Transcriptomics and network analysis highlight potential pathways in the pathogenesis of pterygium

AbstractPterygium is a common ocular surface condition frequently associated with irritative symptoms. The precise identity of its critical triggers as well as the hierarchical relationship between all the elements involved in the pathogenesis of this disease are not yet elucidated. Meta-analysis of gene expression studies represents a novel strategy capable of identifying key pathogenic mediators and therapeutic targets in complex diseases. Samples from nine patients were collected during surgery after photo documentation and clinical characterization of pterygia. Gene expression experiments were performed using Human Clariom D Assay gene chip. Differential gene expression analysis between active and atrophic pterygia was performed using limma package after adjusting variables by age. In addition, a meta-analysis was performed including recent gene expression studies available at the Gene Expression Omnibus public repository. Two databases including samples from adults with pterygium and controls fulfilled our inclusion criteria. Meta-analysis was performed using the Rank Production algorithm of the RankProd package. Gene set analysis was performed using ClueGO and the transcription factor regulatory network prediction was performed using appropriate bioinformatics tools. Finally, miRNA-mRNA regulatory network was reconstructed using up-regulated genes identified in the gene set analysis from the meta-analysis and their interacting miRNAs from the Brazilian cohort expression data. The meta-analysis identified 154 up-regulated and 58 down-regulated genes. A gene set analysis with the top up-regulated genes evidenced an overrepresentation of pathways associated with remodeling of extracellular matrix. Other pathways represented in the network included formation of cornified envelopes and unsaturated fatty acid metabolic processes. The miRNA-mRNA target prediction network, also reconstructed based on the set of up-regulated genes presented in the gene ontology and biological pathways network, showed that 17 target genes were negatively correlated with their interacting miRNAs from the Brazilian cohort expression data. Once again, the main identified cluster involved extracellular matrix remodeling mechanisms, while the second cluster involved formation of cornified envelope, establishment of skin barrier and unsaturated fatty acid metabolic process. Differential expression comparing active pterygium with atrophic pterygium using data generated from the Brazilian cohort identified differentially expressed genes between the two forms of presentation of this condition. Our results reveal differentially expressed genes not only in pterygium, but also in active pterygium when compared to the atrophic ones. New insights in relation to pterygium’s pathophysiology are suggested.

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Statistical Approach of Gene Set Analysis with Quantitative Trait Loci for Crop Gene Expression Studies

Entropy ◽

10.3390/e23080945 ◽

2021 ◽

Vol 23 (8) ◽

pp. 945

Author(s):

Samarendra Das ◽

Shesh N. Rai

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Statistical Approach ◽

Gene Set Analysis ◽

Expression Data ◽

Expression Study ◽

Gene Set ◽

Gene Sets ◽

Expression Studies ◽

Gene Expression Studies

Genome-wide expression study is a powerful genomic technology to quantify expression dynamics of genes in a genome. In gene expression study, gene set analysis has become the first choice to gain insights into the underlying biology of diseases or stresses in plants. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results from the primary downstream differential expression analysis. The gene set analysis approaches are well developed in microarrays and RNA-seq gene expression data analysis. These approaches mainly focus on analyzing the gene sets with gene ontology or pathway annotation data. However, in plant biology, such methods may not establish any formal relationship between the genotypes and the phenotypes, as most of the traits are quantitative and controlled by polygenes. The existing Quantitative Trait Loci (QTL)-based gene set analysis approaches only focus on the over-representation analysis of the selected genes while ignoring their associated gene scores. Therefore, we developed an innovative statistical approach, GSQSeq, to analyze the gene sets with trait enriched QTL data. This approach considers the associated differential expression scores of genes while analyzing the gene sets. The performance of the developed method was tested on five different crop gene expression datasets obtained from real crop gene expression studies. Our analytical results indicated that the trait-specific analysis of gene sets was more robust and successful through the proposed approach than existing techniques. Further, the developed method provides a valuable platform for integrating the gene expression data with QTL data.

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Gene Expression Studies May Identify Lower Risk Myelodysplastic Syndrome Patients Likely to Respond to Therapy with Ezatiostat Hydrochloride (TLK199)

Blood ◽

10.1182/blood.v118.21.2779.2779 ◽

2011 ◽

Vol 118 (21) ◽

pp. 2779-2779

Author(s):

Naomi Galili ◽

Pablo Tamayo ◽

Olga B Botvinnik ◽

Jill P Mesirov ◽

Jennifer Zikria ◽

...

Keyword(s):

Gene Expression ◽

Angiotensin Ii ◽

Mononuclear Cells ◽

Expression Data ◽

Phase 2 ◽

Glutathione S Transferase ◽

Gene Set ◽

Expression Studies ◽

Phase 2 Study ◽

Gene Expression Studies

Abstract Abstract 2779 Interpretation of gene expression studies in MDS have been especially challenging due to the heterogeneity of the cell lineages that comprise the malignant clone. In attempting to overcome these difficulties we have used a bedside-to-bench approach to define an expression signature that may identify patients likely to respond. Ezatiostat hydrochloride (TLK199) is an inhibitor of glutathione S-transferase, an enzyme that is over expressed in many cancers, and has been shown in vitro to stimulate growth and differentiation of hematopoietic progenitor cells and to induce apoptosis in leukemia cells. Based on multilineage responses in low-Int1 MDS patients in our phase 2 study of oral TLK199, a multi institutional phase 2 study was conducted in low-Int1 patients. Response was evaluated by International Working Group (IWG 2006) criteria. Pre-therapy bone marrow mononuclear cells of patients treated with TLK199 were analyzed for gene expression on the Illumina HT12v4 whole genome array with IRB approval. RNA isolated from the marrow mononuclear cells was available on 9 responders (R) and 21 non-responders (NR). Five R and 13 NR were randomly chosen to create a training set with the intent to later use the remaining samples for model testing. We identified the top 100 differentially expressed genes using a sensitive metric based on the normalized mutual information. We also performed single-sample Gene Set Enrichment Analysis to find the most salient differences in terms of pathways and biological processes between R/NR. Of special note are the 4 microRNA s differentially expressed between R/NR. Three miRNAs are under-expressed (miR-129, 802 and 548e) and one (miR-155) is over-expressed in R. Reduced expression of miR-129 has been reported in solid tumors when over-expressed has been shown to have anti-proliferative activity in cell lines. SOX4 is a target gene for miR129 and reduced expression of miR-129 results in concomitant up-regulation of SOX4 mRNA which can function as both an oncogene and a tumor suppressor gene depending on tumor lineage. Over-expression of SOX4 inhibited cytokine induced granulocyte maturation in the myeloid 32Dcl3 cell line suggesting a possible role in MDS. MiR-802 targets the receptor for angiotensin II and when expression is decreased there is increased angiotensin II activity. It has recently been shown that angiotensin is a pro-inflammatory mediator that participates in apoptosis, angiogenesis and promotes mitochondrial dysfunction, all characteristics of MDS. In addition, the transcription factor ZFHX3, a predicted target of miR-802, is a negative regulator of c-MYB which has been shown to be up-regulated in all subtypes of MDS. Similarly, c-MYB is a predicted target of miR-155, which is over-expressed in TLK199 responders. MiR-155 was shown to be over-expressed in marrow cells of a subset of human AML patients. Of particular note are the studies showing that sustained expression of miR-155 in mouse hematopoietic stem cells cause a myeloproliferative/myelodysplastic disorder. Subsequent pathway analysis of this expression data revealed that a JNK gene set as defined from the GEO dataset GDSS8081 was consistently under-expressed in responders and over-expressed in non-responders. TLK199 has been shown to induce JUN/JNK by binding to glutathione S-transferase, a key inhibitor of this pathway. The expression data confirms that patients whose pre-therapy marrow shows under-expression of the JNK gene set are precisely those who benefit from this drug therapy and those patients who already over-express these genes are unlikely to respond. This study highlights two important points: 1) Using a bedside-to-bench strategy yielded a signature that distinguished responders from non-responders 2) The signature identified genes and signaling pathways that shed light on both the biology of the disease and the mechanism of action of the drug. In conclusion, if these results are confirmed in the test set, we will use the signature in a future prospective study to preselect MDS patients for therapy with this promising drug. Disclosures: Brown: Telik, Inc.: Employment, Equity Ownership.

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Gene Expression Studies to Identify Significant Genes in AR, MTOR, MAPK Pathways and their Overlapping Regulatory Role in Prostate Cancer

Journal of Integrative Bioinformatics ◽

10.1515/jib-2018-0080 ◽

2019 ◽

Vol 16 (3) ◽

Author(s):

Nimisha Asati ◽

Abhinav Mishra ◽

Ankita Shukla ◽

Tiratha Raj Singh

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Gene Expression Data ◽

Meta Analysis ◽

Expression Patterns ◽

Mitogen Activated Protein Kinase ◽

Expression Data ◽

Mapk Pathways ◽

Expression Studies ◽

Gene Expression Studies

AbstractGene expression studies revealed a large degree of variability in gene expression patterns particularly in tissues even in genetically identical individuals. It helps to reveal the components majorly fluctuating during the disease condition. With the advent of gene expression studies many microarray studies have been conducted in prostate cancer, but the results have varied across different studies. To better understand the genetic and biological regulatory mechanisms of prostate cancer, we conducted a meta-analysis of three major pathways i.e. androgen receptor (AR), mechanistic target of rapamycin (mTOR) and Mitogen-Activated Protein Kinase (MAPK) on prostate cancer. Meta-analysis has been performed for the gene expression data for the human species that are exposed to prostate cancer. Twelve datasets comprising AR, mTOR, and MAPK pathways were taken for analysis, out of which thirteen potential biomarkers were identified through meta-analysis. These findings were compiled based upon the quantitative data analysis by using different tools. Also, various interconnections were found amongst the pathways in study. Our study suggests that the microarray analysis of the gene expression data and their pathway level connections allows detection of the potential predictors that can prove to be putative therapeutic targets with biological and functional significance in progression of prostate cancer.

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Estimation of random effects and identifying heterogeneous genes in meta-analysis of gene expression studies

Briefings in Bioinformatics ◽

10.1093/bib/bbw050 ◽

2016 ◽

pp. bbw050

Author(s):

Umaporn Siangphoe ◽

Kellie J. Archer

Keyword(s):

Gene Expression ◽

Random Effects ◽

Meta Analysis ◽

Expression Studies ◽

Gene Expression Studies

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Genome Improvement and Core Gene Set Refinement of Fugacium kawagutii

Microorganisms ◽

10.3390/microorganisms8010102 ◽

2020 ◽

Vol 8 (1) ◽

pp. 102 ◽

Cited By ~ 3

Author(s):

Tangcheng Li ◽

Liying Yu ◽

Bo Song ◽

Yue Song ◽

Ling Li ◽

...

Keyword(s):

Gene Expression ◽

Gene Annotation ◽

Gene Prediction ◽

Acid Synthesis ◽

Core Gene ◽

Chromosome Conformation ◽

Gene Set ◽

Kegg Pathways ◽

Expression Studies ◽

Gene Expression Studies

Cataloging an accurate functional gene set for the Symbiodiniaceae species is crucial for addressing biological questions of dinoflagellate symbiosis with corals and other invertebrates. To improve the gene models of Fugacium kawagutii, we conducted high-throughput chromosome conformation capture (Hi-C) for the genome and Illumina combined with PacBio sequencing for the transcriptome to achieve a new genome assembly and gene prediction. A 0.937-Gbp assembly of F. kawagutii were obtained, with a N50 > 13 Mbp and the longest scaffold of 121 Mbp capped with telomere motif at both ends. Gene annotation produced 45,192 protein-coding genes, among which, 11,984 are new compared to previous versions of the genome. The newly identified genes are mainly enriched in 38 KEGG pathways including N-Glycan biosynthesis, mRNA surveillance pathway, cell cycle, autophagy, mitophagy, and fatty acid synthesis, which are important for symbiosis, nutrition, and reproduction. The newly identified genes also included those encoding O-methyltransferase (O-MT), 3-dehydroquinate synthase, homologous-pairing protein 2-like (HOP2) and meiosis protein 2 (MEI2), which function in mycosporine-like amino acids (MAAs) biosynthesis and sexual reproduction, respectively. The improved version of the gene set (Fugka_Geneset _V3) raised transcriptomic read mapping rate from 33% to 54% and BUSCO match from 29% to 55%. Further differential gene expression analysis yielded a set of stably expressed genes under variable trace metal conditions, of which 115 with annotated functions have recently been found to be stably expressed under three other conditions, thus further developing the “core gene set” of F. kawagutii. This improved genome will prove useful for future Symbiodiniaceae transcriptomic, gene structure, and gene expression studies, and the refined “core gene set” will be a valuable resource from which to develop reference genes for gene expression studies.

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ExAtlas: An interactive online tool for meta-analysis of gene expression data

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720015500195 ◽

2015 ◽

Vol 13 (06) ◽

pp. 1550019 ◽

Cited By ~ 37

Author(s):

Alexei A. Sharov ◽

David Schlessinger ◽

Minoru S. H. Ko

Keyword(s):

Gene Expression ◽

Gene Ontology ◽

Gene Expression Data ◽

Fixed Effects ◽

Expression Profiles ◽

Meta Analysis ◽

Data Sets ◽

Expression Data ◽

Gene Set ◽

Public Data

We have developed ExAtlas, an on-line software tool for meta-analysis and visualization of gene expression data. In contrast to existing software tools, ExAtlas compares multi-component data sets and generates results for all combinations (e.g. all gene expression profiles versus all Gene Ontology annotations). ExAtlas handles both users’ own data and data extracted semi-automatically from the public repository (GEO/NCBI database). ExAtlas provides a variety of tools for meta-analyses: (1) standard meta-analysis (fixed effects, random effects, z-score, and Fisher’s methods); (2) analyses of global correlations between gene expression data sets; (3) gene set enrichment; (4) gene set overlap; (5) gene association by expression profile; (6) gene specificity; and (7) statistical analysis (ANOVA, pairwise comparison, and PCA). ExAtlas produces graphical outputs, including heatmaps, scatter-plots, bar-charts, and three-dimensional images. Some of the most widely used public data sets (e.g. GNF/BioGPS, Gene Ontology, KEGG, GAD phenotypes, BrainScan, ENCODE ChIP-seq, and protein–protein interaction) are pre-loaded and can be used for functional annotations.

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