scholarly journals Screening and functional analysis of differentially expressed genes in an animal model ofEBV-associated lymphomas

2019 ◽  
Author(s):  
Yang Zhang ◽  
Chengkun Wang ◽  
Liangzhuan Liu ◽  
Qiu Peng ◽  
Xiaoning Gan ◽  
...  
Keyword(s):  
Malignant Transformation ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Human Lymphocytes ◽  
Ring Finger ◽  
Tumor Formation ◽  
Scid Mice ◽  
Differentially Expressed ◽  
Normal Human

AbstractEpstein-Barr virus(EBV) is an important human oncogenic virus. This paper is to explore how EBV induce malignant transformation of human lymphocytes and the related mechanism of lymphomagenesis. We have constructedhu-PBL/SCID chimeric miceand established a model of EBV-associated human-derived lymphomas. By using Agilent human whole genome microarray and a series of bioinformatic analyses, a total of 202 differentially expressed genes were screened from the EBV-induced lymphomas inhu-PBL/SCID mice, including 44 up-regulated and 158 down-regulated genes. Calculation of the rank score (RS) values of these genes in the HIPPIE protein interaction networks showed that topoisomerase II alpha (TOP2A), ubiquitin like with PHD and ring finger domains 1 (UHRF1), histone cluster 2 H2B family member E (HIST2H2BE), phosphoglycerate dehydrogenase (PHGDH), vinculin (VCL), insulin-like growth factor 1 receptor (IGF1R), Fos proto-oncogene (FOS), snail family transcriptional repressor 1 (SNAI1), PDZ binding kinase (PBK), and ring finger protein 144B (RNF144B) were the top 10 key node genes of EBV-induced lymphoma. In which, PBK, an up-regulated genes with the highest number of GO annotations, was verified by cellular function experiments and clinical lymphoma samples.Author summaryEB virus is closely associated with human lymphoma and nasopharyngeal carcinoma. Since the susceptible hosts of EBV limit to human and cottontop tammarins, there are no appropriate animal models so far to study the EBV-associated oncogenesis. In our previous experiments, the EBV-associated lymphomas were induced inhu-PBL/SCID chimera(a new humanized mouse model). However, the cellular and molecular mechanisms of malignant transformation of normal human cells and tumor formation induced by EBV remain unclear. In this study, we examined and compared the gene expression profiles of EBV-induced lymphomas and normal human lymphocytes of the same origin in SCID mice. By constructing the gene-function relationship network, we preliminarily found that TOP2A, UHRF1, HIST2H2BE, PHGDH, VCL, IGF1R, FOS, SNAI1, PBK, and RNF144B may be the key genes in EBV-induced lymphomas. These findings suggest that the induction of lymphoma by EBV is a complex process that involves multiple genes and pathways.

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.

A Comprehensive Data Analysis of Differentially Regulated Genes in Melanoma

2020 ◽  
Author(s):  
Yanjie Han ◽  
Xinxin Li ◽  
Jiliang Yan ◽  
Chunyan Ma ◽  
Xin Wang ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Growth Factor Receptor ◽  
Principal Component ◽  
Distant Metastases ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Ppi Networks

Abstract Background: Melanoma is the most deadly tumor in skin tumors and is prone to distant metastases. The incidence of melanoma has increased rapidly in the past few decades, and current trends indicate that this growth is continuing. This study was aimed to explore the molecular mechanisms of melanoma pathogenesis and discover underlying pathways and genes associated with melanoma.Methods: We used high-throughput expression data to study differential expression profiles of related genes in melanoma. The differentially expressed genes (DEGs) of melanoma in GSE15605, GSE46517, GSE7553 and the Cancer Genome Atlas (TCGA) datasets were analyzed. Differentially expressed genes (DEGs) were identified by paired t-test. Then the DEGs were performed cluster and principal component analyses and protein–protein interaction (PPI) network construction. After that, we analyzed the differential genes through bioinformatics and got hub genes. Finally, the expression of hub genes was confirmed in the TCGA databases and collected patient tissue samples.Results: Total 144 up-regulated DEGs and 16 down-regulated DEGs were identified. A total of 17 gene ontology analysis (GO) terms and 11 pathways were closely related to melanoma. Pathway of pathways in cancer was enriched in 8 DEGs, such as junction plakoglobin (JUP) and epidermal growth factor receptor (EGFR). In the PPI networks, 9 hub genes were obtained, such as loricrin (LOR), filaggrin (FLG), keratin 5 (KRT5), corneodesmosin (CDSN), desmoglein 1 (DSG1), desmoglein 3 (DSG3), keratin 1 (KRT1), involucrin (IVL) and EGFR. The pathway of pathways in cancer and its enriched DEGs may play important roles in the process of melanoma. The hub genes of DEGs may become promising melanoma candidate genes. Five key genes FLG, DSG1, DSG3, IVL and EGFR were identified in the TCGA database and melanoma tissues.Conclusions: The results suggested that FLG, DSG1, DSG3, IVL and EGFR might play important roles and potentially be valuable in the prognosis and treatment of melanoma.

scholarly journals Transcriptome profiling of peanut (Arachis hypogaea) gynophores in gravitropic response

2013 ◽  
Vol 40 (12) ◽  
pp. 1249 ◽  
Author(s):  
Hai-fen Li ◽  
Xiao-Ping Chen ◽  
Fang-he Zhu ◽  
Hai-Yan Liu ◽  
Yan-Bin Hong ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Arachis Hypogaea ◽  
Molecular Mechanisms ◽  
Carbon Fixation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Pentose Phosphate ◽  
Differentially Expressed ◽  
Pcr Analysis

Peanut (Arachis hypogaea L.) produces flowers aerially, but the fruit develops underground. This process is mediated by the gynophore, which always grows vertically downwards. The genetic basis underlying gravitropic bending of gynophores is not well understood. To identify genes related to gynophore gravitropism, gene expression profiles of gynophores cultured in vitro with tip pointing upward (gravitropic stimulation sample) and downward (control) at both 6 and 12 h were compared through a high-density peanut microarray. After gravitropic stimulation, there were 174 differentially expressed genes, including 91 upregulated and 83 downregulated genes at 6 h, and 491 differentially expressed genes including 129 upregulated and 362 downregulated genes at 12 h. The differentially expressed genes identified were assigned to 24 functional categories. Twenty pathways including carbon fixation, aminoacyl-tRNA biosynthesis, pentose phosphate pathway, starch and sucrose metabolism were identified. The quantitative real-time PCR analysis was performed for validation of microarray results. Our study paves the way to better understand the molecular mechanisms underlying the peanut gynophore gravitropism.

scholarly journals Comprehensive analysis of differential expression profiles via transcriptome sequencing in SH-SY5Y cells infected with CV-A16

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241174
Author(s):  
Yajie Hu ◽  
Zhen Yang ◽  
Shenglan Wang ◽  
Danxiong Sun ◽  
Mingmei Zhong ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Transcriptome Sequencing ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Transcriptome Profiling ◽  
Differentially Expressed ◽  
Control Group ◽  
Protein Coding ◽  
Qrt Pcr ◽  
Protein Coding Genes

Coxsackievirus A16 (CV-A16) is one of the viruses that is most frequently associated with hand-foot-and-mouth disease (HFMD). Previous studies have shown that CV-A16 infections are mostly self-limiting, but in recent years, it has been gradually found that CV-A16 infections can also induce neurological complications and eventually cause death in children with HFMD. Moreover, no curative drugs or preventative vaccines have been developed for CV-A16 infection. Therefore, it is particularly important to investigate the mechanism of CV-A16 infection-induced neuropathy. In the current study, transcriptome sequencing technology was used to identify changes in the transcriptome of SH-SY5Y cells infected with CV-A16, which might hide the mechanism of CV-A16-induced neuropathology. The transcriptome profiling showed that 82,406,974, 108,652,260 and 97,753,565 clean reads were obtained in the Control, CV-A16-12 h and CV-A16-24 h groups, respectively. And it was further detected that a total of 136 and 161 differentially expressed genes in CV-A16-12 h and CV-A16-24 h groups, respectively, when compared with Control group. Then, to explore the mechanism of CV-A16 infection, we focused on the common differentially expressed genes at different time points of CV-A16 infection and found that there were 34 differentially expressed genes based on which clustering analysis and functional category enrichment analysis were performed. The results indicated that changes in oxidation levels were particularly evident in the GO term analysis, while only the “Gonadotropin-releasing hormone receptor pathway” was enriched in the KEGG pathway analysis, which might be closely related to the neurotoxicity caused by CV-A16 infection. Meanwhile, the ID2 closely related to nervous system has been demonstrated to be increased during CV-A16 infection. Additionally, the data on differentially expressed non-protein-coding genes of different types within the transcriptome sequencing results were analyzed, and it was speculated that these dysregulated non-protein-coding genes played a pivotal role in CV-A16 infection. Ultimately, qRT-PCR was utilized to validate the transcriptome sequencing findings, and the results of qRT-PCR were in agreement with the transcriptome sequencing data. In conclusion, transcriptome profiling was carried out to analyze response of SH-SY5Y cells to CV-A16 infection. And our findings provide important information to elucidate the possible molecular mechanisms which were linked to the neuropathogenesis of CV-A16 infection.

scholarly journals Identification of Differentially Expressed Genes and Pathways for Abdominal Fat Deposition in Ovariectomized and Sham-Operated Chickens

Genes ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 155 ◽  
Author(s):  
Xiaopeng Mu ◽  
Xiaoyan Cui ◽  
Ranran Liu ◽  
Qinghe Li ◽  
Maiqing Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Abdominal Fat ◽  
Fat Deposition ◽  
Differentially Expressed ◽  
Feed Conversion ◽  
Fat Percentage ◽  
Steroid Biosynthesis

Ovariectomy results in improved meat quality (growth rate, tenderness, and flavor) of broilers. However, some negative effects increased (abdominal fat (AF) deposition, low feed conversion, etc.) have also been reported. In this study, the gene expression profiles of AF tissue in ovariectomized and sham-operated chickens were determined to identify differentially expressed genes (DEGs) and pathways to explore the molecular mechanisms underlying AF accumulation. Comparing the ovariectomized group and the sham-operated group, the abdominal fat weight (AFW) and abdominal fat percentage (AFP) were increased significantly (p < 0.05) at 14 and 19 weeks after ovariectomy. According to the gene expression profiling analysis, 108 DEGs of fat metabolism were screened from 1461 DEGs. Among them, ABCA1, ABCACA, LPL, CREB1, PNPLA2, which are involved in glycerolipid—or steroid—associated biological processes, and the hormone receptor genes, ESR1 and PRLR, were down-regulated significantly in the ovariectomized group compared to the sham-operated group (p < 0.05). Conversely, CETP, DGAT2, DHCR24, HSD17B7 and MSMO1, were significantly up-regulated (p < 0.05) after ovariectomy. Based on the DEGs, the glycerolipid metabolism, steroid biosynthesis, and other signaling pathways (MAPK, TGF-β, and adhesion pathways, etc.) were enriched, which may also contribute to the regulation of AF deposition. Our data suggest that AF deposition was significantly increased in ovariectomized chickens by the down-regulation of the decomposition genes of glycerolipid metabolism, which inhibits AF degradation, and the up-regulation of steroid biosynthesis genes, which increases fat accumulation. These findings provide new insights into the molecular mechanisms of fat deposition in the ovariectomized chickens.

Identification of key biomarkers for thyroid cancer by integrative gene expression profiles

2021 ◽  
pp. 153537022110088
Author(s):  
Jinyi Tian ◽  
Yizhou Bai ◽  
Anyang Liu ◽  
Bin Luo
Keyword(s):  
Gene Expression ◽  
Thyroid Cancer ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Thyroid Tissue ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Tissue Samples

Thyroid cancer is a frequently diagnosed malignancy and the incidence has been increased rapidly in recent years. Despite the favorable prognosis of most thyroid cancer patients, advanced patients with metastasis and recurrence still have poor prognosis. Therefore, the molecular mechanisms of progression and targeted biomarkers were investigated for developing effective targets for treating thyroid cancer. Eight chip datasets from the gene expression omnibus database were selected and the inSilicoDb and inSilicoMerging R/Bioconductor packages were used to integrate and normalize them across platforms. After merging the eight gene expression omnibus datasets, we obtained one dataset that contained the expression profiles of 319 samples (188 tumor samples plus 131 normal thyroid tissue samples). After screening, we identified 594 significantly differentially expressed genes (277 up-regulated genes plus 317 down-regulated genes) between the tumor and normal tissue samples. The differentially expressed genes exhibited enrichment in multiple signaling pathways, such as p53 signaling. By building a protein–protein interaction network and module analysis, we confirmed seven hub genes, and they were all differentially expressed at all the clinical stages of thyroid cancer. A diagnostic seven-gene signature was established using a logistic regression model with the area under the receiver operating characteristic curve (AUC) of 0.967. Seven robust candidate biomarkers predictive of thyroid cancer were identified, and the obtained seven-gene signature may serve as a useful marker for thyroid cancer diagnosis and prognosis.

scholarly journals Integrated analyses of miRNAome and transcriptome reveal zinc deficiency responses in rice seedlings

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Houqing Zeng ◽  
Xin Zhang ◽  
Ming Ding ◽  
Yiyong Zhu
Keyword(s):  
Differentially Expressed Genes ◽  
Transcriptome Sequencing ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Small Rna Sequencing ◽  
Zn Deficiency ◽  
Rice Seedlings ◽  
Regulatory Pathways

Abstract Background Zinc (Zn) deficiency is one of the most widespread soil constraints affecting rice productivity, but the molecular mechanisms underlying the regulation of Zn deficiency response is still limited. Here, we aim to understand the molecular mechanisms of Zn deficiency response by integrating the analyses of the global miRNA and mRNA expression profiles under Zn deficiency and resupply in rice seedlings by integrating Illumina’s high-throughput small RNA sequencing and transcriptome sequencing. Results The transcriptome sequencing identified 360 genes that were differentially expressed in the shoots and roots of Zn-deficient rice seedlings, and 97 of them were recovered after Zn resupply. A total of 68 miRNAs were identified to be differentially expressed under Zn deficiency and/or Zn resupply. The integrated analyses of miRNAome and transcriptome data showed that 12 differentially expressed genes are the potential target genes of 10 Zn-responsive miRNAs such as miR171g-5p, miR397b-5p, miR398a-5p and miR528-5p. Some miRNA genes and differentially expressed genes were selected for validation by quantitative RT-PCR, and their expressions were similar to that of the sequencing results. Conclusion These results provide insights into miRNA-mediated regulatory pathways in Zn deficiency response, and provide candidate genes for genetic improvement of Zn deficiency tolerance in rice.

Identification of Differentially Expressed Genes Associated with Papillary Thyroid Carcinoma

2020 ◽  
Vol 23 (6) ◽  
pp. 546-553
Author(s):  
Hongyuan Cui ◽  
Mingwei Zhu ◽  
Junhua Zhang ◽  
Wenqin Li ◽  
Lihui Zou ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Cellular Proliferation ◽  
Mrna Level ◽  
Thyroid Tissue ◽  
Differentially Expressed ◽  
Thyroid Tumors ◽  
Papillary Thyroid

Objective: Next-generation sequencing (NGS) was performed to identify genes that were differentially expressed between normal thyroid tissue and papillary thyroid carcinoma (PTC). Materials & Methods: Six candidate genes were selected and further confirmed with quantitative real-time polymerase chain reaction (qRT-PCR), and immunohistochemistry in samples from 24 fresh thyroid tumors and adjacent normal tissues. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to investigate signal transduction pathways of the differentially expressed genes. Results: In total, 1690 genes were differentially expressed between samples from patients with PTC and the adjacent normal tissue. Among these, SFRP4, ZNF90, and DCN were the top three upregulated genes, whereas KIRREL3, TRIM36, and GABBR2 were downregulated with the smallest p values. Several pathways were associated with the differentially expressed genes and involved in cellular proliferation, cell migration, and endocrine system tumor progression, which may contribute to the pathogenesis of PTC. Upregulation of SFRP4, ZNF90, and DCN at the mRNA level was further validated with RT-PCR, and DCN expression was further confirmed with immunostaining of PTC samples. Conclusion: These results provide new insights into the molecular mechanisms of PTC. Identification of differentially expressed genes should not only improve the tumor signature for thyroid tumors as a diagnostic biomarker but also reveal potential targets for thyroid tumor treatment.

scholarly journals Identification of Differentially Expressed Genes in Porcine Ovaries at Proestrus and Estrus Stages Using RNA-Seq Technique

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Songbai Yang ◽  
Xiaolong Zhou ◽  
Yue Pei ◽  
Han Wang ◽  
Ke He ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Hormone Secretion ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
The Novel ◽  
Kegg Pathways ◽  
Go Enrichment ◽  
Single Organism

Estrus is an important factor for the fecundity of sows, and it is involved in ovulation and hormone secretion in ovaries. To better understand the molecular mechanisms of porcine estrus, the expression patterns of ovarian mRNA at proestrus and estrus stages were analyzed using RNA sequencing technology. A total of 2,167 differentially expressed genes (DEGs) were identified (P≤0.05, log2  Ratio≥1), of which 784 were upregulated and 1,383 were downregulated in the estrus compared with the proestrus group. Gene Ontology (GO) enrichment indicated that these DEGs were mainly involved in the cellular process, single-organism process, cell and cell part, and binding and metabolic process. In addition, a pathway analysis showed that these DEGs were significantly enriched in 33 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including cell adhesion molecules, ECM-receptor interaction, and cytokine-cytokine receptor interaction. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) confirmed the differential expression of 10 selected DEGs. Many of the novel candidate genes identified in this study will be valuable for understanding the molecular mechanisms of the sow estrous cycle.

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.

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