scholarly journals EBP2 Is a Member of the Yeast RRB Regulon, a Transcriptionally Coregulated Set of Genes That Are Required for Ribosome and rRNA Biosynthesis

2001 ◽  
Vol 21 (24) ◽  
pp. 8638-8650 ◽  
Author(s):  
Christopher Wade ◽  
Kathleen A. Shea ◽  
Roderick V. Jensen ◽  
Michael A. McAlear
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Expression Profiles ◽  
Yeast Cells ◽  
Diauxic Shift ◽  
Rrna Processing ◽  
Data Set ◽  
Consensus Sequences ◽  
Alpha Factor ◽  
Yeast Genes

ABSTRACT In an effort to identify sets of yeast genes that are coregulated across various cellular transitions, gene expression data sets derived from yeast cells progressing through the cell cycle, sporulation, and diauxic shift were analyzed. A partitioning algorithm was used to divide each data set into 24 clusters of similar expression profiles, and the membership of the clusters was compared across the three experiments. A single cluster of 189 genes from the cell cycle experiment was found to share 65 genes with a cluster of 159 genes from the sporulation data set. Many of these genes were found to be clustered in the diauxic-shift experiment as well. The overlapping set was enriched for genes required for rRNA biosynthesis and included genes encoding RNA helicases, subunits of RNA polymerases I and III, and rRNA processing factors. A subset of the 65 genes was tested for expression by a quantitative-relative reverse transcriptase PCR technique, and they were found to be coregulated after release from alpha factor arrest, heat shock, and tunicamycin treatment. Promoter scanning analysis revealed that the 65 genes within this ribosome and rRNA biosynthesis (RRB) regulon were enriched for two motifs: the 13-base GCGATGAGATGAG and the 11-base TGAAAAATTTT consensus sequences. Both motifs were found to be important for promoting gene expression after release from alpha factor arrest in a test rRNA processing gene (EBP2), which suggests that these consensus sequences may function broadly in the regulation of a set of genes required for ribosome and rRNA biosynthesis.

scholarly journals Transcriptional Repression by the Pho4 Transcription Factor Controls the Timing of SNZ1 Expression

2008 ◽  
Vol 7 (6) ◽  
pp. 949-957 ◽  
Author(s):  
Masafumi Nishizawa ◽  
Tae Komai ◽  
Nobuyuki Morohashi ◽  
Mitsuhiro Shimizu ◽  
Akio Toh-e
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcriptional Repression ◽  
Structural Changes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Nutrient Sensing ◽  
Yeast Cells ◽  
Diauxic Shift

ABSTRACT Nutrient-sensing kinases play important roles for the yeast Saccharomyces cerevisiae to adapt to new nutrient conditions when the nutrient status changes. Our previous global gene expression analysis revealed that the Pho85 kinase, one of the yeast nutrient-sensing kinases, is involved in the changes in gene expression profiles when yeast cells undergo a diauxic shift. We also found that the stationary phase-specific genes SNZ1 and SNO1, whch share a common promoter, are not properly induced when Pho85 is absent. To examine the role of the kinase in SNZ1/SNO1 regulation, we analyzed their expression during the growth of various yeast mutants, including those affecting Pho85 function or lacking the Pho4 transcription factor, an in vivo substrate of Pho85, and tested Pho4 binding by chromatin immunoprecipitation. Pho4 exhibits temporal binding to the SNZ1/SNO1 promoter to down-regulate the promoter activity, and a Δpho4 mutation advances the timing of SNZ1/SNO1 expression. SNZ2, another member of the SNZ/SNO family, is expressed at an earlier growth stage than SNZ1, and Pho4 does not affect this timing, although Pho85 is required for SNZ2 expression. Thus, Pho4 appears to regulate the different timing of the expression of the SNZ/SNO family members. Pho4 binding to the SNZ1/SNO1 promoter is accompanied by alterations in chromatin structure, and Rpd3 histone deacetylase is required for the proper timing of SNZ1/SNO1 expression, while Asf1 histone chaperone is indispensable for their expression. These results imply that Pho4 plays positive and negative roles in transcriptional regulation, with both cases involving structural changes in its target chromatin.

scholarly journals MNBDR: A Module Network Based Method for Drug Repositioning

Genes ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 25
Author(s):  
He-Gang Chen ◽  
Xiong-Hui Zhou
Keyword(s):  
Gene Expression ◽  
Protein Interactions ◽  
Drug Response ◽  
Drug Repositioning ◽  
Expression Profiles ◽  
Drug Repurposing ◽  
Recent Decade ◽  
Data Set ◽  
Module Network ◽  
The Cross

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.

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

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.

scholarly journals Integrative transcriptome data mining for identification of core lncRNAs in breast cancer

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7821 ◽  
Author(s):  
Xiaoming Zhang ◽  
Jing Zhuang ◽  
Lijuan Liu ◽  
Zhengguo He ◽  
Cun Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Prognostic Value ◽  
Early Stage ◽  
Expression Profiles ◽  
Diagnostic Value ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Data Set

Background Cumulative evidence suggests that long non-coding RNAs (lncRNAs) play an important role in tumorigenesis. This study aims to identify lncRNAs that can serve as new biomarkers for breast cancer diagnosis or screening. Methods First, the linear fitting method was used to identify differentially expressed genes from the breast cancer RNA expression profiles in The Cancer Genome Atlas (TCGA). Next, the diagnostic value of all differentially expressed lncRNAs was evaluated using a receiver operating characteristic (ROC) curve. Then, the top ten lncRNAs with the highest diagnostic value were selected as core genes for clinical characteristics and prognosis analysis. Furthermore, core lncRNA-mRNA co-expression networks based on weighted gene co-expression network analysis (WGCNA) were constructed, and functional enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The differential expression level and diagnostic value of core lncRNAs were further evaluated by using independent data set from Gene Expression Omnibus (GEO). Finally, the expression status and prognostic value of core lncRNAs in various tumors were analyzed based on Gene Expression Profiling Interactive Analysis (GEPIA). Results Seven core lncRNAs (LINC00478, PGM5-AS1, AL035610.1, MIR143HG, RP11-175K6.1, AC005550.4, and MIR497HG) have good single-factor diagnostic value for breast cancer. AC093850.2 has a prognostic value for breast cancer. AC005550.4 and MIR497HG can better distinguish breast cancer patients in early-stage from the advanced-stage. Low expression of MAGI2-AS3, LINC00478, AL035610.1, MIR143HG, and MIR145 may be associated with lymph node metastasis in breast cancer. Conclusion Our study provides candidate biomarkers for the diagnosis and prognosis of breast cancer, as well as a bioinformatics basis for the further elucidation of the molecular pathological mechanism of breast cancer.

Induction of yeast histone genes by stimulation of stationary-phase cells

1990 ◽  
Vol 10 (12) ◽  
pp. 6356-6361
Author(s):  
M A Drebot ◽  
L M Veinot-Drebot ◽  
R A Singer ◽  
G C Johnston
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Stationary Phase ◽  
Mitotic Cell ◽  
Specific Gene ◽  
Mitotic Cell Cycle ◽  
Histone Genes ◽  
Yeast Saccharomyces Cerevisiae ◽  
Alpha Factor ◽  
Stimulation Of

In the cell cycle of the budding yeast Saccharomyces cerevisiae, expression of the histone genes H2A and H2B of the TRT1 and TRT2 loci is regulated by the performance of "start," the step that also regulates the cell cycle. Here we show that histone production is also subject to an additional form of regulation that is unrelated to the mitotic cell cycle. Expression of histone genes, as assessed by Northern (RNA) analysis, was shown to increase promptly after the stimulation, brought about by fresh medium, that activates stationary-phase cells to reenter the mitotic cell cycle. The use of a yeast mutant that is conditionally blocked in the resumption of proliferation at a step that is not part of the mitotic cell cycle (M.A. Drebot, G.C. Johnston, and R.A. Singer, Proc. Natl. Acad. Sci. 84:7948, 1987) showed that this increased gene expression that occurs upon stimulation of stationary-phase cells took place in the absence of DNA synthesis and without the performance of start. This stimulation-specific gene expression was blocked by the mating pheromone alpha-factor, indicating that alpha-factor directly inhibits expression of these histone genes, independently of start.

Improved Feature Selection by Incorporating Gene Similarity into the LASSO

2012 ◽  
Vol 3 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Christopher E. Gillies ◽  
Xiaoli Gao ◽  
Nilesh V. Patel ◽  
Mohammad-Reza Siadat ◽  
George D. Wilson
Keyword(s):  
Gene Expression ◽  
Feature Selection ◽  
Personalized Medicine ◽  
Objective Function ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Genetic Profile ◽  
Data Set ◽  
Coordinate Descent Algorithm ◽  
Gene Similarity

Personalized medicine is customizing treatments to a patient’s genetic profile and has the potential to revolutionize medical practice. An important process used in personalized medicine is gene expression profiling. Analyzing gene expression profiles is difficult, because there are usually few patients and thousands of genes, leading to the curse of dimensionality. To combat this problem, researchers suggest using prior knowledge to enhance feature selection for supervised learning algorithms. The authors propose an enhancement to the LASSO, a shrinkage and selection technique that induces parameter sparsity by penalizing a model’s objective function. Their enhancement gives preference to the selection of genes that are involved in similar biological processes. The authors’ modified LASSO selects similar genes by penalizing interaction terms between genes. They devise a coordinate descent algorithm to minimize the corresponding objective function. To evaluate their method, the authors created simulation data where they compared their model to the standard LASSO model and an interaction LASSO model. The authors’ model outperformed both the standard and interaction LASSO models in terms of detecting important genes and gene interactions for a reasonable number of training samples. They also demonstrated the performance of their method on a real gene expression data set from lung cancer cell lines.

scholarly journals Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression

2019 ◽  
Vol 116 (39) ◽  
pp. 19490-19499 ◽  
Author(s):  
Chenglong Xia ◽  
Jean Fan ◽  
George Emanuel ◽  
Junjie Hao ◽  
Xiaowei Zhuang
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Spatial Information ◽  
Detection Efficiency ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Rna Profiling ◽  
Spatially Resolved ◽  
Cycle Dependent

The expression profiles and spatial distributions of RNAs regulate many cellular functions. Image-based transcriptomic approaches provide powerful means to measure both expression and spatial information of RNAs in individual cells within their native environment. Among these approaches, multiplexed error-robust fluorescence in situ hybridization (MERFISH) has achieved spatially resolved RNA quantification at transcriptome scale by massively multiplexing single-molecule FISH measurements. Here, we increased the gene throughput of MERFISH and demonstrated simultaneous measurements of RNA transcripts from ∼10,000 genes in individual cells with ∼80% detection efficiency and ∼4% misidentification rate. We combined MERFISH with cellular structure imaging to determine subcellular compartmentalization of RNAs. We validated this approach by showing enrichment of secretome transcripts at the endoplasmic reticulum, and further revealed enrichment of long noncoding RNAs, RNAs with retained introns, and a subgroup of protein-coding mRNAs in the cell nucleus. Leveraging spatially resolved RNA profiling, we developed an approach to determine RNA velocity in situ using the balance of nuclear versus cytoplasmic RNA counts. We applied this approach to infer pseudotime ordering of cells and identified cells at different cell-cycle states, revealing ∼1,600 genes with putative cell cycle-dependent expression and a gradual transcription profile change as cells progress through cell-cycle stages. Our analysis further revealed cell cycle-dependent and cell cycle-independent spatial heterogeneity of transcriptionally distinct cells. We envision that the ability to perform spatially resolved, genome-wide RNA profiling with high detection efficiency and accuracy by MERFISH could help address a wide array of questions ranging from the regulation of gene expression in cells to the development of cell fate and organization in tissues.

scholarly journals PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kota Fujisawa ◽  
Mamoru Shimo ◽  
Y.-H. Taguchi ◽  
Shinya Ikematsu ◽  
Ryota Miyata
Keyword(s):  
Gene Expression ◽  
Feature Extraction ◽  
Target Genes ◽  
Gene Selection ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Principal Component ◽  
Data Set ◽  
Immune Related Genes ◽  
Unsupervised Feature Extraction

AbstractCoronavirus disease 2019 (COVID-19) is raging worldwide. This potentially fatal infectious disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the complete mechanism of COVID-19 is not well understood. Therefore, we analyzed gene expression profiles of COVID-19 patients to identify disease-related genes through an innovative machine learning method that enables a data-driven strategy for gene selection from a data set with a small number of samples and many candidates. Principal-component-analysis-based unsupervised feature extraction (PCAUFE) was applied to the RNA expression profiles of 16 COVID-19 patients and 18 healthy control subjects. The results identified 123 genes as critical for COVID-19 progression from 60,683 candidate probes, including immune-related genes. The 123 genes were enriched in binding sites for transcription factors NFKB1 and RELA, which are involved in various biological phenomena such as immune response and cell survival: the primary mediator of canonical nuclear factor-kappa B (NF-κB) activity is the heterodimer RelA-p50. The genes were also enriched in histone modification H3K36me3, and they largely overlapped the target genes of NFKB1 and RELA. We found that the overlapping genes were downregulated in COVID-19 patients. These results suggest that canonical NF-κB activity was suppressed by H3K36me3 in COVID-19 patient blood.

scholarly journals The effects of a globin blocker on the resolution of 3’mRNA sequencing data in porcine blood

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Kyu-Sang Lim ◽  
Qian Dong ◽  
Pamela Moll ◽  
Jana Vitkovska ◽  
Gregor Wiktorin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Data Sets ◽  
Globin Genes ◽  
Sequencing Data ◽  
Globin Mrna ◽  
Data Set ◽  
Mrna Sequencing ◽  
Porcine Blood

Abstract Background Gene expression profiling in blood is a potential source of biomarkers to evaluate or predict phenotypic differences between pigs but is expensive and inefficient because of the high abundance of globin mRNA in porcine blood. These limitations can be overcome by the use of QuantSeq 3’mRNA sequencing (QuantSeq) combined with a method to deplete or block the processing of globin mRNA prior to or during library construction. Here, we validated the effectiveness of QuantSeq using a novel specific globin blocker (GB) that is included in the library preparation step of QuantSeq. Results In data set 1, four concentrations of the GB were applied to RNA samples from two pigs. The GB significantly reduced the proportion of globin reads compared to non-GB (NGB) samples (P = 0.005) and increased the number of detectable non-globin genes. The highest evaluated concentration (C1) of the GB resulted in the largest reduction of globin reads compared to the NGB (from 56.4 to 10.1%). The second highest concentration C2, which showed very similar globin depletion rates (12%) as C1 but a better correlation of the expression of non-globin genes between NGB and GB (r = 0.98), allowed the expression of an additional 1295 non-globin genes to be detected, although 40 genes that were detected in the NGB sample (at a low level) were not present in the GB library. Concentration C2 was applied in the rest of the study. In data set 2, the distribution of the percentage of globin reads for NGB (n = 184) and GB (n = 189) samples clearly showed the effects of the GB on reducing globin reads, in particular for HBB, similar to results from data set 1. Data set 3 (n = 84) revealed that the proportion of globin reads that remained in GB samples was significantly and positively correlated with the reticulocyte count in the original blood sample (P < 0.001). Conclusions The effect of the GB on reducing the proportion of globin reads in porcine blood QuantSeq was demonstrated in three data sets. In addition to increasing the efficiency of sequencing non-globin mRNA, the GB for QuantSeq has an advantage that it does not require an additional step prior to or during library creation. Therefore, the GB is a useful tool in the quantification of whole gene expression profiles in porcine blood.

345 GENE EXPRESSION IN OOCYTES AFTER MEIOTIC INHIBITION WITH THE CYCLIN-DEPENDENT KINASE INHIBITOR BUTYROLACTONE I

2010 ◽  
Vol 22 (1) ◽  
pp. 329
Author(s):  
C. L. V. Leal ◽  
S. Mamo ◽  
T. Fair ◽  
P. Lonergan
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Relative Abundance ◽  
Kinase Inhibitor ◽  
Expression Profiles ◽  
Cyclin Dependent Kinase ◽  
Oocyte Competence ◽  
Cyclin Dependent Kinase Inhibitor ◽  
Bovine Oocytes

Once removed from the follicle, mammalian oocytes resume meiosis spontaneously and progress through breakdown of the germinal vesicle to the matured state at metaphase II. The ability to reversibly inhibit such meiotic resumption has been reported and is a potentially useful method for studying developmental competence acquisition in oocytes as well as in some cases allowing flexibility in an IVF system where oocytes are collected from distant locations or on different days. The aim of the present study was to determine the effect of temporary inhibition of meiotic resumption using the cyclin-dependent kinase inhibitor butyrolactone I (BLI) on gene expression in bovine oocytes. Immature bovine oocytes were recovered from the ovaries of slaughtered heifers at a commercial abattoir and assigned to 1 of 4 groups: (1) Control: immature oocytes were collected either immediately or (2) after IVM for 24 h in TCM-199 containing 10 ng mL-1 EGF and 10% (v/v) FCS, (3) Inhibited oocytes collected either 24 h after incubation in the presence of 100 μM BLI in TCM-199 with 3 mg mL-1 BSA or (4) after meiotic inhibition for 24 h followed by in vitro maturation. All cultures were carried out at 38.5°C under 5% CO2 in air and maximum humidity. For mRNA relative abundance analysis, cumulus cells were removed and pools of 10 denuded oocytes were snap frozen in liquid nitrogen and stored at -80°C until use. A total of 42 transcripts, previously reported to be related to cell cycle regulation and/or oocyte competence were evaluated by quantitative real time PCR. Differences in relative abundance were analyzed by ANOVA and Student’s t-test. The majority of transcripts were downregulated (P < 0.05) after IVM in control oocytes (23 out of 42) and the same pattern was observed in inhibited oocytes that were allowed to mature. Twelve transcripts remained stable (P > 0.05) after IVM in control oocytes; of these, only two (PTTG1 and INHBA) did not show the same pattern in inhibited and matured oocytes. Few genes (7) were upregulated after IVM in control oocytes (P < 0.05) and of these, three (PLAT1, RBP1, and INHBB) were not upregulated in inhibited oocytes after IVM. Inhibited oocytes showed similar levels of expression (P > 0.05) as immature control oocytes, except for two genes (LUM and INHBB), which were increased in these oocytes (P < 0.05). The expression profiles of cell cycle genes were mostly unaffected by the BLI treatment. The few genes affected were previously reported as competence-related and could be useful markers of oocyte competence following pretreatment. In conclusion, the changes occurring in transcript abundance during oocyte maturation in vitro were to a large extent mirrored following inhibition of meiotic resumption prior to IVM and subsequent release from inhibition and maturation. CLV Leal was supported by CNPq, Brazil (PDE 201487/2007-1); Supported by Science Foundation Ireland (07/SRC/B1156).

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