scholarly journals Transcriptional Profiling of Leucocyte Count Variation from Porcine Peripheral Blood Reveals Differential Gene Expression

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Adeyinka Abiola Adetula ◽  
Xiangdong Liu ◽  
Thuy Nhien Tran Thi ◽  
Ali Akbar Bhuiyan ◽  
Xiaoyong Du ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Differential Expression ◽  
Leucocyte Count ◽  
Expression Profiles ◽  
Transcriptional Profiling ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Poly I:C ◽  
Biological Processes

Leucocytes have tremendous health-check importance related to the individual antiviral capacity of pigs and other mammals. However, the molecular mechanism of the immune response of blood leucocytes in pigs is not completely known. This study investigated the leucocyte-count variation before and after poly I:C stimulation in a Duroc–Erhualian F2 population. Pigs with increased and decreased differences in leucocyte counts were coded as increased responder (IR) and decreased responder (DR), respectively. Then, we used microarray technology to compare the gene-expression profiles of both groups of pigs. Transcriptomic analysis identified 129 differentially expressed genes (DEGs) in IR pigs and 136 DEGs in DR pigs. Forty-one common DEGs showed that both groups had similar expression patterns of immune responses. These results illustrated a differential expression in both groups. Furthermore, qPCR experiment was performed to verify the differential-expression profile. Functional annotation of the DEGs indicated that both IR and DR pigs were similar in several biological processes, including innate immune response, and also exhibited distinct differences in biological processes, molecular function, and pathways. These results provided insights into the mechanism underlying the antiviral capacity of pigs.Trial registration numberis CAS Registry Number24939-03-5.

scholarly journals RankerGUI: A Computational Framework to Compare Differential Gene Expression Profiles Using Rank Based Statistics

2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Differential Gene Expression ◽  
Web Application ◽  
Cellular Response ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Experimental Conditions ◽  
Differential Gene

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.

scholarly journals Methyl donor deficient diets cause distinct alterations in lipid metabolism but are poorly representative of human NAFLD

2017 ◽  
Vol 2 ◽  
pp. 67 ◽  
Author(s):  
Marcus J. Lyall ◽  
Jessy Cartier ◽  
James A Richards ◽  
Diego Cobice ◽  
John P Thomson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dietary Intervention ◽  
Expression Profiles ◽  
Transcriptional Profiling ◽  
Expression Patterns ◽  
Density Lipoprotein ◽  
Gene Expression Profiles ◽  
Transcriptional Level ◽  
Alcoholic Fatty Liver ◽  
Methyl Donor

Background: Non-alcoholic fatty liver disease (NAFLD) is a global health issue. Dietary methyl donor restriction is used to induce a NAFLD/non-alcoholic steatohepatitis (NASH) phenotype in rodents, however the extent to which this model reflects human NAFLD remains incompletely understood. To address this, we undertook hepatic transcriptional profiling of methyl donor restricted rodents and compared these to published human NAFLD datasets.              Methods: Adult C57BL/6J mice were maintained on control, choline deficient (CDD) or methionine/choline deficient (MCDD) diets for four weeks; the effects on methyl donor and lipid biology were investigated by bioinformatic analysis of hepatic gene expression profiles followed by a cross-species comparison with human expression data of all stages of NAFLD. Results: Compared to controls, expression of the very low density lipoprotein (VLDL) packaging carboxylesterases (Ces1d, Ces1f, Ces3b) and the NAFLD risk allele Pnpla3 were suppressed in MCDD; with Pnpla3 and the liver predominant Ces isoform, Ces3b, also suppressed in CDD. With respect to 1-carbon metabolism, down-regulation of Chka, Chkb, Pcty1a, Gnmt and Ahcy with concurrent upregulation of Mat2a suggests a drive to maintain S-adenosylmethionine levels. There was minimal similarity between global gene expression patterns in either dietary intervention and any stage of human NAFLD, however some common transcriptomic changes in inflammatory, fibrotic and proliferative mediators were identified in MCDD, NASH and HCC. Conclusions: This study suggests suppression of VLDL assembly machinery may contribute to hepatic lipid accumulation in these models, but that CDD and MCDD rodent diets are minimally representative of human NAFLD at the transcriptional level.

scholarly journals A classifier driven approach to find biomarkers for affective disorders from transcription profiles in blood

2016 ◽  
Vol 1 (1) ◽  
pp. 34 ◽  
Author(s):  
Wiktor Mazin ◽  
Joseph A Tamm ◽  
Irina A Antonijevic ◽  
Aicha Abdourahman ◽  
Munish Das ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Affective Disorders ◽  
Expression Profiles ◽  
Quantitative Polymerase Chain Reaction ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Expression Levels ◽  
Control Subjects ◽  
Transcription Profiles

Gene expression profiles in blood are increasingly being used to identify biomarkers for different affective disorders. We have selected a set of 29 genes to generate expression profiles for healthy control subjects as well as for patients diagnosed with acute post-traumatic stress disorder (PTSD) and with borderline personality disorder (BPD). Measurements were performed by quantitative polymerase chain reaction (qPCR). Using the actual data in an anonym-ous form we constructed a series of artificial data sets with known gene expression profiles. These sets were used to test 14 classification algorithms and feature selection methods for their ability to identify the correct expression patterns. Application of the three most effective algorithms to the actual expression data showed that control subjects can be dis-tinguished from BPD patients based on differential expression levels of the gene transcripts Gi2, GR and MAPK14, targets that may have links to stress related diseases. Controls can also be distinguished from acute PTSD patients by differential expression levels of the transcripts for ERK2 and RGS2 that are known to be associated with mood disord-ers and social anxiety. We conclude that it is possible to identify informative transcription profiles in blood samples from individuals with affective disorders.

scholarly journals NIMG-44. NON-INVASIVE ADVANCED IMAGING METRICS PROVIDE POTENTIAL BIOMARKERS FOR GBM BIOLOGICAL HETEROGENEITY AND IMMUNE LANDSCAPE VARIANCE

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi171-vi171
Author(s):  
Cymon Kersch ◽  
Leslie Muldoon ◽  
Rochelle Fu ◽  
Cheryl Claunch ◽  
Edward Neuwelt ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Set Enrichment Analysis ◽  
Immune Gene ◽  
Biological Processes ◽  
Non Invasive ◽  
Mri Features ◽  
Inflammatory Immune Response

Abstract BACKGROUND Treatment of glioblastoma multiforme (GBM) is complicated by extensive tumor heterogeneity. We hypothesize that transcriptomic analysis of brain tumor regions with different magnetic resonance imaging (MRI) characteristics will define specific biological processes, providing a non-invasive method for tumor characterization and stratification. METHODS Previously at the University of California San Francisco, treatment naïve GBM tissue from gadolinium contrast enhancing lesion (CEL) and non-enhancing lesion (NCEL) regions were stereotactically sampled; prior to resection, relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) were determined. The tissue samples were characterized by immunohistochemistry and assessed for gene expression by microarray analysis. We correlated gene expression patterns in the CEL, NCEL, and non-tumor gliotic brain samples with multimodal physiological imaging metrics and immunohistochemical phenotypes. Gene expression networks were probed using Gene Set Enrichment Analysis. Key immunologic genes were examined individually. RESULTS Samples with differing MRI and histological phenotypes demonstrated transcriptomic variance reflecting distinct biological networks. We found significant differences in immune pathways, with immune gene signature prominent in CEL areas, moderate in NCEL and low in gliotic non-tumor brain. Within homogenously enhancing areas of CEL and NCEL there was underlying heterogeneity detectable by variable rCBV, ADC and histological phenotypes, which correlate with differing gene expression profiles indicative of biological and immunological tumor microenvironments. Increasing rCBV was correlated with an anti-inflammatory immune response in the CEL and a pro-inflammatory immune response in the NCEL. ADC was negatively correlated with cell cycle and immune networks in CEL, while NCEL ADC was positively correlated with immune processes. GBM samples with the mesenchymal molecular subtype had the greatest immune response. CONCLUSIONS Multimodal MRI features identify regionally diverse transcriptomic-based biological and immunological phenotypes in GBM. We propose that imaging genomics provides a technique for localizing biological processes and tumor immune microenvironments across space and time in GBM.

scholarly journals Transcriptomic metaanalyses of autistic brains reveals shared gene expression and biological pathway abnormalities with cancer

2018 ◽  
Author(s):  
Jaume Forés-Martos ◽  
Ferrán Catalá-López ◽  
Jon Sánchez-Valle ◽  
Kristina Ibáñez ◽  
Héctor Tejero ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Atp Synthesis ◽  
Autism Spectrum ◽  
Functional Enrichment ◽  
Biological Processes ◽  
Cancer Types

AbstractEpidemiological and clinical evidence points to cancer as a comorbidity in people with autism spectrum disorders (ASD). A significant overlap of genes and biological processes between both diseases has also been reported. Here, for the first time, we compared the gene expression profiles of ASD frontal cortex tissues and 22 cancer types obtained by differential expression meta-analysis. Four cancer types (brain, thyroid, kidney, and pancreatic cancers) presented a significant overlap in gene expression deregulations in the same direction as ASD whereas two cancer types (lung and prostate cancers) showed differential expression profiles significantly deregulated in the opposite direction from ASD. Functional enrichment and LINCS L1000 based drug set enrichment analyses revealed the implication of several biological processes and pathways that were affected jointly in both diseases, including impairments of the immune system, and impairments in oxidative phosphorylation and ATP synthesis among others. Our data also suggest that brain and kidney cancer have patterns of transcriptomic dysregulation in the PI3K/AKT/MTOR axis that are similar to those found in ASD. These shared transcriptomic alterations could help explain epidemiological observations suggesting direct and inverse comorbid associations between ASD and particular cancer types.

scholarly journals Modulation of the Immune Response by Deferasirox in Myelodysplastic Syndrome Patients

2021 ◽  
Vol 14 (1) ◽  
pp. 41
Author(s):  
Hana Votavova ◽  
Zuzana Urbanova ◽  
David Kundrat ◽  
Michaela Dostalova Merkerova ◽  
Martin Vostry ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Blood Cell ◽  
Myelodysplastic Syndrome ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Adaptive Immune Response ◽  
Gene Expression Profiles ◽  
Iron Chelator ◽  
Multiple Cancer

Deferasirox (DFX) is an oral iron chelator used to reduce iron overload (IO) caused by frequent blood cell transfusions in anemic myelodysplastic syndrome (MDS) patients. To study the molecular mechanisms by which DFX improves outcome in MDS, we analyzed the global gene expression in untreated MDS patients and those who were given DFX treatment. The gene expression profiles of bone marrow CD34+ cells were assessed by whole-genome microarrays. Initially, differentially expressed genes (DEGs) were determined between patients with normal ferritin levels and those with IO to address the effect of excessive iron on cellular pathways. These DEGs were annotated to Gene Ontology terms associated with cell cycle, apoptosis, adaptive immune response and protein folding and were enriched in cancer-related pathways. The deregulation of multiple cancer pathways in iron-overloaded patients suggests that IO is a cofactor favoring the progression of MDS. The DEGs between patients with IO and those treated with DFX were involved predominantly in biological processes related to the immune response and inflammation. These data indicate DFX modulates the immune response mainly via neutrophil-related genes. Suppression of negative regulators of blood cell differentiation essential for cell maturation and upregulation of heme metabolism observed in DFX-treated patients may contribute to the hematopoietic improvement.

scholarly journals Gene Expression Profiles at Moxibustioned Site (ST36): A Microarray Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Hai-Yan Yin ◽  
Yong Tang ◽  
Sheng-Feng Lu ◽  
Ling Luo ◽  
Jia-Ping Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Expression Profiles ◽  
Alternative Therapy ◽  
Gene Expression Profiles ◽  
Biological Processes ◽  
Physiological Conditions ◽  
Pathological Conditions ◽  
Molecular Events ◽  
Zusanli Acupoint

As a major alternative therapy in Traditional Chinese Medicine, it has been demonstrated that moxibustion could generate a series of molecular events in blood, spleen, and brain, and so forth. However, what would happen at the moxibustioned site remained unclear. To answer this question, we performed a microarray analysis with skin tissue taken from the moxibustioned site also Zusanli acupoint (ST36) where 15-minute moxibustion stimulation was administrated. The results exhibited 145 upregulated and 72 downregulated genes which responded immediately under physiological conditions, and 255 upregulated and 243 downregulated genes under pathological conditions. Interestingly, most of the pathways and biological processes of the differentially expressed genes (DEGs) under pathological conditions get involved in immunity, while those under physiological conditions are involved in metabolism.

scholarly journals Discovering Distinct Patterns in Gene Expression Profiles

2008 ◽  
Vol 5 (2) ◽  
Author(s):  
Li Teng ◽  
Laiwan Chan
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Clustering Methods ◽  
Gene Expressions ◽  
Real Gene ◽  
Large Scale Dataset ◽  
Coexpressed Genes

SummaryTraditional analysis of gene expression profiles use clustering to find groups of coexpressed genes which have similar expression patterns. However clustering is time consuming and could be diffcult for very large scale dataset. We proposed the idea of Discovering Distinct Patterns (DDP) in gene expression profiles. Since patterns showing by the gene expressions reveal their regulate mechanisms. It is significant to find all different patterns existing in the dataset when there is little prior knowledge. It is also a helpful start before taking on further analysis. We propose an algorithm for DDP by iteratively picking out pairs of gene expression patterns which have the largest dissimilarities. This method can also be used as preprocessing to initialize centers for clustering methods, like K-means. Experiments on both synthetic dataset and real gene expression datasets show our method is very effective in finding distinct patterns which have gene functional significance and is also effcient.

CFTR ΔF508 mutation has minimal effect on the gene expression profile of differentiated human airway epithelia

2005 ◽  
Vol 289 (4) ◽  
pp. L545-L553 ◽  
Author(s):  
Joseph Zabner ◽  
Todd E. Scheetz ◽  
Hakeem G. Almabrazi ◽  
Thomas L. Casavant ◽  
Jian Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cystic Fibrosis ◽  
Large Scale ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Primary Cultures ◽  
Gene Expression Profiles ◽  
Filter Method ◽  
Tissue Destruction ◽  
Airway Epithelia

Cystic fibrosis (CF) is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR), an epithelial chloride channel regulated by phosphorylation. Most of the disease-associated morbidity is the consequence of chronic lung infection with progressive tissue destruction. As an approach to investigate the cellular effects of CFTR mutations, we used large-scale microarray hybridization to contrast the gene expression profiles of well-differentiated primary cultures of human CF and non-CF airway epithelia grown under resting culture conditions. We surveyed the expression profiles for 10 non-CF and 10 ΔF508 homozygote samples. Of the 22,283 genes represented on the Affymetrix U133A GeneChip, we found evidence of significant changes in expression in 24 genes by two-sample t-test ( P < 0.00001). A second, three-filter method of comparative analysis found no significant differences between the groups. The levels of CFTR mRNA were comparable in both groups. There were no significant differences in the gene expression patterns between male and female CF specimens. There were 18 genes with significant increases and 6 genes with decreases in CF relative to non-CF samples. Although the function of many of the differentially expressed genes is unknown, one transcript that was elevated in CF, the KCl cotransporter (KCC4), is a candidate for further study. Overall, the results indicate that CFTR dysfunction has little direct impact on airway epithelial gene expression in samples grown under these conditions.

scholarly journals Gene Expression in RET/PTC3 and E7 Transgenic Mouse Thyroids: RET/PTC3 But Not E7 Tumors Are Partial and Transient Models of Human Papillary Thyroid Cancers

Endocrinology ◽  
2008 ◽  
Vol 149 (10) ◽  
pp. 5107-5117 ◽  
Author(s):  
Agnès Burniat ◽  
Ling Jin ◽  
Vincent Detours ◽  
Natacha Driessens ◽  
Jean-Christophe Goffard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Fusion Gene ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Human Thyroid ◽  
Matrix Remodeling ◽  
Biological Processes ◽  
Papillary Thyroid ◽  
Thyroid Cancers ◽  
Transient Models

We studied gene expression profiles in two mouse models of human thyroid carcinoma: the Tg-RET/PTC3 (RP3) and Tg-E7 mice. RP3 fusion gene is the most frequent mutation found in the first wave post-Chernobyl papillary thyroid cancers (PTCs). E7 is an oncoprotein derived from the human papillomavirus 16 responsible for most cervical carcinoma in women. Both transgenic mice develop thyroid hyperplasia followed by solid differentiated carcinoma in older animals. To understand the different steps leading to carcinoma, we analyzed thyroid gene expression in both strains at different ages by microarray technology. Important biological processes were differentially regulated in the two tumor types. In E7 thyroids, cell cycle was the most up-regulated process, an observation consistent with the huge size of these tumors. In RP3 thyroids, contrary to E7 tumors, several human PTC characteristics were observed: overexpression of many immune-related genes, regulation of human PTC markers, up-regulation of EGF-like growth factors and significant regulation of angiogenesis and extracellular matrix remodeling-related genes. However, similarities were incomplete; they did not concern the overall gene expression and were not conserved in old animals. Therefore, RP3 tumors are partial and transient models of human PTC. They constitute a good model, especially in young animals, to study the respective role of the biological processes shared with human PTC and will allow testing drugs targeting these validated variables.

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