Abstract Background Conventional differential gene expression analysis by methods such as students t-test, SAM, and Empirical Bayes often searches for statistically significant genes without considering the interactions among them. Network-based approaches provide a natural way to study these interactions and to investigate the rewiring interactions in disease versus control groups. In this paper, we apply weighted graphical LASSO (wgLASSO) algorithm to integrate a data-driven network model with prior biological knowledge (i.e., protein-protein interactions) for biological network inference. We propose a novel differentially weighted graphical LASSO (dwgLASSO) algorithm that builds group-specific networks and perform network-based differential gene expression analysis to select biomarker candidates by considering their topological differences between the groups. Results Through simulation, we showed that wgLASSO can achieve better performance in building biologically relevant networks than ...
Gene Expression Profiling Analysis of Bisphenol A-Induced Perturbation in Biological Processes in ER-Negative HEK293 Cells. . Biblioteca virtual para leer y descargar libros, documentos, trabajos y tesis universitarias en PDF. Material universiario, documentación y tareas realizadas por universitarios en nuestra biblioteca. Para descargar gratis y para leer online.
The heterogeneity of prostate cancers extends within clinical states and across states. At the extreme ends of the clinical spectrum are prognostically favorable localized tumors with a low biological potential for metastasis and tumors with a high propensity for early dissemination that are invariably lethal. These clinical phenotypes are related in part to the intrinsic biology of tumor cells and are reflected in the pattern of expression of specific genes. Using comprehensive gene expression analysis of tumor samples representing the nonmetastatic and metastatic phenotypes, we identified genes that were consistently and strongly differentially expressed and represent common and valid biological differences underlying clinical heterogeneity.. Few prior studies have used high-throughput gene expression analysis to study prostate cancer metastases. One reason is that well-preserved surgical tissue samples of metastatic prostate cancer are rare, which limits the availability of appropriate ...
Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified. Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n = 101) and/or poor quality control criteria (n = 10) (test set). With 10-marker classifiers, all training set samples as well as 97 of the 101 test
Osteoarthritis (OA) is characterized by alterations to subchondral bone as well as articular cartilage. Changes to bone in OA have also been identified at sites distal to the affected joint, which include increased bone volume fraction and reduced bone mineralization. Altered bone remodelling has been proposed to underlie these bone changes in OA. To investigate the molecular basis for these changes, we performed microarray gene expression profiling of bone obtained at autopsy from individuals with no evidence of joint disease (control) and from individuals undergoing joint replacement surgery for either degenerative hip OA, or fractured neck of femur (osteoporosis [OP]). The OP sample set was included because an inverse association, with respect to bone density, has been observed between OA and the low bone density disease OP. Compugen human 19K-oligo microarray slides were used to compare the gene expression profiles of OA, control and OP bone samples. Four sets of samples were analyzed, comprising 10
Since their first use nearly fifteen years ago [1], microarray gene expression profiling experiments have become a ubiquitous tool in the study of disease. The vast number of gene transcripts assayed by modern microarrays (105-106) has driven forward our understanding of biological processes tremendously, elucidating the genes and regulatory mechanisms that drive specific phenotypes. However, the high-dimensional data produced in these experiments--often comprising many more variables than samples and subject to noise--also presents analytical challenges.. The analysis of gene expression data can be broadly grouped into two categories: the identification of differentially expressed genes (or gene-sets) between two or more known conditions, and the unsupervised identification (clustering) of samples or genes that exhibit similar profiles across the data set. In the former case, each gene is tested individually for association with the phenotype of interest, adjusting at the end for the vast ...
A peripheral blood gene expression score is associated with plaque volume and phenotype by intravascular ultrasound with radiofrequency backscatter analysis: results from the ATLANTA study
Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for molecular subtype classification in diffuse large B-cell lymphoma: a report from the International DLBCL Rituximab-CHOP Consortium Program Study.
Purpose: Retinopathy of prematurity (ROP) is a common blinding disease caused by the abnormal growth of blood vessels in the retina of premature babies with low birth weight and low gestation period. However, the mechanisms and factors contributing to the progression of ROP are still unknown. The present study aimed to identify gene(s) responsible for ROP progression by a global gene expression profiling.. Methods: From a cohort of 600 subjects comprising ROP babies (n=350) and controls (n=250), 15 ROP babies at any stage (gestational age [GA] ≤ 35 weeks and/or birth weight [BW] ≤ 1700 g) and premature babies with no ROP (n=6) (GA ≤ 35 weeks and/or BW ≤ 1700 g) and full term babies of the same age and no ROP (n=3), were screened. RNA was isolated from 0.5-1 ml of blood using RNeasy mini kit from Qiagen and the purity and integrity of RNA was checked with Bioanalyzer 2100 (Agilent). Global gene expression profiling was performed by using Illumina bead Chip array having ~47,000 ...
The increased use of microarray expression profiling to study both the molecular biology of cancer and the cellular physiology of difficult-to-isolate cell types has led to a growing need for methods that allow the use of limiting quantities of RNA. This limitation has prompted the development of amplification methods that produce the quantities of RNA required for microarray analysis. Efforts have become increasingly focused upon developing a protocol that minimizes amplification bias, provides versatility, and reduces technical complexity. We evaluated the new protocol Transplex™ Whole Transcriptome Amplification (WTA) produced by Rubicon Genomics. The kit was tested on Human Reference RNA (Stratagene) and on RNA extracted from a renal tumor cell line. Reproducibility, sensitivity and reliability in calling differentially expressed genes were evaluated by both Real-Time PCR and GeneChip® technology (Affymetrix). We tested reproducibility by comparing the expression profiles provided by U133 ...
Association rules mining methods have been recently applied to gene expression data analysis to reveal relationships between genes and different conditions and features. However, not much effort has focused on detecting the relation between gene expression maps and related gene functions. Here we describe such an approach to mine association rules among gene functions in clusters of similar gene expression maps on mouse brain. The experimental results show that the detected association rules make sense biologically.
Seker, H. (2004) A Multi-Fuzzy Filtering Approach to Reliable Gene Expression Profile Analysis. Proceedings of the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, October 2004, pp. 37-40 ...
APC (Adenomatous polyposis coli) plays an important role in the pathogenesis of both familial and sporadic colorectal cancer. Patients carrying germline APC mutations develop multiple colonic adenomas at younger age and higher frequency than non-carrier cases which indicates that silencing of one APC allele may be sufficient to initiate the transformation process. To elucidate the biological dysregulation underlying adenoma formation we examined global gene expression profiles of adenomas and corresponding normal mucosa from an FAP patient. Differential expression of the most significant gene identified in this study was further validated by mRNA in situ hybridization, reverse transcriptase PCR and Northern blotting in different sets of adenomas, tumours and cancer cell lines. Eighty four genes were differentially expressed between all adenomas and corresponding normal mucosa, while only seven genes showed differential expression within the adenomas. The first group included pregnancy specific β-1
Background: Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. Methods: Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. Results: Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the ...
Purpose This article provides a review of the transcriptomic expression profiling studies that have been performed on meningiomas so far. We discuss some future prospects and challenges ahead in the field of gene expression profiling. Methods We performed a systematic search in the PubMed and EMBASE databases in May 2010 using the following search terms alone or in combination: "meningioma", "microarray analysis", "oligonucleotide array sequence analysis", or "gene expression profiling". Only original research articles in English that had used RNA hybridized to high-resolution microarray chips to generate gene expression profiles were included. Results We identified 13 articles matching the inclusion criteria. All studies had been performed during the last decade. Conclusions The main results of the studies can be grouped in three categories: (1) several groups have identified meningioma-specific genes and genes associated with the three WHO grades, and the main histological subtypes of grade I ...
Background Parkinsons disease (PD) is affecting 5 million people worldwide, but the response mechanisms of the striatum are still unclear. Therefore, identification of gene expression alterations in...
Large mammals are capable of thermoregulation shortly after birth due to the presence of brown adipose tissue (BAT). The majority of BAT disappears after birth and is replaced by white adipose tissue (WAT). We analyzed the postnatal transformation of adipose in sheep with a time course study of the perirenal adipose depot. We observed changes in tissue morphology, gene expression and metabolism within the first two weeks of postnatal life consistent with the expected transition from BAT to WAT. The transformation was characterized by massively decreased mitochondrial abundance and down-regulation of gene expression related to mitochondrial function and oxidative phosphorylation. Global gene expression profiling demonstrated that the time points grouped into three phases: a brown adipose phase, a transition phase and a white adipose phase. Between the brown adipose and the transition phase 170 genes were differentially expressed, and 717 genes were differentially expressed between the transition and the
BACKGROUND: 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. FINDINGS: 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. CONCLUSIONS: 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 ...
The identification of a prognostic gene expression signature in breast cancer that is valid across multiple independent data sets and different microarray platforms is a challenging problem [1]. Recently, there have been reports of molecular prognostic and predictive signatures that were also valid in external independent cohorts [2-7]. One of these studies derived the prognostic signature from genes correlating with histological grade [4], while in [5] it was derived directly from correlations with clinical outcome data and was validated in estrogen receptor positive lymph node negative (ER+LN-) breast cancer. Another study validated a predictive score, based on 21 genes, for ER+LN-tamoxifen treated breast cancer [2]. These results are encouraging, yet, as explained recently in [8, 9], much larger cohort sizes may be needed before a consensus prognostic signature emerges. While the intrinsic subtype classification does appear to constitute a set of consensus signatures [7], it is also clear ...
PubMed Central Canada (PMC Canada) provides free access to a stable and permanent online digital archive of full-text, peer-reviewed health and life sciences research publications. It builds on PubMed Central (PMC), the U.S. National Institutes of Health (NIH) free digital archive of biomedical and life sciences journal literature and is a member of the broader PMC International (PMCI) network of e-repositories.
EpiRegNet aims to build a transcriptional regulatory network composing of histone modification and transcription factor binding in promoters and interactions between factors in these two fields ...
1. Chockalingm A, Campbell NR, Fodor JG. Worldwide epidemic of hypertension. Can J Cardio. 2006;22:553-555 2. Tomson J, Lip GYH. Blood Pressure demographic: nature or nurture…… genes or environment?. BMC Med. 2005;3:3 3. WHO. World Health Report 2002: Reducing Risks, Promoting Healthy life. Geneva: World Health Organization. 2002 4. Heller RA. et al. Discovery and analysis of inflammatory disease related genes using cDNA microarrays. Proc Nat Acad Sci. 1997;94:2150- 2155 5. Lockhart DJ, Dong H, Byrne MC, Follettie MT, Gallo MV, Chee MS, Mittmann M, Wang C, Kobayashi M, Horton H, Brown EL. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat Biotechnol. 1996;14:1675-80 6. Tzouvelekis A, Patlakas G, Bouros D. Application of Microarray Technology in pulmonary diseases. Respir Res. 2004;5:26 7. King HC, Sinha AA. Gene expression profile analysis by DNA microarrays: promise and pitfalls. JAMA. 2001;286:2280-2288 8. LI JJ. Inflammation in hypertension: primary ...
Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z-score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z-score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when ...
This project is an investigation of whether analysing subsets of time series gene expression data can give additional information about putatively co-regulated genes, compared to only using the whole time series. The original gene expression data set was partitioned into subsets and similarity was computed for both the whole timed series and subsets. Pearson correlation was used as similarity measure between gene expression profiles. The results indicate that analysing co-expression in subsets of gene expression data derives true-positive connections, with respect to co-regulation, that are not detected by only using the whole time series data. Unfortunately, with the actual data set, chosen similarity measure and partitioning of the data, randomly generated connections have the same amount of true-positives as the ones derived by the applied analysis. However, it is worth to continue further analysis of the subsets of gene expression data, which is based on the multi-factorial nature of gene ...
Preface. Acknowledgments.. 1 Introduction.. 1.1 Basic Terminology.. 1.1.1 The Central Dogma of Molecular Biology.. 1.1.2 Genome.. 1.1.3 Proteome.. 1.1.4 DNA (Deoxyribonucleic Acid).. 1.1.5 RNA (Ribonucleic Acid).. 1.1.6 mRNA (messenger RNA).. 1.1.7 Genetic Code.. 1.1.8 Gene.. 1.1.9 Gene Expression and the Gene Expression Level.. 1.1.10 Protein.. 1.2 Overlapping Areas of Research.. 1.2.1 Genomics.. 1.2.2 Proteomics.. 1.2.3 Bioinformatics.. 1.2.4 Transcriptomics and Other -omics.. 1.2.5 Data Mining.. 2 Basic Analysis of Gene Expression Microarray Data.. 2.1 Introduction.. 2.2 Microarray Technology.. 2.2.1 Spotted Microarrays.. 2.2.2 Affymetrix GeneChip® Microarrays.. 2.2.3 Bead-Based Microarrays.. 2.3 Low-Level Preprocessing of Assymetrix Microarrays.. 2.3.1 MAS5.. 2.3.2 RMA.. 2.3.3 GCRMA.. 2.3.4 PLIER.. 2.4 Public Repositories of Microarray Data.. 2.4.1 Microarray Gene Expression Data Society (MGED) Standards.. 2.4.2 Public Databases.. 2.4.2.1 Gene Expression Omnibus (GEO).. 2.4.2.2 ...
Report on emerging technologies for translational bioinformatics: a symposium on gene expression profiling for archival tissues. . Biblioteca virtual para leer y descargar libros, documentos, trabajos y tesis universitarias en PDF. Material universiario, documentación y tareas realizadas por universitarios en nuestra biblioteca. Para descargar gratis y para leer online.
Background & objective: Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used to effectively analyze the problems of large-p and small-n. Therefore, RF can be used to select and rank the genes for the diagnosis and effective treatment of cancer. Methods: The microarray gene expression data of colon, leukemia, and prostate cancers were collected from public databases. Primary preprocessing was done on them using limma package, and then, the RF classification method was implemented on datasets separately in R software. Finally, the selected genes in each of the cancers were evaluated and compared with those of previous experimental studies and their functionalities were assessed in molecular cancer processes. Result: The RF method extracted very small sets of genes while it retained its
Breast cancer is the most common malignancy among women in the United States with the second highest incidence of cancer-related death following lung cancer. The decision-making process regarding adjuvant therapy is a time intensive dialogue between the patient and her oncologist. There are multiple tools that help individualize the treatment options for a patient. Population-based analysis with Adjuvant! Online and genomic profiling with Oncotype DX are two commonly used tools in patients with early stage, node-negative breast cancer. This case report illustrates a situation in which the population-based prognostic and predictive information differed dramatically from that obtained from genomic profiling and affected the patients decision. In light of this case, we discuss the benefits and limitations of these tools.
A limiting factor of cDNA microarray technology is the need for a substantial amount of RNA per labeling reaction. Thus, 20-200 micro-grams total RNA or 0.5-2 micro-grams poly (A) RNA is typically required for monitoring gene expression. In addition, gene expression profiles from large, heterogeneous cell populations provide complex patterns from which biological data for the target cells may be difficult to extract. In this study, we chose to investigate a widely used mRNA amplification protocol that allows gene expression studies to be performed on samples with limited starting material. We present a quantitative study of the variation and noise present in our data set obtained from experiments with either amplified or non-amplified material. Using analysis of variance (ANOVA) and multiple hypothesis testing, we estimated the impact of amplification on the preservation of gene expression ratios. Both methods showed that the gene expression ratios were not completely preserved between amplified and non
A meta-analysis was performed across six public microarray datasets for human small cell lung cancer (SCLC) comprising 365 samples across eight different platforms. Genes were ranked according to effect size and p-value for tumor versus control samples, and false discovery rates were calculated. The top scoring 48 genes that were significant by both methods, along with the 48 highest rated surface antigen genes, were used to populate a gene list for subsequent single cell evaluation. High throughput gene expression analysis was performed for 400 individual cells from one SCLC line (H446) using the Fluidigm microfluidic platform. Supervised machine learning was applied to identify transcriptionally-defined subgroups among these cells. The non-parametric Kolmogorov-Smirnov test was then used to determine those surface markers best able to distinguish each cluster. Individual cells from each group were then FACS-isolated, and clonogenicity was evaluated after 14 days in culture. Using these surface ...
Gene expression profiling classifies individual tumors by their gene expression patterns and may also describe and predict therapeutic resistance and sensitivity patterns. Profiling in several cancers, such as breast cancer, colon cancer, lymphoma, leukemia, and melanoma [3], has already identified molecular subclasses of tumors. Identification of tumor subtypes may be predictive for prognosis or response to drug therapy [6, 7, 28-31].. The potential of routine gene expression profiling to predict clinical outcomes for cancer patients has yet to be determined. The Evaluation of Genomic Applications in Practice and Prevention Working Group stated in 2009 that there was "insufficient evidence to make a recommendation for or against the use of tumor gene expression profiles to improve outcomes in defined populations of women with breast cancer" [32]. Clearly, more work needs to be done to translate promising research findings into clinically relevant results.. Comparison of FFPET sample-derived ...
Background Differential expression analysis on the basis of RNA-Seq count data has become a standard tool in transcriptomics. Several studies have shown that prior normalization of the data is crucial for a reliable detection of transcriptional differences. Until now it has not been clear whether and how the transcriptomic approach can be used for differential expression analysis in metatranscriptomics. Methods We propose a model for differential expression in metatranscriptomics that explicitly accounts for variations in the taxonomic composition of transcripts across different samples. As a main consequence the correct normalization of metatranscriptomic count data under this model requires the taxonomic separation of the data into organism-specific bins. Then the taxon-specific scaling of organism profiles yields a valid normalization and allows us to recombine the scaled profiles into a metatranscriptomic count matrix. This matrix can then be analyzed with statistical tools for transcriptomic count
Cancer is a disease characterized by uncontrolled cell growth and proliferation. For cancer to develop, genes regulating cell growth and differentiation must be altered; these mutations are then maintained through subsequent cell divisions and are thus present in all cancerous cells. Gene expression profiling is a technique used in molecular biology to query the expression of thousands of genes simultaneously. In the context of cancer, gene expression profiling has been used to more accurately classify tumors. The information derived from gene expression profiling often helps in predicting the patients clinical outcome. Oncogenesis is the process by which normal cells acquire the properties of cancer cells leading to the formation of a cancer or tumor (see: tumorigenesis). It is characterized by a molecular reprogramming of a cell to undergo uninhibited cell division, allowing the formation of a malignant mass. The cells forming this mass undergo natural selection: as cells acquire mutations ...
Large amounts of information generated by gene expression profiling will increase implementation of data management tools Gene expression profiling can...
Welcome to the homepage of the GenT er mining tool! GenT er is an application tool for alignment, analysis and mining of gene expression time series. The core algorithm is based on dynamic time warping techniques used in the speech recognition field(1). These techniques allow for non-linear (elastic) alignment of temporal sequences of feature vectors and consequently enable detection of similar shapes with different phases, as demonstrated on the figure below.. ...
DI-fusion, le Dépôt institutionnel numérique de lULB, est loutil de référencementde la production scientifique de lULB.Linterface de recherche DI-fusion permet de consulter les publications des chercheurs de lULB et les thèses qui y ont été défendues.
In the present study, we established a novel TNBC classification system, the FUSCC classification, by integrating the expression profiles of both mRNAs and lncRNAs. TNBC samples can be clearly classified into four subtypes according to our system: IM, LAR, MES, and BLIS. Each subtype has its own unique transcriptome profile. Furthermore, we filtrated out several subtype-specific lncRNAs and predicted possible functions of these lncRNAs in TNBC biological processes by analyzing the co-expression network between lncRNAs and mRNAs. To the best of our knowledge, the present study is the first to develop a novel TNBC classification system based on the transcriptome profiles of both mRNAs and lncRNAs in a large TNBC cohort.. Several novel findings were revealed in our in-depth transcriptome analysis. First, considering the expanding roles of lncRNAs in tumorigenesis and disease development, we integrated the expression profiles of both mRNAs and lncRNAs in an attempt to comprehensively understand the ...
OBJECTIVES: An inflammatory process following stroke in human brains and systemic inflammatory responses after stroke in humans have been reported by numerous investigators. The aim of the study was to investigate if genes involved in the cyclooxygenase 2 (COX-2) pathway are upregulated at peripheral level in patients after transient ischaemic attack (TIA) and stroke. DESIGN OF STUDY: Blood samples were obtained from two groups of patients undergoing carotid endarterectomy ...
The rapid accumulation of gene expression data has offered unprecedented opportunities to study human diseases. The National Center for Biotechnology Information Gene Expression Omnibus is currently the largest database that systematically documents the genome-wide molecular basis of diseases. However, thus far, this resource has been far from fully utilized. This paper describes the first study to transform public gene expression repositories into an automated disease diagnosis database. Particularly, we have developed a systematic framework, including a two-stage Bayesian learning approach, to achieve the diagnosis of one or multiple diseases for a query expression profile along a hierarchical disease taxonomy. Our approach, including standardizing cross-platform gene expression data and heterogeneous disease annotations, allows analyzing both sources of information in a unified probabilistic system. A high level of overall diagnostic accuracy was shown by cross validation. It was also ...
TY - JOUR. T1 - Transcription network construction for large-scale microarray datasets using a high-performance computing approach. AU - Zhu, Mengxia Michelle. AU - Wu, Qishi. PY - 2008/3/4. Y1 - 2008/3/4. N2 - Background: The advance in high-throughput genomic technologies including microarrays has demonstrated the potential of generating a tremendous amount of gene expression data for the entire genome. Deciphering transcriptional networks that convey information on intracluster correlations and intercluster connections of genes is a crucial analysis task in the post-sequence era. Most of the existing analysis methods for genome-wide gene expression profiles consist of several steps that often require human involvement based on experiential knowledge that is generally difficult to acquire and formalize. Moreover, large-scale datasets typically incur prohibitively expensive computation overhead and thus result in a long experiment-analysis research cycle. Results: We propose a parallel ...
The HLX gene encoding a diverged homeobox transcription factor has been found to be up-regulated by vascular endothelial growth factor-A (VEGF-A) in endothelial cells. endothelial growth factor-A (VEGF-A) is the major trigger of vasculogenesis and angiogenesis during embryogenesis and blood-vessel formation in the adult.1,2 It has also been implicated in pathologic angiogenesis in diseases such as cancer, chronic inflammatory disorders, and retinopathy.3 Whereas several peptide products are generated from the VEGF-A gene by differential splicing, the available data suggest that isoform VEGF-A165 is the RAB11FIP4 predominant form responsible for the major angiogenic effects.4 The gene repertoire induced by VEGF-A mainly via VEGF receptor 2 has been investigated by several groups5-7; however, the transcription factors up-regulated by VEGF-A and how they mediate its specific and unique biologic functions remain largely uncharacterized. We have recently identified a group of genes or at least ...
A distinct feature of human being prostate tumor (PCa) is the advancement of osteoblastic (bone-forming) bone fragments metastases. on growth cells and stromal cells, that is certainly, endothelial osteoblasts and cells. In comparison, CXCL1 features as a paracrine aspect through the CXCR2 receptor portrayed in endothelial osteoblasts and cells. Hence, our research reveals a complicated PCa bone fragments metastasis secretome with paracrine and autocrine signaling features that mediate cross-talk among multiple cell types within the growth microenvironment. A specific feature of individual prostate tumor (PCa)1 with fatal potential is certainly the buy 77-95-2 advancement of metastases in bone fragments with a bone-forming phenotype (1). This home of PCa bone fragments metastasis suggests that PCa cells possess exclusive connections with cells in the bone fragments microenvironment. Cells that are known to become present in the bone tissue microenvironment consist of osteoblasts, osteoclasts, ...
We did a genome-wide transcription profiling study of 60 children, with first relapse of ALL enrolled in the relapse trial ALL-REZ BFM 2002 of the BFM study group. Genetic and immunologic subclasses described by gene expression profiling studies of initial ALL (10, 12) were correctly predicted from microarray data in relapse patients, thus proving consistency of microarray-based leukemia subtype classification across different stages of disease. To identify molecular determinants of the major prognostic factors at ALL relapse, we compared prognostic groups of B-cell precursor ALL relapse classified according to each of these factors. No significant gene expression patterns were found to correlate with the prognostic factors site of relapse and MRD. About the most evident prognostic factor time of relapse, we identified significant differences in gene expression between patients with very early and late relapse. We obtained a list of 83 differentially expressed genes mostly up-regulated in very ...
Blood is an ideal tissue for the identification of novel genomic biomarkers for toxicity or efficacy. However, using blood for transcriptomic profiling presents significant technical challenges due to the transcriptomic changes induced by ex vivo handling and the interference of highly abundant globin mRNA. Most whole blood RNA stabilization and isolation methods also require significant volumes of blood, limiting their effective use in small animal species, such as rodents. To overcome these challenges, a QIAzol-based RNA stabilization and isolation method (QSI) was developed to isolate sufficient amounts of high quality total RNA from 25 to 500 μL of rat whole blood. The method was compared to the standard PAXgene Blood RNA System using blood collected from rats exposed to saline or lipopolysaccharide (LPS). The QSI method yielded an average of 54 ng total RNA per μL of rat whole blood with an average RNA Integrity Number (RIN) of 9, a performance comparable with the standard PAXgene method. Total
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 ...
The developmental transition to motherhood requires gene expression changes that alter the brain to prepare and drive the female to perform maternal behaviors. Furthermore, it is expected that the many physiological changes accompanying pregnancy and postpartum stages will impact brain gene expression patterns. To understand how extensive these gene expression changes are, we examined the global transcriptional response broadly, by examining four different brain regions: hypothalamus, hippocampus, neocortex, and cerebellum. Further, to understand the time course of these changes we performed RNA-sequencing analyses on mRNA derived from virgin females, two pregnancy time points and three postpartum time points. We find that each brain region and time point shows a unique molecular signature, with only 49 genes differentially expressed in all four regions, across the time points. Additionally, several genes previously implicated in underlying postpartum depression change expression. This study serves as a
As shown in Figure 2A and Table 1, GO enriched functions for the 74 overlapped up-regulated genes and 79 overlapped down-regulated genes were involved in a number of biological processes (BP), including cell cycle phase, M phase, mitotic cell cycle, cell cycle process, and cell division for the up-regulated genes, and muscle system process, purine nucleotide metabolic process, negative regulation of cell proliferation, regulation of RNA metabolic process, and transcription for the down-regulated genes. With regard to molecular function (MF), the top six MFs of the up-regulated DEGs were microtubule motor activity, ATP binding, adenyl ribonucleotide binding, purine nucleoside binding, nucleoside binding, and ribonucleotide binding, and the top four MFs of the down-regulated DEGs were transcription factor activity, DNA binding, transcription regulator activity, and cAMP binding (Figure 2B and Table 1). For the cellular component (CC) terms, majority of the up-regulated DEGs were enriched for ...
Release Date: 06/05/2019 Boston University (BU) researchers, in collaboration with researchers at the National Toxicology Program (NTP) and the Broad Institute, have developed and evaluated a new approach to assess whether exposure to a chemical increases a persons long-term cancer risk. The fast, cost-effective method uses gene expression profiling, which measures the activity of a thousand or more genes to capture what is happening in a cell. Based on gene expression profiling data, the researchers were able to infer specific biological changes at the cellular level and predict potential carcinogenicity of chemicals, or the ability of chemicals to cause cancer.. ...
DataMed is a prototype biomedical data search engine. Its goal is to discover data sets across data repositories or data aggregators. In the future it will allow searching outside these boundaries. DataMed supports the NIH-endorsed FAIR principles of Findability, Accessibility, Interoperability and Reusability of datasets with current functionality assisting in finding datasets and providing access information about them.
Differential gene expression patterns in developing sexually dimorphic rat brain regions exposed to antiandrogenic, estrogenic, or complex endocrine disruptor mixtures: Glutamatergic synapses as ...
Background: Besides having an impact on human health, the porcine muscle fatty acid profile determines meat quality and taste. The RNA-Seq technologies allowed us to explore the pig muscle transcriptome with an unprecedented detail. The aim of this study was to identify differentially-expressed genes between two groups of 6 sows belonging to an Iberian 6 Landrace backcross with extreme phenotypes according to FA profile. Results: We sequenced the muscle transcriptome acquiring 787.5 M of 75 bp paired-end reads. About 85.1% of reads were mapped to the reference genome. Of the total reads, 79.1% were located in exons, 6.0% in introns and 14.9% in intergenic regions, indicating expressed regions not annotated in the reference genome. We identified a 34.5% of the intergenic regions as interspersed repetitive regions. We predicted a total of 2,372 putative proteins. Pathway analysis with 131 differentially-expressed genes revealed that the most statistically-significant metabolic pathways were related with
Gene-expression profiling is the most popular method since it provides a total overview of the expression levels in your sample. All protein-coding (poly-A containing) transcripts are consistently and accurately represented. It provides an affordable approach to examine differential gene-expression analysis between groups of samples, such as various treatments, time-points, or disease versus control samples.. Our ISO-accredited service includes all novel features: Unique Molecular Identifiers (UMIs), identification of antisense transcripts, and can handle a broad range of input RNA, starting from 5 ng. It is applicable for FFPE-material or other (partly) degraded and challenging samples (see below).. For whole blood analysis, we offer globin reduction that removes the globin transcripts originating from erythrocytes, so you reduce the sequencing capacity that is required per sample with 30 to 40%. The removal of ribosomal RNA is not necessary, since these transcripts do not contain a poly-A ...
Detailed analysis of the immunological pathways leading to robust vaccine responses has become possible with the application of systems biology, including transcriptomic analysis. Venous blood is usually obtained for such studies but others have obtained capillary blood (e.g. finger-prick). Capillary samples are practically advantageous, especially in children.The aim of this study was to compare gene expression profiles in venous and capillary blood before, 12h and 24h after vaccination with 23-valent pneumococcal polysaccharide or trivalent inactivated seasonal influenza vaccines.Gene expression at baseline was markedly different between venous and capillary samples, with 4940 genes differentially expressed, and followed a different pattern of changes after vaccination. At baseline, multiple pathways were upregulated in venous compared to capillary blood, including transforming growth factor-beta receptor signalling and toll-like receptor cascades. After vaccination with the influenza vaccine, there
h1,D-NetWeaver Overview,/h1, ,p,D-NetWeaver is an application to enable the manipulation and analysis of time course data matrices, such as gene expression data as generated by microarray or RNA-seq experiments. It is specifically geared toward reconstructing gene regulatory networks from time course gene expression data using differential equation network models. ,/p, ,p,It provides the ability to apply six primary steps to gene expression data: ,/p, ,ol, ,li,Significant gene detection,/li, ,li,Clustering,/li, ,li,Smoothing,/li, ,li,Functional enrichment analysis,/li, ,li,Regulation identification (otherwise known as variable selection of differential equation network models) ,/li, ,li,Parameter estimation refinement,/li, ,/ol, ,p,The software provides many data manipulation and data visualization features to assist users in exploring their data and interpreting the results of these six primary steps.,/p, ,p,The end goal is the creation of a dynamic network model. Currently, the only supported ...
Technologies used for high-throughput gene expression analysis.. A. Breast cancer tumors are sampled at the treatment location and shipped to the central laboratory doing the assay, where pathologic review is done to assess cancer cell contents, followed by RNA preparation and integrity evaluation. Suitable samples are used to quantify RNA levels, thus assessing gene expression. When a gene is expressed, the transcription complex copies its DNA sequence into complementary RNA transcripts that are translated into proteins. High-throughput gene expression analysis aims to quantify messenger RNA (mRNA) populations in a given tissue. B. DNA microarray is the molecular biology technique enabling gene expression analysis in MammaPrint. RNA is labeled with fluorescent dye and hybridized against thousands of different nucleotide sequences corresponding to different genes and arrayed on a solid surface (that is, a modified microscope glass slide). On hybridization, fluorescence emitted by single ...
In the present study, we examined the gene expression profile of 25 IGHV4-34 patients including subset #4, #16 and non-subset 4/16 cases. Initially, we compared the gene expression profiles between subset #4 and non-subset 4/16 patients and between subset #16 patients and non-subset 4/16 patients, and detected only few significant differences. This is probably because, overall, non-subset 4/16 IGHV4-34 cases exhibited a more heterogeneous gene expression profile, likely reflecting the structural heterogeneity of their BCR, which would be expected to be responsive to a far wider range of antigens than that recognized by stereotyped subsets. Interestingly, however, we detected distinct differences in gene expression patterns when comparing subset #4 and #16 cases, both of which can be reliably defined at the molecular level based on subset-specific VH CDR3 and subset-biased features of somatic hypermutation.8 This finding is supported by the recent observation that stereotyped subset cases have ...
Gene expression data provide invaluable insights into disease mechanisms. In Huntingtons disease (HD), a neurodegenerative disease caused by a tri-nucleotide repeat expansion in the huntingtin gene, extensive transcriptional dysregulation has been reported. Conventional dysregulation analysis has shown that e.g. in the caudate nucleus of the post mortem HD brain the gene expression level of about a third of all genes was altered. Owing to this large number of dysregulated genes, the underlying relevance of expression changes is often lost in huge gene lists that are difficult to comprehend. To alleviate this problem, we employed weighted correlation network analysis to archival gene expression datasets of HD post mortem brain regions. We were able to uncover previously unidentified transcription dysregulation in the HD cerebellum that contained a gene expression signature in common with the caudate nucleus and the BA4 region of the frontal cortex. Furthermore, we found that yet unassociated pathways, e
Neurohormonal activation in heart failure is well established and involves activation of the renin-angiotensin-aldosterone network and the sympathetic nervous system. Associated with this process is the enhanced production of cytokines and other inflammatory factors that have been directly implicated in the pathophysiological progression of heart failure (2, 6, 11, 15). These factors have both direct and indirect effects on cardiac remodeling and can also affect gene expression in other tissues (19). Due to the systemic nature of the disease, we tested the hypothesis that noncardiac tissue can exhibit specific gene expression signatures that associate with cardiovascular events.. By performing blood gene expression profiling analysis, we analyzed ,27,000 transcripts in blood and demonstrated for the first time that blood gene expression varies as a function of patient outcomes (see online data supplement).1 A total of 197 mortality genes were discovered. Intriguingly, a large number ...
Purpose: ATG41 is involved both in autophagy and zinc-deficient growth. The goal of this study is to compare transcriptomic profiles of wild-type and atg41Δ strains to discover autophagy-independent molecular phenotypes for the mutant. The atg1Δ mutant is a control for autophagy activity. Methods: Wild-type and mutant yeast were grown to mid-log phase in replete medium and shifted to zinc-deficient medium for 8 hours, after which, cells were harvested for RNA sequencing to detect differential gene expression. Results: Gene expression data for virtually every gene (~6,000) was obtained with ~12,000,000 reads per sample. Differential gene expression analysis showed that several hundred genes were differentially experessed in the atg41Δ mutant (greater than 2-fold) at an FDR of 0.5. Conclusions: Most strikingly, we found that the atg41Δ mutant transcriptome shows signs that sulfur metabolism is distrupted during zinc-deficinet growth. Expression of Met4 gene targets is increased.
Sigma-Aldrich offers abstracts and full-text articles by [Youichi Higuchi, Motohiro Kojima, Genichiro Ishii, Kazuhiko Aoyagi, Hiroki Sasaki, Atsushi Ochiai].
... Future Conference: GENE EXPRESSION 2018; GENE EXPRESSION 2019; GENE EXPRESSION 2020;
BACKGROUND: Tumorigenesis is characterised by changes in transcriptional control. Extensive transcript expression data have been acquired over the last decade and used to classify prostate cancers. Prostate cancer is, however, a heterogeneous multifocal cancer and this poses challenges in identifying robust transcript biomarkers. METHODS: In this study, we have undertaken a meta-analysis of publicly available transcriptomic data spanning datasets and technologies from the last decade and encompassing laser capture microdissected and macrodissected sample sets. RESULTS: We identified a 33 gene signature that can discriminate between benign tissue controls and localised prostate cancers irrespective of detection platform or dissection status. These genes were significantly overexpressed in localised prostate cancer versus benign tissue in at least three datasets within the Oncomine Compendium of Expression Array Data. In addition, they were also overexpressed in a recent exon-array dataset as well a
The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental factors including treatments, mutations and pathogen infections. Similarly, drugs may be discovered by the relationship between the transcript profiles effectuated or impacted by a candidate drug and by the target disease. The integration of such data enables systems biology to predict the interplay between experimental factors affecting a biological system. Unfortunately, direct comparisons of gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment-specific biases. Here we suggest a novel yet conceptually simple approach for deriving Functional Association(s) by Response Overlap (FARO) between microarray gene expression
Search "+CPT1A -METABRIC -eQTL +Meta-analysis of the global gene expression profile of triple-negative breast cancer identifies genes for the prognostication and treatment of aggressive breast cancer -June 21 ...
With advent of high throughput transcriptomic profiling, biomarker identification has been taken to the genomic level. Several studies have been published so far where transcriptomic profiling and consequently biomarker identification in form of single genes, or a signature composed of several genes, has been done on cancer samples, and such data are available in public domain. Gene signatures prognostic for overall, metastasis free or recurrence free survival have been developed using transcriptomic profiling. In several such studies gene signatures have been developed specific for prognostication in particular subtype of a cancer, for instance, a subgroup of population treated with a specific drug. 70 Gene signature Mammaprint® [1], PAM50 [2], OncotypeDx® [3] are some examples of gene signatures of prognostic importance in breast cancer. Similar signatures have also been developed in other cancers such as Colon cancer [4, 5], Liver cancer [6], Lung cancer [7, 8] and Pancreatic Cancer [9] ...
BioMed Research International is a peer-reviewed, Open Access journal that publishes original research articles, review articles, and clinical studies covering a wide range of subjects in life sciences and medicine. The journal is divided into 55 subject areas.
The diagnosis and treatment of prostate cancer are fields with long histories. Various efforts have led to the progressive understanding of the disease. However, the present criteria of diagnosis and prognosis, as well as the approaches of treatment and surgery, are not sufficiently reliable. Previous gene expression profiling studies on prostate tumors and normal tissues demonstrated the feasibility in characterizing the molecular alterations at the overall mRNA transcript level. However, these transcriptome analyses were based on the old central dogma of "one gene, one mRNA", which may underestimate the complexity of tumorigenesis [23].. Previously, we carried out a study of prostate cancer by exon-junction microarray-based assay and demonstrated the power of this integrated technology in detecting both transcriptional and splicing regulation [25, 29]. In this paper, we present systematic analyses with the focus on using splice isoform profiling for prostate cancer classification. ...
The constant maintenance of both DC and Mϕ cell pools in the lung is essential for effective immune surveillance in pulmonary tissue. Recent reports highlight the role of PBMo that emigrate into the lung and differentiate into both lung DC and Mϕ, thereby serving as a constant supply for the renewal of the lung DC and Mϕ pool [6]. While many studies have investigated monocyte recruitment under inflammatory conditions, little is known about the pathways mediating monocyte trafficking and differentiation in lung tissue under non-inflammatory conditions [27, 31, 32]. Since PBMo are believed to be precursors for lung Mϕ and DC, a global gene expression profiling approach was chosen to reveal crucial differences between these cell types, to better understand their relation to one another, and to identify gene clusters relevant for the migration and differentiation process that takes place under steady-state conditions. Previous microarray studies investigating the relation, differentiation and/or ...
Fibroblasts are ubiquitous mesenchymal cells with many vital functions during development, tissue repair, and disease. Fibroblasts from different anatomic sites have distinct and characteristic gene expression patterns, but the principles that govern their molecular specialization are poorly understood. Spatial organization of cellular differentiation may be achieved by unique specification of each cell type; alternatively, organization may arise by cells interpreting their position along a coordinate system. Here we test these models by analyzing the genome-wide gene expression profiles of primary fibroblast populations from 43 unique anatomical sites spanning the human body. Large-scale differences in the gene expression programs were related to three anatomic divisions: anterior-posterior (rostral-caudal), proximal-distal, and dermal versus nondermal. A set of 337 genes that varied according to these positional divisions was able to group all 47 samples by their anatomic sites of origin. Genes
Behaviourally driven gene expression reveals song nuclei in hummingbird brain.s profile, publications, research topics, and co-authors
Unraveling the relationship between molecular signatures in the brain and their functional, architectonic, and anatomic correlates is an important neuroscientific goal. It is still not well understood whether the diversity demonstrated by histological studies in the human brain is reflected in the spatial patterning of whole brain transcriptional profiles. Using genome-wide maps of transcriptional distribution of the human brain by the Allen Brain Institute, we test the hypothesis that gene expression profiles are specific to anatomically described brain regions. In this work, we demonstrate that this is indeed the case by showing that gene similarity clusters appear to respect conventional basal-cortical and caudal-rostral gradients. To fully investigate the causes of this observed spatial clustering, we test a connectionist hypothesis that states that the spatial patterning of gene expression in the brain is simply reflective of the fiber tract connectivity between brain regions. We find that ...
Wheat spike development is a coordinated process of cell proliferation and differentiation with distinctive phases and architecture changes. However, the dynamic alteration of gene expression in this process remains enigmatic. Here, we characterized and dissected bread wheat spike into six developmental stages, and used genome-wide gene expression profiling, to investigate the underlying regulatory mechanisms. High gene expression correlations between any two given stages indicated that wheat early spike development is controlled by a small subset of genes. Throughout, auxin signaling increased, while cytokinin signaling decreased. Besides, many genes associated with stress responses highly expressed during the double ridge stage. Among the differentially expressed genes (DEGs), were identified 375 transcription factor (TF) genes, of which some homologs in rice or Arabidopsis are proposed to function in meristem maintenance, flowering time, meristem initiation or transition, floral organ ...
Gene set enrichment analysis (GSEA) is a popular tool to identify underlying biological processes in clinical samples using their gene expression phenotypes. GSEA measures the enrichment of annotated gene sets that represent biological processes for differentially expressed genes (DEGs) in clinical samples. GSEA may be suboptimal for functional gene sets; however, because DEGs from the expression dataset may not be functional genes per se but dysregulated genes perturbed by bona fide functional genes. To overcome this shortcoming, we developed network-based GSEA (NGSEA), which measures the enrichment score of functional gene sets using the expression difference of not only individual genes but also their neighbors in the functional network. We found that NGSEA outperformed GSEA in identifying pathway gene sets for matched gene expression phenotypes. We also observed that NGSEA substantially improved the ability to retrieve known anti-cancer drugs from patient-derived gene expression data using ...
5-Fluorouracil (5-FU) is the most common chemotherapeutic agent used in the treatment of colorectal cancer, yet objective response rates are low. Recently, camptothecin (CPT) has emerged as an effective alternative therapy. Decisive means to determine treatment, based on the likelihood of response to each of these agents, could greatly enhance the management of this disease. Here, the ability of cDNA microarray-generated basal gene expression profiles to predict apoptotic response to 5-FU and CPT was determined in a panel of 30 colon carcinoma cell lines. Genes whose basal level of expression correlated significantly with 5-FU- and CPT-induced apoptosis were selected, and their predictive power was assessed using a "leave one out" jackknife cross-validation strategy. Selection of the 50 genes best correlated with 5-FU-induced apoptosis, but not 50 randomly selected genes, significantly predicted response to this agent. Importantly, this gene expression profiling approach predicted response more ...
Previous studies indicate that autism spectrum disorders (ASDs) can be conceptualized as the result of multiple rare and common variants that act in combination to shape different aspects of cognition and behavior.
Currently one of the largest online repositories for human and mouse stem cell gene expression data, StemBase was first designed as a simple web-interface to DNA microarray data generated by the Canadian Stem Cell Network to facilitate the discovery of gene functions relevant to stem cell control and differentiation. Since its creation, StemBase has grown in both size and scope into a system with analysis tools that examine either the whole database at once, or slices of data, based on tissue type, cell type or gene of interest. As of September 1, 2008, StemBase contains gene expression data (microarray and Serial Analysis of Gene Expression) from 210 stem cell samples in 60 different experiments. StemBase can be used to study gene expression in human and murine stem cells and is available at http://www.stembase.ca .
Data analysis of microarrays has become an area of intense research.[11] Simply stating that a group of genes were regulated by at least twofold, once a common practice, lacks a solid statistical footing. With five or fewer replicates in each group, typical for microarrays, a single outlier observation can create an apparent difference greater than two-fold. In addition, arbitrarily setting the bar at two-fold is not biologically sound, as it eliminates from consideration many genes with obvious biological significance. Rather than identify differentially expressed genes using a fold change cutoff, one can use a variety of statistical tests or omnibus tests such as ANOVA, all of which consider both fold change and variability to create a p-value, an estimate of how often we would observe the data by chance alone. Applying p-values to microarrays is complicated by the large number of multiple comparisons (genes) involved. For example, a p-value of 0.05 is typically thought to indicate ...
The identification of early and stage-specific biomarkers for Alzheimers disease (AD) is critical, as the development of disease-modification therapies may depend on the discovery and validation of such markers. The identification of early reliable biomarkers depends on the development of new diagnostic algorithms to computationally exploit the information in large biological datasets. To identify potential biomarkers from mRNA expression profile data, we used the Logic Mining method for the unbiased analysis of a large microarray expression dataset from the anti-NGF AD11 transgenic mouse model. The gene expression profile of AD11 brain regions was investigated at different neurodegeneration stages by whole genome microarrays. A new implementation of the Logic Mining method was applied both to early (1-3 months) and late stage (6-15 months) expression data, coupled to standard statistical methods. A small number of fingerprinting formulas was isolated, encompassing mRNAs whose expression ...
Transcriptional programs that regulate development are exquisitely controlled in space and time. Elucidating these programs that underlie development is essential to understanding the acquisition of cell and tissue identity. We present microarray expression profiles of a high resolution set of developmental time points within a single Arabidopsis root, and a comprehensive map of nearly all root cell-types. These cell-type specific transcriptional signatures often predict novel cellular functions. A computational pipeline identified dominant expression patterns that demonstrate transcriptional connections between disparate cell types. Dominant expression patterns along the roots longitudinal axis do not strictly correlate with previously defined developmental zones, and in many cases, expression fluctuation along this axis was observed. Both robust co-regulation of gene expression and potential phasing of gene expression were identified between individual roots. Methods that combine these two sets of
Transcriptome analysis of RNAs extracted from livers of wild type or Smurf1 knock out (KO) or Smurf2 KO mice at age of 11 month old. We prepared RNA from the following groups: livers of Wild type (WT) or Smurf1 KO or Smurf2 KO mouse from mixed Black Swiss/129SvEv background at age of 11 month old. The gene expression profiles were compared, and selected genes that showed either increased or decreased expression by a cut-off of 1.5 folds, p| 0.05. The results showed that 1211 genes in the Smurf1-/- livers were differentially expressed over their WT controls, whereas only 302 genes were differentially expressed in the Smurf2-/- livers, and 114 genes were commonly differentially expressed. Many genes that are involved in lipid metabolism were upregulated in Smurf1-/- livers. These results also indicate that Smurf1 plays a more prominent role in the liver than Smurf2.
It is well know that in contrast to moderate physical activity, an acute bout of prolonged, exhaustive exercise such as marathon or half-marathon running can cause adverse effects on immunity as reflected by transient immunosuppression following the event. We used microarray technology as well as other approaches to study the response of selected and non-selected immune-related genes and proteins following an exercise program. The capacity of whole blood cultures to produce cytokines in response to endotoxin (LPS) was studied (Paper I). Further, the early steps of the immune reaction to pathogen contact were evaluated in details using whole blood culture and gene expression profiling approach in athletes before, 30 min after, 3 h after and 24 h after a half-marathon run (Paper II). Gender and menstrual phase dependent differences in cytokine and gene expression profiles of 12 male subjects (M) and 9 women with regular menstrual cycles was also studied in response to an aerobic exercise at 93% of ...
Time-series gene expression data analysis plays an important role in bioinformatics. In this paper, we propose a biclustering method to detect local expres
Tumour hypoxia is a driver of breast cancer progression associated with worse prognosis and more aggressive disease. The cellular response to hypoxia is mediated by the hypoxia-inducible transcription factors HIF-1 and HIF-2, whose transcriptional activity is canonically regulated through their oxygen-labile HIF-α subunits. These are constitutively degraded in the presence of oxygen; however, HIF-1α can be stabilised, even at high oxygen concentrations, through the activation of HER receptor signalling. Despite this, there is still limited understanding on how HER receptor signalling interacts with HIF activity to contribute to breast cancer progression in the context of tumour hypoxia. 2D and 3D cell line models were used alongside microarray gene expression analysis and meta-analysis of publicly available gene expression datasets to assess the impact of HER2 overexpression on HIF-1α/HIF-2α regulation and to compare the global transcriptomic response to acute and chronic hypoxia in an isogenic cell
MAPPFinder is a tool that creates a global gene-expression profile across all areas of biology by integrating the annotations of the Gene Ontology (GO) Project with the free software package GenMAPP http://www.GenMAPP.org . The results are displayed in a searchable browser, allowing the user to rapidly identify GO terms with over-represented numbers of gene-expression changes. Clicking on GO terms generates GenMAPP graphical files where gene relationships can be explored, annotated, and files can be freely exchanged.
Prostate cancer (PCa) is a malignancy cause of cancer deaths and frequently diagnosed in male. This study aimed to identify tumor suppressor genes, hub genes and their pathways by combined bioinformatics analysis. A combined analysis method was used for two types of microarray datasets (DNA methylation and gene expression profiles) from the Gene Expression Omnibus (GEO). Differentially methylated genes (DMGs) were identified by the R package minfi and differentially expressed genes (DEGs) were screened out via the R package limma. A total of 4451 DMGs and 1509 DEGs, identified with nine overlaps between DMGs, DEGs and tumor suppressor genes, were screened for candidate tumor suppressor genes. All these nine candidate tumor suppressor genes were validated by TCGA (The Cancer Genome Atlas) database and Oncomine database. And then, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed by DAVID (Database for Annotation, Visualization and
International Journal of Plant Genomics is an international, peer-reviewed Open Access journal that publishes novel and advanced original research results of wide interest in all fields of plant genomics, genome technologies and applications of genomic tools in plant breeding. In addition, the journal welcomes field review articles of general interest to plant scientists in plant genomics. Although the journal is dedicated to publish the research results in plant genomics, research articles in genomics of animals or other organisms that are of significance in advancing or potentially applicable to plant genomics are considered for publication in the journal.
Because microarray experiments literally involve the comparison of thousands of data points, the scientific community has grappled with identifying specific guidelines for the conductance, statistical analysis, and interpretation of microarray experiments due to the significant potential for false positives (i.e. , type I error). To this end, the Microarray Gene Expression Data Society, an international organization of molecular biologists, computer scientists, and data analysts, developed standards known as the Minimum Information About a Microarray Experiment (MIAME), which outlines the minimum information that should be reported about a microarray experiment to enable its unambiguous interpretation and reproduction.5 1In addition adhering to the MIAME guidelines, Lucchinetti et al. analyzed their microarray data using a highly sophisticated technique known as gene set enrichment analysis. Gene set enrichment analysis is a computational method that determines whether an a priori defined set of ...
Overall gene expression levels and dynamics related to microbial metabolisms for each Bin-genome.Gene expression levels and changes were calculated (see Supplem
TY - JOUR. T1 - Constructing gene expression-based diagnostic rules for understanding individualized etiology of heart failure. AU - Gao, Zhong. AU - Tomaselli, Gordon. AU - Wei, Chiming. AU - Winslow, Raimond. PY - 2006/3/1. Y1 - 2006/3/1. N2 - Gene expression profiling has the potential to improve individualized etiology diagnosis. A statistical approach based on a multidimensional scaling (MDS) vector model is introduced to construct patient-specific rules for individualized diagnosis based on gene expression profiles. The method has a dual function of discovering new disease classes/ subclasses as well as constructing patient-specific diagnostic rules without prior knowledge of class distinction. The diagnostic rule consists of two components: (1) diagnostic gene expression pattern that suggests a critical etiological condition associated with a disease category, and (2) patient-specific correlations to the diagnostic pattern. The method is applied to construct the diagnostic rule for heart ...
We report here that our initially identified set of predictive genes for detection of lymph node metastasis in patients with head and neck cancer ( 13) is a subset of a larger group of predictive genes. Using a resampling approach, we have identified a large set of 825 genes that can be used for prediction of metastasis. Based on this group of genes, multiple predictive signatures can be made with high predictive accuracy. The phenomenon that different sets of genes can be used for accurate prediction is not exclusive for this study but is becoming apparent in other cancer profiling studies ( 7, 17). Due to minor differences in gene expression, different genes are selected for optimal prediction when the signature is built using different samples, especially when comparing studies that have been done in different institutes ( 3, 12). This instability in gene composition of different predictive signatures is not detrimental as long as the predictive outcome and accuracy remain similar. Different ...
Free Online Library: Integrating miRNA and mRNA Expression Profiling Uncovers miRNAs Underlying Fat Deposition in Sheep.(Research Article, Report) by BioMed Research International; Biotechnology industry High technology industry Adipose tissue Analysis Genetic aspects Adipose tissues Genes Messenger RNA Physiological aspects MicroRNA
Tubular carcinoma (TC) is an uncommon special type of breast cancer characterized by an indolent clinical course. Although described as part of a spectrum of related lesions named low-grade breast neoplasia family due to immunophenotypical and genetic similarities, TCs, low-grade invasive ductal carcinomas of no special type (IDC-NSTs), and classic invasive lobular carcinomas (ILCs) significantly differ in terms of histological features and clinical outcome. The aim of this study was to investigate whether pure TCs constitute an entity distinct from low-grade IDC-NSTs and from classic ILCs. To define the transcriptomic differences between TCs and IDC-NSTs and ILCs whilst minimizing the impact of histological grade and molecular subtype on their profiles, we subjected a series of grade- and molecular subtype-matched TCs and IDC-NSTs and molecular subtype-matched TCs and classic ILCs to genome-wide gene expression profiling using oligonucleotide microarrays. Unsupervised and supervised analysis ...
In this report, we demonstrate that gene expression profile can significantly improve the prediction of OSCC development over clinical and histologic variables in OPL patients. Multiple prediction models were developed and compared using CoxBoost algorithm. We observed a marked improvement in prediction accuracy when a gene expression profile was used. With the gene expression profile only, we developed a 29-trancript prediction model that had prediction error rate around 8%. Using the profile in combination with the previously known risk factors, the model showed a similar prediction error rate as the expression profile alone. Because using the previously known risk factors alone had a clear inferior performance (Fig. 1) compared with models 1 and 2, it is clear that the expression profiles have a predictive value beyond the known risk factors. As an alternative way to assess the misclassification rate of genomic predictors in general, we employed a simpler approach, which used DLDA algorithm ...
Purpose: The role and clinical implication of the transmembrane protein with EGF and two follistatin motifs 2 (TMEFF2) in gastric cancer is poorly understood.. Experimental Design: Gene expression profile analyses were performed and Gene Set Enrichment Analysis (GSEA) was used to explore its gene signatures. AGS and MKN45 cells were transfected with TMEFF2 or control plasmids and analyzed for gene expression patterns, proliferation, and apoptosis. TMEFF2 expression was knocked down with shRNAs, and the effects on genome stability were assessed. Interactions between TMEFF2 and SHP-1 were determined by mass spectrometry and immunoprecipitation assays.. Results: Integrated analysis revealed that TMEFF2 expression was significantly decreased in gastric cancer cases and its expression was negatively correlated with the poor pathologic stage, large tumor size, and poor prognosis. GSEA in The Cancer Genome Atlas (TCGA) and Jilin datasets revealed that cell proliferation, apoptosis, and DNA ...
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High-throughput gene expression profiling can identify sets of genes that are differentially expressed between different phenotypes. Discovering marker genes is particularly important in diagnosis of a cancer phenotype. However, gene sets produced to date are too large to be economically viable diagnostics. We use a hybrid decision tree-discriminant analysis to identify small sets of genes, i.e. single genes and gene pairs, which separate normal samples from different stages of tumor samples. Half the samples are selected for training to form the probability distribution of expression values of each gene. The distributions for the tumor and normal phenotypes are then used to classify the test samples. The algorithm also identifies gene pairs by combining the probability distributions to construct a decision tree which is used to determine the class of test samples. After a series of training and testing sessions, genes and gene pairs that classify all samples correctly are recorded. The method ...
Discussion. sAML develops in approximately 40% of patients with MDS and the clinical discrimination between AML and MDS is based on cytomorphological analysis, since patients with MDS have dysplastic hematopoiesis and a myeloblast count of less than 20%, whereas those with a myeloblast count of 20% or more have AML.6 sAML has clinical and biological heterogeneity linked to chromosome aberrations or molecular changes with the association between them suggesting that those mechanisms are significantly involved in leukemogenesis.1 This case report shows evidence that t(8;13)(q22;q11) could be involved in the pathogenesis and severity of AML. The translocation t(8;13) with breakpoints at (8q22) and (13q11) has neither been reported nor described for possible altered genes. The gene expression profile was performed to determine the specific signature in cells from this patient and to try to clarify a new possible molecular pathway involved in disease evolution. Of the 874 genes differentially ...
Abstract Background MI-319 is a synthetic small molecule designed to target the MDM2-P53 interaction. It is closely related to MDM2 antagonists MI-219 and Nutlin-3 in terms of the expected working mechanisms. The purpose of this study was to evaluate anti-lymphoma activity of MI-319 in WSU-FSCCL, a B-cell follicular lymphoma line. For comparison purpose, MI-319, MI-219 and Nutlin-3 were assessed side by side against FSCCL and three other B-cell hematological tumor cell lines in growth inhibition and gene expression profiling experiments. Results MI-319 was shown to bind to MDM2 protein with an affinity slightly higher than that of MI-219 and Nutlin-3. Nevertheless, cell growth inhibition and gene expression profiling experiments revealed that the three compounds have quite similar potency against the tumor cell lines tested in this study. In vitro, MI-319 exhibited the strongest anti-proliferation activity against FSCCL and four patient cells, which all have wild-type p53. Data obtained from Western
Cancer clinical outcome prediction using gene expression profiles has been proposed by the field of translational bioinformatics for better diagnostics, prognostics, and further therapeutics [1]. Somatic mutations and regulation abnormalities in a tumor cell cause substantial gene expression changes [2]. Expression of oncogenes or tumor suppressor genes promotes the malignant phenotype of cancer cells or inhibits cell division, development, or survival of cancer cell [2]. Thus, DNA microarray technologies have been widely used to predict clinical phenotypes such as stage, grade, metastatic status, recurrence, and patient survival in several cancers [3-5]. In terms of translational bioinformatics, accurate phenotype prediction based on the molecular signature can be used clinically to choose the best of several available therapies for a cancer patient.. However, clinical phenotype prediction based on gene expression profiles can vary between independent data sets [6, 7]. One possible explanation ...
GOurmet: A tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributions - Background: The ever-expanding population of gene expression profiles (EPs) from specified cells and tissues under a variety of experimental conditions is an important but difficult resource for investigators to utilize effectively. Software tools have been recently developed to use the distribution of gene ontology (GO) terms associated with the genes in an EP to identify specific biological functions or processes that are over- or under-represented in that EP relative to other EPs. Additionally, it is possible to use the distribution of GO terms inherent to each EP to relate that EP as a whole to other EPs. Because GO term annotation is organized in a tree-like cascade of variable granularity, this approach allows the user to relate (e.g., by hierarchical clustering) EPs of varying length and from different platforms (e.g., GeneChip, SAGE, EST library). Results: Here