scholarly journals A Mixture Modeling Framework for Differential Analysis of High-Throughput Data

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Cenny Taslim ◽  
Shili Lin
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Mixture Modeling ◽  
Data Type ◽  
Moving Target ◽  
Type I ◽  
Common Theme ◽  
Differential Analysis ◽  
Data Types ◽  
Modeling Framework

The inventions of microarray and next generation sequencing technologies have revolutionized research in genomics; platforms have led to massive amount of data in gene expression, methylation, and protein-DNA interactions. A common theme among a number of biological problems using high-throughput technologies is differential analysis. Despite the common theme, different data types have their own unique features, creating a “moving target” scenario. As such, methods specifically designed for one data type may not lead to satisfactory results when applied to another data type. To meet this challenge so that not only currently existing data types but also data from future problems, platforms, or experiments can be analyzed, we propose a mixture modeling framework that is flexible enough to automatically adapt to any moving target. More specifically, the approach considers several classes of mixture models and essentially provides a model-based procedure whose model is adaptive to the particular data being analyzed. We demonstrate the utility of the methodology by applying it to three types of real data: gene expression, methylation, and ChIP-seq. We also carried out simulations to gauge the performance and showed that the approach can be more efficient than any individual model without inflating type I error.

scholarly journals Towards the integration of computational systems biology and high-throughput data: supporting differential analysis of microarray gene expression data

2008 ◽  
Vol 5 (1) ◽  
pp. 57-71 ◽  
Author(s):  
Nicola Segata ◽  
Enrico Blanzieri ◽  
Corrado Priami
Keyword(s):  
Gene Expression ◽  
Systems Biology ◽  
High Throughput ◽  
System Level ◽  
Expression Data ◽  
Differential Analysis ◽  
Computational Systems Biology ◽  
Microarray Gene Expression ◽  
High Throughput Data ◽  
Computational Systems

Summary The paradigmatic shift occurred in biology that led first to high-throughput experimental techniques and later to computational systems biology must be applied also to the analysis paradigm of the relation between local models and data to obtain an effective prediction tool. In this work we introduce a unifying notational framework for systems biology models and high-throughput data in order to allow new integrations on the systemic scale like the use of in silico predictions to support the mining of gene expression datasets. Using the framework, we propose two applications concerning the use of system level models to support the differential analysis of microarray expression data. We tested the potentialities of the approach with a specific microarray experiment on the phosphate system in Saccharomyces cerevisiae and a computational model of the PHO pathway that supports the systems biology concepts.

scholarly journals Hydra: A mixture modeling framework for subtyping pediatric cancer cohorts using multimodal gene expression signatures

2020 ◽  
Vol 16 (4) ◽  
pp. e1007753
Author(s):  
Jacob Pfeil ◽  
Lauren M. Sanders ◽  
Ioannis Anastopoulos ◽  
A. Geoffrey Lyle ◽  
Alana S. Weinstein ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pediatric Cancer ◽  
Mixture Modeling ◽  
Modeling Framework ◽  
Gene Expression Signatures

scholarly journals Prediction of cancer mutation states using multiple data modalities reveals the utility and consistency of gene expression and DNA methylation

2021 ◽  
Author(s):  
Jake Crawford ◽  
Brock C Christensen ◽  
Maria Chikina ◽  
Casey S Greene
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Rna Sequencing ◽  
Genetic Alterations ◽  
Cellular Function ◽  
Data Type ◽  
Omics Data ◽  
Data Types ◽  
Cancer Mutation ◽  
Combining Data

In studies of cellular function in cancer, researchers are increasingly able to choose from many -omics assays as functional readouts. Choosing the correct readout for a given study can be difficult, and which layer of cellular function is most suitable to capture the relevant signal may be unclear. In this study, we consider prediction of cancer mutation status (presence or absence) from functional -omics data as a representative problem. Since functional signatures of cancer mutation have been identified across many data types, this problem presents an opportunity to quantify and compare the ability of different -omics readouts to capture signals of dysregulation in cancer. The TCGA Pan-Cancer Atlas contains genetic alteration data including somatic mutations and copy number variants (CNVs), as well as several -omics data types. From TCGA, we focus on RNA sequencing, DNA methylation arrays, reverse phase protein arrays (RPPA), microRNA, and somatic mutational signatures as -omics readouts. Across a collection of cancer-associated genetic alterations, RNA sequencing and DNA methylation were the most effective predictors of alteration state. Surprisingly, we found that for most alterations, they were approximately equally effective predictors. The target gene was the primary driver of performance, rather than the data type, and there was little difference between the top data types for the majority of genes. We also found that combining data types into a single multi-omics model often provided little or no improvement in predictive ability over the best individual data type. Based on our results, for the design of studies focused on the functional outcomes of cancer mutations, we recommend focusing on gene expression or DNA methylation as first-line readouts.

Neuroserpin in Bipolar Disorder

2020 ◽  
Vol 20 (7) ◽  
pp. 518-523
Author(s):  
Rugül Köse Çinar
Keyword(s):  
Gene Expression ◽  
Bipolar Disorder ◽  
Polymerase Chain Reaction Method ◽  
Type I ◽  
Healthy Controls ◽  
Neuroprotective Effects ◽  
Expression Levels ◽  
Disease States ◽  
Cord Injury ◽  
System Functioning

Objective: Neuroserpin is a serine protease inhibitor predominantly expressed in the nervous system functioning mainly in neuronal migration and axonal growth. Neuroprotective effects of neuroserpin were shown in animal models of stroke, brain, and spinal cord injury. Postmortem studies confirmed the involvement of neuroserpin in Alzheimer’s disease. Since altered adult neurogenesis was postulated as an aetiological mechanism for bipolar disorder, the possible effect of neuroserpin gene expression in the disorder was evaluated. Methods: Neuroserpin mRNA expression levels were examined in the peripheral blood of bipolar disorder type I manic and euthymic patients and healthy controls using the polymerase chain reaction method. The sample comprised of 60 physically healthy, middle-aged men as participants who had no substance use disorder. Results: The gene expression levels of neuroserpin were found lower in the bipolar disorder patients than the healthy controls (p=0.000). The neuroserpin levels did not differ between mania and euthymia (both 96% down-regulated compared to the controls). Conclusion: Since we detected differences between the patients and the controls, not the disease states, the dysregulation in the neuroserpin gene could be interpreted as a result of the disease itself.

scholarly journals Modulation of Chicken Intestinal Immune Gene Expression by Small Cationic Peptides as Feed Additives during the First Week Posthatch

2013 ◽  
Vol 20 (9) ◽  
pp. 1440-1448 ◽  
Author(s):  
Michael H. Kogut ◽  
Kenneth J. Genovese ◽  
Haiqi He ◽  
Christina L. Swaggerty ◽  
Yiwei Jiang
Keyword(s):  
Gene Expression ◽  
Proinflammatory Cytokines ◽  
Proinflammatory Cytokine ◽  
Feed Additives ◽  
Feed Additive ◽  
Cationic Peptides ◽  
Type I ◽  
Immune Gene ◽  
Content Type ◽  
Functional Efficiency

ABSTRACTWe have been investigating modulation strategies tailored around the selective stimulation of the host's immune system as an alternative to direct targeting of microbial pathogens by antibiotics. One such approach is the use of a group of small cationic peptides (BT) produced by a Gram-positive soil bacterium,Brevibacillus texasporus. These peptides have immune modulatory properties that enhance both leukocyte functional efficiency and leukocyte proinflammatory cytokine and chemokine mRNA transcription activitiesin vitro. In addition, when provided as a feed additive for just 4 days posthatch, BT peptides significantly induce a concentration-dependent protection against cecal and extraintestinal colonization bySalmonella entericaserovar Enteritidis. In the present studies, we assessed the effects of feeding BT peptides on transcriptional changes on proinflammatory cytokines, inflammatory chemokines, and Toll-like receptors (TLR) in the ceca of broiler chickens with and withoutS. Enteritidis infection. After feeding a BT peptide-supplemented diet for the first 4 days posthatch, chickens were then challenged withS. Enteritidis, and intestinal gene expression was measured at 1 or 7 days postinfection (p.i.) (5 or 11 days of age). Intestinal expression of innate immune mRNA transcripts was analyzed by quantitative real-time PCR (qRT-PCR). Analysis of relative mRNA expression showed that a BT peptide-supplemented diet did not directly induce the transcription of proinflammatory cytokine, inflammatory chemokine, type I/II interferon (IFN), or TLR mRNA in chicken cecum. However, feeding the BT peptide-supplemented diet primed cecal tissue for increased (P≤ 0.05) transcription of TLR4, TLR15, and TLR21 upon infection withS. Enteritidis on days 1 and 7 p.i. Likewise, feeding the BT peptides primed the cecal tissue for increased transcription of proinflammatory cytokines (interleukin 1β [IL-1β], IL-6, IL-18, type I and II IFNs) and inflammatory chemokine (CxCLi2) in response toS. Enteritidis infection 1 and 7 days p.i. compared to the chickens fed the basal diet. These small cationic peptides may prove useful as alternatives to antibiotics as local immune modulators in neonatal poultry by providing prophylactic protection againstSalmonellainfections.

scholarly journals STING and cGAS gene expressions were downregulated among HIV-1-infected persons after antiretroviral therapy

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Lorena Leticia Peixoto de Lima ◽  
Allysson Quintino Tenório de Oliveira ◽  
Tuane Carolina Ferreira Moura ◽  
Ednelza da Silva Graça Amoras ◽  
Sandra Souza Lima ◽  
...  
Keyword(s):  
Gene Expression ◽  
Viral Load ◽  
T Cell ◽  
Antiretroviral Therapy ◽  
Cell Count ◽  
Enzyme Linked Immunosorbent Assay ◽  
Type I ◽  
Α Level ◽  
The Impact ◽  
Hiv 1

Abstract Background The HIV-1 epidemic is still considered a global public health problem, but great advances have been made in fighting it by antiretroviral therapy (ART). ART has a considerable impact on viral replication and host immunity. The production of type I interferon (IFN) is key to the innate immune response to viral infections. The STING and cGAS proteins have proven roles in the antiviral cascade. The present study aimed to evaluate the impact of ART on innate immunity, which was represented by STING and cGAS gene expression and plasma IFN-α level. Methods This cohort study evaluated a group of 33 individuals who were initially naïve to therapy and who were treated at a reference center and reassessed 12 months after starting ART. Gene expression levels and viral load were evaluated by real-time PCR, CD4+ and CD8+ T lymphocyte counts by flow cytometry, and IFN-α level by enzyme-linked immunosorbent assay. Results From before to after ART, the CD4+ T cell count and the CD4+/CD8+ ratio significantly increased (p < 0.0001), the CD8+ T cell count slightly decreased, and viral load decreased to undetectable levels in most of the group (84.85%). The expression of STING and cGAS significantly decreased (p = 0.0034 and p = 0.0001, respectively) after the use of ART, but IFN-α did not (p = 0.1558). Among the markers evaluated, the only markers that showed a correlation with each other were STING and CD4+ T at the time of the first collection. Conclusions ART provided immune recovery and viral suppression to the studied group and indirectly downregulated the STING and cGAS genes. In contrast, ART did not influence IFN-α. The expression of STING and cGAS was not correlated with the plasma level of IFN-α, which suggests that there is another pathway regulating this cytokine in addition to the STING–cGAS pathway.

scholarly journals Insights into the Mechanism of Bovine Spermiogenesis Based on Comparative Transcriptomic Studies

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 80
Author(s):  
Xin Li ◽  
Chenying Duan ◽  
Ruyi Li ◽  
Dong Wang
Keyword(s):  
Gene Expression ◽  
Semen Quality ◽  
Regulation Of Gene Expression ◽  
Physiological Mechanism ◽  
Interaction Network ◽  
Seminiferous Tubules ◽  
Differential Analysis ◽  
Epididymal Sperm ◽  
Bioinformatics Analyses ◽  
Acrosome Formation

To reduce subfertility caused by low semen quality and provide theoretical guidance for the eradication of human male infertility, we sequenced the bovine transcriptomes of round, elongated spermatids and epididymal sperms. The differential analysis was carried out with the reference of the mouse transcriptome, and the homology trends of gene expression to the mouse were also analysed. First, to explore the physiological mechanism of spermiogenesis that profoundly affects semen quality, homological trends of differential genes were compared during spermiogenesis in dairy cattle and mice. Next, Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment, protein–protein interaction network (PPI network), and bioinformatics analyses were performed to uncover the regulation network of acrosome formation during the transition from round to elongated spermatids. In addition, processes that regulate gene expression during spermiogenesis from elongated spermatid to epididymal sperm, such as ubiquitination, acetylation, deacetylation, and glycosylation, and the functional ART3 gene may play important roles during spermiogenesis. Therefore, its localisation in the seminiferous tubules and epididymal sperm were investigated using immunofluorescent analysis, and its structure and function were also predicted. Our findings provide a deeper understanding of the process of spermiogenesis, which involves acrosome formation, histone replacement, and the fine regulation of gene expression.

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