scholarly journals Identification of differentially expressed genes in hip cartilage with femoral head necrosis, based on genome‑wide expression profiles

2019 ◽  
Author(s):  
Wen Li ◽  
De Bai ◽  
Yang Xu ◽  
Rui Xu ◽  
Wen Hou
Keyword(s):  
Femoral Head ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Femoral Head Necrosis ◽  
Differentially Expressed ◽  
Genome Wide ◽  
Hip Cartilage ◽  
Genome Wide Expression

Combined analysis of genome-wide expression profiling of maize (Zea mays L.) leaves infected with Ustilago maydis

Genome ◽  
2018 ◽  
Vol 61 (7) ◽  
pp. 505-513 ◽  
Author(s):  
Jinglu Wang ◽  
Ying Zhang ◽  
Jianjun Du ◽  
Xiaodi Pan ◽  
Liming Ma ◽  
...  
Keyword(s):  
Quality Control ◽  
Differentially Expressed Genes ◽  
Expression Profiling ◽  
Ustilago Maydis ◽  
Differentially Expressed ◽  
Data Sets ◽  
Combined Analysis ◽  
Genome Wide ◽  
Maize Leaves ◽  
Genome Wide Expression

Although many gene expression profiling studies of maize leaves infected with Ustilago maydis have been published, heterogeneity of the results, caused by various data processing methods and pathogenic strains in different data sets, remains strong. Hence, we conducted a combined analysis of six genome-wide expression data sets of maize leaves infected with five different U. maydis strains by using the same pre-processing and quality control procedures. Six data sets were regrouped into five groups according to pathogenic strain used. Subsequently, each group of data set was processed by Multi-array Average for pre-processing and by pair-wise Pearson correlation for quality control. The differentially expressed genes were calculated by a standard linear mixed-effect model and then validated by various sensitivity analysis and multiple evidences. Finally, 44 unique differentially expressed genes were identified. Pathway enrichment analysis indicated that these genes related to response to fungus, oxidation-reduction, transferase activity, and several carbohydrate metabolic and catabolic processes. In addition, the hub genes within protein–protein interaction networks showed high relevance with the basic pathogenesis. We report a highly credible differentially expressed list, and the genes with multiple validations may denote a common signature of U. maydis in maize, which provides a new window for disease-resistant protection of maize plants.

scholarly journals Genome-wide transcriptome profiling uncovers differential miRNAs and lncRNAs in ovaries of Hu sheep at different developmental stages

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Samina Shabbir ◽  
Prerona Boruah ◽  
Lingli Xie ◽  
Muhammad Fakhar-e-Alam Kulyar ◽  
Mohsin Nawaz ◽  
...  
Keyword(s):  
Target Genes ◽  
Expression Profiles ◽  
Ovarian Follicle ◽  
Follicular Development ◽  
Differentially Expressed ◽  
Ovary Development ◽  
Estrogen Metabolism ◽  
Genome Wide ◽  
Micro Rnas ◽  
Hu Sheep

AbstractOvary development is an important determinant of the procreative capacity of female animals. Here, we performed genome-wide sequencing of long non-coding RNAs (lncRNAs) and mRNAs on ovaries of 1, 3 and 8 months old Hu sheep to assess their expression profiles and roles in ovarian development. We identified 37,309 lncRNAs, 45,404 messenger RNAs (mRNAs) and 330 novel micro RNAs (miRNAs) from the transcriptomic analysis. Six thousand, seven hundred and sixteen (6716) mRNAs and 1972 lncRNAs were significantly and differentially expressed in ovaries of 1 month and 3 months old Hu sheep (H1 vs H3). These mRNAs and target genes of lncRNAs were primarily enriched in the TGF-β and PI3K-Akt signalling pathways which are closely associated with ovarian follicular development and steroid hormone biosynthesis regulation. We identified MSTRG.162061.1, MSTRG.222844.7, MSTRG.335777.1, MSTRG.334059.16, MSTRG.188947.6 and MSTRG.24344.3 as vital genes in ovary development by regulating CTNNB1, CCNA2, CDK2, CDC20, CDK1 and EGFR expressions. A total of 2903 mRNAs and 636 lncRNAs were differentially expressed in 3 and 8 months old ovaries of Hu sheep (H3 vs H8); and were predominantly enriched in PI3K-Akt, progesterone-mediated oocyte maturation, estrogen metabolism, ovulation from the ovarian follicle and oogenesis pathways. These lncRNAs were also found to regulate FGF7, PRLR, PTK2, AMH and INHBA expressions during follicular development. Our result indicates the identified genes participate in the development of the final stages of follicles and ovary development in Hu sheep.

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.

FRI0309 The genome-wide expression of human osteoarthritic cartilage shows different GENE-expression profiles OA-related

2013 ◽  
Vol 71 (Suppl 3) ◽  
pp. 418.3-418
Author(s):  
J. Fernandez-Tajes ◽  
A. Soto-Hermida ◽  
M. Fernandez-Moreno ◽  
M.E. Vazquez-Mosquera ◽  
N. Oreiro ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Osteoarthritic Cartilage ◽  
Genome Wide ◽  
Genome Wide Expression

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 Transcriptome analysis ofSchistosoma mansonilarval development using serial analysis of gene expression (SAGE)

Parasitology ◽  
2009 ◽  
Vol 136 (5) ◽  
pp. 469-485 ◽  
Author(s):  
A. S. TAFT ◽  
J. J. VERMEIRE ◽  
J. BERNIER ◽  
S. R. BIRKELAND ◽  
M. J. CIPRIANO ◽  
...  
Keyword(s):  
Gene Expression ◽  
Sequence Data ◽  
Subsequent Development ◽  
Differentially Expressed ◽  
Cdna Libraries ◽  
Genome Wide ◽  
A Genome ◽  
Genome Wide Expression ◽  
Cell Conditioned Medium

SUMMARYInfection of the snail,Biomphalaria glabrata, by the free-swimming miracidial stage of the human blood fluke,Schistosoma mansoni, and its subsequent development to the parasitic sporocyst stage is critical to establishment of viable infections and continued human transmission. We performed a genome-wide expression analysis of theS. mansonimiracidia and developing sporocyst using Long Serial Analysis of Gene Expression (LongSAGE). Five cDNA libraries were constructed from miracidia andin vitrocultured 6- and 20-day-old sporocysts maintained in sporocyst medium (SM) or in SM conditioned by previous cultivation with cells of theB. glabrataembryonic (Bge) cell line. We generated 21 440 SAGE tags and mapped 13 381 to theS. mansonigene predictions (v4.0e) either by estimating theoretical 3′ UTR lengths or using existing 3′ EST sequence data. Overall, 432 transcripts were found to be differentially expressed amongst all 5 libraries. In total, 172 tags were differentially expressed between miracidia and 6-day conditioned sporocysts and 152 were differentially expressed between miracidia and 6-day unconditioned sporocysts. In addition, 53 and 45 tags, respectively, were differentially expressed in 6-day and 20-day cultured sporocysts, due to the effects of exposure to Bge cell-conditioned medium.

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.

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