scholarly journals Global Analysis of Gene Expression Profiles in Glutinous Rice 89-1 (Oryza sativa L.) Seedlings Exposed to Chilling Stress

2021 ◽  
Author(s):  
Xiaoxue Pan ◽  
Hong Wu ◽  
Mingyu Hu ◽  
Zhongwei Wang ◽  
Xiaoying Jiang ◽  
...  
Keyword(s):  
Cell Wall ◽  
Oryza Sativa ◽  
Differentially Expressed Genes ◽  
Oryza Sativa L ◽  
Expression Profiles ◽  
Global Analysis ◽  
Chilling Stress ◽  
Cold Treatment ◽  
Differentially Expressed ◽  
Glutinous Rice

AbstractRice (Oryza sativa) is a tropical cereal crop that is severely affected by chilling stress at the seedling stage, although glutinous rice 89-1 (Gr89-1) in Chongqing, China, shows tolerance to low temperatures and overwintering ability. However, little research has been conducted on the mechanisms regulating chilling stress in Gr89-1. In this study, a comprehensive of transcriptional profiles of Gr89-1 seedlings at the three-leaf stage was conducted after a 4 °C treatment for 2, 6, 12, 24, or 48 h. Overall, 2993 differentially expressed genes were detected in Gr89-1 seedlings upon cold exposure. Gene Ontology testing and pathway analysis revealed differentially expressed genes involved in transcriptional regulation, carbohydrate metabolism, plant hormone signal, and cell wall composition. A total of 243 transcription factors were differentially expressed during the cold treatment; in particular, the AP2/EREBP, bHLH, NAC, WRKY, C2H2, and TIFY families were generally upregulated after cold treatment, whereas the mTERF and GNAT families were downregulated. Chilling stress changed the starch and sucrose metabolism, coupled with the accumulation of sucrose and trehalose level, and increases in jasmonic acid level in Gr89-1 seedlings. Furthermore, a number of the cell wall-related genes identified in the present study were also differentially expressed during the cold treatment. The genes and pathways identified in the current study increase our understanding of the mechanisms underlying cold resistance in rice seedlings.

scholarly journals Global analysis of differentially expressed genes between two Japonica rice varieties induced by low temperature during the booting stage by RNA-Seq

2020 ◽  
Vol 7 (6) ◽  
pp. 192243
Author(s):  
Zhenhua Guo ◽  
Lijun Cai ◽  
Chuanxue Liu ◽  
Cuihong Huang ◽  
Zhiqiang Chen ◽  
...  
Keyword(s):  
Low Temperature ◽  
Differentially Expressed Genes ◽  
Chilling Stress ◽  
Cold Treatment ◽  
Chilling Tolerance ◽  
Differentially Expressed ◽  
Antioxidant Enzyme Activities ◽  
Japonica Rice ◽  
Rice Varieties ◽  
Booting Stage

As one of the abiotic stresses, low temperature severely threatens rice production during its entire growth period, especially during the booting stage. In the present study, transcriptome analysis was performed comparing Longjing (LJ) 25 (chilling-tolerant) and LJ 11 (chilling-sensitive) rice varieties to identify genes associated with chilling tolerance in rice spikelets. A total of 23 845 expressed genes and 13 205 differentially expressed genes (DEGs) were identified, respectively. Gene ontology (GO) enrichment analyses revealed ‘response to cold’ (containing 180 DEGs) as the only category enriched in both varieties during the entire cold treatment period. Through M ap M an analysis, we identified nine and six DEGs related to the Calvin cycle and antioxidant enzymes, respectively, including OsRBCS3 , OsRBCS2 , OsRBCS4 , OsAPX2 and OsCATC , that under chilling stress were markedly downregulated in LJ11 compared with LJ25. Furthermore, we predicted their protein–protein interaction (PPI) network and identified nine hub genes (the threshold of co-expressed gene number ≥ 11) in Cytoscape, including three RuBisCO-related genes with 14 co-expressed genes. Under chilling stress, antioxidant enzyme activities (peroxidase (POD) and catalase (CAT)) were downregulated in LJ11 compared with LJ25. However, the content of malondialdehyde (MDA) was higher in LJ11 compared with LJ25. Collectively, our findings identify low temperature responsive genes that can be effectively used as candidate genes for molecular breeding programmes to increase the chilling tolerance of rice.

scholarly journals Identification of GCC-box and TCC-box motifs in the promoters of differentially expressed genes in rice (Oryza sativa L.): Experimental and computational approaches

PLoS ONE ◽  
2019 ◽  
Vol 14 (4) ◽  
pp. e0214964
Author(s):  
Gopal Kumar Prajapati ◽  
Bharati Pandey ◽  
Awdhesh Kumar Mishra ◽  
Kwang-Hyun Baek ◽  
Dev Mani Pandey
Keyword(s):  
Oryza Sativa ◽  
Differentially Expressed Genes ◽  
Oryza Sativa L ◽  
Differentially Expressed ◽  
Computational Approaches ◽  
Gcc Box

Identification of differentially expressed genes under heat stress conditions in rice (Oryza sativa L.)

2020 ◽  
Vol 47 (3) ◽  
pp. 1935-1948 ◽  
Author(s):  
Mustaq Mohammed S. Wahab ◽  
Srividhya Akkareddy ◽  
P. Shanthi ◽  
P. Latha
Keyword(s):  
Oryza Sativa ◽  
Heat Stress ◽  
Differentially Expressed Genes ◽  
Oryza Sativa L ◽  
Stress Conditions ◽  
Differentially Expressed

Microarray analysis of different expression profiles between wild-type and transgenic rice seedlings overexpression OsDREB1BI gene

Biologia ◽  
2015 ◽  
Vol 70 (6) ◽  
Author(s):  
Jing Zhuang ◽  
Feng Wang ◽  
Zhi-Sheng Xu ◽  
Ai-Sheng Xiong
Keyword(s):  
Differentially Expressed Genes ◽  
Transgenic Rice ◽  
Rice Plant ◽  
Oryza Sativa L ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Wild Type ◽  
Japonica Variety ◽  
Gene Encoding ◽  
Abiotic Tolerance

AbstractOverexpressed genes encoding the transcription factors of DREB/CBF can improve abiotic tolerance in transgenic plants. However, the mechanism of plant abiotic tolerance at the molecular level has not been clearly elucidated. In this study, the OsDREB1BI gene was introduced to Zhonghua 11, an Oryza sativa L. japonica variety. The rice plant hosting the OsDREB1BI gene showed an improved tolerance to low temperatures compared with wild-type plants. A total of 404 differentially expressed genes were detected in transgenic and wild-type rice plants by using the Affymetrix microarray system. Results showed that 180 or 224 genes were induced or suppressed, respectively. The functional classification of these differentially expressed genes indicated that such genes are involved in various metabolic pathways, including coding for stress-response-related proteins. The number of up-regulated genes (56) was greater than that of the down-regulated genes (24). Proteins with an unknown function constituted the highest proportion. The gene encoding an AP2 domaincontaining protein RAP2.8 was down-regulated in the transgenic rice plant. Many “hot” sites, where some up-regulated or down-regulated genes were clustered, were found in rice chromosomes.

scholarly journals HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Differentially Expressed Genes ◽  
Cd4 T Cells ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Infected Cells ◽  
Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

scholarly journals Expression profiles of differentially expressed genes affecting fecundity in goat ovarian tissues

2015 ◽  
Vol 14 (4) ◽  
pp. 18743-18752 ◽  
Author(s):  
Y.H. Ling ◽  
Q. Quan ◽  
H. Xiang ◽  
L. Zhu ◽  
M.X. Chu ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Differentially Expressed

scholarly journals Genomic Expression Profiling of Colorectal Cancer in Silico

2021 ◽  
Author(s):  
Feifei Liu ◽  
Yu Wang ◽  
Wenxue Li ◽  
Diancheng Li ◽  
Yuwei Xin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Survival Analysis ◽  
Mrna Expression ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Analysis Tool ◽  
Hub Genes ◽  
Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

scholarly journals Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

2021 ◽  
Author(s):  
Li Guoquan ◽  
Du Junwei ◽  
He Qi ◽  
Fu Xinghao ◽  
Ji Feihong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Treatment Options ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Chronic Lymphocytic Thyroiditis ◽  
Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

scholarly journals Insight into Molecular Profile Changes after Skeletal Muscle Contusion Using Microarray and Bioinformatics Analyses

2020 ◽  
Author(s):  
Na Li ◽  
Ru-feng Bai ◽  
Chun Li ◽  
Li-hong Dang ◽  
Qiu-xiang Du ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Healing Process ◽  
Differentially Expressed ◽  
Molecular Profile ◽  
Wound Age ◽  
Functional Modules

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

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