scholarly journals Sequential Gene Expression Analysis During the Early Alloreactive Phenomena After Allogeneic BMT Identifies Gene Sets and Pathways Differentially Expressed in the Skin and the Blood of BMT Recipients: Implications for the Discovery of Biomarkers of Cutaneous GVHD That Are Relevant to the Target Organ

2011 ◽  
Vol 17 (2) ◽  
pp. S324
Author(s):  
R.F. Duarte ◽  
J.V. Garcia-Gutierrez ◽  
I. Sanchez-Ortega ◽  
M.J. Remigia ◽  
M.E. Rodriguez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Target Organ ◽  
Differentially Expressed ◽  
Allogeneic Bmt ◽  
Gene Sets

Isolation of differentially expressed genes in wheat caryopses with contrasting starch granule size

2013 ◽  
Vol 8 (3) ◽  
pp. 297-305
Author(s):  
Rita Armonienė ◽  
Kristina Jonavičienė ◽  
Vytautas Ruzgas ◽  
Gintaras Brazauskas
Keyword(s):  
Gene Expression ◽  
Winter Wheat ◽  
Differentially Expressed Genes ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Starch Granule ◽  
Wheat Breeding ◽  
Granule Size ◽  
Differentially Expressed ◽  
Breeding Lines

AbstractIn order to identify genes responsible for starch granule initiation during early development of wheat caryopsis, nine winter wheat breeding lines were studied. Two breeding lines, which are the most diverse in A-type granule size (26.85 µm versus 23.65 µm) were chosen for further differential gene expression analysis in developing caryopses at 10 and 15 days post-anthesis (DPA). cDNA-amplified fragment length polymorphism (cDNA-AFLP) analysis resulted in 384 transcript-derived fragments, out of which 18 were identified as being differentially expressed. Six differentially expressed genes, together with the six well-known starch biosynthesis genes, were chosen for semi-quantitative gene expression analysis in developing wheat caryopses at 10 and 15 DPA. This study provides genomic information on 18 genes differentially expressed at early stages of wheat caryopses development and reports on the identification of genes putatively involved in the production of large A-type granules. These genes are targets for further validation on their role in starch granule synthesis control and provide the basis for the development of DNA marker tools in winter wheat breeding for enhanced starch quality.

Global Gene Expression Analysis Demonstrates that Transforming Growth Factor β1 (TGF-β1) Signals Exclusively through Receptor Complexes Involving TGF-β Receptor I and Identifies Numerous Targets of TGF-β Signaling.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2178-2178
Author(s):  
Goran Karlsson ◽  
Yingchun Liu ◽  
Marie-José Goumans ◽  
Jonas Larsson ◽  
Ju-Seog Lee ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Target Genes ◽  
Global Gene Expression ◽  
Differentially Expressed ◽  
Global Gene Expression Analysis ◽  
Β Receptor ◽  
Tgf Β1

Abstract In the hematopoietic system, TGF-β1 is one of the most potent extrinsic regulators, affecting both early progenitors and committed cells. At the top of the hematopoietic hierarchy, TGF-β1 maintains hematopoietic stem cells (HSCs) in quiescence in vitro through transcriptional regulation of genes encoding proteins important in the cell cycle. We have shown that TGF-β receptor I (TβRI) −/− HSCs exhibit increased proliferative capacity in vitro and that TβRII−/− mice develop a multifocal autoimmune disease, mainly mediated by T-cells (Larsson et al, 2003, Levéen et al 2002). The mechanisms of TGF-β signaling in hematopoietic cells are poorly understood and many target genes of TGF-β signaling remain elusive. In this study we have used global gene expression analysis to investigate whether all TGF-β signaling is mediated by TβRI and II. Furthermore, we asked what target genes are affected upon TGF-β stimulation in normal and TGF-β signaling deficient murine embryonic fibroblasts (MEFs). MEFs were grown with and without TGF-β1 stimulation and proliferation, transcriptional responses and expression analysis were performed. We demonstrate through Western Blot analysis, luciferase reporter assays and cell expansion experiments how these cells lack functional TβRI. Additionally, transcriptional assays show that no other Smad activity is triggered by TGF-β1 stimulation. Furthermore, we demonstrate through quantitative RT-PCR that the inhibitor of differentiation family of genes, known targets of TGF-β signaling, are not affected by TGF-β1 in TβRI−/− MEFs, while wt cells downregulate these genes 4–8.5 fold in response to stimulation. In order to completely exclude alternative receptors outside the TGF-β superfamily and signaling pathways activated through TβRII alone, we performed global gene expression profiling on TGF-β1 stimulated TβRI−/− MEFs with unstimulated TβRI deficient cells as reference. Very few (0.05 %) of the more than 37,000 spots on the microarray had a >2 fold differential expression in the two experiments conducted. Similar experiments performed on wt cells resulted in differential expression of between 2.6–3.9 % of the genes printed. From this data we conclude that no signaling affecting gene expression occur in the absence of TβRI in these cells. Additionally we present transcriptional profiles of MEF cell lines that either are normal or are TβRI deficient. By means of cDNA microarray technology, we have identified genes that were differentially expressed when TβRI deficient fibroblasts were compared to wt cells stimulated with TGF-β1. Our results create a data base of 461 significantly differentially expressed (p<0.01) target genes of TGF-β signaling. These include genes potentially responsible for the growth arrest induced by TGF-β1, like Gadd45g, Gas5, Id1, Id2 and Id3. However, the most significantly enriched number of differentially expressed genes are involved in protein folding and chaperone activities (Hspa9a, Hsp105, Hspe1, Hsp60, Cct2, Cct3, Cct8, Tcp1 and Dnaja1. Studies to identify TGF-β signaling responsive genes in HSCs are in progress.

scholarly journals A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour Survivals

2009 ◽  
Vol 2009 ◽  
pp. 1-7 ◽  
Author(s):  
Qihua Tan ◽  
Mads Thomassen ◽  
Kirsten M. Jochumsen ◽  
Ole Mogensen ◽  
Kaare Christensen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Feature Selection ◽  
Expression Analysis ◽  
Survival Data ◽  
Gene Expression Analysis ◽  
Cancer Survival ◽  
Feature Space ◽  
Differentially Expressed ◽  
Selection Strategy ◽  
Marker Genes

Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances.

Gene-Expression Profiling of Graft-Versus-Host Disease by Oligonucleotide Microarrays.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 4645-4645
Author(s):  
Jan Verner ◽  
Jitka Kabathova ◽  
Boris Tichy ◽  
Zbynek Zdrahal ◽  
Alexandra Tomancova ◽  
...  
Keyword(s):  
Gene Expression ◽  
Czech Republic ◽  
Differentially Expressed Genes ◽  
Expression Analysis ◽  
Graft Versus Host Disease ◽  
Gene Expression Analysis ◽  
Differentially Expressed ◽  
Oligonucleotide Microarrays ◽  
Post Transplantation ◽  
Graft Versus Host

Abstract Abstract 4645 Background Graft-versus-host disease (GvHD) is the life-threatening complication of allogeneic hematopoietic stem cells transplantation (allo-HSCT). GvHD is mediated by an immune reaction of donor T lymphocytes against recipient's tissues/cells. Acute GvHD (aGvHD) appearing within the first 100 days post transplantation is the most frequent cause of recipient's death and characterization of biomarkers for early prediction of aGvHD or resistance to corticoid treatment could be of great clinical relevance. Biomarker panels for aGvHD are currently extensively studied by proteomic and gene expression based approaches but so far very few markers were described and validated (Kaiser et al., 2004; Baron et al., 2007; Weissinger et al., 2007; Paczesny et al., 2009). Aim In this study, we performed microarray gene expression analysis (whole genome Human OneArray, Phalanx) of 43 leukemia patients who received allo-HSCT. Mononuclear cells isolated from peripheral blood samples (Ficoll-Paque) were collected at i) 14 days before transplantation, ii) 20 and iii) 30 days after transplantation and iv) at the time of aGvHD manifestation. We also performed gene-expression analysis for corticoid-resistant vs. corticoid-sensitive aGvHD cases. Results The SAM supervised analysis of samples collected at day +20 post transplantation revealed set of differentially expressed genes between groups of patients that developed aGvHD vs. aGvHD-free recipients. Among others, genes CASP1 (encoding caspase 1, protein implicated in apoptosis), HLA-DRA (member of MHC class II family) and LILRA3 (leukocyte immunoglobulin-like receptor, subfamily A member 3) showed the highest difference in expression. Gene expression with regard to corticoid response was analyzed at the time of first aGvHD manifestation. The SAM supervised analysis of gene expression between patients with corticoid-sensitive aGvHD (n=10) or aGvHD resistant to corticoid treatment (n=4) revealed a set of significantly differentially expressed genes including NR4A2 (nuclear receptor subfamily 4; member of the steroid-thyroid hormone-retinoid receptor superfamily), DEDD2 (death effector domain containing 2), TREM1 (triggering receptor expressed on myeloid cells 1), TPK1 (thiamin pyrophosphokinase 1) and HBEGF (heparin-binding EGF-like growth factor). Conclusion Oligonucleotide microarrays proved to be a useful tool for expression studies of hematological malignancies and our work shows that they may help to identify markers for early diagnosis/treatment of aGvHD. The limited patients' cohort and their heterogeneity complicate such studies. Our future effort will be focused on experimental group extension, cohort uniformity and verification of the obtained data. This work is supported by the grant NS9683-4/2008 provided by the IGA MH of the Czech Republic, and MSM0021622430 provided by MEYS of Czech Republic Disclosures: No relevant conflicts of interest to declare.

scholarly journals Exploiting aberrant mRNA expression in autism for gene discovery and diagnosis

2015 ◽  
Author(s):  
Jinting Guan ◽  
Ence Yang ◽  
Jizhou Yang ◽  
Yong Zeng ◽  
Guoli Ji ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Genetic Heterogeneity ◽  
Gene Expression Analysis ◽  
Autism Spectrum ◽  
Data Set ◽  
Expression Variability ◽  
Aberrant Gene Expression ◽  
Gene Sets ◽  
Aberrant Gene

AbstractAutism spectrum disorder (ASD) is characterized by substantial phenotypic and genetic heterogeneity, which greatly complicates the identification of genetic factors that contribute to the disease. Study designs have mainly focused on group differences between cases and controls. The problem is that, by their nature, group difference-based methods (e.g., differential expression analysis) blur or collapse the heterogeneity within groups. By ignoring genes with variable within-group expression, an important axis of genetic heterogeneity contributing to expression variability among affected individuals has been overlooked. To this end, we develop a new gene expression analysis method—aberrant gene expression analysis, based on the multivariate distance commonly used for outlier detection. Our method detects the discrepancies in gene expression dispersion between groups and identifies genes with significantly different expression variability. Using this new method, we re-visited RNA sequencing data generated from post-mortem brain tissues of 47 ASD and 57 control samples. We identified 54 functional gene sets whose expression dispersion in ASD samples is more pronounced than that in controls, as well as 76 co-expression modules present in controls but absent in ASD samples due to ASD-specific aberrant gene expression. We also exploited aberrantly expressed genes as biomarkers for ASD diagnosis. With a whole blood expression data set, we identified three aberrantly expressed gene sets whose expression levels serve as discriminating variables achieving >70% classification accuracy. In summary, our method represents a novel discovery and diagnostic strategy for ASD. Our findings may help open an expression variability-centered research avenue for other genetically heterogeneous disorders.

scholarly journals Changes in gene expression at the CD160 locus in the whole blood of sepsis patients.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Expression Analysis ◽  
Whole Blood ◽  
Gene Expression Analysis ◽  
Differentially Expressed ◽  
Blood Gene Expression ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Sepsis is a leading cause of mortality (1). We mined published datasets from the whole blood of patients with sepsis to identify differentially expressed genes in the septic state (2, 3). We found changes in CD160 expression as among the most significant quantitative differences in sepsis whole blood gene expression. Analysis of a separate dataset (4) demonstrated significant repression of a long non-coding RNA produced at the CD160 locus in the blood of patients with sepsis. In the datasets we analyzed, changes in coding and non-coding gene expression at the CD160 locus were among the most significant changes in gene expression in the blood of patients with sepsis.

scholarly journals Coding and non-coding RNAs transcribed at the RORA locus (ROR𝛂) are differentially expressed in the whole blood of sepsis patients.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Expression Analysis ◽  
Whole Blood ◽  
Gene Expression Analysis ◽  
Differentially Expressed ◽  
Blood Gene Expression ◽  
Non Coding Rna ◽  
Non Coding Rnas ◽  
Long Non Coding Rna

Sepsis is a leading cause of mortality (1). We mined published datasets from the whole blood of patients with sepsis to identify differentially expressed genes in the septic state (2, 3). We found changes in RORA expression as among the most significant quantitative differences in sepsis whole blood gene expression. Analysis of a separate dataset (4) demonstrated significant repression of a long non-coding RNA produced at the RORA locus in the blood of patients with sepsis.

scholarly journals Gene expression analysis reveals chronic low level exposure to the pesticide diazinon affects psychological disorders gene sets in the adult rat

Toxicology ◽  
2018 ◽  
Vol 393 ◽  
pp. 90-101 ◽  
Author(s):  
Claire Y. Savy ◽  
Ann E. Fitchett ◽  
Peter G. Blain ◽  
Christopher M. Morris ◽  
Sarah J. Judge
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Psychological Disorders ◽  
Low Level ◽  
Adult Rat ◽  
Gene Sets
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