scholarly journals Transcriptome analyses identify five transcription factors differentially expressed in the hypothalamus of post- versus prepubertal Brahman heifers1

2016 ◽  
Vol 94 (9) ◽  
pp. 3693-3702 ◽  
Author(s):  
M. R. S. Fortes ◽  
L. T. Nguyen ◽  
M. M. D. C. A. Weller ◽  
A. Cánovas ◽  
A. Islas-Trejo ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Differentially Expressed ◽  
Transcriptome Analyses

Reproductive performance and transcriptome analyses of Tetranychus urticae when feeding on bean leaves and an artificial diet

2019 ◽  
Vol 24 (7) ◽  
pp. 1272-1283
Author(s):  
Yongjuan He ◽  
Jiale Lv ◽  
Endong Wang ◽  
Xuenong Xu
Keyword(s):  
Tetranychus Urticae ◽  
Artificial Diet ◽  
Mass Rearing ◽  
Differentially Expressed ◽  
Detoxification Enzymes ◽  
Adult Longevity ◽  
Natural Food ◽  
Leaf Extracts ◽  
Transcriptome Analyses ◽  
Bean Leaves

As an important pest, Tetranychus urticae fed on thousands of host plants and showed strong capability in host adaptation. However, hardly any success artificial diet has been developed for it. In this study, we compared adult longevity and reproduction of T. urticae that fed on its natural food (bean leaves) and an artificial diet with leaf extracts added, and tried to investigate the reason why the artificial diet was inefficient through transcriptome analyses. Mean adult longevity and cumulative fecundities of T. urticae was reduced by 53.4% and 93.8%, respectively. Transcriptome analyses showed that 1731 genes were differentially expressed comparing individuals fed with the artificial diet and with their natural food, among which most (77.1%) were down regulated. No significant induced expression of xenobiotic transporters and detoxification enzymes were observed when T. urticae were fed with the artificial diet. In contrast, differentially expressed genes were mainly enriched in digestive related terms, especially in lipid metabolism related pathways, with most genes down regulated. Our results indicated the significance in further investigating lipid demand and metabolism of T. urticae to improve its mass rearing techniques.

scholarly journals Transcriptome analyses and virus induced gene silencing identify genes in the Rpp4-mediated Asian soybean rust resistance pathway

2013 ◽  
Vol 40 (10) ◽  
pp. 1029 ◽  
Author(s):  
Aguida M. A. P. Morales ◽  
Jamie A. O'Rourke ◽  
Martijn van de Mortel ◽  
Katherine T. Scheider ◽  
Timothy J. Bancroft ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Silencing ◽  
Differentially Expressed ◽  
Soybean Rust ◽  
Phakopsora Pachyrhizi ◽  
R Gene ◽  
Virus Induced Gene Silencing ◽  
Asian Soybean Rust ◽  
Defence Responses

Rpp4 (Resistance to Phakopsora pachyrhizi 4) confers resistance to Phakopsora pachyrhizi Sydow, the causal agent of Asian soybean rust (ASR). By combining expression profiling and virus induced gene silencing (VIGS), we are developing a genetic framework for Rpp4-mediated resistance. We measured gene expression in mock-inoculated and P. pachyrhizi-infected leaves of resistant soybean accession PI459025B (Rpp4) and the susceptible cultivar (Williams 82) across a 12-day time course. Unexpectedly, two biphasic responses were identified. In the incompatible reaction, genes induced at 12 h after infection (hai) were not differentially expressed at 24 hai, but were induced at 72 hai. In contrast, genes repressed at 12 hai were not differentially expressed from 24 to 144 hai, but were repressed 216 hai and later. To differentiate between basal and resistance-gene (R-gene) mediated defence responses, we compared gene expression in Rpp4-silenced and empty vector-treated PI459025B plants 14 days after infection (dai) with P. pachyrhizi. This identified genes, including transcription factors, whose differential expression is dependent upon Rpp4. To identify differentially expressed genes conserved across multiple P. pachyrhizi resistance pathways, Rpp4 expression datasets were compared with microarray data previously generated for Rpp2 and Rpp3-mediated defence responses. Fourteen transcription factors common to all resistant and susceptible responses were identified, as well as fourteen transcription factors unique to R-gene-mediated resistance responses. These genes are targets for future P. pachyrhizi resistance research.

scholarly journals Genes Encoding Transcription Factors TaDREB5 and TaNFYC-A7 Are Differentially Expressed in Leaves of Bread Wheat in Response to Drought, Dehydration and ABA

2018 ◽  
Vol 9 ◽  
Author(s):  
Lyudmila Zotova ◽  
Akhylbek Kurishbayev ◽  
Satyvaldy Jatayev ◽  
Gulmira Khassanova ◽  
Askar Zhubatkanov ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Bread Wheat ◽  
Differentially Expressed ◽  
Genes Encoding

scholarly journals Potential Prognostic Immune Biomarkers of Overall Survival in Ovarian Cancer Through Comprehensive Bioinformatics Analysis: A Novel Artificial Intelligence Survival Prediction System

2021 ◽  
Vol 8 ◽  
Author(s):  
Tingshan He ◽  
Liwen Huang ◽  
Jing Li ◽  
Peng Wang ◽  
Zhiqiao Zhang
Keyword(s):  
Artificial Intelligence ◽  
Ovarian Cancer ◽  
Overall Survival ◽  
Transcription Factors ◽  
Cancer Patients ◽  
Prognostic Model ◽  
Cox Regression ◽  
Differentially Expressed ◽  
Immune Genes ◽  
Immune Biomarkers

Background: The tumour immune microenvironment plays an important role in the biological mechanisms of tumorigenesis and progression. Artificial intelligence medicine studies based on big data and advanced algorithms are helpful for improving the accuracy of prediction models of tumour prognosis. The current research aims to explore potential prognostic immune biomarkers and develop a predictive model for the overall survival of ovarian cancer (OC) based on artificial intelligence algorithms.Methods: Differential expression analyses were performed between normal tissues and tumour tissues. Potential prognostic biomarkers were identified using univariate Cox regression. An immune regulatory network was constructed of prognostic immune genes and their highly related transcription factors. Multivariate Cox regression was used to identify potential independent prognostic immune factors and develop a prognostic model for ovarian cancer patients. Three artificial intelligence algorithms, random survival forest, multitask logistic regression, and Cox survival regression, were used to develop a novel artificial intelligence survival prediction system.Results: The current study identified 1,307 differentially expressed genes and 337 differentially expressed immune genes between tumour samples and normal samples. Further univariate Cox regression identified 84 prognostic immune gene biomarkers for ovarian cancer patients in the model dataset (GSE32062 dataset and GSE53963 dataset). An immune regulatory network was constructed involving 63 immune genes and 5 transcription factors. Fourteen immune genes (PSMB9, FOXJ1, IFT57, MAL, ANXA4, CTSH, SCRN1, MIF, LTBR, CTSD, KIFAP3, PSMB8, HSPA5, and LTN1) were recognised as independent risk factors by multivariate Cox analyses. Kaplan-Meier survival curves showed that these 14 prognostic immune genes were closely related to the prognosis of ovarian cancer patients. A prognostic nomogram was developed by using these 14 prognostic immune genes. The concordance indexes were 0.760, 0.733, and 0.765 for 1-, 3-, and 5-year overall survival, respectively. This prognostic model could differentiate high-risk patients with poor overall survival from low-risk patients. According to three artificial intelligence algorithms, the current study developed an artificial intelligence survival predictive system that could provide three individual mortality risk curves for ovarian cancer.Conclusion: In conclusion, the current study identified 1,307 differentially expressed genes and 337 differentially expressed immune genes in ovarian cancer patients. Multivariate Cox analyses identified fourteen prognostic immune biomarkers for ovarian cancer. The current study constructed an immune regulatory network involving 63 immune genes and 5 transcription factors, revealing potential regulatory associations among immune genes and transcription factors. The current study developed a prognostic model to predict the prognosis of ovarian cancer patients. The current study further developed two artificial intelligence predictive tools for ovarian cancer, which are available at https://zhangzhiqiao8.shinyapps.io/Smart_Cancer_Survival_Predictive_System_17_OC_F1001/ and https://zhangzhiqiao8.shinyapps.io/Gene_Survival_Subgroup_Analysis_17_OC_F1001/. An artificial intelligence survival predictive system could help improve individualised treatment decision-making.

scholarly journals A Comparison of Gene Expression Changes in the Blood of Individuals Consuming Diets Supplemented with Olives, Nuts or Long-Chain Omega-3 Fatty Acids

Nutrients ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3765
Author(s):  
Virginie Bottero ◽  
Judith A. Potashkin
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Fatty Acids ◽  
Transcription Factors ◽  
Mediterranean Diet ◽  
Differentially Expressed ◽  
Omega 3 Fatty Acids ◽  
Omega 3 ◽  
The Mediterranean ◽  
Long Chain

Background: The Mediterranean diet, which is rich in olive oil, nuts, and fish, is considered healthy and may reduce the risk of chronic diseases. Methods: Here, we compared the transcriptome from the blood of subjects with diets supplemented with olives, nuts, or long-chain omega-3 fatty acids and identified the genes differentially expressed. The dietary genes obtained were subjected to network analysis to determine the main pathways, as well as the transcription factors and microRNA interaction networks to elucidate their regulation. Finally, a gene-associated disease interaction network was performed. Results: We identified several genes whose expression is altered after the intake of components of the Mediterranean diets compared to controls. These genes were associated with infection and inflammation. Transcription factors and miRNAs were identified as potential regulators of the dietary genes. Interestingly, caspase 1 and sialophorin are differentially expressed in the opposite direction after the intake of supplements compared to Alzheimer’s disease patients. In addition, ten transcription factors were identified that regulated gene expression in supplemented diets, mild cognitive impairment, and Alzheimer’s disease. Conclusions: We identified genes whose expression is altered after the intake of the supplements as well as the transcription factors and miRNAs involved in their regulation. These genes are associated with schizophrenia, neoplasms, and rheumatic arthritis, suggesting that the Mediterranean diet may be beneficial in reducing these diseases. In addition, the results suggest that the Mediterranean diet may also be beneficial in reducing the risk of dementia.

scholarly journals Comprehensive Transcriptome Analysis Revealed the Effects of the Light Quality, Light Intensity, and Photoperiod on Phlorizin Accumulation in Lithocarpus polystachyus Rehd.

Forests ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 995 ◽  
Author(s):  
Yantong Zhang ◽  
Limei Lin ◽  
Yuehong Long ◽  
Hongyu Guo ◽  
Zhuo Wang ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Light Intensity ◽  
Light Exposure ◽  
Southern China ◽  
Green Light ◽  
Differentially Expressed ◽  
Chromatography Method ◽  
Pal Activity ◽  
Study Results ◽  
Regulatory Effects

Lithocarpus polystachyus Rehd. is an important medicinal plant species grown in southern China, with phlorizin as its main active substance. The effects of light conditions on phlorizin biosynthesis in L. polystachyus remain unclear. Thus, we analyzed the transcriptomes of L. polystachyus plants cultivated under diverse light qualities, light intensities, and photoperiods. The light treatments resulted in 5977–8027 differentially expressed genes (DEGs), which were functionally annotated based on the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Genes encoding transcription factors from 89 families were differentially expressed after the light treatments, implying these transcription factors are photoresponsive. Phenylalanine ammonia lyase (PAL) and 4-coumarate-CoA ligase (4CL) are the key enzymes for the accumulation of phlorizin. The transcription levels of PAL2, PAL, 4CL1 (DN121614), 4CLL7, and 4CL1 (DN102161) were positively correlated with phlorizin accumulation, suggesting that these genes are important for phlorizin biosynthesis. An ultra-high-performance liquid chromatography method was used to quantify the phlorizin content. Phlorizin accumulated in response to the green light treatment and following appropriate decreases in the light intensity or appropriate increases in the duration of the light exposure. The green light, 2000 lx, and 3000 lx treatments increased the PAL activity of L. polystachyus, but the regulatory effects of the light intensity treatments on PAL activity were relatively weak. This study represents the first comprehensive analysis of the light-induced transcriptome of L. polystachyus. The study results may form the basis of future studies aimed at elucidating the molecular mechanism underlying phlorizin biosynthesis in L. polystachyus. Moreover, this study may be relevant for clarifying the regulatory effects of light on the abundance of bioactive components in medicinal plants.

Role of strain differences on host resistance and the transcriptional response of macrophages to infection withYersinia enterocolitica

2006 ◽  
Vol 25 (1) ◽  
pp. 75-84 ◽  
Author(s):  
Katrin van Erp ◽  
Kristina Dach ◽  
Isabel Koch ◽  
Jürgen Heesemann ◽  
Reinhard Hoffmann
Keyword(s):  
Transcription Factors ◽  
Host Resistance ◽  
Genetic Background ◽  
Antibacterial Properties ◽  
Differentially Expressed ◽  
Transcriptional Responses ◽  
Yersinia Infection ◽  
Ifn Γ ◽  
The Impact

The outcome of a host-pathogen encounter is determined by virulence factors of the pathogen and defense factors of the host. We characterized the impact of host factors [resistant (C57BL/6) or susceptible (BALB/c) genetic background and exposure to interferon (IFN)-γ] on transcriptional responses of bone marrow-derived macrophages (BMDM) to infection with Yersinia enterocolitica. IFN-γ treatment more profoundly altered the transcriptome of BMDM than did bacterial infection or genetic background. In BALB/c BMDM, 1,161 genes were differentially expressed in response to Yersinia infection with or without IFN-γ prestimulation. Fourteen genes (1.2%) could only be induced by BALB/c BMDM in response to Yersinia infection after IFN-γ pretreatment. These genes inhibit apoptosis, activate NF-κB and Erk signaling, are chemotactic to neutrophils, and are involved in cytoskeletal reorganization, hence possibly in phagocytosis. Ten of these genes possess a common module of binding sites for Hox, Pou, and Creb transcription factors in 2 kb of upstream genomic sequence, suggesting a possible novel role of these transcription factors in regulation of immune responses. Fifty-two of one thousand fifty differentially expressed genes (4.9%) were induced more strongly by C57BL/6 BMDM in response to Yersinia infection than BALB/c BMDM. These genes activate NK cells, have antibacterial properties, or are involved in sensing chemokines and lipopolysaccharide (LPS). These data show that host resistance factors modulate a surprisingly small, but identifiable and functionally significant, portion of the macrophage transcriptome in response to Yersinia infection.

scholarly journals E2F transcription factors are differentially expressed in murine gametes and early embryos

2000 ◽  
Vol 97 (1-2) ◽  
pp. 211-215 ◽  
Author(s):  
Antonella Palena ◽  
Rosamaria Mangiacasale ◽  
Anna Rosa Magnano ◽  
Laura Barberi ◽  
Roberto Giordano ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Differentially Expressed ◽  
Early Embryos ◽  
E2f Transcription Factors

scholarly journals Combined Analysis of the Metabolome and Transcriptome Identified Candidate Genes Involved in Phenolic Acid Biosynthesis in the Leaves of Cyclocarya paliurus

2020 ◽  
Vol 21 (4) ◽  
pp. 1337 ◽  
Author(s):  
Weida Lin ◽  
Yueling Li ◽  
Qiuwei Lu ◽  
Hongfei Lu ◽  
Junmin Li
Keyword(s):  
Transcription Factors ◽  
Candidate Genes ◽  
Phenolic Acid ◽  
Developmental Stages ◽  
Ultra Performance Liquid Chromatography ◽  
Differentially Expressed ◽  
Regulation Mechanism ◽  
Acid Biosynthesis ◽  
Cyclocarya Paliurus ◽  
Helix Loop Helix

To assess changes of metabolite content and regulation mechanism of the phenolic acid biosynthesis pathway at different developmental stages of leaves, this study performed a combined metabolome and transcriptome analysis of Cyclocarya paliurus leaves at different developmental stages. Metabolite and transcript profiling were conducted by ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometer and high-throughput RNA sequencing, respectively. Transcriptome identification showed that 58 genes were involved in the biosynthesis of phenolic acid. Among them, 10 differentially expressed genes were detected between every two developmental stages. Identification and quantification of metabolites indicated that 14 metabolites were located in the phenolic acid biosynthetic pathway. Among them, eight differentially accumulated metabolites were detected between every two developmental stages. Association analysis between metabolome and transcriptome showed that six differentially expressed structural genes were significantly positively correlated with metabolite accumulation and showed similar expression trends. A total of 128 transcription factors were identified that may be involved in the regulation of phenolic acid biosynthesis; these include 12 MYBs and 10 basic helix–loop–helix (bHLH) transcription factors. A regulatory network of the phenolic acid biosynthesis was established to visualize differentially expressed candidate genes that are involved in the accumulation of metabolites with significant differences. The results of this study contribute to the further understanding of phenolic acid biosynthesis during the development of leaves of C. paliurus.

scholarly journals Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Xinhong Liu ◽  
Feng Chen ◽  
Fang Tan ◽  
Fang Li ◽  
Ruokun Yi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcription Factors ◽  
Target Genes ◽  
Differential Expression Analysis ◽  
Mirna Gene ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Epithelial Tissue ◽  
Hub Genes ◽  
Geo Database

Background. Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive breast cancer-miRNA-gene interaction map. Methods. Three miRNA microarray datasets (GSE26659, GSE45666, and GSE58210) were obtained from the GEO database. Then, the R software “LIMMA” package was used to identify differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The BRCA GE-mRNA datasets (GSE109169 and GSE139038) were downloaded from the GEO database for identifying differentially expressed genes (DE-genes). Next, GO annotation and KEGG pathway enrichment analysis were conducted. A PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes were further evaluated. Results. We found 6 upregulated differentially expressed- (DE-) miRNAs and 18 downregulated DE-miRNAs by analyzing 3 Gene Expression Omnibus databases, and we predicted the upstream transcription factors and downstream target genes for these DE-miRNAs. Then, we used the GEO database to perform differential analysis on breast cancer mRNA and obtained differentially expressed mRNA. We found 10 hub genes of upregulated DE-miRNAs and 10 hub genes of downregulated DE-miRNAs through interaction analysis. Conclusions. In this study, we have performed an integrated bioinformatics analysis to construct a more comprehensive BRCA-miRNA-gene network and provide new targets and research directions for the treatment and prognosis of BRCA.

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