scholarly journals Global Gene Expression Analysis of Yeast Cells during Sake Brewing

2006 ◽  
Vol 72 (11) ◽  
pp. 7353-7358 ◽  
Author(s):  
Hong Wu ◽  
Xiaohong Zheng ◽  
Yoshio Araki ◽  
Hiroshi Sahara ◽  
Hiroshi Takagi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Global Gene Expression ◽  
Yeast Cells ◽  
Yeast Gene ◽  
High Concentration ◽  
Brewing Process ◽  
Global Gene Expression Analysis

ABSTRACT During the brewing of Japanese sake, Saccharomyces cerevisiae cells produce a high concentration of ethanol compared with other ethanol fermentation methods. We analyzed the gene expression profiles of yeast cells during sake brewing using DNA microarray analysis. This analysis revealed some characteristics of yeast gene expression during sake brewing and provided a scaffold for a molecular level understanding of the sake brewing process.

scholarly journals Biomarkers in Parkinson Disease: global gene expression analysis in peripheral blood from patients with and without mutations in PARK2 and PARK8

2010 ◽  
Vol 8 (3) ◽  
pp. 291-297 ◽  
Author(s):  
Patricia Maria de Carvalho Aguiar ◽  
Patricia Severino
Keyword(s):  
Gene Expression ◽  
Parkinson Disease ◽  
Expression Analysis ◽  
Peripheral Blood ◽  
Gene Expression Analysis ◽  
Small Sample Size ◽  
Expression Profiles ◽  
Global Gene Expression ◽  
Small Sample ◽  
Global Gene Expression Analysis

ABSTRACT Objective: To evaluate the performance of gene expression analysis in the peripheral blood of Parkinson disease patients with different genetic profiles using microarray as a tool to identify possible diseases related biomarkers which could contribute to the elucidation of the pathological process, as well as be useful in diagnosis. Methods: Global gene expression analysis by means of DNA microarrays was performed in peripheral blood of Parkinson disease patients with previously identified mutations in PARK2 or PARK8 genes, Parkinson disease patients without known mutations in these genes and normal controls. Each group consisted of five individuals. Results: Global gene expression profiles were heterogeneous among patients and controls, and it was not possible to detect a consistent pattern between groups. However, analyzing genes with differential expression of p < 0.005 and fold change ≥ 1.2, we were able to identify a small group of well-annotated genes. Conclusions: Despite the small sample size, the identification of differentially expressed genes suggests that the microarray technique may be useful in identifying potential biomarkers in the peripheral blood of Parkinson disease patients or in people at risk of developing the disease. This will be important once neuroprotective therapies become available, and may contribute to the identification of new pathways involved in the disease physiopathology. Results presented here should be further validated in larger groups of patients.

Effect of ovarian hormones on the healthy equine uterus: a global gene expression analysis

2016 ◽  
Vol 28 (11) ◽  
pp. 1810 ◽  
Author(s):  
Christina D. Marth ◽  
Neil D. Young ◽  
Lisa Y. Glenton ◽  
Drew M. Noden ◽  
Glenn F. Browning ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Cell Communication ◽  
Gene Expression Profiles ◽  
Global Gene Expression ◽  
Rna Seq ◽  
Complete Understanding ◽  
Pathway Enrichment ◽  
Uterine Inflammation ◽  
Global Gene Expression Analysis

The physiological changes associated with the varying hormonal environment throughout the oestrous cycle are linked to the different functions the uterus needs to fulfil. The aim of the present study was to generate global gene expression profiles for the equine uterus during oestrus and Day 5 of dioestrus. To achieve this, samples were collected from five horses during oestrus (follicle >35 mm in diameter) and dioestrus (5 days after ovulation) and analysed using high-throughput RNA sequencing techniques (RNA-Seq). Differentially expressed genes between the two cycle stages were further investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The expression of 1577 genes was found to be significantly upregulated during oestrus, whereas 1864 genes were expressed at significantly higher levels in dioestrus. Most genes upregulated during oestrus were associated with the extracellular matrix, signal interaction and transduction, cell communication or immune function, whereas genes expressed at higher levels in early dioestrus were most commonly associated with metabolic or transport functions, correlating well with the physiological functions of the uterus. These results allow for a more complete understanding of the hormonal influence on gene expression in the equine uterus by functional analysis of up- and downregulated genes in oestrus and dioestrus, respectively. In addition, a valuable baseline is provided for further research, including analyses of changes associated with uterine inflammation.

scholarly journals Granulosa cells from human primordial and primary follicles show differential global gene expression profiles

2018 ◽  
Vol 33 (4) ◽  
pp. 666-679 ◽  
Author(s):  
E H Ernst ◽  
S Franks ◽  
K Hardy ◽  
P Villesen ◽  
K Lykke-Hartmann
Keyword(s):  
Gene Expression ◽  
Granulosa Cells ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Global Gene Expression

scholarly journals Global Gene Expression Analysis of the Brainstem in EV71- and CVA16-Infected Gerbils

Viruses ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 46 ◽  
Author(s):  
Yi-Sheng Sun ◽  
Zhang-Nv Yang ◽  
Fang Xu ◽  
Chen Chen ◽  
Hang-Jing Lu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Enterovirus 71 ◽  
Foot And Mouth Disease ◽  
Global Gene Expression ◽  
Solid Foundation ◽  
Differential Gene ◽  
Global Gene Expression Analysis ◽  
Upregulated Genes

Enterovirus 71 (EV71) and coxsackievirus A16 (CVA16) are the two most important pathogens of hand, foot, and mouth disease (HFMD). However, the neuropathogenesis of EV71 and CVA16 has not been elucidated. In our previous study, we established gerbils as a useful model for both EV71 and CVA16 infection. In this work, we used RNA-seq technology to analyze the global gene expression of the brainstem of EV71- and CVA16-infected gerbils. We found that 3434 genes were upregulated while 916 genes were downregulated in EV71-infected gerbils. In CVA16-infected gerbils, 1039 genes were upregulated, and 299 genes were downregulated. We also found significant dysregulation of cytokines, such as IP-10 and CXCL9, in the brainstem of gerbils. The expression levels of 10 of the most upregulated genes were confirmed by real-time RT-PCR, and the upregulated tendency of most genes was in accordance with the differential gene expression (DGE) results. Our work provided global gene expression analysis of virus-infected gerbils and laid a solid foundation for elucidating the neuropathogenesis mechanisms of EV71 and CVA16.

scholarly journals Dynamical consequences of regional heterogeneity in the brain’s transcriptional landscape

2020 ◽  
Author(s):  
Gustavo Deco ◽  
Kevin Aquino ◽  
Aurina Arnatkevičiūtė ◽  
Stuart Oldham ◽  
Kristina Sabaroedin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Global Gene Expression ◽  
Brain Regions ◽  
Biophysical Model ◽  
Neuronal Dynamics ◽  
Regional Heterogeneity ◽  
Magnetic Resonance Imaging Mri

AbstractBrain regions vary in their molecular and cellular composition, but how this heterogeneity shapes neuronal dynamics is unclear. Here, we investigate the dynamical consequences of regional heterogeneity using a biophysical model of whole-brain functional magnetic resonance imaging (MRI) dynamics in humans. We show that models in which transcriptional variations in excitatory and inhibitory receptor (E:I) gene expression constrain regional heterogeneity more accurately reproduce the spatiotemporal structure of empirical functional connectivity estimates than do models constrained by global gene expression profiles and MRI-derived estimates of myeloarchitecture. We further show that regional heterogeneity is essential for yielding both ignition-like dynamics, which are thought to support conscious processing, and a wide variance of regional activity timescales, which supports a broad dynamical range. We thus identify a key role for E:I heterogeneity in generating complex neuronal dynamics and demonstrate the viability of using transcriptional data to constrain models of large-scale brain function.

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