-INVASIVE RADIOIODINE IMAGING FOR ACCURATE QUANTITATION OF NIS REPORTER GENE EXPRESSION IN TRANSPLANTED HEARTS

    PubMed Central

    Ricci, Davide; Mennander, Ari A; Pham, Linh D; Rao, Vinay P; Miyagi, Naoto; Byrne, Guerard W; Russell, Stephen J; McGregor, Christopher GA

    2008-01-01

    Objectives We studied the concordance of transgene expression in the transplanted heart using bicistronic adenoviral vector coding for a transgene of interest (human carcinoembryonic antigen: hCEA - beta human chorionic gonadotropin: βhCG) and for a marker imaging transgene (human sodium iodide symporter: hNIS). Methods Inbred Lewis rats were used for syngeneic heterotopic cardiac transplantation. Donor rat hearts were perfused ex vivo for 30 minutes prior to transplantation with University of Wisconsin (UW) solution (n=3), with 109 pfu/ml of adenovirus expressing hNIS (Ad-NIS; n=6), hNIS-hCEA (Ad-NIS-CEA; n=6) and hNIS-βhCG (Ad-NIS-CG; n=6). On post-operative day (POD) 5, 10, 15 all animals underwent micro-SPECT/CT imaging of the donor hearts after tail vein injection of 1000 μCi 123I and blood sample collection for hCEA and βhCG quantification. Results Significantly higher image intensity was noted in the hearts perfused with Ad-NIS (1.1±0.2; 0.9±0.07), Ad-NIS-CEA (1.2±0.3; 0.9±0.1) and Ad-NIS-CG (1.1±0.1; 0.9±0.1) compared to UW group (0.44±0.03; 0.47±0.06) on POD 5 and 10 (p<0.05). Serum levels of hCEA and βhCG increased in animals showing high cardiac 123I uptake, but not in those with lower uptake. Above this threshold, image intensities correlated well with serum levels of hCEA and βhCG (R2=0.99 and R2=0.96 respectively). Conclusions These data demonstrate that hNIS is an excellent reporter gene for the transplanted heart. The expression level of hNIS can be accurately and non-invasively monitored by serial radioisotopic single photon emission computed tomography (SPECT) imaging. High concordance has been demonstrated between imaging and soluble marker peptides at the maximum transgene expression on POD 5. PMID:17980613

  2. Bacterial reference genes for gene expression studies by RT-qPCR: survey and analysis.

    PubMed

    Rocha, Danilo J P; Santos, Carolina S; Pacheco, Luis G C

    2015-09-01

    The appropriate choice of reference genes is essential for accurate normalization of gene expression data obtained by the method of reverse transcription quantitative real-time PCR (RT-qPCR). In 2009, a guideline called the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) highlighted the importance of the selection and validation of more than one suitable reference gene for obtaining reliable RT-qPCR results. Herein, we searched the recent literature in order to identify the bacterial reference genes that have been most commonly validated in gene expression studies by RT-qPCR (in the first 5 years following publication of the MIQE guidelines). Through a combination of different search parameters with the text mining tool MedlineRanker, we identified 145 unique bacterial genes that were recently tested as candidate reference genes. Of these, 45 genes were experimentally validated and, in most of the cases, their expression stabilities were verified using the software tools geNorm and NormFinder. It is noteworthy that only 10 of these reference genes had been validated in two or more of the studies evaluated. An enrichment analysis using Gene Ontology classifications demonstrated that genes belonging to the functional categories of DNA Replication (GO: 0006260) and Transcription (GO: 0006351) rendered a proportionally higher number of validated reference genes. Three genes in the former functional class were also among the top five most stable genes identified through an analysis of gene expression data obtained from the Pathosystems Resource Integration Center. These results may provide a guideline for the initial selection of candidate reference genes for RT-qPCR studies in several different bacterial species.

  3. Prostate cancer-associated gene expression alterations determined from needle biopsies.

    PubMed

    Qian, David Z; Huang, Chung-Ying; O'Brien, Catherine A; Coleman, Ilsa M; Garzotto, Mark; True, Lawrence D; Higano, Celestia S; Vessella, Robert; Lange, Paul H; Nelson, Peter S; Beer, Tomasz M

    2009-05-01

    To accurately identify gene expression alterations that differentiate neoplastic from normal prostate epithelium using an approach that avoids contamination by unwanted cellular components and is not compromised by acute gene expression changes associated with tumor devascularization and resulting ischemia. Approximately 3,000 neoplastic and benign prostate epithelial cells were isolated using laser capture microdissection from snap-frozen prostate biopsy specimens provided by 31 patients who subsequently participated in a clinical trial of preoperative chemotherapy. cDNA synthesized from amplified total RNA was hybridized to custom-made microarrays composed of 6,200 clones derived from the Prostate Expression Database. Expression differences for selected genes were verified using quantitative reverse transcription-PCR. Comparative analyses identified 954 transcript alterations associated with cancer (q < 0.01%), including 149 differentially expressed genes with no known functional roles. Gene expression changes associated with ischemia and surgical removal of the prostate gland were absent. Genes up-regulated in prostate cancer were statistically enriched in categories related to cellular metabolism, energy use, signal transduction, and molecular transport. Genes down-regulated in prostate cancers were enriched in categories related to immune response, cellular responses to pathogens, and apoptosis. A heterogeneous pattern of androgen receptor expression changes was noted. In exploratory analyses, androgen receptor down-regulation was associated with a lower probability of cancer relapse after neoadjuvant chemotherapy followed by radical prostatectomy. Assessments of tumor phenotypes based on gene expression for treatment stratification and drug targeting of oncogenic alterations may best be ascertained using biopsy-based analyses where the effects of ischemia do not complicate interpretation.

  4. Prostate Cancer-Associated Gene Expression Alterations Determined from Needle Biopsies

    PubMed Central

    Qian, David Z.; Huang, Chung-Ying; O'Brien, Catherine A.; Coleman, Ilsa M.; Garzotto, Mark; True, Lawrence D.; Higano, Celestia S.; Vessella, Robert; Lange, Paul H.; Nelson, Peter S.; Beer, Tomasz M.

    2010-01-01

    Purpose To accurately identify gene expression alterations that differentiate neoplastic from normal prostate epithelium using an approach that avoids contamination by unwanted cellular components and is not compromised by acute gene expression changes associated with tumor devascularization and resulting ischemia. Experimental Design Approximately 3,000 neoplastic and benign prostate epithelial cells were isolated using laser capture microdissection from snap-frozen prostate biopsy specimens provided by 31 patients who subsequently participated in a clinical trial of preoperative chemotherapy. cDNA synthesized from amplified total RNA was hybridized to custom-made microarrays comprised of 6200 clones derived from the Prostate Expression Database. Expression differences for selected genes were verified using quantitative RT-PCR. Results Comparative analyses identified 954 transcript alterations associated with cancer (q value <0.01%) including 149 differentially expressed genes with no known functional roles. Gene expression changes associated with ischemia and surgical removal of the prostate gland were absent. Genes up-regulated in prostate cancer were statistically enriched in categories related to cellular metabolism, energy utilization, signal transduction, and molecular transport. Genes down-regulated in prostate cancers were enriched in categories related to immune response, cellular responses to pathogens, and apoptosis. A heterogeneous pattern of AR expression changes was noted. In exploratory analyses, AR down regulation was associated with a lower probability of cancer relapse after neoadjuvant chemotherapy followed by radical prostatectomy. Conclusions Assessments of tumor phenotypes based on gene expression for treatment stratification and drug targeting of oncogenic alterations may best be ascertained using biopsy-based analyses where the effects of ischemia do not complicate interpretation. PMID:19366833

  5. 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

  6. Selection of reference genes for gene expression studies related to intramuscular fat deposition in Capra hircus skeletal muscle.

    PubMed

    Zhu, Wuzheng; Lin, Yaqiu; Liao, Honghai; Wang, Yong

    2015-01-01

    The identification of suitable reference genes is critical for obtaining reliable results from gene expression studies using quantitative real-time PCR (qPCR) because the expression of reference genes may vary considerably under different experimental conditions. In most cases, however, commonly used reference genes are employed in data normalization without proper validation, which may lead to incorrect data interpretation. Here, we aim to select a set of optimal reference genes for the accurate normalization of gene expression associated with intramuscular fat (IMF) deposition during development. In the present study, eight reference genes (PPIB, HMBS, RPLP0, B2M, YWHAZ, 18S, GAPDH and ACTB) were evaluated by three different algorithms (geNorm, NormFinder and BestKeeper) in two types of muscle tissues (longissimus dorsi muscle and biceps femoris muscle) across different developmental stages. All three algorithms gave similar results. PPIB and HMBS were identified as the most stable reference genes, while the commonly used reference genes 18S and GAPDH were the most variably expressed, with expression varying dramatically across different developmental stages. Furthermore, to reveal the crucial role of appropriate reference genes in obtaining a reliable result, analysis of PPARG expression was performed by normalization to the most and the least stable reference genes. The relative expression levels of PPARG normalized to the most stable reference genes greatly differed from those normalized to the least stable one. Therefore, evaluation of reference genes must be performed for a given experimental condition before the reference genes are used. PPIB and HMBS are the optimal reference genes for analysis of gene expression associated with IMF deposition in skeletal muscle during development.

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

    PubMed

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

    2015-01-01

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

  8. A biomarker-based screen of a gene expression compendium ...

    EPA Pesticide Factsheets

    Computational approaches were developed to identify factors that regulate Nrf2 in a large gene expression compendium of microarray profiles including >2000 comparisons which queried the effects of chemicals, genes, diets, and infectious agents on gene expression in the mouse liver. A gene expression biomarker of 48 genes which accurately predicted Nrf2 activation was used to identify factors which resulted in a gene expression profile with significant correlation to the biomarker. A number of novel insights were made. Chemicals that activated the xenosensor constitutive activated receptor (CAR) consistently activated Nrf2 across hundreds of profiles, possibly downstream of Cyp-induced increases in oxidative stress. Nrf2 activation was also found to be negatively regulated by the growth hormone (GH)- and androgen-regulated transcription factor STAT5b, a transcription factor suppressed by CAR. Nrf2 was activated when STAT5b was suppressed in female mice vs. male mice, after exposure to estrogens, or in genetic mutants in which GH signaling was disrupted. A subset of the mutants that show STAT5b suppression and Nrf2 activation result in increased resistance to environmental stressors and increased longevity. This study describes a novel approach for understanding the network of factors that regulate the Nrf2 pathway and highlights novel interactions between Nrf2, CAR and STAT5b transcription factors. (This abstract does not represent EPA policy.) Computational appr

  9. Spatial reconstruction of single-cell gene expression data.

    PubMed

    Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

    2015-05-01

    Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

  10. 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.

  11. The Renilla luciferase gene as a reference gene for normalization of gene expression in transiently transfected cells.

    PubMed

    Jiwaji, Meesbah; Daly, Rónán; Pansare, Kshama; McLean, Pauline; Yang, Jingli; Kolch, Walter; Pitt, Andrew R

    2010-12-31

    The importance of appropriate normalization controls in quantitative real-time polymerase chain reaction (qPCR) experiments has become more apparent as the number of biological studies using this methodology has increased. In developing a system to study gene expression from transiently transfected plasmids, it became clear that normalization using chromosomally encoded genes is not ideal, at it does not take into account the transfection efficiency and the significantly lower expression levels of the plasmids. We have developed and validated a normalization method for qPCR using a co-transfected plasmid. The best chromosomal gene for normalization in the presence of the transcriptional activators used in this study, cadmium, dexamethasone, forskolin and phorbol-12-myristate 13-acetate was first identified. qPCR data was analyzed using geNorm, Normfinder and BestKeeper. Each software application was found to rank the normalization controls differently with no clear correlation. Including a co-transfected plasmid encoding the Renilla luciferase gene (Rluc) in this analysis showed that its calculated stability was not as good as the optimised chromosomal genes, most likely as a result of the lower expression levels and transfection variability. Finally, we validated these analyses by testing two chromosomal genes (B2M and ActB) and a co-transfected gene (Rluc) under biological conditions. When analyzing co-transfected plasmids, Rluc normalization gave the smallest errors compared to the chromosomal reference genes. Our data demonstrates that transfected Rluc is the most appropriate normalization reference gene for transient transfection qPCR analysis; it significantly reduces the standard deviation within biological experiments as it takes into account the transfection efficiencies and has easily controllable expression levels. This improves reproducibility, data validity and most importantly, enables accurate interpretation of qPCR data.

  12. Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis.

    PubMed

    Chen, Chun; Xie, Tingna; Ye, Sudan; Jensen, Annette Bruun; Eilenberg, Jørgen

    2016-01-01

    The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host-pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S), 28S rRNA(28S) and elongation factor 1 alpha-like protein (EF1), were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae), and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189), 28S (1.414) and EF1 (3). The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis. Copyright © 2015 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

  13. Evaluation of reference genes for gene expression studies in radish (Raphanus sativus L.) using quantitative real-time PCR.

    PubMed

    Xu, Yuanyuan; Zhu, Xianwen; Gong, Yiqin; Xu, Liang; Wang, Yan; Liu, Liwang

    2012-08-03

    Real-time quantitative reverse transcription PCR (RT-qPCR) is a rapid and reliable method for gene expression studies. Normalization based on reference genes can increase the reliability of this technique; however, recent studies have shown that almost no single reference gene is universal for all possible experimental conditions. In this study, eight frequently used reference genes were investigated, including Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), Actin2/7 (ACT), Tubulin alpha-5 (TUA), Tubulin beta-1 (TUB), 18S ribosomal RNA (18SrRNA), RNA polymerase-II transcription factor (RPII), Elongation factor 1-b (EF-1b) and Translation elongation factor 2 (TEF2). Expression stability of candidate reference genes was examined across 27 radish samples, representing a range of tissue types, cultivars, photoperiodic and vernalization treatments, and developmental stages. The eight genes in these sample pools displayed a wide range of Ct values and were variably expressed. Two statistical software packages, geNorm and NormFinder showed that TEF2, RPII and ACT appeared to be relatively stable and therefore the most suitable for use as reference genes. These results facilitate selection of desirable reference genes for accurate gene expression studies in radish. Copyright © 2012 Elsevier Inc. All rights reserved.

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

    PubMed Central

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

    2018-01-01

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

  15. Gene Expression Profiling of Benign and Malignant Pheochromocytoma

    PubMed Central

    BROUWERS, FREDERIEKE M.; ELKAHLOUN, ABDEL G.; MUNSON, PETER J.; EISENHOFER, GRAEME; BARB, JENNIFER; LINEHAN, W. MARSTON; LENDERS, JACQUES W.M.; DE KRIJGER, RONALD; MANNELLI, MASSIMO; UDELSMAN, ROBERT; OCAL, IDRIS T.; SHULKIN, BARRY L.; BORNSTEIN, STEFAN R.; BREZA, JAN; KSINANTOVA, LUCIA; PACAK, KAREL

    2016-01-01

    There are currently no reliable diagnostic and prognostic markers or effective treatments for malignant pheochromocytoma. This study used oligonucleotide microarrays to examine gene expression profiles in pheochromocytomas from 90 patients, including 20 with malignant tumors, the latter including metastases and primary tumors from which metastases developed. Other subgroups of tumors included those defined by tissue norepinephrine compared to epinephrine contents (i.e., noradrenergic versus adrenergic phenotypes), adrenal versus extra-adrenal locations, and presence of germline mutations of genes pre-disposing to the tumor. Correcting for the confounding influence of nora-drenergic versus adrenergic catecholamine phenotype by the analysis of variance revealed a larger and more accurate number of genes that discriminated benign from malignant pheochromocytomas than when the confounding influence of catecholamine phenotype was not considered. Seventy percent of these genes were underexpressed in malignant compared to benign tumors. Similarly, 89% of genes were underexpressed in malignant primary tumors compared to benign tumors, suggesting that malignant potential is largely characterized by a less-differentiated pattern of gene expression. The present database of differentially expressed genes provides a unique resource for mapping the pathways leading to malignancy and for establishing new targets for treatment and diagnostic and prognostic markers of malignant disease. The database may also be useful for examining mechanisms of tumorigenesis and genotype–phenotype relationships. Further progress on the basis of this database can be made from follow-up confirmatory studies, application of bioinformatics approaches for data mining and pathway analyses, testing in pheochromocytoma cell culture and animal model systems, and retrospective and prospective studies of diagnostic markers. PMID:17102123

  16. 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

  17. 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.

  18. Reliable Gene Expression Measurements from Fine Needle Aspirates of Pancreatic Tumors

    PubMed Central

    Anderson, Michelle A.; Brenner, Dean E.; Scheiman, James M.; Simeone, Diane M.; Singh, Nalina; Sikora, Matthew J.; Zhao, Lili; Mertens, Amy N.; Rae, James M.

    2010-01-01

    Background and aims: Biomarker use for pancreatic cancer diagnosis has been impaired by a lack of samples suitable for reliable quantitative RT-PCR (qRT-PCR). Fine needle aspirates (FNAs) from pancreatic masses were studied to define potential causes of RNA degradation and develop methods for accurately measuring gene expression. Methods: Samples from 32 patients were studied. RNA degradation was assessed by using a multiplex PCR assay for varying lengths of glyceraldehyde-3-phosphate dehydrogenase, and effects on qRT-PCR were determined by using a 150-bp and a 80-bp amplicon for RPS6. Potential causes of and methods to circumvent RNA degradation were studied by using FNAs from a pancreatic cancer xenograft. Results: RNA extracted from pancreatic mass FNAs was extensively degraded. Fragmentation was related to needle bore diameter and could not be overcome by alterations in aspiration technique. Multiplex PCR for glyceraldehyde-3-phosphate dehydrogenase could distinguish samples that were suitable for qRT-PCR. The use of short PCR amplicons (<100 bp) provided reliable gene expression analysis from FNAs. When appropriate samples were used, the assay was highly reproducible for gene copy number with minimal (0.0003 or about 0.7% of total) variance. Conclusions: The degraded properties of endoscopic FNAs markedly affect the accuracy of gene expression measurements. Our novel approach to designate specimens “informative” for qRT-PCR allowed accurate molecular assessment for the diagnosis of pancreatic diseases. PMID:20709792

  19. Comprehensive evaluation of candidate reference genes for gene expression studies in Lysiphlebia japonica (Hymenoptera: Aphidiidae) using RT-qPCR.

    PubMed

    Gao, Xue-Ke; Zhang, Shuai; Luo, Jun-Yu; Wang, Chun-Yi; Lü, Li-Min; Zhang, Li-Juan; Zhu, Xiang-Zhen; Wang, Li; Lu, Hui; Cui, Jin-Jie

    2017-12-30

    Lysiphlebia japonica (Ashmead) is a predominant parasitoid of cotton-melon aphids in the fields of northern China with a proven ability to effectively control cotton aphid populations in early summer. For accurate normalization of gene expression in L. japonica using quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR), reference genes with stable gene expression patterns are essential. However, no appropriate reference genes is L. japonica have been investigated to date. In the present study, 12 selected housekeeping genes from L. japonica were cloned. We evaluated the stability of these genes under various experimental treatments by RT-qPCR using four independent (geNorm, NormFinder, BestKeeper and Delta Ct) and one comparative (RefFinder) algorithm. We identified genes showing the most stable levels of expression: DIMT, 18S rRNA, and RPL13 during different stages; AK, RPL13, and TBP among sexes; EF1A, PPI, and RPL27 in different tissues, and EF1A, RPL13, and PPI in adults fed on different diets. Moreover, the expression profile of a target gene (odorant receptor 1, OR1) studied during the developmental stages confirms the reliability of the chosen selected reference genes. This study provides for the first time a comprehensive list of suitable reference genes for gene expression studies in L. japonica and will benefit subsequent genomics and functional genomics research on this natural enemy. Copyright © 2017. Published by Elsevier B.V.

  20. Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat

    PubMed Central

    2014-01-01

    Background Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution ‘nullisomic-tetrasomic’ lines) with next generation deep sequencing of gene transcripts (RNA-Seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative contribution of individual homoeoloci to gene expression. Results We discover, based on a sample comprising ~5-10% of the total wheat gene content, that at least 45% of wheat genes are expressed from all three distinct homoeoloci. Most of these genes show strikingly biased expression patterns in which expression is dominated by a single homoeolocus. The remaining ~55% of wheat genes are expressed from either one or two homoeoloci only, through a combination of extensive transcriptional silencing and homoeolocus loss. Conclusions We conclude that wheat is tending towards functional diploidy, through a variety of mechanisms causing single homoeoloci to become the predominant source of gene transcripts. This discovery has profound consequences for wheat breeding and our understanding of wheat evolution. PMID:24726045

  1. Identification of internal control genes for quantitative expression analysis by real-time PCR in bovine peripheral lymphocytes.

    PubMed

    Spalenza, Veronica; Girolami, Flavia; Bevilacqua, Claudia; Riondato, Fulvio; Rasero, Roberto; Nebbia, Carlo; Sacchi, Paola; Martin, Patrice

    2011-09-01

    Gene expression studies in blood cells, particularly lymphocytes, are useful for monitoring potential exposure to toxicants or environmental pollutants in humans and livestock species. Quantitative PCR is the method of choice for obtaining accurate quantification of mRNA transcripts although variations in the amount of starting material, enzymatic efficiency, and the presence of inhibitors can lead to evaluation errors. As a result, normalization of data is of crucial importance. The most common approach is the use of endogenous reference genes as an internal control, whose expression should ideally not vary among individuals and under different experimental conditions. The accurate selection of reference genes is therefore an important step in interpreting quantitative PCR studies. Since no systematic investigation in bovine lymphocytes has been performed, the aim of the present study was to assess the expression stability of seven candidate reference genes in circulating lymphocytes collected from 15 dairy cows. Following the characterization by flow cytometric analysis of the cell populations obtained from blood through a density gradient procedure, three popular softwares were used to evaluate the gene expression data. The results showed that two genes are sufficient for normalization of quantitative PCR studies in cattle lymphocytes and that YWAHZ, S24 and PPIA are the most stable genes. Copyright © 2010 Elsevier Ltd. All rights reserved.

  2. 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.

  3. 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

  4. Identification of stable reference genes for gene expression analysis of three-dimensional cultivated human bone marrow-derived mesenchymal stromal cells for bone tissue engineering.

    PubMed

    Rauh, Juliane; Jacobi, Angela; Stiehler, Maik

    2015-02-01

    The principles of tissue engineering (TE) are widely used for bone regeneration concepts. Three-dimensional (3D) cultivation of autologous human mesenchymal stromal cells (MSCs) on porous scaffolds is the basic prerequisite to generate newly formed bone tissue. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a specific and sensitive analytical tool for the measurement of mRNA-levels in cells or tissues. For an accurate quantification of gene expression levels, stably expressed reference genes (RGs) are essential to obtain reliable results. Since the 3D environment can affect a cell's morphology, proliferation, and gene expression profile compared with two-dimensional (2D) cultivation, there is a need to identify robust RGs for the quantification of gene expression. So far, this issue has not been adequately investigated. The aim of this study was to identify the most stably expressed RGs for gene expression analysis of 3D-cultivated human bone marrow-derived MSCs (BM-MSCs). For this, we analyzed the gene expression levels of n=31 RGs in 3D-cultivated human BM-MSCs from six different donors compared with conventional 2D cultivation using qRT-PCR. MSCs isolated from bone marrow aspirates were cultivated on human cancellous bone cube scaffolds for 14 days. Osteogenic differentiation was assessed by cell-specific alkaline phosphatase (ALP) activity and expression of osteogenic marker genes. Expression levels of potential reference and target genes were quantified using commercially available TaqMan(®) assays. mRNA expression stability of RGs was determined by calculating the coefficient of variation (CV) and using the algorithms of geNorm and NormFinder. Using both algorithms, we identified TATA box binding protein (TBP), transferrin receptor (p90, CD71) (TFRC), and hypoxanthine phosphoribosyltransferase 1 (HPRT1) as the most stably expressed RGs in 3D-cultivated BM-MSCs. Notably, genes that are routinely used as RGs, for example, beta actin

  5. Identification of Stable Reference Genes for Gene Expression Analysis of Three-Dimensional Cultivated Human Bone Marrow-Derived Mesenchymal Stromal Cells for Bone Tissue Engineering

    PubMed Central

    Rauh, Juliane; Jacobi, Angela

    2015-01-01

    The principles of tissue engineering (TE) are widely used for bone regeneration concepts. Three-dimensional (3D) cultivation of autologous human mesenchymal stromal cells (MSCs) on porous scaffolds is the basic prerequisite to generate newly formed bone tissue. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a specific and sensitive analytical tool for the measurement of mRNA-levels in cells or tissues. For an accurate quantification of gene expression levels, stably expressed reference genes (RGs) are essential to obtain reliable results. Since the 3D environment can affect a cell's morphology, proliferation, and gene expression profile compared with two-dimensional (2D) cultivation, there is a need to identify robust RGs for the quantification of gene expression. So far, this issue has not been adequately investigated. The aim of this study was to identify the most stably expressed RGs for gene expression analysis of 3D-cultivated human bone marrow-derived MSCs (BM-MSCs). For this, we analyzed the gene expression levels of n=31 RGs in 3D-cultivated human BM-MSCs from six different donors compared with conventional 2D cultivation using qRT-PCR. MSCs isolated from bone marrow aspirates were cultivated on human cancellous bone cube scaffolds for 14 days. Osteogenic differentiation was assessed by cell-specific alkaline phosphatase (ALP) activity and expression of osteogenic marker genes. Expression levels of potential reference and target genes were quantified using commercially available TaqMan® assays. mRNA expression stability of RGs was determined by calculating the coefficient of variation (CV) and using the algorithms of geNorm and NormFinder. Using both algorithms, we identified TATA box binding protein (TBP), transferrin receptor (p90, CD71) (TFRC), and hypoxanthine phosphoribosyltransferase 1 (HPRT1) as the most stably expressed RGs in 3D-cultivated BM-MSCs. Notably, genes that are routinely used as RGs, for example, beta actin

  6. Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

    PubMed

    Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

    2014-05-01

    Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  7. Selection of reference genes for gene expression studies in virus-infected monocots using quantitative real-time PCR.

    PubMed

    Zhang, Kun; Niu, Shaofang; Di, Dianping; Shi, Lindan; Liu, Deshui; Cao, Xiuling; Miao, Hongqin; Wang, Xianbing; Han, Chenggui; Yu, Jialin; Li, Dawei; Zhang, Yongliang

    2013-10-10

    Both genome-wide transcriptomic surveys of the mRNA expression profiles and virus-induced gene silencing-based molecular studies of target gene during virus-plant interaction involve the precise estimation of the transcript abundance. Quantitative real-time PCR (qPCR) is the most widely adopted technique for mRNA quantification. In order to obtain reliable quantification of transcripts, identification of the best reference genes forms the basis of the preliminary work. Nevertheless, the stability of internal controls in virus-infected monocots needs to be fully explored. In this work, the suitability of ten housekeeping genes (ACT, EF1α, FBOX, GAPDH, GTPB, PP2A, SAND, TUBβ, UBC18 and UK) for potential use as reference genes in qPCR were investigated in five different monocot plants (Brachypodium, barley, sorghum, wheat and maize) under infection with different viruses including Barley stripe mosaic virus (BSMV), Brome mosaic virus (BMV), Rice black-streaked dwarf virus (RBSDV) and Sugarcane mosaic virus (SCMV). By using three different algorithms, the most appropriate reference genes or their combinations were identified for different experimental sets and their effectiveness for the normalisation of expression studies were further validated by quantitative analysis of a well-studied PR-1 gene. These results facilitate the selection of desirable reference genes for more accurate gene expression studies in virus-infected monocots. Copyright © 2013 Elsevier B.V. All rights reserved.

  8. Quantification of differential gene expression by multiplexed targeted resequencing of cDNA

    PubMed Central

    Arts, Peer; van der Raadt, Jori; van Gestel, Sebastianus H.C.; Steehouwer, Marloes; Shendure, Jay; Hoischen, Alexander; Albers, Cornelis A.

    2017-01-01

    Whole-transcriptome or RNA sequencing (RNA-Seq) is a powerful and versatile tool for functional analysis of different types of RNA molecules, but sample reagent and sequencing cost can be prohibitive for hypothesis-driven studies where the aim is to quantify differential expression of a limited number of genes. Here we present an approach for quantification of differential mRNA expression by targeted resequencing of complementary DNA using single-molecule molecular inversion probes (cDNA-smMIPs) that enable highly multiplexed resequencing of cDNA target regions of ∼100 nucleotides and counting of individual molecules. We show that accurate estimates of differential expression can be obtained from molecule counts for hundreds of smMIPs per reaction and that smMIPs are also suitable for quantification of relative gene expression and allele-specific expression. Compared with low-coverage RNA-Seq and a hybridization-based targeted RNA-Seq method, cDNA-smMIPs are a cost-effective high-throughput tool for hypothesis-driven expression analysis in large numbers of genes (10 to 500) and samples (hundreds to thousands). PMID:28474677

  9. Selection and testing of reference genes for accurate RT-qPCR in rice seedlings under iron toxicity.

    PubMed

    Santos, Fabiane Igansi de Castro Dos; Marini, Naciele; Santos, Railson Schreinert Dos; Hoffman, Bianca Silva Fernandes; Alves-Ferreira, Marcio; de Oliveira, Antonio Costa

    2018-01-01

    Reverse Transcription quantitative PCR (RT-qPCR) is a technique for gene expression profiling with high sensibility and reproducibility. However, to obtain accurate results, it depends on data normalization by using endogenous reference genes whose expression is constitutive or invariable. Although the technique is widely used in plant stress analyzes, the stability of reference genes for iron toxicity in rice (Oryza sativa L.) has not been thoroughly investigated. Here, we tested a set of candidate reference genes for use in rice under this stressful condition. The test was performed using four distinct methods: NormFinder, BestKeeper, geNorm and the comparative ΔCt. To achieve reproducible and reliable results, Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines were followed. Valid reference genes were found for shoot (P2, OsGAPDH and OsNABP), root (OsEF-1a, P8 and OsGAPDH) and root+shoot (OsNABP, OsGAPDH and P8) enabling us to perform further reliable studies for iron toxicity in both indica and japonica subspecies. The importance of the study of other than the traditional endogenous genes for use as normalizers is also shown here.

  10. Selection and testing of reference genes for accurate RT-qPCR in rice seedlings under iron toxicity

    PubMed Central

    dos Santos, Fabiane Igansi de Castro; Marini, Naciele; dos Santos, Railson Schreinert; Hoffman, Bianca Silva Fernandes; Alves-Ferreira, Marcio

    2018-01-01

    Reverse Transcription quantitative PCR (RT-qPCR) is a technique for gene expression profiling with high sensibility and reproducibility. However, to obtain accurate results, it depends on data normalization by using endogenous reference genes whose expression is constitutive or invariable. Although the technique is widely used in plant stress analyzes, the stability of reference genes for iron toxicity in rice (Oryza sativa L.) has not been thoroughly investigated. Here, we tested a set of candidate reference genes for use in rice under this stressful condition. The test was performed using four distinct methods: NormFinder, BestKeeper, geNorm and the comparative ΔCt. To achieve reproducible and reliable results, Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines were followed. Valid reference genes were found for shoot (P2, OsGAPDH and OsNABP), root (OsEF-1a, P8 and OsGAPDH) and root+shoot (OsNABP, OsGAPDH and P8) enabling us to perform further reliable studies for iron toxicity in both indica and japonica subspecies. The importance of the study of other than the traditional endogenous genes for use as normalizers is also shown here. PMID:29494624

  11. 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

  12. Selection of Reliable Reference Genes for Gene Expression Studies on Rhododendron molle G. Don.

    PubMed

    Xiao, Zheng; Sun, Xiaobo; Liu, Xiaoqing; Li, Chang; He, Lisi; Chen, Shangping; Su, Jiale

    2016-01-01

    The quantitative real-time polymerase chain reaction (qRT-PCR) approach has become a widely used method to analyze expression patterns of target genes. The selection of an optimal reference gene is a prerequisite for the accurate normalization of gene expression in qRT-PCR. The present study constitutes the first systematic evaluation of potential reference genes in Rhododendron molle G. Don. Eleven candidate reference genes in different tissues and flowers at different developmental stages of R. molle were assessed using the following three software packages: GeNorm, NormFinder, and BestKeeper. The results showed that EF1- α (elongation factor 1-alpha), 18S (18s ribosomal RNA), and RPL3 (ribosomal protein L3) were the most stable reference genes in developing rhododendron flowers and, thus, in all of the tested samples, while tublin ( TUB ) was the least stable. ACT5 (actin), RPL3 , 18S , and EF1- α were found to be the top four choices for different tissues, whereas TUB was not found to favor qRT-PCR normalization in these tissues. Three stable reference genes are recommended for the normalization of qRT-PCR data in R. molle . Furthermore, the expression profiles of RmPSY (phytoene synthase) and RmPDS (phytoene dehydrogenase) were assessed using EF1- α, 18S , ACT5 , RPL3 , and their combination as internals. Similar trends were found, but these trends varied when the least stable reference gene TUB was used. The results further prove that it is necessary to validate the stability of reference genes prior to their use for normalization under different experimental conditions. This study provides useful information for reliable qRT-PCR data normalization in gene studies of R. molle .

  13. RNA-seq reveals more consistent reference genes for gene expression studies in human non-melanoma skin cancers

    PubMed Central

    Tan, Jean-Marie; Payne, Elizabeth J.; Lin, Lynlee L.; Sinnya, Sudipta; Raphael, Anthony P.; Lambie, Duncan; Frazer, Ian H.; Dinger, Marcel E.; Soyer, H. Peter

    2017-01-01

    Identification of appropriate reference genes (RGs) is critical to accurate data interpretation in quantitative real-time PCR (qPCR) experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq) to analyse the transcriptome of a panel of non-melanoma skin cancer lesions, identifying genes that are consistently expressed across all samples. Genes encoding ribosomal proteins were amongst the most stable in this dataset. Validation of this RNA-seq data was examined using qPCR to confirm the suitability of a set of highly stable genes for use as qPCR RGs. These genes will provide a valuable resource for the normalisation of qPCR data for the analysis of non-melanoma skin cancer. PMID:28852586

  14. Enhancing biological relevance of a weighted gene co-expression network for functional module identification.

    PubMed

    Prom-On, Santitham; Chanthaphan, Atthawut; Chan, Jonathan Hoyin; Meechai, Asawin

    2011-02-01

    Relationships among gene expression levels may be associated with the mechanisms of the disease. While identifying a direct association such as a difference in expression levels between case and control groups links genes to disease mechanisms, uncovering an indirect association in the form of a network structure may help reveal the underlying functional module associated with the disease under scrutiny. This paper presents a method to improve the biological relevance in functional module identification from the gene expression microarray data by enhancing the structure of a weighted gene co-expression network using minimum spanning tree. The enhanced network, which is called a backbone network, contains only the essential structural information to represent the gene co-expression network. The entire backbone network is decoupled into a number of coherent sub-networks, and then the functional modules are reconstructed from these sub-networks to ensure minimum redundancy. The method was tested with a simulated gene expression dataset and case-control expression datasets of autism spectrum disorder and colorectal cancer studies. The results indicate that the proposed method can accurately identify clusters in the simulated dataset, and the functional modules of the backbone network are more biologically relevant than those obtained from the original approach.

  15. 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

  16. 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

  17. Epidermal Growth Factor Receptor (EGFR) mutation analysis, gene expression profiling and EGFR protein expression in primary prostate cancer

    PubMed Central

    2011-01-01

    Background Activating mutations of the epidermal growth factor receptor (EGFR) confer sensitivity to the tyrosine kinase inhibitors (TKi), gefitinib and erlotinib. We analysed EGFR expression, EGFR mutation status and gene expression profiles of prostate cancer (PC) to supply a rationale for EGFR targeted therapies in this disease. Methods Mutational analysis of EGFR TK domain (exons from 18 to 21) and immunohistochemistry for EGFR were performed on tumour tissues derived from radical prostatectomy from 100 PC patients. Gene expression profiling using oligo-microarrays was also carried out in 51 of the PC samples. Results EGFR protein overexpression (EGFRhigh) was found in 36% of the tumour samples, and mutations were found in 13% of samples. Patients with EGFRhigh tumours experienced a significantly increased risk of biochemical relapse (hazard ratio-HR 2.52, p=0.02) compared with patients with tumours expressing low levels of EGFR (EGFRlow). Microarray analysis did not reveal any differences in gene expression between EGFRhigh and EGFRlow tumours. Conversely, in EGFRhigh tumours, we were able to identify a 79 gene signature distinguishing mutated from non-mutated tumours. Additionally, 29 genes were found to be differentially expressed between mutated/EGFRhigh (n=3) and mutated/EGFRlow tumours (n=5). Four of the down-regulated genes, U19/EAF2, ABCC4, KLK3 and ANXA3 and one of the up-regulated genes, FOXC1, are involved in PC progression. Conclusions Based on our findings, we hypothesize that accurate definition of the EGFR status could improve prognostic stratification and we suggest a possible role for EGFR-directed therapies in PC patients. Having been generated in a relatively small sample of patients, our results warrant confirmation in larger series. PMID:21266046

  18. Epidermal Growth Factor Receptor (EGFR) mutation analysis, gene expression profiling and EGFR protein expression in primary prostate cancer.

    PubMed

    Peraldo-Neia, Caterina; Migliardi, Giorgia; Mello-Grand, Maurizia; Montemurro, Filippo; Segir, Raffaella; Pignochino, Ymera; Cavalloni, Giuliana; Torchio, Bruno; Mosso, Luciano; Chiorino, Giovanna; Aglietta, Massimo

    2011-01-25

    Activating mutations of the epidermal growth factor receptor (EGFR) confer sensitivity to the tyrosine kinase inhibitors (TKi), gefitinib and erlotinib. We analysed EGFR expression, EGFR mutation status and gene expression profiles of prostate cancer (PC) to supply a rationale for EGFR targeted therapies in this disease. Mutational analysis of EGFR TK domain (exons from 18 to 21) and immunohistochemistry for EGFR were performed on tumour tissues derived from radical prostatectomy from 100 PC patients. Gene expression profiling using oligo-microarrays was also carried out in 51 of the PC samples. EGFR protein overexpression (EGFRhigh) was found in 36% of the tumour samples, and mutations were found in 13% of samples. Patients with EGFRhigh tumours experienced a significantly increased risk of biochemical relapse (hazard ratio-HR 2.52, p=0.02) compared with patients with tumours expressing low levels of EGFR (EGFRlow). Microarray analysis did not reveal any differences in gene expression between EGFRhigh and EGFRlow tumours. Conversely, in EGFRhigh tumours, we were able to identify a 79 gene signature distinguishing mutated from non-mutated tumours. Additionally, 29 genes were found to be differentially expressed between mutated/EGFRhigh (n=3) and mutated/EGFRlow tumours (n=5). Four of the down-regulated genes, U19/EAF2, ABCC4, KLK3 and ANXA3 and one of the up-regulated genes, FOXC1, are involved in PC progression. Based on our findings, we hypothesize that accurate definition of the EGFR status could improve prognostic stratification and we suggest a possible role for EGFR-directed therapies in PC patients. Having been generated in a relatively small sample of patients, our results warrant confirmation in larger series.

  19. Modeling Bi-modality Improves Characterization of Cell Cycle on Gene Expression in Single Cells

    PubMed Central

    Danaher, Patrick; Finak, Greg; Krouse, Michael; Wang, Alice; Webster, Philippa; Beechem, Joseph; Gottardo, Raphael

    2014-01-01

    Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%–17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome. PMID:25032992

  20. RapGene: a fast and accurate strategy for synthetic gene assembly in Escherichia coli

    PubMed Central

    Zampini, Massimiliano; Stevens, Pauline Rees; Pachebat, Justin A.; Kingston-Smith, Alison; Mur, Luis A. J.; Hayes, Finbarr

    2015-01-01

    The ability to assemble DNA sequences de novo through efficient and powerful DNA fabrication methods is one of the foundational technologies of synthetic biology. Gene synthesis, in particular, has been considered the main driver for the emergence of this new scientific discipline. Here we describe RapGene, a rapid gene assembly technique which was successfully tested for the synthesis and cloning of both prokaryotic and eukaryotic genes through a ligation independent approach. The method developed in this study is a complete bacterial gene synthesis platform for the quick, accurate and cost effective fabrication and cloning of gene-length sequences that employ the widely used host Escherichia coli. PMID:26062748

  1. Inferring gene expression from ribosomal promoter sequences, a crowdsourcing approach

    PubMed Central

    Meyer, Pablo; Siwo, Geoffrey; Zeevi, Danny; Sharon, Eilon; Norel, Raquel; Segal, Eran; Stolovitzky, Gustavo; Siwo, Geoffrey; Rider, Andrew K.; Tan, Asako; Pinapati, Richard S.; Emrich, Scott; Chawla, Nitesh; Ferdig, Michael T.; Tung, Yi-An; Chen, Yong-Syuan; Chen, Mei-Ju May; Chen, Chien-Yu; Knight, Jason M.; Sahraeian, Sayed Mohammad Ebrahim; Esfahani, Mohammad Shahrokh; Dreos, Rene; Bucher, Philipp; Maier, Ezekiel; Saeys, Yvan; Szczurek, Ewa; Myšičková, Alena; Vingron, Martin; Klein, Holger; Kiełbasa, Szymon M.; Knisley, Jeff; Bonnell, Jeff; Knisley, Debra; Kursa, Miron B.; Rudnicki, Witold R.; Bhattacharjee, Madhuchhanda; Sillanpää, Mikko J.; Yeung, James; Meysman, Pieter; Rodríguez, Aminael Sánchez; Engelen, Kristof; Marchal, Kathleen; Huang, Yezhou; Mordelet, Fantine; Hartemink, Alexander; Pinello, Luca; Yuan, Guo-Cheng

    2013-01-01

    The Gene Promoter Expression Prediction challenge consisted of predicting gene expression from promoter sequences in a previously unknown experimentally generated data set. The challenge was presented to the community in the framework of the sixth Dialogue for Reverse Engineering Assessments and Methods (DREAM6), a community effort to evaluate the status of systems biology modeling methodologies. Nucleotide-specific promoter activity was obtained by measuring fluorescence from promoter sequences fused upstream of a gene for yellow fluorescence protein and inserted in the same genomic site of yeast Saccharomyces cerevisiae. Twenty-one teams submitted results predicting the expression levels of 53 different promoters from yeast ribosomal protein genes. Analysis of participant predictions shows that accurate values for low-expressed and mutated promoters were difficult to obtain, although in the latter case, only when the mutation induced a large change in promoter activity compared to the wild-type sequence. As in previous DREAM challenges, we found that aggregation of participant predictions provided robust results, but did not fare better than the three best algorithms. Finally, this study not only provides a benchmark for the assessment of methods predicting activity of a specific set of promoters from their sequence, but it also shows that the top performing algorithm, which used machine-learning approaches, can be improved by the addition of biological features such as transcription factor binding sites. PMID:23950146

  2. Validation of reference genes for RT-qPCR studies of gene expression in banana fruit under different experimental conditions.

    PubMed

    Chen, Lei; Zhong, Hai-ying; Kuang, Jian-fei; Li, Jian-guo; Lu, Wang-jin; Chen, Jian-ye

    2011-08-01

    Reverse transcription quantitative real-time PCR (RT-qPCR) is a sensitive technique for quantifying gene expression, but its success depends on the stability of the reference gene(s) used for data normalization. Only a few studies on validation of reference genes have been conducted in fruit trees and none in banana yet. In the present work, 20 candidate reference genes were selected, and their expression stability in 144 banana samples were evaluated and analyzed using two algorithms, geNorm and NormFinder. The samples consisted of eight sample sets collected under different experimental conditions, including various tissues, developmental stages, postharvest ripening, stresses (chilling, high temperature, and pathogen), and hormone treatments. Our results showed that different suitable reference gene(s) or combination of reference genes for normalization should be selected depending on the experimental conditions. The RPS2 and UBQ2 genes were validated as the most suitable reference genes across all tested samples. More importantly, our data further showed that the widely used reference genes, ACT and GAPDH, were not the most suitable reference genes in many banana sample sets. In addition, the expression of MaEBF1, a gene of interest that plays an important role in regulating fruit ripening, under different experimental conditions was used to further confirm the validated reference genes. Taken together, our results provide guidelines for reference gene(s) selection under different experimental conditions and a foundation for more accurate and widespread use of RT-qPCR in banana.

  3. Mapping gene expression patterns during myeloid differentiation using the EML hematopoietic progenitor cell line.

    PubMed

    Du, Yang; Campbell, Janee L; Nalbant, Demet; Youn, Hyewon; Bass, Ann C Hughes; Cobos, Everardo; Tsai, Schickwann; Keller, Jonathan R; Williams, Simon C

    2002-07-01

    The detailed examination of the molecular events that control the early stages of myeloid differentiation has been hampered by the relative scarcity of hematopoietic stem cells and the lack of suitable cell line models. In this study, we examined the expression of several myeloid and nonmyeloid genes in the murine EML hematopoietic stem cell line. Expression patterns for 19 different genes were examined by Northern blotting and RT-PCR in RNA samples from EML, a variety of other immortalized cell lines, and purified murine hematopoietic stem cells. Representational difference analysis (RDA) was performed to identify differentially expressed genes in EML. Expression patterns of genes encoding transcription factors (four members of the C/EBP family, GATA-1, GATA-2, PU.1, CBFbeta, SCL, and c-myb) in EML were examined and were consistent with the proposed functions of these proteins in hematopoietic differentiation. Expression levels of three markers of terminal myeloid differentiation (neutrophil elastase, proteinase 3, and Mac-1) were highest in EML cells at the later stages of differentiation. In a search for genes that were differentially expressed in EML cells during myeloid differentiation, six cDNAs were isolated. These included three known genes (lysozyme, histidine decarboxylase, and tryptophan hydroxylase) and three novel genes. Expression patterns of known genes in differentiating EML cells accurately reflected their expected expression patterns based on previous studies. The identification of three novel genes, two of which encode proteins that may act as regulators of hematopoietic differentiation, suggests that EML is a useful model system for the molecular analysis of hematopoietic differentiation.

  4. Accurate Identification of Fear Facial Expressions Predicts Prosocial Behavior

    PubMed Central

    Marsh, Abigail A.; Kozak, Megan N.; Ambady, Nalini

    2009-01-01

    The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants’ ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale. PMID:17516803

  5. Accurate identification of fear facial expressions predicts prosocial behavior.

    PubMed

    Marsh, Abigail A; Kozak, Megan N; Ambady, Nalini

    2007-05-01

    The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants' ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale.

  6. 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

  7. 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.

  8. 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

  9. Temporally and spatially controllable gene expression and knockout in mouse urothelium.

    PubMed

    Zhou, Haiping; Liu, Yan; He, Feng; Mo, Lan; Sun, Tung-Tien; Wu, Xue-Ru

    2010-08-01

    Urothelium that lines almost the entire urinary tract performs important functions and is prone to assaults by urinary microbials, metabolites, and carcinogens. To improve our understanding of urothelial physiology and disease pathogenesis, we sought to develop two novel transgenic systems, one that would allow inducible and urothelium-specific gene expression, and another that would allow inducible and urothelium-specific knockout. Toward this end, we combined the ability of the mouse uroplakin II promoter (mUPII) to drive urothelium-specific gene expression with a versatile tetracycline-mediated inducible system. We found that, when constructed under the control of mUPII, only a modified, reverse tetracycline trans-activator (rtTA-M2), but not its original version (rtTA), could efficiently trans-activate reporter gene expression in mouse urothelium on doxycycline (Dox) induction. The mUPII/rtTA-M2-inducible system retained its strict urothelial specificity, had no background activity in the absence of Dox, and responded rapidly to Dox administration. Using a reporter gene whose expression was secondarily controlled by histone remodeling, we were able to identify, colocalize with 5-bromo-2-deoxyuridine incorporation, and semiquantify newly divided urothelial cells. Finally, we established that, when combined with a Cre recombinase under the control of the tetracycline operon, the mUPII-driven rtTA-M2 could inducibly inactivate any gene of interest in mouse urothelium. The establishment of these two new transgenic mouse systems enables the manipulation of gene expression and/or inactivation in adult mouse urothelium at any given time, thus minimizing potential compensatory effects due to gene overexpression or loss and allowing more accurate modeling of urothelial diseases than previously reported constitutive systems.

  10. Validation of Reference Genes for Gene Expression by Quantitative Real-Time RT-PCR in Stem Segments Spanning Primary to Secondary Growth in Populus tomentosa.

    PubMed

    Wang, Ying; Chen, Yajuan; Ding, Liping; Zhang, Jiewei; Wei, Jianhua; Wang, Hongzhi

    2016-01-01

    The vertical segments of Populus stems are an ideal experimental system for analyzing the gene expression patterns involved in primary and secondary growth during wood formation. Suitable internal control genes are indispensable to quantitative real time PCR (qRT-PCR) assays of gene expression. In this study, the expression stability of eight candidate reference genes was evaluated in a series of vertical stem segments of Populus tomentosa. Analysis through software packages geNorm, NormFinder and BestKeeper showed that genes ribosomal protein (RP) and tubulin beta (TUBB) were the most unstable across the developmental stages of P. tomentosa stems, and the combination of the three reference genes, eukaryotic translation initiation factor 5A (eIF5A), Actin (ACT6) and elongation factor 1-beta (EF1-beta) can provide accurate and reliable normalization of qRT-PCR analysis for target gene expression in stem segments undergoing primary and secondary growth in P. tomentosa. These results provide crucial information for transcriptional analysis in the P. tomentosa stem, which may help to improve the quality of gene expression data in these vertical stem segments, which constitute an excellent plant system for the study of wood formation.

  11. Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data.

    PubMed

    Chen, Shuonan; Mar, Jessica C

    2018-06-19

    A fundamental fact in biology states that genes do not operate in isolation, and yet, methods that infer regulatory networks for single cell gene expression data have been slow to emerge. With single cell sequencing methods now becoming accessible, general network inference algorithms that were initially developed for data collected from bulk samples may not be suitable for single cells. Meanwhile, although methods that are specific for single cell data are now emerging, whether they have improved performance over general methods is unknown. In this study, we evaluate the applicability of five general methods and three single cell methods for inferring gene regulatory networks from both experimental single cell gene expression data and in silico simulated data. Standard evaluation metrics using ROC curves and Precision-Recall curves against reference sets sourced from the literature demonstrated that most of the methods performed poorly when they were applied to either experimental single cell data, or simulated single cell data, which demonstrates their lack of performance for this task. Using default settings, network methods were applied to the same datasets. Comparisons of the learned networks highlighted the uniqueness of some predicted edges for each method. The fact that different methods infer networks that vary substantially reflects the underlying mathematical rationale and assumptions that distinguish network methods from each other. This study provides a comprehensive evaluation of network modeling algorithms applied to experimental single cell gene expression data and in silico simulated datasets where the network structure is known. Comparisons demonstrate that most of these assessed network methods are not able to predict network structures from single cell expression data accurately, even if they are specifically developed for single cell methods. Also, single cell methods, which usually depend on more elaborative algorithms, in general have less

  12. Breast cancer prognosis by combinatorial analysis of gene expression data.

    PubMed

    Alexe, Gabriela; Alexe, Sorin; Axelrod, David E; Bonates, Tibérius O; Lozina, Irina I; Reiss, Michael; Hammer, Peter L

    2006-01-01

    The potential of applying data analysis tools to microarray data for diagnosis and prognosis is illustrated on the recent breast cancer dataset of van 't Veer and coworkers. We re-examine that dataset using the novel technique of logical analysis of data (LAD), with the double objective of discovering patterns characteristic for cases with good or poor outcome, using them for accurate and justifiable predictions; and deriving novel information about the role of genes, the existence of special classes of cases, and other factors. Data were analyzed using the combinatorics and optimization-based method of LAD, recently shown to provide highly accurate diagnostic and prognostic systems in cardiology, cancer proteomics, hematology, pulmonology, and other disciplines. LAD identified a subset of 17 of the 25,000 genes, capable of fully distinguishing between patients with poor, respectively good prognoses. An extensive list of 'patterns' or 'combinatorial biomarkers' (that is, combinations of genes and limitations on their expression levels) was generated, and 40 patterns were used to create a prognostic system, shown to have 100% and 92.9% weighted accuracy on the training and test sets, respectively. The prognostic system uses fewer genes than other methods, and has similar or better accuracy than those reported in other studies. Out of the 17 genes identified by LAD, three (respectively, five) were shown to play a significant role in determining poor (respectively, good) prognosis. Two new classes of patients (described by similar sets of covering patterns, gene expression ranges, and clinical features) were discovered. As a by-product of the study, it is shown that the training and the test sets of van 't Veer have differing characteristics. The study shows that LAD provides an accurate and fully explanatory prognostic system for breast cancer using genomic data (that is, a system that, in addition to predicting good or poor prognosis, provides an individualized

  13. 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

  14. 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.

  15. Gene Expression Changes in Phosphorus Deficient Potato (Solanum tuberosum L.) Leaves and the Potential for Diagnostic Gene Expression Markers

    PubMed Central

    Hammond, John P.; Broadley, Martin R.; Bowen, Helen C.; Spracklen, William P.; Hayden, Rory M.; White, Philip J.

    2011-01-01

    Background There are compelling economic and environmental reasons to reduce our reliance on inorganic phosphate (Pi) fertilisers. Better management of Pi fertiliser applications is one option to improve the efficiency of Pi fertiliser use, whilst maintaining crop yields. Application rates of Pi fertilisers are traditionally determined from analyses of soil or plant tissues. Alternatively, diagnostic genes with altered expression under Pi limiting conditions that suggest a physiological requirement for Pi fertilisation, could be used to manage Pifertiliser applications, and might be more precise than indirect measurements of soil or tissue samples. Results We grew potato (Solanum tuberosum L.) plants hydroponically, under glasshouse conditions, to control their nutrient status accurately. Samples of total leaf RNA taken periodically after Pi was removed from the nutrient solution were labelled and hybridised to potato oligonucleotide arrays. A total of 1,659 genes were significantly differentially expressed following Pi withdrawal. These included genes that encode proteins involved in lipid, protein, and carbohydrate metabolism, characteristic of Pi deficient leaves and included potential novel roles for genes encoding patatin like proteins in potatoes. The array data were analysed using a support vector machine algorithm to identify groups of genes that could predict the Pi status of the crop. These groups of diagnostic genes were tested using field grown potatoes that had either been fertilised or unfertilised. A group of 200 genes could correctly predict the Pi status of field grown potatoes. Conclusions This paper provides a proof-of-concept demonstration for using microarrays and class prediction tools to predict the Pi status of a field grown potato crop. There is potential to develop this technology for other biotic and abiotic stresses in field grown crops. Ultimately, a better understanding of crop stresses may improve our management of the crop, improving

  16. 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

  17. A gene expression signature associated with survival in metastatic melanoma

    PubMed Central

    Mandruzzato, Susanna; Callegaro, Andrea; Turcatel, Gianluca; Francescato, Samuela; Montesco, Maria C; Chiarion-Sileni, Vanna; Mocellin, Simone; Rossi, Carlo R; Bicciato, Silvio; Wang, Ena; Marincola, Francesco M; Zanovello, Paola

    2006-01-01

    Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells. PMID:17129373

  18. Sample entropy analysis of cervical neoplasia gene-expression signatures

    PubMed Central

    Botting, Shaleen K; Trzeciakowski, Jerome P; Benoit, Michelle F; Salama, Salama A; Diaz-Arrastia, Concepcion R

    2009-01-01

    Background We introduce Approximate Entropy as a mathematical method of analysis for microarray data. Approximate entropy is applied here as a method to classify the complex gene expression patterns resultant of a clinical sample set. Since Entropy is a measure of disorder in a system, we believe that by choosing genes which display minimum entropy in normal controls and maximum entropy in the cancerous sample set we will be able to distinguish those genes which display the greatest variability in the cancerous set. Here we describe a method of utilizing Approximate Sample Entropy (ApSE) analysis to identify genes of interest with the highest probability of producing an accurate, predictive, classification model from our data set. Results In the development of a diagnostic gene-expression profile for cervical intraepithelial neoplasia (CIN) and squamous cell carcinoma of the cervix, we identified 208 genes which are unchanging in all normal tissue samples, yet exhibit a random pattern indicative of the genetic instability and heterogeneity of malignant cells. This may be measured in terms of the ApSE when compared to normal tissue. We have validated 10 of these genes on 10 Normal and 20 cancer and CIN3 samples. We report that the predictive value of the sample entropy calculation for these 10 genes of interest is promising (75% sensitivity, 80% specificity for prediction of cervical cancer over CIN3). Conclusion The success of the Approximate Sample Entropy approach in discerning alterations in complexity from biological system with such relatively small sample set, and extracting biologically relevant genes of interest hold great promise. PMID:19232110

  19. 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.

  20. 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.

  1. 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

  2. Gene expression signature in urine for diagnosing and assessing aggressiveness of bladder urothelial carcinoma.

    PubMed

    Mengual, Lourdes; Burset, Moisès; Ribal, María José; Ars, Elisabet; Marín-Aguilera, Mercedes; Fernández, Manuel; Ingelmo-Torres, Mercedes; Villavicencio, Humberto; Alcaraz, Antonio

    2010-05-01

    To develop an accurate and noninvasive method for bladder cancer diagnosis and prediction of disease aggressiveness based on the gene expression patterns of urine samples. Gene expression patterns of 341 urine samples from bladder urothelial cell carcinoma (UCC) patients and 235 controls were analyzed via TaqMan Arrays. In a first phase of the study, three consecutive gene selection steps were done to identify a gene set expression signature to detect and stratify UCC in urine. Subsequently, those genes more informative for UCC diagnosis and prediction of tumor aggressiveness were combined to obtain a classification system of bladder cancer samples. In a second phase, the obtained gene set signature was evaluated in a routine clinical scenario analyzing only voided urine samples. We have identified a 12+2 gene expression signature for UCC diagnosis and prediction of tumor aggressiveness on urine samples. Overall, this gene set panel had 98% sensitivity (SN) and 99% specificity (SP) in discriminating between UCC and control samples and 79% SN and 92% SP in predicting tumor aggressiveness. The translation of the model to the clinically applicable format corroborates that the 12+2 gene set panel described maintains a high accuracy for UCC diagnosis (SN = 89% and SP = 95%) and tumor aggressiveness prediction (SN = 79% and SP = 91%) in voided urine samples. The 12+2 gene expression signature described in urine is able to identify patients suffering from UCC and predict tumor aggressiveness. We show that a panel of molecular markers may improve the schedule for diagnosis and follow-up in UCC patients. Copyright 2010 AACR.

  3. 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.

  4. Purification of cardiac myocytes from human heart biopsies for gene expression analysis.

    PubMed

    Kosloski, L M; Bales, I K; Allen, K B; Walker, B L; Borkon, A M; Stuart, R S; Pak, A F; Wacker, M J

    2009-09-01

    The collection of gene expression data from human heart biopsies is important for understanding the cellular mechanisms of arrhythmias and diseases such as cardiac hypertrophy and heart failure. Many clinical and basic research laboratories conduct gene expression analysis using RNA from whole cardiac biopsies. This allows for the analysis of global changes in gene expression in areas of the heart, while eliminating the need for more complex and technically difficult single-cell isolation procedures (such as flow cytometry, laser capture microdissection, etc.) that require expensive equipment and specialized training. The abundance of fibroblasts and other cell types in whole biopsies, however, can complicate gene expression analysis and the interpretation of results. Therefore, we have designed a technique to quickly and easily purify cardiac myocytes from whole cardiac biopsies for RNA extraction. Human heart tissue samples were collected, and our purification method was compared with the standard nonpurification method. Cell imaging using acridine orange staining of the purified sample demonstrated that >98% of total RNA was contained within identifiable cardiac myocytes. Real-time RT-PCR was performed comparing nonpurified and purified samples for the expression of troponin T (myocyte marker), vimentin (fibroblast marker), and alpha-smooth muscle actin (smooth muscle marker). Troponin T expression was significantly increased, and vimentin and alpha-smooth muscle actin were significantly decreased in the purified sample (n = 8; P < 0.05). Extracted RNA was analyzed during each step of the purification, and no significant degradation occurred. These results demonstrate that this isolation method yields a more purified cardiac myocyte RNA sample suitable for downstream applications, such as real-time RT-PCR, and allows for more accurate gene expression changes in cardiac myocytes from heart biopsies.

  5. 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...

  6. Impact of Ischemia and Procurement Conditions on Gene Expression in Renal Cell Carcinoma

    PubMed Central

    Liu, Nick W.; Sanford, Thomas; Srinivasan, Ramaprasad; Liu, Jack L.; Khurana, Kiranpreet; Aprelikova, Olga; Valero, Vladimir; Bechert, Charles; Worrell, Robert; Pinto, Peter A.; Yang, Youfeng; Merino, Maria; Linehan, W. Marston; Bratslavsky, Gennady

    2013-01-01

    Purpose Previous studies have shown that ischemia alters gene expression in normal and malignant tissues. There are no studies that evaluated effects of ischemia in renal tumors. This study examines the impact of ischemia and tissue procurement conditions on RNA integrity and gene expression in renal cell carcinoma. Experimental Design Ten renal tumors were resected without renal hilar clamping from 10 patients with renal clear cell carcinoma. Immediately after tumor resection, a piece of tumor was snap frozen. Remaining tumor samples were stored at 4C, 22C and 37C and frozen at 5, 30, 60, 120, and 240 minutes. Histopathologic evaluation was performed on all tissue samples, and only those with greater than 80% tumor were selected for further analysis. RNA integrity was confirmed by electropherograms and quantitated using RIN index. Altered gene expression was assessed by paired, two-sample t-test between the zero time point and aliquots from various conditions obtained from the same tumor. Results One hundred and forty microarrays were performed. Some RNA degradation was observed 240 mins after resection at 37C. The expression of over 4,000 genes was significantly altered by ischemia times or storage conditions. The greatest gene expression changes were observed with longer ischemia time and warmer tissue procurement conditions. Conclusion RNA from kidney cancer remains intact for up to 4 hours post surgical resection regardless of storage conditions. Despite excellent RNA preservation, time after resection and procurement conditions significantly influence gene expression profiles. Meticulous attention to pre-acquisition variables is of paramount importance for accurate tumor profiling. PMID:23136194

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

    PubMed

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

    2016-02-19

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

  8. Improved methods and resources for paramecium genomics: transcription units, gene annotation and gene expression.

    PubMed

    Arnaiz, Olivier; Van Dijk, Erwin; Bétermier, Mireille; Lhuillier-Akakpo, Maoussi; de Vanssay, Augustin; Duharcourt, Sandra; Sallet, Erika; Gouzy, Jérôme; Sperling, Linda

    2017-06-26

    The 15 sibling species of the Paramecium aurelia cryptic species complex emerged after a whole genome duplication that occurred tens of millions of years ago. Given extensive knowledge of the genetics and epigenetics of Paramecium acquired over the last century, this species complex offers a uniquely powerful system to investigate the consequences of whole genome duplication in a unicellular eukaryote as well as the genetic and epigenetic mechanisms that drive speciation. High quality Paramecium gene models are important for research using this system. The major aim of the work reported here was to build an improved gene annotation pipeline for the Paramecium lineage. We generated oriented RNA-Seq transcriptome data across the sexual process of autogamy for the model species Paramecium tetraurelia. We determined, for the first time in a ciliate, candidate P. tetraurelia transcription start sites using an adapted Cap-Seq protocol. We developed TrUC, multi-threaded Perl software that in conjunction with TopHat mapping of RNA-Seq data to a reference genome, predicts transcription units for the annotation pipeline. We used EuGene software to combine annotation evidence. The high quality gene structural annotations obtained for P. tetraurelia were used as evidence to improve published annotations for 3 other Paramecium species. The RNA-Seq data were also used for differential gene expression analysis, providing a gene expression atlas that is more sensitive than the previously established microarray resource. We have developed a gene annotation pipeline tailored for the compact genomes and tiny introns of Paramecium species. A novel component of this pipeline, TrUC, predicts transcription units using Cap-Seq and oriented RNA-Seq data. TrUC could prove useful beyond Paramecium, especially in the case of high gene density. Accurate predictions of 3' and 5' UTR will be particularly valuable for studies of gene expression (e.g. nucleosome positioning, identification of cis

  9. Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

    PubMed

    Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

    2012-01-01

    Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

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

    PubMed

    Taylor, Candy M; Jost, Ricarda; Erskine, William; Nelson, Matthew N

    2016-01-01

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

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

    PubMed Central

    Erskine, William; Nelson, Matthew N.

    2016-01-01

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

  12. 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.

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

    PubMed Central

    Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

    2015-01-01

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

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

    PubMed

    Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

    2015-01-01

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

  15. Spatial reconstruction of single-cell gene expression

    PubMed Central

    Satija, Rahul; Farrell, Jeffrey A.; Gennert, David; Schier, Alexander F.; Regev, Aviv

    2015-01-01

    Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. PMID:25867923

  16. Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

    PubMed

    Zhou, Xionghui; Liu, Juan

    2014-01-01

    Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for

  17. A Computational Framework for Analyzing Stochasticity in Gene Expression

    PubMed Central

    Sherman, Marc S.; Cohen, Barak A.

    2014-01-01

    Stochastic fluctuations in gene expression give rise to distributions of protein levels across cell populations. Despite a mounting number of theoretical models explaining stochasticity in protein expression, we lack a robust, efficient, assumption-free approach for inferring the molecular mechanisms that underlie the shape of protein distributions. Here we propose a method for inferring sets of biochemical rate constants that govern chromatin modification, transcription, translation, and RNA and protein degradation from stochasticity in protein expression. We asked whether the rates of these underlying processes can be estimated accurately from protein expression distributions, in the absence of any limiting assumptions. To do this, we (1) derived analytical solutions for the first four moments of the protein distribution, (2) found that these four moments completely capture the shape of protein distributions, and (3) developed an efficient algorithm for inferring gene expression rate constants from the moments of protein distributions. Using this algorithm we find that most protein distributions are consistent with a large number of different biochemical rate constant sets. Despite this degeneracy, the solution space of rate constants almost always informs on underlying mechanism. For example, we distinguish between regimes where transcriptional bursting occurs from regimes reflecting constitutive transcript production. Our method agrees with the current standard approach, and in the restrictive regime where the standard method operates, also identifies rate constants not previously obtainable. Even without making any assumptions we obtain estimates of individual biochemical rate constants, or meaningful ratios of rate constants, in 91% of tested cases. In some cases our method identified all of the underlying rate constants. The framework developed here will be a powerful tool for deducing the contributions of particular molecular mechanisms to specific patterns

  18. 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

  19. 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.

  20. 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).

  1. Modeling leaderless transcription and atypical genes results in more accurate gene prediction in prokaryotes.

    PubMed

    Lomsadze, Alexandre; Gemayel, Karl; Tang, Shiyuyun; Borodovsky, Mark

    2018-05-17

    In a conventional view of the prokaryotic genome organization, promoters precede operons and ribosome binding sites (RBSs) with Shine-Dalgarno consensus precede genes. However, recent experimental research suggesting a more diverse view motivated us to develop an algorithm with improved gene-finding accuracy. We describe GeneMarkS-2, an ab initio algorithm that uses a model derived by self-training for finding species-specific (native) genes, along with an array of precomputed "heuristic" models designed to identify harder-to-detect genes (likely horizontally transferred). Importantly, we designed GeneMarkS-2 to identify several types of distinct sequence patterns (signals) involved in gene expression control, among them the patterns characteristic for leaderless transcription as well as noncanonical RBS patterns. To assess the accuracy of GeneMarkS-2, we used genes validated by COG (Clusters of Orthologous Groups) annotation, proteomics experiments, and N-terminal protein sequencing. We observed that GeneMarkS-2 performed better on average in all accuracy measures when compared with the current state-of-the-art gene prediction tools. Furthermore, the screening of ∼5000 representative prokaryotic genomes made by GeneMarkS-2 predicted frequent leaderless transcription in both archaea and bacteria. We also observed that the RBS sites in some species with leadered transcription did not necessarily exhibit the Shine-Dalgarno consensus. The modeling of different types of sequence motifs regulating gene expression prompted a division of prokaryotic genomes into five categories with distinct sequence patterns around the gene starts. © 2018 Lomsadze et al.; Published by Cold Spring Harbor Laboratory Press.

  2. 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

  3. HOXB homeobox gene expression in cervical carcinoma.

    PubMed

    López, R; Garrido, E; Piña, P; Hidalgo, A; Lazos, M; Ochoa, R; Salcedo, M

    2006-01-01

    The homeobox (HOX) genes are a family of transcription factors that bind to specific DNA sequences in target genes regulating gene expression. Thirty-nine HOX genes have been mapped in four conserved clusters: A, B, C, and D; they act as master genes regulating the identity of body segments along the anteroposterior axis of the embryo. The role played by HOX genes in adult cell differentiation is unclear to date, but growing evidence suggests that they may play an important role in the development of cancer. To study the role played by HOX genes in cervical cancer, in the present work, we analyzed the expression of HOXB genes and the localization of their transcripts in human cervical tissues. Reverse transcription-polymerase chain reaction analysis and nonradioactive RNA in situ hybridization were used to detect HOXB expression in 11 normal cervical tissues and 17 cervical carcinomas. It was determined that HOXB1, B3, B5, B6, B7, B8, and B9 genes are expressed in normal adult cervical epithelium and squamous cervical carcinomas. Interestingly, HOXB2, HOXB4, and HOXB13 gene expression was found only in tumor tissues. Our findings suggest that the new expression of HOXB2, HOXB4, and B13 genes is involved in cervical cancer.

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

    PubMed Central

    Xu, Pingzhen

    2018-01-01

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

  5. 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

  6. A tool for identification of genes expressed in patterns of interest using the Allen Brain Atlas

    PubMed Central

    Davis, Fred P.; Eddy, Sean R.

    2009-01-01

    Motivation: Gene expression patterns can be useful in understanding the structural organization of the brain and the regulatory logic that governs its myriad cell types. A particularly rich source of spatial expression data is the Allen Brain Atlas (ABA), a comprehensive genome-wide in situ hybridization study of the adult mouse brain. Here, we present an open-source program, ALLENMINER, that searches the ABA for genes that are expressed, enriched, patterned or graded in a user-specified region of interest. Results: Regionally enriched genes identified by ALLENMINER accurately reflect the in situ data (95–99% concordance with manual curation) and compare with regional microarray studies as expected from previous comparisons (61–80% concordance). We demonstrate the utility of ALLENMINER by identifying genes that exhibit patterned expression in the caudoputamen and neocortex. We discuss general characteristics of gene expression in the mouse brain and the potential application of ALLENMINER to design strategies for specific genetic access to brain regions and cell types. Availability: ALLENMINER is freely available on the Internet at http://research.janelia.org/davis/allenminer. Contact: davisf@janelia.hhmi.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19414530

  7. Validation of Reference Genes for RT-qPCR Studies of Gene Expression in Preharvest and Postharvest Longan Fruits under Different Experimental Conditions

    PubMed Central

    Wu, Jianyang; Zhang, Hongna; Liu, Liqin; Li, Weicai; Wei, Yongzan; Shi, Shengyou

    2016-01-01

    Reverse transcription quantitative PCR (RT-qPCR) as the accurate and sensitive method is use for gene expression analysis, but the veracity and reliability result depends on whether select appropriate reference gene or not. To date, several reliable reference gene validations have been reported in fruits trees, but none have been done on preharvest and postharvest longan fruits. In this study, 12 candidate reference genes, namely, CYP, RPL, GAPDH, TUA, TUB, Fe-SOD, Mn-SOD, Cu/Zn-SOD, 18SrRNA, Actin, Histone H3, and EF-1a, were selected. Expression stability of these genes in 150 longan samples was evaluated and analyzed using geNorm and NormFinder algorithms. Preharvest samples consisted of seven experimental sets, including different developmental stages, organs, hormone stimuli (NAA, 2,4-D, and ethephon) and abiotic stresses (bagging and girdling with defoliation). Postharvest samples consisted of different temperature treatments (4 and 22°C) and varieties. Our findings indicate that appropriate reference gene(s) should be picked for each experimental condition. Our data further showed that the commonly used reference gene Actin does not exhibit stable expression across experimental conditions in longan. Expression levels of the DlACO gene, which is a key gene involved in regulating fruit abscission under girdling with defoliation treatment, was evaluated to validate our findings. In conclusion, our data provide a useful framework for choice of suitable reference genes across different experimental conditions for RT-qPCR analysis of preharvest and postharvest longan fruits. PMID:27375640

  8. Liver Gene Expression Profiles of Rats Treated with Clofibric Acid

    PubMed Central

    Michel, Cécile; Desdouets, Chantal; Sacre-Salem, Béatrice; Gautier, Jean-Charles; Roberts, Ruth; Boitier, Eric

    2003-01-01

    Clofibric acid (CLO) is a peroxisome proliferator (PP) that acts through the peroxisome proliferator activated receptor α, leading to hepatocarcinogenesis in rodents. CLO-induced hepatocarcinogenesis is a multi-step process, first transforming normal liver cells into foci. The combination of laser capture microdissection (LCM) and genomics has the potential to provide expression profiles from such small cell clusters, giving an opportunity to understand the process of cancer development in response to PPs. To our knowledge, this is the first evaluation of the impact of the successive steps of LCM procedure on gene expression profiling by comparing profiles from LCM samples to those obtained with non-microdissected liver samples collected after a 1 month CLO treatment in the rat. We showed that hematoxylin and eosin (H&E) staining and laser microdissection itself do not impact on RNA quality. However, the overall process of the LCM procedure affects the RNA quality, resulting in a bias in the gene profiles. Nonetheless, this bias did not prevent accurate determination of a CLO-specific molecular signature. Thus, gene-profiling analysis of microdissected foci, identified by H&E staining may provide insight into the mechanisms underlying non-genotoxic hepatocarcinogenesis in the rat by allowing identification of specific genes that are regulated by CLO in early pre-neoplastic foci. PMID:14633594

  9. Pre-gastrula expression of zebrafish extraembryonic genes

    PubMed Central

    2010-01-01

    Background Many species form extraembryonic tissues during embryogenesis, such as the placenta of humans and other viviparous mammals. Extraembryonic tissues have various roles in protecting, nourishing and patterning embryos. Prior to gastrulation in zebrafish, the yolk syncytial layer - an extraembryonic nuclear syncytium - produces signals that induce mesoderm and endoderm formation. Mesoderm and endoderm precursor cells are situated in the embryonic margin, an external ring of cells along the embryo-yolk interface. The yolk syncytial layer initially forms below the margin, in a domain called the external yolk syncytial layer (E-YSL). Results We hypothesize that key components of the yolk syncytial layer's mesoderm and endoderm inducing activity are expressed as mRNAs in the E-YSL. To identify genes expressed in the E-YSL, we used microarrays to compare the transcription profiles of intact pre-gastrula embryos with pre-gastrula embryonic cells that we had separated from the yolk and yolk syncytial layer. This identified a cohort of genes with enriched expression in intact embryos. Here we describe our whole mount in situ hybridization analysis of sixty-eight of them. This includes ten genes with E-YSL expression (camsap1l1, gata3, znf503, hnf1ba, slc26a1, slc40a1, gata6, gpr137bb, otop1 and cebpa), four genes with expression in the enveloping layer (EVL), a superficial epithelium that protects the embryo (zgc:136817, zgc:152778, slc14a2 and elovl6l), three EVL genes whose expression is transiently confined to the animal pole (elovl6l, zgc:136359 and clica), and six genes with transient maternal expression (mtf1, wu:fj59f04, mospd2, rftn2, arrdc1a and pho). We also assessed the requirement of Nodal signaling for the expression of selected genes in the E-YSL, EVL and margin. Margin expression was Nodal dependent for all genes we tested, including the concentrated margin expression of an EVL gene: zgc:110712. All other instances of EVL and E-YSL expression that we

  10. Regulation of gene expression in plasmid ColE1: delayed expression of the kil gene.

    PubMed Central

    Zhang, S P; Yan, L F; Zubay, G

    1988-01-01

    cea, imm, and kil are a cluster of three functionally related genes of the plasmid ColE1. The cea and kil genes are in the same inducible operon, with transcription being initiated from a promoter adjacent to the cea gene. The imm gene is located between the cea and kil genes, but it is transcribed in the opposite direction. Complementary interaction between the imm mRNA and the anti-imm sequences in the middle of the cea-kil transcript causes a pronounced delay in expression of the kil gene when the cea-kil operon is induced. A segment in the overlapping region between the cea and imm genes causes delayed expression of the kil gene in the absence of imm gene transcription. This delay effect increases the yields of colicin synthesized in induced cells. Images PMID:3142845

  11. Identification of appropriate reference genes for normalizing transcript expression by quantitative real-time PCR in Litsea cubeba.

    PubMed

    Lin, Liyuan; Han, Xiaojiao; Chen, Yicun; Wu, Qingke; Wang, Yangdong

    2013-12-01

    Quantitative real-time PCR has emerged as a highly sensitive and widely used method for detection of gene expression profiles, via which accurate detection depends on reliable normalization. Since no single control is appropriate for all experimental treatments, it is generally advocated to select suitable internal controls prior to use for normalization. This study reported the evaluation of the expression stability of twelve potential reference genes in different tissue/organs and six fruit developmental stages of Litsea cubeba in order to screen the superior internal reference genes for data normalization. Two softwares-geNorm, and NormFinder-were used to identify stability of these candidate genes. The cycle threshold difference and coefficient of variance were also calculated to evaluate the expression stability of candidate genes. F-BOX, EF1α, UBC, and TUA were selected as the most stable reference genes across 11 sample pools. F-BOX, EF1α, and EIF4α exhibited the highest expression stability in different tissue/organs and different fruit developmental stages. Besides, a combination of two stable reference genes would be sufficient for gene expression normalization in different fruit developmental stages. In addition, the relative expression profiles of DXS and DXR were evaluated by EF1α, UBC, and SAMDC. The results further validated the reliability of stable reference genes and also highlighted the importance of selecting suitable internal controls for L. cubeba. These reference genes will be of great importance for transcript normalization in future gene expression studies on L. cubeba.

  12. Digital gene expression for non-model organisms

    PubMed Central

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

    2011-01-01

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

  13. Semantic integration of gene expression analysis tools and data sources using software connectors

    PubMed Central

    2013-01-01

    Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools

  14. Semantic integration of gene expression analysis tools and data sources using software connectors.

    PubMed

    Miyazaki, Flávia A; Guardia, Gabriela D A; Vêncio, Ricardo Z N; de Farias, Cléver R G

    2013-10-25

    The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heterogeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The

  15. Gene expression systems in corynebacteria.

    PubMed

    Srivastava, Preeti; Deb, J K

    2005-04-01

    Corynebacterium belongs to a group of gram-positive bacteria having moderate to high G+C content, the other members being Mycobacterium, Nocardia, and Rhodococcus. Considerable information is now available on the plasmids, gene regulatory elements, and gene expression in corynebacteria, especially in soil corynebacteria such as Corynebacterium glutamicum. These bacteria are non-pathogenic and, unlike Bacillus and Streptomyces, are low in proteolytic activity and thus have the potential of becoming attractive systems for expression of heterologous proteins. This review discusses recent advances in our understanding of the organization of various regulatory elements, such as promoters, transcription terminators, and development of vectors for cloning and gene expression.

  16. Positron emission tomography and gene therapy: basic concepts and experimental approaches for in vivo gene expression imaging.

    PubMed

    Peñuelas, Iván; Boán, JoséF; Martí-Climent, Josep M; Sangro, Bruno; Mazzolini, Guillermo; Prieto, Jesús; Richter, José A

    2004-01-01

    More than two decades of intense research have allowed gene therapy to move from the laboratory to the clinical setting, where its use for the treatment of human pathologies has been considerably increased in the last years. However, many crucial questions remain to be solved in this challenging field. In vivo imaging with positron emission tomography (PET) by combination of the appropriate PET reporter gene and PET reporter probe could provide invaluable qualitative and quantitative information to answer multiple unsolved questions about gene therapy. PET imaging could be used to define parameters not available by other techniques that are of substantial interest not only for the proper understanding of the gene therapy process, but also for its future development and clinical application in humans. This review focuses on the molecular biology basis of gene therapy and molecular imaging, describing the fundamentals of in vivo gene expression imaging by PET, and the application of PET to gene therapy, as a technology that can be used in many different ways. It could be applied to avoid invasive procedures for gene therapy monitoring; accurately diagnose the pathology for better planning of the most adequate therapeutic approach; as treatment evaluation to image the functional effects of gene therapy at the biochemical level; as a quantitative noninvasive way to monitor the location, magnitude and persistence of gene expression over time; and would also help to a better understanding of vector biology and pharmacology devoted to the development of safer and more efficient vectors.

  17. Nanobarcode gene expression monitoring system for potential miniaturized space applications

    NASA Astrophysics Data System (ADS)

    Ruan, Weiming; Eastman, P. Scott; Cooke, Patrick A.; Park, Jennifer S.; Chu, Julia S. F.; Gray, Joe W.; Li, Song; Chen, Fanqing Frank

    Manned mission to space has been threatened by various cosmos risks including radiation, mirogravity, vacuum, confinement, etc., which may cause genetic variations of astronauts and eventually lead to damages of their health. Thus, the development of small biomedical devices, which can monitor astronaut gene expression changes, is useful for future long-term space missions. Using magnetic microbeads packed with nanocrystal quantum dots at controlled ratios, we were able to generate highly multiplexed nanobarcodes, which can encode a flexible panel of genes. Also, by using a reporter quantum dot, this nanobarcode platform can monitor and quantify gene expression level with improved speed and sensitivity. As a comparison, we studied TGF-β1 induced transcription changes in human bone marrow mesenchymal stem cells with both the nanobarcode microbead system and the Affymetrix GeneChip ® HTA system, which is currently considered as the industrial standard. Though using only 1/20 of the sample RNA, the nanobarcode system showed sensitivity equivalent to Affymetrix GeneChip ® system. The coefficient of variation, dynamic range, and accuracy of the nanobarcodes measurement is equivalent to that of the GeneChip ® HTA system. Therefore, this newly invented nanobarcode microbead platform is thought to be sensitive, flexible, cost-effective and accurate in a level equivalent to the conventional methods. As an extension of the use of this new platform, spacecrafts may carry this miniaturized system as a diagnostic tool for the astronauts.

  18. Identification of suitable internal control genes for expression studies in Coffea arabica under different experimental conditions

    PubMed Central

    Barsalobres-Cavallari, Carla F; Severino, Fábio E; Maluf, Mirian P; Maia, Ivan G

    2009-01-01

    expressed and are therefore adequate for normalization purposes, showing equivalent transcript levels in different tissue/organ samples. Gapdh is therefore the recommended reference gene for measuring gene expression in Coffea arabica. Its use will enable more accurate and reliable normalization of tissue/organ-specific gene expression studies in this important cherry crop plant. PMID:19126214

  19. The CesA Gene Family of Barley. Quantitative Analysis of Transcripts Reveals Two Groups of Co-Expressed Genes1

    PubMed Central

    Burton, Rachel A.; Shirley, Neil J.; King, Brendon J.; Harvey, Andrew J.; Fincher, Geoffrey B.

    2004-01-01

    Sequence data from cDNA and genomic clones, coupled with analyses of expressed sequence tag databases, indicate that the CesA (cellulose synthase) gene family from barley (Hordeum vulgare) has at least eight members, which are distributed across the genome. Quantitative polymerase chain reaction has been used to determine the relative abundance of mRNA transcripts for individual HvCesA genes in vegetative and floral tissues, at different stages of development. To ensure accurate expression profiling, geometric averaging of multiple internal control gene transcripts has been applied for the normalization of transcript abundance. Total HvCesA mRNA levels are highest in coleoptiles, roots, and stems and much lower in floral tissues, early developing grain, and in the elongation zone of leaves. In most tissues, HvCesA1, HvCesA2, and HvCesA6 predominate, and their relative abundance is very similar; these genes appear to be coordinately transcribed. A second group, comprising HvCesA4, HvCesA7, and HvCesA8, also appears to be coordinately transcribed, most obviously in maturing stem and root tissues. The HvCesA3 expression pattern does not fall into either of these two groups, and HvCesA5 transcript levels are extremely low in all tissues. Thus, the HvCesA genes fall into two general groups of three genes with respect to mRNA abundance, and the co-expression of the groups identifies their products as candidates for the rosettes that are involved in cellulose biosynthesis at the plasma membrane. Phylogenetic analysis allows the two groups of genes to be linked with orthologous Arabidopsis CesA genes that have been implicated in primary and secondary wall synthesis. PMID:14701917

  20. Evaluation and Selection of Appropriate Reference Genes for Real-Time Quantitative PCR Analysis of Gene Expression in Nile Tilapia (Oreochromis niloticus) during Vaccination and Infection

    PubMed Central

    Wang, Erlong; Wang, Kaiyu; Chen, Defang; Wang, Jun; He, Yang; Long, Bo; Yang, Lei; Yang, Qian; Geng, Yi; Huang, Xiaoli; Ouyang, Ping; Lai, Weimin

    2015-01-01

    qPCR as a powerful and attractive methodology has been widely applied to aquaculture researches for gene expression analyses. However, the suitable reference selection is critical for normalizing target genes expression in qPCR. In the present study, six commonly used endogenous controls were selected as candidate reference genes to evaluate and analyze their expression levels, stabilities and normalization to immune-related gene IgM expression during vaccination and infection in spleen of tilapia with RefFinder and GeNorm programs. The results showed that all of these candidate reference genes exhibited transcriptional variations to some extent at different periods. Among them, EF1A was the most stable reference with RefFinder, followed by 18S rRNA, ACTB, UBCE, TUBA and GAPDH respectively and the optimal number of reference genes for IgM normalization under different experiment sets was two with GeNorm. Meanwhile, combination the Cq (quantification cycle) value and the recommended comprehensive ranking of reference genes, EF1A and ACTB, the two optimal reference genes, were used together as reference genes for accurate analysis of immune-related gene expression during vaccination and infection in Nile tilapia with qPCR. Moreover, the highest IgM expression level was at two weeks post-vaccination when normalized to EF1A, 18S rRNA, ACTB, and EF1A together with ACTB compared to one week post-vaccination before normalizing, which was also consistent with the IgM antibody titers detection by ELISA. PMID:25941937

  1. 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

  2. Gene Expression: Sizing it all up

    USDA-ARS?s Scientific Manuscript database

    Genomic architecture appears to be a largely unexplored component of gene expression. Although surely not the end of the story, we are learning that when it comes to gene expression, size is important. We have been surprised to find that certain patterns of expression, tissue-specific versus constit...

  3. Direct Introduction of Genes into Rats and Expression of the Genes

    NASA Astrophysics Data System (ADS)

    Benvenisty, Nissim; Reshef, Lea

    1986-12-01

    A method of introducing actively expressed genes into intact mammals is described. DNA precipitated with calcium phosphate has been injected intraperitoneally into newborn rats. The injected genes have been taken up and expressed by the animal tissues. To examine the generality of the method we have injected newborn rats with the chloramphenicol acetyltransferase prokaryotic gene fused with various viral and cellular gene promoters and the gene for hepatitis B surface antigen, and we observed appearance of chloramphenicol acetyltransferase activity and hepatitis B surface antigen in liver and spleen. In addition, administration of genes coding for hormones (insulin or growth hormone) resulted in their expression.

  4. Cloud-scale genomic signals processing classification analysis for gene expression microarray data.

    PubMed

    Harvey, Benjamin; Soo-Yeon Ji

    2014-01-01

    As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring inference though analysis of DNA/mRNA sequence data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological inference by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale classification analysis of microarray data using Wavelet thresholding in a Cloud environment to identify significantly expressed features. This paper proposes a novel methodology that uses Wavelet based Denoising to initialize a threshold for determination of significantly expressed genes for classification. Additionally, this research was implemented and encompassed within cloud-based distributed processing environment. The utilization of Cloud computing and Wavelet thresholding was used for the classification 14 tumor classes from the Global Cancer Map (GCM). The results proved to be more accurate than using a predefined p-value for differential expression classification. This novel methodology analyzed Wavelet based threshold features of gene expression in a Cloud environment, furthermore classifying the expression of samples by analyzing gene patterns, which inform us of biological processes. Moreover, enabling researchers to face the present and forthcoming challenges that may arise in the analysis of data in functional genomics of large microarray datasets.

  5. Methods for monitoring multiple gene expression

    DOEpatents

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    2013-10-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  6. Methods for monitoring multiple gene expression

    DOEpatents

    Berka, Randy [Davis, CA; Bachkirova, Elena [Davis, CA; Rey, Michael [Davis, CA

    2012-05-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  7. Methods for monitoring multiple gene expression

    DOEpatents

    Berka, Randy [Davis, CA; Bachkirova, Elena [Davis, CA; Rey, Michael [Davis, CA

    2008-06-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  10. Hematopoietic progenitors express neural genes

    PubMed Central

    Goolsby, James; Marty, Marie C.; Heletz, Dafna; Chiappelli, Joshua; Tashko, Gerti; Yarnell, Deborah; Fishman, Paul S.; Dhib-Jalbut, Suhayl; Bever, Christopher T.; Pessac, Bernard; Trisler, David

    2003-01-01

    Bone marrow, or cells selected from bone marrow, were reported recently to give rise to cells with a neural phenotype after in vitro treatment with neural-inducing factors or after delivery into the brain. However, we showed previously that untreated bone marrow cells express products of the neural myelin basic protein gene, and we demonstrate here that a subset of ex vivo bone marrow cells expresses the neurogenic transcription factor Pax-6 as well as neuronal genes encoding neurofilament H, NeuN (neuronal nuclear protein), HuC/HuD (Hu-antigen C/Hu-antigen D), and GAD65 (glutamic acid decarboxylase 65), as well as the oligodendroglial gene encoding CNPase (2′,3′ cyclic nucleotide 3′-phosphohydrolase). In contrast, astroglial glial fibrillary acidic protein (GFAP) was not detected. These cells also were CD34+, a marker of hematopoietic stem cells. Cultures of these highly proliferative CD34+ cells, derived from adult mouse bone marrow, uniformly displayed a phenotype comparable with that of hematopoietic progenitor cells (CD45+, CD34+, Sca-1+, AA4.1+, cKit+, GATA-2+, and LMO-2+). The neuronal and oligodendroglial genes expressed in ex vivo bone marrow also were expressed in all cultured CD34+ cells, and GFAP was not observed. After CD34+ cell transplantation into adult brain, neuronal or oligodendroglial markers segregated into distinct nonoverlapping cell populations, whereas astroglial GFAP appeared, in the absence of other neural markers, in a separate set of implanted cells. Thus, neuronal and oligodendroglial gene products are present in a subset of bone marrow cells, and the expression of these genes can be regulated in brain. The fact that these CD34+ cells also express transcription factors (Rex-1 and Oct-4) that are found in early development elicits the hypothesis that they may be pluripotent embryonic-like stem cells. PMID:14634211

  11. Gene expression during blow fly development: improving the precision of age estimates in forensic entomology.

    PubMed

    Tarone, Aaron M; Foran, David R

    2011-01-01

    Forensic entomologists use size and developmental stage to estimate blow fly age, and from those, a postmortem interval. Since such estimates are generally accurate but often lack precision, particularly in the older developmental stages, alternative aging methods would be advantageous. Presented here is a means of incorporating developmentally regulated gene expression levels into traditional stage and size data, with a goal of more precisely estimating developmental age of immature Lucilia sericata. Generalized additive models of development showed improved statistical support compared to models that did not include gene expression data, resulting in an increase in estimate precision, especially for postfeeding third instars and pupae. The models were then used to make blind estimates of development for 86 immature L. sericata raised on rat carcasses. Overall, inclusion of gene expression data resulted in increased precision in aging blow flies. © 2010 American Academy of Forensic Sciences.

  12. Cell-specific prediction and application of drug-induced gene expression profiles.

    PubMed

    Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David; Dudley, Joel

    2018-01-01

    Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes.

  13. Cell-specific prediction and application of drug-induced gene expression profiles

    PubMed Central

    Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R.; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David

    2017-01-01

    Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes. PMID:29218867

  14. Digital gene expression analysis of the zebra finch genome

    PubMed Central

    2010-01-01

    Background In order to understand patterns of adaptation and molecular evolution it is important to quantify both variation in gene expression and nucleotide sequence divergence. Gene expression profiling in non-model organisms has recently been facilitated by the advent of massively parallel sequencing technology. Here we investigate tissue specific gene expression patterns in the zebra finch (Taeniopygia guttata) with special emphasis on the genes of the major histocompatibility complex (MHC). Results Almost 2 million 454-sequencing reads from cDNA of six different tissues were assembled and analysed. A total of 11,793 zebra finch transcripts were represented in this EST data, indicating a transcriptome coverage of about 65%. There was a positive correlation between the tissue specificity of gene expression and non-synonymous to synonymous nucleotide substitution ratio of genes, suggesting that genes with a specialised function are evolving at a higher rate (or with less constraint) than genes with a more general function. In line with this, there was also a negative correlation between overall expression levels and expression specificity of contigs. We found evidence for expression of 10 different genes related to the MHC. MHC genes showed relatively tissue specific expression levels and were in general primarily expressed in spleen. Several MHC genes, including MHC class I also showed expression in brain. Furthermore, for all genes with highest levels of expression in spleen there was an overrepresentation of several gene ontology terms related to immune function. Conclusions Our study highlights the usefulness of next-generation sequence data for quantifying gene expression in the genome as a whole as well as in specific candidate genes. Overall, the data show predicted patterns of gene expression profiles and molecular evolution in the zebra finch genome. Expression of MHC genes in particular, corresponds well with expression patterns in other vertebrates

  15. Regulatory systems for hypoxia-inducible gene expression in ischemic heart disease gene therapy.

    PubMed

    Kim, Hyun Ah; Rhim, Taiyoun; Lee, Minhyung

    2011-07-18

    Ischemic heart diseases are caused by narrowed coronary arteries that decrease the blood supply to the myocardium. In the ischemic myocardium, hypoxia-responsive genes are up-regulated by hypoxia-inducible factor-1 (HIF-1). Gene therapy for ischemic heart diseases uses genes encoding angiogenic growth factors and anti-apoptotic proteins as therapeutic genes. These genes increase blood supply into the myocardium by angiogenesis and protect cardiomyocytes from cell death. However, non-specific expression of these genes in normal tissues may be harmful, since growth factors and anti-apoptotic proteins may induce tumor growth. Therefore, tight gene regulation is required to limit gene expression to ischemic tissues, to avoid unwanted side effects. For this purpose, various gene expression strategies have been developed for ischemic-specific gene expression. Transcriptional, post-transcriptional, and post-translational regulatory strategies have been developed and evaluated in ischemic heart disease animal models. The regulatory systems can limit therapeutic gene expression to ischemic tissues and increase the efficiency of gene therapy. In this review, recent progresses in ischemic-specific gene expression systems are presented, and their applications to ischemic heart diseases are discussed. Copyright © 2011 Elsevier B.V. All rights reserved.

  16. Combination of gene expression patterns in whole blood discriminate between tuberculosis infection states

    PubMed Central

    2014-01-01

    Background Genetic factors are involved in susceptibility or protection to tuberculosis (TB). Apart from gene polymorphisms and mutations, changes in levels of gene expression, induced by non-genetic factors, may also determine whether individuals progress to active TB. Methods We analysed the expression level of 45 genes in a total of 47 individuals (23 healthy household contacts and 24 new smear-positive pulmonary TB patients) in Addis Ababa using a dual colour multiplex ligation-dependent probe amplification (dcRT-MLPA) technique to assess gene expression profiles that may be used to distinguish TB cases and their contacts and also latently infected (LTBI) and uninfected household contacts. Results The gene expression level of BLR1, Bcl2, IL4d2, IL7R, FCGR1A, MARCO, MMP9, CCL19, and LTF had significant discriminatory power between sputum smear-positive TB cases and household contacts, with AUCs of 0.84, 0.81, 0.79, 0.79, 0.78, 0.76, 0.75, 0.75 and 0.68 respectively. The combination of Bcl2, BLR1, FCGR1A, IL4d2 and MARCO identified 91.66% of active TB cases and 95.65% of household contacts without active TB. The expression of CCL19, TGFB1, and Foxp3 showed significant difference between LTBI and uninfected contacts, with AUCs of 0.85, 0.82, and 0.75, respectively, whereas the combination of BPI, CCL19, FoxP3, FPR1 and TGFB1 identified 90.9% of QFT- and 91.6% of QFT+ household contacts. Conclusions Expression of single and especially combinations of host genes can accurately differentiate between active TB cases and healthy individuals as well as between LTBI and uninfected contacts. PMID:24885723

  17. Identification and validation of quantitative real-time reverse transcription PCR reference genes for gene expression analysis in teak (Tectona grandis L.f.)

    PubMed Central

    2014-01-01

    Background Teak (Tectona grandis L.f.) is currently the preferred choice of the timber trade for fabrication of woody products due to its extraordinary qualities and is widely grown around the world. Gene expression studies are essential to explore wood formation of vascular plants, and quantitative real-time reverse transcription PCR (qRT-PCR) is a sensitive technique employed for quantifying gene expression levels. One or more appropriate reference genes are crucial to accurately compare mRNA transcripts through different tissues/organs and experimental conditions. Despite being the focus of some genetic studies, a lack of molecular information has hindered genetic exploration of teak. To date, qRT-PCR reference genes have not been identified and validated for teak. Results Identification and cloning of nine commonly used qRT-PCR reference genes from teak, including ribosomal protein 60s (rp60s), clathrin adaptor complexes medium subunit family (Cac), actin (Act), histone 3 (His3), sand family (Sand), β-Tubulin (Β-Tub), ubiquitin (Ubq), elongation factor 1-α (Ef-1α), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Expression profiles of these genes were evaluated by qRT-PCR in six tissue and organ samples (leaf, flower, seedling, root, stem and branch secondary xylem) of teak. Appropriate gene cloning and sequencing, primer specificity and amplification efficiency was verified for each gene. Their stability as reference genes was validated by NormFinder, BestKeeper, geNorm and Delta Ct programs. Results obtained from all programs showed that TgUbq and TgEf-1α are the most stable genes to use as qRT-PCR reference genes and TgAct is the most unstable gene in teak. The relative expression of the teak cinnamyl alcohol dehydrogenase (TgCAD) gene in lignified tissues at different ages was assessed by qRT-PCR, using TgUbq and TgEf-1α as internal controls. These analyses exposed a consistent expression pattern with both reference genes. Conclusion This study

  18. Selection of reference genes for expression analyses of red-fleshed sweet orange (Citrus sinensis).

    PubMed

    Pinheiro, T T; Nishimura, D S; De Nadai, F B; Figueira, A; Latado, R R

    2015-12-28

    Red-fleshed oranges (Citrus sinensis) contain high levels of carotenoids and lycopene. The growing consumer demand for products with health benefits has increased interest in these types of Citrus cultivars as a potential source of nutraceuticals. However, little is known about the physiology of these cultivars under Brazilian conditions. Transcriptome and gene expression analyses are important tools in the breeding and management of red-fleshed sweet orange cultivars. Reverse transcription quantitative polymerase chain reaction is a method of quantifying gene expression, but various standardizations are required to obtain precise, accurate, and specific results. Among the standardizations required, the choice of suitable stable reference genes is fundamental. The objective of this study was to evaluate the stability of 11 candidate genes using various tissue and organ samples from healthy plants or leaves from citrus greening disease (Huanglongbing)-symptomatic plants of a Brazilian red-fleshed cultivar ('Sanguínea de Mombuca'), in order to select the most suitable reference gene for investigating gene expression under these conditions. geNorm and NormFinder identified genes that encoded translation initiation factor 3, ribosomal protein L35, and translation initiation factor 5A as the most stable genes under the biological conditions tested, and genes coding actin (ACT) and the subunit of the PSI reaction center subunit III were the least stable. Phosphatase, malate dehydrogenase, and ACT were the most stable genes in the leaf samples of infected plants.

  19. Method of controlling gene expression

    DOEpatents

    Peters, Norman K.; Frost, John W.; Long, Sharon R.

    1991-12-03

    A method of controlling expression of a DNA segment under the control of a nod gene promoter which comprises administering to a host containing a nod gene promoter an amount sufficient to control expression of the DNA segment of a compound of the formula: ##STR1## in which each R is independently H or OH, is described.

  20. SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models

    PubMed Central

    2014-01-01

    Background Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. Results SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. Conclusions SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/. PMID:24980894

  1. Transient, Inducible, Placenta-Specific Gene Expression in Mice

    PubMed Central

    Fan, Xiujun; Petitt, Matthew; Gamboa, Matthew; Huang, Mei; Dhal, Sabita; Druzin, Maurice L.; Wu, Joseph C.

    2012-01-01

    Molecular understanding of placental functions and pregnancy disorders is limited by the absence of methods for placenta-specific gene manipulation. Although persistent placenta-specific gene expression has been achieved by lentivirus-based gene delivery methods, developmentally and physiologically important placental genes have highly stage-specific functions, requiring controllable, transient expression systems for functional analysis. Here, we describe an inducible, placenta-specific gene expression system that enables high-level, transient transgene expression and monitoring of gene expression by live bioluminescence imaging in mouse placenta at different stages of pregnancy. We used the third generation tetracycline-responsive tranactivator protein Tet-On 3G, with 10- to 100-fold increased sensitivity to doxycycline (Dox) compared with previous versions, enabling unusually sensitive on-off control of gene expression in vivo. Transgenic mice expressing Tet-On 3G were created using a new integrase-based, site-specific approach, yielding high-level transgene expression driven by a ubiquitous promoter. Blastocysts from these mice were transduced with the Tet-On 3G-response element promoter-driving firefly luciferase using lentivirus-mediated placenta-specific gene delivery and transferred into wild-type pseudopregnant recipients for placenta-specific, Dox-inducible gene expression. Systemic Dox administration at various time points during pregnancy led to transient, placenta-specific firefly luciferase expression as early as d 5 of pregnancy in a Dox dose-dependent manner. This system enables, for the first time, reliable pregnancy stage-specific induction of gene expression in the placenta and live monitoring of gene expression during pregnancy. It will be widely applicable to studies of both placental development and pregnancy, and the site-specific Tet-On G3 mouse will be valuable for studies in a broad range of tissues. PMID:23011919

  2. Quantitative RT-PCR analysis of estrogen receptor gene expression in laser microdissected prostate cancer tissue.

    PubMed

    Walton, Thomas J; Li, Geng; McCulloch, Thomas A; Seth, Rashmi; Powe, Desmond G; Bishop, Michael C; Rees, Robert C

    2009-06-01

    Real-time quantitative RT-PCR analysis of laser microdissected tissue is considered the most accurate technique for determining tissue gene expression. The discovery of estrogen receptor beta (ERbeta) has focussed renewed interest on the role of estrogen receptors in prostate cancer, yet few studies have utilized the technique to analyze estrogen receptor gene expression in prostate cancer. Fresh tissue was obtained from 11 radical prostatectomy specimens and from 6 patients with benign prostate hyperplasia. Pure populations of benign and malignant prostate epithelium were laser microdissected, followed by RNA isolation and electrophoresis. Quantitative RT-PCR was performed using primers for androgen receptor (AR), estrogen receptor beta (ERbeta), estrogen receptor alpha (ERalpha), progesterone receptor (PGR) and prostate specific antigen (PSA), with normalization to two housekeeping genes. Differences in gene expression were analyzed using the Mann-Whitney U-test. Correlation coefficients were analyzed using Spearman's test. Significant positive correlations were seen when AR and AR-dependent PSA, and ERalpha and ERalpha-dependent PGR were compared, indicating a representative population of RNA transcripts. ERbeta gene expression was significantly over-expressed in the cancer group compared with benign controls (P < 0.01). In contrast, PGR expression was significantly down-regulated in the cancer group (P < 0.05). There were no significant differences in AR, ERalpha or PSA expression between the groups. This study represents the first to show an upregulation of ERbeta gene expression in laser microdissected prostate cancer specimens. In concert with recent studies the findings suggest differential production of ERbeta splice variants, which may play important roles in the genesis of prostate cancer. (c) 2009 Wiley-Liss, Inc.

  3. Two-pass imputation algorithm for missing value estimation in gene expression time series.

    PubMed

    Tsiporkova, Elena; Boeva, Veselka

    2007-10-01

    Gene expression microarray experiments frequently generate datasets with multiple values missing. However, most of the analysis, mining, and classification methods for gene expression data require a complete matrix of gene array values. Therefore, the accurate estimation of missing values in such datasets has been recognized as an important issue, and several imputation algorithms have already been proposed to the biological community. Most of these approaches, however, are not particularly suitable for time series expression profiles. In view of this, we propose a novel imputation algorithm, which is specially suited for the estimation of missing values in gene expression time series data. The algorithm utilizes Dynamic Time Warping (DTW) distance in order to measure the similarity between time expression profiles, and subsequently selects for each gene expression profile with missing values a dedicated set of candidate profiles for estimation. Three different DTW-based imputation (DTWimpute) algorithms have been considered: position-wise, neighborhood-wise, and two-pass imputation. These have initially been prototyped in Perl, and their accuracy has been evaluated on yeast expression time series data using several different parameter settings. The experiments have shown that the two-pass algorithm consistently outperforms, in particular for datasets with a higher level of missing entries, the neighborhood-wise and the position-wise algorithms. The performance of the two-pass DTWimpute algorithm has further been benchmarked against the weighted K-Nearest Neighbors algorithm, which is widely used in the biological community; the former algorithm has appeared superior to the latter one. Motivated by these findings, indicating clearly the added value of the DTW techniques for missing value estimation in time series data, we have built an optimized C++ implementation of the two-pass DTWimpute algorithm. The software also provides for a choice between three different

  4. Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

    PubMed Central

    2014-01-01

    Background Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. Results S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. Conclusions This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved

  5. Gene expression of indoor fungal communities under damp building conditions: Implications for human health.

    PubMed

    Hegarty, B; Dannemiller, K C; Peccia, J

    2018-03-03

    Dampness and visible mold growth in homes are associated with negative human health outcomes, but causal relationships between fungal exposure and health are not well established. The purpose of this study was to determine whether dampness in buildings impacts fungal community gene expression and how, in turn, gene expression may modulate human health impacts. A metatranscriptomic study was performed on house dust fungal communities to investigate the expression of genes and metabolic processes in chamber experiments at water activity levels of 0.5, 0.85, and 1.0. Fungi at water activities as low as 0.5 were metabolically active, focusing their transcriptional resources on primary processes essential for cell maintenance. Metabolic complexity increased with water activity where communities at 1.0 displayed more diverse secondary metabolic processes. Greater gene expression at increasing water activity has important implications for human health: Fungal communities at 1.0 a w upregulated a greater number of allergen-, mycotoxin-, and pathogenicity-encoding genes versus communities at 0.85 and 0.5 a w . In damp buildings, fungi may display increases in secondary metabolic processes with the potential for greater per-cell production of allergens, toxins, and pathogenicity. Assessments in wet versus dry buildings that do not account for this elevated health impact may not accurately reflect exposure. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  6. Faster-X Evolution of Gene Expression in Drosophila

    PubMed Central

    Meisel, Richard P.; Malone, John H.; Clark, Andrew G.

    2012-01-01

    DNA sequences on X chromosomes often have a faster rate of evolution when compared to similar loci on the autosomes, and well articulated models provide reasons why the X-linked mode of inheritance may be responsible for the faster evolution of X-linked genes. We analyzed microarray and RNA–seq data collected from females and males of six Drosophila species and found that the expression levels of X-linked genes also diverge faster than autosomal gene expression, similar to the “faster-X” effect often observed in DNA sequence evolution. Faster-X evolution of gene expression was recently described in mammals, but it was limited to the evolutionary lineages shortly following the creation of the therian X chromosome. In contrast, we detect a faster-X effect along both deep lineages and those on the tips of the Drosophila phylogeny. In Drosophila males, the dosage compensation complex (DCC) binds the X chromosome, creating a unique chromatin environment that promotes the hyper-expression of X-linked genes. We find that DCC binding, chromatin environment, and breadth of expression are all predictive of the rate of gene expression evolution. In addition, estimates of the intraspecific genetic polymorphism underlying gene expression variation suggest that X-linked expression levels are not under relaxed selective constraints. We therefore hypothesize that the faster-X evolution of gene expression is the result of the adaptive fixation of beneficial mutations at X-linked loci that change expression level in cis. This adaptive faster-X evolution of gene expression is limited to genes that are narrowly expressed in a single tissue, suggesting that relaxed pleiotropic constraints permit a faster response to selection. Finally, we present a conceptional framework to explain faster-X expression evolution, and we use this framework to examine differences in the faster-X effect between Drosophila and mammals. PMID:23071459

  7. Gene expression patterns in rainbow trout, Oncorhynchus mykiss, exposed to a suite of model toxicants

    PubMed Central

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

    2008-01-01

    steroidogenesis, p450 and estrogen responsive genes appear to be useful for selectively identifying toxicant mode of action in fish, suggesting a link between gene expression profile and mode of toxicity. Our array results showed good agreement with quantitative real time polymerase chain reaction (qRT PCR), which demonstrates that the arrays are an accurate measure of gene expression. The specificity of the gene expression profile in response to a model toxicant, the link between genes with altered expression and mode of toxic action, and the consistency between array and qRT PCR results all suggest that cDNA microarrays have the potential to screen environmental contaminants for biomarkers and mode of toxic action. PMID:16488489

  8. Gene expression patterns in rainbow trout, Oncorhynchus mykiss, exposed to a suite of model toxicants.

    PubMed

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

    2006-05-25

    , p450 and estrogen responsive genes appear to be useful for selectively identifying toxicant mode of action in fish, suggesting a link between gene expression profile and mode of toxicity. Our array results showed good agreement with quantitative real time polymerase chain reaction (qRT PCR), which demonstrates that the arrays are an accurate measure of gene expression. The specificity of the gene expression profile in response to a model toxicant, the link between genes with altered expression and mode of toxic action, and the consistency between array and qRT PCR results all suggest that cDNA microarrays have the potential to screen environmental contaminants for biomarkers and mode of toxic action.

  9. Analysis of global gene expression profiles to identify differentially expressed genes critical for embryo development in Brassica rapa.

    PubMed

    Zhang, Yu; Peng, Lifang; Wu, Ya; Shen, Yanyue; Wu, Xiaoming; Wang, Jianbo

    2014-11-01

    Embryo development represents a crucial developmental period in the life cycle of flowering plants. To gain insights into the genetic programs that control embryo development in Brassica rapa L., RNA sequencing technology was used to perform transcriptome profiling analysis of B. rapa developing embryos. The results generated 42,906,229 sequence reads aligned with 32,941 genes. In total, 27,760, 28,871, 28,384, and 25,653 genes were identified from embryos at globular, heart, early cotyledon, and mature developmental stages, respectively, and analysis between stages revealed a subset of stage-specific genes. We next investigated 9,884 differentially expressed genes with more than fivefold changes in expression and false discovery rate ≤ 0.001 from three adjacent-stage comparisons; 1,514, 3,831, and 6,633 genes were detected between globular and heart stage embryo libraries, heart stage and early cotyledon stage, and early cotyledon and mature stage, respectively. Large numbers of genes related to cellular process, metabolism process, response to stimulus, and biological process were expressed during the early and middle stages of embryo development. Fatty acid biosynthesis, biosynthesis of secondary metabolites, and photosynthesis-related genes were expressed predominantly in embryos at the middle stage. Genes for lipid metabolism and storage proteins were highly expressed in the middle and late stages of embryo development. We also identified 911 transcription factor genes that show differential expression across embryo developmental stages. These results increase our understanding of the complex molecular and cellular events during embryo development in B. rapa and provide a foundation for future studies on other oilseed crops.

  10. 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

  11. Stochastic gene expression in Arabidopsis thaliana.

    PubMed

    Araújo, Ilka Schultheiß; Pietsch, Jessica Magdalena; Keizer, Emma Mathilde; Greese, Bettina; Balkunde, Rachappa; Fleck, Christian; Hülskamp, Martin

    2017-12-14

    Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

  12. 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

  13. Multiscale Embedded Gene Co-expression Network Analysis

    PubMed Central

    Song, Won-Min; Zhang, Bin

    2015-01-01

    Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma. PMID:26618778

  14. Multiscale Embedded Gene Co-expression Network Analysis.

    PubMed

    Song, Won-Min; Zhang, Bin

    2015-11-01

    Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

  15. 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

  16. Gene expression profiles of fin regeneration in loach (Paramisgurnus dabryanu).

    PubMed

    Li, Li; He, Jingya; Wang, Linlin; Chen, Weihua; Chang, Zhongjie

    2017-11-01

    Teleost fins can regenerate accurate position-matched structure and function after amputation. However, we still lack systematic transcriptional profiling and methodologies to understand the molecular basis of fin regeneration. After histological analysis, we established a suppression subtraction hybridization library containing 418 distinct sequences expressed differentially during the process of blastema formation and differentiation in caudal fin regeneration. Genome ontology and comparative analysis of differential distribution of our data and the reference zebrafish genome showed notable subcategories, including multi-organism processes, response to stimuli, extracellular matrix, antioxidant activity, and cell junction function. KEGG pathway analysis allowed the effective identification of relevant genes in those pathways involved in tissue morphogenesis and regeneration, including tight junction, cell adhesion molecules, mTOR and Jak-STAT signaling pathway. From relevant function subcategories and signaling pathways, 78 clones were examined for further Southern-blot hybridization. Then, 17 genes were chosen and characterized using semi-quantitative PCR. Then 4 candidate genes were identified, including F11r, Mmp9, Agr2 and one without a match to any database. After real-time quantitative PCR, the results showed obvious expression changes in different periods of caudal fin regeneration. We can assume that the 4 candidates, likely valuable genes associated with fin regeneration, deserve additional attention. Thus, our study demonstrated how to investigate the transcript profiles with an emphasis on bioinformatics intervention and how to identify potential genes related to fin regeneration processes. The results also provide a foundation or knowledge for further research into genes and molecular mechanisms of fin regeneration. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Vascular gene expression: a hypothesis

    PubMed Central

    Martínez-Navarro, Angélica C.; Galván-Gordillo, Santiago V.; Xoconostle-Cázares, Beatriz; Ruiz-Medrano, Roberto

    2013-01-01

    The phloem is the conduit through which photoassimilates are distributed from autotrophic to heterotrophic tissues and is involved in the distribution of signaling molecules that coordinate plant growth and responses to the environment. Phloem function depends on the coordinate expression of a large array of genes. We have previously identified conserved motifs in upstream regions of the Arabidopsis genes, encoding the homologs of pumpkin phloem sap mRNAs, displaying expression in vascular tissues. This tissue-specific expression in Arabidopsis is predicted by the overrepresentation of GA/CT-rich motifs in gene promoters. In this work we have searched for common motifs in upstream regions of the homologous genes from plants considered to possess a “primitive” vascular tissue (a lycophyte), as well as from others that lack a true vascular tissue (a bryophyte), and finally from chlorophytes. Both lycophyte and bryophyte display motifs similar to those found in Arabidopsis with a significantly low E-value, while the chlorophytes showed either a different conserved motif or no conserved motif at all. These results suggest that these same genes are expressed coordinately in non-vascular plants; this coordinate expression may have been one of the prerequisites for the development of conducting tissues in plants. We have also analyzed the phylogeny of conserved proteins that may be involved in phloem function and development. The presence of CmPP16, APL, FT, and YDA in chlorophytes suggests the recruitment of ancient regulatory networks for the development of the vascular tissue during evolution while OPS is a novel protein specific to vascular plants. PMID:23882276

  18. Selection of Reference Genes for Quantitative Gene Expression in Porcine Mesenchymal Stem Cells Derived from Various Sources along with Differentiation into Multilineages

    PubMed Central

    Lee, Won-Jae; Jeon, Ryoung-Hoon; Jang, Si-Jung; Park, Ji-Sung; Lee, Seung-Chan; Baregundi Subbarao, Raghavendra; Lee, Sung-Lim; Park, Bong-Wook; King, William Allan; Rho, Gyu-Jin

    2015-01-01

    The identification of stable reference genes is a prerequisite for ensuring accurate validation of gene expression, yet too little is known about stable reference genes of porcine MSCs. The present study was, therefore, conducted to assess the stability of reference genes in porcine MSCs derived from bone marrow (BMSCs), adipose (AMSCs), and skin (SMSCs) with their in vitro differentiated cells into mesenchymal lineages such as adipocytes, osteocytes, and chondrocytes. Twelve commonly used reference genes were investigated for their threshold cycle (Ct) values by qRT-PCR. The Ct values of candidate reference genes were analyzed by geNorm software to clarify stable expression regardless of experimental conditions. Thus, Pearson's correlation was applied to determine correlation between the three most stable reference genes (NF3) and optimal number of reference genes (NFopt). In assessment of stability of reference gene across experimental conditions by geNorm analysis, undifferentiated MSCs and each differentiated status into mesenchymal lineages showed slightly different results but similar patterns about more or less stable rankings. Furthermore, Pearson's correlation revealed high correlation (r > 0.9) between NF3 and NFopt. Overall, the present study showed that HMBS, YWHAZ, SDHA, and TBP are suitable reference genes for qRT-PCR in porcine MSCs. PMID:25972899

  19. GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

    PubMed

    Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

    2018-01-01

    When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

  20. DeSigN: connecting gene expression with therapeutics for drug repurposing and development.

    PubMed

    Lee, Bernard Kok Bang; Tiong, Kai Hung; Chang, Jit Kang; Liew, Chee Sun; Abdul Rahman, Zainal Ariff; Tan, Aik Choon; Khang, Tsung Fei; Cheong, Sok Ching

    2017-01-25

    The drug discovery and development pipeline is a long and arduous process that inevitably hampers rapid drug development. Therefore, strategies to improve the efficiency of drug development are urgently needed to enable effective drugs to enter the clinic. Precision medicine has demonstrated that genetic features of cancer cells can be used for predicting drug response, and emerging evidence suggest that gene-drug connections could be predicted more accurately by exploring the cumulative effects of many genes simultaneously. We developed DeSigN, a web-based tool for predicting drug efficacy against cancer cell lines using gene expression patterns. The algorithm correlates phenotype-specific gene signatures derived from differentially expressed genes with pre-defined gene expression profiles associated with drug response data (IC 50 ) from 140 drugs. DeSigN successfully predicted the right drug sensitivity outcome in four published GEO studies. Additionally, it predicted bosutinib, a Src/Abl kinase inhibitor, as a sensitive inhibitor for oral squamous cell carcinoma (OSCC) cell lines. In vitro validation of bosutinib in OSCC cell lines demonstrated that indeed, these cell lines were sensitive to bosutinib with IC 50 of 0.8-1.2 μM. As further confirmation, we demonstrated experimentally that bosutinib has anti-proliferative activity in OSCC cell lines, demonstrating that DeSigN was able to robustly predict drug that could be beneficial for tumour control. DeSigN is a robust method that is useful for the identification of candidate drugs using an input gene signature obtained from gene expression analysis. This user-friendly platform could be used to identify drugs with unanticipated efficacy against cancer cell lines of interest, and therefore could be used for the repurposing of drugs, thus improving the efficiency of drug development.

  1. Gene expression profiling of whole blood: Comparison of target preparation methods for accurate and reproducible microarray analysis

    PubMed Central

    Vartanian, Kristina; Slottke, Rachel; Johnstone, Timothy; Casale, Amanda; Planck, Stephen R; Choi, Dongseok; Smith, Justine R; Rosenbaum, James T; Harrington, Christina A

    2009-01-01

    Background Peripheral blood is an accessible and informative source of transcriptomal information for many human disease and pharmacogenomic studies. While there can be significant advantages to analyzing RNA isolated from whole blood, particularly in clinical studies, the preparation of samples for microarray analysis is complicated by the need to minimize artifacts associated with highly abundant globin RNA transcripts. The impact of globin RNA transcripts on expression profiling data can potentially be reduced by using RNA preparation and labeling methods that remove or block globin RNA during the microarray assay. We compared four different methods for preparing microarray hybridization targets from human whole blood collected in PAXGene tubes. Three of the methods utilized the Affymetrix one-cycle cDNA synthesis/in vitro transcription protocol but varied treatment of input RNA as follows: i. no treatment; ii. treatment with GLOBINclear; or iii. treatment with globin PNA oligos. In the fourth method cDNA targets were prepared with the Ovation amplification and labeling system. Results We find that microarray targets generated with labeling methods that reduce globin mRNA levels or minimize the impact of globin transcripts during hybridization detect more transcripts in the microarray assay compared with the standard Affymetrix method. Comparison of microarray results with quantitative PCR analysis of a panel of genes from the NF-kappa B pathway shows good correlation of transcript measurements produced with all four target preparation methods, although method-specific differences in overall correlation were observed. The impact of freezing blood collected in PAXGene tubes on data reproducibility was also examined. Expression profiles show little or no difference when RNA is extracted from either fresh or frozen blood samples. Conclusion RNA preparation and labeling methods designed to reduce the impact of globin mRNA transcripts can significantly improve the

  2. Integrative sparse principal component analysis of gene expression data.

    PubMed

    Liu, Mengque; Fan, Xinyan; Fang, Kuangnan; Zhang, Qingzhao; Ma, Shuangge

    2017-12-01

    In the analysis of gene expression data, dimension reduction techniques have been extensively adopted. The most popular one is perhaps the PCA (principal component analysis). To generate more reliable and more interpretable results, the SPCA (sparse PCA) technique has been developed. With the "small sample size, high dimensionality" characteristic of gene expression data, the analysis results generated from a single dataset are often unsatisfactory. Under contexts other than dimension reduction, integrative analysis techniques, which jointly analyze the raw data of multiple independent datasets, have been developed and shown to outperform "classic" meta-analysis and other multidatasets techniques and single-dataset analysis. In this study, we conduct integrative analysis by developing the iSPCA (integrative SPCA) method. iSPCA achieves the selection and estimation of sparse loadings using a group penalty. To take advantage of the similarity across datasets and generate more accurate results, we further impose contrasted penalties. Different penalties are proposed to accommodate different data conditions. Extensive simulations show that iSPCA outperforms the alternatives under a wide spectrum of settings. The analysis of breast cancer and pancreatic cancer data further shows iSPCA's satisfactory performance. © 2017 WILEY PERIODICALS, INC.

  3. In silico method for modelling metabolism and gene product expression at genome scale

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

    Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem

    2012-07-03

    Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome andmore » transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.« less

  4. Customized oligonucleotide microarray gene expression-based classification of neuroblastoma patients outperforms current clinical risk stratification.

    PubMed

    Oberthuer, André; Berthold, Frank; Warnat, Patrick; Hero, Barbara; Kahlert, Yvonne; Spitz, Rüdiger; Ernestus, Karen; König, Rainer; Haas, Stefan; Eils, Roland; Schwab, Manfred; Brors, Benedikt; Westermann, Frank; Fischer, Matthias

    2006-11-01

    To develop a gene expression-based classifier for neuroblastoma patients that reliably predicts courses of the disease. Two hundred fifty-one neuroblastoma specimens were analyzed using a customized oligonucleotide microarray comprising 10,163 probes for transcripts with differential expression in clinical subgroups of the disease. Subsequently, the prediction analysis for microarrays (PAM) was applied to a first set of patients with maximally divergent clinical courses (n = 77). The classification accuracy was estimated by a complete 10-times-repeated 10-fold cross validation, and a 144-gene predictor was constructed from this set. This classifier's predictive power was evaluated in an independent second set (n = 174) by comparing results of the gene expression-based classification with those of risk stratification systems of current trials from Germany, Japan, and the United States. The first set of patients was accurately predicted by PAM (cross-validated accuracy, 99%). Within the second set, the PAM classifier significantly separated cohorts with distinct courses (3-year event-free survival [EFS] 0.86 +/- 0.03 [favorable; n = 115] v 0.52 +/- 0.07 [unfavorable; n = 59] and 3-year overall survival 0.99 +/- 0.01 v 0.84 +/- 0.05; both P < .0001) and separated risk groups of current neuroblastoma trials into subgroups with divergent outcome (NB2004: low-risk 3-year EFS 0.86 +/- 0.04 v 0.25 +/- 0.15, P < .0001; intermediate-risk 1.00 v 0.57 +/- 0.19, P = .018; high-risk 0.81 +/- 0.10 v 0.56 +/- 0.08, P = .06). In a multivariate Cox regression model, the PAM predictor classified patients of the second set more accurately than risk stratification of current trials from Germany, Japan, and the United States (P < .001; hazard ratio, 4.756 [95% CI, 2.544 to 8.893]). Integration of gene expression-based class prediction of neuroblastoma patients may improve risk estimation of current neuroblastoma trials.

  5. HOX gene expression in phenotypic and genotypic subgroups and low HOXA gene expression as an adverse prognostic factor in pediatric ALL.

    PubMed

    Starkova, Julia; Zamostna, Blanka; Mejstrikova, Ester; Krejci, Roman; Drabkin, Harry A; Trka, Jan

    2010-12-01

    HOX genes play an important role in both normal lymphopoiesis and leukemogenesis. However, HOX expression patterns in leukemia cells compared to normal lymphoid progenitors have not been systematically studied in acute lymphoblastic leukemia (ALL) subtypes. The RNA expression levels of HOXA, HOXB, and CDX1/2 genes were analyzed by qRT-PCR in a cohort of 61 diagnostic pediatric ALL samples and FACS-sorted subpopulations of normal lymphoid progenitors. The RNA expression of HOXA7-10, HOXA13, and HOXB2-4 genes was exclusively detected in leukemic cells and immature progenitors. The RNA expression of HOXB6 and CDX2 genes was exclusively detected in leukemic cells but not in B-lineage cells at any of the studied developmental stages. HOXA3-4, HOXA7, and HOXB3-4 genes were differentially expressed between BCP-ALL and T-ALL subgroups, and among genotypically defined MLL/AF4, TEL/AML1, BCR/ABL, hyperdiploid and normal karyotype subgroups. However, this differential expression did not define specific clusters in hierarchical cluster analysis. HOXA7 gene was low expressed at the RNA level in patients with hyperdiploid leukemia, whereas HOXB7 and CDX2 genes were low expressed in TEL/AML1-positive and BCR/ABL-positive cases, respectively. In contrast to previous findings in acute myeloid leukemia, high HOXA RNA expression was associated with an excellent prognosis in Cox's regression model (P = 0.03). In MLL/AF4-positive ALL, lower HOXA RNA expression correlated with the methylation status of their promoters. HOX gene RNA expression cannot discriminate leukemia subgroups or relative maturity of leukemic cells. However, HOXA RNA expression correlates with prognosis, and particular HOX genes are expressed in specific genotypically characterized subgroups.

  6. DNMT3B modulates the expression of cancer-related genes and downregulates the expression of the gene VAV3 via methylation

    PubMed Central

    Peralta-Arrieta, Irlanda; Hernández-Sotelo, Daniel; Castro-Coronel, Yaneth; Leyva-Vázquez, Marco Antonio; Illades-Aguiar, Berenice

    2017-01-01

    Altered promoter DNA methylation is one of the most important epigenetic abnormalities in human cancer. DNMT3B, de novo methyltransferase, is clearly related to abnormal methylation of tumour suppressor genes, DNA repair genes and its overexpression contributes to oncogenic processes and tumorigenesis in vivo. The purpose of this study was to assess the effect of the overexpression of DNMT3B in HaCaT cells on global gene expression and on the methylation of selected genes to the identification of genes that can be target of DNMT3B. We found that the overexpression of DNMT3B in HaCaT cells, modulate the expression of genes related to cancer, downregulated the expression of 151 genes with CpG islands and downregulated the expression of the VAV3 gene via methylation of its promoter. These results highlight the importance of DNMT3B in gene expression and human cancer. PMID:28123849

  7. DNMT3B modulates the expression of cancer-related genes and downregulates the expression of the gene VAV3 via methylation.

    PubMed

    Peralta-Arrieta, Irlanda; Hernández-Sotelo, Daniel; Castro-Coronel, Yaneth; Leyva-Vázquez, Marco Antonio; Illades-Aguiar, Berenice

    2017-01-01

    Altered promoter DNA methylation is one of the most important epigenetic abnormalities in human cancer. DNMT3B, de novo methyltransferase, is clearly related to abnormal methylation of tumour suppressor genes, DNA repair genes and its overexpression contributes to oncogenic processes and tumorigenesis in vivo . The purpose of this study was to assess the effect of the overexpression of DNMT3B in HaCaT cells on global gene expression and on the methylation of selected genes to the identification of genes that can be target of DNMT3B. We found that the overexpression of DNMT3B in HaCaT cells, modulate the expression of genes related to cancer, downregulated the expression of 151 genes with CpG islands and downregulated the expression of the VAV3 gene via methylation of its promoter. These results highlight the importance of DNMT3B in gene expression and human cancer.

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

    PubMed

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

    2012-10-01

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

  9. Magnetic field-controlled gene expression in encapsulated cells

    PubMed Central

    Ortner, Viktoria; Kaspar, Cornelius; Halter, Christian; Töllner, Lars; Mykhaylyk, Olga; Walzer, Johann; Günzburg, Walter H.; Dangerfield, John A.; Hohenadl, Christine; Czerny, Thomas

    2012-01-01

    Cell and gene therapies have an enormous range of potential applications, but as for most other therapies, dosing is a critical issue, which makes regulated gene expression a prerequisite for advanced strategies. Several inducible expression systems have been established, which mainly rely on small molecules as inducers, such as hormones or antibiotics. The application of these inducers is difficult to control and the effects on gene regulation are slow. Here we describe a novel system for induction of gene expression in encapsulated cells. This involves the modification of cells to express potential therapeutic genes under the control of a heat inducible promoter and the co-encapsulation of these cells with magnetic nanoparticles. These nanoparticles produce heat when subjected to an alternating magnetic field; the elevated temperatures in the capsules then induce gene expression. In the present study we define the parameters of such systems and provide proof-of-principle using reporter gene constructs. The fine-tuned heating of nanoparticles in the magnetic field allows regulation of gene expression from the outside over a broad range and within short time. Such a system has great potential for advancement of cell and gene therapy approaches. PMID:22197778

  10. Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

    PubMed Central

    Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

    2013-01-01

    The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

  11. Arabidopsis gene expression patterns are altered during spaceflight

    NASA Astrophysics Data System (ADS)

    Paul, Anna-Lisa; Popp, Michael P.; Gurley, William B.; Guy, Charles; Norwood, Kelly L.; Ferl, Robert J.

    The exposure of Arabidopsis thaliana (Arabidopsis) plants to spaceflight environments results in differential gene expression. 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 gene expression patterns initially by using the Adh/GUS transgene to address specifically the possibility that spaceflight induces a hypoxic stress response (Paul, A.L., Daugherty, C.J., Bihn, E.A., Chapman, D.K., Norwood, K.L., Ferl, R.J., 2001. Transgene expression patterns indicate that spaceflight affects stress signal perception and transduction in arabidopsis, Plant Physiol. 126, 613-621). As a follow-on to the reporter gene analysis, we report here the evaluation of genome-wide patterns of native gene expression within Arabidopsis shoots utilizing the Agilent DNA array of 21,000 Arabidopsis genes. As a control for the veracity of the array analyses, a selection of genes was further characterized with quantitative Real-Time RT PCR (ABI - Taqman®). Comparison of the patterns of expression for arrays probed with RNA isolated from plants exposed to spaceflight compared to RNA isolated from ground control plants revealed 182 genes that were differentially expressed in response to the spaceflight mission by more than 4-fold, and of those only 50 genes were expressed at levels chosen to support a conservative change call. None of the genes that are hallmarks of hypoxic stress were induced to this level. However, genes related to heat shock were dramatically induced - but in a pattern and under growth conditions that are not easily explained by elevated temperatures. These gene expression data are discussed in light of current models for plant responses to the spaceflight environment and with regard to potential future spaceflight experiment

  12. Reference genes for measuring mRNA expression.

    PubMed

    Dundas, Jitesh; Ling, Maurice

    2012-12-01

    The aim of this review is to find answers to some of the questions surrounding reference genes and their reliability for quantitative experiments. Reference genes are assumed to be at a constant expression level, over a range of conditions such as temperature. These genes, such as GADPH and beta-actin, are used extensively for gene expression studies using techniques like quantitative PCR. There have been several studies carried out on identifying reference genes. However, a lot of evidence indicates issues to the general suitability of these genes. Recent studies had shown that different factors, including the environment and methods, play an important role in changing the expression levels of the reference genes. Thus, we conclude that there is no reference gene that can deemed suitable for all the experimental conditions. In addition, we believe that every experiment will require the scientific evaluation and selection of the best candidate gene for use as a reference gene to obtain reliable scientific results.

  13. Confocal quantification of cis-regulatory reporter gene expression in living sea urchin.

    PubMed

    Damle, Sagar; Hanser, Bridget; Davidson, Eric H; Fraser, Scott E

    2006-11-15

    Quantification of GFP reporter gene expression at single cell level in living sea urchin embryos can now be accomplished by a new method of confocal laser scanning microscopy (CLSM). Eggs injected with a tissue-specific GFP reporter DNA construct were grown to gastrula stage and their fluorescence recorded as a series of contiguous Z-section slices that spanned the entire embryo. To measure the depth-dependent signal decay seen in the successive slices of an image stack, the eggs were coinjected with a freely diffusible internal fluorescent standard, rhodamine dextran. The measured rhodamine fluorescence was used to generate a computational correction for the depth-dependent loss of GFP fluorescence per slice. The intensity of GFP fluorescence was converted to the number of GFP molecules using a conversion constant derived from CLSM imaging of eggs injected with a measured quantity of GFP protein. The outcome is a validated method for accurately counting GFP molecules in given cells in reporter gene transfer experiments, as we demonstrate by use of an expression construct expressed exclusively in skeletogenic cells.

  14. Biased gene expression in early honeybee larval development

    PubMed Central

    2013-01-01

    Background Female larvae of the honeybee (Apis mellifera) develop into either queens or workers depending on nutrition. This nutritional stimulus triggers different developmental trajectories, resulting in adults that differ from each other in physiology, behaviour and life span. Results To understand how these trajectories are established we have generated a comprehensive atlas of gene expression throughout larval development. We found substantial differences in gene expression between worker and queen-destined larvae at 6 hours after hatching. Some of these early changes in gene expression are maintained throughout larval development, indicating that caste-specific developmental trajectories are established much earlier than previously thought. Within our gene expression data we identified processes that potentially underlie caste differentiation. Queen-destined larvae have higher expression of genes involved in transcription, translation and protein folding early in development with a later switch to genes involved in energy generation. Using RNA interference, we were able to demonstrate that one of these genes, hexamerin 70b, has a role in caste differentiation. Both queen and worker developmental trajectories are associated with the expression of genes that have alternative splice variants, although only a single variant of a gene tends to be differentially expressed in a given caste. Conclusions Our data, based on the biases in gene expression early in development together with published data, supports the idea that caste development in the honeybee consists of two phases; an initial biased phase of development, where larvae can still switch to the other caste by differential feeding, followed by commitment to a particular developmental trajectory. PMID:24350621

  15. GeneSigDB—a curated database of gene expression signatures

    PubMed Central

    Culhane, Aedín C.; Schwarzl, Thomas; Sultana, Razvan; Picard, Kermshlise C.; Picard, Shaita C.; Lu, Tim H.; Franklin, Katherine R.; French, Simon J.; Papenhausen, Gerald; Correll, Mick; Quackenbush, John

    2010-01-01

    The primary objective of most gene expression studies is the identification of one or more gene signatures; lists of genes whose transcriptional levels are uniquely associated with a specific biological phenotype. Whilst thousands of experimentally derived gene signatures are published, their potential value to the community is limited by their computational inaccessibility. Gene signatures are embedded in published article figures, tables or in supplementary materials, and are frequently presented using non-standard gene or probeset nomenclature. We present GeneSigDB (http://compbio.dfci.harvard.edu/genesigdb) a manually curated database of gene expression signatures. GeneSigDB release 1.0 focuses on cancer and stem cells gene signatures and was constructed from more than 850 publications from which we manually transcribed 575 gene signatures. Most gene signatures (n = 560) were successfully mapped to the genome to extract standardized lists of EnsEMBL gene identifiers. GeneSigDB provides the original gene signature, the standardized gene list and a fully traceable gene mapping history for each gene from the original transcribed data table through to the standardized list of genes. The GeneSigDB web portal is easy to search, allows users to compare their own gene list to those in the database, and download gene signatures in most common gene identifier formats. PMID:19934259

  16. Gene Expression Studies in Lygus lineolaris

    USDA-ARS?s Scientific Manuscript database

    Genes are expressed in insect cells, as in all living organisms, by transcription of DNA into RNA followed by translation of RNA into proteins. The intricate patterns of differential gene expression in time and space directly influence the development and function of every aspect of the organism. Wh...

  17. Central nervous system gene expression changes in a transgenic mouse model for bovine spongiform encephalopathy

    PubMed Central

    2011-01-01

    Gene expression analysis has proven to be a very useful tool to gain knowledge of the factors involved in the pathogenesis of diseases, particularly in the initial or preclinical stages. With the aim of finding new data on the events occurring in the Central Nervous System in animals affected with Bovine Spongiform Encephalopathy, a comprehensive genome wide gene expression study was conducted at different time points of the disease on mice genetically modified to model the bovine species brain in terms of cellular prion protein. An accurate analysis of the information generated by microarray technique was the key point to assess the biological relevance of the data obtained in terms of Transmissible Spongiform Encephalopathy pathogenesis. Validation of the microarray technique was achieved by RT-PCR confirming the RNA change and immunohistochemistry techniques that verified that expression changes were translated into variable levels of protein for selected genes. Our study reveals changes in the expression of genes, some of them not previously associated with prion diseases, at early stages of the disease previous to the detection of the pathological prion protein, that might have a role in neuronal degeneration and several transcriptional changes showing an important imbalance in the Central Nervous System homeostasis in advanced stages of the disease. Genes whose expression is altered at early stages of the disease should be considered as possible therapeutic targets and potential disease markers in preclinical diagnostic tool development. Genes non-previously related to prion diseases should be taken into consideration for further investigations. PMID:22035425

  18. Identification of reference genes in human myelomonocytic cells for gene expression studies in altered gravity.

    PubMed

    Thiel, Cora S; Hauschild, Swantje; Tauber, Svantje; Paulsen, Katrin; Raig, Christiane; Raem, Arnold; Biskup, Josefine; Gutewort, Annett; Hürlimann, Eva; Unverdorben, Felix; Buttron, Isabell; Lauber, Beatrice; Philpot, Claudia; Lier, Hartwin; Engelmann, Frank; Layer, Liliana E; Ullrich, Oliver

    2015-01-01

    Gene expression studies are indispensable for investigation and elucidation of molecular mechanisms. For the process of normalization, reference genes ("housekeeping genes") are essential to verify gene expression analysis. Thus, it is assumed that these reference genes demonstrate similar expression levels over all experimental conditions. However, common recommendations about reference genes were established during 1 g conditions and therefore their applicability in studies with altered gravity has not been demonstrated yet. The microarray technology is frequently used to generate expression profiles under defined conditions and to determine the relative difference in expression levels between two or more different states. In our study, we searched for potential reference genes with stable expression during different gravitational conditions (microgravity, normogravity, and hypergravity) which are additionally not altered in different hardware systems. We were able to identify eight genes (ALB, B4GALT6, GAPDH, HMBS, YWHAZ, ABCA5, ABCA9, and ABCC1) which demonstrated no altered gene expression levels in all tested conditions and therefore represent good candidates for the standardization of gene expression studies in altered gravity.

  19. Nephron segment-specific gene expression using AAV vectors.

    PubMed

    Asico, Laureano D; Cuevas, Santiago; Ma, Xiaobo; Jose, Pedro A; Armando, Ines; Konkalmatt, Prasad R

    2018-02-26

    AAV9 vector provides efficient gene transfer in all segments of the renal nephron, with minimum expression in non-renal cells, when administered retrogradely via the ureter. It is important to restrict the transgene expression to the desired cell type within the kidney, so that the physiological endpoints represent the function of the transgene expressed in that specific cell type within kidney. We hypothesized that segment-specific gene expression within the kidney can be accomplished using the highly efficient AAV9 vectors carrying the promoters of genes that are expressed exclusively in the desired segment of the nephron in combination with administration by retrograde infusion into the kidney via the ureter. We constructed AAV vectors carrying eGFP under the control of: kidney-specific cadherin (KSPC) gene promoter for expression in the entire nephron; Na + /glucose co-transporter (SGLT2) gene promoter for expression in the S1 and S2 segments of the proximal tubule; sodium, potassium, 2 chloride co-transporter (NKCC2) gene promoter for expression in the thick ascending limb of Henle's loop (TALH); E-cadherin (ECAD) gene promoter for expression in the collecting duct (CD); and cytomegalovirus (CMV) early promoter that provides expression in most of the mammalian cells, as control. We tested the specificity of the promoter constructs in vitro for cell type-specific expression in mouse kidney cells in primary culture, followed by retrograde infusion of the AAV vectors via the ureter in the mouse. Our data show that AAV9 vector, in combination with the segment-specific promoters administered by retrograde infusion via the ureter, provides renal nephron segment-specific gene expression. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Identifying osteosarcoma metastasis associated genes by weighted gene co-expression network analysis (WGCNA).

    PubMed

    Tian, Honglai; Guan, Donghui; Li, Jianmin

    2018-06-01

    Osteosarcoma (OS), the most common malignant bone tumor, accounts for the heavy healthy threat in the period of children and adolescents. OS occurrence usually correlates with early metastasis and high death rate. This study aimed to better understand the mechanism of OS metastasis.Based on Gene Expression Omnibus (GEO) database, we downloaded 4 expression profile data sets associated with OS metastasis, and selected differential expressed genes. Weighted gene co-expression network analysis (WGCNA) approach allowed us to investigate the most OS metastasis-correlated module. Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to give annotation of selected OS metastasis-associated genes.We select 897 differential expressed genes from OS metastasis and OS non-metastasis groups. Based on these selected genes, WGCNA further explored 142 genes included in the most OS metastasis-correlated module. Gene Ontology functional and KEGG pathway enrichment analyses showed that significantly OS metastasis-associated genes were involved in pathway correlated with insulin-like growth factor binding.Our research figured out several potential molecules participating in metastasis process and factors acting as biomarker. With this study, we could better explore the mechanism of OS metastasis and further discover more therapy targets.

  1. Gene expression analysis of pancreatic cell lines reveals genes overexpressed in pancreatic cancer.

    PubMed

    Alldinger, Ingo; Dittert, Dag; Peiper, Matthias; Fusco, Alberto; Chiappetta, Gennaro; Staub, Eike; Lohr, Matthias; Jesnowski, Ralf; Baretton, Gustavo; Ockert, Detlef; Saeger, Hans-Detlev; Grützmann, Robert; Pilarsky, Christian

    2005-01-01

    Pancreatic cancer is one of the leading causes of cancer-related death. Using DNA gene expression analysis based on a custom made Affymetrix cancer array, we investigated the expression pattern of both primary and established pancreatic carcinoma cell lines. We analyzed the gene expression of 5 established pancreatic cancer cell lines (AsPC-1, BxPC-3, Capan-1, Capan-2 and HPAF II) and 5 primary isolates, 1 of them derived from benign pancreatic duct cells. Out of 1,540 genes which were expressed in at least 3 experiments, we found 122 genes upregulated and 18 downregulated in tumor cell lines compared to benign cells with a fold change >3. Several of the upregulated genes (like Prefoldin 5, ADAM9 and E-cadherin) have been associated with pancreatic cancer before. The other differentially regulated genes, however, play a so far unknown role in the course of human pancreatic carcinoma. By means of immunohistochemistry we could show that thymosin beta-10 (TMSB10), upregulated in tumor cell lines, is expressed in human pancreatic carcinoma, but not in non-neoplastic pancreatic tissue, suggesting a role for TMSB10 in the carcinogenesis of pancreatic carcinoma. Using gene expression profiling of pancreatic cell lines we were able to identify genes differentially expressed in pancreatic adenocarcinoma, which might contribute to pancreatic cancer development. Copyright 2005 S. Karger AG, Basel.

  2. Random forests-based differential analysis of gene sets for gene expression data.

    PubMed

    Hsueh, Huey-Miin; Zhou, Da-Wei; Tsai, Chen-An

    2013-04-10

    In DNA microarray studies, gene-set analysis (GSA) has become the focus of gene expression data analysis. GSA utilizes the gene expression profiles of functionally related gene sets in Gene Ontology (GO) categories or priori-defined biological classes to assess the significance of gene sets associated with clinical outcomes or phenotypes. Many statistical approaches have been proposed to determine whether such functionally related gene sets express differentially (enrichment and/or deletion) in variations of phenotypes. However, little attention has been given to the discriminatory power of gene sets and classification of patients. In this study, we propose a method of gene set analysis, in which gene sets are used to develop classifications of patients based on the Random Forest (RF) algorithm. The corresponding empirical p-value of an observed out-of-bag (OOB) error rate of the classifier is introduced to identify differentially expressed gene sets using an adequate resampling method. In addition, we discuss the impacts and correlations of genes within each gene set based on the measures of variable importance in the RF algorithm. Significant classifications are reported and visualized together with the underlying gene sets and their contribution to the phenotypes of interest. Numerical studies using both synthesized data and a series of publicly available gene expression data sets are conducted to evaluate the performance of the proposed methods. Compared with other hypothesis testing approaches, our proposed methods are reliable and successful in identifying enriched gene sets and in discovering the contributions of genes within a gene set. The classification results of identified gene sets can provide an valuable alternative to gene set testing to reveal the unknown, biologically relevant classes of samples or patients. In summary, our proposed method allows one to simultaneously assess the discriminatory ability of gene sets and the importance of genes for

  3. 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

  4. Perspectives: Gene Expression in Fisheries Management

    USGS Publications Warehouse

    Nielsen, Jennifer L.; Pavey, Scott A.

    2010-01-01

    Functional genes and gene expression have been connected to physiological traits linked to effective production and broodstock selection in aquaculture, selective implications of commercial fish harvest, and adaptive changes reflected in non-commercial fish populations subject to human disturbance and climate change. Gene mapping using single nucleotide polymorphisms (SNPs) to identify functional genes, gene expression (analogue microarrays and real-time PCR), and digital sequencing technologies looking at RNA transcripts present new concepts and opportunities in support of effective and sustainable fisheries. Genomic tools have been rapidly growing in aquaculture research addressing aspects of fish health, toxicology, and early development. Genomic technologies linking effects in functional genes involved in growth, maturation and life history development have been tied to selection resulting from harvest practices. Incorporating new and ever-increasing knowledge of fish genomes is opening a different perspective on local adaptation that will prove invaluable in wild fish conservation and management. Conservation of fish stocks is rapidly incorporating research on critical adaptive responses directed at the effects of human disturbance and climate change through gene expression studies. Genomic studies of fish populations can be generally grouped into three broad categories: 1) evolutionary genomics and biodiversity; 2) adaptive physiological responses to a changing environment; and 3) adaptive behavioral genomics and life history diversity. We review current genomic research in fisheries focusing on those that use microarrays to explore differences in gene expression among phenotypes and within or across populations, information that is critically important to the conservation of fish and their relationship to humans.

  5. Reference gene selection for normalization of RT-qPCR gene expression data from Actinidia deliciosa leaves infected with Pseudomonas syringae pv. actinidiae

    PubMed Central

    Petriccione, Milena; Mastrobuoni, Francesco; Zampella, Luigi; Scortichini, Marco

    2015-01-01

    Normalization of data, by choosing the appropriate reference genes (RGs), is fundamental for obtaining reliable results in reverse transcription-quantitative PCR (RT-qPCR). In this study, we assessed Actinidia deliciosa leaves inoculated with two doses of Pseudomonas syringae pv. actinidiae during a period of 13 days for the expression profile of nine candidate RGs. Their expression stability was calculated using four algorithms: geNorm, NormFinder, BestKeeper and the deltaCt method. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and protein phosphatase 2A (PP2A) were the most stable genes, while β-tubulin and 7s-globulin were the less stable. Expression analysis of three target genes, chosen for RGs validation, encoding the reactive oxygen species scavenging enzymes ascorbate peroxidase (APX), superoxide dismutase (SOD) and catalase (CAT) indicated that a combination of stable RGs, such as GAPDH and PP2A, can lead to an accurate quantification of the expression levels of such target genes. The APX level varied during the experiment time course and according to the inoculum doses, whereas both SOD and CAT resulted down-regulated during the first four days, and up-regulated afterwards, irrespective of inoculum dose. These results can be useful for better elucidating the molecular interaction in the A. deliciosa/P. s. pv. actinidiae pathosystem and for RGs selection in bacteria-plant pathosystems. PMID:26581656

  6. Identification of Reference Genes in Human Myelomonocytic Cells for Gene Expression Studies in Altered Gravity

    PubMed Central

    Thiel, Cora S.; Hauschild, Swantje; Tauber, Svantje; Paulsen, Katrin; Raig, Christiane; Raem, Arnold; Biskup, Josefine; Gutewort, Annett; Hürlimann, Eva; Philpot, Claudia; Lier, Hartwin; Engelmann, Frank; Layer, Liliana E.

    2015-01-01

    Gene expression studies are indispensable for investigation and elucidation of molecular mechanisms. For the process of normalization, reference genes (“housekeeping genes”) are essential to verify gene expression analysis. Thus, it is assumed that these reference genes demonstrate similar expression levels over all experimental conditions. However, common recommendations about reference genes were established during 1 g conditions and therefore their applicability in studies with altered gravity has not been demonstrated yet. The microarray technology is frequently used to generate expression profiles under defined conditions and to determine the relative difference in expression levels between two or more different states. In our study, we searched for potential reference genes with stable expression during different gravitational conditions (microgravity, normogravity, and hypergravity) which are additionally not altered in different hardware systems. We were able to identify eight genes (ALB, B4GALT6, GAPDH, HMBS, YWHAZ, ABCA5, ABCA9, and ABCC1) which demonstrated no altered gene expression levels in all tested conditions and therefore represent good candidates for the standardization of gene expression studies in altered gravity. PMID:25654098

  7. 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

  8. 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.

  9. Identification and validation of reference genes for normalization of gene expression analysis using qRT-PCR in Helicoverpa armigera (Lepidoptera: Noctuidae).

    PubMed

    Zhang, Songdou; An, Shiheng; Li, Zhen; Wu, Fengming; Yang, Qingpo; Liu, Yichen; Cao, Jinjun; Zhang, Huaijiang; Zhang, Qingwen; Liu, Xiaoxia

    2015-01-25

    Recent studies have focused on determining functional genes and microRNAs in the pest Helicoverpa armigera (Lepidoptera: Noctuidae). Most of these studies used quantitative real-time PCR (qRT-PCR). Suitable reference genes are necessary to normalize gene expression data of qRT-PCR. However, a comprehensive study on the reference genes in H. armigera remains lacking. Twelve candidate reference genes of H. armigera were selected and evaluated for their expression stability under different biotic and abiotic conditions. The comprehensive stability ranking of candidate reference genes was recommended by RefFinder and the optimal number of reference genes was calculated by geNorm. Two target genes, thioredoxin (TRX) and Cu/Zn superoxide dismutase (SOD), were used to validate the selection of reference genes. Results showed that the most suitable candidate combinations of reference genes were as follows: 28S and RPS15 for developmental stages; RPS15 and RPL13 for larvae tissues; EF and RPL27 for adult tissues; GAPDH, RPL27, and β-TUB for nuclear polyhedrosis virus infection; RPS15 and RPL32 for insecticide treatment; RPS15 and RPL27 for temperature treatment; and RPL32, RPS15, and RPL27 for all samples. This study not only establishes an accurate method for normalizing qRT-PCR data in H. armigera but also serve as a reference for further study on gene transcription in H. armigera and other insects. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities

    PubMed Central

    Fang, Xin; Sastry, Anand; Mih, Nathan; Kim, Donghyuk; Tan, Justin; Lloyd, Colton J.; Gao, Ye; Yang, Laurence; Palsson, Bernhard O.

    2017-01-01

    Transcriptional regulatory networks (TRNs) have been studied intensely for >25 y. Yet, even for the Escherichia coli TRN—probably the best characterized TRN—several questions remain. Here, we address three questions: (i) How complete is our knowledge of the E. coli TRN; (ii) how well can we predict gene expression using this TRN; and (iii) how robust is our understanding of the TRN? First, we reconstructed a high-confidence TRN (hiTRN) consisting of 147 transcription factors (TFs) regulating 1,538 transcription units (TUs) encoding 1,764 genes. The 3,797 high-confidence regulatory interactions were collected from published, validated chromatin immunoprecipitation (ChIP) data and RegulonDB. For 21 different TF knockouts, up to 63% of the differentially expressed genes in the hiTRN were traced to the knocked-out TF through regulatory cascades. Second, we trained supervised machine learning algorithms to predict the expression of 1,364 TUs given TF activities using 441 samples. The algorithms accurately predicted condition-specific expression for 86% (1,174 of 1,364) of the TUs, while 193 TUs (14%) were predicted better than random TRNs. Third, we identified 10 regulatory modules whose definitions were robust against changes to the TRN or expression compendium. Using surrogate variable analysis, we also identified three unmodeled factors that systematically influenced gene expression. Our computational workflow comprehensively characterizes the predictive capabilities and systems-level functions of an organism’s TRN from disparate data types. PMID:28874552

  11. Discovering causal signaling pathways through gene-expression patterns

    PubMed Central

    Parikh, Jignesh R.; Klinger, Bertram; Xia, Yu; Marto, Jarrod A.; Blüthgen, Nils

    2010-01-01

    High-throughput gene-expression studies result in lists of differentially expressed genes. Most current meta-analyses of these gene lists include searching for significant membership of the translated proteins in various signaling pathways. However, such membership enrichment algorithms do not provide insight into which pathways caused the genes to be differentially expressed in the first place. Here, we present an intuitive approach for discovering upstream signaling pathways responsible for regulating these differentially expressed genes. We identify consistently regulated signature genes specific for signal transduction pathways from a panel of single-pathway perturbation experiments. An algorithm that detects overrepresentation of these signature genes in a gene group of interest is used to infer the signaling pathway responsible for regulation. We expose our novel resource and algorithm through a web server called SPEED: Signaling Pathway Enrichment using Experimental Data sets. SPEED can be freely accessed at http://speed.sys-bio.net/. PMID:20494976

  12. Validation of reference genes for normalization of qPCR gene expression data from Coffea spp. hypocotyls inoculated with Colletotrichum kahawae

    PubMed Central

    2013-01-01

    Background Coffee production in Africa represents a significant share of the total export revenues and influences the lives of millions of people, yet severe socio-economic repercussions are annually felt in result of the overall losses caused by the coffee berry disease (CBD). This quarantine disease is caused by the fungus Colletotrichum kahawae Waller and Bridge, which remains one of the most devastating threats to Coffea arabica production in Africa at high altitude, and its dispersal to Latin America and Asia represents a serious concern. Understanding the molecular genetic basis of coffee resistance to this disease is of high priority to support breeding strategies. Selection and validation of suitable reference genes presenting stable expression in the system studied is the first step to engage studies of gene expression profiling. Results In this study, a set of ten genes (S24, 14-3-3, RPL7, GAPDH, UBQ9, VATP16, SAND, UQCC, IDE and β-Tub9) was evaluated to identify reference genes during the first hours of interaction (12, 48 and 72 hpi) between resistant and susceptible coffee genotypes and C. kahawae. Three analyses were done for the selection of these genes considering the entire dataset and the two genotypes (resistant and susceptible), separately. The three statistical methods applied GeNorm, NormFinder, and BestKeeper, allowed identifying IDE as one of the most stable genes for all datasets analysed, and in contrast GADPH and UBQ9 as the least stable ones. In addition, the expression of two defense-related transcripts, encoding for a receptor like kinase and a pathogenesis related protein 10, were used to validate the reference genes selected. Conclusion Taken together, our results provide guidelines for reference gene(s) selection towards a more accurate and widespread use of qPCR to study the interaction between Coffea spp. and C. kahawae. PMID:24073624

  13. Systematic identification of human housekeeping genes possibly useful as references in gene expression studies.

    PubMed

    Caracausi, Maria; Piovesan, Allison; Antonaros, Francesca; Strippoli, Pierluigi; Vitale, Lorenza; Pelleri, Maria Chiara

    2017-09-01

    The ideal reference, or control, gene for the study of gene expression in a given organism should be expressed at a medium‑high level for easy detection, should be expressed at a constant/stable level throughout different cell types and within the same cell type undergoing different treatments, and should maintain these features through as many different tissues of the organism. From a biological point of view, these theoretical requirements of an ideal reference gene appear to be best suited to housekeeping (HK) genes. Recent advancements in the quality and completeness of human expression microarray data and in their statistical analysis may provide new clues toward the quantitative standardization of human gene expression studies in biology and medicine, both cross‑ and within‑tissue. The systematic approach used by the present study is based on the Transcriptome Mapper tool and exploits the automated reassignment of probes to corresponding genes, intra‑ and inter‑sample normalization, elaboration and representation of gene expression values in linear form within an indexed and searchable database with a graphical interface recording quantitative levels of expression, expression variability and cross‑tissue width of expression for more than 31,000 transcripts. The present study conducted a meta‑analysis of a pool of 646 expression profile data sets from 54 different human tissues and identified actin γ 1 as the HK gene that best fits the combination of all the traditional criteria to be used as a reference gene for general use; two ribosomal protein genes, RPS18 and RPS27, and one aquaporin gene, POM121 transmembrane nucleporin C, were also identified. The present study provided a list of tissue‑ and organ‑specific genes that may be most suited for the following individual tissues/organs: Adipose tissue, bone marrow, brain, heart, kidney, liver, lung, ovary, skeletal muscle and testis; and also provides in these cases a representative

  14. The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data.

    PubMed

    Mansourian, Robert; Mutch, David M; Antille, Nicolas; Aubert, Jerome; Fogel, Paul; Le Goff, Jean-Marc; Moulin, Julie; Petrov, Anton; Rytz, Andreas; Voegel, Johannes J; Roberts, Matthew-Alan

    2004-11-01

    Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. The GEA code for R

  15. Carcinogen-induced trans activation of gene expression.

    PubMed Central

    Kleinberger, T; Flint, Y B; Blank, M; Etkin, S; Lavi, S

    1988-01-01

    We report a new mechanism of carcinogen action by which the expression of several genes was concomitantly enhanced. This mechanism involved the altered activity of cellular factors which modulate the expression of genes under their control. The increased expression was regulated at least in part on the transcriptional level and did not require amplification of the overexpressed genes. This phenomenon was transient; it was apparent as early as 24 h after carcinogen treatment and declined a few days later. Images PMID:2835673

  16. Clustering Algorithms: Their Application to Gene Expression Data

    PubMed Central

    Oyelade, Jelili; Isewon, Itunuoluwa; Oladipupo, Funke; Aromolaran, Olufemi; Uwoghiren, Efosa; Ameh, Faridah; Achas, Moses; Adebiyi, Ezekiel

    2016-01-01

    Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure. PMID:27932867

  17. 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

  18. Hepatic Xenobiotic Metabolizing Enzyme Gene Expression ...

    EPA Pesticide Factsheets

    BACKGROUND: Differences in responses to environmental chemicals and drugs between life stages are likely due in part to differences in the expression of xenobiotic metabolizing enzymes and transporters (XMETs). No comprehensive analysis of the mRNA expression of XMETs has been carried out through life stages in any species. RESULTS: Using full-genome arrays, the mRNA expression of all XMETs and their regulatory proteins was examined during fetal (gestation day (GD) 19), neonatal (postnatal day (PND) 7), prepubescent (PND32), middle age (12 months), and old age (18 and 24 months) in the C57BL/6J (C57) mouse liver and compared to adults. Fetal and neonatal life stages exhibited dramatic differences in XMET mRNA expression compared to the relatively minor effects of old age. The total number of XMET probe sets that differed from adults was 636, 500, 84, 5, 43, and 102 for GD19, PND7, PND32, 12 months, 18 months and 24 months, respectively. At all life stages except PND32, under-expressed genes outnumbered over-expressed genes. The altered XMETs included those in all of the major metabolic and transport phases including introduction of reactive or polar groups (Phase I), conjugation (Phase II) and excretion (Phase III). In the fetus and neonate, parallel increases in expression were noted in the dioxin receptor, Nrf2 components and their regulated genes while nuclear receptors and regulated genes were generally down-regulated. Suppression of male-specific XMETs w

  19. Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data.

    PubMed

    Tintle, Nathan L; Sitarik, Alexandra; Boerema, Benjamin; Young, Kylie; Best, Aaron A; Dejongh, Matthew

    2012-08-08

    Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

  20. Plasticity-Related Gene Expression During Eszopiclone-Induced Sleep.

    PubMed

    Gerashchenko, Dmitry; Pasumarthi, Ravi K; Kilduff, Thomas S

    2017-07-01

    Experimental evidence suggests that restorative processes depend on synaptic plasticity changes in the brain during sleep. We used the expression of plasticity-related genes to assess synaptic plasticity changes during drug-induced sleep. We first characterized sleep induced by eszopiclone in mice during baseline conditions and during the recovery from sleep deprivation. We then compared the expression of 18 genes and two miRNAs critically involved in synaptic plasticity in these mice. Gene expression was assessed in the cerebral cortex and hippocampus by the TaqMan reverse transcription polymerase chain reaction and correlated with sleep parameters. Eszopiclone reduced the latency to nonrapid eye movement (NREM) sleep and increased NREM sleep amounts. Eszopiclone had no effect on slow wave activity (SWA) during baseline conditions but reduced the SWA increase during recovery sleep (RS) after sleep deprivation. Gene expression analyses revealed three distinct patterns: (1) four genes had higher expression either in the cortex or hippocampus in the group of mice with increased amounts of wakefulness; (2) a large proportion of plasticity-related genes (7 out of 18 genes) had higher expression during RS in the cortex but not in the hippocampus; and (3) six genes and the two miRNAs showed no significant changes across conditions. Even at a relatively high dose (20 mg/kg), eszopiclone did not reduce the expression of plasticity-related genes during RS period in the cortex. These results indicate that gene expression associated with synaptic plasticity occurs in the cortex in the presence of a hypnotic medication. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

  1. Dual Luciferase Assay System for Rapid Assessment of Gene Expression in Saccharomyces cerevisiae

    PubMed Central

    McNabb, David S.; Reed, Robin; Marciniak, Robert A.

    2005-01-01

    A new reporter system has been developed for quantifying gene expression in the yeast Saccharomyces cerevisiae. The system relies on two different reporter genes, Renilla and firefly luciferase, to evaluate regulated gene expression. The gene encoding Renilla luciferase is fused to a constitutive promoter (PGK1 or SPT15) and integrated into the yeast genome at the CAN1 locus as a control for normalizing the assay. The firefly luciferase gene is fused to the test promoter and integrated into the yeast genome at the ura3 or leu2 locus. The dual luciferase assay is performed by sequentially measuring the firefly and Renilla luciferase activities of the same sample, with the results expressed as the ratio of firefly to Renilla luciferase activity (Fluc/Rluc). The yeast dual luciferase reporter (DLR) was characterized and shown to be very efficient, requiring approximately 1 minute to complete each assay, and has proven to yield data that accurately and reproducibly reflect promoter activity. A series of integrating plasmids were generated that contain either the firefly or Renilla luciferase gene preceded by a multicloning region in two different orientations and the three reading frames to make possible the generation of translational fusions. Additionally, each set of plasmids contains either the URA3 or LEU2 marker for genetic selection in yeast. A series of S288C-based yeast strains, including a two-hybrid strain, were developed to facilitate the use of the yeast DLR assay. This assay can be readily adapted to a high-throughput platform for studies requiring numerous measurements. PMID:16151247

  2. Chamber Specific Gene Expression Landscape of the Zebrafish Heart

    PubMed Central

    Singh, Angom Ramcharan; Sivadas, Ambily; Sabharwal, Ankit; Vellarikal, Shamsudheen Karuthedath; Jayarajan, Rijith; Verma, Ankit; Kapoor, Shruti; Joshi, Adita; Scaria, Vinod; Sivasubbu, Sridhar

    2016-01-01

    The organization of structure and function of cardiac chambers in vertebrates is defined by chamber-specific distinct gene expression. This peculiarity and uniqueness of the genetic signatures demonstrates functional resolution attributed to the different chambers of the heart. Altered expression of the cardiac chamber genes can lead to individual chamber related dysfunctions and disease patho-physiologies. Information on transcriptional repertoire of cardiac compartments is important to understand the spectrum of chamber specific anomalies. We have carried out a genome wide transcriptome profiling study of the three cardiac chambers in the zebrafish heart using RNA sequencing. We have captured the gene expression patterns of 13,396 protein coding genes in the three cardiac chambers—atrium, ventricle and bulbus arteriosus. Of these, 7,260 known protein coding genes are highly expressed (≥10 FPKM) in the zebrafish heart. Thus, this study represents nearly an all-inclusive information on the zebrafish cardiac transcriptome. In this study, a total of 96 differentially expressed genes across the three cardiac chambers in zebrafish were identified. The atrium, ventricle and bulbus arteriosus displayed 20, 32 and 44 uniquely expressing genes respectively. We validated the expression of predicted chamber-restricted genes using independent semi-quantitative and qualitative experimental techniques. In addition, we identified 23 putative novel protein coding genes that are specifically restricted to the ventricle and not in the atrium or bulbus arteriosus. In our knowledge, these 23 novel genes have either not been investigated in detail or are sparsely studied. The transcriptome identified in this study includes 68 differentially expressing zebrafish cardiac chamber genes that have a human ortholog. We also carried out spatiotemporal gene expression profiling of the 96 differentially expressed genes throughout the three cardiac chambers in 11 developmental stages and 6

  3. Analytical workflow profiling gene expression in murine macrophages

    PubMed Central

    Nixon, Scott E.; González-Peña, Dianelys; Lawson, Marcus A.; McCusker, Robert H.; Hernandez, Alvaro G.; O’Connor, Jason C.; Dantzer, Robert; Kelley, Keith W.

    2015-01-01

    Comprehensive and simultaneous analysis of all genes in a biological sample is a capability of RNA-Seq technology. Analysis of the entire transcriptome benefits from summarization of genes at the functional level. As a cellular response of interest not previously explored with RNA-Seq, peritoneal macrophages from mice under two conditions (control and immunologically challenged) were analyzed for gene expression differences. Quantification of individual transcripts modeled RNA-Seq read distribution and uncertainty (using a Beta Negative Binomial distribution), then tested for differential transcript expression (False Discovery Rate-adjusted p-value < 0.05). Enrichment of functional categories utilized the list of differentially expressed genes. A total of 2079 differentially expressed transcripts representing 1884 genes were detected. Enrichment of 92 categories from Gene Ontology Biological Processes and Molecular Functions, and KEGG pathways were grouped into 6 clusters. Clusters included defense and inflammatory response (Enrichment Score = 11.24) and ribosomal activity (Enrichment Score = 17.89). Our work provides a context to the fine detail of individual gene expression differences in murine peritoneal macrophages during immunological challenge with high throughput RNA-Seq. PMID:25708305

  4. Geometric Morphometrics on Gene Expression Patterns Within Phenotypes: A Case Example on Limb Development

    PubMed Central

    Martínez-Abadías, Neus; Mateu, Roger; Niksic, Martina; Russo, Lucia; Sharpe, James

    2016-01-01

    How the genotype translates into the phenotype through development is critical to fully understand the evolution of phenotypes. We propose a novel approach to directly assess how changes in gene expression patterns are associated with changes in morphology using the limb as a case example. Our method combines molecular biology techniques, such as whole-mount in situ hybridization, with image and shape analysis, extending the use of Geometric Morphometrics to the analysis of nonanatomical shapes, such as gene expression domains. Elliptical Fourier and Procrustes-based semilandmark analyses were used to analyze the variation and covariation patterns of the limb bud shape with the expression patterns of two relevant genes for limb morphogenesis, Hoxa11 and Hoxa13. We devised a multiple thresholding method to semiautomatically segment gene domains at several expression levels in large samples of limb buds from C57Bl6 mouse embryos between 10 and 12 postfertilization days. Besides providing an accurate phenotyping tool to quantify the spatiotemporal dynamics of gene expression patterns within developing structures, our morphometric analyses revealed high, non-random, and gene-specific variation undergoing canalization during limb development. Our results demonstrate that Hoxa11 and Hoxa13, despite being paralogs with analogous functions in limb patterning, show clearly distinct dynamic patterns, both in shape and size, and are associated differently with the limb bud shape. The correspondence between our results and already well-established molecular processes underlying limb development confirms that this morphometric approach is a powerful tool to extract features of development regulating morphogenesis. Such multilevel analyses are promising in systems where not so much molecular information is available and will advance our understanding of the genotype–phenotype map. In systematics, this knowledge will increase our ability to infer how evolution modified a common

  5. Differential co-expression analysis of a microarray gene expression profiles of pulmonary adenocarcinoma.

    PubMed

    Fu, Shijie; Pan, Xufeng; Fang, Wentao

    2014-08-01

    Lung cancer severely reduces the quality of life worldwide and causes high socioeconomic burdens. However, key genes leading to the generation of pulmonary adenocarcinoma remain elusive despite intensive research efforts. The present study aimed to identify the potential associations between transcription factors (TFs) and differentially co‑expressed genes (DCGs) in the regulation of transcription in pulmonary adenocarcinoma. Gene expression profiles of pulmonary adenocarcinoma were downloaded from the Gene Expression Omnibus, and gene expression was analyzed using a computational method. A total of 37,094 differentially co‑expressed links (DCLs) and 251 DCGs were identified, which were significantly enriched in 10 pathways. The construction of the regulatory network and the analysis of the regulatory impact factors revealed eight crucial TFs in the regulatory network. These TFs regulated the expression of DCGs by promoting or inhibiting their expression. In addition, certain TFs and target genes associated with DCGs did not appear in the DCLs, which indicated that those TFs could be synergistic with other factors. This is likely to provide novel insights for research into pulmonary adenocarcinoma. In conclusion, the present study may enhance the understanding of disease mechanisms and lead to an improved diagnosis of lung cancer. However, further studies are required to confirm these observations.

  6. 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

  7. The Gene Expression Omnibus Database.

    PubMed

    Clough, Emily; Barrett, Tanya

    2016-01-01

    The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.

  8. The Gene Expression Omnibus database

    PubMed Central

    Clough, Emily; Barrett, Tanya

    2016-01-01

    The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

  9. Using RNA-seq data to select reference genes for normalizing gene expression in apple roots.

    PubMed

    Zhou, Zhe; Cong, Peihua; Tian, Yi; Zhu, Yanmin

    2017-01-01

    Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for their potential use as reliable reference genes. These genes were selected based on their low variance of gene expression in apple root tissues from a recent RNA-seq data set, and a few previously reported apple reference genes for other tissue types. Four methods, Delta Ct, geNorm, NormFinder and BestKeeper, were used to evaluate their stability in apple root tissues of various genotypes and under different experimental conditions. A small panel of stably expressed genes, MDP0000095375, MDP0000147424, MDP0000233640, MDP0000326399 and MDP0000173025 were recommended for normalizing quantitative gene expression data in apple roots under various abiotic or biotic stresses. When the most stable and least stable reference genes were used for data normalization, significant differences were observed on the expression patterns of two target genes, MdLecRLK5 (MDP0000228426, a gene encoding a lectin receptor like kinase) and MdMAPK3 (MDP0000187103, a gene encoding a mitogen-activated protein kinase). Our data also indicated that for those carefully validated reference genes, a single reference gene is sufficient for reliable normalization of the quantitative gene expression. Depending on the experimental conditions, the most suitable reference genes can be specific to the sample of interest for more reliable RT-qPCR data normalization.

  10. Using RNA-seq data to select reference genes for normalizing gene expression in apple roots

    PubMed Central

    Zhou, Zhe; Cong, Peihua; Tian, Yi

    2017-01-01

    Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for their potential use as reliable reference genes. These genes were selected based on their low variance of gene expression in apple root tissues from a recent RNA-seq data set, and a few previously reported apple reference genes for other tissue types. Four methods, Delta Ct, geNorm, NormFinder and BestKeeper, were used to evaluate their stability in apple root tissues of various genotypes and under different experimental conditions. A small panel of stably expressed genes, MDP0000095375, MDP0000147424, MDP0000233640, MDP0000326399 and MDP0000173025 were recommended for normalizing quantitative gene expression data in apple roots under various abiotic or biotic stresses. When the most stable and least stable reference genes were used for data normalization, significant differences were observed on the expression patterns of two target genes, MdLecRLK5 (MDP0000228426, a gene encoding a lectin receptor like kinase) and MdMAPK3 (MDP0000187103, a gene encoding a mitogen-activated protein kinase). Our data also indicated that for those carefully validated reference genes, a single reference gene is sufficient for reliable normalization of the quantitative gene expression. Depending on the experimental conditions, the most suitable reference genes can be specific to the sample of interest for more reliable RT-qPCR data normalization. PMID:28934340

  11. Regulated Expression of Adenoviral Vectors-Based Gene Therapies

    PubMed Central

    Curtin, James F.; Candolfi, Marianela; Puntel, Mariana; Xiong, Weidong; Muhammad, A. K. M.; Kroeger, Kurt; Mondkar, Sonali; Liu, Chunyan; Bondale, Niyati; Lowenstein, Pedro R.; Castro, Maria G.

    2008-01-01

    Summary Regulatable promoter systems allow gene expression to be tightly controlled in vivo. This is highly desirable for the development of safe, efficacious adenoviral vectors that can be used to treat human diseases in the clinic. Ideally, regulatable cassettes should have minimal gene expression in the “OFF” state, and expression should quickly reach therapeutic levels in the “ON” state. In addition, the components of regulatable cassettes should be non-toxic at physiological concentrations and should not be immunogenic, especially when treating chronic illness that requires long-lasting gene expression. In this chapter, we will describe in detail protocols to develop and validate first generation (Ad) and high-capacity adenoviral (HC-Ad) vectors that express therapeutic genes under the control of the TetON regulatable system. Our laboratory has successfully used these protocols to regulate the expression of marker genes, immune stimulatory genes, and toxins for cancer gene therapeutics, i.e., glioma that is a deadly form of brain cancer. We have shown that this third generation TetON regulatable system, incorporating a doxycycline (DOX)-sensitive rtTA2S-M2 inducer and tTSKid silencer, is non-toxic, relatively non-immunogenic, and can tightly regulate reporter transgene expression downstream of a TRE promoter from adenoviral vectors in vitro and also in vivo. PMID:18470649

  12. Identification and validation of reference genes for quantification of target gene expression with quantitative real-time PCR for tall fescue under four abiotic stresses.

    PubMed

    Yang, Zhimin; Chen, Yu; Hu, Baoyun; Tan, Zhiqun; Huang, Bingru

    2015-01-01

    Tall fescue (Festuca arundinacea Schreb.) is widely utilized as a major forage and turfgrass species in the temperate regions of the world and is a valuable plant material for studying molecular mechanisms of grass stress tolerance due to its superior drought and heat tolerance among cool-season species. Selection of suitable reference genes for quantification of target gene expression is important for the discovery of molecular mechanisms underlying improved growth traits and stress tolerance. The stability of nine potential reference genes (ACT, TUB, EF1a, GAPDH, SAND, CACS, F-box, PEPKR1 and TIP41) was evaluated using four programs, GeNorm, NormFinder, BestKeeper, and RefFinder. The combinations of SAND and TUB or TIP41 and TUB were most stably expressed in salt-treated roots or leaves. The combinations of GAPDH with TIP41 or TUB were stable in roots and leaves under drought stress. TIP41 and PEPKR1 exhibited stable expression in cold-treated roots, and the combination of F-box, TIP41 and TUB was also stable in cold-treated leaves. CACS and TUB were the two most stable reference genes in heat-stressed roots. TIP41 combined with TUB and ACT was stably expressed in heat-stressed leaves. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) assays of the target gene FaWRKY1 using the identified most stable reference genes confirmed the reliability of selected reference genes. The selection of suitable reference genes in tall fescue will allow for more accurate identification of stress-tolerance genes and molecular mechanisms conferring stress tolerance in this stress-tolerant species.

  13. Targeting gene expression selectively in cancer cells by using the progression-elevated gene-3 promoter.

    PubMed

    Su, Zhao-Zhong; Sarkar, Devanand; Emdad, Luni; Duigou, Gregory J; Young, Charles S H; Ware, Joy; Randolph, Aaron; Valerie, Kristoffer; Fisher, Paul B

    2005-01-25

    One impediment to effective cancer-specific gene therapy is the rarity of regulatory sequences targeting gene expression selectively in tumor cells. Although many tissue-specific promoters are recognized, few cancer-selective gene promoters are available. Progression-elevated gene-3 (PEG-3) is a rodent gene identified by subtraction hybridization that displays elevated expression as a function of transformation by diversely acting oncogenes, DNA damage, and cancer cell progression. The promoter of PEG-3, PEG-Prom, displays robust expression in a broad spectrum of human cancer cell lines with marginal expression in normal cellular counterparts. Whereas GFP expression, when under the control of a CMV promoter, is detected in both normal and cancer cells, when GFP is expressed under the control of the PEG-Prom, cancer-selective expression is evident. Mutational analysis identifies the AP-1 and PEA-3 transcription factors as primary mediators of selective, cancer-specific expression of the PEG-Prom. Synthesis of apoptosis-inducing genes, under the control of the CMV promoter, inhibits the growth of both normal and cancer cells, whereas PEG-Prom-mediated expression of these genes kills only cancer cells and spares normal cells. The efficacy of the PEG-Prom as part of a cancer gene therapeutic regimen is further documented by in vivo experiments in which PEG-Prom-controlled expression of an apoptosis-inducing gene completely inhibited prostate cancer xenograft growth in nude mice. These compelling observations indicate that the PEG-Prom, with its cancer-specific expression, provides a means of selectively delivering genes to cancer cells, thereby providing a crucial component in developing effective cancer gene therapies.

  14. Covariance Structure Models for Gene Expression Microarray Data

    ERIC Educational Resources Information Center

    Xie, Jun; Bentler, Peter M.

    2003-01-01

    Covariance structure models are applied to gene expression data using a factor model, a path model, and their combination. The factor model is based on a few factors that capture most of the expression information. A common factor of a group of genes may represent a common protein factor for the transcript of the co-expressed genes, and hence, it…

  15. Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

    PubMed

    Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

    2017-08-01

    This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

  16. Genetic effects on gene expression across human tissues

    PubMed Central

    2017-01-01

    Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease. PMID:29022597

  17. Genetic effects on gene expression across human tissues.

    PubMed

    Battle, Alexis; Brown, Christopher D; Engelhardt, Barbara E; Montgomery, Stephen B

    2017-10-11

    Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

  18. 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

  19. 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

  20. Sex-Biased Gene Expression and Sexual Conflict throughout Development

    PubMed Central

    Ingleby, Fiona C.; Flis, Ilona; Morrow, Edward H.

    2015-01-01

    Sex-biased gene expression is likely to account for most sexually dimorphic traits because males and females share much of their genome. When fitness optima differ between sexes for a shared trait, sexual dimorphism can allow each sex to express their optimum trait phenotype, and in this way, the evolution of sex-biased gene expression is one mechanism that could help to resolve intralocus sexual conflict. Genome-wide patterns of sex-biased gene expression have been identified in a number of studies, which we review here. However, very little is known about how sex-biased gene expression relates to sex-specific fitness and about how sex-biased gene expression and conflict vary throughout development or across different genotypes, populations, and environments. We discuss the importance of these neglected areas of research and use data from a small-scale experiment on sex-specific expression of genes throughout development to highlight potentially interesting avenues for future research. PMID:25376837

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

    PubMed

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

    2017-04-12

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

  2. Identification of differentially expressed genes in flax (Linum usitatissimum L.) under saline-alkaline stress by digital gene expression.

    PubMed

    Yu, Ying; Huang, Wengong; Chen, Hongyu; Wu, Guangwen; Yuan, Hongmei; Song, Xixia; Kang, Qinghua; Zhao, Dongsheng; Jiang, Weidong; Liu, Yan; Wu, Jianzhong; Cheng, Lili; Yao, Yubo; Guan, Fengzhi

    2014-10-01

    The salinization and alkalization of soil are widespread environmental problems, and alkaline salt stress is more destructive than neutral salt stress. Therefore, understanding the mechanism of plant tolerance to saline-alkaline stress has become a major challenge. However, little attention has been paid to the mechanism of plant alkaline salt tolerance. In this study, gene expression profiling of flax was analyzed under alkaline-salt stress (AS2), neutral salt stress (NSS) and alkaline stress (AS) by digital gene expression. Three-week-old flax seedlings were placed in 25 mM Na2CO3 (pH11.6) (AS2), 50mM NaCl (NSS) and NaOH (pH11.6) (AS) for 18 h. There were 7736, 1566 and 454 differentially expressed genes in AS2, NSS and AS compared to CK, respectively. The GO category gene enrichment analysis revealed that photosynthesis was particularly affected in AS2, carbohydrate metabolism was particularly affected in NSS, and the response to biotic stimulus was particularly affected in AS. We also analyzed the expression pattern of five categories of genes including transcription factors, signaling transduction proteins, phytohormones, reactive oxygen species proteins and transporters under these three stresses. Some key regulatory gene families involved in abiotic stress, such as WRKY, MAPKKK, ABA, PrxR and ion channels, were differentially expressed. Compared with NSS and AS, AS2 triggered more differentially expressed genes and special pathways, indicating that the mechanism of AS2 was more complex than NSS and AS. To the best of our knowledge, this was the first transcriptome analysis of flax in response to saline-alkaline stress. These data indicate that common and diverse features of saline-alkaline stress provide novel insights into the molecular mechanisms of plant saline-alkaline tolerance and offer a number of candidate genes as potential markers of tolerance to saline-alkaline stress. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Genomics Analysis of Genes Expressed in Maize Endosperm Identifies Novel Seed Proteins and Clarifies Patterns of Zein Gene Expression

    PubMed Central

    Woo, Young-Min; Hu, David Wang-Nan; Larkins, Brian A.; Jung, Rudolf

    2001-01-01

    We analyzed cDNA libraries from developing endosperm of the B73 maize inbred line to evaluate the expression of storage protein genes. This study showed that zeins are by far the most highly expressed genes in the endosperm, but we found an inverse relationship between the number of zein genes and the relative amount of specific mRNAs. Although α-zeins are encoded by large multigene families, only a few of these genes are transcribed at high or detectable levels. In contrast, relatively small gene families encode the γ- and δ-zeins, and members of these gene families, especially the γ-zeins, are highly expressed. Knowledge of expressed storage protein genes allowed the development of DNA and antibody probes that distinguish between closely related gene family members. Using in situ hybridization, we found differences in the temporal and spatial expression of the α-, γ-, and δ-zein gene families, which provides evidence that γ-zeins are synthesized throughout the endosperm before α- and δ-zeins. This observation is consistent with earlier studies that suggested that γ-zeins play an important role in prolamin protein body assembly. Analysis of endosperm cDNAs also revealed several previously unidentified proteins, including a 50-kD γ-zein, an 18-kD α-globulin, and a legumin-related protein. Immunolocalization of the 50-kD γ-zein showed this protein to be located at the surface of prolamin-containing protein bodies, similar to other γ-zeins. The 18-kD α-globulin, however, is deposited in novel, vacuole-like organelles that were not described previously in maize endosperm. PMID:11595803

  4. Noise in gene expression is coupled to growth rate

    PubMed Central

    Keren, Leeat; van Dijk, David; Weingarten-Gabbay, Shira; Davidi, Dan; Jona, Ghil; Weinberger, Adina; Milo, Ron; Segal, Eran

    2015-01-01

    Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle–regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications. PMID:26355006

  5. Models of stochastic gene expression

    NASA Astrophysics Data System (ADS)

    Paulsson, Johan

    2005-06-01

    Gene expression is an inherently stochastic process: Genes are activated and inactivated by random association and dissociation events, transcription is typically rare, and many proteins are present in low numbers per cell. The last few years have seen an explosion in the stochastic modeling of these processes, predicting protein fluctuations in terms of the frequencies of the probabilistic events. Here I discuss commonalities between theoretical descriptions, focusing on a gene-mRNA-protein model that includes most published studies as special cases. I also show how expression bursts can be explained as simplistic time-averaging, and how generic approximations can allow for concrete interpretations without requiring concrete assumptions. Measures and nomenclature are discussed to some extent and the modeling literature is briefly reviewed.

  6. Imprinted gene expression in fetal growth and development.

    PubMed

    Lambertini, L; Marsit, C J; Sharma, P; Maccani, M; Ma, Y; Hu, J; Chen, J

    2012-06-01

    Experimental studies showed that genomic imprinting is fundamental in fetoplacental development by timely regulating the expression of the imprinted genes to overlook a set of events determining placenta implantation, growth and embryogenesis. We examined the expression profile of 22 imprinted genes which have been linked to pregnancy abnormalities that may ultimately influence childhood development. The study was conducted in a subset of 106 placenta samples, overrepresented with small and large for gestational age cases, from the Rhode Island Child Health Study. We investigated associations between imprinted gene expression and three fetal development parameters: newborn head circumference, birth weight, and size for gestational age. Results from our investigation show that the maternally imprinted/paternally expressed gene ZNF331 inversely associates with each parameter to drive smaller fetal size, while paternally imprinted/maternally expressed gene SLC22A18 directly associates with the newborn head circumference promoting growth. Multidimensional Scaling analysis revealed two clusters within the 22 imprinted genes which are independently associated with fetoplacental development. Our data suggest that cluster 1 genes work by assuring cell growth and tissue development, while cluster 2 genes act by coordinating these processes. Results from this epidemiologic study offer solid support for the key role of imprinting in fetoplacental development. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2011-02-01

    The gonadal soma-derived factor (GSDF) belongs to the transforming growth factor-β superfamily and is conserved in teleostean fish species. Gsdf is specifically expressed in the gonads, and gene expression is restricted to the granulosa and Sertoli cells in trout and medaka. The gsdf gene expression is correlated to early testis differentiation in medaka and was shown to stimulate primordial germ cell and spermatogonia proliferation in trout. In the present study, we show that the gsdf gene localizes to a syntenic chromosomal fragment conserved among vertebrates although no gsdf-related gene is detected on the corresponding genomic region in tetrapods. We demonstrate using quantitative RT-PCR that most of the genes localized in the synteny are specifically expressed in medaka gonads. Gsdf is the only gene of the synteny with a much higher expression in the testis compared to the ovary. In contrast, gene expression pattern analysis of the gsdf surrounding genes (nup54, aff1, klhl8, sdad1, and ptpn13) indicates that these genes are preferentially expressed in the female gonads. The tissue distribution of these genes is highly similar in medaka and zebrafish, two teleostean species that have diverged more than 110 million years ago. The cellular localization of these genes was determined in medaka gonads using the whole-mount in situ hybridization technique. We confirm that gsdf gene expression is restricted to Sertoli and granulosa cells in contact with the premeiotic and meiotic cells. The nup54 gene is expressed in spermatocytes and previtellogenic oocytes. Transcripts corresponding to the ovary-specific genes (aff1, klhl8, and sdad1) are detected only in previtellogenic oocytes. No expression was detected in the gonocytes in 10 dpf embryos. In conclusion, we show that the gsdf gene localizes to a syntenic chromosomal fragment harboring evolutionary conserved genes in vertebrates. These genes are preferentially expressed in previtelloogenic oocytes, and thus, they

  8. 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.

  9. 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.

  10. Gene expression profiling of human breast tissue samples using SAGE-Seq.

    PubMed

    Wu, Zhenhua Jeremy; Meyer, Clifford A; Choudhury, Sibgat; Shipitsin, Michail; Maruyama, Reo; Bessarabova, Marina; Nikolskaya, Tatiana; Sukumar, Saraswati; Schwartzman, Armin; Liu, Jun S; Polyak, Kornelia; Liu, X Shirley

    2010-12-01

    We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.

  11. Classification of early-stage non-small cell lung cancer by weighing gene expression profiles with connectivity information.

    PubMed

    Zhang, Ao; Tian, Suyan

    2018-05-01

    Pathway-based feature selection algorithms, which utilize biological information contained in pathways to guide which features/genes should be selected, have evolved quickly and become widespread in the field of bioinformatics. Based on how the pathway information is incorporated, we classify pathway-based feature selection algorithms into three major categories-penalty, stepwise forward, and weighting. Compared to the first two categories, the weighting methods have been underutilized even though they are usually the simplest ones. In this article, we constructed three different genes' connectivity information-based weights for each gene and then conducted feature selection upon the resulting weighted gene expression profiles. Using both simulations and a real-world application, we have demonstrated that when the data-driven connectivity information constructed from the data of specific disease under study is considered, the resulting weighted gene expression profiles slightly outperform the original expression profiles. In summary, a big challenge faced by the weighting method is how to estimate pathway knowledge-based weights more accurately and precisely. Only until the issue is conquered successfully will wide utilization of the weighting methods be impossible. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Global Expression Profiling in Atopic Eczema Reveals Reciprocal Expression of Inflammatory and Lipid Genes

    PubMed Central

    Sääf, Annika M.; Tengvall-Linder, Maria; Chang, Howard Y.; Adler, Adam S.; Wahlgren, Carl-Fredrik; Scheynius, Annika; Nordenskjöld, Magnus; Bradley, Maria

    2008-01-01

    Background Atopic eczema (AE) is a common chronic inflammatory skin disorder. In order to dissect the genetic background several linkage and genetic association studies have been performed. Yet very little is known about specific genes involved in this complex skin disease, and the underlying molecular mechanisms are not fully understood. Methodology/Findings We used human DNA microarrays to identify a molecular picture of the programmed responses of the human genome to AE. The transcriptional program was analyzed in skin biopsy samples from lesional and patch-tested skin from AE patients sensitized to Malassezia sympodialis (M. sympodialis), and corresponding biopsies from healthy individuals. The most notable feature of the global gene-expression pattern observed in AE skin was a reciprocal expression of induced inflammatory genes and repressed lipid metabolism genes. The overall transcriptional response in M. sympodialis patch-tested AE skin was similar to the gene-expression signature identified in lesional AE skin. In the constellation of genes differentially expressed in AE skin compared to healthy control skin, we have identified several potential susceptibility genes that may play a critical role in the pathological condition of AE. Many of these genes, including genes with a role in immune responses, lipid homeostasis, and epidermal differentiation, are localized on chromosomal regions previously linked to AE. Conclusions/Significance Through genome-wide expression profiling, we were able to discover a distinct reciprocal expression pattern of induced inflammatory genes and repressed lipid metabolism genes in skin from AE patients. We found a significant enrichment of differentially expressed genes in AE with cytobands associated to the disease, and furthermore new chromosomal regions were found that could potentially guide future region-specific linkage mapping in AE. The full data set is available at http://microarray-pubs.stanford.edu/eczema. PMID

  13. Global gene expression analyses of hematopoietic stem cell-like cell lines with inducible Lhx2 expression

    PubMed Central

    Richter, Karin; Wirta, Valtteri; Dahl, Lina; Bruce, Sara; Lundeberg, Joakim; Carlsson, Leif; Williams, Cecilia

    2006-01-01

    Background Expression of the LIM-homeobox gene Lhx2 in murine hematopoietic cells allows for the generation of hematopoietic stem cell (HSC)-like cell lines. To address the molecular basis of Lhx2 function, we generated HSC-like cell lines where Lhx2 expression is regulated by a tet-on system and hence dependent on the presence of doxycyclin (dox). These cell lines efficiently down-regulate Lhx2 expression upon dox withdrawal leading to a rapid differentiation into various myeloid cell types. Results Global gene expression of these cell lines cultured in dox was compared to different time points after dox withdrawal using microarray technology. We identified 267 differentially expressed genes. The majority of the genes overlapping with HSC-specific databases were those down-regulated after turning off Lhx2 expression and a majority of the genes overlapping with those defined as late progenitor-specific genes were the up-regulated genes, suggesting that these cell lines represent a relevant model system for normal HSCs also at the level of global gene expression. Moreover, in situ hybridisations of several genes down-regulated after dox withdrawal showed overlapping expression patterns with Lhx2 in various tissues during embryonic development. Conclusion Global gene expression analysis of HSC-like cell lines with inducible Lhx2 expression has identified genes putatively linked to self-renewal / differentiation of HSCs, and function of Lhx2 in organ development and stem / progenitor cells of non-hematopoietic origin. PMID:16600034

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

    PubMed Central

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

    2012-01-01

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

  15. Querying Co-regulated Genes on Diverse Gene Expression Datasets Via Biclustering.

    PubMed

    Deveci, Mehmet; Küçüktunç, Onur; Eren, Kemal; Bozdağ, Doruk; Kaya, Kamer; Çatalyürek, Ümit V

    2016-01-01

    Rapid development and increasing popularity of gene expression microarrays have resulted in a number of studies on the discovery of co-regulated genes. One important way of discovering such co-regulations is the query-based search since gene co-expressions may indicate a shared role in a biological process. Although there exist promising query-driven search methods adapting clustering, they fail to capture many genes that function in the same biological pathway because microarray datasets are fraught with spurious samples or samples of diverse origin, or the pathways might be regulated under only a subset of samples. On the other hand, a class of clustering algorithms known as biclustering algorithms which simultaneously cluster both the items and their features are useful while analyzing gene expression data, or any data in which items are related in only a subset of their samples. This means that genes need not be related in all samples to be clustered together. Because many genes only interact under specific circumstances, biclustering may recover the relationships that traditional clustering algorithms can easily miss. In this chapter, we briefly summarize the literature using biclustering for querying co-regulated genes. Then we present a novel biclustering approach and evaluate its performance by a thorough experimental analysis.

  16. A deep auto-encoder model for gene expression prediction.

    PubMed

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

    2017-11-17

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

  17. Quantification of multiple gene expression in individual cells.

    PubMed

    Peixoto, António; Monteiro, Marta; Rocha, Benedita; Veiga-Fernandes, Henrique

    2004-10-01

    Quantitative gene expression analysis aims to define the gene expression patterns determining cell behavior. So far, these assessments can only be performed at the population level. Therefore, they determine the average gene expression within a population, overlooking possible cell-to-cell heterogeneity that could lead to different cell behaviors/cell fates. Understanding individual cell behavior requires multiple gene expression analyses of single cells, and may be fundamental for the understanding of all types of biological events and/or differentiation processes. We here describe a new reverse transcription-polymerase chain reaction (RT-PCR) approach allowing the simultaneous quantification of the expression of 20 genes in the same single cell. This method has broad application, in different species and any type of gene combination. RT efficiency is evaluated. Uniform and maximized amplification conditions for all genes are provided. Abundance relationships are maintained, allowing the precise quantification of the absolute number of mRNA molecules per cell, ranging from 2 to 1.28 x 10(9) for each individual gene. We evaluated the impact of this approach on functional genetic read-outs by studying an apparently homogeneous population (monoclonal T cells recovered 4 d after antigen stimulation), using either this method or conventional real-time RT-PCR. Single-cell studies revealed considerable cell-to-cell variation: All T cells did not express all individual genes. Gene coexpression patterns were very heterogeneous. mRNA copy numbers varied between different transcripts and in different cells. As a consequence, this single-cell assay introduces new and fundamental information regarding functional genomic read-outs. By comparison, we also show that conventional quantitative assays determining population averages supply insufficient information, and may even be highly misleading.

  18. Soybean kinome: functional classification and gene expression patterns

    PubMed Central

    Liu, Jinyi; Chen, Nana; Grant, Joshua N.; Cheng, Zong-Ming (Max); Stewart, C. Neal; Hewezi, Tarek

    2015-01-01

    The protein kinase (PK) gene family is one of the largest and most highly conserved gene families in plants and plays a role in nearly all biological functions. While a large number of genes have been predicted to encode PKs in soybean, a comprehensive functional classification and global analysis of expression patterns of this large gene family is lacking. In this study, we identified the entire soybean PK repertoire or kinome, which comprised 2166 putative PK genes, representing 4.67% of all soybean protein-coding genes. The soybean kinome was classified into 19 groups, 81 families, and 122 subfamilies. The receptor-like kinase (RLK) group was remarkably large, containing 1418 genes. Collinearity analysis indicated that whole-genome segmental duplication events may have played a key role in the expansion of the soybean kinome, whereas tandem duplications might have contributed to the expansion of specific subfamilies. Gene structure, subcellular localization prediction, and gene expression patterns indicated extensive functional divergence of PK subfamilies. Global gene expression analysis of soybean PK subfamilies revealed tissue- and stress-specific expression patterns, implying regulatory functions over a wide range of developmental and physiological processes. In addition, tissue and stress co-expression network analysis uncovered specific subfamilies with narrow or wide interconnected relationships, indicative of their association with particular or broad signalling pathways, respectively. Taken together, our analyses provide a foundation for further functional studies to reveal the biological and molecular functions of PKs in soybean. PMID:25614662

  19. Evolution under monogamy feminizes gene expression in Drosophila melanogaster.

    PubMed

    Hollis, Brian; Houle, David; Yan, Zheng; Kawecki, Tadeusz J; Keller, Laurent

    2014-03-18

    Many genes have evolved sexually dimorphic expression as a consequence of divergent selection on males and females. However, because the sexes share a genome, the extent to which evolution can shape gene expression independently in each sex is controversial. Here, we use experimental evolution to reveal suboptimal sex-specific expression for much of the genome. By enforcing a monogamous mating system in populations of Drosophila melanogaster for over 100 generations, we eliminated major components of selection on males: female choice and male-male competition. If gene expression is subject to sexually antagonistic selection, relaxed selection on males should cause evolution towards female optima. Monogamous males and females show this pattern of feminization in both the whole-body and head transcriptomes. Genes with male-biased expression patterns evolved decreased expression under monogamy, while genes with female-biased expression evolved increased expression, relative to polygamous populations. Our results demonstrate persistent and widespread evolutionary tension between male and female adaptation.

  20. 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

  1. Integrated analysis of gene expression and methylation profiles of 48 candidate genes in breast cancer patients.

    PubMed

    Li, Zibo; Heng, Jianfu; Yan, Jinhua; Guo, Xinwu; Tang, Lili; Chen, Ming; Peng, Limin; Wu, Yepeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Wang, Jun

    2016-11-01

    Gene-specific methylation and expression have shown biological and clinical importance for breast cancer diagnosis and prognosis. Integrated analysis of gene methylation and gene expression may identify genes associated with biology mechanism and clinical outcome of breast cancer and aid in clinical management. Using high-throughput microfluidic quantitative PCR, we analyzed the expression profiles of 48 candidate genes in 96 Chinese breast cancer patients and investigated their correlation with gene methylation and associations with breast cancer clinical parameters. Breast cancer-specific gene expression alternation was found in 25 genes with significant expression difference between paired tumor and normal tissues. A total of 9 genes (CCND2, EGFR, GSTP1, PGR, PTGS2, RECK, SOX17, TNFRSF10D, and WIF1) showed significant negative correlation between methylation and gene expression, which were validated in the TCGA database. Total 23 genes (ACADL, APC, BRCA2, CADM1, CAV1, CCND2, CST6, EGFR, ESR2, GSTP1, ICAM5, NPY, PGR, PTGS2, RECK, RUNX3, SFRP1, SOX17, SYK, TGFBR2, TNFRSF10D, WIF1, and WRN) annotated with potential TFBSs in the promoter regions showed negative correlation between methylation and expression. In logistics regression analysis, 31 of the 48 genes showed improved performance in disease prediction with combination of methylation and expression coefficient. Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.

  2. Monitoring the regulation of gene expression in a growing organ using a fluid mechanics formalism

    PubMed Central

    2010-01-01

    Background Technological advances have enabled the accurate quantification of gene expression, even within single cell types. While transcriptome analyses are routinely performed, most experimental designs only provide snapshots of gene expression. Molecular mechanisms underlying cell fate or positional signalling have been revealed through these discontinuous datasets. However, in developing multicellular structures, temporal and spatial cues, known to directly influence transcriptional networks, get entangled as the cells are displaced and expand. Access to an unbiased view of the spatiotemporal regulation of gene expression occurring during development requires a specific framework that properly quantifies the rate of change of a property in a moving and expanding element, such as a cell or an organ segment. Results We show how the rate of change in gene expression can be quantified by combining kinematics and real-time polymerase chain reaction data in a mechanistic model which considers any organ as a continuum. This framework was applied in order to assess the developmental regulation of the two reference genes Actin11 and Elongation Factor 1-β in the apex of poplar root. The growth field was determined by time-lapse photography and transcript density was obtained at high spatial resolution. The net accumulation rates of the transcripts of the two genes were found to display highly contrasted developmental profiles. Actin11 showed pulses of up and down regulation in the accelerating and decelerating parts of the growth zone while the dynamic of EF1β were much slower. This framework provides key information about gene regulation in a developing organ, such as the location, the duration and the intensity of gene induction/repression. Conclusions We demonstrated that gene expression patterns can be monitored using the continuity equation without using mutants or reporter constructions. Given the rise of imaging technologies, this framework in our view opens a

  3. Identification of a reference gene for the quantification of mRNA and miRNA expression during skin wound healing.

    PubMed

    Etich, Julia; Bergmeier, Vera; Pitzler, Lena; Brachvogel, Bent

    2017-03-01

    Wound healing is a coordinated process to restore tissue homeostasis and reestablish the protective barrier of the skin. miRNAs may modulate the expression of target genes to contribute to repair processes, but due to the complexity of the tissue it is challenging to quantify gene expression during the distinct phases of wound repair. Here, we aimed to identify a common reference gene to quantify changes in miRNA and mRNA expression during skin wound healing. Quantitative real-time PCR and bioinformatic analysis tools were used to identify suitable reference genes during skin repair and their reliability was tested by studying the expression of mRNAs and miRNAs. Morphological assessment of wounds showed that the injury model recapitulates the distinct phases of skin repair. Non-degraded RNA could be isolated from skin and wounds and used to study the expression of non-coding small nuclear RNAs during wound healing. Among those, RNU6B was most constantly expressed during skin repair. Using this reference gene we could confirm the transient upregulation of IL-1β and PTPRC/CD45 during the early phase as well as the increased expression of collagen type I at later stages of repair and validate the differential expression of miR-204, miR-205, and miR-31 in skin wounds. In contrast to Gapdh the normalization to multiple reference genes gave a similar outcome. RNU6B is an accurate alternative normalizer to quantify mRNA and miRNA expression during the distinct phases of skin wound healing when analysis of multiple reference genes is not feasible.

  4. Noise in gene expression is coupled to growth rate.

    PubMed

    Keren, Leeat; van Dijk, David; Weingarten-Gabbay, Shira; Davidi, Dan; Jona, Ghil; Weinberger, Adina; Milo, Ron; Segal, Eran

    2015-12-01

    Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle-regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications. © 2015 Keren et al.; Published by Cold Spring Harbor Laboratory Press.

  5. Vaginal Gene Expression During Treatment With Aromatase Inhibitors.

    PubMed

    Kallak, Theodora Kunovac; Baumgart, Juliane; Nilsson, Kerstin; Åkerud, Helena; Poromaa, Inger Sundström; Stavreus-Evers, Anneli

    2015-12-01

    Aromatase inhibitor (AI) treatment suppresses estrogen biosynthesis and causes genitourinary symptoms of menopause such as vaginal symptoms, ultimately affecting the quality of life for many postmenopausal women with breast cancer. Thus, the aim of this study was to examine vaginal gene expression in women during treatment with AIs compared with estrogen-treated women. The secondary aim was to study the presence and localization of vaginal aromatase. Vaginal biopsies were collected from postmenopausal women treated with AIs and from age-matched control women treated with vaginal estrogen therapy. Differential gene expression was studied with the Affymetrix Gene Chip Gene 1.0 ST Array (Affymetrix Inc, Santa Clara, CA) system, Ingenuity pathway analysis, quantitative real-time polymerase chain reaction, and immunohistochemistry. The expression of 279 genes differed between the 2 groups; AI-treated women had low expression of genes involved in cell differentiation, proliferation, and cell adhesion. Some differentially expressed genes were found to interact indirectly with the estrogen receptor alpha. In addition, aromatase protein staining was evident in the basal and the intermediate vaginal epithelium layers, and also in stromal cells with a slightly stronger staining intensity found in AI-treated women. In this study, we demonstrated that genes involved in cell differentiation, proliferation, and cell adhesion are differentially expressed in AI-treated women. The expression of vaginal aromatase suggests that this could be the result of local and systemic inhibition of aromatase. Our results emphasize the role of estrogen for vaginal cell differentiation and proliferation and future drug candidates should be aimed at improving cell differentiation and proliferation. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Analysis of lamprey clustered Fox genes: insight into Fox gene evolution and expression in vertebrates.

    PubMed

    Wotton, Karl R; Shimeld, Sebastian M

    2011-12-01

    In the human genome, members of the FoxC, FoxF, FoxL1, and FoxQ1 gene families are found in two paralagous clusters. One cluster contains the genes FOXQ1, FOXF2, FOXC1 and the second consists of FOXF1, FOXC2, and FOXL1. In jawed vertebrates these genes are known to be expressed in different pharyngeal tissues and all, except FoxQ1, are involved in patterning the early embryonic mesoderm. We have previously traced the evolution of this cluster in the bony vertebrates, and the gene content is identical in the dogfish, a member of the most basally branching lineage of the jawed vertebrates. Here we extend these analyses to jawless vertebrates. Using genomic searches and molecular approaches we have identified homologues of these genes from lampreys. We identify two FoxC genes, two FoxF genes, two FoxQ1 genes and single FoxL1 gene. We examine the embryonic expression of one predominantly mesodermally expressed gene family, FoxC, and the endodermally expressed member of the cluster, FoxQ1. We identified FoxQ1 transcripts in the pharyngeal endoderm, while the two FoxC genes are differentially expressed in the pharyngeal mesenchyme and ectoderm. Furthermore we identify conserved expression of lamprey FoxC genes in the paraxial and intermediate mesoderms. We interpret our results through a chordate-wide comparison of expression patterns and discuss gene content in the context of theories on the evolution of the vertebrate genome. 2011 Elsevier B.V. All rights reserved.

  7. Gene expression models for prediction of longitudinal dispersion coefficient in streams

    NASA Astrophysics Data System (ADS)

    Sattar, Ahmed M. A.; Gharabaghi, Bahram

    2015-05-01

    Longitudinal dispersion is the key hydrologic process that governs transport of pollutants in natural streams. It is critical for spill action centers to be able to predict the pollutant travel time and break-through curves accurately following accidental spills in urban streams. This study presents a novel gene expression model for longitudinal dispersion developed using 150 published data sets of geometric and hydraulic parameters in natural streams in the United States, Canada, Europe, and New Zealand. The training and testing of the model were accomplished using randomly-selected 67% (100 data sets) and 33% (50 data sets) of the data sets, respectively. Gene expression programming (GEP) is used to develop empirical relations between the longitudinal dispersion coefficient and various control variables, including the Froude number which reflects the effect of reach slope, aspect ratio, and the bed material roughness on the dispersion coefficient. Two GEP models have been developed, and the prediction uncertainties of the developed GEP models are quantified and compared with those of existing models, showing improved prediction accuracy in favor of GEP models. Finally, a parametric analysis is performed for further verification of the developed GEP models. The main reason for the higher accuracy of the GEP models compared to the existing regression models is that exponents of the key variables (aspect ratio and bed material roughness) are not constants but a function of the Froude number. The proposed relations are both simple and accurate and can be effectively used to predict the longitudinal dispersion coefficients in natural streams.

  8. Regulation of gene expression in protozoa parasites.

    PubMed

    Gomez, Consuelo; Esther Ramirez, M; Calixto-Galvez, Mercedes; Medel, Olivia; Rodríguez, Mario A

    2010-01-01

    Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or drug resistance, and the comprehension of the mechanisms implicated in that control could help to develop novel therapeutic strategies. However, until now these mechanisms are poorly understood in protozoa. Recent investigations into gene expression in protozoa parasites suggest that they possess many of the canonical machineries employed by higher eukaryotes for the control of gene expression at transcriptional, posttranscriptional, and epigenetic levels, but they also contain exclusive mechanisms. Here, we review the current understanding about the regulation of gene expression in Plasmodium sp., Trypanosomatids, Entamoeba histolytica and Trichomonas vaginalis.

  9. Divergent and nonuniform gene expression patterns in mouse brain

    PubMed Central

    Morris, John A.; Royall, Joshua J.; Bertagnolli, Darren; Boe, Andrew F.; Burnell, Josh J.; Byrnes, Emi J.; Copeland, Cathy; Desta, Tsega; Fischer, Shanna R.; Goldy, Jeff; Glattfelder, Katie J.; Kidney, Jolene M.; Lemon, Tracy; Orta, Geralyn J.; Parry, Sheana E.; Pathak, Sayan D.; Pearson, Owen C.; Reding, Melissa; Shapouri, Sheila; Smith, Kimberly A.; Soden, Chad; Solan, Beth M.; Weller, John; Takahashi, Joseph S.; Overly, Caroline C.; Lein, Ed S.; Hawrylycz, Michael J.; Hohmann, John G.; Jones, Allan R.

    2010-01-01

    Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs. PMID:20956311

  10. Transcriptomic Analysis of Differentially Expressed Genes During Larval Development of Rapana venosa by Digital Gene Expression Profiling.

    PubMed

    Song, Hao; Yu, Zheng-Lin; Sun, Li-Na; Xue, Dong-Xiu; Zhang, Tao; Wang, Hai-Yan

    2016-07-07

    During the life cycle of shellfish, larval development, especially metamorphosis, has a vital influence on the dynamics, distribution, and recruitment of natural populations, as well as seed breeding. Rapana venosa, a carnivorous gastropod, is an important commercial shellfish in China, and is an ecological invader in the United States, Argentina, and France. However, information about the mechanism of its early development is still limited, because research in this area has long suffered from a lack of genomic resources. In this study, 15 digital gene expression (DGE) libraries from five developmental stages of R. venosa were constructed and sequenced on the IIIumina Hi-Sequation 2500 platform. Bioinformaticsanalysis identified numerous differentially and specifically expressed genes, which revealed that genes associated with growth, nervous system, digestive system, immune system, and apoptosis participate in important developmental processes. The functional analysis of differentially expressed genes was further implemented by gene ontology, and Kyoto encyclopedia of genes and genomes enrichment. DGE profiling provided a general picture of the transcriptomic activities during the early development of R. venosa, which may provide interesting hints for further study. Our data represent the first comparative transcriptomic information available for the early development of R. venosa, which is a prerequisite for a better understanding of the physiological traits controlling development. Copyright © 2016 Song et al.

  11. Appropriate 'housekeeping' genes for use in expression profiling the effects of environmental estrogens in fish

    PubMed Central

    Filby, Amy L; Tyler, Charles R

    2007-01-01

    Background Attempts to develop a mechanistic understanding of the effects of environmental estrogens on fish are increasingly conducted at the level of gene expression. Appropriate application of real-time PCR in such studies requires the use of a stably expressed 'housekeeping' gene as an internal control to normalize for differences in the amount of starting template between samples. Results We sought to identify appropriate genes for use as internal controls in experimental treatments with estrogen by analyzing the expression of eight functionally distinct 'housekeeping' genes (18S ribosomal RNA [18S rRNA], ribosomal protein l8 [rpl8], elongation factor 1 alpha [ef1a], glucose-6-phosphate dehydrogenase [g6pd], beta actin [bactin], glyceraldehyde-3-phosphate dehydrogenase [gapdh], hypoxanthine phosphoribosyltransferase 1 [hprt1], and tata box binding protein [tbp]) following exposure to the environmental estrogen, 17α-ethinylestradiol (EE2), in the fathead minnow (Pimephales promelas). Exposure to 10 ng/L EE2 for 21 days down-regulated the expression of ef1a, g6pd, bactin and gapdh in the liver, and bactin and gapdh in the gonad. Some of these effects were gender-specific, with bactin in the liver and gapdh in the gonad down-regulated by EE2 in males only. Furthermore, when ef1a, g6pd, bactin or gapdh were used for normalization, the hepatic expression of two genes of interest, vitellogenin (vtg) and cytochrome P450 1A (cyp1a) following exposure to EE2 was overestimated. Conclusion Based on the data presented, we recommend 18S rRNA, rpl8, hprt1 and/or tbp, but not ef1a, g6pd, bactin and/or gapdh, as likely appropriate internal controls in real-time PCR studies of estrogens effects in fish. Our studies show that pre-validation of control genes considering the scope and nature of the experiments to be performed, including both gender and tissue type, is critical for accurate assessments of the effects of environmental estrogens on gene expression in fish. PMID

  12. Rethinking cell-cycle-dependent gene expression in Schizosaccharomyces pombe.

    PubMed

    Cooper, Stephen

    2017-11-01

    Three studies of gene expression during the division cycle of Schizosaccharomyces pombe led to the proposal that a large number of genes are expressed at particular times during the S. pombe cell cycle. Yet only a small fraction of genes proposed to be expressed in a cell-cycle-dependent manner are reproducible in all three published studies. In addition to reproducibility problems, questions about expression amplitudes, cell-cycle timing of expression, synchronization artifacts, and the problem with methods for synchronizing cells must be considered. These problems and complications prompt the idea that caution should be used before accepting the conclusion that there are a large number of genes expressed in a cell-cycle-dependent manner in S. pombe.

  13. Transposon integration enhances expression of stress response genes.

    PubMed

    Feng, Gang; Leem, Young-Eun; Levin, Henry L

    2013-01-01

    Transposable elements possess specific patterns of integration. The biological impact of these integration profiles is not well understood. Tf1, a long-terminal repeat retrotransposon in Schizosaccharomyces pombe, integrates into promoters with a preference for the promoters of stress response genes. To determine the biological significance of Tf1 integration, we took advantage of saturated maps of insertion activity and studied how integration at hot spots affected the expression of the adjacent genes. Our study revealed that Tf1 integration did not reduce gene expression. Importantly, the insertions activated the expression of 6 of 32 genes tested. We found that Tf1 increased gene expression by inserting enhancer activity. Interestingly, the enhancer activity of Tf1 could be limited by Abp1, a host surveillance factor that sequesters transposon sequences into structures containing histone deacetylases. We found the Tf1 promoter was activated by heat treatment and, remarkably, only genes that themselves were induced by heat could be activated by Tf1 integration, suggesting a synergy of Tf1 enhancer sequence with the stress response elements of target promoters. We propose that the integration preference of Tf1 for the promoters of stress response genes and the ability of Tf1 to enhance the expression of these genes co-evolved to promote the survival of cells under stress.

  14. Transposon integration enhances expression of stress response genes

    PubMed Central

    Feng, Gang; Leem, Young-Eun; Levin, Henry L.

    2013-01-01

    Transposable elements possess specific patterns of integration. The biological impact of these integration profiles is not well understood. Tf1, a long-terminal repeat retrotransposon in Schizosaccharomyces pombe, integrates into promoters with a preference for the promoters of stress response genes. To determine the biological significance of Tf1 integration, we took advantage of saturated maps of insertion activity and studied how integration at hot spots affected the expression of the adjacent genes. Our study revealed that Tf1 integration did not reduce gene expression. Importantly, the insertions activated the expression of 6 of 32 genes tested. We found that Tf1 increased gene expression by inserting enhancer activity. Interestingly, the enhancer activity of Tf1 could be limited by Abp1, a host surveillance factor that sequesters transposon sequences into structures containing histone deacetylases. We found the Tf1 promoter was activated by heat treatment and, remarkably, only genes that themselves were induced by heat could be activated by Tf1 integration, suggesting a synergy of Tf1 enhancer sequence with the stress response elements of target promoters. We propose that the integration preference of Tf1 for the promoters of stress response genes and the ability of Tf1 to enhance the expression of these genes co-evolved to promote the survival of cells under stress. PMID:23193295

  15. Variation-preserving normalization unveils blind spots in gene expression profiling

    PubMed Central

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

    2017-01-01

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

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

    PubMed

    Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

    2017-11-13

    The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly

  17. G-NEST: A gene neighborhood scoring tool to identify co-conserved, co-expressed genes

    USDA-ARS?s Scientific Manuscript database

    In previous studies, gene neighborhoods--spatial clusters of co-expressed genes in the genome--have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Sc...

  18. Generating Facial Expressions Using an Anatomically Accurate Biomechanical Model.

    PubMed

    Wu, Tim; Hung, Alice; Mithraratne, Kumar

    2014-11-01

    This paper presents a computational framework for modelling the biomechanics of human facial expressions. A detailed high-order (Cubic-Hermite) finite element model of the human head was constructed using anatomical data segmented from magnetic resonance images. The model includes a superficial soft-tissue continuum consisting of skin, the subcutaneous layer and the superficial Musculo-Aponeurotic system. Embedded within this continuum mesh, are 20 pairs of facial muscles which drive facial expressions. These muscles were treated as transversely-isotropic and their anatomical geometries and fibre orientations were accurately depicted. In order to capture the relative composition of muscles and fat, material heterogeneity was also introduced into the model. Complex contact interactions between the lips, eyelids, and between superficial soft tissue continuum and deep rigid skeletal bones were also computed. In addition, this paper investigates the impact of incorporating material heterogeneity and contact interactions, which are often neglected in similar studies. Four facial expressions were simulated using the developed model and the results were compared with surface data obtained from a 3D structured-light scanner. Predicted expressions showed good agreement with the experimental data.

  19. Low-rank regularization for learning gene expression programs.

    PubMed

    Ye, Guibo; Tang, Mengfan; Cai, Jian-Feng; Nie, Qing; Xie, Xiaohui

    2013-01-01

    Learning gene expression programs directly from a set of observations is challenging due to the complexity of gene regulation, high noise of experimental measurements, and insufficient number of experimental measurements. Imposing additional constraints with strong and biologically motivated regularizations is critical in developing reliable and effective algorithms for inferring gene expression programs. Here we propose a new form of regulation that constrains the number of independent connectivity patterns between regulators and targets, motivated by the modular design of gene regulatory programs and the belief that the total number of independent regulatory modules should be small. We formulate a multi-target linear regression framework to incorporate this type of regulation, in which the number of independent connectivity patterns is expressed as the rank of the connectivity matrix between regulators and targets. We then generalize the linear framework to nonlinear cases, and prove that the generalized low-rank regularization model is still convex. Efficient algorithms are derived to solve both the linear and nonlinear low-rank regularized problems. Finally, we test the algorithms on three gene expression datasets, and show that the low-rank regularization improves the accuracy of gene expression prediction in these three datasets.

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

    PubMed

    Zeidan, Amer M; Prebet, Thomas; Saad Aldin, Ehab; Gore, Steven David

    2014-04-01

    Evaluation of: Pellagatti A, Benner A, Mills KI et al. Identification of gene expression-based prognostic markers in the hematopoietic stem cells of patients with myelodysplastic syndromes. J. Clin. Oncol. 31(28), 3557-3564 (2013). Patients with myelodysplastic syndromes (MDS) exhibit wide heterogeneity in clinical outcomes making accurate risk-stratification an integral part of the risk-adaptive management paradigm. Current prognostic schemes for MDS rely on clinicopathological parameters. Despite the increasing knowledge of the genetic landscape of MDS and the prognostic impact of many newly discovered molecular aberrations, none to date has been incorporated formally into the major risk models. Efforts are ongoing to use data generated from genome-wide high-throughput techniques to improve the 'individualized' outcome prediction for patients. We here discuss an important paper in which gene expression profiling (GEP) technology was applied to marrow CD34(+) cells from 125 MDS patients to generate and validate a standardized GEP-based prognostic signature.

  1. Sensitive and quantitative measurement of gene expression directly from a small amount of whole blood.

    PubMed

    Zheng, Zhi; Luo, Yuling; McMaster, Gary K

    2006-07-01

    Accurate and precise quantification of mRNA in whole blood is made difficult by gene expression changes during blood processing, and by variations and biases introduced by sample preparations. We sought to develop a quantitative whole-blood mRNA assay that eliminates blood purification, RNA isolation, reverse transcription, and target amplification while providing high-quality data in an easy assay format. We performed single- and multiplex gene expression analysis with multiple hybridization probes to capture mRNA directly from blood lysate and used branched DNA to amplify the signal. The 96-well plate singleplex assay uses chemiluminescence detection, and the multiplex assay combines Luminex-encoded beads with fluorescent detection. The single- and multiplex assays could quantitatively measure as few as 6000 and 24,000 mRNA target molecules (0.01 and 0.04 amoles), respectively, in up to 25 microL of whole blood. Both formats had CVs < 10% and dynamic ranges of 3-4 logs. Assay sensitivities allowed quantitative measurement of gene expression in the minority of cells in whole blood. The signals from whole-blood lysate correlated well with signals from purified RNA of the same sample, and absolute mRNA quantification results from the assay were similar to those obtained by quantitative reverse transcription-PCR. Both single- and multiplex assay formats were compatible with common anticoagulants and PAXgene-treated samples; however, PAXgene preparations induced expression of known antiapoptotic genes in whole blood. Both the singleplex and the multiplex branched DNA assays can quantitatively measure mRNA expression directly from small volumes of whole blood. The assay offers an alternative to current technologies that depend on RNA isolation and is amenable to high-throughput gene expression analysis of whole blood.

  2. Defective Cell Cycle Checkpoint Functions in Melanoma Are Associated with Altered Patterns of Gene Expression

    PubMed Central

    Kaufmann, William K.; Nevis, Kathleen R.; Qu, Pingping; Ibrahim, Joseph G.; Zhou, Tong; Zhou, Yingchun; Simpson, Dennis A.; Helms-Deaton, Jennifer; Cordeiro-Stone, Marila; Moore, Dominic T.; Thomas, Nancy E.; Hao, Honglin; Liu, Zhi; Shields, Janiel M.; Scott, Glynis A.; Sharpless, Norman E.

    2009-01-01

    Defects in DNA damage responses may underlie genetic instability and malignant progression in melanoma. Cultures of normal human melanocytes (NHMs) and melanoma lines were analyzed to determine whether global patterns of gene expression could predict the efficacy of DNA damage cell cycle checkpoints that arrest growth and suppress genetic instability. NHMs displayed effective G1 and G2 checkpoint responses to ionizing radiation-induced DNA damage. A majority of melanoma cell lines (11/16) displayed significant quantitative defects in one or both checkpoints. Melanomas with B-RAF mutations as a class displayed a significant defect in DNA damage G2 checkpoint function. In contrast the epithelial-like subtype of melanomas with wild-type N-RAS and B-RAF alleles displayed an effective G2 checkpoint but a significant defect in G1 checkpoint function. RNA expression profiling revealed that melanoma lines with defects in the DNA damage G1 checkpoint displayed reduced expression of p53 transcriptional targets, such as CDKN1A and DDB2, and enhanced expression of proliferation-associated genes, such as CDC7 and GEMININ. A Bayesian analysis tool was more accurate than significance analysis of microarrays for predicting checkpoint function using a leave-one-out method. The results suggest that defects in DNA damage checkpoints may be recognized in melanomas through analysis of gene expression. PMID:17597816

  3. Aging and Gene Expression in the Primate Brain

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

    Fraser, Hunter B.; Khaitovich, Philipp; Plotkin, Joshua B.

    2005-02-18

    It is well established that gene expression levels in many organisms change during the aging process, and the advent of DNA microarrays has allowed genome-wide patterns of transcriptional changes associated with aging to be studied in both model organisms and various human tissues. Understanding the effects of aging on gene expression in the human brain is of particular interest, because of its relation to both normal and pathological neurodegeneration. Here we show that human cerebral cortex, human cerebellum, and chimpanzee cortex each undergo different patterns of age-related gene expression alterations. In humans, many more genes undergo consistent expression changes inmore » the cortex than in the cerebellum; in chimpanzees, many genes change expression with age in cortex, but the pattern of changes in expression bears almost no resemblance to that of human cortex. These results demonstrate the diversity of aging patterns present within the human brain, as well as how rapidly genome-wide patterns of aging can evolve between species; they may also have implications for the oxidative free radical theory of aging, and help to improve our understanding of human neurodegenerative diseases.« less

  4. Identification and Characterization of Genes Required for Early Myxococcus xanthus Developmental Gene Expression

    PubMed Central

    Guo, Dongchuan; Wu, Yun; Kaplan, Heidi B.

    2000-01-01

    Starvation and cell density regulate the developmental expression of Myxococcus xanthus gene 4521. Three classes of mutants allow expression of this developmental gene during growth on nutrient agar, such that colonies of strains containing a Tn5 lac Ω4521 fusion are Lac+. One class of these mutants inactivates SasN, a negative regulator of 4521 expression; another class activates SasS, a sensor kinase-positive regulator of 4521 expression; and a third class blocks lipopolysaccharide (LPS) O-antigen biosynthesis. To identify additional positive regulators of 4521 expression, 11 Lac− TnV.AS transposon insertion mutants were isolated from a screen of 18,000 Lac+ LPS O-antigen mutants containing Tn5 lac Ω4521 (Tcr). Ten mutations identified genes that could encode positive regulators of 4521 developmental expression based on their ability to abolish 4521 expression during development in the absence of LPS O antigen and in an otherwise wild-type background. Eight of these mutations mapped to the sasB locus, which encodes the known 4521 regulators SasS and SasN. One mapped to sasS, whereas seven identified new genes. Three mutations mapped to a gene encoding an NtrC-like response regulator homologue, designated sasR, and four others mapped to a gene designated sasP. One mutation, designated ssp10, specifically suppressed the LPS O-antigen defect; the ssp10 mutation had no effect on 4521 expression in an otherwise wild-type background but reduced 4521 developmental expression in the absence of LPS O antigen to a level close to that of the parent strain. All of the mutations except those in sasP conferred defects during growth and development. These data indicate that a number of elements are required for 4521 developmental expression and that most of these are necessary for normal growth and fruiting body development. PMID:10913090

  5. An RNA-Seq based gene expression atlas of the common bean.

    PubMed

    O'Rourke, Jamie A; Iniguez, Luis P; Fu, Fengli; Bucciarelli, Bruna; Miller, Susan S; Jackson, Scott A; McClean, Philip E; Li, Jun; Dai, Xinbin; Zhao, Patrick X; Hernandez, Georgina; Vance, Carroll P

    2014-10-06

    Common bean (Phaseolus vulgaris) is grown throughout the world and comprises roughly 50% of the grain legumes consumed worldwide. Despite this, genetic resources for common beans have been lacking. Next generation sequencing, has facilitated our investigation of the gene expression profiles associated with biologically important traits in common bean. An increased understanding of gene expression in common bean will improve our understanding of gene expression patterns in other legume species. Combining recently developed genomic resources for Phaseolus vulgaris, including predicted gene calls, with RNA-Seq technology, we measured the gene expression patterns from 24 samples collected from seven tissues at developmentally important stages and from three nitrogen treatments. Gene expression patterns throughout the plant were analyzed to better understand changes due to nodulation, seed development, and nitrogen utilization. We have identified 11,010 genes differentially expressed with a fold change ≥ 2 and a P-value < 0.05 between different tissues at the same time point, 15,752 genes differentially expressed within a tissue due to changes in development, and 2,315 genes expressed only in a single tissue. These analyses identified 2,970 genes with expression patterns that appear to be directly dependent on the source of available nitrogen. Finally, we have assembled this data in a publicly available database, The Phaseolus vulgaris Gene Expression Atlas (Pv GEA), http://plantgrn.noble.org/PvGEA/ . Using the website, researchers can query gene expression profiles of their gene of interest, search for genes expressed in different tissues, or download the dataset in a tabular form. These data provide the basis for a gene expression atlas, which will facilitate functional genomic studies in common bean. Analysis of this dataset has identified genes important in regulating seed composition and has increased our understanding of nodulation and impact of the

  6. [Up regulation of phenylacetate to glioma homeobox gene expression].

    PubMed

    Tian, Yu; Yang, Chaohua; Zhao, Conghai

    2002-03-01

    Even though phenylacetate (PA) bas been shown to inhibit the growth and induce differentiation in rat C6 glioma cell line, its mechanisms are still poorly understood. This study is aimed to identify which Hox gene is related to glioma and to observe the change in expression on mRNA level as treated by phenylasetate. Twenty-two kinds of Hox gene were divided into 3 groups according to their primer sequence. Semiquantitative reverse transcription- polymerase chain reaction (RT-PCR) was used to investigate the mRNA expression of Hox gene groups and some Hox gene in rat C6 glioma cell line following differentiation induced by PA. The level of Hox gene expression was expressed as ratio expression rate (RER) of Hox gene/beta-actin according to computer image analysis and the difference between C6 cells and PA treated C6 cells was analyzed by student t-test. It was found that Hox genes matching to primers P2 were mildly expressed in C6 cells and the expression of HoxB2 mRNA was significantly up-regulated in PA treated C6 cells (P < 0.001). The weak expression of HoxB2 may be involved in glioma origin and the mechanisms of PA action are correlated with transcription process in the glioma cells.

  7. Molecular transformation, gene cloning, and gene expression systems for filamentous fungi

    USGS Publications Warehouse

    Gold, Scott E.; Duick, John W.; Redman, Regina S.; Rodriguez, Rusty J.

    2001-01-01

    This chapter discusses the molecular transformation, gene cloning, and gene expression systems for filamentous fungi. Molecular transformation involves the movement of discrete amounts of DNA into cells, the expression of genes on the transported DNA, and the sustainable replication of the transforming DNA. The ability to transform fungi is dependent on the stable replication and expression of genes located on the transforming DNA. Three phenomena observed in bacteria, that is, competence, plasmids, and restriction enzymes to facilitate cloning, were responsible for the development of molecular transformation in fungi. Initial transformation success with filamentous fungi, involving the complementation of auxotrophic mutants by exposure to sheared genomic DNA or RNA from wt isolates, occurred with low transformation efficiencies. In addition, it was difficult to retrieve complementing DNA fragments and isolate genes of interest. This prompted the development of transformation vectors and methods to increase efficiencies. The physiological studies performed with fungi indicated that the cell wall could be removed to generate protoplasts. It was evident that protoplasts could be transformed with significantly greater efficiencies than walled cells.

  8. With Reference to Reference Genes: A Systematic Review of Endogenous Controls in Gene Expression Studies.

    PubMed

    Chapman, Joanne R; Waldenström, Jonas

    2015-01-01

    The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR gene expression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate gene expression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies.

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

    PubMed

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

    2013-01-01

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

  10. Comparison of monocyte gene expression among patients with neurocysticercosis-associated epilepsy, Idiopathic Epilepsy and idiopathic headaches in India.

    PubMed

    Prabhakaran, Vasudevan; Drevets, Douglas A; Ramajayam, Govindan; Manoj, Josephine J; Anderson, Michael P; Hanas, Jay S; Rajshekhar, Vedantam; Oommen, Anna; Carabin, Hélène

    2017-06-01

    Neurocysticercosis (NCC), a neglected tropical disease, inflicts substantial health and economic costs on people living in endemic areas such as India. Nevertheless, accurate diagnosis using brain imaging remains poorly accessible and too costly in endemic countries. The goal of this study was to test if blood monocyte gene expression could distinguish patients with NCC-associated epilepsy, from NCC-negative imaging lesion-free patients presenting with idiopathic epilepsy or idiopathic headaches. Patients aged 18 to 51 were recruited from the Department of Neurological Sciences, Christian Medical College and Hospital, Vellore, India, between January 2013 and October 2014. mRNA from CD14+ blood monocytes was isolated from 76 patients with NCC, 10 Recovered NCC (RNCC), 29 idiopathic epilepsy and 17 idiopathic headaches patients. A preliminary microarray analysis was performed on six NCC, six idiopathic epilepsy and four idiopathic headaches patients to identify genes differentially expressed in NCC-associated epilepsy compared with other groups. This analysis identified 1411 upregulated and 733 downregulated genes in patients with NCC compared to Idiopathic Epilepsy. Fifteen genes up-regulated in NCC patients compared with other groups were selected based on possible relevance to NCC, and analyzed by qPCR in all patients' samples. Differential gene expression among patients was assessed using linear regression models. qPCR analysis of 15 selected genes showed generally higher gene expression among NCC patients, followed by RNCC, idiopathic headaches and Idiopathic Epilepsy. Gene expression was also generally higher among NCC patients with single cyst granulomas, followed by mixed lesions and single calcifications. Expression of certain genes in blood monocytes can distinguish patients with NCC-related epilepsy from patients with active Idiopathic Epilepsy and idiopathic headaches. These findings are significant because they may lead to the development of new tools to

  11. Gravity-regulated gene expression in Arabidopsis thaliana

    NASA Astrophysics Data System (ADS)

    Sederoff, Heike; Brown, Christopher S.; Heber, Steffen; Kajla, Jyoti D.; Kumar, Sandeep; Lomax, Terri L.; Wheeler, Benjamin; Yalamanchili, Roopa

    Plant growth and development is regulated by changes in environmental signals. Plants sense environmental changes and respond to them by modifying gene expression programs to ad-just cell growth, differentiation, and metabolism. Functional expression of genes comprises many different processes including transcription, translation, post-transcriptional and post-translational modifications, as well as the degradation of RNA and proteins. Recently, it was discovered that small RNAs (sRNA, 18-24 nucleotides long), which are heritable and systemic, are key elements in regulating gene expression in response to biotic and abiotic changes. Sev-eral different classes of sRNAs have been identified that are part of a non-cell autonomous and phloem-mobile network of regulators affecting transcript stability, translational kinetics, and DNA methylation patterns responsible for heritable transcriptional silencing (epigenetics). Our research has focused on gene expression changes in response to gravistimulation of Arabidopsis roots. Using high-throughput technologies including microarrays and 454 sequencing, we iden-tified rapid changes in transcript abundance of genes as well as differential expression of small RNA in Arabidopsis root apices after minutes of reorientation. Some of the differentially regu-lated transcripts are encoded by genes that are important for the bending response. Functional mutants of those genes respond faster to reorientation than the respective wild type plants, indicating that these proteins are repressors of differential cell elongation. We compared the gravity responsive sRNAs to the changes in transcript abundances of their putative targets and identified several potential miRNA: target pairs. Currently, we are using mutant and transgenic Arabidopsis plants to characterize the function of those miRNAs and their putative targets in gravitropic and phototropic responses in Arabidopsis.

  12. General statistics of stochastic process of gene expression in eukaryotic cells.

    PubMed Central

    Kuznetsov, V A; Knott, G D; Bonner, R F

    2002-01-01

    Thousands of genes are expressed at such very low levels (< or =1 copy per cell) that global gene expression analysis of rarer transcripts remains problematic. Ambiguity in identification of rarer transcripts creates considerable uncertainty in fundamental questions such as the total number of genes expressed in an organism and the biological significance of rarer transcripts. Knowing the distribution of the true number of genes expressed at each level and the corresponding gene expression level probability function (GELPF) could help resolve these uncertainties. We found that all observed large-scale gene expression data sets in yeast, mouse, and human cells follow a Pareto-like distribution model skewed by many low-abundance transcripts. A novel stochastic model of the gene expression process predicts the universality of the GELPF both across different cell types within a multicellular organism and across different organisms. This model allows us to predict the frequency distribution of all gene expression levels within a single cell and to estimate the number of expressed genes in a single cell and in a population of cells. A random "basal" transcription mechanism for protein-coding genes in all or almost all eukaryotic cell types is predicted. This fundamental mechanism might enhance the expression of rarely expressed genes and, thus, provide a basic level of phenotypic diversity, adaptability, and random monoallelic expression in cell populations. PMID:12136033

  13. Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

    NASA Technical Reports Server (NTRS)

    Eichler, Gabriel S.; Huang, Sui; Ingber, Donald E.

    2003-01-01

    Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/ge/gedihome.html Supplementary information: http://www.chip.org/ge/gedihome.html.

  14. Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis.

    PubMed

    dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

    2015-01-01

    Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis.

  15. Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis

    PubMed Central

    dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

    2015-01-01

    Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis. PMID:26393928

  16. Gene Expression by Mouse Inner Ear Hair Cells during Development

    PubMed Central

    Scheffer, Déborah I.; Shen, Jun

    2015-01-01

    Hair cells of the inner ear are essential for hearing and balance. As a consequence, pathogenic variants in genes specifically expressed in hair cells often cause hereditary deafness. Hair cells are few in number and not easily isolated from the adjacent supporting cells, so the biochemistry and molecular biology of hair cells can be difficult to study. To study gene expression in hair cells, we developed a protocol for hair cell isolation by FACS. With nearly pure hair cells and surrounding cells, from cochlea and utricle and from E16 to P7, we performed a comprehensive cell type-specific RNA-Seq study of gene expression during mouse inner ear development. Expression profiling revealed new hair cell genes with distinct expression patterns: some are specific for vestibular hair cells, others for cochlear hair cells, and some are expressed just before or after maturation of mechanosensitivity. We found that many of the known hereditary deafness genes are much more highly expressed in hair cells than surrounding cells, suggesting that genes preferentially expressed in hair cells are good candidates for unknown deafness genes. PMID:25904789

  17. Vascular Gene Expression in Nonneoplastic and Malignant Brain

    PubMed Central

    Madden, Stephen L.; Cook, Brian P.; Nacht, Mariana; Weber, William D.; Callahan, Michelle R.; Jiang, Yide; Dufault, Michael R.; Zhang, Xiaoming; Zhang, Wen; Walter-Yohrling, Jennifer; Rouleau, Cecile; Akmaev, Viatcheslav R.; Wang, Clarence J.; Cao, Xiaohong; St. Martin, Thia B.; Roberts, Bruce L.; Teicher, Beverly A.; Klinger, Katherine W.; Stan, Radu-Virgil; Lucey, Brenden; Carson-Walter, Eleanor B.; Laterra, John; Walter, Kevin A.

    2004-01-01

    Malignant gliomas are uniformly lethal tumors whose morbidity is mediated in large part by the angiogenic response of the brain to the invading tumor. This profound angiogenic response leads to aggressive tumor invasion and destruction of surrounding brain tissue as well as blood-brain barrier breakdown and life-threatening cerebral edema. To investigate the molecular mechanisms governing the proliferation of abnormal microvasculature in malignant brain tumor patients, we have undertaken a cell-specific transcriptome analysis from surgically harvested nonneoplastic and tumor-associated endothelial cells. SAGE-derived endothelial cell gene expression patterns from glioma and nonneoplastic brain tissue reveal distinct gene expression patterns and consistent up-regulation of certain glioma endothelial marker genes across patient samples. We define the G-protein-coupled receptor RDC1 as a tumor endothelial marker whose expression is distinctly induced in tumor endothelial cells of both brain and peripheral vasculature. Further, we demonstrate that the glioma-induced gene, PV1, shows expression both restricted to endothelial cells and coincident with endothelial cell tube formation. As PV1 provides a framework for endothelial cell caveolar diaphragms, this protein may serve to enhance glioma-induced disruption of the blood-brain barrier and transendothelial exchange. Additional characterization of this extensive brain endothelial cell gene expression database will provide unique molecular insights into vascular gene expression. PMID:15277233

  18. Robust diagnosis of non-Hodgkin lymphoma phenotypes validated on gene expression data from different laboratories.

    PubMed

    Bhanot, Gyan; Alexe, Gabriela; Levine, Arnold J; Stolovitzky, Gustavo

    2005-01-01

    A major challenge in cancer diagnosis from microarray data is the need for robust, accurate, classification models which are independent of the analysis techniques used and can combine data from different laboratories. We propose such a classification scheme originally developed for phenotype identification from mass spectrometry data. The method uses a robust multivariate gene selection procedure and combines the results of several machine learning tools trained on raw and pattern data to produce an accurate meta-classifier. We illustrate and validate our method by applying it to gene expression datasets: the oligonucleotide HuGeneFL microarray dataset of Shipp et al. (www.genome.wi.mit.du/MPR/lymphoma) and the Hu95Av2 Affymetrix dataset (DallaFavera's laboratory, Columbia University). Our pattern-based meta-classification technique achieves higher predictive accuracies than each of the individual classifiers , is robust against data perturbations and provides subsets of related predictive genes. Our techniques predict that combinations of some genes in the p53 pathway are highly predictive of phenotype. In particular, we find that in 80% of DLBCL cases the mRNA level of at least one of the three genes p53, PLK1 and CDK2 is elevated, while in 80% of FL cases, the mRNA level of at most one of them is elevated.

  19. Blood expression profiles of fragile X premutation carriers identify candidate genes involved in neurodegenerative and infertility phenotypes.

    PubMed

    Mateu-Huertas, Elisabet; Rodriguez-Revenga, Laia; Alvarez-Mora, Maria Isabel; Madrigal, Irene; Willemsen, Rob; Milà, Montserrat; Martí, Eulàlia; Estivill, Xavier

    2014-05-01

    Male premutation carriers presenting between 55 and 200 CGG repeats in the Fragile-X-associated (FMR1) gene are at risk of developing Fragile X Tremor/Ataxia Syndrome (FXTAS), and females undergo Premature Ovarian Failure (POF1). Here, we have evaluated gene expression profiles from blood in male FMR1 premutation carriers and detected a strong deregulation of genes enriched in FXTAS relevant biological pathways, including inflammation, neuronal homeostasis and viability. Gene expression profiling distinguished between control individuals, carriers with FXTAS and carriers without FXTAS, with levels of expanded FMR1 mRNA being increased in FXTAS patients. In vitro studies in a neuronal cell model indicate that expression levels of expanded FMR1 5'-UTR are relevant in modulating the transcriptome. Thus, perturbations of the transcriptome may be an interplay between the CGG expansion size and FMR1 expression levels. Several deregulated genes (DFFA, BCL2L11, BCL2L1, APP, SOD1, RNF10, HDAC5, KCNC3, ATXN7, ATXN3 and EAP1) were validated in brain samples of a FXTAS mouse model. Downregulation of EAP1, a gene involved in the female reproductive system physiology, was confirmed in female carriers. Decreased levels were detected in female carriers with POF1 compared to those without POF1, suggesting that EAP1 levels contribute to ovarian insufficiency. In summary, gene expression profiling in blood has uncovered mechanisms that may underlie different pathological aspects of the premutation. A better understanding of the transcriptome dynamics in relation with expanded FMR1 mRNA expression levels and CGG expansion size may provide mechanistic insights into the disease process and a more accurate FXTAS diagnosis to the myriad of phenotypes associated with the premutation. Copyright © 2014. Published by Elsevier Inc.

  20. 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

  1. Anterior-posterior regionalized gene expression in the Ciona notochord

    PubMed Central

    Veeman, Michael

    2014-01-01

    Background In the simple ascidian chordate Ciona the signaling pathways and gene regulatory networks giving rise to initial notochord induction are largely understood and the mechanisms of notochord morphogenesis are being systematically elucidated. The notochord has generally been thought of as a non-compartmentalized or regionalized organ that is not finely patterned at the level of gene expression. Quantitative imaging methods have recently shown, however, that notochord cell size, shape and behavior vary consistently along the anterior-posterior (AP) axis. Results Here we screen candidate genes by whole mount in situ hybridization for potential AP asymmetry. We identify 4 genes that show non-uniform expression in the notochord. Ezrin/radixin/moesin (ERM) is expressed more strongly in the secondary notochord lineage than the primary. CTGF is expressed stochastically in a subset of notochord cells. A novel calmodulin-like gene (BCamL) is expressed more strongly at both the anterior and posterior tips of the notochord. A TGF-β ortholog is expressed in a gradient from posterior to anterior. The asymmetries in ERM, BCamL and TGF-β expression are evident even before the notochord cells have intercalated into a single-file column. Conclusions We conclude that the Ciona notochord is not a homogeneous tissue but instead shows distinct patterns of regionalized gene expression. PMID:24288133

  2. Genomic DNA-based absolute quantification of gene expression in Vitis

    USDA-ARS?s Scientific Manuscript database

    Many studies in which gene expression is quantified by polymerase chain reaction represent the expression of a gene of interest (GOI) relative to that of a reference gene (RG). Relative expression is founded on the assumptions that RG expression is stable across samples, treatments, organs, etc., an...

  3. Automated Discovery of Functional Generality of Human Gene Expression Programs

    PubMed Central

    Gerber, Georg K; Dowell, Robin D; Jaakkola, Tommi S; Gifford, David K

    2007-01-01

    An important research problem in computational biology is the identification of expression programs, sets of co-expressed genes orchestrating normal or pathological processes, and the characterization of the functional breadth of these programs. The use of human expression data compendia for discovery of such programs presents several challenges including cellular inhomogeneity within samples, genetic and environmental variation across samples, uncertainty in the numbers of programs and sample populations, and temporal behavior. We developed GeneProgram, a new unsupervised computational framework based on Hierarchical Dirichlet Processes that addresses each of the above challenges. GeneProgram uses expression data to simultaneously organize tissues into groups and genes into overlapping programs with consistent temporal behavior, to produce maps of expression programs, which are sorted by generality scores that exploit the automatically learned groupings. Using synthetic and real gene expression data, we showed that GeneProgram outperformed several popular expression analysis methods. We applied GeneProgram to a compendium of 62 short time-series gene expression datasets exploring the responses of human cells to infectious agents and immune-modulating molecules. GeneProgram produced a map of 104 expression programs, a substantial number of which were significantly enriched for genes involved in key signaling pathways and/or bound by NF-κB transcription factors in genome-wide experiments. Further, GeneProgram discovered expression programs that appear to implicate surprising signaling pathways or receptor types in the response to infection, including Wnt signaling and neurotransmitter receptors. We believe the discovered map of expression programs involved in the response to infection will be useful for guiding future biological experiments; genes from programs with low generality scores might serve as new drug targets that exhibit minimal “cross-talk,” and

  4. 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

  5. Xylella fastidiosa gene expression analysis by DNA microarrays.

    PubMed

    Travensolo, Regiane F; Carareto-Alves, Lucia M; Costa, Maria V C G; Lopes, Tiago J S; Carrilho, Emanuel; Lemos, Eliana G M

    2009-04-01

    Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM(2) and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

  6. A Compendium of Canine Normal Tissue Gene Expression

    PubMed Central

    Chen, Qing-Rong; Wen, Xinyu; Khan, Javed; Khanna, Chand

    2011-01-01

    Background Our understanding of disease is increasingly informed by changes in gene expression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue gene expression compendium with corresponding human cross-species analysis. Methodology/Principal Findings The Affymetrix platform was utilized to catalogue gene expression signatures of 10 normal canine tissues including: liver, kidney, heart, lung, cerebrum, lymph node, spleen, jejunum, pancreas and skeletal muscle. The quality of the database was assessed in several ways. Organ defining gene sets were identified for each tissue and functional enrichment analysis revealed themes consistent with known physio-anatomic functions for each organ. In addition, a comparison of orthologous gene expression between matched canine and human normal tissues uncovered remarkable similarity. To demonstrate the utility of this dataset, novel canine gene annotations were established based on comparative analysis of dog and human tissue selective gene expression and manual curation of canine probeset mapping. Public access, using infrastructure identical to that currently in use for human normal tissues, has been established and allows for additional comparisons across species. Conclusions/Significance These data advance our understanding of the canine genome through a comprehensive analysis of gene expression in a diverse set of tissues, contributing to improved functional annotation that has been lacking. Importantly, it will be used to inform future studies of disease in the dog as a model for human translational research and provides a novel resource to the community at large. PMID:21655323

  7. Too much data, but little inter-changeability: a lesson learned from mining public data on tissue specificity of gene expression.

    PubMed

    Li, Shuyu; Li, Yiqun Helen; Wei, Tao; Su, Eric Wen; Duffin, Kevin; Liao, Birong

    2006-10-25

    that the exploitation of rich public expression resource requires extensive knowledge about the technologies, and experiment. Informatic methodologies for better interoperability among platforms still remain a gap. One of the areas that can be improved practically is the accurate sequence mapping of SAGE tags and array probes to full-length genes.

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

    PubMed

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

    2012-03-01

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

  9. Integrating gene and protein expression data with genome-scale metabolic networks to infer functional pathways.

    PubMed

    Pey, Jon; Valgepea, Kaspar; Rubio, Angel; Beasley, John E; Planes, Francisco J

    2013-12-08

    The study of cellular metabolism in the context of high-throughput -omics data has allowed us to decipher novel mechanisms of importance in biotechnology and health. To continue with this progress, it is essential to efficiently integrate experimental data into metabolic modeling. We present here an in-silico framework to infer relevant metabolic pathways for a particular phenotype under study based on its gene/protein expression data. This framework is based on the Carbon Flux Path (CFP) approach, a mixed-integer linear program that expands classical path finding techniques by considering additional biophysical constraints. In particular, the objective function of the CFP approach is amended to account for gene/protein expression data and influence obtained paths. This approach is termed integrative Carbon Flux Path (iCFP). We show that gene/protein expression data also influences the stoichiometric balancing of CFPs, which provides a more accurate picture of active metabolic pathways. This is illustrated in both a theoretical and real scenario. Finally, we apply this approach to find novel pathways relevant in the regulation of acetate overflow metabolism in Escherichia coli. As a result, several targets which could be relevant for better understanding of the phenomenon leading to impaired acetate overflow are proposed. A novel mathematical framework that determines functional pathways based on gene/protein expression data is presented and validated. We show that our approach is able to provide new insights into complex biological scenarios such as acetate overflow in Escherichia coli.

  10. Using Gene Expression Biomarkers to Identify Chemicals that Induce Key Events in Cancer and Endocrine Disruption AOPs: Androgen Receptor as an Example

    EPA Science Inventory

    High-throughput transcriptomic (HTTr) technologies are increasingly being used to screen environmental chemicals in vitro to provide mechanistic context for regulatory testing. The development of gene expression biomarkers that accurately predict molecular and toxicological effec...

  11. Ion channel gene expression predicts survival in glioma patients

    PubMed Central

    Wang, Rong; Gurguis, Christopher I.; Gu, Wanjun; Ko, Eun A; Lim, Inja; Bang, Hyoweon; Zhou, Tong; Ko, Jae-Hong

    2015-01-01

    Ion channels are important regulators in cell proliferation, migration, and apoptosis. The malfunction and/or aberrant expression of ion channels may disrupt these important biological processes and influence cancer progression. In this study, we investigate the expression pattern of ion channel genes in glioma. We designate 18 ion channel genes that are differentially expressed in high-grade glioma as a prognostic molecular signature. This ion channel gene expression based signature predicts glioma outcome in three independent validation cohorts. Interestingly, 16 of these 18 genes were down-regulated in high-grade glioma. This signature is independent of traditional clinical, molecular, and histological factors. Resampling tests indicate that the prognostic power of the signature outperforms random gene sets selected from human genome in all the validation cohorts. More importantly, this signature performs better than the random gene signatures selected from glioma-associated genes in two out of three validation datasets. This study implicates ion channels in brain cancer, thus expanding on knowledge of their roles in other cancers. Individualized profiling of ion channel gene expression serves as a superior and independent prognostic tool for glioma patients. PMID:26235283

  12. Base composition and expression level of human genes.

    PubMed

    Arhondakis, Stilianos; Auletta, Fabio; Torelli, Giuseppe; D'Onofrio, Giuseppe

    2004-01-21

    It is well known that the gene distribution is non-uniform in the human genome, reaching the highest concentration in the GC-rich isochores. Also the amino acid frequencies, and the hydrophobicity, of the corresponding encoded proteins are affected by the high GC level of the genes localized in the GC-rich isochores. It was hypothesized that the gene expression level as well is higher in GC-rich compared to GC-poor isochores [Mol. Biol. Evol. 10 (1993) 186]. Several features of human genes and proteins, namely expression level, coding and non-coding lengths, and hydrophobicity were investigated in the present paper. The results support the hypothesis reported above, since all the parameters so far studied converge to the same conclusion, that the average expression level of the GC-rich genes is significantly higher than that of the GC-poor genes.

  13. Gene expression patterns combined with bioinformatics analysis identify genes associated with cholangiocarcinoma.

    PubMed

    Li, Chen; Shen, Weixing; Shen, Sheng; Ai, Zhilong

    2013-12-01

    To explore the molecular mechanisms of cholangiocarcinoma (CC), microarray technology was used to find biomarkers for early detection and diagnosis. The gene expression profiles from 6 patients with CC and 5 normal controls were downloaded from Gene Expression Omnibus and compared. As a result, 204 differentially co-expressed genes (DCGs) in CC patients compared to normal controls were identified using a computational bioinformatics analysis. These genes were mainly involved in coenzyme metabolic process, peptidase activity and oxidation reduction. A regulatory network was constructed by mapping the DCGs to known regulation data. Four transcription factors, FOXC1, ZIC2, NKX2-2 and GCGR, were hub nodes in the network. In conclusion, this study provides a set of targets useful for future investigations into molecular biomarker studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Polyandry and sex-specific gene expression

    PubMed Central

    Mank, Judith E.; Wedell, Nina; Hosken, David J.

    2013-01-01

    Polyandry is widespread in nature, and has important evolutionary consequences for the evolution of sexual dimorphism and sexual conflict. Although many of the phenotypic consequences of polyandry have been elucidated, our understanding of the impacts of polyandry and mating systems on the genome is in its infancy. Polyandry can intensify selection on sexual characters and generate more intense sexual conflict. This has consequences for sequence evolution, but also for sex-biased gene expression, which acts as a link between mating systems, sex-specific selection and the evolution of sexual dimorphism. We discuss this and the remarkable confluence of sexual-conflict theory and patterns of gene expression, while also making predictions about transcription patterns, mating systems and sexual conflict. Gene expression is a key link in the genotype–phenotype chain, and although in its early stages, understanding the sexual selection–transcription relationship will provide significant insights into this critical association. PMID:23339238

  15. Novel expression of the stanniocalcin gene in fish.

    PubMed

    McCudden, C R; Kogon, M R; DiMattia, G E; Wagner, G F

    2001-10-01

    It is currently accepted that the fish stanniocalcin (STC) gene is expressed exclusively in the corpuscles of Stannius (CS), unique endocrine glands on the kidneys of bony fishes. In this study, we have re-examined the pattern of fish STC gene expression in the light of the recent evidence for widespread expression of the gene in mammals. Surprisingly, we found by Northern blotting that the fish gene was also expressed in the kidneys and gonads, in addition to the CS glands. Moreover, Southern blotting of RT-PCR products revealed STC mRNA transcripts in all tissues assayed, including brain, heart, gill, muscle and intestine. In situ hybridization studies using digoxigenin-labeled riboprobes localized STC mRNA to chondrocytes, and both mature and developing nephritic tubules. Immunocytochemical staining indicated that the STC protein was widespread in cells of the gill, kidney, brain, eye, pseudobranch and skin. We also characterized the salmon STC gene, establishing that it was comprised of five exons as opposed to four in mammals. A single transcription start site was identified by primer extension 99 bp upstream of the start codon. This is the first evidence of STC gene expression in fish tissues other than the CS glands and suggests that, as in mammals, fish STC operates via both local and endocrine pathways.

  16. The low noise limit in gene expression

    DOE PAGES

    Dar, Roy D.; Weinberger, Leor S.; Cox, Chris D.; ...

    2015-10-21

    Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i) the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii) the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression. While growing evidence suggests that transcriptional bursting may set the low noise limit, variability in translational bursting has been largely ignored. We show that genome-wide systematic variation in translational efficiencymore » can-and in the case of E. coli does-control the low noise limit in gene expression. Therefore constitutive extrinsic noise is small and only plays a role in the absence of a systematic variation in translational efficiency. Lastly, these results show the existence of two distinct expression noise patterns: (1) a global noise floor uniformly imposed on all genes by expression bursting; and (2) high noise distributed to only a select group of genes.« less

  17. Oxygen and tissue culture affect placental gene expression.

    PubMed

    Brew, O; Sullivan, M H F

    2017-07-01

    Placental explant culture is an important model for studying placental development and functions. We investigated the differences in placental gene expression in response to tissue culture, atmospheric and physiologic oxygen concentrations. Placental explants were collected from normal term (38-39 weeks of gestation) placentae with no previous uterine contractile activity. Placental transcriptomic expressions were evaluated with GeneChip ® Human Genome U133 Plus 2.0 arrays (Affymetrix). We uncovered sub-sets of genes that regulate response to stress, induction of apoptosis programmed cell death, mis-regulation of cell growth, proliferation, cell morphogenesis, tissue viability, and protection from apoptosis in cultured placental explants. We also identified a sub-set of genes with highly unstable pattern of expression after exposure to tissue culture. Tissue culture irrespective of oxygen concentration induced dichotomous increase in significant gene expression and increased enrichment of significant pathways and transcription factor targets (TFTs) including HIF1A. The effect was exacerbated by culture at atmospheric oxygen concentration, where further up-regulation of TFTs including PPARA, CEBPD, HOXA9 and down-regulated TFTs such as JUND/FOS suggest intrinsic heightened key biological and metabolic mechanisms such as glucose use, lipid biosynthesis, protein metabolism; apoptosis, inflammatory responses; and diminished trophoblast proliferation, differentiation, invasion, regeneration, and viability. These findings demonstrate that gene expression patterns differ between pre-culture and cultured explants, and the gene expression of explants cultured at atmospheric oxygen concentration favours stressed, pro-inflammatory and increased apoptotic transcriptomic response. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. VH gene expression and regulation in the mutant Alicia rabbit. Rescue of VHa2 allotype expression.

    PubMed

    Chen, H T; Alexander, C B; Young-Cooper, G O; Mage, R G

    1993-04-01

    Rabbits of the Alicia strain, derived from rabbits expressing the VHa2 allotype, have a mutation in the H chain locus that has a cis effect upon the expression of VHa2 and VHa- genes. A small deletion at the most J-proximal (3') end of the VH locus leads to low expression of all the genes on the entire chromosome in heterozygous ali mutants and altered relative expression of VH genes in homozygotes. To study VH gene expression and regulation, we used the polymerase chain reaction to amplify the VH genes expressed in spleens of young and adult wild-type and mutant Alicia rabbits. The cDNA from reverse transcription of splenic mRNA was amplified and polymerase chain reaction libraries were constructed and screened with oligonucleotides from framework regions 1 and 3, as well as JH. Thirty-three VH-positive clones were sequenced and analyzed. We found that in mutant Alicia rabbits, products of the first functional VH gene (VH4a2), (or VH4a2-like genes) were expressed in 2- to 8-wk-olds. Expression of both the VHx and VHy types of VHa- genes was also elevated but the relative proportions of VHx and VHy, especially VHx, decreased whereas the relative levels of expression of VH4a2 or VH4a2-like genes increased with age. Our results suggest that the appearance of sequences resembling that of the VH1a2, which is deleted in the mutant ali rabbits, could be caused by alterations of the sequences of the rearranged VH4a2 genes by gene conversions and/or rearrangement of upstream VH1a2-like genes later in development.

  19. The human cumulus--oocyte complex gene-expression profile

    PubMed Central

    Assou, Said; Anahory, Tal; Pantesco, Véronique; Le Carrour, Tanguy; Pellestor, Franck; Klein, Bernard; Reyftmann, Lionel; Dechaud, Hervé; De Vos, John; Hamamah, Samir

    2006-01-01

    BACKGROUND The understanding of the mechanisms regulating human oocyte maturation is still rudimentary. We have identified transcripts differentially expressed between immature and mature oocytes, and cumulus cells. METHODS Using oligonucleotides microarrays, genome wide gene expression was studied in pooled immature and mature oocytes or cumulus cells from patients who underwent IVF. RESULTS In addition to known genes such as DAZL, BMP15 or GDF9, oocytes upregulated 1514 genes. We show that PTTG3 and AURKC are respectively the securin and the Aurora kinase preferentially expressed during oocyte meiosis. Strikingly, oocytes overexpressed previously unreported growth factors such as TNFSF13/APRIL, FGF9, FGF14, and IL4, and transcription factors including OTX2, SOX15 and SOX30. Conversely, cumulus cells, in addition to known genes such as LHCGR or BMPR2, overexpressed cell-tocell signaling genes including TNFSF11/RANKL, numerous complement components, semaphorins (SEMA3A, SEMA6A, SEMA6D) and CD genes such as CD200. We also identified 52 genes progressively increasing during oocyte maturation, comprising CDC25A and SOCS7. CONCLUSION The identification of genes up and down regulated during oocyte maturation greatly improves our understanding of oocyte biology and will provide new markers that signal viable and competent oocytes. Furthermore, genes found expressed in cumulus cells are potential markers of granulosa cell tumors. PMID:16571642

  20. Broad Integration of Expression Maps and Co-Expression Networks Compassing Novel Gene Functions in the Brain

    PubMed Central

    Okamura-Oho, Yuko; Shimokawa, Kazuro; Nishimura, Masaomi; Takemoto, Satoko; Sato, Akira; Furuichi, Teiichi; Yokota, Hideo

    2014-01-01

    Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas. PMID:25382412

  1. GEOMetaCuration: a web-based application for accurate manual curation of Gene Expression Omnibus metadata

    PubMed Central

    Li, Zhao; Li, Jin; Yu, Peng

    2018-01-01

    Abstract Metadata curation has become increasingly important for biological discovery and biomedical research because a large amount of heterogeneous biological data is currently freely available. To facilitate efficient metadata curation, we developed an easy-to-use web-based curation application, GEOMetaCuration, for curating the metadata of Gene Expression Omnibus datasets. It can eliminate mechanical operations that consume precious curation time and can help coordinate curation efforts among multiple curators. It improves the curation process by introducing various features that are critical to metadata curation, such as a back-end curation management system and a curator-friendly front-end. The application is based on a commonly used web development framework of Python/Django and is open-sourced under the GNU General Public License V3. GEOMetaCuration is expected to benefit the biocuration community and to contribute to computational generation of biological insights using large-scale biological data. An example use case can be found at the demo website: http://geometacuration.yubiolab.org. Database URL: https://bitbucket.com/yubiolab/GEOMetaCuration PMID:29688376

  2. Application of community phylogenetic approaches to understand gene expression: differential exploration of venom gene space in predatory marine gastropods.

    PubMed

    Chang, Dan; Duda, Thomas F

    2014-06-05

    Predatory marine gastropods of the genus Conus exhibit substantial variation in venom composition both within and among species. Apart from mechanisms associated with extensive turnover of gene families and rapid evolution of genes that encode venom components ('conotoxins'), the evolution of distinct conotoxin expression patterns is an additional source of variation that may drive interspecific differences in the utilization of species' 'venom gene space'. To determine the evolution of expression patterns of venom genes of Conus species, we evaluated the expression of A-superfamily conotoxin genes of a set of closely related Conus species by comparing recovered transcripts of A-superfamily genes that were previously identified from the genomes of these species. We modified community phylogenetics approaches to incorporate phylogenetic history and disparity of genes and their expression profiles to determine patterns of venom gene space utilization. Less than half of the A-superfamily gene repertoire of these species is expressed, and only a few orthologous genes are coexpressed among species. Species exhibit substantially distinct expression strategies, with some expressing sets of closely related loci ('under-dispersed' expression of available genes) while others express sets of more disparate genes ('over-dispersed' expression). In addition, expressed genes show higher dN/dS values than either unexpressed or ancestral genes; this implies that expression exposes genes to selection and facilitates rapid evolution of these genes. Few recent lineage-specific gene duplicates are expressed simultaneously, suggesting that expression divergence among redundant gene copies may be established shortly after gene duplication. Our study demonstrates that venom gene space is explored differentially by Conus species, a process that effectively permits the independent and rapid evolution of venoms in these species.

  3. Finding gene regulatory network candidates using the gene expression knowledge base.

    PubMed

    Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

    2014-12-10

    Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

  4. Zipf's Law in Gene Expression

    NASA Astrophysics Data System (ADS)

    Furusawa, Chikara; Kaneko, Kunihiko

    2003-02-01

    Using data from gene expression databases on various organisms and tissues, including yeast, nematodes, human normal and cancer tissues, and embryonic stem cells, we found that the abundances of expressed genes exhibit a power-law distribution with an exponent close to -1; i.e., they obey Zipf’s law. Furthermore, by simulations of a simple model with an intracellular reaction network, we found that Zipf’s law of chemical abundance is a universal feature of cells where such a network optimizes the efficiency and faithfulness of self-reproduction. These findings provide novel insights into the nature of the organization of reaction dynamics in living cells.

  5. Validation of reference genes for quantifying changes in gene expression in virus-infected tobacco.

    PubMed

    Baek, Eseul; Yoon, Ju-Yeon; Palukaitis, Peter

    2017-10-01

    To facilitate quantification of gene expression changes in virus-infected tobacco plants, eight housekeeping genes were evaluated for their stability of expression during infection by one of three systemically-infecting viruses (cucumber mosaic virus, potato virus X, potato virus Y) or a hypersensitive-response-inducing virus (tobacco mosaic virus; TMV) limited to the inoculated leaf. Five reference-gene validation programs were used to establish the order of the most stable genes for the systemically-infecting viruses as ribosomal protein L25 > β-Tubulin > Actin, and the least stable genes Ubiquitin-conjugating enzyme (UCE) < PP2A < GAPDH. For local infection by TMV, the most stable genes were EF1α > Cysteine protease > Actin, and the least stable genes were GAPDH < PP2A < UCE. Using two of the most stable and the two least stable validated reference genes, three defense responsive genes were examined to compare their relative changes in gene expression caused by each virus. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Dlx homeobox gene family expression in osteoclasts.

    PubMed

    Lézot, F; Thomas, B L; Blin-Wakkach, C; Castaneda, B; Bolanos, A; Hotton, D; Sharpe, P T; Heymann, D; Carles, G F; Grigoriadis, A E; Berdal, A

    2010-06-01

    Skeletal growth and homeostasis require the finely orchestrated secretion of mineralized tissue matrices by highly specialized cells, balanced with their degradation by osteoclasts. Time- and site-specific expression of Dlx and Msx homeobox genes in the cells secreting these matrices have been identified as important elements in the regulation of skeletal morphology. Such specific expression patterns have also been reported in osteoclasts for Msx genes. The aim of the present study was to establish the expression patterns of Dlx genes in osteoclasts and identify their function in regulating skeletal morphology. The expression patterns of all Dlx genes were examined during the whole osteoclastogenesis using different in vitro models. The results revealed that Dlx1 and Dlx2 are the only Dlx family members with a possible function in osteoclastogenesis as well as in mature osteoclasts. Dlx5 and Dlx6 were detected in the cultures but appear to be markers of monocytes and their derivatives. In vivo, Dlx2 expression in osteoclasts was examined using a Dlx2/LacZ transgenic mouse. Dlx2 is expressed in a subpopulation of osteoclasts in association with tooth, brain, nerve, and bone marrow volumetric growths. Altogether the present data suggest a role for Dlx2 in regulation of skeletal morphogenesis via functions within osteoclasts. (c) 2010 Wiley-Liss, Inc.

  7. Sex-specific gene expression during asexual development of Neurospora crassa.

    PubMed

    Wang, Zheng; Kin, Koryu; López-Giráldez, Francesc; Johannesson, Hanna; Townsend, Jeffrey P

    2012-07-01

    The impact of loci that determine sexual identity upon the asexual, dominant stage of fungal life history has been well studied. To investigate their impact, expression differences between strains of different mating type during asexual development were assayed, with RNA sampled from otherwise largely isogenic mat A and mat a strains of Neurospora crassa at early, middle, and late clonal stages of development. We observed significant differences in overall gene expression between mating types across clonal development, especially at late development stages. The expression levels of mating-type genes and pheromone genes were assayed by reverse transcription and quantitative PCR, revealing expression of pheromone and receptor genes in strains of both mating types in all development stages, and revealing that mating type (mat) genes were increasingly expressed over the course of asexual development. Interestingly, among differentially expressed genes, the mat A genotype more frequently exhibited a higher expression level than mat a, and demonstrated greater transcriptional regulatory dynamism. Significant up-regulation of expression was observed for many late light-responsive genes at late asexual development stages. Further investigation of the impact of light and the roles of light response genes in asexual development of both mating types are warranted. Copyright © 2012 Elsevier Inc. All rights reserved.

  8. Codon usage and amino acid usage influence genes expression level.

    PubMed

    Paul, Prosenjit; Malakar, Arup Kumar; Chakraborty, Supriyo

    2018-02-01

    Highly expressed genes in any species differ in the usage frequency of synonymous codons. The relative recurrence of an event of the favored codon pair (amino acid pairs) varies between gene and genomes due to varying gene expression and different base composition. Here we propose a new measure for predicting the gene expression level, i.e., codon plus amino bias index (CABI). Our approach is based on the relative bias of the favored codon pair inclination among the genes, illustrated by analyzing the CABI score of the Medicago truncatula genes. CABI showed strong correlation with all other widely used measures (CAI, RCBS, SCUO) for gene expression analysis. Surprisingly, CABI outperforms all other measures by showing better correlation with the wet-lab data. This emphasizes the importance of the neighboring codons of the favored codon in a synonymous group while estimating the expression level of a gene.

  9. Profile of the genes expressed in the human peripheral retina, macula, and retinal pigment epithelium determined through serial analysis of gene expression (SAGE)

    PubMed Central

    Sharon, Dror; Blackshaw, Seth; Cepko, Constance L.; Dryja, Thaddeus P.

    2002-01-01

    We used the serial analysis of gene expression (SAGE) technique to catalogue and measure the relative levels of expression of the genes expressed in the human peripheral retina, macula, and retinal pigment epithelium (RPE) from one or both of two humans, aged 88 and 44 years. The cone photoreceptor contribution to all transcription in the retina was found to be similar in the macula versus the retinal periphery, whereas the rod contribution was greater in the periphery versus the macula. Genes encoding structural proteins for axons were found to be expressed at higher levels in the macula versus the retinal periphery, probably reflecting the large proportion of ganglion cells in the central retina. In comparison with the younger eye, the peripheral retina of the older eye had a substantially higher proportion of mRNAs from genes encoding proteins involved in iron metabolism or protection against oxidative damage and a substantially lower proportion of mRNAs from genes encoding proteins involved in rod phototransduction. These differences may reflect the difference in age between the two donors or merely interindividual variation. The RPE library had numerous previously unencountered tags, suggesting that this cell type has a large, idiosyncratic repertoire of expressed genes. Comparison of these libraries with 100 reported nonocular SAGE libraries revealed 89 retina-specific or enriched genes expressed at substantial levels, of which 14 are known to cause a retinal disease and 53 are RPE-specific genes. We expect that these libraries will serve as a resource for understanding the relative expression levels of genes in the retina and the RPE and for identifying additional disease genes. PMID:11756676

  10. Chemical Approaches to Control Gene Expression

    PubMed Central

    Gottesfeld, Joel M.; Turner, James M.; Dervan, Peter B.

    2000-01-01

    A current goal in molecular medicine is the development of new strategies to interfere with gene expression in living cells in the hope that novel therapies for human disease will result from these efforts. This review focuses on small-molecule or chemical approaches to manipulate gene expression by modulating either transcription of messenger RNA-coding genes or protein translation. The molecules under study include natural products, designed ligands, and compounds identified through functional screens of combinatorial libraries. The cellular targets for these molecules include DNA, messenger RNA, and the protein components of the transcription, RNA processing, and translational machinery. Studies with model systems have shown promise in the inhibition of both cellular and viral gene transcription and mRNA utilization. Moreover, strategies for both repression and activation of gene transcription have been described. These studies offer promise for treatment of diseases of pathogenic (viral, bacterial, etc.) and cellular origin (cancer, genetic diseases, etc.). PMID:11097426

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

    PubMed

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

    2005-10-01

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

  12. Gene Expression Profiling in the Hibernating Primate, Cheirogaleus Medius

    PubMed Central

    Faherty, Sheena L.; Villanueva-Cañas, José Luis; Klopfer, Peter H.; Albà, M. Mar; Yoder, Anne D.

    2016-01-01

    Hibernation is a complex physiological response that some mammalian species employ to evade energetic demands. Previous work in mammalian hibernators suggests that hibernation is activated not by a set of genes unique to hibernators, but by differential expression of genes that are present in all mammals. This question of universal genetic mechanisms requires further investigation and can only be tested through additional investigations of phylogenetically dispersed species. To explore this question, we use RNA-Seq to investigate gene expression dynamics as they relate to the varying physiological states experienced throughout the year in a group of primate hibernators—Madagascar’s dwarf lemurs (genus Cheirogaleus). In a novel experimental approach, we use longitudinal sampling of biological tissues as a method for capturing gene expression profiles from the same individuals throughout their annual hibernation cycle. We identify 90 candidate genes that have variable expression patterns when comparing two active states (Active 1 and Active 2) with a torpor state. These include genes that are involved in metabolic pathways, feeding behavior, and circadian rhythms, as might be expected to correlate with seasonal physiological state changes. The identified genes appear to be critical for maintaining the health of an animal that undergoes prolonged periods of metabolic depression concurrent with the hibernation phenotype. By focusing on these differentially expressed genes in dwarf lemurs, we compare gene expression patterns in previously studied mammalian hibernators. Additionally, by employing evolutionary rate analysis, we find that hibernation-related genes do not evolve under positive selection in hibernating species relative to nonhibernators. PMID:27412611

  13. Metadata Analysis of Phanerochaete chrysosporium Gene Expression Data Identified Common CAZymes Encoding Gene Expression Profiles Involved in Cellulose and Hemicellulose Degradation.

    PubMed

    Kameshwar, Ayyappa Kumar Sista; Qin, Wensheng

    2017-01-01

    In literature, extensive studies have been conducted on popular wood degrading white rot fungus, Phanerochaete chrysosporium about its lignin degrading mechanisms compared to the cellulose and hemicellulose degrading abilities. This study delineates cellulose and hemicellulose degrading mechanisms through large scale metadata analysis of P. chrysosporium gene expression data (retrieved from NCBI GEO) to understand the common expression patterns of differentially expressed genes when cultured on different growth substrates. Genes encoding glycoside hydrolase classes commonly expressed during breakdown of cellulose such as GH-5,6,7,9,44,45,48 and hemicellulose are GH-2,8,10,11,26,30,43,47 were found to be highly expressed among varied growth conditions including simple customized and complex natural plant biomass growth mediums. Genes encoding carbohydrate esterase class enzymes CE (1,4,8,9,15,16) polysaccharide lyase class enzymes PL-8 and PL-14, and glycosyl transferases classes GT (1,2,4,8,15,20,35,39,48) were differentially expressed in natural plant biomass growth mediums. Based on these results, P. chrysosporium, on natural plant biomass substrates was found to express lignin and hemicellulose degrading enzymes more than cellulolytic enzymes except GH-61 (LPMO) class enzymes, in early stages. It was observed that the fate of P. chrysosporium transcriptome is significantly affected by the wood substrate provided. We believe, the gene expression findings in this study plays crucial role in developing genetically efficient microbe with effective cellulose and hemicellulose degradation abilities.

  14. Anterior-posterior regionalized gene expression in the Ciona notochord.

    PubMed

    Reeves, Wendy; Thayer, Rachel; Veeman, Michael

    2014-04-01

    In the simple ascidian chordate Ciona, the signaling pathways and gene regulatory networks giving rise to initial notochord induction are largely understood and the mechanisms of notochord morphogenesis are being systematically elucidated. The notochord has generally been thought of as a non-compartmentalized or regionalized organ that is not finely patterned at the level of gene expression. Quantitative imaging methods have recently shown, however, that notochord cell size, shape, and behavior vary consistently along the anterior-posterior (AP) axis. Here we screen candidate genes by whole mount in situ hybridization for potential AP asymmetry. We identify 4 genes that show non-uniform expression in the notochord. Ezrin/radixin/moesin (ERM) is expressed more strongly in the secondary notochord lineage than the primary. CTGF is expressed stochastically in a subset of notochord cells. A novel calmodulin-like gene (BCamL) is expressed more strongly at both the anterior and posterior tips of the notochord. A TGF-β ortholog is expressed in a gradient from posterior to anterior. The asymmetries in ERM, BCamL, and TGF-β expression are evident even before the notochord cells have intercalated into a single-file column. We conclude that the Ciona notochord is not a homogeneous tissue but instead shows distinct patterns of regionalized gene expression. Copyright © 2013 Wiley Periodicals, Inc.

  15. Evaluation of Allelic Expression of Imprinted Genes in Adult Human Blood

    PubMed Central

    Frost, Jennifer M.; Monk, Dave; Stojilkovic-Mikic, Taita; Woodfine, Kathryn; Chitty, Lyn S.; Murrell, Adele; Stanier, Philip; Moore, Gudrun E.

    2010-01-01

    Background Imprinted genes are expressed from only one allele in a parent-of-origin dependent manner. Loss of imprinted (LOI) expression can result in a variety of human disorders and is frequently reported in cancer. Biallelic expression of imprinted genes in adult blood has been suggested as a useful biomarker and is currently being investigated in colorectal cancer. In general, the expression profiles of imprinted genes are well characterised during human and mouse fetal development, but not in human adults. Methodology/Principal Findings We investigated quantitative expression of 36 imprinted genes in adult human peripheral blood leukocytes obtained from healthy individuals. Allelic expression was also investigated in B and T lymphocytes and myeloid cells. We found that 21 genes were essentially undetectable in adult blood. Only six genes were demonstrably monoallelic, and most importantly, we found that nine genes were either biallelic or showed variable expression in different individuals. Separated leukocyte populations showed the same expression patterns as whole blood. Differential methylation at each of the imprinting control loci analysed was maintained, including regions that contained biallelically expressed genes. This suggests in some cases methylation has become uncoupled from its role in regulating gene expression. Conclusions/Significance We conclude that only a limited set of imprinted genes, including IGF2 and SNRPN, may be useful for LOI cancer biomarker studies. In addition, blood is not a good tissue to use for the discovery of new imprinted genes. Finally, lymphocyte DNA methylation status in the adult may not always be a reliable indicator of monoallelic gene expression. PMID:21042416

  16. DNA-Demethylase Regulated Genes Show Methylation-Independent Spatiotemporal Expression Patterns

    PubMed Central

    Schumann, Ulrike; Lee, Joanne; Kazan, Kemal; Ayliffe, Michael; Wang, Ming-Bo

    2017-01-01

    Recent research has indicated that a subset of defense-related genes is downregulated in the Arabidopsis DNA demethylase triple mutant rdd (ros1 dml2 dml3) resulting in increased susceptibility to the fungal pathogen Fusarium oxysporum. In rdd plants these downregulated genes contain hypermethylated transposable element sequences (TE) in their promoters, suggesting that this methylation represses gene expression in the mutant and that these sequences are actively demethylated in wild-type plants to maintain gene expression. In this study, the tissue-specific and pathogen-inducible expression patterns of rdd-downregulated genes were investigated and the individual role of ROS1, DML2, and DML3 demethylases in these spatiotemporal regulation patterns was determined. Large differences in defense gene expression were observed between pathogen-infected and uninfected tissues and between root and shoot tissues in both WT and rdd plants, however, only subtle changes in promoter TE methylation patterns occurred. Therefore, while TE hypermethylation caused decreased gene expression in rdd plants it did not dramatically effect spatiotemporal gene regulation, suggesting that this latter regulation is largely methylation independent. Analysis of ros1-3, dml2-1, and dml3-1 single gene mutant lines showed that promoter TE hypermethylation and defense-related gene repression was predominantly, but not exclusively, due to loss of ROS1 activity. These data demonstrate that DNA demethylation of TE sequences, largely by ROS1, promotes defense-related gene expression but does not control spatiotemporal expression in Arabidopsis. Summary: Ros1-mediated DNA demethylation of promoter transposable elements is essential for activation of defense-related gene expression in response to fungal infection in Arabidopsis thaliana. PMID:28894455

  17. Expression pattern of circadian genes and steroidogenesis-related genes after testosterone stimulation in the human ovary.

    PubMed

    Chen, Minghui; Xu, Yanwen; Miao, Benyu; Zhao, Hui; Luo, Lu; Shi, Huijuan; Zhou, Canquan

    2016-09-10

    Previous studies have shown that circadian genes might be involved in the development of polycystic ovarian syndrome (PCOS). Hyperandrogenism is a hallmark feature of PCOS. However, the effect of hyperandrogenism on circadian gene expression in human granulosa cells is unknown, and the general expression pattern of circadian genes in the human ovary is unclear. Expression of the circadian proteins CLOCK and PER2 in human ovaries was observed by immunohistochemistry. The mRNA expression patterns of the circadian genes CLOCK, PER2, and BMAL1, and the steroidogenesis-related genes STAR, CYP11A1, HSD3B2, and CYP19A1 in cultured human luteinized granulosa cells were analyzed over the course of 48 h after testosterone treatment by quantitative polymerase chain reaction. Immunostaining of CLOCK and PER2 protein was detected in the granulosa cells of dominant antral follicles but was absent in the primordial, primary, or preantral follicles of human ovaries. After testosterone stimulation, expression of PER2 showed an oscillating pattern, with two peaks occurring at the 24th and 44th hours; expression of CLOCK increased significantly to the peak at the 24th hour, whereas expression of BMAL1 did not change significantly over time in human luteinized granulosa cells. Among the four steroidogenesis-related genes evaluated, only STAR displayed an oscillating expression pattern with two peaks occurring at the 24th and 40th hours after testosterone stimulation. Circadian genes are expressed in the dominant antral follicles of the human ovary. Oscillating expression of the circadian gene PER2 can be induced by testosterone in human granulosa cells in vitro. Expression of STAR also displayed an oscillating pattern after testosterone stimulation. Our results indicate a potential relationship between the circadian clock and steroidogenesis in the human ovary, and demonstrate the effect of testosterone on circadian gene expression in granulosa cells.

  18. The mouse forkhead gene Foxp2 modulates expression of the lung genes.

    PubMed

    Yang, Zhi; Hikosaka, Keisuke; Sharkar, Mohammad T K; Tamakoshi, Tomoki; Chandra, Abhishek; Wang, Bo; Itakura, Tatsuo; Xue, XiaoDong; Uezato, Tadayoshi; Kimura, Wataru; Miura, Naoyuki

    2010-07-03

    Foxp2 is expressed in the lung during mouse development. A monoclonal anti-mouse Foxp2 antibody was created to determine the expression pattern in the developing lung. Next, transcriptional control of two lung genes, CC10 and surfactant protein C (SPC) genes, by Foxp2 was investigated in H441 and A549 cells. Thirdly, expression patterns of Foxp2 and Foxf2 were compared in the developing lung. Finally, Foxp2 expression was determined in the Foxf2-null mice. Immunohistochemical staining and in situ hybridization were applied to the sections of lungs in the developing embryos. Monoclonal anti-Foxp2 antibody demonstrated that Foxp2 was expressed in the bronchial epithelium at E10.5 and its expression became restricted to the distal portion of the elongating bronchiolar epithelium and finally to type II alveolar epithelial cells around birth and in the adult. Foxp2 activated the SPC gene promoter in the presence of Nkx2.1 in A549 cells while it repressed the CC10 gene promoter in H441 cells. Next, the expression domains of the Foxp2 and Foxf2 were found to be exclusive in the lung. Finally, the expression of Foxp2 did not change in the lung of Foxf2-null mice. The Foxp2 protein is expressed in the growing distal edge of airway epithelium. When the bronchiolus elongates, Foxp2 suppresses CC10 expression. When the lung alveolus is formed, Foxp2 modulates the Nkx2.1-mediated SPC expression in type II alveolar cells. Foxp2 and Foxf2 independently play distinct roles in the alveoli and the mesenchyme, respectively. Copyright (c) 2010 Elsevier Inc. All rights reserved.

  19. Using RNA-Seq data to select refence genes for normalizing gene expression in apple roots

    USDA-ARS?s Scientific Manuscript database

    Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for t...

  20. The complexity of gene expression dynamics revealed by permutation entropy

    PubMed Central

    2010-01-01

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

  1. Gene Expression in Parp1 Deficient Mice Exposed to a Median Lethal Dose of Gamma Rays.

    PubMed

    Kumar, M A Suresh; Laiakis, Evagelia C; Ghandhi, Shanaz A; Morton, Shad R; Fornace, Albert J; Amundson, Sally A

    2018-05-10

    There is a current interest in the development of biodosimetric methods for rapidly assessing radiation exposure in the wake of a large-scale radiological event. This work was initially focused on determining the exposure dose to an individual using biological indicators. Gene expression signatures show promise for biodosimetric application, but little is known about how these signatures might translate for the assessment of radiological injury in radiosensitive individuals, who comprise a significant proportion of the general population, and who would likely require treatment after exposure to lower doses. Using Parp1 -/- mice as a model radiation-sensitive genotype, we have investigated the effect of this DNA repair deficiency on the gene expression response to radiation. Although Parp1 is known to play general roles in regulating transcription, the pattern of gene expression changes observed in Parp1 -/- mice 24 h postirradiation to a LD 50/30 was remarkably similar to that in wild-type mice after exposure to LD 50/30 . Similar levels of activation of both the p53 and NFκB radiation response pathways were indicated in both strains. In contrast, exposure of wild-type mice to a sublethal dose that was equal to the Parp1 -/- LD 50/30 , which resulted in a lower magnitude gene expression response. Thus, Parp1 -/- mice displayed a heightened gene expression response to radiation, which was more similar to the wild-type response to an equitoxic dose than to an equal absorbed dose. Gene expression classifiers trained on the wild-type data correctly identified all wild-type samples as unexposed, exposed to a sublethal dose or exposed to an LD 50/30 . All unexposed samples from Parp1 -/- mice were also correctly classified with the same gene set, and 80% of irradiated Parp1 -/- samples were identified as exposed to an LD 50/30 . The results of this study suggest that, at least for some pathways that may influence radiosensitivity in humans, specific gene expression

  2. 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.

  3. ArraySolver: an algorithm for colour-coded graphical display and Wilcoxon signed-rank statistics for comparing microarray gene expression data.

    PubMed

    Khan, Haseeb Ahmad

    2004-01-01

    The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann-Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n < or = 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform.

  4. ArraySolver: An Algorithm for Colour-Coded Graphical Display and Wilcoxon Signed-Rank Statistics for Comparing Microarray Gene Expression Data

    PubMed Central

    2004-01-01

    The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann–Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n ≤ 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform. PMID:18629036

  5. 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.

  6. Ebola virus infection induces irregular dendritic cell gene expression.

    PubMed

    Melanson, Vanessa R; Kalina, Warren V; Williams, Priscilla

    2015-02-01

    Filoviruses subvert the human immune system in part by infecting and replicating in dendritic cells (DCs). Using gene arrays, a phenotypic profile of filovirus infection in human monocyte-derived DCs was assessed. Monocytes from human donors were cultured in GM-CSF and IL-4 and were infected with Ebola virus Kikwit variant for up to 48 h. Extracted DC RNA was analyzed on SuperArray's Dendritic and Antigen Presenting Cell Oligo GEArray and compared to uninfected controls. Infected DCs exhibited increased expression of cytokine, chemokine, antiviral, and anti-apoptotic genes not seen in uninfected controls. Significant increases of intracellular antiviral and MHC I and II genes were also noted in EBOV-infected DCs. However, infected DCs failed to show any significant difference in co-stimulatory T-cell gene expression from uninfected DCs. Moreover, several chemokine genes were activated, but there was sparse expression of chemokine receptors that enabled activated DCs to home to lymph nodes. Overall, statistically significant expression of several intracellular antiviral genes was noted, which may limit viral load but fails to stop replication. EBOV gene expression profiling is of vital importance in understanding pathogenesis and devising novel therapeutic treatments such as small-molecule inhibitors.

  7. Differential gene expression in queen–worker caste determination in bumble-bees

    PubMed Central

    Pereboom, Jeffrey J. M; Jordan, William C; Sumner, Seirian; Hammond, Robert L; Bourke, Andrew F. G

    2005-01-01

    Investigating how differential gene expression underlies caste determination in the social Hymenoptera is central to understanding how variation in gene expression underlies adaptive phenotypic diversity. We investigated for the first time the association between differential gene expression and queen–worker caste determination in the bumble-bee Bombus terrestris. Using suppression subtractive hybridization we isolated 12 genes that were differentially expressed in queen- and worker-destined larvae. We found that the sets of genes underlying caste differences in larvae and adults failed to overlap greatly. We also found that B. terrestris shares some of the genes whose differential expression is associated with caste determination in the honeybee, Apis mellifera, but their expression patterns were not identical. Instead, we found B. terrestris to exhibit a novel pattern, whereby most genes upregulated (i.e. showing relatively higher levels of expression) in queen-destined larvae early in development were upregulated in worker-destined larvae late in development. Overall, our results suggest that caste determination in B. terrestris involves a difference not so much in the identity of genes expressed by queen- and worker-destined larvae, but primarily in the relative timing of their expression. This conclusion is of potential importance in the further study of phenotypic diversification via differential gene expression. PMID:16024376

  8. Comparative studies of gene expression and the evolution of gene regulation

    PubMed Central

    Romero, Irene Gallego; Ruvinsky, Ilya; Gilad, Yoav

    2014-01-01

    The hypothesis that differences in gene regulation play an important role in speciation and adaptation is more than 40 years old. With the advent of new sequencing technologies, we are able to characterize and study gene expression levels and associated regulatory mechanisms in a large number of individuals and species at unprecedented resolution and scale. We have thus gained new insights into the evolutionary pressures that shape gene expression levels, as well as developed an appreciation for the relative importance of evolutionary changes in different regulatory genetic and epigenetic mechanisms. The current challenge is to link gene regulatory changes to adaptive evolution of complex phenotypes. Here we mainly focus on comparative studies in primates, and how they are complemented by studies in model organisms. PMID:22705669

  9. Gene expression in obstetric antiphospholipid syndrome: a systematic review.

    PubMed

    Muhammad Aliff, M; Muhammad Shazwan, S; Nur Fariha, M M; Hayati, A R; Nur Syahrina, A R; Maizatul Azma, M; Nazefah, A H; Jameela, S; Asral Wirda, A A

    2016-12-01

    Antiphospholipid syndrome (APS) is a multisystem disease that may present as venous or arterial thrombosis and/or pregnancy complications with the presence of antiphospholipid antibodies. Until today, heterogeneity of pathogenic mechanism fits well with various clinical manifestations. Moreover, previous studies have indicated that genes are differentially expressed between normal and in the disease state. Hence, this study systematically searched the literature on human gene expression that was differentially expressed in Obstetric APS. Electronic search was performed until 31st March 2015 through PubMed and Embase databases; where the following Medical Subject Heading (MeSH) terms were used and they had been specified as the primary focus of the articles; gene, antiphospholipid, obstetric, and pregnancy in the title or abstract. From 502 studies retrieved from the search, only original publications that had performed gene expression analyses of human placental tissue that reported on differentially expressed gene in pregnancies with Obstetric APS were included. Two reviewers independently scrutinized the titles and the abstracts before examining the eligibility of studies that met the inclusion criteria. For each study; diagnostic criteria for APS, method for analysis, and the gene signature were extracted independently by two reviewers. The genes listed were further analysed with the DAVID and the KEGG pathways. Three eligible gene expression studies involving obstetric APS, comprising the datasets on gene expression, were identified. All three studies showed a reduction in transcript expression on PRL, STAT5, TF, DAF, ABCA1, and HBEGF in Obstetric APS. The high enrichment score for functionality in DAVID had been positive regulation of cell proliferation. Meanwhile, pertaining to the KEGG pathway, two pathways were associated with some of the listed genes, which were ErBb signalling pathway and JAK-STAT signalling pathway. Ultimately, studies on a genetic level

  10. Differentially expressed genes in nonsmall cell lung cancer: expression profiling of cancer-related genes in squamous cell lung cancer.

    PubMed

    Kettunen, Eeva; Anttila, Sisko; Seppänen, Jouni K; Karjalainen, Antti; Edgren, Henrik; Lindström, Irmeli; Salovaara, Reijo; Nissén, Anna-Maria; Salo, Jarmo; Mattson, Karin; Hollmén, Jaakko; Knuutila, Sakari; Wikman, Harriet

    2004-03-01

    The expression patterns of cancer-related genes in 13 cases of squamous cell lung cancer (SCC) were characterized and compared with those in normal lung tissue and 13 adenocarcinomas (AC), the other major type of nonsmall cell lung cancer (NSCLC). cDNA array was used to screen the gene expression levels and the array results were verified using a real-time reverse-transcriptase-polymerase chain reaction (RT-PCR). Thirty-nine percent of the 25 most upregulated and the 25 most downregulated genes were common to SCC and AC. Of these genes, DSP, HMGA1 (alias HMGIY), TIMP1, MIF, CCNB1, TN, MMP11, and MMP12 were upregulated and COPEB (alias CPBP), TYROBP, BENE, BMPR2, SOCS3, TIMP3, CAV1, and CAV2 were downregulated. The expression levels of several genes from distinct protein families (cytokeratins and hemidesmosomal proteins) were markedly increased in SCC compared with AC and normal lung. In addition, several genes, overexpressed in SCC, such as HMGA1, CDK4, IGFBP3, MMP9, MMP11, MMP12, and MMP14, fell into distinct chromosomal loci, which we have detected as gained regions on the basis of comparative genomic hybridization data. Our study revealed new candidate genes involved in NSCLC.

  11. Comprehensive evaluation of AmpliSeq transcriptome, a novel targeted whole transcriptome RNA sequencing methodology for global gene expression analysis.

    PubMed

    Li, Wenli; Turner, Amy; Aggarwal, Praful; Matter, Andrea; Storvick, Erin; Arnett, Donna K; Broeckel, Ulrich

    2015-12-16

    Whole transcriptome sequencing (RNA-seq) represents a powerful approach for whole transcriptome gene expression analysis. However, RNA-seq carries a few limitations, e.g., the requirement of a significant amount of input RNA and complications led by non-specific mapping of short reads. The Ion AmpliSeq Transcriptome Human Gene Expression Kit (AmpliSeq) was recently introduced by Life Technologies as a whole-transcriptome, targeted gene quantification kit to overcome these limitations of RNA-seq. To assess the performance of this new methodology, we performed a comprehensive comparison of AmpliSeq with RNA-seq using two well-established next-generation sequencing platforms (Illumina HiSeq and Ion Torrent Proton). We analyzed standard reference RNA samples and RNA samples obtained from human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs). Using published data from two standard RNA reference samples, we observed a strong concordance of log2 fold change for all genes when comparing AmpliSeq to Illumina HiSeq (Pearson's r = 0.92) and Ion Torrent Proton (Pearson's r = 0.92). We used ROC, Matthew's correlation coefficient and RMSD to determine the overall performance characteristics. All three statistical methods demonstrate AmpliSeq as a highly accurate method for differential gene expression analysis. Additionally, for genes with high abundance, AmpliSeq outperforms the two RNA-seq methods. When analyzing four closely related hiPSC-CM lines, we show that both AmpliSeq and RNA-seq capture similar global gene expression patterns consistent with known sources of variations. Our study indicates that AmpliSeq excels in the limiting areas of RNA-seq for gene expression quantification analysis. Thus, AmpliSeq stands as a very sensitive and cost-effective approach for very large scale gene expression analysis and mRNA marker screening with high accuracy.

  12. 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

  13. Variability of cytokine gene expression in intestinal tissue and the impact of normalization with the use of reference genes.

    PubMed

    McGowan, Ian; Janocko, Laura; Burneisen, Shaun; Bhat, Anand; Richardson-Harman, Nicola

    2015-01-01

    To determine the intra- and inter-subject variability of mucosal cytokine gene expression in rectal biopsies from healthy volunteers and to screen cytokine and chemokine mRNA as potential biomarkers of mucosal inflammation. Rectal biopsies were collected from 8 participants (3 biopsies per participant) and 1 additional participant (10 biopsies). Quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to quantify IL-1β, IL-6, IL-12p40, IL-8, IFN-γ, MIP-1α, MIP-1β, RANTES, and TNF-α gene expression in the rectal tissue. The intra-assay, inter-biopsy and inter-subject variance was measured in the eight participants. Bootstrap re-sampling of the biopsy measurements was performed to determine the accuracy of gene expression data obtained for 10 biopsies obtained from one participant. Cytokines were both non-normalized and normalized using four reference genes (GAPDH, β-actin, β2 microglobulin, and CD45). Cytokine measurement accuracy was increased with the number of biopsy samples, per person; four biopsies were typically needed to produce a mean result within a 95% confidence interval of the subject's cytokine level approximately 80% of the time. Intra-assay precision (% geometric standard deviation) ranged between 8.2 and 96.9 with high variance between patients and even between different biopsies from the same patient. Variability was not greatly reduced with the use of reference genes to normalize data. The number of biopsy samples required to provide an accurate result varied by target although 4 biopsy samples per subject and timepoint, provided for >77% accuracy across all targets tested. Biopsies within the same subjects and between subjects had similar levels of variance while variance within a biopsy (intra-assay) was generally lower. Normalization of inflammatory cytokines against reference genes failed to consistently reduce variance. The accuracy and reliability of mRNA expression of inflammatory cytokines will set a ceiling

  14. Functional clustering of time series gene expression data by Granger causality

    PubMed Central

    2012-01-01

    Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

  15. Gene and enhancer trap tagging of vascular-expressed genes in poplar trees

    Treesearch

    Andrew Groover; Joseph R. Fontana; Gayle Dupper; Caiping Ma; Robert Martienssen; Steven Strauss; Richard Meilan

    2004-01-01

    We report a gene discovery system for poplar trees based on gene and enhancer traps. Gene and enhancer trap vectors carrying the β-glucuronidase (GUS) reporter gene were inserted into the poplar genome via Agrobacterium tumefaciens transformation, where they reveal the expression pattern of genes at or near the insertion sites. Because GUS...

  16. Gene duplication, tissue-specific gene expression and sexual conflict in stalk-eyed flies (Diopsidae).

    PubMed

    Baker, Richard H; Narechania, Apurva; Johns, Philip M; Wilkinson, Gerald S

    2012-08-19

    Gene duplication provides an essential source of novel genetic material to facilitate rapid morphological evolution. Traits involved in reproduction and sexual dimorphism represent some of the fastest evolving traits in nature, and gene duplication is intricately involved in the origin and evolution of these traits. Here, we review genomic research on stalk-eyed flies (Diopsidae) that has been used to examine the extent of gene duplication and its role in the genetic architecture of sexual dimorphism. Stalk-eyed flies are remarkable because of the elongation of the head into long stalks, with the eyes and antenna laterally displaced at the ends of these stalks. Many species are strongly sexually dimorphic for eyespan, and these flies have become a model system for studying sexual selection. Using both expressed sequence tag and next-generation sequencing, we have established an extensive database of gene expression in the developing eye-antennal imaginal disc, the adult head and testes. Duplicated genes exhibit narrower expression patterns than non-duplicated genes, and the testes, in particular, provide an abundant source of gene duplication. Within somatic tissue, duplicated genes are more likely to be differentially expressed between the sexes, suggesting gene duplication may provide a mechanism for resolving sexual conflict.

  17. Gene duplication, tissue-specific gene expression and sexual conflict in stalk-eyed flies (Diopsidae)

    PubMed Central

    Baker, Richard H.; Narechania, Apurva; Johns, Philip M.; Wilkinson, Gerald S.

    2012-01-01

    Gene duplication provides an essential source of novel genetic material to facilitate rapid morphological evolution. Traits involved in reproduction and sexual dimorphism represent some of the fastest evolving traits in nature, and gene duplication is intricately involved in the origin and evolution of these traits. Here, we review genomic research on stalk-eyed flies (Diopsidae) that has been used to examine the extent of gene duplication and its role in the genetic architecture of sexual dimorphism. Stalk-eyed flies are remarkable because of the elongation of the head into long stalks, with the eyes and antenna laterally displaced at the ends of these stalks. Many species are strongly sexually dimorphic for eyespan, and these flies have become a model system for studying sexual selection. Using both expressed sequence tag and next-generation sequencing, we have established an extensive database of gene expression in the developing eye-antennal imaginal disc, the adult head and testes. Duplicated genes exhibit narrower expression patterns than non-duplicated genes, and the testes, in particular, provide an abundant source of gene duplication. Within somatic tissue, duplicated genes are more likely to be differentially expressed between the sexes, suggesting gene duplication may provide a mechanism for resolving sexual conflict. PMID:22777023

  18. Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

    PubMed

    Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

    2018-04-23

    Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis

  19. Self-Expression on Social Media: Do Tweets Present Accurate and Positive Portraits of Impulsivity, Self-Esteem, and Attachment Style?

    PubMed

    Orehek, Edward; Human, Lauren J

    2017-01-01

    Self-expression values are at an all-time high, and people are increasingly relying upon social media platforms to express themselves positively and accurately. We examined whether self-expression on the social media platform Twitter elicits positive and accurate social perceptions. Eleven perceivers rated 128 individuals (targets; total dyadic impressions = 1,408) on their impulsivity, self-esteem, and attachment style, based solely on the information provided in targets' 10 most recent tweets. Targets were on average perceived normatively and with distinctive self-other agreement, indicating both positive and accurate social perceptions. There were also individual differences in how positively and accurately targets were perceived, which exploratory analyses indicated may be partially driven by differential word usage, such as the use of positive emotion words and self- versus other-focus. This study demonstrates that self-expression on social media can elicit both positive and accurate perceptions and begins to shed light on how to curate such perceptions.

  20. 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

  1. Hypergravity-induced changes in gene expression in Arabidopsis hypocotyls

    NASA Astrophysics Data System (ADS)

    Yoshioka, R.; Soga, K.; Wakabayashi, K.; Takeba, G.; Hoson, T.

    2003-05-01

    Under hypergravity conditions, the cell wall of stem organs becomes mechanically rigid and elongation growth is suppressed, which can be recognized as the mechanism for plants to resist gravitational force. The changes in gene expression by hypergravity treatment were analyzed in Arabidopsis hypocotyls by the differential display method, for identifying genes involved in hypergravity-induced growth suppression. Sixty-two cDNA clones were expressed differentially between the control and 300 g conditions: the expression levels of 39 clones increased, whereas those of 23 clones decreased under hypergravity conditions. Sequence analysis and database searching revealed that 12 clones, 9 up-regulated and 3 down-regulated, have homology to known proteins. The expression of these genes was further analyzed using RT-PCR. Finally, six genes were confirmed to be up-regulated by hypergravity. One of such genes encoded 3-hydroxy-3-methylglutaryl-Coenzyme A reductase (HMGR), which catalyzes a reaction producing mevalonic acid, a key precursor ofterpenoids such as membrane sterols and several types of hormones. The expression of HMGR gene increased within several hours after hypergravity treatment. Also, compactin, an inhibitor of HMGR, prevented hypergravity-induced growth suppression, suggesting that HMGR is involved in suppression of Arabidopsis hypocotyl growth by hypergravity. In addition, hypergravity increased the expression levels of genes encoding CCR1 and ERD15, which were shown to take part in the signaling pathway of environmental stimuli such as temperature and water, and those of the α-tubulin gene. These genes may be involved in a series of cellular events leading to growth suppression of stem organs under hypergravity conditions.

  2. Genes Expressed During Fruiting Body Formation of Agrocybe cylindracea

    PubMed Central

    Shim, Sung Mi; Kim, Sang Beom; Kim, Hey Young; Rho, Hyun-Su; Lee, Hyun Sook; Lee, Min Woong; Lee, U Youn; Im, Kyung Hoan

    2006-01-01

    Agrocybe cylindracea, an edible mushroom belonging to Bolbitiaceae, Agaricales, is widely used as invaluable medicinal material in the oriental countries. This study was initiated to find the genes expressed during the fruiting body formation of A. cylindracea. The cDNAs expressed differentially during fruiting body morphogenesis of A. cylindracea were isolated through subtractive hybridization between vegetative mycelia and fruiting bodies. The cDNAs expressed in the fruiting body morphogenesis of A. cylindracea were cloned and twenty genes were identified. Eleven were homologous to genes of known functions, three were homologous to genes in other organism without any function known. Six were completely novel genes specific to A. cylindracea so far examined. Some genes with known functions were a pleurotolysin, a self-assembling poreforming cytolysins; Aa-Pri1 and Pir2p, specifically induced genes during fruiting initiation of other mushroom, Agrocybe aegerita; an amino acid permease; a cytochrome P450; a MADS-box gene; a peptidylprolyl isomerase; and a serine proteinase. For other clones, no clear function was annotated so far. We believe the first report of the differentially expressed genes in fruiting process of A. cylindracea will be great helps for further research. PMID:24039501

  3. Dynamic changes in gene expression during human trophoblast differentiation.

    PubMed

    Handwerger, Stuart; Aronow, Bruce

    2003-01-01

    The genetic program that directs human placental differentiation is poorly understood. In a recent study, we used DNA microarray analyses to determine genes that are dynamically regulated during human placental development in an in vitro model system in which highly purified cytotrophoblast cells aggregate spontaneously and fuse to form a multinucleated syncytium that expresses placental lactogen, human chorionic gonadotropin, and other proteins normally expressed by fully differentiated syncytiotrophoblast cells. Of the 6918 genes present on the Incyte Human GEM V microarray that we analyzed over a 9-day period, 141 were induced and 256 were downregulated by more than 2-fold. The dynamically regulated genes fell into nine distinct kinetic patterns of induction or repression, as detected by the K-means algorithm. Classifying the genes according to functional characteristics, the regulated genes could be divided into six overall categories: cell and tissue structural dynamics, cell cycle and apoptosis, intercellular communication, metabolism, regulation of gene expression, and expressed sequence tags and function unknown. Gene expression changes within key functional categories were tightly coupled to the morphological changes that occurred during trophoblast differentiation. Within several key gene categories (e.g., cell and tissue structure), many genes were strongly activated, while others with related function were strongly repressed. These findings suggest that trophoblast differentiation is augmented by "categorical reprogramming" in which the ability of induced genes to function is enhanced by diminished synthesis of other genes within the same category. We also observed categorical reprogramming in human decidual fibroblasts decidualized in vitro in response to progesterone, estradiol, and cyclic AMP. While there was little overlap between genes that are dynamically regulated during trophoblast differentiation versus decidualization, many of the categories

  4. Expression of HES and HEY genes in infantile hemangiomas.

    PubMed

    Adepoju, Omotinuwe; Wong, Alvin; Kitajewski, Alex; Tong, Karen; Boscolo, Elisa; Bischoff, Joyce; Kitajewski, Jan; Wu, June K

    2011-08-11

    Infantile hemangiomas (IHs) are the most common benign tumor of infancy, yet their pathogenesis is poorly understood. IHs are believed to originate from a progenitor cell, the hemangioma stem cell (HemSC). Recent studies by our group showed that NOTCH proteins and NOTCH ligands are expressed in hemangiomas, indicating Notch signaling may be active in IHs. We sought to investigate downstream activation of Notch signaling in hemangioma cells by evaluating the expression of the basic HLH family proteins, HES/HEY, in IHs. HemSCs and hemangioma endothelial cells (HemECs) are isolated from freshly resected hemangioma specimens. Quantitative RT-PCR was performed to probe for relative gene transcript levels (normalized to beta-actin). Immunofluorescence was performed to evaluate protein expression. Co-localization studies were performed with CD31 (endothelial cells) and NOTCH3 (peri-vascular, non-endothelial cells). HemSCs were treated with the gamma secretase inhibitor (GSI) Compound E, and gene transcript levels were quantified with real-time PCR. HEY1, HEYL, and HES1 are highly expressed in HemSCs, while HEY2 is highly expressed in HemECs. Protein expression evaluation by immunofluorescence confirms that HEY2 is expressed by HemECs (CD31+ cells), while HEY1, HEYL, and HES1 are more widely expressed and mostly expressed by perivascular cells of hemangiomas. Inhibition of Notch signaling by addition of GSI resulted in down-regulation of HES/HEY genes. HES/HEY genes are expressed in IHs in cell type specific patterns; HEY2 is expressed in HemECs and HEY1, HEYL, HES1 are expressed in HemSCs. This pattern suggests that HEY/HES genes act downstream of Notch receptors that function in distinct cell types of IHs. HES/HEY gene transcripts are decreased with the addition of a gamma-secretase inhibitor, Compound E, demonstrating that Notch signaling is active in infantile hemangioma cells.

  5. Monoallelic expression of the human FOXP2 speech gene

    PubMed Central

    Adegbola, Abidemi A.; Cox, Gerald F.; Bradshaw, Elizabeth M.; Hafler, David A.; Gimelbrant, Alexander; Chess, Andrew

    2015-01-01

    The recent descriptions of widespread random monoallelic expression (RMAE) of genes distributed throughout the autosomal genome indicate that there are more genes subject to RMAE on autosomes than the number of genes on the X chromosome where X-inactivation dictates RMAE of X-linked genes. Several of the autosomal genes that undergo RMAE have independently been implicated in human Mendelian disorders. Thus, parsing the relationship between allele-specific expression of these genes and disease is of interest. Mutations in the human forkhead box P2 gene, FOXP2, cause developmental verbal dyspraxia with profound speech and language deficits. Here, we show that the human FOXP2 gene undergoes RMAE. Studying an individual with developmental verbal dyspraxia, we identify a deletion 3 Mb away from the FOXP2 gene, which impacts FOXP2 gene expression in cis. Together these data suggest the intriguing possibility that RMAE impacts the haploinsufficiency phenotypes observed for FOXP2 mutations. PMID:25422445

  6. Monoallelic expression of the human FOXP2 speech gene.

    PubMed

    Adegbola, Abidemi A; Cox, Gerald F; Bradshaw, Elizabeth M; Hafler, David A; Gimelbrant, Alexander; Chess, Andrew

    2015-06-02

    The recent descriptions of widespread random monoallelic expression (RMAE) of genes distributed throughout the autosomal genome indicate that there are more genes subject to RMAE on autosomes than the number of genes on the X chromosome where X-inactivation dictates RMAE of X-linked genes. Several of the autosomal genes that undergo RMAE have independently been implicated in human Mendelian disorders. Thus, parsing the relationship between allele-specific expression of these genes and disease is of interest. Mutations in the human forkhead box P2 gene, FOXP2, cause developmental verbal dyspraxia with profound speech and language deficits. Here, we show that the human FOXP2 gene undergoes RMAE. Studying an individual with developmental verbal dyspraxia, we identify a deletion 3 Mb away from the FOXP2 gene, which impacts FOXP2 gene expression in cis. Together these data suggest the intriguing possibility that RMAE impacts the haploinsufficiency phenotypes observed for FOXP2 mutations.

  7. Assessment of Normal Variability in Peripheral Blood Gene Expression

    DOE PAGES

    Campbell, Catherine; Vernon, Suzanne D.; Karem, Kevin L.; ...

    2002-01-01

    Peripheral blood is representative of many systemic processes and is an ideal sample for expression profiling of diseases that have no known or accessible lesion. Peripheral blood is a complex mixture of cell types and some differences in peripheral blood gene expression may reflect the timing of sample collection rather than an underlying disease process. For this reason, it is important to assess study design factors that may cause variability in gene expression not related to what is being analyzed. Variation in the gene expression of circulating peripheral blood mononuclear cells (PBMCs) from three healthy volunteers sampled three times onemore » day each week for one month was examined for 1,176 genes printed on filter arrays. Less than 1% of the genes showed any variation in expression that was related to the time of collection, and none of the changes were noted in more than one individual. These results suggest that observed variation was due to experimental variability.« less

  8. Estradiol-induced gene expression in largemouth bass (Micropterus salmoides)

    USGS Publications Warehouse

    Bowman, C.J.; Kroll, K.J.; Gross, T.G.; Denslow, N.D.

    2002-01-01

    Vitellogenin (Vtg) and estrogen receptor (ER) gene expression levels were measured in largemouth bass to evaluate the activation of the ER-mediated pathway by estradiol (E2). Single injections of E2 ranging from 0.0005 to 5 mg/kg up-regulated plasma Vtg in a dose-dependent manner. Vtg and ER mRNAs were measured using partial cDNA sequences corresponding to the C-terminal domain for Vtg and the ligand-binding domain of ER?? sequences. After acute E2-exposures (2 mg/kg), Vtg and ER mRNAs and plasma Vtg levels peaked after 2 days. The rate of ER mRNA accumulation peaked 36-42 h earlier than Vtg mRNA. The expression window for ER defines the primary response to E2 in largemouth bass and that for Vtg a delayed primary response. The specific effect of E2 on other estrogen-regulated genes was tested during these same time windows using differential display RT-PCR. Specific up-regulated genes that are expressed in the same time window as Vtg were ERp72 (a membrane-bound disulfide isomerase) and a gene with homology to an expressed gene identified in zebrafish. Genes that were expressed in a pattern that mimics the ER include the gene for zona radiata protein ZP2, and a gene with homology to an expressed gene found in winter flounder. One gene for fibrinogen ?? was down-regulated and an unidentified gene was transiently up-regulated after 12 h of exposure and returned to basal levels by 48 h. Taken together these studies indicate that the acute molecular response to E2 involves a complex network of responses over time. ?? 2002 Elsevier Science Ireland Ltd. All rights reserved.

  9. Gene expression correlates of postinfective fatigue syndrome after infectious mononucleosis.

    PubMed

    Cameron, Barbara; Galbraith, Sally; Zhang, Yun; Davenport, Tracey; Vollmer-Conna, Ute; Wakefield, Denis; Hickie, Ian; Dunsmuir, William; Whistler, Toni; Vernon, Suzanne; Reeves, William C; Lloyd, Andrew R

    2007-07-01

    Infectious mononucleosis (IM) commonly triggers a protracted postinfective fatigue syndrome (PIFS) of unknown pathogenesis. Seven subjects with PIFS with 6 or more months of disabling symptoms and 8 matched control subjects who had recovered promptly from documented IM were studied. The expression of 30,000 genes was examined in the peripheral blood by microarray analysis in 65 longitudinally collected samples. Gene expression patterns associated with PIFS were sought by correlation with symptom factor scores. Differential expression of 733 genes was identified when samples collected early during the illness and at the late (recovered) time point were compared. Of these genes, 234 were found to be significantly correlated with the reported severity of the fatigue symptom factor, and 180 were found to be correlated with the musculoskeletal pain symptom factor. Validation by analysis of the longitudinal expression pattern revealed 35 genes for which changes in expression were consistent with the illness course. These genes included several that are involved in signal transduction pathways, metal ion binding, and ion channel activity. Gene expression correlates of the cardinal symptoms of PIFS after IM have been identified. Further studies of these gene products may help to elucidate the pathogenesis of PIFS.

  10. 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.

  11. Case-based retrieval framework for gene expression data.

    PubMed

    Anaissi, Ali; Goyal, Madhu; Catchpoole, Daniel R; Braytee, Ali; Kennedy, Paul J

    2015-01-01

    The process of retrieving similar cases in a case-based reasoning system is considered a big challenge for gene expression data sets. The huge number of gene expression values generated by microarray technology leads to complex data sets and similarity measures for high-dimensional data are problematic. Hence, gene expression similarity measurements require numerous machine-learning and data-mining techniques, such as feature selection and dimensionality reduction, to be incorporated into the retrieval process. This article proposes a case-based retrieval framework that uses a k-nearest-neighbor classifier with a weighted-feature-based similarity to retrieve previously treated patients based on their gene expression profiles. The herein-proposed methodology is validated on several data sets: a childhood leukemia data set collected from The Children's Hospital at Westmead, as well as the Colon cancer, the National Cancer Institute (NCI), and the Prostate cancer data sets. Results obtained by the proposed framework in retrieving patients of the data sets who are similar to new patients are as follows: 96% accuracy on the childhood leukemia data set, 95% on the NCI data set, 93% on the Colon cancer data set, and 98% on the Prostate cancer data set. The designed case-based retrieval framework is an appropriate choice for retrieving previous patients who are similar to a new patient, on the basis of their gene expression data, for better diagnosis and treatment of childhood leukemia. Moreover, this framework can be applied to other gene expression data sets using some or all of its steps.

  12. Gene expression distribution deconvolution in single-cell RNA sequencing.

    PubMed

    Wang, Jingshu; Huang, Mo; Torre, Eduardo; Dueck, Hannah; Shaffer, Sydney; Murray, John; Raj, Arjun; Li, Mingyao; Zhang, Nancy R

    2018-06-26

    Single-cell RNA sequencing (scRNA-seq) enables the quantification of each gene's expression distribution across cells, thus allowing the assessment of the dispersion, nonzero fraction, and other aspects of its distribution beyond the mean. These statistical characterizations of the gene expression distribution are critical for understanding expression variation and for selecting marker genes for population heterogeneity. However, scRNA-seq data are noisy, with each cell typically sequenced at low coverage, thus making it difficult to infer properties of the gene expression distribution from raw counts. Based on a reexamination of nine public datasets, we propose a simple technical noise model for scRNA-seq data with unique molecular identifiers (UMI). We develop deconvolution of single-cell expression distribution (DESCEND), a method that deconvolves the true cross-cell gene expression distribution from observed scRNA-seq counts, leading to improved estimates of properties of the distribution such as dispersion and nonzero fraction. DESCEND can adjust for cell-level covariates such as cell size, cell cycle, and batch effects. DESCEND's noise model and estimation accuracy are further evaluated through comparisons to RNA FISH data, through data splitting and simulations and through its effectiveness in removing known batch effects. We demonstrate how DESCEND can clarify and improve downstream analyses such as finding differentially expressed genes, identifying cell types, and selecting differentiation markers. Copyright © 2018 the Author(s). Published by PNAS.

  13. Gene expression in Pseudomonas aeruginosa exposed to hydroxyl-radicals.

    PubMed

    Aharoni, Noa; Mamane, Hadas; Biran, Dvora; Lakretz, Anat; Ron, Eliora Z

    2018-05-01

    Recent studies have shown the efficiency of hydroxyl radicals generated via ultraviolet (UV)-based advanced oxidation processes (AOPs) combined with hydrogen peroxide (UV/H 2 O 2 ) as a treatment process in water. The effects of AOP treatments on bacterial gene expression was examined using Pseudomonas aeruginosa strain PAO1 as a model-organism bacterium. Many bacterial genes are not expressed all the time, but their expression is regulated. The regulation is at the beginning of the gene, in a genetic region called "promoter" and affects the level of transcription (synthesis of messenger RNA) and translation (synthesis of protein). The level of expression of the regulated genes can change as a function of environmental conditions, and they can be expressed more (induced, upregulated) or less (downregulated). Exposure of strain PAO1 to UV/H 2 O 2 treatment resulted in a major change in gene expression, including elevated expression of several genes. One interesting gene is PA3237, which was significantly upregulated under UV/H 2 O 2 as compared to UV or H 2 O 2 treatments alone. The induction of this gene is probably due to formation of radicals, as it is abolished in the presence of the radical scavenger tert-butanol (TBA) and is seen even when the bacteria are added after the treatment (post-treatment exposure). Upregulation of the PA3237 promoter could also be detected using a reporter gene, suggesting the use of such genetic constructs to develop biosensors for monitoring AOPs in water-treatment plants. Currently biosensors for AOPs do not exist, consequently impairing the ability to monitor these processes on-line according to radical exposure in natural waters. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms.

    PubMed

    Jani, Saurin D; Argraves, Gary L; Barth, Jeremy L; Argraves, W Scott

    2010-04-01

    An important objective of DNA microarray-based gene expression experimentation is determining inter-relationships that exist between differentially expressed genes and biological processes, molecular functions, cellular components, signaling pathways, physiologic processes and diseases. Here we describe GeneMesh, a web-based program that facilitates analysis of DNA microarray gene expression data. GeneMesh relates genes in a query set to categories available in the Medical Subject Headings (MeSH) hierarchical index. The interface enables hypothesis driven relational analysis to a specific MeSH subcategory (e.g., Cardiovascular System, Genetic Processes, Immune System Diseases etc.) or unbiased relational analysis to broader MeSH categories (e.g., Anatomy, Biological Sciences, Disease etc.). Genes found associated with a given MeSH category are dynamically linked to facilitate tabular and graphical depiction of Entrez Gene information, Gene Ontology information, KEGG metabolic pathway diagrams and intermolecular interaction information. Expression intensity values of groups of genes that cluster in relation to a given MeSH category, gene ontology or pathway can be displayed as heat maps of Z score-normalized values. GeneMesh operates on gene expression data derived from a number of commercial microarray platforms including Affymetrix, Agilent and Illumina. GeneMesh is a versatile web-based tool for testing and developing new hypotheses through relating genes in a query set (e.g., differentially expressed genes from a DNA microarray experiment) to descriptors making up the hierarchical structure of the National Library of Medicine controlled vocabulary thesaurus, MeSH. The system further enhances the discovery process by providing links between sets of genes associated with a given MeSH category to a rich set of html linked tabular and graphic information including Entrez Gene summaries, gene ontologies, intermolecular interactions, overlays of genes onto KEGG

  15. 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.

  16. Heterologous gene expression driven by carbonic anhydrase gene promoter in Dunaliella salina

    NASA Astrophysics Data System (ADS)

    Chai, Yurong; Lu, Yumin; Wang, Tianyun; Hou, Weihong; Xue, Lexun

    2006-12-01

    Dunaliella salina, a halotolerant unicellular green alga without a rigid cell wall, can live in salinities ranging from 0.05 to 5 mol/L NaCl. These features of D. salina make it an ideal host for the production of antibodies, oral vaccine, and commercially valuable polypeptides. To produce high level of heterologous proteins from D. salina, highly efficient promoters are required to drive expression of target genes under controlled condition. In the present study, we cloned a 5' franking region of 1.4 kb from the carbonic anhydrase ( CAH) gene of D. salina by genomic walking and PCR. The fragment was ligated to the pMD18-T vector and characterized. Sequence analysis indicated that this region contained conserved motifs, including a TATA- like box and CAAT-box. Tandem (GT)n repeats that had a potential role of transcriptional control, were also found in this region. The transcription start site (TSS) of the CAH gene was determined by 5' RACE and nested PCR method. Transformation assays showed that the 1.4 kb fragment was able to drive expression of the selectable bar (bialaphos resistance) gene when the fusion was transformed into D. salina by biolistics. Northern blotting hybridizations showed that the bar transcript was most abundant in cells grown in 2 mol/L NaCl, and less abundant in 0.5 mol/L NaCl, indicating that expression of the bar gene was induced at high salinity. These results suggest the potential use of the CAH gene promoter to induce the expression of heterologous genes in D. salina under varied salt condition.

  17. 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.

  18. Ethanol modifies the effect of handling stress on gene expression: problems in the analysis of two-way gene expression studies in mouse brain.

    PubMed

    Rulten, Stuart L; Ripley, Tamzin L; Manerakis, Ektor; Stephens, David N; Mayne, Lynne V

    2006-08-02

    Studies analysing the effects of acute treatments on animal behaviour and brain biochemistry frequently use pairwise comparisons between sham-treated and -untreated animals. In this study, we analyse expression of tPA, Grik2, Smarca2 and the transcription factor, Sp1, in mouse cerebellum following acute ethanol treatment. Expression is compared to saline-injected and -untreated control animals. We demonstrate that acute i.p. injection of saline may alter gene expression in a gene-specific manner and that ethanol may modify the effects of sham treatment on gene expression, as well as inducing specific effects independent of any handling related stress. In addition to demonstrating the complexity of gene expression in response to physical and environmental stress, this work raises questions on the interpretation and validity of studies relying on pairwise comparisons.

  19. Transcriptional Coupling of Neighboring Genes and Gene Expression Noise: Evidence that Gene Orientation and Noncoding Transcripts Are Modulators of Noise

    PubMed Central

    Wang, Guang-Zhong; Lercher, Martin J.; Hurst, Laurence D.

    2011-01-01

    Abstract How is noise in gene expression modulated? Do mechanisms of noise control impact genome organization? In yeast, the expression of one gene can affect that of a very close neighbor. As the effect is highly regionalized, we hypothesize that genes in different orientations will have differing degrees of coupled expression and, in turn, different noise levels. Divergently organized gene pairs, in particular those with bidirectional promoters, have close promoters, maximizing the likelihood that expression of one gene affects the neighbor. With more distant promoters, the same is less likely to hold for gene pairs in nondivergent orientation. Stochastic models suggest that coupled chromatin dynamics will typically result in low abundance-corrected noise (ACN). Transcription of noncoding RNA (ncRNA) from a bidirectional promoter, we thus hypothesize to be a noise-reduction, expression-priming, mechanism. The hypothesis correctly predicts that protein-coding genes with a bidirectional promoter, including those with a ncRNA partner, have lower ACN than other genes and divergent gene pairs uniquely have correlated ACN. Moreover, as predicted, ACN increases with the distance between promoters. The model also correctly predicts ncRNA transcripts to be often divergently transcribed from genes that a priori would be under selection for low noise (essential genes, protein complex genes) and that the latter genes should commonly reside in divergent orientation. Likewise, that genes with bidirectional promoters are rare subtelomerically, cluster together, and are enriched in essential gene clusters is expected and observed. We conclude that gene orientation and transcription of ncRNAs are candidate modulators of noise. PMID:21402863

  20. Angiogenesis-related gene expression analysis in celiac disease.

    PubMed

    Castellanos-Rubio, Ainara; Caja, Sergio; Irastorza, Iñaki; Fernandez-Jimenez, Nora; Plaza-Izurieta, Leticia; Vitoria, Juan Carlos; Maki, Markku; Lindfors, Katri; Bilbao, Jose Ramon

    2012-05-01

    Celiac disease (CD) involves disturbance of the small-bowel mucosal vascular network, and transglutaminase autoantibodies (TGA) have been related to angiogenesis disturbance, a complex phenomenon probably also influenced by common genetic variants in angiogenesis-related genes. A set of genes with "angiogenesis" GO term identified in a previous expression microarray experiment (SCG2, STAB1, TGFA, ANG, ERBB2, GNA13, PML, CASP8, ECGF1, JAG1, HIF1A, TNFSF13 and TGM2) was selected for genetic and functional studies. SNPs that showed a trend for association with CD in the first GWAS were genotyped in 555 patients and 541 controls. Gene expression of all genes was quantified in 15 pairs of intestinal biopsies (diagnosis vs. GFD) and in three-dimensional HUVEC and T84 cell cultures incubated with TGA-positive and negative serum. A regulatory SNP in TNFSF13 (rs11552708) is associated with CD (p = 0.01, OR = 0.7). Expression changes in biopsies pointed to TGM2 and PML as up-regulated antiangiogenic genes and to GNA13, TGFA, ERBB2 and SCG2 as down-regulated proangiogenic factors in CD. TGA seem to enhance TGM2 expression in both cell models, but PML expression was induced only in T84 enterocytes while GNA13 and ERBB2 were repressed in HUVEC endothelial cells, with several genes showing discordant effects in each model, highlighting the complexity of gene interactions in the pathogenesis of CD. Finally, cell culture models are useful tools to help dissect complex responses observed in human explants.

  1. RefEx, a reference gene expression dataset as a web tool for the functional analysis of genes.

    PubMed

    Ono, Hiromasa; Ogasawara, Osamu; Okubo, Kosaku; Bono, Hidemasa

    2017-08-29

    Gene expression data are exponentially accumulating; thus, the functional annotation of such sequence data from metadata is urgently required. However, life scientists have difficulty utilizing the available data due to its sheer magnitude and complicated access. We have developed a web tool for browsing reference gene expression pattern of mammalian tissues and cell lines measured using different methods, which should facilitate the reuse of the precious data archived in several public databases. The web tool is called Reference Expression dataset (RefEx), and RefEx allows users to search by the gene name, various types of IDs, chromosomal regions in genetic maps, gene family based on InterPro, gene expression patterns, or biological categories based on Gene Ontology. RefEx also provides information about genes with tissue-specific expression, and the relative gene expression values are shown as choropleth maps on 3D human body images from BodyParts3D. Combined with the newly incorporated Functional Annotation of Mammals (FANTOM) dataset, RefEx provides insight regarding the functional interpretation of unfamiliar genes. RefEx is publicly available at http://refex.dbcls.jp/.

  2. Establishment of a 12-gene expression signature to predict colon cancer prognosis

    PubMed Central

    Zhao, Guangxi; Dong, Pingping; Wu, Bingrui

    2018-01-01

    A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM) stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD) prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA). The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS): Kaplan Meier (KM) Log Rank p = 0.0034; overall survival (OS): KM Log Rank p = 0.0336) in GSE17538. For patients with proficient mismatch repair system (pMMR) in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS): KM Log Rank p = 0.022). Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher’s exact test p = 0.0003). After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01) and stage II & III (Log Rank p = 0.017) in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT) and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041). Among stage II/III pMMR patients with

  3. Exploring the key genes and pathways in enchondromas using a gene expression microarray.

    PubMed

    Shi, Zhongju; Zhou, Hengxing; Pan, Bin; Lu, Lu; Kang, Yi; Liu, Lu; Wei, Zhijian; Feng, Shiqing

    2017-07-04

    Enchondromas are the most common primary benign osseous neoplasms that occur in the medullary bone; they can undergo malignant transformation into chondrosarcoma. However, enchondromas are always undetected in patients, and the molecular mechanism is unclear. To identify key genes and pathways associated with the occurrence and development of enchondromas, we downloaded the gene expression dataset GSE22855 and obtained the differentially expressed genes (DEGs) by analyzing high-throughput gene expression in enchondromas. In total, 635 genes were identified as DEGs. Of these, 225 genes (35.43%) were up-regulated, and the remaining 410 genes (64.57%) were down-regulated. We identified the predominant gene ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were significantly over-represented in the enchondromas samples compared with the control samples. Subsequently the top 10 core genes were identified from the protein-protein interaction (PPI) network. The enrichment analyses of the genes mainly involved in two significant modules showed that the DEGs were principally related to ribosomes, protein digestion and absorption, ECM-receptor interaction, focal adhesion, amoebiasis and the PI3K-Akt signaling pathway.Together, these data elucidate the molecular mechanisms underlying the occurrence and development of enchondromas and provide promising candidates for therapeutic intervention and prognostic evaluation. However, further experimental studies are needed to confirm these results.

  4. 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.

  5. 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.

  6. Validation of reference genes for quantitative RT-PCR studies of gene expression in perennial ryegrass (Lolium perenne L.)

    PubMed Central

    2010-01-01

    Background Perennial ryegrass (Lolium perenne L.) is an important pasture and turf crop. Biotechniques such as gene expression studies are being employed to improve traits in this temperate grass. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is among the best methods available for determining changes in gene expression. Before analysis of target gene expression, it is essential to select an appropriate normalisation strategy to control for non-specific variation between samples. Reference genes that have stable expression at different biological and physiological states can be effectively used for normalisation; however, their expression stability must be validated before use. Results Existing Serial Analysis of Gene Expression data were queried to identify six moderately expressed genes that had relatively stable gene expression throughout the year. These six candidate reference genes (eukaryotic elongation factor 1 alpha, eEF1A; TAT-binding protein homolog 1, TBP-1; eukaryotic translation initiation factor 4 alpha, eIF4A; YT521-B-like protein family protein, YT521-B; histone 3, H3; ubiquitin-conjugating enzyme, E2) were validated for qRT-PCR normalisation in 442 diverse perennial ryegrass (Lolium perenne L.) samples sourced from field- and laboratory-grown plants under a wide range of experimental conditions. Eukaryotic EF1A is encoded by members of a multigene family exhibiting differential expression and necessitated the expression analysis of different eEF1A encoding genes; a highly expressed eEF1A (h), a moderately, but stably expressed eEF1A (s), and combined expression of multigene eEF1A (m). NormFinder identified eEF1A (s) and YT521-B as the best combination of two genes for normalisation of gene expression data in perennial ryegrass following different defoliation management in the field. Conclusions This study is unique in the magnitude of samples tested with the inclusion of numerous field-grown samples, helping pave the way to

  7. 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.

  8. 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.

  9. 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.

  10. dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface.

    PubMed

    Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

    2009-08-25

    Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms.

  11. dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

    PubMed Central

    Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

    2009-01-01

    Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156

  12. Automatic Control of Gene Expression in Mammalian Cells.

    PubMed

    Fracassi, Chiara; Postiglione, Lorena; Fiore, Gianfranco; di Bernardo, Diego

    2016-04-15

    Automatic control of gene expression in living cells is paramount importance to characterize both endogenous gene regulatory networks and synthetic circuits. In addition, such a technology can be used to maintain the expression of synthetic circuit components in an optimal range in order to ensure reliable performance. Here we present a microfluidics-based method to automatically control gene expression from the tetracycline-inducible promoter in mammalian cells in real time. Our approach is based on the negative-feedback control engineering paradigm. We validated our method in a monoclonal population of cells constitutively expressing a fluorescent reporter protein (d2EYFP) downstream of a minimal CMV promoter with seven tet-responsive operator motifs (CMV-TET). These cells also constitutively express the tetracycline transactivator protein (tTA). In cells grown in standard growth medium, tTA is able to bind the CMV-TET promoter, causing d2EYFP to be maximally expressed. Upon addition of tetracycline to the culture medium, tTA detaches from the CMV-TET promoter, thus preventing d2EYFP expression. We tested two different model-independent control algorithms (relay and proportional-integral (PI)) to force a monoclonal population of cells to express an intermediate level of d2EYFP equal to 50% of its maximum expression level for up to 3500 min. The control input is either tetracycline-rich or standard growth medium. We demonstrated that both the relay and PI controllers can regulate gene expression at the desired level, despite oscillations (dampened in the case of the PI controller) around the chosen set point.

  13. The evolution of duplicate gene expression in mammalian organs

    PubMed Central

    Guschanski, Katerina; Warnefors, Maria; Kaessmann, Henrik

    2017-01-01

    Gene duplications generate genomic raw material that allows the emergence of novel functions, likely facilitating adaptive evolutionary innovations. However, global assessments of the functional and evolutionary relevance of duplicate genes in mammals were until recently limited by the lack of appropriate comparative data. Here, we report a large-scale study of the expression evolution of DNA-based functional gene duplicates in three major mammalian lineages (placental mammals, marsupials, egg-laying monotremes) and birds, on the basis of RNA sequencing (RNA-seq) data from nine species and eight organs. We observe dynamic changes in tissue expression preference of paralogs with different duplication ages, suggesting differential contribution of paralogs to specific organ functions during vertebrate evolution. Specifically, we show that paralogs that emerged in the common ancestor of bony vertebrates are enriched for genes with brain-specific expression and provide evidence for differential forces underlying the preferential emergence of young testis- and liver-specific expressed genes. Further analyses uncovered that the overall spatial expression profiles of gene families tend to be conserved, with several exceptions of pronounced tissue specificity shifts among lineage-specific gene family expansions. Finally, we trace new lineage-specific genes that may have contributed to the specific biology of mammalian organs, including the little-studied placenta. Overall, our study provides novel and taxonomically broad evidence for the differential contribution of duplicate genes to tissue-specific transcriptomes and for their importance for the phenotypic evolution of vertebrates. PMID:28743766

  14. Identification of differentially expressed genes in childhood asthma.

    PubMed

    Zhang, Nian-Zhen; Chen, Xiu-Juan; Mu, Yu-Hua; Wang, Hewen

    2018-05-01

    Asthma has been the most common chronic disease in children that places a major burden for affected people and their families.An integrated analysis of microarrays studies was performed to identify differentially expressed genes (DEGs) in childhood asthma compared with normal control. We also obtained the differentially methylated genes (DMGs) in childhood asthma according to GEO. The genes that were both differentially expressed and differentially methylated were identified. Functional annotation and protein-protein interaction network construction were performed to interpret biological functions of DEGs. We performed q-RT-PCR to verify the expression of selected DEGs.One DNA methylation and 3 gene expression datasets were obtained. Four hundred forty-one DEGs and 1209 DMGs in childhood asthma were identified. Among which, 16 genes were both differentially expressed and differentially methylated in childhood asthma. Natural killer cell mediated cytotoxicity pathway, Jak-STAT signaling pathway, and Wnt signaling pathway were 3 significantly enriched pathways in childhood asthma according to our KEGG enrichment analysis. The PPI network of top 20 up- and downregulated DEGs consisted of 822 nodes and 904 edges and 2 hub proteins (UBQLN4 and MID2) were identified. The expression of 8 DEGs (GZMB, FGFBP2, CLC, TBX21, ALOX15, IL12RB2, UBQLN4) was verified by qRT-PCR and only the expression of GZMB and FGFBP2 was inconsistent with our integrated analysis.Our finding was helpful to elucidate the underlying mechanism of childhood asthma and develop new potential diagnostic biomarker and provide clues for drug design.

  15. Caffeine exposure alters cardiac gene expression in embryonic cardiomyocytes

    PubMed Central

    Fang, Xiefan; Mei, Wenbin; Barbazuk, William B.; Rivkees, Scott A.

    2014-01-01

    Previous studies demonstrated that in utero caffeine treatment at embryonic day (E) 8.5 alters DNA methylation patterns, gene expression, and cardiac function in adult mice. To provide insight into the mechanisms, we examined cardiac gene and microRNA (miRNA) expression in cardiomyocytes shortly after exposure to physiologically relevant doses of caffeine. In HL-1 and primary embryonic cardiomyocytes, caffeine treatment for 48 h significantly altered the expression of cardiac structural genes (Myh6, Myh7, Myh7b, Tnni3), hormonal genes (Anp and BnP), cardiac transcription factors (Gata4, Mef2c, Mef2d, Nfatc1), and microRNAs (miRNAs; miR208a, miR208b, miR499). In addition, expressions of these genes were significantly altered in embryonic hearts exposed to in utero caffeine. For in utero experiments, pregnant CD-1 dams were treated with 20–60 mg/kg of caffeine, which resulted in maternal circulation levels of 37.3–65.3 μM 2 h after treatment. RNA sequencing was performed on embryonic ventricles treated with vehicle or 20 mg/kg of caffeine daily from E6.5-9.5. Differential expression (DE) analysis revealed that 124 genes and 849 transcripts were significantly altered, and differential exon usage (DEU) analysis identified 597 exons that were changed in response to prenatal caffeine exposure. Among the DE genes identified by RNA sequencing were several cardiac structural genes and genes that control DNA methylation and histone modification. Pathway analysis revealed that pathways related to cardiovascular development and diseases were significantly affected by caffeine. In addition, global cardiac DNA methylation was reduced in caffeine-treated cardiomyocytes. Collectively, these data demonstrate that caffeine exposure alters gene expression and DNA methylation in embryonic cardiomyocytes. PMID:25354728

  16. 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.

  17. Expression profile of genes associated with mastitis in dairy cattle

    PubMed Central

    2009-01-01

    In order to characterize the expression of genes associated with immune response mechanisms to mastitis, we quantified the relative expression of the IL-2, IL-4, IL-6, IL-8, IL-10, IFN-γ and TNF- α genes in milk cells of healthy cows and cows with clinical mastitis. Total RNA was extracted from milk cells of six Black and White Holstein (BW) cows and six Gyr cows, including three animals with and three without mastitis per breed. Gene expression was analyzed by real-time PCR. IL-10 gene expression was higher in the group of BW and Gyr cows with mastitis compared to animals free of infection from both breeds (p < 0.05). It was also higher in BW Holstein animals with clinical mastitis (p < 0.001), but it was not significant when Gyr cows with and without mastitis were compared (0.05 < p < 0.10). Among healthy cows, BW Holstein animals tended to present a higher expression of all genes studied, with a significant difference for the IL-2 and IFN- γ genes (p < 0.001). For animals with mastitis no significant difference in gene expression was observed between the two breeds. These findings suggest that animals with mastitis develop a preferentially cell-mediated immune response. Further studies including larger samples are necessary to better characterize the gene expression profile in cows with mastitis. PMID:21637453

  18. The Role of Multiple Transcription Factors In Archaeal Gene Expression

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

    Charles J. Daniels

    2008-09-23

    Since the inception of this research program, the project has focused on two central questions: What is the relationship between the 'eukaryal-like' transcription machinery of archaeal cells and its counterparts in eukaryal cells? And, how does the archaeal cell control gene expression using its mosaic of eukaryal core transcription machinery and its bacterial-like transcription regulatory proteins? During the grant period we have addressed these questions using a variety of in vivo approaches and have sought to specifically define the roles of the multiple TATA binding protein (TBP) and TFIIB-like (TFB) proteins in controlling gene expression in Haloferax volcanii. H. volcaniimore » was initially chosen as a model for the Archaea based on the availability of suitable genetic tools; however, later studies showed that all haloarchaea possessed multiple tbp and tfb genes, which led to the proposal that multiple TBP and TFB proteins may function in a manner similar to alternative sigma factors in bacterial cells. In vivo transcription and promoter analysis established a clear relationship between the promoter requirements of haloarchaeal genes and those of the eukaryal RNA polymerase II promoter. Studies on heat shock gene promoters, and the demonstration that specific tfb genes were induced by heat shock, provided the first indication that TFB proteins may direct expression of specific gene families. The construction of strains lacking tbp or tfb genes, coupled with the finding that many of these genes are differentially expressed under varying growth conditions, provided further support for this model. Genetic tools were also developed that led to the construction of insertion and deletion mutants, and a novel gene expression scheme was designed that allowed the controlled expression of these genes in vivo. More recent studies have used a whole genome array to examine the expression of these genes and we have established a linkage between the expression of

  19. Evaluation and selection of reliable reference genes for gene expression under abiotic stress in cotton (Gossypium hirsutum L.).

    PubMed

    Wang, Min; Wang, Qinglian; Zhang, Baohong

    2013-11-01

    Reference genes are critical for normalization of the gene expression level of target genes. The widely used housekeeping genes may change their expression levels at different tissue under different treatment or stress conditions. Therefore, systematical evaluation on the housekeeping genes is required for gene expression analysis. Up to date, no work was performed to evaluate the housekeeping genes in cotton under stress treatment. In this study, we chose 10 housekeeping genes to systematically assess their expression levels at two different tissues (leaves and roots) under two different abiotic stresses (salt and drought) with three different concentrations. Our results show that there is no best reference gene for all tissues at all stress conditions. The reliable reference gene should be selected based on a specific condition. For example, under salt stress, UBQ7, GAPDH and EF1A8 are better reference genes in leaves; TUA10, UBQ7, CYP1, GAPDH and EF1A8 were better in roots. Under drought stress, UBQ7, EF1A8, TUA10, and GAPDH showed less variety of expression level in leaves and roots. Thus, it is better to identify reliable reference genes first before performing any gene expression analysis. However, using a combination of housekeeping genes as reference gene may provide a new strategy for normalization of gene expression. In this study, we found that combination of four housekeeping genes worked well as reference genes under all the stress conditions. © 2013.

  20. Influence of Gene Expression on Hardness in Wheat

    PubMed Central

    Nirmal, Ravi C.; Wrigley, Colin

    2016-01-01

    Puroindoline (Pina and Pinb) genes control grain texture or hardness in wheat. Wild-type/soft alleles lead to softer grain while a mutation in one or both of these genes results in a hard grain. Variation in hardness in genotypes with identical Pin alleles (wild-type or mutant) is known but the molecular basis of this is not known. We now report the identification of wheat genotypes with hard grain texture and wild-type/soft Pin alleles indicating that hardness in wheat may be controlled by factors other than mutations in the coding region of the Pin genes. RNA-Seq analysis was used to determine the variation in the transcriptome of developing grains of thirty three diverse wheat genotypes including hard (mutant Pin) and soft (wild type) and those that were hard without having Pin mutations. This defined the role of pin gene expression and identified other candidate genes associated with hardness. Pina was not expressed in hard wheat with a mutation in the Pina gene. The ratio of Pina to Pinb expression was generally lower in the hard non mutant genotypes. Hardness may be associated with differences in Pin expression and other factors and is not simply associated with mutations in the PIN protein coding sequences. PMID:27741295

  1. Influence of Gene Expression on Hardness in Wheat.

    PubMed

    Nirmal, Ravi C; Furtado, Agnelo; Wrigley, Colin; Henry, Robert J

    2016-01-01

    Puroindoline (Pina and Pinb) genes control grain texture or hardness in wheat. Wild-type/soft alleles lead to softer grain while a mutation in one or both of these genes results in a hard grain. Variation in hardness in genotypes with identical Pin alleles (wild-type or mutant) is known but the molecular basis of this is not known. We now report the identification of wheat genotypes with hard grain texture and wild-type/soft Pin alleles indicating that hardness in wheat may be controlled by factors other than mutations in the coding region of the Pin genes. RNA-Seq analysis was used to determine the variation in the transcriptome of developing grains of thirty three diverse wheat genotypes including hard (mutant Pin) and soft (wild type) and those that were hard without having Pin mutations. This defined the role of pin gene expression and identified other candidate genes associated with hardness. Pina was not expressed in hard wheat with a mutation in the Pina gene. The ratio of Pina to Pinb expression was generally lower in the hard non mutant genotypes. Hardness may be associated with differences in Pin expression and other factors and is not simply associated with mutations in the PIN protein coding sequences.

  2. 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

  3. 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 .

  4. DNA Methylation of Gene Expression in Acanthamoeba castellanii Encystation.

    PubMed

    Moon, Eun-Kyung; Hong, Yeonchul; Lee, Hae-Ahm; Quan, Fu-Shi; Kong, Hyun-Hee

    2017-04-01

    Encystation mediating cyst specific cysteine proteinase (CSCP) of Acanthamoeba castellanii is expressed remarkably during encystation. However, the molecular mechanism involved in the regulation of CSCP gene expression remains unclear. In this study, we focused on epigenetic regulation of gene expression during encystation of Acanthamoeba . To evaluate methylation as a potential mechanism involved in the regulation of CSCP expression, we first investigated the correlation between promoter methylation status of CSCP gene and its expression. A 2,878 bp of promoter sequence of CSCP gene was amplified by PCR. Three CpG islands (island 1-3) were detected in this sequence using bioinformatics tools. Methylation of CpG island in trophozoites and cysts was measured by bisulfite sequence PCR. CSCP promoter methylation of CpG island 1 (1,633 bp) was found in 8.2% of trophozoites and 7.3% of cysts. Methylation of CpG island 2 (625 bp) was observed in 4.2% of trophozoites and 5.8% of cysts. Methylation of CpG island 3 (367 bp) in trophozoites and cysts was both 3.6%. These results suggest that DNA methylation system is present in CSCP gene expression of Acanthamoeba . In addition, the expression of encystation mediating CSCP is correlated with promoter CpG island 1 hypomethylation.

  5. GEsture: an online hand-drawing tool for gene expression pattern search.

    PubMed

    Wang, Chunyan; Xu, Yiqing; Wang, Xuelin; Zhang, Li; Wei, Suyun; Ye, Qiaolin; Zhu, Youxiang; Yin, Hengfu; Nainwal, Manoj; Tanon-Reyes, Luis; Cheng, Feng; Yin, Tongming; Ye, Ning

    2018-01-01

    Gene expression profiling data provide useful information for the investigation of biological function and process. However, identifying a specific expression pattern from extensive time series gene expression data is not an easy task. Clustering, a popular method, is often used to classify similar expression genes, however, genes with a 'desirable' or 'user-defined' pattern cannot be efficiently detected by clustering methods. To address these limitations, we developed an online tool called GEsture. Users can draw, or graph a curve using a mouse instead of inputting abstract parameters of clustering methods. GEsture explores genes showing similar, opposite and time-delay expression patterns with a gene expression curve as input from time series datasets. We presented three examples that illustrate the capacity of GEsture in gene hunting while following users' requirements. GEsture also provides visualization tools (such as expression pattern figure, heat map and correlation network) to display the searching results. The result outputs may provide useful information for researchers to understand the targets, function and biological processes of the involved genes.

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

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

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

    2014-08-28

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

  7. Adult mouse brain gene expression patterns bear an embryologic imprint

    PubMed Central

    Zapala, Matthew A.; Hovatta, Iiris; Ellison, Julie A.; Wodicka, Lisa; Del Rio, Jo A.; Tennant, Richard; Tynan, Wendy; Broide, Ron S.; Helton, Rob; Stoveken, Barbara S.; Winrow, Christopher; Lockhart, Daniel J.; Reilly, John F.; Young, Warren G.; Bloom, Floyd E.; Lockhart, David J.; Barlow, Carrolee

    2005-01-01

    The current model to explain the organization of the mammalian nervous system is based on studies of anatomy, embryology, and evolution. To further investigate the molecular organization of the adult mammalian brain, we have built a gene expression-based brain map. We measured gene expression patterns for 24 neural tissues covering the mouse central nervous system and found, surprisingly, that the adult brain bears a transcriptional “imprint” consistent with both embryological origins and classic evolutionary relationships. Embryonic cellular position along the anterior–posterior axis of the neural tube was shown to be closely associated with, and possibly a determinant of, the gene expression patterns in adult structures. We also observed a significant number of embryonic patterning and homeobox genes with region-specific expression in the adult nervous system. The relationships between global expression patterns for different anatomical regions and the nature of the observed region-specific genes suggest that the adult brain retains a degree of overall gene expression established during embryogenesis that is important for regional specificity and the functional relationships between regions in the adult. The complete collection of extensively annotated gene expression data along with data mining and visualization tools have been made available on a publicly accessible web site (www.barlow-lockhart-brainmapnimhgrant.org). PMID:16002470

  8. Correct Hox gene expression established independently of position in Caenorhabditis elegans.

    PubMed

    Cowing, D; Kenyon, C

    1996-07-25

    The Hox genes are expressed in a conserved sequence of spatial domains along the anteroposterior (A/P) body axes of many organisms. In Drosophila, position-specific signals located along the A/P axis establish the pattern of Hox gene expression. In the nematode Caenorhabditis elegans, it is not known how the pattern of Hox gene expression is established. C. elegans uses lineal control mechanisms and local cell interactions to specify early blastomere identities. However, many cells expressing the same Hox gene are unrelated by lineage, suggesting that, as in Drosophila, domains of Hox gene expression may be defined by cell-extrinsic A/P positional signals. To test this, we have investigated whether posterior mesodermal and ectodermal cells will express their normal posterior Hox gene when they are mispositioned in the anterior. Surprisingly, we find that correct Hox gene expression does not depend on cell position, but is highly correlated with cell lineage. Thus, although the most striking feature of Hox gene expression is its positional specificity, in C. elegans the pattern is achieved, at least in part, by a lineage-specific control system that operates without regard to A/P position.

  9. Abundant Gene-by-Environment Interactions in Gene Expression Reaction Norms to Copper within Saccharomyces cerevisiae

    PubMed Central

    Hodgins-Davis, Andrea; Adomas, Aleksandra B.; Warringer, Jonas; Townsend, Jeffrey P.

    2012-01-01

    Genetic variation for plastic phenotypes potentially contributes phenotypic variation to populations that can be selected during adaptation to novel ecological contexts. However, the basis and extent of plastic variation that manifests in diverse environments remains elusive. Here, we characterize copper reaction norms for mRNA abundance among five Saccharomyces cerevisiae strains to 1) describe population variation across the full range of ecologically relevant copper concentrations, from starvation to toxicity, and 2) to test the hypothesis that plastic networks exhibit increased population variation for gene expression. We find that although the vast majority of the variation is small in magnitude (considerably <2-fold), not just some, but most genes demonstrate variable expression across environments, across genetic backgrounds, or both. Plastically expressed genes included both genes regulated directly by copper-binding transcription factors Mac1 and Ace1 and genes indirectly responding to the downstream metabolic consequences of the copper gradient, particularly genes involved in copper, iron, and sulfur homeostasis. Copper-regulated gene networks exhibited more similar behavior within the population in environments where those networks have a large impact on fitness. Nevertheless, expression variation in genes like Cup1, important to surviving copper stress, was linked with variation in mitotic fitness and in the breadth of differential expression across the genome. By revealing a broader and deeper range of population variation, our results provide further evidence for the interconnectedness of genome-wide mRNA levels, their dependence on environmental context and genetic background, and the abundance of variation in gene expression that can contribute to future evolution. PMID:23019066

  10. Wheat differential gene expression induced by different races of Puccinia triticina.

    PubMed

    Neugebauer, Kerri A; Bruce, Myron; Todd, Tim; Trick, Harold N; Fellers, John P

    2018-01-01

    Puccinia triticina, the causal agent of wheat leaf rust, causes significant losses in wheat yield and quality each year worldwide. During leaf rust infection, the host plant recognizes numerous molecules, some of which trigger host defenses. Although P. triticina reproduces clonally, there is still variation within the population due to a high mutation frequency, host specificity, and environmental adaptation. This study explores how wheat responds on a gene expression level to different P. triticina races. Six P. triticina races were inoculated onto a susceptible wheat variety and samples were taken at six days post inoculation, just prior to pustule eruption. RNA sequence data identified 63 wheat genes differentially expressed between the six races. A time course, conducted over the first seven days post inoculation, was used to examine the expression pattern of 63 genes during infection. Forty-seven wheat genes were verified to have differential expression. Three common expression patterns were identified. In addition, two genes were associated with race specific gene expression. Differential expression of an ER molecular chaperone gene was associated with races from two different P. triticina lineages. Also, differential expression in an alanine glyoxylate aminotransferase gene was associated with races with virulence shifts for leaf rust resistance genes.

  11. Gene Expression in Human Accessory Lacrimal Glands of Wolfring

    PubMed Central

    Ubels, John L.; Gipson, Ilene K.; Spurr-Michaud, Sandra J.; Tisdale, Ann S.; Van Dyken, Rachel E.; Hatton, Mark P.

    2012-01-01

    Purpose. The accessory lacrimal glands are assumed to contribute to the production of tear fluid, but little is known about their function. The goal of this study was to conduct an analysis of gene expression by glands of Wolfring that would provide a more complete picture of the function of these glands. Methods. Glands of Wolfring were isolated from frozen sections of human eyelids by laser microdissection. RNA was extracted from the cells and hybridized to gene expression arrays. The expression of several of the major genes was confirmed by immunohistochemistry. Results. Of the 24 most highly expressed genes, 9 were of direct relevance to lacrimal function. These included lysozyme, lactoferrin, tear lipocalin, and lacritin. The glands of Wolfring are enriched in genes related to protein synthesis, targeting, and secretion, and a large number of genes for proteins with antimicrobial activity were detected. Ion channels and transporters, carbonic anhydrase, and aquaporins were abundantly expressed. Genes for control of lacrimal function, including cholinergic, adrenergic, vasoactive intestinal polypeptide, purinergic, androgen, and prolactin receptors were also expressed in gland of Wolfring. Conclusions. The data suggest that the function of glands of Wolfring is similar to that of main lacrimal glands and are consistent with secretion electrolytes, fluid, and protein under nervous and hormonal control. Since these glands secrete directly onto the ocular surface, their location may allow rapid response to exogenous stimuli and makes them readily accessible to topical drugs. PMID:22956620

  12. Transposon Variants and Their Effects on Gene Expression in Arabidopsis

    PubMed Central

    Wang, Xi; Weigel, Detlef; Smith, Lisa M.

    2013-01-01

    Transposable elements (TEs) make up the majority of many plant genomes. Their transcription and transposition is controlled through siRNAs and epigenetic marks including DNA methylation. To dissect the interplay of siRNA–mediated regulation and TE evolution, and to examine how TE differences affect nearby gene expression, we investigated genome-wide differences in TEs, siRNAs, and gene expression among three Arabidopsis thaliana accessions. Both TE sequence polymorphisms and presence of linked TEs are positively correlated with intraspecific variation in gene expression. The expression of genes within 2 kb of conserved TEs is more stable than that of genes next to variant TEs harboring sequence polymorphisms. Polymorphism levels of TEs and closely linked adjacent genes are positively correlated as well. We also investigated the distribution of 24-nt-long siRNAs, which mediate TE repression. TEs targeted by uniquely mapping siRNAs are on average farther from coding genes, apparently because they more strongly suppress expression of adjacent genes. Furthermore, siRNAs, and especially uniquely mapping siRNAs, are enriched in TE regions missing in other accessions. Thus, targeting by uniquely mapping siRNAs appears to promote sequence deletions in TEs. Overall, our work indicates that siRNA–targeting of TEs may influence removal of sequences from the genome and hence evolution of gene expression in plants. PMID:23408902

  13. Mucin gene expression in human male urogenital tract epithelia

    PubMed Central

    Russo, Cindy Leigh; Spurr-Michaud, Sandra; Tisdale, Ann; Pudney, Jeffrey; Anderson, Deborah; Gipson, Ilene K.

    2010-01-01

    BACKGROUND Mucins are large, hydrophilic glycoproteins that protect wet-surfaced epithelia from pathogen invasion as well as provide lubrication. At least 17 mucin genes have been cloned to date. This study sought to determine the mucin gene expression profile of the human male urogenital tract epithelia, to determine if mucins are present in seminal fluid, and to assess the effect of androgens on mucin expression. METHODS AND RESULTS Testis, epididymis, vas deferens, seminal vesicle, prostate, bladder, urethra and foreskin were assessed for mucin expression by RT-PCR and immunohistochemistry. Epithelia of the vas deferens, prostate and urethra expressed the greatest number of mucins, each expressing 5–8 mucins. Messenger RNA of MUC1 and MUC20, both membrane-associated mucins, were detected in most tissues analyzed. Conversely, MUC6 was predominantly detected in seminal vesicle. MUC1, MUC5B and MUC6 were detected in seminal fluid samples by immunoblot analysis. Androgens had no effect on mucin expression by cultured human prostatic epithelial cells. CONCLUSIONS Each region of urogenital tract epithelium expressed a unique mucin gene repertoire. Secretory mucins are present in seminal fluid, and androgens do not appear to regulate mucin gene expression. PMID:16997931

  14. VH gene family expression in mice with the xid defect

    PubMed Central

    1991-01-01

    Preferential use of particular VH gene families in the response to specific antigens has been demonstrated in several systems. The lack of responses to certain types of antigens, therefore, could be the result of deletion of or failure to express some VH genes. Because CBA/N mice, which carry the X-linked immunodeficiency (xid) gene defect, have been shown to be unresponsive to thymus-independent polysaccharide antigens, it was of interest to examine if this unresponsiveness could be accounted for by abnormal expression of particular VH gene families. Using in situ hybridization on B cell colonies, we determined the expression of nine VH gene families in CBA/CaHN females (genotypically normal), CBA/N males (xid) and females (xid), and (CBA/N x CBA/CaHN)F1 males (xid) and females (phenotypically normal). Our results indicate that VH gene family expression, including the S107 family, in CBA/N males and F1 males, is similar to that of CBA/CaHN and F1 females with predominant expression of J558, the largest gene family, in all individuals. Interestingly, CBA/N female mice, which carry two defective X chromosomes, as a group expressed significantly reduced levels of the J558 gene family, and as individuals showed variation in which family was predominantly expressed. We conclude that the unresponsiveness of mice with the xid defect to polysaccharide antigens can not attributed to a failure to express the nine VH gene families that we examined. Our findings do not support previous studies (Primi, D., and P.-A. Cazenave 1986. J. Exp. Med. 165:357), which found an absence of expression of the S107 family in xid mice. PMID:1711566

  15. 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.

  16. 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

  17. Influence of Genetic Variations in Selenoprotein Genes on the Pattern of Gene Expression after Supplementation with Brazil Nuts

    PubMed Central

    Rogero, Marcelo M.; Hesketh, John

    2017-01-01

    Selenium (Se) is an essential micronutrient for human health. Its beneficial effects are exerted by selenoproteins, which can be quantified in blood and used as molecular biomarkers of Se status. We hypothesize that the presence of genetic polymorphisms in selenoprotein genes may: (1) influence the gene expression of specific selenoproteins and (2) influence the pattern of global gene expression after Brazil nut supplementation. The study was conducted with 130 healthy volunteers in Sao Paulo, Brazil, who consumed one Brazil nut (300 μg/Se) a day for eight weeks. Gene expression of GPX1 and SELENOP and genotyping were measured by real-time PCR using TaqMan Assays. Global gene expression was assessed by microarray using Illumina HumanHT-12 v4 BeadChips. Brazil nut supplementation significantly increased GPX1 mRNA expression only in subjects with CC genotype at rs1050450 (p < 0.05). SELENOP mRNA expression was significantly higher in A-carriers at rs7579 either before or after supplementation (p < 0.05). Genotype for rs713041 in GPX4 affected the pattern of blood cell global gene expression. Genetic variations in selenoprotein genes modulated both GPX1 and SELENOP selenoprotein gene expression and global gene expression in response to Brazil nut supplementation. PMID:28696394

  18. Transgenic Arabidopsis Gene Expression System

    NASA Technical Reports Server (NTRS)

    Ferl, Robert; Paul, Anna-Lisa

    2009-01-01

    The Transgenic Arabidopsis Gene Expression System (TAGES) investigation is one in a pair of investigations that use the Advanced Biological Research System (ABRS) facility. TAGES uses Arabidopsis thaliana, thale cress, with sensor promoter-reporter gene constructs that render the plants as biomonitors (an organism used to determine the quality of the surrounding environment) of their environment using real-time nondestructive Green Fluorescent Protein (GFP) imagery and traditional postflight analyses.

  19. RefEx, a reference gene expression dataset as a web tool for the functional analysis of genes

    PubMed Central

    Ono, Hiromasa; Ogasawara, Osamu; Okubo, Kosaku; Bono, Hidemasa

    2017-01-01

    Gene expression data are exponentially accumulating; thus, the functional annotation of such sequence data from metadata is urgently required. However, life scientists have difficulty utilizing the available data due to its sheer magnitude and complicated access. We have developed a web tool for browsing reference gene expression pattern of mammalian tissues and cell lines measured using different methods, which should facilitate the reuse of the precious data archived in several public databases. The web tool is called Reference Expression dataset (RefEx), and RefEx allows users to search by the gene name, various types of IDs, chromosomal regions in genetic maps, gene family based on InterPro, gene expression patterns, or biological categories based on Gene Ontology. RefEx also provides information about genes with tissue-specific expression, and the relative gene expression values are shown as choropleth maps on 3D human body images from BodyParts3D. Combined with the newly incorporated Functional Annotation of Mammals (FANTOM) dataset, RefEx provides insight regarding the functional interpretation of unfamiliar genes. RefEx is publicly available at http://refex.dbcls.jp/. PMID:28850115

  20. Altered gene expression in tree shrew retina and retinal pigment epithelium produced by short periods of minus-lens wear.

    PubMed

    He, Li; Frost, Michael R; Siegwart, John T; Norton, Thomas T

    2018-03-01

    remained up-regulated. mRNA levels for six genes no longer showed differential expression, whilst nine genes, not differentially expressed at 6 h, now showed differential expression. In the combined retina + RPE after 24 h, mRNA levels for only seven genes were differentially regulated despite the differential expression of many genes in the RPE. Four genes showed the same expression in combined tissue as in retina alone, including up-regulation of VIP despite significant VIP down-regulation in RPE. Thus, hyperopia-induced GO signaling, as measured by differential gene expression, differs in the retina and the RPE. Retinal gene expression changed between 6 h and 24 h of treatment, suggesting evolution of the retinal response. Gene expression in the RPE was similar at both time points, suggesting sustained signaling. The combined retina + RPE does not accurately represent gene expression in either retina or, especially, RPE. When gene expression signatures were compared with those in choroid and sclera, GO signaling, as encoded by differential gene expression, differs in each compartment of the direct emmetropization signaling cascade. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Function and expression pattern of nonsyndromic deafness genes

    PubMed Central

    Hilgert, Nele; Smith, Richard J.H.; Van Camp, Guy

    2010-01-01

    Hearing loss is the most common sensory disorder, present in 1 of every 500 newborns. To date, 46 genes have been identified that cause nonsyndromic hearing loss, making it an extremely heterogeneous trait. This review provides a comprehensive overview of the inner ear function and expression pattern of these genes. In general, they are involved in hair bundle morphogenesis, form constituents of the extracellular matrix, play a role in cochlear ion homeostasis or serve as transcription factors. During the past few years, our knowledge of genes involved in hair bundle morphogenesis has increased substantially. We give an up-to-date overview of both the nonsyndromic and Usher syndrome genes involved in this process, highlighting proteins that interact to form macromolecular complexes. For every gene, we also summarize its expression pattern and impact on hearing at the functional level. Gene-specific cochlear expression is summarized in a unique table by structure/cell type and is illustrated on a cochlear cross-section, which is available online via the Hereditary Hearing Loss Homepage. This review should provide auditory scientists the most relevant information for all identified nonsyndromic deafness genes. PMID:19601806

  2. Locus ceruleus control of state-dependent gene expression.

    PubMed

    Cirelli, Chiara; Tononi, Giulio

    2004-06-09

    Wakefulness and sleep are accompanied by changes in behavior and neural activity, as well as by the upregulation of different functional categories of genes. However, the mechanisms responsible for such state-dependent changes in gene expression are unknown. Here we investigate to what extent state-dependent changes in gene expression depend on the central noradrenergic (NA) system, which is active in wakefulness and reduces its firing during sleep. We measured the levels of approximately 5000 transcripts expressed in the cerebral cortex of control rats and in rats pretreated with DSP-4 [N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine], a neurotoxin that removes the noradrenergic innervation of the cortex. We found that NA depletion reduces the expression of approximately 20% of known wakefulness-related transcripts. Most of these transcripts are involved in synaptic plasticity and in the cellular response to stress. In contrast, NA depletion increased the expression of the sleep-related gene encoding the translation elongation factor 2. These results indicate that the activity of the central NA system during wakefulness modulates neuronal transcription to favor synaptic potentiation and counteract cellular stress, whereas its inactivity during sleep may play a permissive role to enhance brain protein synthesis.

  3. Expression of an Msx homeobox gene in ascidians: insights into the archetypal chordate expression pattern.

    PubMed

    Ma, L; Swalla, B J; Zhou, J; Dobias, S L; Bell, J R; Chen, J; Maxson, R E; Jeffery, W R

    1996-03-01

    The Msx homeobox genes are expressed in complex patterns during vertebrate development in conjunction with inductive tissue interactions. As a means of understanding the archetypal role of Msx genes in chordates, we have isolated and characterized an Msx gene in ascidians, protochordates with a relatively simple body plan. The Mocu Msx-a and McMsx-a genes, isolated from the ascidians Molgula oculata and Molgula citrina, respectively, have homeodomains that place them in the msh-like subclass of Msx genes. Therefore, the Molgula Msx-a genes are most closely related to the msh genes previously identified in a number of invertebrates. Southern blot analysis suggests that there are one or two copies of the Msx-a gene in the Molgula genome. Northern blot and RNase protection analysis indicate that Msx-a transcripts are restricted to the developmental stages of the life cycle. In situ hybridization showed that Msx-a mRNA first appears just before gastrulation in the mesoderm (presumptive notochord and muscle) and ectoderm (neural plate) cells. Transcript levels decline in mesoderm cells after the completion of gastrulation, but are enhanced in the folding neural plate during neurulation. Later, Msx-a mRNA is also expressed in the posterior ectoderm and in a subset of the tail muscle cells. The ectoderm and mesoderm cells that express Msx-a are undergoing morphogenetic movements during gastrulation, neurulation, and tail formation. Msx-a expression ceases after these cells stop migrating. The ascidian M. citrina, in which adult tissues and organs begin to develop precociously in the larva, was used to study Msx-a expression during adult development. Msx-a transcripts are expressed in the heart primordium and the rudiments of the ampullae, epidermal protrusions with diverse functions in the juvenile. The heart and ampullae develop in regions where mesenchyme cells interact with endodermal or epidermal epithelia. A comparison of the expression patterns of the Molgula genes

  4. Salmonella induces prominent gene expression in the rat colon

    PubMed Central

    Rodenburg, Wendy; Keijer, Jaap; Kramer, Evelien; Roosing, Susanne; Vink, Carolien; Katan, Martijn B; van der Meer, Roelof; Bovee-Oudenhoven, Ingeborg MJ

    2007-01-01

    Background Salmonella enteritidis is suggested to translocate in the small intestine. In vivo it induces gene expression changes in the ileal mucosa and Peyer's patches. Stimulation of Salmonella translocation by dietary prebiotics fermented in colon suggests involvement of the colon as well. However, effects of Salmonella on colonic gene expression in vivo are largely unknown. We aimed to characterize time dependent Salmonella-induced changes of colonic mucosal gene expression in rats using whole genome microarrays. For this, rats were orally infected with Salmonella enteritidis to mimic a foodborne infection and colonic gene expression was determined at days 1, 3 and 6 post-infection (n = 8 rats per time-point). As fructo-oligosaccharides (FOS) affect colonic physiology, we analyzed colonic mucosal gene expression of FOS-fed versus cellulose-fed rats infected with Salmonella in a separate experiment. Colonic mucosal samples were isolated at day 2 post-infection. Results Salmonella affected transport (e.g. Chloride channel calcium activated 6, H+/K+ transporting Atp-ase), antimicrobial defense (e.g. Lipopolysaccharide binding protein, Defensin 5 and phospholipase A2), inflammation (e.g. calprotectin), oxidative stress related genes (e.g. Dual oxidase 2 and Glutathione peroxidase 2) and Proteolysis (e.g. Ubiquitin D and Proteosome subunit beta type 9). Furthermore, Salmonella translocation increased serum IFNγ and many interferon-related genes in colonic mucosa. The gene most strongly induced by Salmonella infection was Pancreatitis Associated Protein (Pap), showing >100-fold induction at day 6 after oral infection. Results were confirmed by Q-PCR in individual rats. Stimulation of Salmonella translocation by dietary FOS was accompanied by enhancement of the Salmonella-induced mucosal processes, not by induction of other processes. Conclusion We conclude that the colon is a target tissue for Salmonella, considering the abundant changes in mucosal gene expression

  5. Salmonella induces prominent gene expression in the rat colon.

    PubMed

    Rodenburg, Wendy; Keijer, Jaap; Kramer, Evelien; Roosing, Susanne; Vink, Carolien; Katan, Martijn B; van der Meer, Roelof; Bovee-Oudenhoven, Ingeborg M J

    2007-09-12

    Salmonella enteritidis is suggested to translocate in the small intestine. In vivo it induces gene expression changes in the ileal mucosa and Peyer's patches. Stimulation of Salmonella translocation by dietary prebiotics fermented in colon suggests involvement of the colon as well. However, effects of Salmonella on colonic gene expression in vivo are largely unknown. We aimed to characterize time dependent Salmonella-induced changes of colonic mucosal gene expression in rats using whole genome microarrays. For this, rats were orally infected with Salmonella enteritidis to mimic a foodborne infection and colonic gene expression was determined at days 1, 3 and 6 post-infection (n = 8 rats per time-point). As fructo-oligosaccharides (FOS) affect colonic physiology, we analyzed colonic mucosal gene expression of FOS-fed versus cellulose-fed rats infected with Salmonella in a separate experiment. Colonic mucosal samples were isolated at day 2 post-infection. Salmonella affected transport (e.g. Chloride channel calcium activated 6, H+/K+ transporting Atp-ase), antimicrobial defense (e.g. Lipopolysaccharide binding protein, Defensin 5 and phospholipase A2), inflammation (e.g. calprotectin), oxidative stress related genes (e.g. Dual oxidase 2 and Glutathione peroxidase 2) and Proteolysis (e.g. Ubiquitin D and Proteosome subunit beta type 9). Furthermore, Salmonella translocation increased serum IFN gamma and many interferon-related genes in colonic mucosa. The gene most strongly induced by Salmonella infection was Pancreatitis Associated Protein (Pap), showing >100-fold induction at day 6 after oral infection. Results were confirmed by Q-PCR in individual rats. Stimulation of Salmonella translocation by dietary FOS was accompanied by enhancement of the Salmonella-induced mucosal processes, not by induction of other processes. We conclude that the colon is a target tissue for Salmonella, considering the abundant changes in mucosal gene expression.

  6. Differential Connectivity in Colorectal Cancer Gene Expression Network

    PubMed

    Izadi, Fereshteh

    2018-05-30

    Colorectal cancer (CRC) is one of the challenging types of cancers; thus, exploring effective biomarkers related to colorectal could lead to significant progresses toward the treatment of this disease. In the present study, CRC gene expression datasets have been reanalyzed. Mutual differentially expressed genes across 294 normal mucosa and adjacent tumoral samples were then utilized in order to build two independent transcriptional regulatory networks. By analyzing the networks topologically, genes with differential global connectivity related to cancer state were determined for which the potential transcriptional regulators including transcription factors were identified. The majority of differentially connected genes (DCGs) were up-regulated in colorectal transcriptome experiments. Moreover, a number of these genes have been experimentally validated as cancer or CRC-associated genes. The DCGs, including GART, TGFB1, ITGA2, SLC16A5, SOX9, and MMP7, were investigated across 12 cancer types. Functional enrichment analysis followed by detailed data mining exhibited that these candidate genes could be related to CRC by mediating in metastatic cascade in addition to shared pathways with 12 cancer types by triggering the inflammatory events Our study uncovered correlated alterations in gene expression related to CRC susceptibility and progression that the potent candidate biomarkers could provide a link to disease.

  7. Bovine mammary gene expression profiling during the onset of lactation.

    PubMed

    Gao, Yuanyuan; Lin, Xueyan; Shi, Kerong; Yan, Zhengui; Wang, Zhonghua

    2013-01-01

    Lactogenesis includes two stages. Stage I begins a few weeks before parturition. Stage II is initiated around the time of parturition and extends for several days afterwards. To better understand the molecular events underlying these changes, genome-wide gene expression profiling was conducted using digital gene expression (DGE) on bovine mammary tissue at three time points (on approximately day 35 before parturition (-35 d), day 7 before parturition (-7 d) and day 3 after parturition (+3 d)). Approximately 6.2 million (M), 5.8 million (M) and 6.1 million (M) 21-nt cDNA tags were sequenced in the three cDNA libraries (-35 d, -7 d and +3 d), respectively. After aligning to the reference sequences, the three cDNA libraries included 8,662, 8,363 and 8,359 genes, respectively. With a fold change cutoff criteria of ≥ 2 or ≤-2 and a false discovery rate (FDR) of ≤ 0.001, a total of 812 genes were significantly differentially expressed at -7 d compared with -35 d (stage I). Gene ontology analysis showed that those significantly differentially expressed genes were mainly associated with cell cycle, lipid metabolism, immune response and biological adhesion. A total of 1,189 genes were significantly differentially expressed at +3 d compared with -7 d (stage II), and these genes were mainly associated with the immune response and cell cycle. Moreover, there were 1,672 genes significantly differentially expressed at +3 d compared with -35 d. Gene ontology analysis showed that the main differentially expressed genes were those associated with metabolic processes. The results suggest that the mammary gland begins to lactate not only by a gain of function but also by a broad suppression of function to effectively push most of the cell's resources towards lactation.

  8. Blue Light Modulates Murine Microglial Gene Expression in the Absence of Optogenetic Protein Expression.

    PubMed

    Cheng, Kevin P; Kiernan, Elizabeth A; Eliceiri, Kevin W; Williams, Justin C; Watters, Jyoti J

    2016-02-17

    Neural optogenetic applications over the past decade have steadily increased; however the effects of commonly used blue light paradigms on surrounding, non-optogenetic protein-expressing CNS cells are rarely considered, despite their simultaneous exposure. Here we report that blue light (450 nm) repetitively delivered in both long-duration boluses and rapid optogenetic bursts gene-specifically altered basal expression of inflammatory and neurotrophic genes in immortalized and primary murine wild type microglial cultures. In addition, blue light reduced pro-inflammatory gene expression in microglia activated with lipopolysaccharide. These results demonstrate previously unreported, off-target effects of blue light in cells not expressing optogenetic constructs. The unexpected gene modulatory effects of blue light on wild type CNS resident immune cells have novel and important implications for the neuro-optogenetic field. Further studies are needed to elucidate the molecular mechanisms and potential therapeutic utility of blue light modulation of the wild type CNS.

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

    PubMed Central

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

    2016-01-01

    Hox genes 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 Hox genes can also function in terminally differentiated tissue of the lepidopteran Bombyx mori. In this species, Antennapedia (Antp) regulates expression of sericin-1, a major silk protein gene, in the silk gland. Here, we investigated whether Antp can regulate expression of multiple genes in this tissue. By means of proteomic, RT-PCR, and in situ hybridization analyses, we demonstrate that misexpression of Antp in the posterior silk gland induced ectopic expression of major silk protein genes such as sericin-3, fhxh4, and fhxh5. These genes are normally expressed specifically in the middle silk gland as is Antp. Therefore, the evidence strongly suggests that Antp activates these silk protein genes in the middle silk gland. The putative sericin-1 activator complex (middle silk gland-intermolt-specific complex) can bind to the upstream regions of these genes, suggesting that Antp directly activates their expression. We also found that the pattern of gene expression was well conserved between B. mori and 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 Hox genes have a role as a master control in terminally differentiated tissues, possibly acting as a primary regulator for a range of physiological processes. PMID:26814126

  10. VE-Cadherin-Mediated Epigenetic Regulation of Endothelial Gene Expression.

    PubMed

    Morini, Marco F; Giampietro, Costanza; Corada, Monica; Pisati, Federica; Lavarone, Elisa; Cunha, Sara I; Conze, Lei L; O'Reilly, Nicola; Joshi, Dhira; Kjaer, Svend; George, Roger; Nye, Emma; Ma, Anqi; Jin, Jian; Mitter, Richard; Lupia, Michela; Cavallaro, Ugo; Pasini, Diego; Calado, Dinis P; Dejana, Elisabetta; Taddei, Andrea

    2018-01-19

    The mechanistic foundation of vascular maturation is still largely unknown. Several human pathologies are characterized by deregulated angiogenesis and unstable blood vessels. Solid tumors, for instance, get their nourishment from newly formed structurally abnormal vessels which present wide and irregular interendothelial junctions. Expression and clustering of the main endothelial-specific adherens junction protein, VEC (vascular endothelial cadherin), upregulate genes with key roles in endothelial differentiation and stability. We aim at understanding the molecular mechanisms through which VEC triggers the expression of a set of genes involved in endothelial differentiation and vascular stabilization. We compared a VEC-null cell line with the same line reconstituted with VEC wild-type cDNA. VEC expression and clustering upregulated endothelial-specific genes with key roles in vascular stabilization including claudin-5 , vascular endothelial-protein tyrosine phosphatase ( VE-PTP ), and von Willebrand factor ( vWf ). Mechanistically, VEC exerts this effect by inhibiting polycomb protein activity on the specific gene promoters. This is achieved by preventing nuclear translocation of FoxO1 (Forkhead box protein O1) and β-catenin, which contribute to PRC2 (polycomb repressive complex-2) binding to promoter regions of claudin-5 , VE-PTP , and vWf . VEC/β-catenin complex also sequesters a core subunit of PRC2 (Ezh2 [enhancer of zeste homolog 2]) at the cell membrane, preventing its nuclear translocation. Inhibition of Ezh2/VEC association increases Ezh2 recruitment to claudin-5 , VE-PTP , and vWf promoters, causing gene downregulation. RNA sequencing comparison of VEC-null and VEC-positive cells suggested a more general role of VEC in activating endothelial genes and triggering a vascular stability-related gene expression program. In pathological angiogenesis of human ovarian carcinomas, reduced VEC expression paralleled decreased levels of claudin-5 and VE-PTP. These

  11. 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

  12. Gene Expression in Bone

    NASA Astrophysics Data System (ADS)

    D'Ambrogio, A.

    Skeletal system has two main functions, to provide mechanical integrity for both locomotion and protection and to play an important role in mineral homeostasis. There is extensive evidence showing loss of bone mass during long-term Space-Flights. The loss is due to a break in the equilibrium between the activity of osteoblasts (the cells that forms bone) and the activity of osteoclasts (the cells that resorbs bone). Surprisingly, there is scanty information about the possible altered gene expression occurring in cells that form bone in microgravity.(Just 69 articles result from a "gene expression in microgravity" MedLine query.) Gene-chip or microarray technology allows to screen thousands of genes at the same time: the use of this technology on samples coming from cells exposed to microgravity could provide us with many important informations. For example, the identification of the molecules or structures which are the first sensors of the mechanical stress derived from lack of gravity, could help in understanding which is the first event leading to bone loss due to long-term exposure to microgravity. Consequently, this structure could become a target for a custom-designed drug. It is evident that bone mass loss, observed during long-time stay in Space, represents an accelerated model of what happens in aging osteoporosis. Therefore, the discovery and design of drugs able to interfere with the bone-loss process, could help also in preventing negative physiological processes normally observed on Earth. Considering the aims stated above, my research is designed to:

  13. 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.

  14. Regulation of ecmF gene expression and genetic hierarchy among STATa, CudA, and MybC on several prestalk A-specific gene expressions in Dictyostelium.

    PubMed

    Saga, Yukika; Inamura, Tomoka; Shimada, Nao; Kawata, Takefumi

    2016-05-01

    STATa, a Dictyostelium homologue of metazoan signal transducer and activator of transcription, is important for the organizer function in the tip region of the migrating Dictyostelium slug. We previously showed that ecmF gene expression depends on STATa in prestalk A (pstA) cells, where STATa is activated. Deletion and site-directed mutagenesis analysis of the ecmF/lacZ fusion gene in wild-type and STATa null strains identified an imperfect inverted repeat sequence, ACAAATANTATTTGT, as a STATa-responsive element. An upstream sequence element was required for efficient expression in the rear region of pstA zone; an element downstream of the inverted repeat was necessary for sufficient prestalk expression during culmination. Band shift analyses using purified STATa protein detected no sequence-specific binding to those ecmF elements. The only verified upregulated target gene of STATa is cudA gene; CudA directly activates expL7 gene expression in prestalk cells. However, ecmF gene expression was almost unaffected in a cudA null mutant. Several previously reported putative STATa target genes were also expressed in cudA null mutant but were downregulated in STATa null mutant. Moreover, mybC, which encodes another transcription factor, belonged to this category, and ecmF expression was downregulated in a mybC null mutant. These findings demonstrate the existence of a genetic hierarchy for pstA-specific genes, which can be classified into two distinct STATa downstream pathways, CudA dependent and independent. The ecmF expression is indirectly upregulated by STATa in a CudA-independent activation manner but dependent on MybC, whose expression is positively regulated by STATa. © 2016 Japanese Society of Developmental Biologists.

  15. Characterization of human myoblast differentiation for tissue-engineering purposes by quantitative gene expression analysis.

    PubMed

    Stern-Straeter, Jens; Bonaterra, Gabriel Alejandro; Kassner, Stefan S; Zügel, Stefanie; Hörmann, Karl; Kinscherf, Ralf; Goessler, Ulrich Reinhart

    2011-08-01

    Tissue engineering of skeletal muscle is an encouraging possibility for the treatment of muscle loss through the creation of functional muscle tissue in vitro from human stem cells. Currently, the preferred stem cells are primary, non-immunogenic satellite cells ( = myoblasts). The objective of this study was to determine the expression patterns of myogenic markers within the human satellite cell population during their differentiation into multinucleated myotubes for an accurate characterization of stem cell behaviour. Satellite cells were incubated (for 1, 4, 8, 12 or 16 days) with a culture medium containing either a low [ = differentiation medium (DM)] or high [ = growth medium (GM)] concentration of growth factors. Furthermore, we performed a quantitative gene expression analysis of well-defined differentiation makers: myogenic factor 5 (MYF5), myogenin (MYOG), skeletal muscle αactin1 (ACTA1), embryonic (MYH3), perinatal (MYH8) and adult skeletal muscle myosin heavy chain (MYH1). Additionally, the fusion indices of forming myotubes of MYH1, MYH8 and ACTA1 were calculated. We show that satellite cells incubated with DM expressed multiple characteriztic features of mature skeletal muscles, verified by time-dependent upregulation of MYOG, MYH1, MYH3, MYH8 and ACTA1. However, satellite cells incubated with GM did not reveal all morphological aspects of muscle differentiation. Immunocytochemical investigations with antibodies directed against the differentiation markers showed correlations between the gene expression and differentiation. Our data provide information about time-dependent gene expression of differentiation markers in human satellite cells, which can be used for maturation analyses in skeletal muscle tissue-engineering applications. Copyright © 2011 John Wiley & Sons, Ltd.

  16. Endogenous Reference Genes for Gene Expression Studies on Bicuspid Aortic Valve Associated Aortopathy in Humans.

    PubMed

    Harrison, Oliver J; Moorjani, Narain; Torrens, Christopher; Ohri, Sunil K; Cagampang, Felino R

    2016-01-01

    Bicuspid aortic valve (BAV) disease is the most common congenital cardiac abnormality and predisposes patients to life-threatening aortic complications including aortic aneurysm. Quantitative real-time reverse transcription PCR (qRT-PCR) is one of the most commonly used methods to investigate underlying molecular mechanisms involved in aortopathy. The accuracy of the gene expression data is dependent on normalization by appropriate housekeeping (HK) genes, whose expression should remain constant regardless of aortic valve morphology, aortic diameter and other factors associated with aortopathy. Here, we identified an appropriate set of HK genes to be used as endogenous reference for quantifying gene expression in ascending aortic tissue using a spin column-based RNA extraction method. Ascending aortic biopsies were collected intra-operatively from patients undergoing aortic valve and/or ascending aortic surgery. These patients had BAV or tricuspid aortic valve (TAV), and the aortas were either dilated (≥4.5cm) or undilated. The cohort had an even distribution of gender, valve disease and hypertension. The expression stability of 12 reference genes were investigated (ATP5B, ACTB, B2M, CYC1, EIF4A2, GAPDH, SDHA, RPL13A, TOP1, UBC, YWHAZ, and 18S) using geNorm software. The most stable HK genes were found to be GAPDH, UBC and ACTB. Both GAPDH and UBC demonstrated relative stability regardless of valve morphology, aortic diameter, gender and age. The expression of B2M and SDHA were found to be the least stable HK genes. We propose the use of GAPDH, UBC and ACTB as reference genes for gene expression studies of BAV aortopathy using ascending aortic tissue.

  17. A random variance model for detection of differential gene expression in small microarray experiments.

    PubMed

    Wright, George W; Simon, Richard M

    2003-12-12

    Microarray techniques provide a valuable way of characterizing the molecular nature of disease. Unfortunately expense and limited specimen availability often lead to studies with small sample sizes. This makes accurate estimation of variability difficult, since variance estimates made on a gene by gene basis will have few degrees of freedom, and the assumption that all genes share equal variance is unlikely to be true. We propose a model by which the within gene variances are drawn from an inverse gamma distribution, whose parameters are estimated across all genes. This results in a test statistic that is a minor variation of those used in standard linear models. We demonstrate that the model assumptions are valid on experimental data, and that the model has more power than standard tests to pick up large changes in expression, while not increasing the rate of false positives. This method is incorporated into BRB-ArrayTools version 3.0 (http://linus.nci.nih.gov/BRB-ArrayTools.html). ftp://linus.nci.nih.gov/pub/techreport/RVM_supplement.pdf

  18. Reference genes for normalization of gene expression studies in human osteoarthritic articular cartilage.

    PubMed

    Pombo-Suarez, Manuel; Calaza, Manuel; Gomez-Reino, Juan J; Gonzalez, Antonio

    2008-01-29

    Assessment of gene expression is an important component of osteoarthritis (OA) research, greatly improved by the development of quantitative real-time PCR (qPCR). This technique requires normalization for precise results, yet no suitable reference genes have been identified in human articular cartilage. We have examined ten well-known reference genes to determine the most adequate for this application. Analyses of expression stability in cartilage from 10 patients with hip OA, 8 patients with knee OA and 10 controls without OA were done with classical statistical tests and the software programs geNorm and NormFinder. Results from the three methods of analysis were broadly concordant. Some of the commonly used reference genes, GAPDH, ACTB and 18S RNA, performed poorly in our analysis. In contrast, the rarely used TBP, RPL13A and B2M genes were the best. It was necessary to use together several of these three genes to obtain the best results. The specific combination depended, to some extent, on the type of samples being compared. Our results provide a satisfactory set of previously unused reference genes for qPCR in hip and knee OA This confirms the need to evaluate the suitability of reference genes in every tissue and experimental situation before starting the quantitative assessment of gene expression by qPCR.

  19. Novel redox nanomedicine improves gene expression of polyion complex vector

    NASA Astrophysics Data System (ADS)

    Toh, Kazuko; Yoshitomi, Toru; Ikeda, Yutaka; Nagasaki, Yukio

    2011-12-01

    Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS) affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP) as an ROS scavenger. When polyethyleneimine (PEI)/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI)/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF)-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

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

    PubMed Central

    2014-01-01

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

  1. Structure and expression of canary myc family genes.

    PubMed Central

    Collum, R G; Clayton, D F; Alt, F W

    1991-01-01

    We found that the canary N-myc gene is highly related to mammalian N-myc genes in both the protein-coding region and the long 3' untranslated region. Examined coding regions of the canary c-myc gene were also highly related to their mammalian counterparts, but in contrast to N-myc, the canary and mammalian c-myc genes were quite divergent in their 3' untranslated regions. We readily detected N-myc and c-myc expression in the adult canary brain and found N-myc expression both at sites of proliferating neuronal precursors and in mature neurons. Images PMID:1996121

  2. Mining microarray data at NCBI's Gene Expression Omnibus (GEO)*.

    PubMed

    Barrett, Tanya; Edgar, Ron

    2006-01-01

    The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

  3. Gene expression of osteogenic factors following gene therapy in mandibular lengthening.

    PubMed

    Wu, Guoping; Zhou, Bin; Hu, Chunbing; Li, Shaolan

    2015-03-01

    This study investigated the effect of gene therapy on the expression of osteogenic mediators in mandibular distraction osteogenesis rabbits. Bilateral mandibular osteotomies were performed in 45 New-Zealand rabbits. After a latency of 3 days, the mandibles were elongated using distractors with a rate of 0.8 mm/d for 7 days. After the completion of distraction, the rabbits were randomly divided into 5 groups: 2 μg (0.1 μg/μL) of recombinant plasmid pIRES-hVEGF165-hBMP-2, recombinant plasmid pIRES-hBMP2, recombinant plasmid pIRES-hVEGF165, pIRES, and the same volume of normal saline were injected into the distraction gap of groups A, B, C, D, and E, respectively, followed by electroporation. Three animals were killed at the 7th, 14th, and 28th day after gene transfected in different groups, respectively. The lengthened mandibles were harvested and processed for immunohistochemical examinations; the mean optic densities (MODs) and integral optical density of bone morphogenetic protein (BMP-2) and transforming growth factor β1 (TGF-β1)-positive cells were measured by CMIAS-2001A computerized image analyzer. The data were analyzed with SPSS (SPSS Inc, Chicago, IL). Bone morphogenetic protein 2 and TGF-β1 staining was mainly located in inflammatory cells, monocytes, fibroblasts, osteoblasts, osteocytes, and chondrocytes in the distraction zones. Their strongest expression reached to the peak at the seventh day and decreased at the 14th day of consolidation stage; at the 28th day, they expressed weakly. Image analysis results show that, at the seventh day, the expression of BMP-2 in group B (0.26 ± 0.03, 0.36 ± 0.02) was the strongest; there was significant difference among them (P < 0.01), whereas the expression of TGF-β1 in group C (0.38 ± 0.06, 1.05 ± 0.19) is strongest followed by group A (0.34 ± 0.05, 0.95 ± 0.16) and B (0.33 ± 0.07, 0.90 ± 0.19). At every time point, the level of expression of BMP-2 and TGF-β1 in gene therapy groups (groups A, B, and

  4. Gender-Specific Gene Expression in Post-Mortem Human Brain: Localization to Sex Chromosomes

    PubMed Central

    Vawter, Marquis P; Evans, Simon; Choudary, Prabhakara; Tomita, Hiroaki; Meador-Woodruff, Jim; Molnar, Margherita; Li, Jun; Lopez, Juan F; Myers, Rick; Cox, David; Watson, Stanley J; Akil, Huda; Jones, Edward G; Bunney, William E

    2011-01-01

    Gender differences in brain development and in the prevalence of neuropsychiatric disorders such as depression have been reported. Gender differences in human brain might be related to patterns of gene expression. Microarray technology is one useful method for investigation of gene expression in brain. We investigated gene expression, cell types, and regional expression patterns of differentially expressed sex chromosome genes in brain. We profiled gene expression in male and female dorsolateral prefrontal cortex, anterior cingulate cortex, and cerebellum using the Affymetrix oligonucleotide microarray platform. Differentially expressed genes between males and females on the Y chromosome (DBY, SMCY, UTY, RPS4Y, and USP9Y) and X chromosome (XIST) were confirmed using real-time PCR measurements. In situ hybridization confirmed the differential expression of gender-specific genes and neuronal expression of XIST, RPS4Y, SMCY, and UTY in three brain regions examined. The XIST gene, which silences gene expression on regions of the X chromosome, is expressed in a subset of neurons. Since a subset of neurons express gender-specific genes, neural subpopulations may exhibit a subtle sexual dimorphism at the level of differences in gene regulation and function. The distinctive pattern of neuronal expression of XIST, RPS4Y, SMCY, and UTY and other sex chromosome genes in neuronal subpopulations may possibly contribute to gender differences in prevalence noted for some neuropsychiatric disorders. Studies of the protein expression of these sex- chromosome-linked genes in brain tissue are required to address the functional consequences of the observed gene expression differences. PMID:14583743

  5. Comparative modular analysis of gene expression in vertebrate organs.

    PubMed

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

    2012-03-29

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

  6. Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits.

    PubMed

    Mancuso, Nicholas; Shi, Huwenbo; Goddard, Pagé; Kichaev, Gleb; Gusev, Alexander; Pasaniuc, Bogdan

    2017-03-02

    Although genome-wide association studies (GWASs) have identified thousands of risk loci for many complex traits and diseases, the causal variants and genes at these loci remain largely unknown. Here, we introduce a method for estimating the local genetic correlation between gene expression and a complex trait and utilize it to estimate the genetic correlation due to predicted expression between pairs of traits. We integrated gene expression measurements from 45 expression panels with summary GWAS data to perform 30 multi-tissue transcriptome-wide association studies (TWASs). We identified 1,196 genes whose expression is associated with these traits; of these, 168 reside more than 0.5 Mb away from any previously reported GWAS significant variant. We then used our approach to find 43 pairs of traits with significant genetic correlation at the level of predicted expression; of these, eight were not found through genetic correlation at the SNP level. Finally, we used bi-directional regression to find evidence that BMI causally influences triglyceride levels and that triglyceride levels causally influence low-density lipoprotein. Together, our results provide insight into the role of gene expression in the susceptibility of complex traits and diseases. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

  7. Regulatory Divergence between Parental Alleles Determines Gene Expression Patterns in Hybrids

    PubMed Central

    Combes, Marie-Christine; Hueber, Yann; Dereeper, Alexis; Rialle, Stéphanie; Herrera, Juan-Carlos; Lashermes, Philippe

    2015-01-01

    Both hybridization and allopolyploidization generate novel phenotypes by conciliating divergent genomes and regulatory networks in the same cellular context. To understand the rewiring of gene expression in hybrids, the total expression of 21,025 genes and the allele-specific expression of over 11,000 genes were quantified in interspecific hybrids and their parental species, Coffea canephora and Coffea eugenioides using RNA-seq technology. Between parental species, cis- and trans-regulatory divergences affected around 32% and 35% of analyzed genes, respectively, with nearly 17% of them showing both. The relative importance of trans-regulatory divergences between both species could be related to their low genetic divergence and perennial habit. In hybrids, among divergently expressed genes between parental species and hybrids, 77% was expressed like one parent (expression level dominance), including 65% like C. eugenioides. Gene expression was shown to result from the expression of both alleles affected by intertwined parental trans-regulatory factors. A strong impact of C. eugenioides trans-regulatory factors on the upregulation of C. canephora alleles was revealed. The gene expression patterns appeared determined by complex combinations of cis- and trans-regulatory divergences. In particular, the observed biased expression level dominance seemed to be derived from the asymmetric effects of trans-regulatory parental factors on regulation of alleles. More generally, this study illustrates the effects of divergent trans-regulatory parental factors on the gene expression pattern in hybrids. The characteristics of the transcriptional response to hybridization appear to be determined by the compatibility of gene regulatory networks and therefore depend on genetic divergences between the parental species and their evolutionary history. PMID:25819221

  8. Periodontal therapy alters gene expression of peripheral blood monocytes

    PubMed Central

    Papapanou, Panos N.; Sedaghatfar, Michael H.; Demmer, Ryan T.; Wolf, Dana L.; Yang, Jun; Roth, Georg A.; Celenti, Romanita; Belusko, Paul B.; Lalla, Evanthia; Pavlidis, Paul

    2009-01-01

    Aims We investigated the effects of periodontal therapy on gene expression of peripheral blood monocytes. Methods Fifteen patients with periodontitis gave blood samples at four time points: 1 week before periodontal treatment (#1), at treatment initiation (baseline, #2), 6-week (#3) and 10-week post-baseline (#4). At baseline and 10 weeks, periodontal status was recorded and subgingival plaque samples were obtained. Periodontal therapy (periodontal surgery and extractions without adjunctive antibiotics) was completed within 6 weeks. At each time point, serum concentrations of 19 biomarkers were determined. Peripheral blood monocytes were purified, RNA was extracted, reverse-transcribed, labelled and hybridized with AffymetrixU133Plus2.0 chips. Expression profiles were analysed using linear random-effects models. Further analysis of gene ontology terms summarized the expression patterns into biologically relevant categories. Differential expression of selected genes was confirmed by real-time reverse transcriptase-polymerase chain reaction in a subset of patients. Results Treatment resulted in a substantial improvement in clinical periodontal status and reduction in the levels of several periodontal pathogens. Expression profiling over time revealed more than 11,000 probe sets differentially expressed at a false discovery rate of <0.05. Approximately 1/3 of the patients showed substantial changes in expression in genes relevant to innate immunity, apoptosis and cell signalling. Conclusions The data suggest that periodontal therapy may alter monocytic gene expression in a manner consistent with a systemic anti-inflammatory effect. PMID:17716309

  9. Prediction of gene expression in embryonic structures of Drosophila melanogaster.

    PubMed

    Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

    2007-07-01

    Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms.

  10. Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster

    PubMed Central

    Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

    2007-01-01

    Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms. PMID:17658945

  11. Expression of Msx genes in regenerating and developing limbs of axolotl.

    PubMed

    Koshiba, K; Kuroiwa, A; Yamamoto, H; Tamura, K; Ide, H

    1998-12-15

    Msx genes, homeobox-containing genes, have been isolated as homologues of the Drosophila msh gene and are thought to play important roles in the development of chick or mouse limb buds. We isolated two Msx genes, Msx1 and Msx2, from regenerating blastemas of axolotl limbs and examined their expression patterns using Northern blot and whole mount in situ hybridization during regeneration and development. Northern blot analysis revealed that the expression level of both Msx genes increased during limb regeneration. The Msx2 expression level increased in the blastema at the early bud stage, and Msx1 expression level increased at the late bud stage. Whole mount in situ hybridization revealed that Msx2 was expressed in the distal mesenchyme and Msx1 in the entire mesenchyme of the blastema at the late bud stage. In the developing limb bud, Msx1 was expressed in the entire mesenchyme, while Msx2 was expressed in the distal and peripheral mesenchyme. The expression patterns of Msx genes in the blastemas and limb buds of the axolotl were different from those reported for chick or mouse limb buds. These expression patterns of axolotl Msx genes are discussed in relation to the blastema or limb bud morphology and their possible roles in limb patterning.

  12. Gene expression changes with age in skin, adipose tissue, blood and brain.

    PubMed

    Glass, Daniel; Viñuela, Ana; Davies, Matthew N; Ramasamy, Adaikalavan; Parts, Leopold; Knowles, David; Brown, Andrew A; Hedman, Asa K; Small, Kerrin S; Buil, Alfonso; Grundberg, Elin; Nica, Alexandra C; Di Meglio, Paola; Nestle, Frank O; Ryten, Mina; Durbin, Richard; McCarthy, Mark I; Deloukas, Panagiotis; Dermitzakis, Emmanouil T; Weale, Michael E; Bataille, Veronique; Spector, Tim D

    2013-07-26

    Previous studies have demonstrated that gene expression levels change with age. These changes are hypothesized to influence the aging rate of an individual. We analyzed gene expression changes with age in abdominal skin, subcutaneous adipose tissue and lymphoblastoid cell lines in 856 female twins in the age range of 39-85 years. Additionally, we investigated genotypic variants involved in genotype-by-age interactions to understand how the genomic regulation of gene expression alters with age. Using a linear mixed model, differential expression with age was identified in 1,672 genes in skin and 188 genes in adipose tissue. Only two genes expressed in lymphoblastoid cell lines showed significant changes with age. Genes significantly regulated by age were compared with expression profiles in 10 brain regions from 100 postmortem brains aged 16 to 83 years. We identified only one age-related gene common to the three tissues. There were 12 genes that showed differential expression with age in both skin and brain tissue and three common to adipose and brain tissues. Skin showed the most age-related gene expression changes of all the tissues investigated, with many of the genes being previously implicated in fatty acid metabolism, mitochondrial activity, cancer and splicing. A significant proportion of age-related changes in gene expression appear to be tissue-specific with only a few genes sharing an age effect in expression across tissues. More research is needed to improve our understanding of the genetic influences on aging and the relationship with age-related diseases.

  13. 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

  14. A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

    PubMed Central

    Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

    2015-01-01

    In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

  15. A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

    PubMed

    Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

    2015-01-01

    In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data.

  16. Selection of reference genes for gene expression studies in heart failure for left and right ventricles.

    PubMed

    Li, Mengmeng; Rao, Man; Chen, Kai; Zhou, Jianye; Song, Jiangping

    2017-07-15

    Real-time quantitative reverse transcriptase-PCR (qRT-PCR) is a feasible tool for determining gene expression profiles, but the accuracy and reliability of the results depends on the stable expression of selected housekeeping genes in different samples. By far, researches on stable housekeeping genes in human heart failure samples are rare. Moreover the effect of heart failure on the expression of housekeeping genes in right and left ventricles is yet to be studied. Therefore we aim to provide stable housekeeping genes for both ventricles in heart failure and normal heart samples. In this study, we selected seven commonly used housekeeping genes as candidates. By using the qRT-PCR, the expression levels of ACTB, RAB7A, GAPDH, REEP5, RPL5, PSMB4 and VCP in eight heart failure and four normal heart samples were assessed. The stability of candidate housekeeping genes was evaluated by geNorm and Normfinder softwares. GAPDH showed the least variation in all heart samples. Results also indicated the difference of gene expression existed in heart failure left and right ventricles. GAPDH had the highest expression stability in both heart failure and normal heart samples. We also propose using different sets of housekeeping genes for left and right ventricles respectively. The combination of RPL5, GAPDH and PSMB4 is suitable for the right ventricle and the combination of GAPDH, REEP5 and RAB7A is suitable for the left ventricle. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Selection of reliable reference genes for gene expression studies in Trichoderma afroharzianum LTR-2 under oxalic acid stress.

    PubMed

    Lyu, Yuping; Wu, Xiaoqing; Ren, He; Zhou, Fangyuan; Zhou, Hongzi; Zhang, Xinjian; Yang, Hetong

    2017-10-01

    An appropriate reference gene is required to get reliable results from gene expression analysis by quantitative real-time reverse transcription PCR (qRT-PCR). In order to identify stable and reliable reference genes in Trichoderma afroharzianum under oxalic acid (OA) stress, six commonly used housekeeping genes, i.e., elongation factor 1, ubiquitin, ubiquitin-conjugating enzyme, glyceraldehyde-3-phosphate dehydrogenase, α-tubulin, actin, from the effective biocontrol isolate T. afroharzianum strain LTR-2 were tested for their expression during growth in liquid culture amended with OA. Four in silico programs (comparative ΔCt, NormFinder, geNorm and BestKeeper) were used to evaluate the expression stabilities of six candidate reference genes. The elongation factor 1 gene EF-1 was identified as the most stably expressed reference gene, and was used as the normalizer to quantify the expression level of the oxalate decarboxylase coding gene OXDC in T. afroharzianum strain LTR-2 under OA stress. The result showed that the expression of OXDC was significantly up-regulated as expected. This study provides an effective method to quantify expression changes of target genes in T. afroharzianum under OA stress. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. The human phospholamban gene: structure and expression.

    PubMed

    McTiernan, C F; Frye, C S; Lemster, B H; Kinder, E A; Ogletree-Hughes, M L; Moravec, C S; Feldman, A M

    1999-03-01

    Phospholamban, through modulation of sarcoplasmic reticulum calcium-ATPase activity, is a key regulator of cardiac diastolic function. Alterations in phospholamban expression may define parameters of muscle relaxation. In experimental animals, phospholamban is differentially expressed in various striated and smooth muscles, and within the four chambers of the heart. Decreased phospholamban expression within the heart during heart failure has also been observed. Furthermore, regulatory elements of mammalian phospholamban genes remain poorly defined. To extend these studies to humans, we (1) characterized phospholamban expression in various human organs, (2) isolated genomic clones encoding the human phospholamban gene, and (3) prepared human phospholamban promoter/luciferase reporter constructs and performed transient transfection assays to begin identification of regulatory elements. We observed that human ventricle and quadriceps displayed high levels of phospholamban transcripts and proteins, with markedly lower expression observed in smooth muscles, while the right atria also expressed low levels of phospholamban. The human phospholamban gene structure closely resembles that reported for chicken, rabbit, rat, and mouse. Comparison of the human to other mammalian phospholamban genes indicates a marked conservation of sequence for at least 217 bp upstream of the transcription start site, which contains conserved motifs for GATA, CP1/NFY, M-CAT-like, and E-box elements. Transient transfection assays with a series of plasmids containing deleted 5' flanking regions (between -2530 and -66 through +85) showed that sequences between -169 and the CP1-box at -93 were required for maximal promoter activity in neonatal rat cardiomyocytes. Activity of these reporters in HeLa cells was markedly lower than that observed in rat cardiomyocytes, suggesting at least a partial tissue selectivity of these reporter constructs.

  19. DigOut: viewing differential expression genes as outliers.

    PubMed

    Yu, Hui; Tu, Kang; Xie, Lu; Li, Yuan-Yuan

    2010-12-01

    With regards to well-replicated two-conditional microarray datasets, the selection of differentially expressed (DE) genes is a well-studied computational topic, but for multi-conditional microarray datasets with limited or no replication, the same task is not properly addressed by previous studies. This paper adopts multivariate outlier analysis to analyze replication-lacking multi-conditional microarray datasets, finding that it performs significantly better than the widely used limit fold change (LFC) model in a simulated comparative experiment. Compared with the LFC model, the multivariate outlier analysis also demonstrates improved stability against sample variations in a series of manipulated real expression datasets. The reanalysis of a real non-replicated multi-conditional expression dataset series leads to satisfactory results. In conclusion, a multivariate outlier analysis algorithm, like DigOut, is particularly useful for selecting DE genes from non-replicated multi-conditional gene expression dataset.

  20. Coupling between nucleotide excision repair and gene expression.

    PubMed

    Cambindo Botto, Adrián E; Muñoz, Juan C; Muñoz, Manuel J

    2018-05-17

    Gene expression and DNA repair are fundamental processes for life. During the last decade, accumulating experimental evidence point towards different modes of coupling between these processes. Here we discuss the molecular mechanisms by which RNAPII-dependent transcription affects repair by the Nucleotide Excision Repair system (NER) and how NER activity, through the generation of single stranded DNA intermediates and activation of the DNA damage response kinase ATR, drives gene expression in a genotoxic scenario. Since NER-dependent repair is compromised in Xeroderma Pigmentosum (XP) patients, and having in mind that these patients present a high degree of clinical heterogeneity, we speculate that some of the clinical features of XP patients can be explained by misregulation of gene expression.

  1. Complexity of Gene Expression Evolution after Duplication: Protein Dosage Rebalancing

    PubMed Central

    Rogozin, Igor B.

    2014-01-01

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

  2. The genetic architecture of gene expression levels in wild baboons.

    PubMed

    Tung, Jenny; Zhou, Xiang; Alberts, Susan C; Stephens, Matthew; Gilad, Yoav

    2015-02-25

    Primate evolution has been argued to result, in part, from changes in how genes are regulated. However, we still know little about gene regulation in natural primate populations. We conducted an RNA sequencing (RNA-seq)-based study of baboons from an intensively studied wild population. We performed complementary expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses, discovering substantial evidence for, and surprising power to detect, genetic effects on gene expression levels in the baboons. eQTL were most likely to be identified for lineage-specific, rapidly evolving genes; interestingly, genes with eQTL significantly overlapped between baboons and a comparable human eQTL data set. Our results suggest that genes vary in their tolerance of genetic perturbation, and that this property may be conserved across species. Further, they establish the feasibility of eQTL mapping using RNA-seq data alone, and represent an important step towards understanding the genetic architecture of gene expression in primates.

  3. Reliable reference genes for normalization of gene expression data in tea plants (Camellia sinensis) exposed to metal stresses.

    PubMed

    Wang, Ming-Le; Li, Qing-Hui; Xin, Hua-Hong; Chen, Xuan; Zhu, Xu-Jun; Li, Xing-Hui

    2017-01-01

    Tea plants [Camellia sinensis (L.) O. Kuntze] are an important leaf-type crop that are widely used for the production of non-alcoholic beverages in the world. Exposure to excessive amounts of heavy metals adversely affects the quality and yield of tea leaves. To analyze the molecular responses of tea plants to heavy metals, a reliable quantification of gene expression is important and of major importance herein is the normalization of the measured expression levels for the target genes. Ideally, stably expressed reference genes should be evaluated in all experimental systems. In this study, 12 candidate reference genes (i.e., 18S rRNA, Actin, CYP, EF-1α, eIF-4α, GAPDH, MON1, PP2AA3, TBP, TIP41, TUA, and UBC) were cloned from tea plants, and the stability of their expression was examined systematically in 60 samples exposed to diverse heavy metals (i.e., manganese, aluminum, copper, iron, and zinc). Three Excel-based algorithms (geNorm, NormFinder, and BestKeeper) were used to evaluate the expression stability of these genes. PP2AA3 and 18S rRNA were the most stably expressed genes, even though their expression profiles exhibited some variability. Moreover, commonly used reference genes (i.e., GAPDH and TBP) were the least appropriate reference genes for most samples. To further validate the suitability of the analyzed reference genes, the expression level of a phytochelatin synthase gene (i.e., CsPCS1) was determined using the putative reference genes for data normalizations. Our results may be beneficial for future studies involving the quantification of relative gene expression levels in tea plants.

  4. Reliable reference genes for normalization of gene expression data in tea plants (Camellia sinensis) exposed to metal stresses

    PubMed Central

    Wang, Ming-Le; Li, Qing-Hui; Xin, Hua-Hong; Chen, Xuan; Zhu, Xu-Jun

    2017-01-01

    Tea plants [Camellia sinensis (L.) O. Kuntze] are an important leaf-type crop that are widely used for the production of non-alcoholic beverages in the world. Exposure to excessive amounts of heavy metals adversely affects the quality and yield of tea leaves. To analyze the molecular responses of tea plants to heavy metals, a reliable quantification of gene expression is important and of major importance herein is the normalization of the measured expression levels for the target genes. Ideally, stably expressed reference genes should be evaluated in all experimental systems. In this study, 12 candidate reference genes (i.e., 18S rRNA, Actin, CYP, EF-1α, eIF-4α, GAPDH, MON1, PP2AA3, TBP, TIP41, TUA, and UBC) were cloned from tea plants, and the stability of their expression was examined systematically in 60 samples exposed to diverse heavy metals (i.e., manganese, aluminum, copper, iron, and zinc). Three Excel-based algorithms (geNorm, NormFinder, and BestKeeper) were used to evaluate the expression stability of these genes. PP2AA3 and 18S rRNA were the most stably expressed genes, even though their expression profiles exhibited some variability. Moreover, commonly used reference genes (i.e., GAPDH and TBP) were the least appropriate reference genes for most samples. To further validate the suitability of the analyzed reference genes, the expression level of a phytochelatin synthase gene (i.e., CsPCS1) was determined using the putative reference genes for data normalizations. Our results may be beneficial for future studies involving the quantification of relative gene expression levels in tea plants. PMID:28453515

  5. Evaluation of stability and validation of reference genes for RT-qPCR expression studies in rice plants under water deficit.

    PubMed

    Auler, Priscila Ariane; Benitez, Letícia Carvalho; do Amaral, Marcelo Nogueira; Vighi, Isabel Lopes; Dos Santos Rodrigues, Gabriela; da Maia, Luciano Carlos; Braga, Eugenia Jacira Bolacel

    2017-05-01

    Many studies use strategies that allow for the identification of a large number of genes expressed in response to different stress conditions to which the plant is subjected throughout its cycle. In order to obtain accurate and reliable results in gene expression studies, it is necessary to use reference genes, which must have uniform expression in the majority of cells in the organism studied. RNA isolation of leaves and expression analysis in real-time quantitative polymerase chain reaction (RT-qPCR) were carried out. In this study, nine candidate reference genes were tested, actin 11 (ACT11), ubiquitin conjugated to E2 enzyme (UBC-E2), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), beta tubulin (β-tubulin), eukaryotic initiation factor 4α (eIF-4α), ubiquitin 10 (UBQ10), ubiquitin 5 (UBQ5), aquaporin TIP41 (TIP41-Like) and cyclophilin, in two genotypes of rice, AN Cambará and BRS Querência, with different levels of soil moisture (20%, 10% and recovery) in the vegetative (V5) and reproductive stages (period preceding flowering). Currently, there are different softwares that perform stability analyses and define the most suitable reference genes for a particular study. In this study, we used five different methods: geNorm, BestKeeper, ΔCt method, NormFinder and RefFinder. The results indicate that UBC-E2 and UBQ5 can be used as reference genes in all samples and softwares evaluated. The genes β-tubulin and eIF-4α, traditionally used as reference genes, along with GAPDH, presented lower stability values. The gene expression of basic leucine zipper (bZIP23 and bZIP72) was used to validate the selected reference genes, demonstrating that the use of an inappropriate reference can induce erroneous results.

  6. Blue Light Modulates Murine Microglial Gene Expression in the Absence of Optogenetic Protein Expression

    PubMed Central

    Cheng, Kevin P.; Kiernan, Elizabeth A.; Eliceiri, Kevin W.; Williams, Justin C.; Watters, Jyoti J.

    2016-01-01

    Neural optogenetic applications over the past decade have steadily increased; however the effects of commonly used blue light paradigms on surrounding, non-optogenetic protein-expressing CNS cells are rarely considered, despite their simultaneous exposure. Here we report that blue light (450 nm) repetitively delivered in both long-duration boluses and rapid optogenetic bursts gene-specifically altered basal expression of inflammatory and neurotrophic genes in immortalized and primary murine wild type microglial cultures. In addition, blue light reduced pro-inflammatory gene expression in microglia activated with lipopolysaccharide. These results demonstrate previously unreported, off-target effects of blue light in cells not expressing optogenetic constructs. The unexpected gene modulatory effects of blue light on wild type CNS resident immune cells have novel and important implications for the neuro-optogenetic field. Further studies are needed to elucidate the molecular mechanisms and potential therapeutic utility of blue light modulation of the wild type CNS. PMID:26883795

  7. Characteristics of functional enrichment and gene expression level of human putative transcriptional target genes.

    PubMed

    Osato, Naoki

    2018-01-19

    Transcriptional target genes show functional enrichment of genes. However, how many and how significantly transcriptional target genes include functional enrichments are still unclear. To address these issues, I predicted human transcriptional target genes using open chromatin regions, ChIP-seq data and DNA binding sequences of transcription factors in databases, and examined functional enrichment and gene expression level of putative transcriptional target genes. Gene Ontology annotations showed four times larger numbers of functional enrichments in putative transcriptional target genes than gene expression information alone, independent of transcriptional target genes. To compare the number of functional enrichments of putative transcriptional target genes between cells or search conditions, I normalized the number of functional enrichment by calculating its ratios in the total number of transcriptional target genes. With this analysis, native putative transcriptional target genes showed the largest normalized number of functional enrichments, compared with target genes including 5-60% of randomly selected genes. The normalized number of functional enrichments was changed according to the criteria of enhancer-promoter interactions such as distance from transcriptional start sites and orientation of CTCF-binding sites. Forward-reverse orientation of CTCF-binding sites showed significantly higher normalized number of functional enrichments than the other orientations. Journal papers showed that the top five frequent functional enrichments were related to the cellular functions in the three cell types. The median expression level of transcriptional target genes changed according to the criteria of enhancer-promoter assignments (i.e. interactions) and was correlated with the changes of the normalized number of functional enrichments of transcriptional target genes. Human putative transcriptional target genes showed significant functional enrichments. Functional

  8. 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

  9. Modeling and validation of autoinducer-mediated bacterial gene expression in microfluidic environments

    PubMed Central

    Austin, Caitlin M.; Stoy, William; Su, Peter; Harber, Marie C.; Bardill, J. Patrick; Hammer, Brian K.; Forest, Craig R.

    2014-01-01

    Biosensors exploiting communication within genetically engineered bacteria are becoming increasingly important for monitoring environmental changes. Currently, there are a variety of mathematical models for understanding and predicting how genetically engineered bacteria respond to molecular stimuli in these environments, but as sensors have miniaturized towards microfluidics and are subjected to complex time-varying inputs, the shortcomings of these models have become apparent. The effects of microfluidic environments such as low oxygen concentration, increased biofilm encapsulation, diffusion limited molecular distribution, and higher population densities strongly affect rate constants for gene expression not accounted for in previous models. We report a mathematical model that accurately predicts the biological response of the autoinducer N-acyl homoserine lactone-mediated green fluorescent protein expression in reporter bacteria in microfluidic environments by accommodating these rate constants. This generalized mass action model considers a chain of biomolecular events from input autoinducer chemical to fluorescent protein expression through a series of six chemical species. We have validated this model against experimental data from our own apparatus as well as prior published experimental results. Results indicate accurate prediction of dynamics (e.g., 14% peak time error from a pulse input) and with reduced mean-squared error with pulse or step inputs for a range of concentrations (10 μM–30 μM). This model can help advance the design of genetically engineered bacteria sensors and molecular communication devices. PMID:25379076

  10. Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

    PubMed

    Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

    2015-06-01

    To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Regulatory divergence between parental alleles determines gene expression patterns in hybrids.

    PubMed

    Combes, Marie-Christine; Hueber, Yann; Dereeper, Alexis; Rialle, Stéphanie; Herrera, Juan-Carlos; Lashermes, Philippe

    2015-03-29

    Both hybridization and allopolyploidization generate novel phenotypes by conciliating divergent genomes and regulatory networks in the same cellular context. To understand the rewiring of gene expression in hybrids, the total expression of 21,025 genes and the allele-specific expression of over 11,000 genes were quantified in interspecific hybrids and their parental species, Coffea canephora and Coffea eugenioides using RNA-seq technology. Between parental species, cis- and trans-regulatory divergences affected around 32% and 35% of analyzed genes, respectively, with nearly 17% of them showing both. The relative importance of trans-regulatory divergences between both species could be related to their low genetic divergence and perennial habit. In hybrids, among divergently expressed genes between parental species and hybrids, 77% was expressed like one parent (expression level dominance), including 65% like C. eugenioides. Gene expression was shown to result from the expression of both alleles affected by intertwined parental trans-regulatory factors. A strong impact of C. eugenioides trans-regulatory factors on the upregulation of C. canephora alleles was revealed. The gene expression patterns appeared determined by complex combinations of cis- and trans-regulatory divergences. In particular, the observed biased expression level dominance seemed to be derived from the asymmetric effects of trans-regulatory parental factors on regulation of alleles. More generally, this study illustrates the effects of divergent trans-regulatory parental factors on the gene expression pattern in hybrids. The characteristics of the transcriptional response to hybridization appear to be determined by the compatibility of gene regulatory networks and therefore depend on genetic divergences between the parental species and their evolutionary history. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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

    PubMed Central

    Dong, Xiangshu; Yi, Hankuil; Lee, Jeongyeo; Nou, Ill-Sup; Han, Ching-Tack; Hur, Yoonkang

    2015-01-01

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

  13. Gene expression meta-analysis identifies chromosomal regions and candidate genes involved in breast cancer metastasis.

    PubMed

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

    2009-01-01

    Breast cancer cells exhibit complex karyotypic alterations causing deregulation of numerous genes. Some of these genes are probably causal for cancer formation and local growth whereas others are causal for the various steps of metastasis. In a fraction of tumors deregulation of the same genes might be caused by epigenetic modulations, point mutations or the influence of other genes. We have investigated the relation of gene expression and chromosomal position, using eight datasets including more than 1200 breast tumors, to identify chromosomal regions and candidate genes possibly causal for breast cancer metastasis. By use of "Gene Set Enrichment Analysis" we have ranked chromosomal regions according to their relation to metastasis. Overrepresentation analysis identified regions with increased expression for chromosome 1q41-42, 8q24, 12q14, 16q22, 16q24, 17q12-21.2, 17q21-23, 17q25, 20q11, and 20q13 among metastasizing tumors and reduced gene expression at 1p31-21, 8p22-21, and 14q24. By analysis of genes with extremely imbalanced expression in these regions we identified DIRAS3 at 1p31, PSD3, LPL, EPHX2 at 8p21-22, and FOS at 14q24 as candidate metastasis suppressor genes. Potential metastasis promoting genes includes RECQL4 at 8q24, PRMT7 at 16q22, GINS2 at 16q24, and AURKA at 20q13.

  14. Expression analysis of dihydroflavonol 4-reductase genes in Petunia hybrida.

    PubMed

    Chu, Y X; Chen, H R; Wu, A Z; Cai, R; Pan, J S

    2015-05-12

    Dihydroflavonol 4-reductase (DFR) genes from Rosa chinensis (Asn type) and Calibrachoa hybrida (Asp type), driven by a CaMV 35S promoter, were integrated into the petunia (Petunia hybrida) cultivar 9702. Exogenous DFR gene expression characteristics were similar to flower-color changes, and effects on anthocyanin concentration were observed in both types of DFR gene transformants. Expression analysis showed that exogenous DFR genes were expressed in all of the tissues, but the expression levels were significantly different. However, both of them exhibited a high expression level in petals that were starting to open. The introgression of DFR genes may significantly change DFR enzyme activity. Anthocyanin ultra-performance liquid chromatography results showed that anthocyanin concentrations changed according to DFR enzyme activity. Therefore, the change in flower color was probably the result of a DFR enzyme change. Pelargonidin 3-O-glucoside was found in two different transgenic petunias, indicating that both CaDFR and RoDFR could catalyze dihydrokaempferol. Our results also suggest that transgenic petunias with DFR gene of Asp type could biosynthesize pelargonidin 3-O-glucoside.

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

    PubMed

    Li, Ying; He, Ye; Zhang, Yu

    2016-11-01

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

  16. ADGO: analysis of differentially expressed gene sets using composite GO annotation.

    PubMed

    Nam, Dougu; Kim, Sang-Bae; Kim, Seon-Kyu; Yang, Sungjin; Kim, Seon-Young; Chu, In-Sun

    2006-09-15

    Genes are typically expressed in modular manners in biological processes. Recent studies reflect such features in analyzing gene expression patterns by directly scoring gene sets. Gene annotations have been used to define the gene sets, which have served to reveal specific biological themes from expression data. However, current annotations have limited analytical power, because they are classified by single categories providing only unary information for the gene sets. Here we propose a method for discovering composite biological themes from expression data. We intersected two annotated gene sets from different categories of Gene Ontology (GO). We then scored the expression changes of all the single and intersected sets. In this way, we were able to uncover, for example, a gene set with the molecular function F and the cellular component C that showed significant expression change, while the changes in individual gene sets were not significant. We provided an exemplary analysis for HIV-1 immune response. In addition, we tested the method on 20 public datasets where we found many 'filtered' composite terms the number of which reached approximately 34% (a strong criterion, 5% significance) of the number of significant unary terms on average. By using composite annotation, we can derive new and improved information about disease and biological processes from expression data. We provide a web application (ADGO: http://array.kobic.re.kr/ADGO) for the analysis of differentially expressed gene sets with composite GO annotations. The user can analyze Affymetrix and dual channel array (spotted cDNA and spotted oligo microarray) data for four species: human, mouse, rat and yeast. chu@kribb.re.kr http://array.kobic.re.kr/ADGO.

  17. Analysis of baseline gene expression levels from ...

    EPA Pesticide Factsheets

    The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in gene expression. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selectiv

  18. GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

    PubMed Central

    Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

    2009-01-01

    Background DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. Results GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations

  19. GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.

    PubMed

    Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

    2009-09-03

    DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically

  20. Human AZU-1 gene, variants thereof and expressed gene products

    DOEpatents

    Chen, Huei-Mei; Bissell, Mina

    2004-06-22

    A human AZU-1 gene, mutants, variants and fragments thereof. Protein products encoded by the AZU-1 gene and homologs encoded by the variants of AZU-1 gene acting as tumor suppressors or markers of malignancy progression and tumorigenicity reversion. Identification, isolation and characterization of AZU-1 and AZU-2 genes localized to a tumor suppressive locus at chromosome 10q26, highly expressed in nonmalignant and premalignant cells derived from a human breast tumor progression model. A recombinant full length protein sequences encoded by the AZU-1 gene and nucleotide sequences of AZU-1 and AZU-2 genes and variant and fragments thereof. Monoclonal or polyclonal antibodies specific to AZU-1, AZU-2 encoded protein and to AZU-1, or AZU-2 encoded protein homologs.