scholarly journals Blast2GO: A Comprehensive Suite for Functional Analysis in Plant Genomics

2008 ◽  
Vol 2008 ◽  
pp. 1-12 ◽  
Author(s):  
Ana Conesa ◽  
Stefan Götz
Keyword(s):  
Functional Annotation ◽  
Sequence Data ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Plant Genomics ◽  
Kegg Pathways ◽  
Acyclic Graphs ◽  
Genomics Research ◽  
Direct Acyclic Graphs

Functional annotation of novel sequence data is a primary requirement for the utilization of functional genomics approaches in plant research. In this paper, we describe the Blast2GO suite as a comprehensive bioinformatics tool for functional annotation of sequences and data mining on the resulting annotations, primarily based on the gene ontology (GO) vocabulary. Blast2GO optimizes function transfer from homologous sequences through an elaborate algorithm that considers similarity, the extension of the homology, the database of choice, the GO hierarchy, and the quality of the original annotations. The tool includes numerous functions for the visualization, management, and statistical analysis of annotation results, including gene set enrichment analysis. The application supports InterPro, enzyme codes, KEGG pathways, GO direct acyclic graphs (DAGs), and GOSlim. Blast2GO is a suitable tool for plant genomics research because of its versatility, easy installation, and friendly use.

SNPknow: a web server for functional annotation of cattle SNP markers

2011 ◽  
Vol 91 (2) ◽  
pp. 247-253
Author(s):  
Qishan Wang ◽  
Hongbo Zhao ◽  
Yuchun Pan
Keyword(s):  
Functional Annotation ◽  
Genome Wide Association Study ◽  
Web Server ◽  
Enrichment Analysis ◽  
Snp Markers ◽  
Gene Set Enrichment Analysis ◽  
Nucleotide Polymorphisms ◽  
Go Annotation ◽  
Large Sets ◽  
Snp Association

Wang, Q., Zhao, H. and Pan, Y. 2011. SNPknow: a web server for functional annotation of cattle SNP markers. Can. J. Anim. Sci. 91: 247–253. Single nucleotide polymorphisms (SNP) microarray technology provides new insights to identify the genetic factors associated with the traits of interest. To meet the immediate need for a framework of genome-wide association study (GWAS), we have developed SNPknow, a suite of CGI-based tools that provide enrichment analysis and functional annotation for cattle SNP markers and allow the users to navigate and analysis large sets of high-dimensional data from the gene ontology (GO) annotation systems. SNPknow is the only web server currently providing functional annotations of cattle SNP markers in three commercial platforms and dbSNP database. The web server may be particularly beneficial for the analysis of combining SNP association analysis with the gene set enrichment analysis and is freely available at http://klab.sjtu.edu.cn/SNPknow .

scholarly journals Nomogram With a Novel Microenvironment Signature Is Systematically Constructed and Validated to Predict the Survival Rate of Glioma Patients.

2020 ◽  
Author(s):  
Tianhua Li ◽  
Yiguang Chen ◽  
Yongjian Chen ◽  
Guangjie Liu ◽  
Shisheng Zou ◽  
...  
Keyword(s):  
Cox Regression ◽  
Malignant Tumors ◽  
Prognostic Index ◽  
Enrichment Analysis ◽  
Basic Research ◽  
Predictive Performance ◽  
High Risk Group ◽  
Gene Set Enrichment Analysis ◽  
Cox Regression Analysis ◽  
Kegg Pathways

Glioma accounts for the highest proportion of primary intracranial malignant tumors. Microenvironment enormously influences the process of glioma progression. Our study is to establish an individualized prognostic nomogram for glioma patients with microenvironment signature. Glioma samples of Chinese Glioma Genome Atlas (CGGA) were grouped by the immune and stromal score based on ESTIMATE algorithm. Microenvironment-related genes (MRGs) in glioma were analyzed by R. To determine the best prognostic correlation genes, univariate and multivariate Cox regression analysis were used to analyze MRGs. Use the selected genes (CHI3L1, SOCS3, SLC47A2, COL3A1, SRPX2 and SERPINA3), we established the prognostic risk score model (microenvironment signature) and validated it. Gene Set Enrichment Analysis (GSEA) showed that the high-risk group was mainly enriched in immune and stromal function KEGG pathways. Finally, the nomogram was constructed and evaluated. The receiver operating characteristic (ROC) curve, Calibration plots and decision curve analysis (DCA) of training and validation set indicated the excellent predictive performance of nomogram. In conclusion, the 6-gene microenvironment signature can not only provide directions for the basic research of glioma, but also can be included as an independent prognostic index in nomogram for individual prediction to guide clinical treatment.

scholarly journals Identification of biomarkers and pathways in hypertensive nephropathy based on the ceRNA regulatory network

2019 ◽  
Author(s):  
lei kang ◽  
Zhen Wang ◽  
Zhongjie Liu ◽  
Yingxia Liu
Keyword(s):  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Network ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Insulin Signaling Pathway ◽  
Gene Set Enrichment Analysis ◽  
Chronic Hypertension ◽  
Hypertensive Nephropathy ◽  
Kegg Pathways

Abstract Background Hypertensive nephropathy (HTN) is a kind of renal injury caused by chronic hypertension, which seriously affect people’s life. The purpose of this study was to identify the potential biomarkers of HTN and understand its possible mechanisms.Methods The dataset numbered GSE28260 related to hypertensive and normotensive was downloaded from NCBI Gene Expression Omnibus. Then, the differentially expressed RNAs (DERs) were screened using R limma package, and functional analyses of DE-mRNA were performed by DAVID. Afterwards, a ceRNA network was established and KEGG pathway was analyzed based on the Gene Set Enrichment Analysis (GSEA) database. Finally, a ceRNA regulatory network directly associated with HTN was proposed.Results A total of 947 DERs were identified, including 900 DE-mRNAs, 20 DE-lncRNAs and 27 DE-miRNAs. Based on these DE-mRNAs, they were involved in biological processes such as fatty acid beta-oxidation, IRE1-mediated unfolded protein response, and transmembrane transport, and many KEGG pathways like glycine, serine and threonine metabolism, carbon metabolism. Subsequently, lncRNAs KCTD21-AS1, LINC00470 and SNHG14 were found to be hub nodes in the ceRNA regulatory network. KEGG analysis showed that insulin signaling pathway, glycine, serine and threonine metabolism, pathways in cancer, lysosome, and apoptosis was associated with hypertensive. Finally, insulin signaling pathway was screened to directly associate with HTN and was regulated by mRNAs PPP1R3C, PPKAR2B and AKT3, miRNA has-miR-107, and lncRNAs SNHG14, TUG1, ZNF252P-AS1 and MIR503HG.Conclusions Insulin signaling pathway was directly associated with HTN, and miRNA has-miR-107 and lncRNAs SNHG14, TUG1, ZNF252P-AS1 and MIR503HG were the biomarkers of HTN. These results would improve our understanding of the occurrence and development of HTN.

scholarly journals Statistical power of gene-set enrichment analysis is a function of gene set correlation structure

2017 ◽  
Author(s):  
David M. Swanson
Keyword(s):  
Statistical Power ◽  
Sequence Data ◽  
Enrichment Analysis ◽  
Analytical Framework ◽  
Gene Set Enrichment Analysis ◽  
Correlation Structure ◽  
Gene Set ◽  
Type 1 Error ◽  
Gene Set Testing ◽  
Supplementary Material

AbstractMotivation:We describe why statistical power for both self-contained and competitive gene-set tests is a function of the correlation structure of co-expressed genes, and why this characteristic is undesirable for gene-set analyses. Variable statistical power as a function of gene correlation structure has not been observed or studied previously. The observation is important in part because gene-set testing methodology is well-developed, yet this fundamental feature of many of its tests is unknown and has the potential to reinterpret past gene-set test results and guide future implementations, including those using sequence data. Type 1 error inflation is also amenable for study in our statistical framework; while it has been well-studied and described previously for both self-contained and competitive tests, it has less often been done in an analytical framework. Our observations apply to four commonly-used gene-set testing approaches for microarrays, including CAMERA, ROAST, SAFE, and GAGE, and a recently proposed one for RNAseq, MAST.Results:We characterize situations in which power is especially small relative to effect sizes of genes in a set for both competitive and self-contained gene-set tests. We propose three alternative tests, one of which replicates the properties of permutation-based self-contained tests, but avoids the need for even recently proposed, rotation-based approximations to permutations. The two other proposed tests have the unique property that statistical power is not a function of co-expression correlation in the gene-set and therefore is the preferred methodology. We compare our proposed tests to leading gene-set tests and apply them to an already-published study of smoking exposure on pregnant women.Contact:[email protected] Material:Online supplementary material includes additional simulation results supporting the relationship between the “mixed” and “directional” gene-set tests of ROAST and closed-form implementations of them.

scholarly journals Identification of male infertility-related long non-coding RNAs and their functions based on a competing endogenous RNA network

2020 ◽  
Vol 48 (10) ◽  
pp. 030006052096127
Author(s):  
Zuo Zhou ◽  
Bing Wang
Keyword(s):  
Male Infertility ◽  
System Development ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
P Value ◽  
Kegg Pathways ◽  
Cerna Network ◽  
Competing Endogenous Rna Network ◽  
Pathway Analyses

Objective To identify male infertility-related long non-coding (lnc)RNAs and an lncRNA-related competing endogenous (ce)RNA network. Methods Expression data including 13 normospermic and eight teratozoospermic samples from postmortem donors were downloaded from the GEO database (GSE6872). The limma R package was used to discriminate dysregulated lncRNA and micro (m)RNA profiles. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of differentially expressed (DE) mRNAs were performed using the clusterProfiler R package. The ceRNA network of dysregulated genes was visualized by Cytoscape. Results A total of 101 DE lncRNAs and 1722 mRNAs were identified as male infertility-specific RNAs with thresholds of |log2FoldChange| >2.0 and adjusted P-value <0.05. GO and KEGG pathways were analyzed for DE mRNAs. Gene set enrichment analysis revealed that DE genes were enriched in embryonic skeletal system development and cytokine–cytokine receptor interactions. A ceRNA network was constructed with 26 key lncRNAs, 33 microRNAs, and 133 mRNAs. DE lncRNAs in male sterility were mainly associated with transferring phosphorus-containing groups and complexes of histone methyltransferases, methyltransferases, PcG proteins, and serine/threonine protein kinases. Conclusion This provides a novel perspective to study lncRNA-related ceRNA networks in male infertility and assist in identifying new potential biomarkers for diagnostic purposes.

scholarly journals Identification of biomarkers and pathways in hypertensive nephropathy based on the ceRNA regulatory network

2020 ◽  
Author(s):  
Zhen Wang ◽  
Zhongjie Liu ◽  
Yingxia Liu ◽  
Lei Kang
Keyword(s):  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Network ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Insulin Signaling Pathway ◽  
Gene Set Enrichment Analysis ◽  
Chronic Hypertension ◽  
Hypertensive Nephropathy ◽  
Kegg Pathways

Abstract Background Hypertensive nephropathy (HTN) is a kind of renal injury caused by chronic hypertension, which seriously affect people’s life. The purpose of this study was to identify the potential biomarkers of HTN and understand its possible mechanisms. Methods The dataset numbered GSE28260 related to hypertensive and normotensive was downloaded from NCBI Gene Expression Omnibus. Then, the differentially expressed RNAs (DERs) were screened using R limma package, and functional analyses of DE-mRNA were performed by DAVID. Afterwards, a ceRNA network was established and KEGG pathway was analyzed based on the Gene Set Enrichment Analysis (GSEA) database. Finally, a ceRNA regulatory network directly associated with HTN was proposed. Results A total of 947 DERs were identified, including 900 DE-mRNAs, 20 DE-lncRNAs and 27 DE-miRNAs. Based on these DE-mRNAs, they were involved in biological processes such as fatty acid beta-oxidation, IRE1-mediated unfolded protein response, and transmembrane transport, and many KEGG pathways like glycine, serine and threonine metabolism, carbon metabolism. Subsequently, lncRNAs KCTD21-AS1 , LINC00470 and SNHG14 were found to be hub nodes in the ceRNA regulatory network. KEGG analysis showed that insulin signaling pathway, glycine, serine and threonine metabolism, pathways in cancer, lysosome, and apoptosis was associated with hypertensive. Finally, insulin signaling pathway was screened to directly associate with HTN and was regulated by mRNAs PPP1R3C , PPKAR2B and AKT3 , miRNA has-miR-107, and lncRNAs SNHG14 , TUG1 , ZNF252P-AS1 and MIR503HG . Conclusions Insulin signaling pathway was directly associated with HTN, and miRNA has-miR-107 and lncRNAs SNHG14 , TUG1 , ZNF252P-AS1 and MIR503HG were the biomarkers of HTN. These results would improve our understanding of the occurrence and development of HTN.

scholarly journals Expression profiling of small intestinal neuroendocrine tumors identified pathways and gene networks linked to tumorigenesis and metastasis

2020 ◽  
Vol 40 (6) ◽  
Author(s):  
Qiang Wang ◽  
Chaoran Yu
Keyword(s):  
Neuroendocrine Tumors ◽  
Gene Networks ◽  
Protein A ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Gamma Chain ◽  
Molecular Feature ◽  
Kegg Pathways ◽  
Small Intestinal

Abstract Small intestinal neuroendocrine tumors (SI-NETs) remain the most common subset in gastrointestinal neuroendocrine tumors and featured by aggressiveness. However, the molecular feature of SI-NETs remains largely unclear with key genes and pathways yet to be identified. The gene expression profile GSE65286 was retrieved for analysis. Artificial neural networks (ANNs) were constructed for the hub genes network models. A total of 613 differentially expressed genes (DEGs) were identified between normal (N) and primary tumor (T) groups, whereas 61 DEGs were identified between T and liver metastases (LM) groups. The top Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for the DEGs of N versus T were fat digestion and absorption pathway. For T versus LM the top KEGG pathways were complement and coagulation. In gene set enrichment analysis (GSEA), five gene sets, including Notch signaling, inflammatory response, coagulation, KRAS signaling, and allograft rejection were significantly enriched in the T group. The hub genes in the DEGs of T versus LM included albumin, fibrinogen gamma chain, alpha 2-HS glycoprotein, transferrin and GC, vitamin D binding protein. A distinct correlational alteration of hub genes was observed between T and LM groups. In ANN analysis, ALB and TF were the top predictors of metastasis. Moreover, the expression of ALB≤ showed the highest support to T whereas ALB&gt;15.97 supports LM. TF≤7.54 showed the highest negative correlation to the T. This bioinformatics analysis provided insights on potential key pathways and genes networks involved in SI-NETs and established an ANN-based hub gene model for metastatic prediction.

scholarly journals Identification of biomarkers and pathways in hypertensive nephropathy based on the ceRNA regulatory network

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhen Wang ◽  
Zhongjie Liu ◽  
Yingxia Yang ◽  
Lei Kang
Keyword(s):  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Network ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Insulin Signaling Pathway ◽  
Gene Set Enrichment Analysis ◽  
Chronic Hypertension ◽  
Hypertensive Nephropathy ◽  
Kegg Pathways

Abstract Background Hypertensive nephropathy (HTN) is a kind of renal injury caused by chronic hypertension, which seriously affect people’s life. The purpose of this study was to identify the potential biomarkers of HTN and understand its possible mechanisms. Methods The dataset numbered GSE28260 related to hypertensive and normotensive was downloaded from NCBI Gene Expression Omnibus. Then, the differentially expressed RNAs (DERs) were screened using R limma package, and functional analyses of DE-mRNA were performed by DAVID. Afterwards, a ceRNA network was established and KEGG pathway was analyzed based on the Gene Set Enrichment Analysis (GSEA) database. Finally, a ceRNA regulatory network directly associated with HTN was proposed. Results A total of 947 DERs were identified, including 900 DE-mRNAs, 20 DE-lncRNAs and 27 DE-miRNAs. Based on these DE-mRNAs, they were involved in biological processes such as fatty acid beta-oxidation, IRE1-mediated unfolded protein response, and transmembrane transport, and many KEGG pathways like glycine, serine and threonine metabolism, carbon metabolism. Subsequently, lncRNAs KCTD21-AS1, LINC00470 and SNHG14 were found to be hub nodes in the ceRNA regulatory network. KEGG analysis showed that insulin signaling pathway, glycine, serine and threonine metabolism, pathways in cancer, lysosome, and apoptosis was associated with hypertensive. Finally, insulin signaling pathway was screened to directly associate with HTN and was regulated by mRNAs PPP1R3C, PPKAR2B and AKT3, miRNA has-miR-107, and lncRNAs SNHG14, TUG1, ZNF252P-AS1 and MIR503HG. Conclusions Insulin signaling pathway was directly associated with HTN, and miRNA has-miR-107 and lncRNAs SNHG14, TUG1, ZNF252P-AS1 and MIR503HG were the biomarkers of HTN. These results would improve our understanding of the occurrence and development of HTN.

scholarly journals Comparison of Two Experimental Mouse Dry Eye Models through Inflammatory Gene Set Enrichment Analysis Based on a Multiplexed Transcriptomic Approach

2021 ◽  
Vol 22 (19) ◽  
pp. 10770
Author(s):  
Karima Kessal ◽  
Philippe Daull ◽  
Nicolas Cimbolini ◽  
Laurence Feraille ◽  
Sophie Grillo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Dry Eye ◽  
Functional Annotation ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Healthy Controls ◽  
Gene Set Enrichment ◽  
Gene Transcripts ◽  
Experimental Mouse

The goal of this study was to explore the specific signaling pathways related to inflammation in two experimental mouse dry eye (EDE) models. Female C57BL/6 mice housed for 10 days in a controlled desiccative environment were either treated with scopolamine (EDE-1; n = 18) or subjected to extraorbital lacrimal gland excision bilaterally (EDE-2; n = 10). Non-induced mice (n = 20) served as healthy controls. A corneal fluorescein staining (CFS) scoring was used at baseline through to day (D) 10 to evaluate epitheliopathy. At D10, corneas and conjunctivas were collected for multiplexed transcriptomic analysis with the NanoString® mouse inflammatory CodeSet. Both EDE-1 and EDE-2 mice presented a change in corneal integrity, with a significant increase in CFS scores at D10. More gene transcripts were identified in EDE-2 compared with EDE-1 (116 vs. 96, respectively), and only a few were common to both models, 13 for the cornea and 6 for the conjunctiva. The gene functional annotation analysis revealed that the same inflammatory pathways were involved in both models. Comparative profiling of gene expression in the two EDE models leads to the identification of various targets and signaling pathways, which can be extrapolated to and confirmed in human disease.

Identification of key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma

2020 ◽  
Vol 15 ◽  
Author(s):  
Wei Han ◽  
Dongchen Lu ◽  
Chonggao Wang ◽  
Mengdi Cui ◽  
Kai Lu
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differential Expression Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Integrated Analysis ◽  
Papillary Thyroid ◽  
Gene Set Enrichment ◽  
Mirna Expression Data

Background: In the past decades, the incidence of thyroid cancer (TC) has been gradually increasing, owing to the widespread use of ultrasound scanning devices. However, the key mRNAs, miRNAs, and mRNA-miRNA network in papillary thyroid carcinoma (PTC) has not been fully understood. Material and Methods: In this study, multiple bioinformatics methods were employed, including differential expression analysis, gene set enrichment analysis, and miRNA-mRNA interaction network construction. Results: First, we investigated the key miRNAs that regulated significantly more differentially expressed genes based on GSEA method. Second, we searched for the key miRNAs based on the mRNA-miRNA interaction subnetwork involved in PTC. We identified hsa-mir-1275, hsa-mir-1291, hsa-mir-206 and hsa-mir-375 as the key miRNAs involved in PTC pathogenesis. Conclusion: The integrated analysis of the gene and miRNA expression data not only identified key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma, but also improved our understanding of the pathogenesis of PTC.

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