• Genomics & Informatics
• /
• 제5권1호
• /
• pp.10-18
• /
• 2007

Numerous studies have reported that genes with similar expression patterns are co-regulated. From gene expression data, we have assumed that genes having similar expression pattern would share similar transcription factor binding sites (TFBSs). These function as the binding regions for transcription factors (TFs) and thereby regulate gene expression. In this context, various analysis tools have been developed. However, they have shortcomings in the combined analysis of expression patterns and significant TFBSs and in the functional analysis of target genes of significantly overrepresented putative regulators. In this study, we present a web-based A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms (FCAnalyzer). This system integrates microarray clustering data with similar expression patterns, and TFBS data in each cluster. FCAnalyzer is designed to perform two independent clustering procedures. The first process clusters gene expression profiles using the K-means clustering method, and the second process clusters predicted TFBSs in the upstream region of previously clustered genes using the hierarchical biclustering method for simultaneous grouping of genes and samples. This system offers retrieved information for predicted TFBSs in each cluster using $Match^{TM}$ in the TRANSFAC database. We used gene ontology term analysis for functional annotation of genes in the same cluster. We also provide the user with a combinatorial TFBS analysis of TFBS pairs. The enrichment of TFBS analysis and GO term analysis is statistically by the calculation of P values based on Fisher’s exact test, hypergeometric distribution and Bonferroni correction. FCAnalyzer is a web-based, user-friendly functional clustering analysis system that facilitates the transcriptional regulatory analysis of co-expressed genes. This system presents the analyses of clustered genes, significant TFBSs, significantly enriched TFBS combinations, their target genes and TFBS-TF pairs.

• Molecules and Cells
• /
• 제21권1호
• /
• pp.82-88
• /
• 2006

The global pattern of growth-dependent gene expression in Streptococcus pneumoniae strains was evaluated using a high-density DNA microarray. Total RNAs obtained from an avirulent S. pneumoniae strain R6 and a virulent strain AMC96-6 were used to compare the expression patterns at seven time points (2.5, 3.5, 4.5, 5.5, 6.0, 6.5, and 8.0 h). The expression profile of strain R6 changed between log and stationary growth (the Log-Stat switch). There were clear differences between the growth-dependent gene expression profiles of the virulent and avirulent pneumococcal strains in 367 of 1,112 genes. Transcripts of genes associated with bacterial competence and capsular polysaccharide formation, as well as clpP and cbpA, were higher in the virulent strain. Our data suggest that late log or early stationary phase may be the most virulent phase of S. pneumoniae.

• Animal Bioscience
• /
• 제36권6호
• /
• pp.840-850
• /
• 2023

Objective: This study aimed to investigate the polymorphisms of the dopa decarboxylase (DDC) gene and association analysis with lamb quality and expression quantification of the DDC gene in phenotypically divergent Indonesian sheep. Methods: The totals of 189 rams with an average body weight of 24.12 kg at 10 to 12 months were used to identify DDC gene polymorphism using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Among 189 rams, several rams representing various sheep genotypes were used for an association study between genotypes and phenotypic traits with proc general linear model (GLM) analysis. In addition, the gene expression analysis of the DDC mRNA in the phenotypically divergent sheep population was analyzed using quantitative reverse-transcription PCR. Results: The DDC gene (g. 5377439 G>A) showed polymorphisms that indicated three genotypes: AA, AG, and GG. The DDC gene polymorphism was significantly associated (p≤0.05) with carcass characteristics including carcass percentage, carcass length, hot and cold carcass; physical properties of lamb quality including pH value; retail cut carcass; fatty acid composition such as fat content, pentadecanoic acid (C15:0), tricosylic acid (C23:0), lignoceric acid (C24:0), oleic acid (C18:1n9c), elaidic acid (C18:1n9t), nervonic acid (C24:1), linoleic acid (C18:2n6c), arachidonic acid (C20:4n6), cervonic acid (C22:6n3); and mineral content including potassium (K). The GG genotype of the DDC gene had the best association with lamb quality traits. The DDC gene expression analysis mRNA showed no significant difference (p≥0.05) between lamb quality traits. Conclusion: The DDC gene could be used as a potential candidate gene to improve lamb quality.

• Asian Pacific Journal of Cancer Prevention
• /
• 제14권11호
• /
• pp.6347-6350
• /
• 2013

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

• Genomics & Informatics
• /
• 제20권3호
• /
• pp.32.1-32.15
• /
• 2022

Malaria is a life-threatening disease, and Africa is still one of the most affected endemic regions despite years of policy to limit infection and transmission rates. Further, studies into the variable efficacy of the vaccine are needed to provide a better understanding of protective immunity. Thus, the current study is designed to delineate the effect of each dose of vaccine on the transcriptional profiles of subjects to determine its efficacy and understand the molecular mechanisms underlying the protection this vaccine provides. Here, we used gene expression profiles of pre and post-vaccination patients after various doses of RTS,S based on samples collected from the Gene Expression Omnibus datasets. Subsequently, differential gene expression analysis using edgeR revealed the significantly (false discovery rate < 0.005) 158 downregulated and 61 upregulated genes between control vs. controlled human malaria infection samples. Further, enrichment analysis of significant genes delineated the involvement of CCL8, CXCL10, CXCL11, XCR1, CSF3, IFNB1, IFNE, IL12B, IL22, IL6, IL27, etc., genes which found to be upregulated after earlier doses but downregulated after the 3rd dose in cytokine-chemokine pathways. Notably, we identified 13 cytokine genes whose expression significantly varied during three doses. Eventually, these findings give insight into the dual role of cytokine responses in malaria pathogenesis. The variations in their expression patterns after various doses of vaccination are linked to the protection as it decreases the severe inflammatory effects in malaria patients. This study will be helpful in designing a better vaccine against malaria and understanding the functions of cytokine response as well.

• Animal Bioscience
• /
• 제36권5호
• /
• pp.704-709
• /
• 2023

Objective: In tropical, subtropical and arid zones, heat stress is the main cause of productivity reduction in cattle. When climate stressors occur, animals become thermal adapted through differential expression of some genes, including heat shock proteins (HSP) family. The aim of this study was to determine levels of expression of HSP60, HSP70, and HSP90 genes in Simmental cattle raised in tropical environments of Mexico. Methods: In this study, expression of HSP60, HSP70, and HSP90 genes was analyzed in 116 Simmental cattle from three farms with tropical climate located in western Mexico. Animals were sampled twice a day, in the morning and noon. Gene expression was evaluated by quantitative polymerase chain reaction using probes marked with fluorescence. The MIXED procedure of SAS with repeated measures was used for all statistical analysis. Results: HSP60 gene expression differences were found for sex (p = 0.0349). HSP70 gene differences were detected for sampling hour (p = 0.0042), farm (p<0.0001), sex (p = 0.0476), and the interaction sampling hour×farm (p = 0.0002). Gene expression differences for HSP90 were observed for farm (p<0.0001) and year (p = 0.0521). HSP70 gene showed to be a better marker of heat stress than HSP60 and HSP90 genes. Conclusion: Expression of HSP70 gene in Simmental herds of the tropical region of western México was different during early morning and noon, but the expression of the HSP60 and HSP90 genes was similar. Identification of resilient animals to heat stress will be useful in the genetic improvement of the Simmental breed.

• 제어로봇시스템학회논문지
• /
• 제10권12호
• /
• pp.1172-1180
• /
• 2004

Recently, the gene expression data, product of high-throughput technology, appeared in earnest and the studies related with it (so-called bioinformatics) occupied an important position in the field of biological and medical research. The microarray is a revolutionary technology which enables us to monitor several thousands of genes simultaneously and thus to gain an insight into the phenomena in the human body (e.g. the mechanism of cancer progression) at the molecular level. To obtain useful information from such gene expression measurements, it is essential to analyze the data with appropriate techniques. However the high-dimensionality of the data can bring about some problems such as curse of dimensionality and singularity problem of matrix computation, and hence makes it difficult to apply conventional data analysis methods. Therefore, the development of method which can effectively treat the data becomes a challenging issue in the field of computational biology. This research focuses on the gene selection and classification for cancer subtype discrimination based on gene expression (microarray) data.

• Journal of Veterinary Science
• /
• 제21권6호
• /
• pp.91.1-91.15
• /
• 2020

Background: Sulforaphane (SFN) is an isothiocyanate compound present in cruciferous vegetables. Although the anti-inflammatory effects of SFN have been reported, the precise mechanism related to the inflammatory genes is poorly understood. Objectives: This study examined the relationship between the anti-inflammatory effects of SFN and the differential gene expression pattern in SFN treated ob/ob mice. Methods: Nitric oxide (NO) level was measured using a Griess assay. The inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) expression levels were analyzed by Western blot analysis. Pro-inflammatory cytokines (tumor necrosis factor [TNF]-α, interleukin [IL]-1β, and IL-6) were measured by enzyme-linked immunosorbent assay (ELISA). RNA sequencing analysis was performed to evaluate the differential gene expression in the liver of ob/ob mice. Results: The SFN treatment significantly attenuated the iNOS and COX-2 expression levels and inhibited NO, TNF-α, IL-1β, and IL-6 production in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells. RNA sequencing analysis showed that the expression levels of 28 genes related to inflammation were up-regulated (> 2-fold), and six genes were down-regulated (< 0.6-fold) in the control ob/ob mice compared to normal mice. In contrast, the gene expression levels were restored to the normal level by SFN. The protein-protein interaction (PPI) network showed that chemokine ligand (Cxcl14, Ccl1, Ccl3, Ccl4, Ccl17) and chemokine receptor (Ccr3, Cxcr1, Ccr10) were located in close proximity and formed a "functional cluster" in the middle of the network. Conclusions: The overall results suggest that SFN has a potent anti-inflammatory effect by normalizing the expression levels of the genes related to inflammation that were perturbed in ob/ob mice.

• Journal of Acupuncture Research
• /
• 제37권2호
• /
• pp.128-135
• /
• 2020

Background: Classical acupuncture is being used in the treatment of rheumatoid arthritis (RA). To explore the biological response to acupuncture, a network-based analysis was performed on gene expression data collected from an animal model of RA treated with acupuncture. Methods: Gene expression data were obtained from published microarray studies on blood samples from rats with collagen induced arthritis (CIA) and non-CIA rats, both treated with manual acupuncture. The weighted gene co-expression network analysis was performed to identify gene clusters expressed in association with acupuncture treatment time and RA status. Gene ontology and pathway analyses were applied for functional annotation and network visualization. Results: A cluster of 347 genes were identified that differentially downregulated expression in association with acupuncture treatment over time; specifically in rats with CIA with module-RA correlation at 1 hour after acupuncture (-0.27; p < 0.001) and at 34 days after acupuncture (-0.33; p < 0.001). Functional annotation showed highly significant enrichment of porphyrin-containing compound biosynthetic processes (p < 0.001). The network-based analysis also identified a module of 140 genes differentially expressed between CIA and non-CIA in rats (p < 0.001). This cluster of genes was enriched for antigen processing and presentation of exogenous peptide antigen (p < 0.001). Other functional gene clusters previously reported in earlier studies were also observed. Conclusion: The identified gene expression networks and their hub-genes could help with the understanding of mechanisms involved in the pathogenesis of RA, as well understanding the effects of acupuncture treatment of RA.

• Journal of Plant Biotechnology
• /
• 제37권2호
• /
• pp.115-124
• /
• 2010

As the completion of genome sequencing, large collection of expression data and the great efforts in annotating plant genomes, the next challenge is to systematically assign functions to all predicted genes in the genome. Functional genome analysis of plants has entered the high-throughput stage. The generations and collections of mutants at the genome-wide level form technological platform of functional genomics. However, to identify the exact function of unknown genes it is necessary to understand each gene's role in the complex orchestration of all gene activities in the plant cell. Gene function analysis therefore necessitates the analysis of temporal and spatial gene expression patterns. The most conclusive information about changes in gene expression levels can be gained from analysis of the varying qualitative and quantitative changes of messenger RNAs, proteins and metabolites. New technologies have been developed to allow fast and highly parallel measurements of these constituents of the cell that make up gene activity. We have reviewed currently employed technologies to identify unknown functions of predicted genes including map-based cloning, insertional mutagenesis, reverse genetics, chemical mutagenesis, microarray analysis, FOX-hunting system, gene silencing mutagenesis, proteomics and chemical genomics. Recent improvements in technologies for functional genomics enable whole-genome functional analysis, and thus open new avenues for studies of the regulations and functions of unknown genes in plants.