Data set on a study of gene expression in peripheral samples to identify biomarkers of severity of allergic and nonallergic asthma

Drug repurposing/repositioning, which aims to find novel indications for existing drugs, contributes to reducing the time and cost for drug development. For the recent decade, gene expression profiles of drug stimulating samples have been successfully used in drug repurposing. However, most of the existing methods neglect the gene modules and the interactions among the modules, although the cross-talks among pathways are common in drug response. It is essential to develop a method that utilizes the cross-talks information to predict the reliable candidate associations. In this study, we developed MNBDR (Module Network Based Drug Repositioning), a novel method that based on module network to screen drugs. It integrated protein–protein interactions and gene expression profile of human, to predict drug candidates for diseases. Specifically, the MNBDR mined dense modules through protein–protein interaction (PPI) network and constructed a module network to reveal cross-talks among modules. Then, together with the module network, based on existing gene expression data set of drug stimulation samples and disease samples, we used random walk algorithms to capture essential modules in disease development and proposed a new indicator to screen potential drugs for a given disease. Results showed MNBDR could provide better performance than popular methods. Moreover, functional analysis of the essential modules in the network indicated our method could reveal biological mechanism in drug response.

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Unravelling the Complex Interplay of Transcription Factors Orchestrating Seed Oil Content in Brassica napus L.

International Journal of Molecular Sciences ◽

10.3390/ijms22031033 ◽

2021 ◽

Vol 22 (3) ◽

pp. 1033

Author(s):

Abirami Rajavel ◽

Selina Klees ◽

Johanna-Sophie Schlüter ◽

Hendrik Bertram ◽

Kun Lu ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factors ◽

Brassica Napus ◽

Oil Content ◽

Seed Oil ◽

Seed Oil Content ◽

Complex Interplay ◽

Brassica Napus L ◽

Data Set ◽

Developmental Switches

Transcription factors (TFs) and their complex interplay are essential for directing specific genetic programs, such as responses to environmental stresses, tissue development, or cell differentiation by regulating gene expression. Knowledge regarding TF–TF cooperations could be promising in gaining insight into the developmental switches between the cultivars of Brassica napus L., namely Zhongshuang11 (ZS11), a double-low accession with high-oil- content, and Zhongyou821 (ZY821), a double-high accession with low-oil-content. In this regard, we analysed a time series RNA-seq data set of seed tissue from both of the cultivars by mainly focusing on the monotonically expressed genes (MEGs). The consideration of the MEGs enables the capturing of multi-stage progression processes that are orchestrated by the cooperative TFs and, thus, facilitates the understanding of the molecular mechanisms determining seed oil content. Our findings show that TF families, such as NAC, MYB, DOF, GATA, and HD-ZIP are highly involved in the seed developmental process. Particularly, their preferential partner choices as well as changes in their gene expression profiles seem to be strongly associated with the differentiation of the oil content between the two cultivars. These findings are essential in enhancing our understanding of the genetic programs in both cultivars and developing novel hypotheses for further experimental studies.

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GCT-73. EXPRESSION PROFILING OF INTRACRANIAL GERM CELL TUMORS REVEALS UPREGULATION OF RAS THROUGH mRNA-microRNA SIGNALING PATHWAY

Neuro-Oncology ◽

10.1093/neuonc/noaa222.289 ◽

2020 ◽

Vol 22 (Supplement_3) ◽

pp. iii343-iii343

Author(s):

Aaron M Taylor ◽

Jianhe Shen ◽

Lingzhao Ren ◽

Keita Terashima ◽

Lei Huang ◽

...

Keyword(s):

Gene Expression ◽

Germ Cell ◽

Expression Profiling ◽

Model Building ◽

Rna Binding ◽

Molecular Subtype ◽

Germ Cell Tumors ◽

Cell Renewal ◽

Data Set ◽

Intracranial Germ Cell Tumors

Abstract Intracranial germ cell tumors (IGCTs) account for 3% of CNS tumors in children in the U.S. and 11% in Japan and East Asian countries. IGCTs are separated into two distinct subtypes based on histology: germinomas and non-germinomatous germ cell tumors (NGGCTs). The deep central location of IGCTs makes surgical resection and therefore molecular subtype classification difficult, and previous gene expression studies are limited. We performed mRNA expression profiling (Human Genome U133 Plus 2.0) and microRNA expression profiling (ABI TaqMan) with 36 and 49 IGCTs, respectively. Sample stratification using non-negative matrix factorization clustering of gene expression revealed two distinct subgroups that delineated germinomas from NGGCTs. Employing stepwise model building in each data set separately, we were able to separate these groups using only mRNA probes for the LIN28B and L1TD1 genes, and two microRNA, microRNA-26a and microRNA-373. MicroRNA26a suppresses the LIN28B gene and is down-regulated in germinoma. LIN28B directly binds and suppresses the let-7 microRNA family, which suppress the KRAS oncogene, previously found to be mutated in ~19% of IGCTs. L1TD1 is required for human stem cell renewal and directly interacts with LIN28B for its RNA binding function. LIN28B and L1TD1 are both known to be upregulated in other systemic germ cell tumors, but this has not yet been documented in IGCTs. In conclusion, these results show that intracranial germinomas have similar gene expression compared to systemic seminoma, and suggest a mechanism by which activation of LIN28B and L1TD1 downregulates the let-7 microRNA and subsequently upregulates KRAS.

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Differential gene expression analysis of ankylosing spondylitis shows deregulation of the HLA-DRB, HLA-DQB, ITM2A, and CTLA4 genes

Egyptian Journal of Medical Human Genetics ◽

10.1186/s43042-021-00161-0 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Rowan AlEjielat ◽

Anas Khaleel ◽

Amneh H. Tarkhan

Keyword(s):

Gene Expression ◽

Ankylosing Spondylitis ◽

Differentially Expressed Genes ◽

Gene Network ◽

Disease Diagnosis ◽

Receptor Activation ◽

Functional Enrichment ◽

Differentially Expressed ◽

Inflammatory Disorder ◽

Data Set

Abstract Background Ankylosing spondylitis (AS) is a rare inflammatory disorder affecting the spinal joints. Although we know some of the genetic factors that are associated with the disease, the molecular basis of this illness has not yet been fully elucidated, and the genes involved in AS pathogenesis have not been entirely identified. The current study aimed at constructing a gene network that may serve as an AS gene signature and biomarker, both of which will help in disease diagnosis and the identification of therapeutic targets. Previously published gene expression profiles of 16 AS patients and 16 gender- and age-matched controls that were profiled on the Illumina HumanHT-12 V3.0 Expression BeadChip platform were mined. Patients were Portuguese, 21 to 64 years old, were diagnosed based on the modified New York criteria, and had Bath Ankylosing Spondylitis Disease Activity Index scores > 4 and Bath Ankylosing Spondylitis Functional Index scores > 4. All patients were receiving only NSAIDs and/or sulphasalazine. Functional enrichment and pathway analysis were performed to create an interaction network of differentially expressed genes. Results ITM2A, ICOS, VSIG10L, CD59, TRAC, and CTLA-4 were among the significantly differentially expressed genes in AS, but the most significantly downregulated genes were the HLA-DRB6, HLA-DRB5, HLA-DRB4, HLA-DRB3, HLA-DRB1, HLA-DQB1, ITM2A, and CTLA-4 genes. The genes in this study were mostly associated with the regulation of the immune system processes, parts of cell membrane, and signaling related to T cell receptor and antigen receptor, in addition to some overlaps related to the IL2 STAT signaling, as well as the androgen response. The most significantly over-represented pathways in the data set were associated with the “RUNX1 and FOXP3 which control the development of regulatory T lymphocytes (Tregs)” and the “GABA receptor activation” pathways. Conclusions Comprehensive gene analysis of differentially expressed genes in AS reveals a significant gene network that is involved in a multitude of important immune and inflammatory pathways. These pathways and networks might serve as biomarkers for AS and can potentially help in diagnosing the disease and identifying future targets for treatment.

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Metastatic heterogeneity of the consensus molecular subtypes of colorectal cancer

npj Genomic Medicine ◽

10.1038/s41525-021-00223-7 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Peter W. Eide ◽

Seyed H. Moosavi ◽

Ina A. Eilertsen ◽

Tuva H. Brunsell ◽

Jonas Langerud ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Principal Components ◽

Prognostic Value ◽

Tumor Heterogeneity ◽

Molecular Subtypes ◽

R Package ◽

Data Set ◽

Primary Tumors ◽

External Data

AbstractGene expression-based subtypes of colorectal cancer have clinical relevance, but the representativeness of primary tumors and the consensus molecular subtypes (CMS) for metastatic cancers is not well known. We investigated the metastatic heterogeneity of CMS. The best approach to subtype translation was delineated by comparisons of transcriptomic profiles from 317 primary tumors and 295 liver metastases, including multi-metastatic samples from 45 patients and 14 primary-metastasis sets. Associations were validated in an external data set (n = 618). Projection of metastases onto principal components of primary tumors showed that metastases were depleted of CMS1-immune/CMS3-metabolic signals, enriched for CMS4-mesenchymal/stromal signals, and heavily influenced by the microenvironment. The tailored CMS classifier (available in an updated version of the R package CMScaller) therefore implemented an approach to regress out the liver tissue background. The majority of classified metastases were either CMS2 or CMS4. Nonetheless, subtype switching and inter-metastatic CMS heterogeneity were frequent and increased with sampling intensity. Poor-prognostic value of CMS1/3 metastases was consistent in the context of intra-patient tumor heterogeneity.

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Effects of the domestic thyroid stimulating hormone receptor (TSHR) variant on the hypothalamic-pituitary-thyroid axis and behavior in chicken

Genetics ◽

10.1093/genetics/iyaa050 ◽

2021 ◽

Vol 217 (1) ◽

Author(s):

Amir Fallahshahroudi ◽

Martin Johnsson ◽

Enrico Sorato ◽

S J Kumari A Ubhayasekera ◽

Jonas Bergquist ◽

...

Keyword(s):

Gene Expression ◽

Hormone Receptor ◽

Thyroid Stimulating Hormone ◽

Phenotypic Traits ◽

Wild Type ◽

Data Set ◽

Red Junglefowl ◽

Pituitary Thyroid Axis ◽

And Behavior ◽

Stimulating Hormone

Abstract Domestic chickens are less fearful, have a faster sexual development, grow bigger, and lay more eggs than their primary ancestor, the red junglefowl. Several candidate genetic variants selected during domestication have been identified, but only a few studies have directly linked them with distinct phenotypic traits. Notably, a variant of the thyroid stimulating hormone receptor (TSHR) gene has been under strong positive selection over the past millennium, but it’s function and mechanisms of action are still largely unresolved. We therefore assessed the abundance of the domestic TSHR variant and possible genomic selection signatures in an extensive data set comprising multiple commercial and village chicken populations as well as wild-living extant members of the genus Gallus. Furthermore, by mean of extensive backcrossing we introgressed the wild-type TSHR variant from red junglefowl into domestic White Leghorn chickens and investigated gene expression, hormone levels, cold adaptation, and behavior in chickens possessing either the wild-type or domestic TSHR variant. While the domestic TSHR was the most common variant in all studied domestic populations and in one of two red junglefowl population, it was not detected in the other Gallus species. Functionally, the individuals with the domestic TSHR variant had a lower expression of the TSHR in the hypothalamus and marginally higher in the thyroid gland than wild-type TSHR individuals. Expression of TSHB and DIO2, two regulators of sexual maturity and reproduction in birds, was higher in the pituitary gland of the domestic-variant chickens. Furthermore, the domestic variant was associated with higher activity in the open field test. Our findings confirm that the spread of the domestic TSHR variant is limited to domesticated chickens, and to a lesser extent, their wild counterpart, the red junglefowl. Furthermore, we showed that effects of genetic variability in TSHR mirror key differences in gene expression and behavior previously described between the red junglefowl and domestic chicken.

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Septic shock and systemic inflammatory response syndrome patients' CD15+ granulocytes were subjected to global transcriptional profiling (SIRS)

10.31219/osf.io/5zd27 ◽

2021 ◽

Author(s):

Marni Mack ◽

Argo Easston

Keyword(s):

Gene Expression ◽

United States ◽

Septic Shock ◽

Immune Cells ◽

Transcriptional Profiling ◽

The United States ◽

Transcriptional Level ◽

Data Set ◽

Transcriptional Alterations ◽

Level I

In the United States, sepsis, the body's response to infection in a typically sterile circulation, is a leading causeof death (1). To assess the primary transcriptional alterations associated with each illness state, I utilized amicroarray data set from a cohort of thirtyone individuals with septic shock or systemic inflammatory responsesyndrome (2). At the transcriptional level, I discovered that the granulocytes of patients with SIRS weresimilar to those of patients with septic shock. SIRS showed a “intermediate” gene expression state betweenthat of control patients and that of septic shock patients for numerous genes expressed in the granulocyte. Thediscovery of the most differentially expressed genes in the granulocytic immune cells of patients with septicshock might aid the development of new therapies or diagnostics for an illness with a 14.7 percent to 29.9% inhospitaldeath rate despite decades of study (1).

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Testing for Trends in Dose-Response Microarray Experiments: A Comparison of Several Testing Procedures, Multiplicity and Resampling-Based Inference

Statistical Applications in Genetics and Molecular Biology ◽

10.2202/1544-6115.1283 ◽

2007 ◽

Vol 6 (1) ◽

Cited By ~ 14

Author(s):

Dan Lin ◽

Ziv Shkedy ◽

Dani Yekutieli ◽

Tomasz Burzykowski ◽

Hinrich W.H. Göhlmann ◽

...

Keyword(s):

Gene Expression ◽

Dose Response ◽

Multiple Testing ◽

Pharmaceutical Research ◽

Ratio Test ◽

Familywise Error Rate ◽

Response Level ◽

Data Set ◽

Monotonic Trend ◽

Testing Procedures

Dose-response studies are commonly used in experiments in pharmaceutical research in order to investigate the dependence of the response on dose, i.e., a trend of the response level toxicity with respect to dose. In this paper we focus on dose-response experiments within a microarray setting in which several microarrays are available for a sequence of increasing dose levels. A gene is called differentially expressed if there is a monotonic trend (with respect to dose) in the gene expression. We review several testing procedures which can be used in order to test equality among the gene expression means against ordered alternatives with respect to dose, namely Williams' (Williams 1971 and 1972), Marcus' (Marcus 1976), global likelihood ratio test (Bartholomew 1961, Barlow et al. 1972, and Robertson et al. 1988), and M (Hu et al. 2005) statistics. Additionally we introduce a modification to the standard error of the M statistic. We compare the performance of these five test statistics. Moreover, we discuss the issue of one-sided versus two-sided testing procedures. False Discovery Rate (Benjamni and Hochberg 1995, Ge et al. 2003), and resampling-based Familywise Error Rate (Westfall and Young 1993) are used to handle the multiple testing issue. The methods above are applied to a data set with 4 doses (3 arrays per dose) and 16,998 genes. Results on the number of significant genes from each statistic are discussed. A simulation study is conducted to investigate the power of each statistic. A R library IsoGene implementing the methods is available from the first author.

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A fuzzy logic approach to analyzing gene expression data

Physiological Genomics ◽

10.1152/physiolgenomics.2000.3.1.9 ◽

2000 ◽

Vol 3 (1) ◽

pp. 9-15 ◽

Cited By ~ 138

Author(s):

PETER J. WOOLF ◽

YIXIN WANG

Keyword(s):

Gene Expression ◽

Fuzzy Logic ◽

Gene Expression Data ◽

Expression Data ◽

Heuristic Rules ◽

Yeast Gene ◽

Data Set ◽

Fuzzy Logic Approach ◽

Logic Approach ◽

Novel Algorithm

Woolf, Peter J., and Yixin Wang. A fuzzy logic approach to analyzing gene expression data. Physiol Genomics 3: 9–15, 2000.—We have developed a novel algorithm for analyzing gene expression data. This algorithm uses fuzzy logic to transform expression values into qualitative descriptors that can be evaluated by using a set of heuristic rules. In our tests we designed a model to find triplets of activators, repressors, and targets in a yeast gene expression data set. For the conditions tested, the predictions made by the algorithm agree well with experimental data in the literature. The algorithm can also assist in determining the function of uncharacterized proteins and is able to detect a substantially larger number of transcription factors than could be found at random. This technology extends current techniques such as clustering in that it allows the user to generate a connected network of genes using only expression data.

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FERMT3 mediates cigarette smoke-induced epithelial–mesenchymal transition through Wnt/β-catenin signaling

Respiratory Research ◽

10.1186/s12931-021-01881-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Xiaoshan Su ◽

Junjie Chen ◽

Xiaoping Lin ◽

Xiaoyang Chen ◽

Zhixing Zhu ◽

...

Keyword(s):

Gene Expression ◽

Lung Cancer ◽

Cell Cycle ◽

Cell Migration ◽

Cigarette Smoke ◽

Epithelial Mesenchymal Transition ◽

Control Group ◽

Data Set ◽

Mesenchymal Transition

Abstract Background Cigarette smoking is a major risk factor for chronic obstructive pulmonary disease (COPD) and lung cancer. Epithelial–mesenchymal transition (EMT) is an essential pathophysiological process in COPD and plays an important role in airway remodeling, fibrosis, and malignant transformation of COPD. Previous studies have indicated FERMT3 is downregulated and plays a tumor-suppressive role in lung cancer. However, the role of FERMT3 in COPD, including EMT, has not yet been investigated. Methods The present study aimed to explore the potential role of FERMT3 in COPD and its underlying molecular mechanisms. Three GEO datasets were utilized to analyse FERMT3 gene expression profiles in COPD. We then established EMT animal models and cell models through cigarette smoke (CS) or cigarette smoke extract (CSE) exposure to detect the expression of FERMT3 and EMT markers. RT-PCR, western blot, immunohistochemical, cell migration, and cell cycle were employed to investigate the potential regulatory effect of FERMT3 in CSE-induced EMT. Results Based on Gene Expression Omnibus (GEO) data set analysis, FERMT3 expression in bronchoalveolar lavage fluid was lower in COPD smokers than in non-smokers or smokers. Moreover, FERMT3 expression was significantly down-regulated in lung tissues of COPD GOLD 4 patients compared with the control group. Cigarette smoke exposure reduced the FERMT3 expression and induces EMT both in vivo and in vitro. The results showed that overexpression of FERMT3 could inhibit EMT induced by CSE in A549 cells. Furthermore, the CSE-induced cell migration and cell cycle progression were reversed by FERMT3 overexpression. Mechanistically, our study showed that overexpression of FERMT3 inhibited CSE-induced EMT through the Wnt/β-catenin signaling. Conclusions In summary, these data suggest FERMT3 regulates cigarette smoke-induced epithelial–mesenchymal transition through Wnt/β-catenin signaling. These findings indicated that FERMT3 was correlated with the development of COPD and may serve as a potential target for both COPD and lung cancer.

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