scholarly journals Microarray Analysis Shows That Recessive Resistance to Watermelon mosaic virus in Melon Is Associated with the Induction of Defense Response Genes

2012 ◽  
Vol 25 (1) ◽  
pp. 107-118 ◽  
Author(s):  
Daniel Gonzalez-Ibeas ◽  
Joaquin Cañizares ◽  
Miguel A. Aranda
Keyword(s):  
Mosaic Virus ◽  
Defense Response ◽  
Time Course ◽  
Expression Profiles ◽  
Quantitative Polymerase Chain Reaction ◽  
Virus Titer ◽  
Gene Expression Profiles ◽  
Early Response ◽  
Resistant Variety ◽  
Watermelon Mosaic Virus

Resistance to Watermelon mosaic virus (WMV) in melon (Cucumis melo L.) accession TGR-1551 is characterized by a significant reduction in virus titer, and is inherited as a recessive, loss-of-susceptibility allele. We measured virus RNA accumulation in TGR-1551 plants and a susceptible control (‘Tendral’) by real-time quantitative polymerase chain reaction, and also profiled the expression of 17,443 unigenes represented on a melon microarray over a 15-day time course. The virus accumulated to higher levels in cotyledons of the resistant variety up to 9 days postinoculation (dpi) but, thereafter, levels increased in the susceptible variety while those in the resistant variety declined. Microarray experiments looking at the early response to infection (1 and 3 dpi), as well as responses after 7 and 15 dpi, revealed more profound transcriptomic changes in resistant plants than susceptible ones. The gene expression profiles revealed deep and extensive transcriptome remodeling in TGR-1551 plants, often involving genes with pathogen response functions. Overall, our data suggested that resistance to WMV in TGR-1551 melon plants is associated with a defense response, which contrasts with the recessive nature of the resistance trait.

scholarly journals Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Arika Fukushima ◽  
Masahiro Sugimoto ◽  
Satoru Hiwa ◽  
Tomoyuki Hiroyasu
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Response To Therapy ◽  
Hcv Infection ◽  
Entire Treatment Period ◽  
Time Points ◽  
Time Course Data ◽  
Conventional Methods

Abstract Background Historical and updated information provided by time-course data collected during an entire treatment period proves to be more useful than information provided by single-point data. Accurate predictions made using time-course data on multiple biomarkers that indicate a patient’s response to therapy contribute positively to the decision-making process associated with designing effective treatment programs for various diseases. Therefore, the development of prediction methods incorporating time-course data on multiple markers is necessary. Results We proposed new methods that may be used for prediction and gene selection via time-course gene expression profiles. Our prediction method consolidated multiple probabilities calculated using gene expression profiles collected over a series of time points to predict therapy response. Using two data sets collected from patients with hepatitis C virus (HCV) infection and multiple sclerosis (MS), we performed numerical experiments that predicted response to therapy and evaluated their accuracies. Our methods were more accurate than conventional methods and successfully selected genes, the functions of which were associated with the pathology of HCV infection and MS. Conclusions The proposed method accurately predicted response to therapy using data at multiple time points. It showed higher accuracies at early time points compared to those of conventional methods. Furthermore, this method successfully selected genes that were directly associated with diseases.

scholarly journals Discovery of novel mechanosensitive genes in vivo using mouse carotid artery endothelium exposed to disturbed flow

Blood ◽  
2010 ◽  
Vol 116 (15) ◽  
pp. e66-e73 ◽  
Author(s):  
Chih-Wen Ni ◽  
Haiwei Qiu ◽  
Amir Rezvan ◽  
Kihwan Kwon ◽  
Douglas Nam ◽  
...  
Keyword(s):  
Carotid Artery ◽  
Ex Vivo ◽  
Expression Profiles ◽  
Quantitative Polymerase Chain Reaction ◽  
Gene Expression Profiles ◽  
Disturbed Flow ◽  
A Genome ◽  
Pattern Comparison

Abstract Recently, we showed that disturbed flow caused by a partial ligation of mouse carotid artery rapidly induces atherosclerosis. Here, we identified mechanosensitive genes in vivo through a genome-wide microarray study using mouse endothelial RNAs isolated from the flow-disturbed left and the undisturbed right common carotid artery. We found 62 and 523 genes that changed significantly by 12 hours and 48 hours after ligation, respectively. The results were validated by quantitative polymerase chain reaction for 44 of 46 tested genes. This array study discovered numerous novel mechanosensitive genes, including Lmo4, klk10, and dhh, while confirming well-known ones, such as Klf2, eNOS, and BMP4. Four genes were further validated for protein, including LMO4, which showed higher expression in mouse aortic arch and in human coronary endothelium in an asymmetric pattern. Comparison of in vivo, ex vivo, and in vitro endothelial gene expression profiles indicates that numerous in vivo mechanosensitive genes appear to be lost or dysregulated during culture. Gene ontology analyses show that disturbed flow regulates genes involved in cell proliferation and morphology by 12 hours, followed by inflammatory and immune responses by 48 hours. Determining the functional importance of these novel mechanosensitive genes may provide important insights into understanding vascular biology and atherosclerosis.

scholarly journals Prediction of Pharmacological and Xenobiotic Responses to Drugs Based on Time Course Gene Expression Profiles

PLoS ONE ◽  
2009 ◽  
Vol 4 (12) ◽  
pp. e8126 ◽  
Author(s):  
Tao Huang ◽  
WeiRen Cui ◽  
LeLe Hu ◽  
KaiYan Feng ◽  
Yi-Xue Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles

scholarly journals Identification of central nervous system genes involved in the host response to the scrapie agent during preclinical and clinical infection

2004 ◽  
Vol 85 (11) ◽  
pp. 3459-3471 ◽  
Author(s):  
Stephanie Booth ◽  
Christopher Bowman ◽  
Richard Baumgartner ◽  
Garrett Sorensen ◽  
Catherine Robertson ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Time Course ◽  
Early Stage ◽  
Expression Profiles ◽  
Clinical Stage ◽  
Disease Process ◽  
Gene Expression Profiles ◽  
Number Of Genes ◽  
Haematopoietic System

Genes that are expressed differentially in the central nervous system of mice during infection with mouse-adapted scrapie agents were identified in this study. cDNA microarrays were used to examine gene-expression profiles at early, middle (preclinical) and late (clinical) time points after inoculation. A number of genes that showed significant changes in expression during the clinical stage of disease were identified. Of these, 138 were upregulated and 20 were downregulated. A smaller number of genes showed differential expression at the early and middle stages of the disease time course. These genes are interesting, as they may reflect biological processes that are involved in the molecular pathogenesis of the prion agent. At present, little is known about the early events in the disease process that trigger neurodegeneration. Perhaps most interestingly, one group of genes that exhibited decreased expression in all tested stages of the disease was identified in this study. This cluster included four transcripts representing haematopoietic system-related genes, which suggests that the haematopoietic system is involved in the disease process from an early stage.

Gene expression profiling of normal and malignant CD34-derived megakaryocytic cells

Blood ◽  
2004 ◽  
Vol 104 (10) ◽  
pp. 3126-3135 ◽  
Author(s):  
Elena Tenedini ◽  
Maria Elena Fagioli ◽  
Nicola Vianelli ◽  
Pier Luigi Tazzari ◽  
Francesca Ricci ◽  
...  
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Mitochondrial Permeability Transition ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Annexin V ◽  
Permeability Transition Pore ◽  
Permeability Transition ◽  
Course Evaluation ◽  
Oligonucleotide Microarray Analysis

Abstract Gene expression profiles of bone marrow (BM) CD34-derived megakaryocytic cells (MKs) were compared in patients with essential thrombocythemia (ET) and healthy subjects using oligonucleotide microarray analysis to identify differentially expressed genes and disease-specific transcripts. We found that proapoptotic genes such as BAX, BNIP3, and BNIP3L were down-regulated in ET MKs together with genes that are components of the mitochondrial permeability transition pore complex, a system with a pivotal role in apoptosis. Conversely, antiapoptotic genes such as IGF1-R and CFLAR were up-regulated in the malignant cells, as was the SDF1 gene, which favors cell survival. On the basis of the array results, we characterized apoptosis of normal and ET MKs by time-course evaluation of annexin-V and sub-G1 peak DNA stainings of immature and mature MKs after culture in serum-free medium with an optimal thrombopoietin concentration, and annexin-V–positive MKs only, with decreasing thrombopoietin concentrations. ET MKs were more resistant to apoptosis than their normal counterparts. We conclude that imbalance between proliferation and apoptosis seems to be an important step in malignant ET megakaryocytopoiesis.

scholarly journals Comparative analyses of time-course gene expression profiles of the long-lived sch9Δ mutant

2009 ◽  
Vol 38 (1) ◽  
pp. 143-158 ◽  
Author(s):  
Huanying Ge ◽  
Min Wei ◽  
Paola Fabrizio ◽  
Jia Hu ◽  
Chao Cheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Comparative Analyses

scholarly journals Efficient transcriptome profiling across the malaria parasite erythrocytic cycle by flow sorting

2020 ◽  
Author(s):  
Aliou Dia ◽  
Catherine Jett ◽  
Marina McDew-White ◽  
Xue Li ◽  
Timothy J.C. Anderson ◽  
...  
Keyword(s):  
Malaria Parasite ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Transcriptome Profiling ◽  
Complex Life Cycle ◽  
Developmental Cycle ◽  
Mosquito Vector ◽  
Flow Sorting ◽  
Erythrocytic Cycle

AbstractPlasmodium falciparum is the most virulent and widespread of the human malaria parasite species. This parasite has a complex life cycle that involves sexual replication in a mosquito vector and asexual replication in a human host. During the 48-hour intraerythrocytic developmental cycle (IDC), parasites develop and multiply through the morphologically distinct ring, trophozoite and schizont stages. Stage-specific transcriptomic approaches have shown gene expression profiles continually change throughout the IDC. Cultures of tightly synchronized parasites are required to capture the transcriptome specific to a developmental stage. However, the most commonly used synchronization methods require lysis of late stages, potentially perturbing transcription, and often do not result in tightly synchronized cultures. To produce complete transcriptome profiles of the IDC a synchronous culture requires frequent sampling over a 48-hour period, this is both time consuming and labor intensive. Here we develop a method to sample the IDC densely by isolating parasites from an asynchronous culture with fluorescence activated cell sorting (FACS). We sort parasites in tight windows of IDC progression based on their DNA/RNA abundance. We confirmed the tight synchronization and stage specificity by light microscopy and RNAseq profiling. We optimized our protocol for low numbers of sorted cells allowing us to rapidly capture transcriptome profiles across the entire IDC from a single culture flask. This methodology will allow malaria stage-specific studies to perform experiments directly from asynchronous cultures with high accuracy and without the need for labor-intensive time-course experiments.

Analysis of time-course gene expression profiles of a periodontal ligament tissue model under compression

2013 ◽  
Vol 58 (5) ◽  
pp. 511-522 ◽  
Author(s):  
Yu Li ◽  
Meile Li ◽  
Lijun Tan ◽  
Shengbin Huang ◽  
Lixing Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Periodontal Ligament ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Tissue Model
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