Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer.

PubMed

Gao, Xue-Xin; Gao, Lei; Wang, Jiu-Qiang; Qu, Su-Su; Qu, Yue; Sun, Hong-Lei; Liu, Si-Dang; Shang, Ying-Li

2016-07-12

Recent genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with risk of esophageal cancer (EC). However, investigation of genetic basis from the perspective of systematic biology and integrative genomics remains scarce.In this study, we explored genetic basis of EC based on GWAS data and implemented a series of bioinformatics methods including functional annotation, expression quantitative trait loci (eQTL) analysis, pathway enrichment analysis and pathway grouped network analysis.Two hundred and thirteen risk SNPs were identified, in which 44 SNPs were found to have significantly differential gene expression in esophageal tissues by eQTL analysis. By pathway enrichment analysis, 170 risk genes mapped by risk SNPs were enriched into 38 significant GO terms and 17 significant KEGG pathways, which were significantly grouped into 9 sub-networks by pathway grouped network analysis. The 9 groups of interconnected pathways were mainly involved with muscle cell proliferation, cellular response to interleukin-6, cell adhesion molecules, and ethanol oxidation, which might participate in the development of EC.Our findings provide genetic evidence and new insight for exploring the molecular mechanisms of EC.

ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework.

PubMed

Zhang, Kunlin; Chang, Suhua; Cui, Sijia; Guo, Liyuan; Zhang, Liuyan; Wang, Jing

2011-07-01

Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although pathway-based analysis (PBA) has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the challenge for GWAS data interpretation within one analytical framework. ICSNPathway is developed to identify candidate causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP → gene → pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.

Transcriptomic meta-analysis identifies gene expression characteristics in various samples of HIV-infected patients with nonprogressive disease.

PubMed

Zhang, Le-Le; Zhang, Zi-Ning; Wu, Xian; Jiang, Yong-Jun; Fu, Ya-Jing; Shang, Hong

2017-09-12

A small proportion of HIV-infected patients remain clinically and/or immunologically stable for years, including elite controllers (ECs) who have undetectable viremia (<50 copies/ml) and long-term nonprogressors (LTNPs) who maintain normal CD4 + T cell counts for prolonged periods (>10 years). However, the mechanism of nonprogression needs to be further resolved. In this study, a transcriptome meta-analysis was performed on nonprogressor and progressor microarray data to identify differential transcriptome pathways and potential biomarkers. Using the INMEX (integrative meta-analysis of expression data) program, we performed the meta-analysis to identify consistently differentially expressed genes (DEGs) in nonprogressors and further performed functional interpretation (gene ontology analysis and pathway analysis) of the DEGs identified in the meta-analysis. Five microarray datasets (81 cases and 98 controls in total), including whole blood, CD4 + and CD8 + T cells, were collected for meta-analysis. We determined that nonprogressors have reduced expression of important interferon-stimulated genes (ISGs), CD38, lymphocyte activation gene 3 (LAG-3) in whole blood, CD4 + and CD8 + T cells. Gene ontology (GO) analysis showed a significant enrichment in DEGs that function in the type I interferon signaling pathway. Upregulated pathways, including the PI3K-Akt signaling pathway in whole blood, cytokine-cytokine receptor interaction in CD4 + T cells and the MAPK signaling pathway in CD8 + T cells, were identified in nonprogressors compared with progressors. In each metabolic functional category, the number of downregulated DEGs was more than the upregulated DEGs, and almost all genes were downregulated DEGs in the oxidative phosphorylation (OXPHOS) and tricarboxylic acid (TCA) cycle in the three types of samples. Our transcriptomic meta-analysis provides a comprehensive evaluation of the gene expression profiles in major blood types of nonprogressors, providing new insights in the understanding of HIV pathogenesis and developing strategies to delay HIV disease progression.

Exploring pathway interactions in insulin resistant mouse liver

PubMed Central

2011-01-01

Background Complex phenotypes such as insulin resistance involve different biological pathways that may interact and influence each other. Interpretation of related experimental data would be facilitated by identifying relevant pathway interactions in the context of the dataset. Results We developed an analysis approach to study interactions between pathways by integrating gene and protein interaction networks, biological pathway information and high-throughput data. This approach was applied to a transcriptomics dataset to investigate pathway interactions in insulin resistant mouse liver in response to a glucose challenge. We identified regulated pathway interactions at different time points following the glucose challenge and also studied the underlying protein interactions to find possible mechanisms and key proteins involved in pathway cross-talk. A large number of pathway interactions were found for the comparison between the two diet groups at t = 0. The initial response to the glucose challenge (t = 0.6) was typed by an acute stress response and pathway interactions showed large overlap between the two diet groups, while the pathway interaction networks for the late response were more dissimilar. Conclusions Studying pathway interactions provides a new perspective on the data that complements established pathway analysis methods such as enrichment analysis. This study provided new insights in how interactions between pathways may be affected by insulin resistance. In addition, the analysis approach described here can be generally applied to different types of high-throughput data and will therefore be useful for analysis of other complex datasets as well. PMID:21843341

Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways

PubMed Central

Kaushik, Abhinav; Ali, Shakir; Gupta, Dinesh

2017-01-01

Gene connection rewiring is an essential feature of gene network dynamics. Apart from its normal functional role, it may also lead to dysregulated functional states by disturbing pathway homeostasis. Very few computational tools measure rewiring within gene co-expression and its corresponding regulatory networks in order to identify and prioritize altered pathways which may or may not be differentially regulated. We have developed Altered Pathway Analyzer (APA), a microarray dataset analysis tool for identification and prioritization of altered pathways, including those which are differentially regulated by TFs, by quantifying rewired sub-network topology. Moreover, APA also helps in re-prioritization of APA shortlisted altered pathways enriched with context-specific genes. We performed APA analysis of simulated datasets and p53 status NCI-60 cell line microarray data to demonstrate potential of APA for identification of several case-specific altered pathways. APA analysis reveals several altered pathways not detected by other tools evaluated by us. APA analysis of unrelated prostate cancer datasets identifies sample-specific as well as conserved altered biological processes, mainly associated with lipid metabolism, cellular differentiation and proliferation. APA is designed as a cross platform tool which may be transparently customized to perform pathway analysis in different gene expression datasets. APA is freely available at http://bioinfo.icgeb.res.in/APA. PMID:28084397

Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma

PubMed Central

Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

2014-01-01

Background Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. Principal Findings In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Conclusions Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers. PMID:24988079

Integrated analysis of mutation data from various sources identifies key genes and signaling pathways in hepatocellular carcinoma.

PubMed

Zhang, Yuannv; Qiu, Zhaoping; Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

2014-01-01

Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers.

Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.

PubMed

Li, Chunquan; Han, Junwei; Yao, Qianlan; Zou, Chendan; Xu, Yanjun; Zhang, Chunlong; Shang, Desi; Zhou, Lingyun; Zou, Chaoxia; Sun, Zeguo; Li, Jing; Zhang, Yunpeng; Yang, Haixiu; Gao, Xu; Li, Xia

2013-05-01

Various 'omics' technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.

Incorporating Information of microRNAs into Pathway Analysis in a Genome-Wide Association Study of Bipolar Disorder

PubMed Central

Shih, Wei-Liang; Kao, Chung-Feng; Chuang, Li-Chung; Kuo, Po-Hsiu

2012-01-01

MicroRNAs (miRNAs) are known to be important post-transcriptional regulators that are involved in the etiology of complex psychiatric traits. The present study aimed to incorporate miRNAs information into pathway analysis using a genome-wide association dataset to identify relevant biological pathways for bipolar disorder (BPD). We selected psychiatric- and neurological-associated miRNAs (N = 157) from PhenomiR database. The miRNA target genes (miTG) predictions were obtained from microRNA.org. Canonical pathways (N = 4,051) were downloaded from the Molecule Signature Database. We employed a novel weighting scheme for miTGs in pathway analysis using methods of gene set enrichment analysis and sum-statistic. Under four statistical scenarios, 38 significantly enriched pathways (P-value < 0.01 after multiple testing correction) were identified for the risk of developing BPD, including pathways of ion channels associated (e.g., gated channel activity, ion transmembrane transporter activity, and ion channel activity) and nervous related biological processes (e.g., nervous system development, cytoskeleton, and neuroactive ligand receptor interaction). Among them, 19 were identified only when the weighting scheme was applied. Many miRNA-targeted genes were functionally related to ion channels, collagen, and axonal growth and guidance that have been suggested to be associated with BPD previously. Some of these genes are linked to the regulation of miRNA machinery in the literature. Our findings provide support for the potential involvement of miRNAs in the psychopathology of BPD. Further investigations to elucidate the functions and mechanisms of identified candidate pathways are needed. PMID:23264780

Pathway analysis of genome-wide association datasets of personality traits.

PubMed

Kim, H-N; Kim, B-H; Cho, J; Ryu, S; Shin, H; Sung, J; Shin, C; Cho, N H; Sung, Y A; Choi, B-O; Kim, H-L

2015-04-01

Although several genome-wide association (GWA) studies of human personality have been recently published, genetic variants that are highly associated with certain personality traits remain unknown, due to difficulty reproducing results. To further investigate these genetic variants, we assessed biological pathways using GWA datasets. Pathway analysis using GWA data was performed on 1089 Korean women whose personality traits were measured with the Revised NEO Personality Inventory for the 5-factor model of personality. A total of 1042 pathways containing 8297 genes were included in our study. Of these, 14 pathways were highly enriched with association signals that were validated in 1490 independent samples. These pathways include association of: Neuroticism with axon guidance [L1 cell adhesion molecule (L1CAM) interactions]; Extraversion with neuronal system and voltage-gated potassium channels; Agreeableness with L1CAM interaction, neurotransmitter receptor binding and downstream transmission in postsynaptic cells; and Conscientiousness with the interferon-gamma and platelet-derived growth factor receptor beta polypeptide pathways. Several genes that contribute to top-ranked pathways in this study were previously identified in GWA studies or by pathway analysis in schizophrenia or other neuropsychiatric disorders. Here we report the first pathway analysis of all five personality traits. Importantly, our analysis identified novel pathways that contribute to understanding the etiology of personality traits. © 2015 The Authors. Genes, Brain and Behavior published by International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd.

Proteomic analysis reveals diverse proline hydroxylation-mediated oxygen-sensing cellular pathways in cancer cells

PubMed Central

Liu, Bing; Gao, Yankun; Ruan, Hai-Bin; Chen, Yue

2016-01-01

Proline hydroxylation is a critical cellular mechanism regulating oxygen-response pathways in tumor initiation and progression. Yet, its substrate diversity and functions remain largely unknown. Here, we report a system-wide analysis to characterize proline hydroxylation substrates in cancer cells using an immunoaffinity-purification assisted proteomics strategy. We identified 562 sites from 272 proteins in HeLa cells. Bioinformatic analysis revealed that proline hydroxylation substrates are significantly enriched with mRNA processing and stress-response cellular pathways with canonical and diverse flanking sequence motifs. Structural analysis indicates a significant enrichment of proline hydroxylation participating in the secondary structure of substrate proteins. Our study identified and validated Brd4, a key transcription factor, as a novel proline hydroxylation substrate. Functional analysis showed that the inhibition of proline hydroxylation pathway significantly reduced the proline hydroxylation abundance on Brd4 and affected Brd4-mediated transcriptional activity as well as cell proliferation in AML leukemia cells. Taken together, our study identified a broad regulatory role of proline hydroxylation in cellular oxygen-sensing pathways and revealed potentially new targets that dynamically respond to hypoxia microenvironment in tumor cells. PMID:27764789

Genome-wide pathway-based association analysis identifies risk pathways associated with Parkinson's disease.

PubMed

Zhang, Mingming; Mu, Hongbo; Shang, Zhenwei; Kang, Kai; Lv, Hongchao; Duan, Lian; Li, Jin; Chen, Xinren; Teng, Yanbo; Jiang, Yongshuai; Zhang, Ruijie

2017-01-06

Parkinson's disease (PD) is the second most common neurodegenerative disease. It is generally believed that it is influenced by both genetic and environmental factors, but the precise pathogenesis of PD is unknown to date. In this study, we performed a pathway analysis based on genome-wide association study (GWAS) to detect risk pathways of PD in three GWAS datasets. We first mapped all SNP markers to autosomal genes in each GWAS dataset. Then, we evaluated gene risk values using the minimum P-value of the tagSNPs. We took a pathway as a unit to identify the risk pathways based on the cumulative risks of the genes in the pathway. Finally, we combine the analysis results of the three datasets to detect the high risk pathways associated with PD. We found there were five same pathways in the three datasets. Besides, we also found there were five pathways which were shared in two datasets. Most of these pathways are associated with nervoussystem. Five pathways had been reported to be PD-related pathways in the previous literature. Our findings also implied that there was a close association between immune response and PD. Continued investigation of these pathways will further help us explain the pathogenesis of PD. Copyright © 2016. Published by Elsevier Ltd.

Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

PubMed

van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

2015-01-01

Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

Identification of personalized dysregulated pathways in hepatocellular carcinoma.

PubMed

Li, Hong; Jiang, Xiumei; Zhu, Shengjie; Sui, Lihong

2017-04-01

Hepatocellular carcinoma (HCC) is the most common liver malignancy, and ranks the fifth most prevalent malignant tumors worldwide. In general, HCC are detected until the disease is at an advanced stage and may miss the best chance for treatment. Thus, elucidating the molecular mechanisms is critical to clinical diagnosis and treatment for HCC. The purpose of this study was to identify dysregulated pathways of great potential functional relevance in the progression of HCC. Microarray data of 72 pairs of tumor and matched non-tumor surrounding tissues of HCC were transformed to gene expression data. Differentially expressed genes (DEG) between patients and normal controls were identified using Linear Models for Microarray Analysis. Personalized dysregulated pathways were identified using individualized pathway aberrance score module. 169 differentially expressed genes (DEG) were obtained with |logFC|≥1.5 and P≤0.01. 749 dysregulated pathways were obtained with P≤0.01 in pathway statistics, and there were 93 DEG overlapped in the dysregulated pathways. After performing normal distribution analysis, 302 pathways with the aberrance probability≥0.5 were identified. By ranking pathway with aberrance probability, the top 20 pathways were obtained. Only three DEGs (TUBA1C, TPR, CDC20) were involved in the top 20 pathways. These personalized dysregulated pathways and overlapped genes may give new insights into the underlying biological mechanisms in the progression of HCC. Particular attention can be focused on them for further research. Copyright © 2017 Elsevier GmbH. All rights reserved.

Personalized identification of differentially expressed pathways in pediatric sepsis.

PubMed

Li, Binjie; Zeng, Qiyi

2017-10-01

Sepsis is a leading killer of children worldwide with numerous differentially expressed genes reported to be associated with sepsis. Identifying core pathways in an individual is important for understanding septic mechanisms and for the future application of custom therapeutic decisions. Samples used in the study were from a control group (n=18) and pediatric sepsis group (n=52). Based on Kauffman's attractor theory, differentially expressed pathways associated with pediatric sepsis were detected as attractors. When the distribution results of attractors are consistent with the distribution of total data assessed using support vector machine, the individualized pathway aberrance score (iPAS) was calculated to distinguish differences. Through attractor and Kyoto Encyclopedia of Genes and Genomes functional analysis, 277 enriched pathways were identified as attractors. There were 81 pathways with P<0.05 and 59 pathways with P<0.01. Distribution outcomes of screened attractors were mostly consistent with the total data demonstrated by the six classifying parameters, which suggested the efficiency of attractors. Cluster analysis of pediatric sepsis using the iPAS method identified seven pathway clusters and four sample clusters. Thus, in the majority pediatric sepsis samples, core pathways can be detected as different from accumulated normal samples. In conclusion, a novel procedure that identified the dysregulated attractors in individuals with pediatric sepsis was constructed. Attractors can be markers to identify pathways involved in pediatric sepsis. iPAS may provide a correlation score for each of the signaling pathways present in an individual patient. This process may improve the personalized interpretation of disease mechanisms and may be useful in the forthcoming era of personalized medicine.

A novel approach to select differential pathways associated with hypertrophic cardiomyopathy based on gene co‑expression analysis.

PubMed

Chen, Xiao-Min; Feng, Ming-Jun; Shen, Cai-Jie; He, Bin; Du, Xian-Feng; Yu, Yi-Bo; Liu, Jing; Chu, Hui-Min

2017-07-01

The present study was designed to develop a novel method for identifying significant pathways associated with human hypertrophic cardiomyopathy (HCM), based on gene co‑expression analysis. The microarray dataset associated with HCM (E‑GEOD‑36961) was obtained from the European Molecular Biology Laboratory‑European Bioinformatics Institute database. Informative pathways were selected based on the Reactome pathway database and screening treatments. An empirical Bayes method was utilized to construct co‑expression networks for informative pathways, and a weight value was assigned to each pathway. Differential pathways were extracted based on weight threshold, which was calculated using a random model. In order to assess whether the co‑expression method was feasible, it was compared with traditional pathway enrichment analysis of differentially expressed genes, which were identified using the significance analysis of microarrays package. A total of 1,074 informative pathways were screened out for subsequent investigations and their weight values were also obtained. According to the threshold of weight value of 0.01057, 447 differential pathways, including folding of actin by chaperonin containing T‑complex protein 1 (CCT)/T‑complex protein 1 ring complex (TRiC), purine ribonucleoside monophosphate biosynthesis and ubiquinol biosynthesis, were obtained. Compared with traditional pathway enrichment analysis, the number of pathways obtained from the co‑expression approach was increased. The results of the present study demonstrated that this method may be useful to predict marker pathways for HCM. The pathways of folding of actin by CCT/TRiC and purine ribonucleoside monophosphate biosynthesis may provide evidence of the underlying molecular mechanisms of HCM, and offer novel therapeutic directions for HCM.

The BCL2 antagonist of cell death pathway influences endometrial cancer cell sensitivity to cisplatin.

PubMed

Chon, Hye Sook; Marchion, Douglas C; Xiong, Yin; Chen, Ning; Bicaku, Elona; Stickles, Xiaomang Ba; Bou Zgheib, Nadim; Judson, Patricia L; Hakam, Ardeshir; Gonzalez-Bosquet, Jesus; Wenham, Robert M; Apte, Sachin M; Lancaster, Johnathan M

2012-01-01

To identify pathways that influence endometrial cancer (EC) cell sensitivity to cisplatin and to characterize the BCL2 antagonist of cell death (BAD) pathway as a therapeutic target to increase cisplatin sensitivity. Eight EC cell lines (Ishikawa, MFE296, RL 95-2, AN3CA, KLE, MFE280, MFE319, HEC-1-A) were subjected to Affymetrix Human U133A GeneChip expression analysis of approximately 22,000 probe sets. In parallel, endometrial cell line sensitivity to cisplatin was quantified by MTS assay, and IC(50) values were calculated. Pearson's correlation test was used to identify genes associated with response to cisplatin. Genes associated with cisplatin responsiveness were subjected to pathway analysis. The BAD pathway was identified and subjected to targeted modulation, and the effect on cisplatin sensitivity was evaluated. Pearson's correlation analysis identified 1443 genes associated with cisplatin resistance (P<0.05), which included representation of the BAD-apoptosis pathway. Small interfering RNA (siRNA) knockdown of BAD pathway protein phosphatase PP2C expression was associated with increased phosphorylated BAD (serine-155) levels and a parallel increase in cisplatin resistance in Ishikawa (P=0.004) and HEC-1-A (P=0.02) cell lines. In contrast, siRNA knockdown of protein kinase A expression increased cisplatin sensitivity in the Ishikawa (P=0.02) cell line. The BAD pathway influences EC cell sensitivity to cisplatin, likely via modulation of the phosphorylation status of the BAD protein. The BAD pathway represents an appealing therapeutic target to increase EC cell sensitivity to cisplatin. Copyright © 2011 Elsevier Inc. All rights reserved.

Text mining-based in silico drug discovery in oral mucositis caused by high-dose cancer therapy.

PubMed

Kirk, Jon; Shah, Nirav; Noll, Braxton; Stevens, Craig B; Lawler, Marshall; Mougeot, Farah B; Mougeot, Jean-Luc C

2018-08-01

Oral mucositis (OM) is a major dose-limiting side effect of chemotherapy and radiation used in cancer treatment. Due to the complex nature of OM, currently available drug-based treatments are of limited efficacy. Our objectives were (i) to determine genes and molecular pathways associated with OM and wound healing using computational tools and publicly available data and (ii) to identify drugs formulated for topical use targeting the relevant OM molecular pathways. OM and wound healing-associated genes were determined by text mining, and the intersection of the two gene sets was selected for gene ontology analysis using the GeneCodis program. Protein interaction network analysis was performed using STRING-db. Enriched gene sets belonging to the identified pathways were queried against the Drug-Gene Interaction database to find drug candidates for topical use in OM. Our analysis identified 447 genes common to both the "OM" and "wound healing" text mining concepts. Gene enrichment analysis yielded 20 genes representing six pathways and targetable by a total of 32 drugs which could possibly be formulated for topical application. A manual search on ClinicalTrials.gov confirmed no relevant pathway/drug candidate had been overlooked. Twenty-five of the 32 drugs can directly affect the PTGS2 (COX-2) pathway, the pathway that has been targeted in previous clinical trials with limited success. Drug discovery using in silico text mining and pathway analysis tools can facilitate the identification of existing drugs that have the potential of topical administration to improve OM treatment.

Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data.

PubMed

Lee, Hyeonjeong; Shin, Miyoung

2017-01-01

The problem of discovering genetic markers as disease signatures is of great significance for the successful diagnosis, treatment, and prognosis of complex diseases. Even if many earlier studies worked on identifying disease markers from a variety of biological resources, they mostly focused on the markers of genes or gene-sets (i.e., pathways). However, these markers may not be enough to explain biological interactions between genetic variables that are related to diseases. Thus, in this study, our aim is to investigate distinctive associations among active pathways (i.e., pathway-sets) shown each in case and control samples which can be observed from gene expression and/or methylation data. The pathway-sets are obtained by identifying a set of associated pathways that are often active together over a significant number of class samples. For this purpose, gene expression or methylation profiles are first analyzed to identify significant (active) pathways via gene-set enrichment analysis. Then, regarding these active pathways, an association rule mining approach is applied to examine interesting pathway-sets in each class of samples (case or control). By doing so, the sets of associated pathways often working together in activity profiles are finally chosen as our distinctive signature of each class. The identified pathway-sets are aggregated into a pathway activity network (PAN), which facilitates the visualization of differential pathway associations between case and control samples. From our experiments with two publicly available datasets, we could find interesting PAN structures as the distinctive signatures of breast cancer and uterine leiomyoma cancer, respectively. Our pathway-set markers were shown to be superior or very comparable to other genetic markers (such as genes or gene-sets) in disease classification. Furthermore, the PAN structure, which can be constructed from the identified markers of pathway-sets, could provide deeper insights into distinctive associations between pathway activities in case and control samples.

A Cross-Cancer Genetic Association Analysis of the DNA Repair and DNA Damage Signaling Pathways for Lung, Ovary, Prostate, Breast, and Colorectal Cancer.

PubMed

Scarbrough, Peter M; Weber, Rachel Palmieri; Iversen, Edwin S; Brhane, Yonathan; Amos, Christopher I; Kraft, Peter; Hung, Rayjean J; Sellers, Thomas A; Witte, John S; Pharoah, Paul; Henderson, Brian E; Gruber, Stephen B; Hunter, David J; Garber, Judy E; Joshi, Amit D; McDonnell, Kevin; Easton, Doug F; Eeles, Ros; Kote-Jarai, Zsofia; Muir, Kenneth; Doherty, Jennifer A; Schildkraut, Joellen M

2016-01-01

DNA damage is an established mediator of carcinogenesis, although genome-wide association studies (GWAS) have identified few significant loci. This cross-cancer site, pooled analysis was performed to increase the power to detect common variants of DNA repair genes associated with cancer susceptibility. We conducted a cross-cancer analysis of 60,297 single nucleotide polymorphisms, at 229 DNA repair gene regions, using data from the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) Network. Our analysis included data from 32 GWAS and 48,734 controls and 51,537 cases across five cancer sites (breast, colon, lung, ovary, and prostate). Because of the unavailability of individual data, data were analyzed at the aggregate level. Meta-analysis was performed using the Association analysis for SubSETs (ASSET) software. To test for genetic associations that might escape individual variant testing due to small effect sizes, pathway analysis of eight DNA repair pathways was performed using hierarchical modeling. We identified three susceptibility DNA repair genes, RAD51B (P < 5.09 × 10(-6)), MSH5 (P < 5.09 × 10(-6)), and BRCA2 (P = 5.70 × 10(-6)). Hierarchical modeling identified several pleiotropic associations with cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways. Only three susceptibility loci were identified, which had all been previously reported. In contrast, hierarchical modeling identified several pleiotropic cancer risk associations in key DNA repair pathways. Results suggest that many common variants in DNA repair genes are likely associated with cancer susceptibility through small effect sizes that do not meet stringent significance testing criteria. ©2015 American Association for Cancer Research.

Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways

PubMed Central

Li, Chunquan; Han, Junwei; Yao, Qianlan; Zou, Chendan; Xu, Yanjun; Zhang, Chunlong; Shang, Desi; Zhou, Lingyun; Zou, Chaoxia; Sun, Zeguo; Li, Jing; Zhang, Yunpeng; Yang, Haixiu; Gao, Xu; Li, Xia

2013-01-01

Various ‘omics’ technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways. PMID:23482392

Identification of differential pathways in papillary thyroid carcinoma utilizing pathway co-expression analysis.

PubMed

Qiu, Wei-Hai; Chen, Gui-Yan; Cui, Lu; Zhang, Ting-Ming; Wei, Feng; Yang, Yong

2016-01-01

To identify differential pathways between papillary thyroid carcinoma (PTC) patients and normal controls utilizing a novel method which combined pathway with co-expression network. The proposed method included three steps. In the first step, we conducted pretreatments for background pathways and gained representative pathways in PTC. Subsequently, a co-expression network for representative pathways was constructed using empirical Bayes (EB) approach to assign a weight value for each pathway. Finally, random model was extracted to set the thresholds of identifying differential pathways. We obtained 1267 representative pathways and their weight values based on the co-expressed pathway network, and then by meeting the criterion (Weight > 0.0296), 87 differential pathways in total across PTC patients and normal controls were identified. The top three ranked differential pathways were CREB phosphorylation, attachment of GPI anchor to urokinase plasminogen activator receptor (uPAR) and loss of function of SMAD2/3 in cancer. In conclusion, we successfully identified differential pathways (such as CREB phosphorylation, attachment of GPI anchor to uPAR and post-translational modification: synthesis of GPI-anchored proteins) for PTC using the proposed pathway co-expression method, and these pathways might be potential biomarkers for target therapy and detection of PTC.

Elementary Mode Analysis: A Useful Metabolic Pathway Analysis Tool for Characterizing Cellular Metabolism

PubMed Central

Trinh, Cong T.; Wlaschin, Aaron; Srienc, Friedrich

2010-01-01

Elementary Mode Analysis is a useful Metabolic Pathway Analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering. PMID:19015845

Reconstruction of metabolic pathways for the cattle genome

PubMed Central

Seo, Seongwon; Lewin, Harris A

2009-01-01

Background Metabolic reconstruction of microbial, plant and animal genomes is a necessary step toward understanding the evolutionary origins of metabolism and species-specific adaptive traits. The aims of this study were to reconstruct conserved metabolic pathways in the cattle genome and to identify metabolic pathways with missing genes and proteins. The MetaCyc database and PathwayTools software suite were chosen for this work because they are widely used and easy to implement. Results An amalgamated cattle genome database was created using the NCBI and Ensembl cattle genome databases (based on build 3.1) as data sources. PathwayTools was used to create a cattle-specific pathway genome database, which was followed by comprehensive manual curation for the reconstruction of metabolic pathways. The curated database, CattleCyc 1.0, consists of 217 metabolic pathways. A total of 64 mammalian-specific metabolic pathways were modified from the reference pathways in MetaCyc, and two pathways previously identified but missing from MetaCyc were added. Comparative analysis of metabolic pathways revealed the absence of mammalian genes for 22 metabolic enzymes whose activity was reported in the literature. We also identified six human metabolic protein-coding genes for which the cattle ortholog is missing from the sequence assembly. Conclusion CattleCyc is a powerful tool for understanding the biology of ruminants and other cetartiodactyl species. In addition, the approach used to develop CattleCyc provides a framework for the metabolic reconstruction of other newly sequenced mammalian genomes. It is clear that metabolic pathway analysis strongly reflects the quality of the underlying genome annotations. Thus, having well-annotated genomes from many mammalian species hosted in BioCyc will facilitate the comparative analysis of metabolic pathways among different species and a systems approach to comparative physiology. PMID:19284618

Methods and approaches in the topology-based analysis of biological pathways

PubMed Central

Mitrea, Cristina; Taghavi, Zeinab; Bokanizad, Behzad; Hanoudi, Samer; Tagett, Rebecca; Donato, Michele; Voichiţa, Călin; Drăghici, Sorin

2013-01-01

The goal of pathway analysis is to identify the pathways significantly impacted in a given phenotype. Many current methods are based on algorithms that consider pathways as simple gene lists, dramatically under-utilizing the knowledge that such pathways are meant to capture. During the past few years, a plethora of methods claiming to incorporate various aspects of the pathway topology have been proposed. These topology-based methods, sometimes referred to as “third generation,” have the potential to better model the phenomena described by pathways. Although there is now a large variety of approaches used for this purpose, no review is currently available to offer guidance for potential users and developers. This review covers 22 such topology-based pathway analysis methods published in the last decade. We compare these methods based on: type of pathways analyzed (e.g., signaling or metabolic), input (subset of genes, all genes, fold changes, gene p-values, etc.), mathematical models, pathway scoring approaches, output (one or more pathway scores, p-values, etc.) and implementation (web-based, standalone, etc.). We identify and discuss challenges, arising both in methodology and in pathway representation, including inconsistent terminology, different data formats, lack of meaningful benchmarks, and the lack of tissue and condition specificity. PMID:24133454

A Method for Gene-Based Pathway Analysis Using Genomewide Association Study Summary Statistics Reveals Nine New Type 1 Diabetes Associations

PubMed Central

Evangelou, Marina; Smyth, Deborah J; Fortune, Mary D; Burren, Oliver S; Walker, Neil M; Guo, Hui; Onengut-Gumuscu, Suna; Chen, Wei-Min; Concannon, Patrick; Rich, Stephen S; Todd, John A; Wallace, Chris

2014-01-01

Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed () with 12 of the 22 SNPs showing . Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, ), NRP1 (rs722988, ), BAD (rs694739, ), CTSB (rs1296023, ), FYN (rs11964650, ), UBE2G1 (rs9906760, ), MAP3K14 (rs17759555, ), ITGB1 (rs1557150, ), and IL7R (rs1445898, ). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available. PMID:25371288

An integrative somatic mutation analysis to identify pathways linked with survival outcomes across 19 cancer types

PubMed Central

Park, Sunho; Kim, Seung-Jun; Yu, Donghyeon; Peña-Llopis, Samuel; Gao, Jianjiong; Park, Jin Suk; Chen, Beibei; Norris, Jessie; Wang, Xinlei; Chen, Min; Kim, Minsoo; Yong, Jeongsik; Wardak, Zabi; Choe, Kevin; Story, Michael; Starr, Timothy; Cheong, Jae-Ho; Hwang, Tae Hyun

2016-01-01

Motivation: Identification of altered pathways that are clinically relevant across human cancers is a key challenge in cancer genomics. Precise identification and understanding of these altered pathways may provide novel insights into patient stratification, therapeutic strategies and the development of new drugs. However, a challenge remains in accurately identifying pathways altered by somatic mutations across human cancers, due to the diverse mutation spectrum. We developed an innovative approach to integrate somatic mutation data with gene networks and pathways, in order to identify pathways altered by somatic mutations across cancers. Results: We applied our approach to The Cancer Genome Atlas (TCGA) dataset of somatic mutations in 4790 cancer patients with 19 different types of tumors. Our analysis identified cancer-type-specific altered pathways enriched with known cancer-relevant genes and targets of currently available drugs. To investigate the clinical significance of these altered pathways, we performed consensus clustering for patient stratification using member genes in the altered pathways coupled with gene expression datasets from 4870 patients from TCGA, and multiple independent cohorts confirmed that the altered pathways could be used to stratify patients into subgroups with significantly different clinical outcomes. Of particular significance, certain patient subpopulations with poor prognosis were identified because they had specific altered pathways for which there are available targeted therapies. These findings could be used to tailor and intensify therapy in these patients, for whom current therapy is suboptimal. Availability and implementation: The code is available at: http://www.taehyunlab.org. Contact: jhcheong@yuhs.ac or taehyun.hwang@utsouthwestern.edu or taehyun.cs@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26635139

Algorithms on Flag Manifolds for Knowledge Discovery in N-way Arrays

DTIC Science & Technology

2015-11-20

that three of 18 subjects will become symptomatic after only 8 hours. Host pathway analysis of a human endotoxin gene expression data set revealed a 14...pathway analysis of a human endotoxin gene expression data set revealed a 14 pathway signature that identified symptomatic subjects within 2-3 hours post

Identifying novel glioma associated pathways based on systems biology level meta-analysis.

PubMed

Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

2013-01-01

With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

Integrated genomic approaches identify major pathways and upstream regulators in late onset Alzheimer’s disease

PubMed Central

Li, Xinzhong; Long, Jintao; He, Taigang; Belshaw, Robert; Scott, James

2015-01-01

Previous studies have evaluated gene expression in Alzheimer’s disease (AD) brains to identify mechanistic processes, but have been limited by the size of the datasets studied. Here we have implemented a novel meta-analysis approach to identify differentially expressed genes (DEGs) in published datasets comprising 450 late onset AD (LOAD) brains and 212 controls. We found 3124 DEGs, many of which were highly correlated with Braak stage and cerebral atrophy. Pathway Analysis revealed the most perturbed pathways to be (a) nitric oxide and reactive oxygen species in macrophages (NOROS), (b) NFkB and (c) mitochondrial dysfunction. NOROS was also up-regulated, and mitochondrial dysfunction down-regulated, in healthy ageing subjects. Upstream regulator analysis predicted the TLR4 ligands, STAT3 and NFKBIA, for activated pathways and RICTOR for mitochondrial genes. Protein-protein interaction network analysis emphasised the role of NFKB; identified a key interaction of CLU with complement; and linked TYROBP, TREM2 and DOK3 to modulation of LPS signalling through TLR4 and to phosphatidylinositol metabolism. We suggest that NEUROD6, ZCCHC17, PPEF1 and MANBAL are potentially implicated in LOAD, with predicted links to calcium signalling and protein mannosylation. Our study demonstrates a highly injurious combination of TLR4-mediated NFKB signalling, NOROS inflammatory pathway activation, and mitochondrial dysfunction in LOAD. PMID:26202100

Pathway-driven gene stability selection of two rheumatoid arthritis GWAS identifies and validates new susceptibility genes in receptor mediated signalling pathways.

PubMed

Eleftherohorinou, Hariklia; Hoggart, Clive J; Wright, Victoria J; Levin, Michael; Coin, Lachlan J M

2011-09-01

Rheumatoid arthritis (RA) is the commonest chronic, systemic, inflammatory disorder affecting ∼1% of the world population. It has a strong genetic component and a growing number of associated genes have been discovered in genome-wide association studies (GWAS), which nevertheless only account for 23% of the total genetic risk. We aimed to identify additional susceptibility loci through the analysis of GWAS in the context of biological function. We bridge the gap between pathway and gene-oriented analyses of GWAS, by introducing a pathway-driven gene stability-selection methodology that identifies potential causal genes in the top-associated disease pathways that may be driving the pathway association signals. We analysed the WTCCC and the NARAC studies of ∼5000 and ∼2000 subjects, respectively. We examined 700 pathways comprising ∼8000 genes. Ranking pathways by significance revealed that the NARAC top-ranked ∼6% laid within the top 10% of WTCCC. Gene selection on those pathways identified 58 genes in WTCCC and 61 in NARAC; 21 of those were common (P(overlap)< 10(-21)), of which 16 were novel discoveries. Among the identified genes, we validated 10 known RA associations in WTCCC and 13 in NARAC, not discovered using single-SNP approaches on the same data. Gene ontology functional enrichment analysis on the identified genes showed significant over-representation of signalling activity (P< 10(-29)) in both studies. Our findings suggest a novel model of RA genetic predisposition, which involves cell-membrane receptors and genes in second messenger signalling systems, in addition to genes that regulate immune responses, which have been the focus of interest previously.

Whole-Genome Analysis of the SHORT-ROOT Developmental Pathway in Arabidopsis

PubMed Central

Busch, Wolfgang; Cui, Hongchang; Wang, Jean Y; Blilou, Ikram; Hassan, Hala; Nakajima, Keiji; Matsumoto, Noritaka; Lohmann, Jan U; Scheres, Ben

2006-01-01

Stem cell function during organogenesis is a key issue in developmental biology. The transcription factor SHORT-ROOT (SHR) is a critical component in a developmental pathway regulating both the specification of the root stem cell niche and the differentiation potential of a subset of stem cells in the Arabidopsis root. To obtain a comprehensive view of the SHR pathway, we used a statistical method called meta-analysis to combine the results of several microarray experiments measuring the changes in global expression profiles after modulating SHR activity. Meta-analysis was first used to identify the direct targets of SHR by combining results from an inducible form of SHR driven by its endogenous promoter, ectopic expression, followed by cell sorting and comparisons of mutant to wild-type roots. Eight putative direct targets of SHR were identified, all with expression patterns encompassing subsets of the native SHR expression domain. Further evidence for direct regulation by SHR came from binding of SHR in vivo to the promoter regions of four of the eight putative targets. A new role for SHR in the vascular cylinder was predicted from the expression pattern of several direct targets and confirmed with independent markers. The meta-analysis approach was then used to perform a global survey of the SHR indirect targets. Our analysis suggests that the SHR pathway regulates root development not only through a large transcription regulatory network but also through hormonal pathways and signaling pathways using receptor-like kinases. Taken together, our results not only identify the first nodes in the SHR pathway and a new function for SHR in the development of the vascular tissue but also reveal the global architecture of this developmental pathway. PMID:16640459

Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

PubMed

Gao, Haiyan; Yang, Mei; Zhang, Xiaolan

2018-04-01

The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

Pathway Analysis of Metabolic Syndrome Using a Genome-Wide Association Study of Korea Associated Resource (KARE) Cohorts.

PubMed

Shim, Unjin; Kim, Han-Na; Sung, Yeon-Ah; Kim, Hyung-Lae

2014-12-01

Metabolic syndrome (MetS) is a complex disorder related to insulin resistance, obesity, and inflammation. Genetic and environmental factors also contribute to the development of MetS, and through genome-wide association studies (GWASs), important susceptibility loci have been identified. However, GWASs focus more on individual single-nucleotide polymorphisms (SNPs), explaining only a small portion of genetic heritability. To overcome this limitation, pathway analyses are being applied to GWAS datasets. The aim of this study is to elucidate the biological pathways involved in the pathogenesis of MetS through pathway analysis. Cohort data from the Korea Associated Resource (KARE) was used for analysis, which include 8,842 individuals (age, 52.2 ± 8.9 years; body mass index, 24.6 ± 3.2 kg/m(2)). A total of 312,121 autosomal SNPs were obtained after quality control. Pathway analysis was conducted using Meta-analysis Gene-Set Enrichment of Variant Associations (MAGENTA) to discover the biological pathways associated with MetS. In the discovery phase, SNPs from chromosome 12, including rs11066280, rs2074356, and rs12229654, were associated with MetS (p < 5 × 10(-6)), and rs11066280 satisfied the Bonferroni-corrected cutoff (unadjusted p < 1.38 × 10(-7), Bonferroni-adjusted p < 0.05). Through pathway analysis, biological pathways, including electron carrier activity, signaling by platelet-derived growth factor (PDGF), the mitogen-activated protein kinase kinase kinase cascade, PDGF binding, peroxisome proliferator-activated receptor (PPAR) signaling, and DNA repair, were associated with MetS. Through pathway analysis of MetS, pathways related with PDGF, mitogen-activated protein kinase, and PPAR signaling, as well as nucleic acid binding, protein secretion, and DNA repair, were identified. Further studies will be needed to clarify the genetic pathogenesis leading to MetS.

Pathways to Medical Home Recognition: A Qualitative Comparative Analysis of the PCMH Transformation Process.

PubMed

Mendel, Peter; Chen, Emily K; Green, Harold D; Armstrong, Courtney; Timbie, Justin W; Kress, Amii M; Friedberg, Mark W; Kahn, Katherine L

2017-12-15

To understand the process of practice transformation by identifying pathways for attaining patient-centered medical home (PCMH) recognition. The CMS Federally Qualified Health Center (FQHC) Advanced Primary Care Practice Demonstration was designed to help FQHCs achieve NCQA Level 3 PCMH recognition and improve patient outcomes. We used a stratified random sample of 20 (out of 503) participating sites for this analysis. We developed a conceptual model of structural, cultural, and implementation factors affecting PCMH transformation based on literature and initial qualitative interview themes. We then used conventional cross-case analysis, followed by qualitative comparative analysis (QCA), a cross-case method based on Boolean logic algorithms, to systematically identify pathways (i.e., combinations of factors) associated with attaining-or not attaining-Level 3 recognition. Site-level indicators were derived from semistructured interviews with site leaders at two points in time (mid- and late-implementation) and administrative data collected prior to and during the demonstration period. The QCA results identified five distinct pathways to attaining PCMH recognition and four distinct pathways to not attaining recognition by the end of the demonstration. Across these pathways, one condition (change leader capacity) was common to all pathways for attaining recognition, and another (previous improvement or recognition experience) was absent in all pathways for not attaining recognition. In general, sites could compensate for deficiencies in one factor with capacity in others, but they needed a threshold of strengths in cultural and implementation factors to attain PCMH recognition. Future efforts at primary care transformation should take into account multiple pathways sites may pursue. Sites should be assessed on key cultural and implementation factors, in addition to structural components, in order to differentiate interventions and technical assistance. © Health Research and Educational Trust.

A Combined Pathway and Regional Heritability Analysis Indicates NETRIN1 Pathway Is Associated With Major Depressive Disorder.

PubMed

Zeng, Yanni; Navarro, Pau; Fernandez-Pujals, Ana M; Hall, Lynsey S; Clarke, Toni-Kim; Thomson, Pippa A; Smith, Blair H; Hocking, Lynne J; Padmanabhan, Sandosh; Hayward, Caroline; MacIntyre, Donald J; Wray, Naomi R; Deary, Ian J; Porteous, David J; Haley, Chris S; McIntosh, Andrew M

2017-02-15

Genome-wide association studies (GWASs) of major depressive disorder (MDD) have identified few significant associations. Testing the aggregation of genetic variants, in particular biological pathways, may be more powerful. Regional heritability analysis can be used to detect genomic regions that contribute to disease risk. We integrated pathway analysis and multilevel regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS samples [Generation Scotland: The Scottish Family Health Study (GS:SFHS, N = 6455) and Psychiatric Genomics Consortium (PGC:MDD) (N = 18,759)]. A polygenic risk score (PRS) composed of single nucleotide polymorphisms from the pathway most consistently associated with MDD was created, and its accuracy to predict MDD, using area under the curve, logistic regression, and linear mixed model analyses, was tested. In GS:SFHS, four pathways were significantly associated with MDD, and two of these explained a significant amount of pathway-level regional heritability. In PGC:MDD, one pathway was significantly associated with MDD. Pathway-level regional heritability was significant in this pathway in one subset of PGC:MDD. For both samples the regional heritabilities were further localized to the gene and subregion levels. The NETRIN1 signaling pathway showed the most consistent association with MDD across the two samples. PRSs from this pathway showed competitive predictive accuracy compared with the whole-genome PRSs when using area under the curve statistics, logistic regression, and linear mixed model. These post-GWAS analyses highlight the value of combining multiple methods on multiple GWAS data for the identification of risk pathways for MDD. The NETRIN1 signaling pathway is identified as a candidate pathway for MDD and should be explored in further large population studies. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Gene Expression Profiling Identifies Downregulation of the Neurotrophin-MAPK Signaling Pathway in Female Diabetic Peripheral Neuropathy Patients.

PubMed

Luo, Lin; Zhou, Wen-Hua; Cai, Jiang-Jia; Feng, Mei; Zhou, Mi; Hu, Su-Pei; Xu, Jin; Ji, Lin-Dan

2017-01-01

Diabetic peripheral neuropathy (DPN) is a common complication of diabetes mellitus (DM). It is not diagnosed or managed properly in the majority of patients because its pathogenesis remains controversial. In this study, human whole genome microarrays identified 2898 and 4493 differentially expressed genes (DEGs) in DM and DPN patients, respectively. A further KEGG pathway analysis indicated that DPN and DM share four pathways, including apoptosis, B cell receptor signaling pathway, endocytosis, and Toll-like receptor signaling pathway. The DEGs identified through comparison of DPN and DM were significantly enriched in MAPK signaling pathway, NOD-like receptor signaling pathway, and neurotrophin signaling pathway, while the "neurotrophin-MAPK signaling pathway" was notably downregulated. Seven DEGs from the neurotrophin-MAPK signaling pathway were validated in additional 78 samples, and the results confirmed the initial microarray findings. These findings demonstrated that downregulation of the neurotrophin-MAPK signaling pathway may be the major mechanism of DPN pathogenesis, thus providing a potential approach for DPN treatment.

Enriched pathways for major depressive disorder identified from a genome-wide association study.

PubMed

Kao, Chung-Feng; Jia, Peilin; Zhao, Zhongming; Kuo, Po-Hsiu

2012-11-01

Major depressive disorder (MDD) has caused a substantial burden of disease worldwide with moderate heritability. Despite efforts through conducting numerous association studies and now, genome-wide association (GWA) studies, the success of identifying susceptibility loci for MDD has been limited, which is partially attributed to the complex nature of depression pathogenesis. A pathway-based analytic strategy to investigate the joint effects of various genes within specific biological pathways has emerged as a powerful tool for complex traits. The present study aimed to identify enriched pathways for depression using a GWA dataset for MDD. For each gene, we estimated its gene-wise p value using combined and minimum p value, separately. Canonical pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCarta were used. We employed four pathway-based analytic approaches (gene set enrichment analysis, hypergeometric test, sum-square statistic, sum-statistic). We adjusted for multiple testing using Benjamini & Hochberg's method to report significant pathways. We found 17 significantly enriched pathways for depression, which presented low-to-intermediate crosstalk. The top four pathways were long-term depression (p⩽1×10-5), calcium signalling (p⩽6×10-5), arrhythmogenic right ventricular cardiomyopathy (p⩽1.6×10-4) and cell adhesion molecules (p⩽2.2×10-4). In conclusion, our comprehensive pathway analyses identified promising pathways for depression that are related to neurotransmitter and neuronal systems, immune system and inflammatory response, which may be involved in the pathophysiological mechanisms underlying depression. We demonstrated that pathway enrichment analysis is promising to facilitate our understanding of complex traits through a deeper interpretation of GWA data. Application of this comprehensive analytic strategy in upcoming GWA data for depression could validate the findings reported in this study.

Separate enrichment analysis of pathways for up- and downregulated genes.

PubMed

Hong, Guini; Zhang, Wenjing; Li, Hongdong; Shen, Xiaopei; Guo, Zheng

2014-03-06

Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.

Additional targets of the Arabidopsis autonomous pathway members, FCA and FY.

PubMed

Marquardt, S; Boss, P K; Hadfield, J; Dean, C

2006-01-01

A central player in the Arabidopsis floral transition is the floral repressor FLC, the MADS-box transcriptional regulator that inhibits the activity of genes required to switch the meristem from vegetative to floral development. One of the many pathways that regulate FLC expression is the autonomous promotion pathway composed of FCA, FY, FLD, FPA, FVE, LD, and FLK. Rather than a hierarchical set of activities the autonomous promotion pathway comprises sub-pathways of genes with different biochemical functions that all share FLC as a target. One sub-pathway involves FCA and FY, which interact to regulate RNA processing of FLC. Several of the identified components (FY, FVE, and FLD) are homologous to yeast and mammalian proteins with rather generic roles in gene regulation. So why do mutations in these genes specifically show a late-flowering phenotype in Arabidopsis? One reason, found during the analysis of fy alleles, is that the mutant alleles identified in flowering screens can be hypomorphic, they still have partial function. A broader role for the autonomous promotion pathway is supported by a microarray analysis which has identified genes mis-regulated in fca mutants, and whose expression is also altered in fy mutants.

Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

PubMed Central

Silver, Matt; Chen, Peng; Li, Ruoying; Cheng, Ching-Yu; Wong, Tien-Yin; Tai, E-Shyong; Teo, Yik-Ying; Montana, Giovanni

2013-01-01

Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune function. PMID:24278029

Pathways-driven sparse regression identifies pathways and genes associated with high-density lipoprotein cholesterol in two Asian cohorts.

PubMed

Silver, Matt; Chen, Peng; Li, Ruoying; Cheng, Ching-Yu; Wong, Tien-Yin; Tai, E-Shyong; Teo, Yik-Ying; Montana, Giovanni

2013-11-01

Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune function.

Gene Expression Profiling Identifies Downregulation of the Neurotrophin-MAPK Signaling Pathway in Female Diabetic Peripheral Neuropathy Patients

PubMed Central

Luo, Lin; Zhou, Wen-Hua; Cai, Jiang-Jia; Feng, Mei; Zhou, Mi; Hu, Su-Pei

2017-01-01

Diabetic peripheral neuropathy (DPN) is a common complication of diabetes mellitus (DM). It is not diagnosed or managed properly in the majority of patients because its pathogenesis remains controversial. In this study, human whole genome microarrays identified 2898 and 4493 differentially expressed genes (DEGs) in DM and DPN patients, respectively. A further KEGG pathway analysis indicated that DPN and DM share four pathways, including apoptosis, B cell receptor signaling pathway, endocytosis, and Toll-like receptor signaling pathway. The DEGs identified through comparison of DPN and DM were significantly enriched in MAPK signaling pathway, NOD-like receptor signaling pathway, and neurotrophin signaling pathway, while the “neurotrophin-MAPK signaling pathway” was notably downregulated. Seven DEGs from the neurotrophin-MAPK signaling pathway were validated in additional 78 samples, and the results confirmed the initial microarray findings. These findings demonstrated that downregulation of the neurotrophin-MAPK signaling pathway may be the major mechanism of DPN pathogenesis, thus providing a potential approach for DPN treatment. PMID:28900628

Integrative Analysis of Response to Tamoxifen Treatment in ER-Positive Breast Cancer Using GWAS Information and Transcription Profiling.

PubMed

Hicks, Chindo; Kumar, Ranjit; Pannuti, Antonio; Miele, Lucio

2012-01-01

Variable response and resistance to tamoxifen treatment in breast cancer patients remains a major clinical problem. To determine whether genes and biological pathways containing SNPs associated with risk for breast cancer are dysregulated in response to tamoxifen treatment, we performed analysis combining information from 43 genome-wide association studies with gene expression data from 298 ER(+) breast cancer patients treated with tamoxifen and 125 ER(+) controls. We identified 95 genes which distinguished tamoxifen treated patients from controls. Additionally, we identified 54 genes which stratified tamoxifen treated patients into two distinct groups. We identified biological pathways containing SNPs associated with risk for breast cancer, which were dysregulated in response to tamoxifen treatment. Key pathways identified included the apoptosis, P53, NFkB, DNA repair and cell cycle pathways. Combining GWAS with transcription profiling provides a unified approach for associating GWAS findings with response to drug treatment and identification of potential drug targets.

Convergent genetic and expression data implicate immunity in Alzheimer's disease

PubMed Central

Jones, Lesley; Lambert, Jean-Charles; Wang, Li-San; Choi, Seung-Hoan; Harold, Denise; Vedernikov, Alexey; Escott-Price, Valentina; Stone, Timothy; Richards, Alexander; Bellenguez, Céline; Ibrahim-Verbaas, Carla A; Naj, Adam C; Sims, Rebecca; Gerrish, Amy; Jun, Gyungah; DeStefano, Anita L; Bis, Joshua C; Beecham, Gary W; Grenier-Boley, Benjamin; Russo, Giancarlo; Thornton-Wells, Tricia A; Jones, Nicola; Smith, Albert V; Chouraki, Vincent; Thomas, Charlene; Ikram, M Arfan; Zelenika, Diana; Vardarajan, Badri N; Kamatani, Yoichiro; Lin, Chiao-Feng; Schmidt, Helena; Kunkle, Brian; Dunstan, Melanie L; Ruiz, Agustin; Bihoreau, Marie-Thérèse; Reitz, Christiane; Pasquier, Florence; Hollingworth, Paul; Hanon, Olivier; Fitzpatrick, Annette L; Buxbaum, Joseph D; Campion, Dominique; Crane, Paul K; Becker, Tim; Gudnason, Vilmundur; Cruchaga, Carlos; Craig, David; Amin, Najaf; Berr, Claudine; Lopez, Oscar L; De Jager, Philip L; Deramecourt, Vincent; Johnston, Janet A; Evans, Denis; Lovestone, Simon; Letteneur, Luc; Kornhuber, Johanes; Tárraga, Lluís; Rubinsztein, David C; Eiriksdottir, Gudny; Sleegers, Kristel; Goate, Alison M; Fiévet, Nathalie; Huentelman, Matthew J; Gill, Michael; Emilsson, Valur; Brown, Kristelle; Kamboh, M Ilyas; Keller, Lina; Barberger-Gateau, Pascale; McGuinness, Bernadette; Larson, Eric B; Myers, Amanda J; Dufouil, Carole; Todd, Stephen; Wallon, David; Love, Seth; Kehoe, Pat; Rogaeva, Ekaterina; Gallacher, John; George-Hyslop, Peter St; Clarimon, Jordi; Lleὀ, Alberti; Bayer, Anthony; Tsuang, Debby W; Yu, Lei; Tsolaki, Magda; Bossù, Paola; Spalletta, Gianfranco; Proitsi, Petra; Collinge, John; Sorbi, Sandro; Garcia, Florentino Sanchez; Fox, Nick; Hardy, John; Naranjo, Maria Candida Deniz; Razquin, Cristina; Bosco, Paola; Clarke, Robert; Brayne, Carol; Galimberti, Daniela; Mancuso, Michelangelo; Moebus, Susanne; Mecocci, Patrizia; del Zompo, Maria; Maier, Wolfgang; Hampel, Harald; Pilotto, Alberto; Bullido, Maria; Panza, Francesco; Caffarra, Paolo; Nacmias, Benedetta; Gilbert, John R; Mayhaus, Manuel; Jessen, Frank; Dichgans, Martin; Lannfelt, Lars; Hakonarson, Hakon; Pichler, Sabrina; Carrasquillo, Minerva M; Ingelsson, Martin; Beekly, Duane; Alavarez, Victoria; Zou, Fanggeng; Valladares, Otto; Younkin, Steven G; Coto, Eliecer; Hamilton-Nelson, Kara L; Mateo, Ignacio; Owen, Michael J; Faber, Kelley M; Jonsson, Palmi V; Combarros, Onofre; O'Donovan, Michael C; Cantwell, Laura B; Soininen, Hilkka; Blacker, Deborah; Mead, Simon; Mosley, Thomas H; Bennett, David A; Harris, Tamara B; Fratiglioni, Laura; Holmes, Clive; de Bruijn, Renee FAG; Passmore, Peter; Montine, Thomas J; Bettens, Karolien; Rotter, Jerome I; Brice, Alexis; Morgan, Kevin; Foroud, Tatiana M; Kukull, Walter A; Hannequin, Didier; Powell, John F; Nalls, Michael A; Ritchie, Karen; Lunetta, Kathryn L; Kauwe, John SK; Boerwinkle, Eric; Riemenschneider, Matthias; Boada, Mercè; Hiltunen, Mikko; Martin, Eden R; Pastor, Pau; Schmidt, Reinhold; Rujescu, Dan; Dartigues, Jean-François; Mayeux, Richard; Tzourio, Christophe; Hofman, Albert; Nöthen, Markus M; Graff, Caroline; Psaty, Bruce M; Haines, Jonathan L; Lathrop, Mark; Pericak-Vance, Margaret A; Launer, Lenore J; Farrer, Lindsay A; van Duijn, Cornelia M; Van Broekhoven, Christine; Ramirez, Alfredo; Schellenberg, Gerard D; Seshadri, Sudha; Amouyel, Philippe; Holmans, Peter A

2015-01-01

Background Late–onset Alzheimer's disease (AD) is heritable with 20 genes showing genome wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease we extended these genetic data in a pathway analysis. Methods The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (p = 3.27×10-12 after multiple testing correction for pathways), regulation of endocytosis (p = 1.31×10-11), cholesterol transport (p = 2.96 × 10-9) and proteasome-ubiquitin activity (p = 1.34×10-6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected p 0.002 – 0.05). Conclusions The immune response, regulation of endocytosis, cholesterol transport and protein ubiquitination represent prime targets for AD therapeutics. PMID:25533204

Convergent genetic and expression data implicate immunity in Alzheimer's disease.

PubMed

2015-06-01

Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis. The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 × 10(-12) after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 × 10(-11)), cholesterol transport (P = 2.96 × 10(-9)), and proteasome-ubiquitin activity (P = 1.34 × 10(-6)). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002-.05). The immune response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics. Copyright © 2015. Published by Elsevier Inc.

Redundancy control in pathway databases (ReCiPa): an application for improving gene-set enrichment analysis in Omics studies and "Big data" biology.

PubMed

Vivar, Juan C; Pemu, Priscilla; McPherson, Ruth; Ghosh, Sujoy

2013-08-01

Abstract Unparalleled technological advances have fueled an explosive growth in the scope and scale of biological data and have propelled life sciences into the realm of "Big Data" that cannot be managed or analyzed by conventional approaches. Big Data in the life sciences are driven primarily via a diverse collection of 'omics'-based technologies, including genomics, proteomics, metabolomics, transcriptomics, metagenomics, and lipidomics. Gene-set enrichment analysis is a powerful approach for interrogating large 'omics' datasets, leading to the identification of biological mechanisms associated with observed outcomes. While several factors influence the results from such analysis, the impact from the contents of pathway databases is often under-appreciated. Pathway databases often contain variously named pathways that overlap with one another to varying degrees. Ignoring such redundancies during pathway analysis can lead to the designation of several pathways as being significant due to high content-similarity, rather than truly independent biological mechanisms. Statistically, such dependencies also result in correlated p values and overdispersion, leading to biased results. We investigated the level of redundancies in multiple pathway databases and observed large discrepancies in the nature and extent of pathway overlap. This prompted us to develop the application, ReCiPa (Redundancy Control in Pathway Databases), to control redundancies in pathway databases based on user-defined thresholds. Analysis of genomic and genetic datasets, using ReCiPa-generated overlap-controlled versions of KEGG and Reactome pathways, led to a reduction in redundancy among the top-scoring gene-sets and allowed for the inclusion of additional gene-sets representing possibly novel biological mechanisms. Using obesity as an example, bioinformatic analysis further demonstrated that gene-sets identified from overlap-controlled pathway databases show stronger evidence of prior association to obesity compared to pathways identified from the original databases.

Proteomic analysis of pancreatic cancer stem cells: Functional role of fatty acid synthesis and mevalonate pathways.

PubMed

Brandi, Jessica; Dando, Ilaria; Pozza, Elisa Dalla; Biondani, Giulia; Jenkins, Rosalind; Elliott, Victoria; Park, Kevin; Fanelli, Giuseppina; Zolla, Lello; Costello, Eithne; Scarpa, Aldo; Cecconi, Daniela; Palmieri, Marta

2017-01-06

Recently, we have shown that the secretome of pancreatic cancer stem cells (CSCs) is characterized by proteins that participate in cancer differentiation, invasion, and metastasis. However, the differentially expressed intracellular proteins that lead to the specific characteristics of pancreatic CSCs have not yet been identified, and as a consequence the deranged metabolic pathways are yet to be elucidated. To identify the modulated proteins of pancreatic CSCs, iTRAQ-based proteomic analysis was performed to compare the proteome of Panc1 CSCs and Panc1 parental cells, identifying 230 modulated proteins. Pathway analysis revealed activation of glycolysis, the pentose phosphate pathway, the pyruvate-malate cycle, and lipid metabolism as well as downregulation of the Krebs cycle, the splicesome and non-homologous end joining. These findings were supported by metabolomics and immunoblotting analysis. It was also found that inhibition of fatty acid synthase by cerulenin and of mevalonate pathways by atorvastatin have a greater anti-proliferative effect on cancer stem cells than parental cells. Taken together, these results clarify some important aspects of the metabolic network signature of pancreatic cancer stem cells, shedding light on key and novel therapeutic targets and suggesting that fatty acid synthesis and mevalonate pathways play a key role in ensuring their viability. To better understand the altered metabolic pathways of pancreatic cancer stem cells (CSCs), a comprehensive proteomic analysis and metabolite profiling investigation of Panc1 and Panc1 CSCs were carried out. The findings obtained indicate that Panc1 CSCs are characterized by upregulation of glycolysis, pentose phosphate pathway, pyruvate-malate cycle, and lipid metabolism and by downregulation of Krebs cycle, spliceosome and non-homologous end joining. Moreover, fatty acid synthesis and mevalonate pathways are shown to play a critical contribution to the survival of pancreatic cancer stem cells. This study is helpful for broadening the knowledge of pancreatic cancer stem cells and could accelerate the development of novel therapeutic strategies. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of Differentially Expressed Genes and Signaling Pathways Related to Intramuscular Fat Deposition in Skeletal Muscle of Sex-Linked Dwarf Chickens

PubMed Central

Ye, Yaqiong; Lin, Shumao; Mu, Heping; Tang, Xiaohong; Ou, Yangdan; Chen, Jian; Ma, Yongjiang; Li, Yugu

2014-01-01

Intramuscular fat (IMF) plays an important role in meat quality. However, the molecular mechanisms underlying IMF deposition in skeletal muscle have not been addressed for the sex-linked dwarf (SLD) chicken. In this study, potential candidate genes and signaling pathways related to IMF deposition in chicken leg muscle tissue were characterized using gene expression profiling of both 7-week-old SLD and normal chickens. A total of 173 differentially expressed genes (DEGs) were identified between the two breeds. Subsequently, 6 DEGs related to lipid metabolism or muscle development were verified in each breed based on gene ontology (GO) analysis. In addition, KEGG pathway analysis of DEGs indicated that some of them (GHR, SOCS3, and IGF2BP3) participate in adipocytokine and insulin signaling pathways. To investigate the role of the above signaling pathways in IMF deposition, the gene expression of pathway factors and other downstream genes were measured by using qRT-PCR and Western blot analyses. Collectively, the results identified potential candidate genes related to IMF deposition and suggested that IMF deposition in skeletal muscle of SLD chicken is regulated partially by pathways of adipocytokine and insulin and other downstream signaling pathways (TGF-β/SMAD3 and Wnt/catenin-β pathway). PMID:24757673

Pathways Involved in Sasang Constitution from Genome-Wide Analysis in a Korean Population

PubMed Central

Yu, Sung-Gon; Kim, Jong-Yeol; Song, Kwang Hoon

2012-01-01

Abstract Objective Sasang constitution (SC) medicine, a branch of Korean traditional medicine, classifies the individual into one of four constitutional types (Taeum, TE; Soeum, SE; Soyang, SY; and Taeyang, TY) based on physiologic characteristics. The authors of the current article recently reported individual genetic elements associated with SC types via genome-wide association (GWA) analysis. However, to understand the biologic mechanisms underlying constitution, a comprehensive approach that combines individual genetic effects was applied. Design Genotypes of 1222 subjects of defined constitution types were measured for 341,998 genetic loci across the entire genome. The biologic pathways associated with SC types were identified via GWA analysis using three different algorithms—namely, the Z-static method, a restandardized gene set assay, and a gene set enrichment assay. Results Distinct pathways were associated (p<0.05) with each constitution type. The TE type was significantly associated with cytoskeleton-related pathways. The SE type was significantly associated with cardio- and amino-acid metabolism–related pathways. The SY type was associated with enriched melanoma-related pathways. TY subjects were excluded because of the small size of that sample. Among these functionally related pathways, core-node genes regulating multiple pathways were identified. TJP1, PTK2, and SRC were selected as core-nodes for TE; RHOA, and MAOA/MAOB for SE; and GNAO1 for SY (p<0.05), respectively. Conclusions The current authors systematically identified the biologic pathways and core-node genes associated with SC types from the GWA study; this information should provide insights regarding the molecular mechanisms inherent in constitutional pathophysiology. PMID:22889377

Effect of curcumin on aged Drosophila melanogaster: a pathway prediction analysis.

PubMed

Zhang, Zhi-guo; Niu, Xu-yan; Lu, Ai-ping; Xiao, Gary Guishan

2015-02-01

To re-analyze the data published in order to explore plausible biological pathways that can be used to explain the anti-aging effect of curcumin. Microarray data generated from other study aiming to investigate effect of curcumin on extending lifespan of Drosophila melanogaster were further used for pathway prediction analysis. The differentially expressed genes were identified by using GeneSpring GX with a criterion of 3.0-fold change. Two Cytoscape plugins including BisoGenet and molecular complex detection (MCODE) were used to establish the protein-protein interaction (PPI) network based upon differential genes in order to detect highly connected regions. The function annotation clustering tool of Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for pathway analysis. A total of 87 genes expressed differentially in D. melanogaster melanogaster treated with curcumin were identified, among which 50 were up-regulated significantly and 37 were remarkably down-regulated in D. melanogaster melanogaster treated with curcumin. Based upon these differential genes, PPI network was constructed with 1,082 nodes and 2,412 edges. Five highly connected regions in PPI networks were detected by MCODE algorithm, suggesting anti-aging effect of curcumin may be underlined through five different pathways including Notch signaling pathway, basal transcription factors, cell cycle regulation, ribosome, Wnt signaling pathway, and p53 pathway. Genes and their associated pathways in D. melanogaster melanogaster treated with anti-aging agent curcumin were identified using PPI network and MCODE algorithm, suggesting that curcumin may be developed as an alternative therapeutic medicine for treating aging-associated diseases.

A novel method to identify pathways associated with renal cell carcinoma based on a gene co-expression network

PubMed Central

RUAN, XIYUN; LI, HONGYUN; LIU, BO; CHEN, JIE; ZHANG, SHIBAO; SUN, ZEQIANG; LIU, SHUANGQING; SUN, FAHAI; LIU, QINGYONG

2015-01-01

The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson’s correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson’s correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425

PathFinder: reconstruction and dynamic visualization of metabolic pathways.

PubMed

Goesmann, Alexander; Haubrock, Martin; Meyer, Folker; Kalinowski, Jörn; Giegerich, Robert

2002-01-01

Beyond methods for a gene-wise annotation and analysis of sequenced genomes new automated methods for functional analysis on a higher level are needed. The identification of realized metabolic pathways provides valuable information on gene expression and regulation. Detection of incomplete pathways helps to improve a constantly evolving genome annotation or discover alternative biochemical pathways. To utilize automated genome analysis on the level of metabolic pathways new methods for the dynamic representation and visualization of pathways are needed. PathFinder is a tool for the dynamic visualization of metabolic pathways based on annotation data. Pathways are represented as directed acyclic graphs, graph layout algorithms accomplish the dynamic drawing and visualization of the metabolic maps. A more detailed analysis of the input data on the level of biochemical pathways helps to identify genes and detect improper parts of annotations. As an Relational Database Management System (RDBMS) based internet application PathFinder reads a list of EC-numbers or a given annotation in EMBL- or Genbank-format and dynamically generates pathway graphs.

Large-scale transcriptome analysis reveals arabidopsis metabolic pathways are frequently influenced by different pathogens.

PubMed

Jiang, Zhenhong; He, Fei; Zhang, Ziding

2017-07-01

Through large-scale transcriptional data analyses, we highlighted the importance of plant metabolism in plant immunity and identified 26 metabolic pathways that were frequently influenced by the infection of 14 different pathogens. Reprogramming of plant metabolism is a common phenomenon in plant defense responses. Currently, a large number of transcriptional profiles of infected tissues in Arabidopsis (Arabidopsis thaliana) have been deposited in public databases, which provides a great opportunity to understand the expression patterns of metabolic pathways during plant defense responses at the systems level. Here, we performed a large-scale transcriptome analysis based on 135 previously published expression samples, including 14 different pathogens, to explore the expression pattern of Arabidopsis metabolic pathways. Overall, metabolic genes are significantly changed in expression during plant defense responses. Upregulated metabolic genes are enriched on defense responses, and downregulated genes are enriched on photosynthesis, fatty acid and lipid metabolic processes. Gene set enrichment analysis (GSEA) identifies 26 frequently differentially expressed metabolic pathways (FreDE_Paths) that are differentially expressed in more than 60% of infected samples. These pathways are involved in the generation of energy, fatty acid and lipid metabolism as well as secondary metabolite biosynthesis. Clustering analysis based on the expression levels of these 26 metabolic pathways clearly distinguishes infected and control samples, further suggesting the importance of these metabolic pathways in plant defense responses. By comparing with FreDE_Paths from abiotic stresses, we find that the expression patterns of 26 FreDE_Paths from biotic stresses are more consistent across different infected samples. By investigating the expression correlation between transcriptional factors (TFs) and FreDE_Paths, we identify several notable relationships. Collectively, the current study will deepen our understanding of plant metabolism in plant immunity and provide new insights into disease-resistant crop improvement.

Identification and proteomic analysis of osteoblast-derived exosomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ge, Min; Ke, Ronghu; Cai, Tianyi

Exosomes are nanometer-sized vesicles with the function of intercellular communication, and they are released by various cell types. To reveal the knowledge about the exosomes from osteoblast, and explore the potential functions of osteogenesis, we isolated microvesicles from supernatants of mouse Mc3t3 by ultracentrifugation, characterized exosomes by electron microscopy and immunoblotting and presented the protein profile by proteomic analysis. The result demonstrated that microvesicles were between 30 and 100 nm in diameter, round shape with cup-like concavity and expressed exosomal marker tumor susceptibility gene (TSG) 101 and flotillin (Flot) 1. We identified a total number of 1069 proteins among which 786more » proteins overlap with ExoCarta database. Gene Oncology analysis indicated that exosomes mostly derived from plasma membrane and mainly involved in protein localization and intracellular signaling. The Ingenuity Pathway Analysis showed pathways are mostly involved in exosome biogenesis, formation, uptake and osteogenesis. Among the pathways, eukaryotic initiation factor 2 pathways played an important role in osteogenesis. Our study identified osteoblast-derived exosomes, unveiled the content of them, presented potential osteogenesis-related proteins and pathways and provided a rich proteomics data resource that will be valuable for further studies of the functions of individual proteins in bone diseases. - Highlights: • We for the first time identified exosomes from mouse osteoblast. • Osteoblasts-derived exosomes contain osteoblast peculiar proteins. • Proteins from osteoblasts-derived exosomes are intently involved in EIF2 pathway. • EIF2α from the EIF2 pathway plays an important role in osteogenesis.« less

Predicting the points of interaction of small molecules in the NF-κB pathway

PubMed Central

2011-01-01

Background The similarity property principle has been used extensively in drug discovery to identify small compounds that interact with specific drug targets. Here we show it can be applied to identify the interactions of small molecules within the NF-κB signalling pathway. Results Clusters that contain compounds with a predominant interaction within the pathway were created, which were then used to predict the interaction of compounds not included in the clustering analysis. Conclusions The technique successfully predicted the points of interactions of compounds that are known to interact with the NF-κB pathway. The method was also shown to be successful when compounds for which the interaction points were unknown were included in the clustering analysis. PMID:21342508

[Exploration of common biological pathways for attention deficit hyperactivity disorder and low birth weight].

PubMed

Xiang, Bo; Yu, Minglan; Liang, Xuemei; Lei, Wei; Huang, Chaohua; Chen, Jing; He, Wenying; Zhang, Tao; Li, Tao; Liu, Kezhi

2017-12-10

To explore common biological pathways for attention deficit hyperactivity disorder (ADHD) and low birth weight (LBW). Thei-Gsea4GwasV2 software was used to analyze the result of genome-wide association analysis (GWAS) for LBW (pathways were derived from Reactome), and nominally significant (P< 0.05, FDR< 0.25) pathways were tested for replication in ADHD.Significant pathways were analyzed with DAPPLE and Reatome FI software to identify genes involved in such pathways, with each cluster enriched with the gene ontology (GO). The Centiscape2.0 software was used to calculate the degree of genetic networks and the betweenness value to explore the core node (gene). Weighed gene co-expression network analysis (WGCNA) was then used to explore the co-expression of genes in these pathways.With gene expression data derived from BrainSpan, GO enrichment was carried out for each gene module. Eleven significant biological pathways was identified in association with LBW, among which two (Selenoamino acid metabolism and Diseases associated with glycosaminoglycan metabolism) were replicated during subsequent ADHD analysis. Network analysis of 130 genes in these pathways revealed that some of the sub-networksare related with morphology of cerebellum, development of hippocampus, and plasticity of synaptic structure. Upon co-expression network analysis, 120 genes passed the quality control and were found to express in 3 gene modules. These modules are mainly related to the regulation of synaptic structure and activity regulation. ADHD and LBW share some biological regulation processes. Anomalies of such proces sesmay predispose to ADHD.

Pathway analysis with next-generation sequencing data.

PubMed

Zhao, Jinying; Zhu, Yun; Boerwinkle, Eric; Xiong, Momiao

2015-04-01

Although pathway analysis methods have been developed and successfully applied to association studies of common variants, the statistical methods for pathway-based association analysis of rare variants have not been well developed. Many investigators observed highly inflated false-positive rates and low power in pathway-based tests of association of rare variants. The inflated false-positive rates and low true-positive rates of the current methods are mainly due to their lack of ability to account for gametic phase disequilibrium. To overcome these serious limitations, we develop a novel statistic that is based on the smoothed functional principal component analysis (SFPCA) for pathway association tests with next-generation sequencing data. The developed statistic has the ability to capture position-level variant information and account for gametic phase disequilibrium. By intensive simulations, we demonstrate that the SFPCA-based statistic for testing pathway association with either rare or common or both rare and common variants has the correct type 1 error rates. Also the power of the SFPCA-based statistic and 22 additional existing statistics are evaluated. We found that the SFPCA-based statistic has a much higher power than other existing statistics in all the scenarios considered. To further evaluate its performance, the SFPCA-based statistic is applied to pathway analysis of exome sequencing data in the early-onset myocardial infarction (EOMI) project. We identify three pathways significantly associated with EOMI after the Bonferroni correction. In addition, our preliminary results show that the SFPCA-based statistic has much smaller P-values to identify pathway association than other existing methods.

Characterization of biomarkers in stroke based on ego-networks and pathways.

PubMed

Li, Haixia; Guo, Qianqian

2017-12-01

To explore potential biomarkers in stroke based on ego-networks and pathways. EgoNet method was applied to search for the underlying biomarkers in stroke using transcription profiling of E-GEOD-58294 and protein-protein interaction (PPI) data. Eight ego-genes were identified from PPI network according to the degree characteristics at the criteria of top 5% ranked z-sore and degree >1. Eight candidate ego-networks with classification accuracy ≥0.9 were selected. After performed randomization test, seven significant ego-networks with adjusted p value < 0.05 were identified. Pathway enrichment analysis was then conducted with these ego-networks to search for the significant pathways. Finally, two significant pathways were identified, and six of seven ego-networks were enriched to "3'-UTR-mediated translational regulation" pathway, indicating that this pathway performs an important role in the development of stroke. Seven ego-networks were constructed using EgoNet and two significant enriched by pathways were identified. These may provide new insights into the potential biomarkers for the development of stroke.

ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis

PubMed Central

Han, Junwei; Shi, Xinrui; Zhang, Yunpeng; Xu, Yanjun; Jiang, Ying; Zhang, Chunlong; Feng, Li; Yang, Haixiu; Shang, Desi; Sun, Zeguo; Su, Fei; Li, Chunquan; Li, Xia

2015-01-01

Pathway analyses are playing an increasingly important role in understanding biological mechanism, cellular function and disease states. Current pathway-identification methods generally focus on only the changes of gene expression levels; however, the biological relationships among genes are also the fundamental components of pathways, and the dysregulated relationships may also alter the pathway activities. We propose a powerful computational method, Edge Set Enrichment Analysis (ESEA), for the identification of dysregulated pathways. This provides a novel way of pathway analysis by investigating the changes of biological relationships of pathways in the context of gene expression data. Simulation studies illustrate the power and performance of ESEA under various simulated conditions. Using real datasets from p53 mutation, Type 2 diabetes and lung cancer, we validate effectiveness of ESEA in identifying dysregulated pathways. We further compare our results with five other pathway enrichment analysis methods. With these analyses, we show that ESEA is able to help uncover dysregulated biological pathways underlying complex traits and human diseases via specific use of the dysregulated biological relationships. We develop a freely available R-based tool of ESEA. Currently, ESEA can support pathway analysis of the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther). PMID:26267116

Major carcinogenic pathways identified by gene expression analysis of peritoneal mesotheliomas following chemical treatment in F344 rats

EPA Science Inventory

This study was performed to characterize the gene expression profile and to identify the major carcinogenic pathways involved in rat peritoneal mesothelioma (RPM) formation following treatment of Fischer 344 rats with o-nitrotoluene (o-NT) or bromochloracetic acid (BCA). Oligo a...

Genetic association of impulsivity in young adults: a multivariate study

PubMed Central

Khadka, S; Narayanan, B; Meda, S A; Gelernter, J; Han, S; Sawyer, B; Aslanzadeh, F; Stevens, M C; Hawkins, K A; Anticevic, A; Potenza, M N; Pearlson, G D

2014-01-01

Impulsivity is a heritable, multifaceted construct with clinically relevant links to multiple psychopathologies. We assessed impulsivity in young adult (N~2100) participants in a longitudinal study, using self-report questionnaires and computer-based behavioral tasks. Analysis was restricted to the subset (N=426) who underwent genotyping. Multivariate association between impulsivity measures and single-nucleotide polymorphism data was implemented using parallel independent component analysis (Para-ICA). Pathways associated with multiple genes in components that correlated significantly with impulsivity phenotypes were then identified using a pathway enrichment analysis. Para-ICA revealed two significantly correlated genotype–phenotype component pairs. One impulsivity component included the reward responsiveness subscale and behavioral inhibition scale of the Behavioral-Inhibition System/Behavioral-Activation System scale, and the second impulsivity component included the non-planning subscale of the Barratt Impulsiveness Scale and the Experiential Discounting Task. Pathway analysis identified processes related to neurogenesis, nervous system signal generation/amplification, neurotransmission and immune response. We identified various genes and gene regulatory pathways associated with empirically derived impulsivity components. Our study suggests that gene networks implicated previously in brain development, neurotransmission and immune response are related to impulsive tendencies and behaviors. PMID:25268255

Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).

PubMed

Huan, Jinliang; Wang, Lishan; Xing, Li; Qin, Xianju; Feng, Lingbin; Pan, Xiaofeng; Zhu, Ling

2014-01-01

Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with KEGG pathway enrichment, PPI network construction, module analysis and text mining methods to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the genes queried on the Affymetrix Human Genome U133 plus 2.0 microarray, we identified 628 (12h), 852 (24h) and 880 (48 h) differentially expressed genes (DEGs) that showed a robust pattern of regulation by E2. From pathway enrichment analysis, we found out the changes of metabolic pathways of E2 treated samples at each time point. At 12h time point, the changes of metabolic pathways were mainly focused on pathways in cancer, focal adhesion, and chemokine signaling pathway. At 24h time point, the changes were mainly enriched in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction and calcium signaling pathway. At 48 h time point, the significant pathways were pathways in cancer, regulation of actin cytoskeleton, cell adhesion molecules (CAMs), axon guidance and ErbB signaling pathway. Of interest, our PPI network analysis and module analysis found that E2 treatment induced enhancement of PRSS23 at the three time points and PRSS23 was in the central position of each module. Text mining results showed that the important genes of DEGs have relationship with signal pathways, such as ERbB pathway (AREG), Wnt pathway (NDP), MAPK pathway (NTRK3, TH), IP3 pathway (TRA@) and some transcript factors (TCF4, MAF). Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to achieve its widespread effects on breast cancer cells. © 2013 Elsevier B.V. All rights reserved.

Bioinformatics analysis of differentially expressed gene profiles associated with systemic lupus erythematosus

PubMed Central

Wu, Chengjiang; Zhao, Yangjing; Lin, Yu; Yang, Xinxin; Yan, Meina; Min, Yujiao; Pan, Zihui; Xia, Sheng; Shao, Qixiang

2018-01-01

DNA microarray and high-throughput sequencing have been widely used to identify the differentially expressed genes (DEGs) in systemic lupus erythematosus (SLE). However, the big data from gene microarrays are also challenging to work with in terms of analysis and processing. The presents study combined data from the microarray expression profile (GSE65391) and bioinformatics analysis to identify the key genes and cellular pathways in SLE. Gene ontology (GO) and cellular pathway enrichment analyses of DEGs were performed to investigate significantly enriched pathways. A protein-protein interaction network was constructed to determine the key genes in the occurrence and development of SLE. A total of 310 DEGs were identified in SLE, including 193 upregulated genes and 117 downregulated genes. GO analysis revealed that the most significant biological process of DEGs was immune system process. Kyoto Encyclopedia of Genes and Genome pathway analysis showed that these DEGs were enriched in signaling pathways associated with the immune system, including the RIG-I-like receptor signaling pathway, intestinal immune network for IgA production, antigen processing and presentation and the toll-like receptor signaling pathway. The current study screened the top 10 genes with higher degrees as hub genes, which included 2′-5′-oligoadenylate synthetase 1, MX dynamin like GTPase 2, interferon induced protein with tetratricopeptide repeats 1, interferon regulatory factor 7, interferon induced with helicase C domain 1, signal transducer and activator of transcription 1, ISG15 ubiquitin-like modifier, DExD/H-box helicase 58, interferon induced protein with tetratricopeptide repeats 3 and 2′-5′-oligoadenylate synthetase 2. Module analysis revealed that these hub genes were also involved in the RIG-I-like receptor signaling, cytosolic DNA-sensing, toll-like receptor signaling and ribosome biogenesis pathways. In addition, these hub genes, from different probe sets, exhibited significant co-expressed tendency in multi-experiment microarray datasets (P<0.01). In conclusion, these key genes and cellular pathways may improve the current understanding of the underlying mechanism of development of SLE. These key genes may be potential biomarkers of diagnosis, therapy and prognosis for SLE. PMID:29257335

Expanding the view on the evolution of the nematode dauer signalling pathways: refinement through gene gain and pathway co-option.

PubMed

Gilabert, Aude; Curran, David M; Harvey, Simon C; Wasmuth, James D

2016-06-27

Signalling pathways underlie development, behaviour and pathology. To understand patterns in the evolution of signalling pathways, we undertook a comprehensive investigation of the pathways that control the switch between growth and developmentally quiescent dauer in 24 species of nematodes spanning the phylum. Our analysis of 47 genes across these species indicates that the pathways and their interactions are not conserved throughout the Nematoda. For example, the TGF-β pathway was co-opted into dauer control relatively late in a lineage that led to the model species Caenorhabditis elegans. We show molecular adaptations described in C. elegans that are restricted to its genus or even just to the species. Similarly, our analyses both identify species where particular genes have been lost and situations where apparently incorrect orthologues have been identified. Our analysis also highlights the difficulties of working with genome sequences from non-model species as reliance on the published gene models would have significantly restricted our understanding of how signalling pathways evolve. Our approach therefore offers a robust standard operating procedure for genomic comparisons.

Service-based analysis of biological pathways

PubMed Central

Zheng, George; Bouguettaya, Athman

2009-01-01

Background Computer-based pathway discovery is concerned with two important objectives: pathway identification and analysis. Conventional mining and modeling approaches aimed at pathway discovery are often effective at achieving either objective, but not both. Such limitations can be effectively tackled leveraging a Web service-based modeling and mining approach. Results Inspired by molecular recognitions and drug discovery processes, we developed a Web service mining tool, named PathExplorer, to discover potentially interesting biological pathways linking service models of biological processes. The tool uses an innovative approach to identify useful pathways based on graph-based hints and service-based simulation verifying user's hypotheses. Conclusion Web service modeling of biological processes allows the easy access and invocation of these processes on the Web. Web service mining techniques described in this paper enable the discovery of biological pathways linking these process service models. Algorithms presented in this paper for automatically highlighting interesting subgraph within an identified pathway network enable the user to formulate hypothesis, which can be tested out using our simulation algorithm that are also described in this paper. PMID:19796403

Core signaling pathways in ovarian cancer stem cell revealed by integrative analysis of multi-marker genomics data.

PubMed

Zhang, Tianyu; Xu, Jielin; Deng, Siyuan; Zhou, Fengqi; Li, Jin; Zhang, Liwei; Li, Lang; Wang, Qi-En; Li, Fuhai

2018-01-01

Tumor recurrence occurs in more than 70% of ovarian cancer patients, and the majority eventually becomes refractory to treatments. Ovarian Cancer Stem Cells (OCSCs) are believed to be responsible for the tumor relapse and drug resistance. Therefore, eliminating ovarian CSCs is important to improve the prognosis of ovarian cancer patients. However, there is a lack of effective drugs to eliminate OCSCs because the core signaling pathways regulating OCSCs remain unclear. Also it is often hard for biologists to identify a few testable targets and infer driver signaling pathways regulating CSCs from a large number of differentially expression genes in an unbiased manner. In this study, we propose a straightforward and integrative analysis to identify potential core signaling pathways of OCSCs by integrating transcriptome data of OCSCs isolated based on two distinctive markers, ALDH and side population, with regulatory network (Transcription Factor (TF) and Target Interactome) and signaling pathways. We first identify the common activated TFs in two OCSC populations integrating the gene expression and TF-target Interactome; and then uncover up-stream signaling cascades regulating the activated TFs. In specific, 22 activated TFs are identified. Through literature search validation, 15 of them have been reported in association with cancer stem cells. Additionally, 10 TFs are found in the KEGG signaling pathways, and their up-stream signaling cascades are extracted, which also provide potential treatment targets. Moreover, 40 FDA approved drugs are identified to target on the up-stream signaling cascades, and 15 of them have been reported in literatures in cancer stem cell treatment. In conclusion, the proposed approach can uncover the activated up-stream signaling, activated TFs and up-regulated target genes that constitute the potential core signaling pathways of ovarian CSC. Also drugs and drug combinations targeting on the core signaling pathways might be able to eliminate OCSCs. The proposed approach can also be applied for identifying potential activated signaling pathways of other types of cancers.

Systematic analysis of molecular mechanisms for HCC metastasis via text mining approach.

PubMed

Zhen, Cheng; Zhu, Caizhong; Chen, Haoyang; Xiong, Yiru; Tan, Junyuan; Chen, Dong; Li, Jin

2017-02-21

To systematically explore the molecular mechanism for hepatocellular carcinoma (HCC) metastasis and identify regulatory genes with text mining methods. Genes with highest frequencies and significant pathways related to HCC metastasis were listed. A handful of proteins such as EGFR, MDM2, TP53 and APP, were identified as hub nodes in PPI (protein-protein interaction) network. Compared with unique genes for HBV-HCCs, genes particular to HCV-HCCs were less, but may participate in more extensive signaling processes. VEGFA, PI3KCA, MAPK1, MMP9 and other genes may play important roles in multiple phenotypes of metastasis. Genes in abstracts of HCC-metastasis literatures were identified. Word frequency analysis, KEGG pathway and PPI network analysis were performed. Then co-occurrence analysis between genes and metastasis-related phenotypes were carried out. Text mining is effective for revealing potential regulators or pathways, but the purpose of it should be specific, and the combination of various methods will be more useful.

Meta-Analysis of Genome-Wide Association Studies and Network Analysis-Based Integration with Gene Expression Data Identify New Suggestive Loci and Unravel a Wnt-Centric Network Associated with Dupuytren’s Disease

PubMed Central

Becker, Kerstin; Siegert, Sabine; Toliat, Mohammad Reza; Du, Juanjiangmeng; Casper, Ramona; Dolmans, Guido H.; Werker, Paul M.; Tinschert, Sigrid; Franke, Andre; Gieger, Christian; Strauch, Konstantin; Nothnagel, Michael; Nürnberg, Peter; Hennies, Hans Christian

2016-01-01

Dupuytren´s disease, a fibromatosis of the connective tissue in the palm, is a common complex disease with a strong genetic component. Up to date nine genetic loci have been found to be associated with the disease. Six of these loci contain genes that code for Wnt signalling proteins. In spite of this striking first insight into the genetic factors in Dupuytren´s disease, much of the inherited risk in Dupuytren´s disease still needs to be discovered. The already identified loci jointly explain ~1% of the heritability in this disease. To further elucidate the genetic basis of Dupuytren´s disease, we performed a genome-wide meta-analysis combining three genome-wide association study (GWAS) data sets, comprising 1,580 cases and 4,480 controls. We corroborated all nine previously identified loci, six of these with genome-wide significance (p-value < 5x10-8). In addition, we identified 14 new suggestive loci (p-value < 10−5). Intriguingly, several of these new loci contain genes associated with Wnt signalling and therefore represent excellent candidates for replication. Next, we compared whole-transcriptome data between patient- and control-derived tissue samples and found the Wnt/β-catenin pathway to be the top deregulated pathway in patient samples. We then conducted network and pathway analyses in order to identify protein networks that are enriched for genes highlighted in the GWAS meta-analysis and expression data sets. We found further evidence that the Wnt signalling pathways in conjunction with other pathways may play a critical role in Dupuytren´s disease. PMID:27467239

Transcriptome from circulating cells suggests dysregulated pathways associated with long-term recurrent events following first-time myocardial infarction.

PubMed

Suresh, Rahul; Li, Xing; Chiriac, Anca; Goel, Kashish; Terzic, Andre; Perez-Terzic, Carmen; Nelson, Timothy J

2014-09-01

Whole-genome gene expression analysis has been successfully utilized to diagnose, prognosticate, and identify potential therapeutic targets for high-risk cardiovascular diseases. However, the feasibility of this approach to identify outcome-related genes and dysregulated pathways following first-time myocardial infarction (AMI) remains unknown and may offer a novel strategy to detect affected expressome networks that predict long-term outcome. Whole-genome expression microarray on blood samples from normal cardiac function controls (n=21) and first-time AMI patients (n=31) within 48-hours post-MI revealed expected differential gene expression profiles enriched for inflammation and immune-response pathways. To determine molecular signatures at the time of AMI associated with long-term outcomes, transcriptional profiles from sub-groups of AMI patients with (n=5) or without (n=22) any recurrent events over an 18-month follow-up were compared. This analysis identified 559 differentially-expressed genes. Bioinformatic analysis of this differential gene-set for associated pathways revealed 1) increasing disease severity in AMI patients is associated with a decreased expression of genes involved in the developmental epithelial-to-mesenchymal transition pathway, and 2) modulation of cholesterol transport genes that include ABCA1, CETP, APOA1, and LDLR is associated with clinical outcome. Differentially regulated genes and modulated pathways were identified that were associated with recurrent cardiovascular outcomes in first-time AMI patients. This cell-based approach for risk stratification in AMI could represent a novel, non-invasive platform to anticipate modifiable pathways and therapeutic targets to optimize long-term outcome for AMI patients and warrants further study to determine the role of metabolic remodeling and regenerative processes required for optimal outcomes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Genome-wide pathway analysis of memory impairment in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks.

PubMed

Ramanan, Vijay K; Kim, Sungeun; Holohan, Kelly; Shen, Li; Nho, Kwangsik; Risacher, Shannon L; Foroud, Tatiana M; Mukherjee, Shubhabrata; Crane, Paul K; Aisen, Paul S; Petersen, Ronald C; Weiner, Michael W; Saykin, Andrew J

2012-12-01

Memory deficits are prominent features of mild cognitive impairment (MCI) and Alzheimer's disease (AD). The genetic architecture underlying these memory deficits likely involves the combined effects of multiple genetic variants operative within numerous biological pathways. In order to identify functional pathways associated with memory impairment, we performed a pathway enrichment analysis on genome-wide association data from 742 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. A composite measure of memory was generated as the phenotype for this analysis by applying modern psychometric theory to item-level data from the ADNI neuropsychological test battery. Using the GSA-SNP software tool, we identified 27 canonical, expertly-curated pathways with enrichment (FDR-corrected p-value < 0.05) against this composite memory score. Processes classically understood to be involved in memory consolidation, such as neurotransmitter receptor-mediated calcium signaling and long-term potentiation, were highly represented among the enriched pathways. In addition, pathways related to cell adhesion, neuronal differentiation and guided outgrowth, and glucose- and inflammation-related signaling were also enriched. Among genes that were highly-represented in these enriched pathways, we found indications of coordinated relationships, including one large gene set that is subject to regulation by the SP1 transcription factor, and another set that displays co-localized expression in normal brain tissue along with known AD risk genes. These results 1) demonstrate that psychometrically-derived composite memory scores are an effective phenotype for genetic investigations of memory impairment and 2) highlight the promise of pathway analysis in elucidating key mechanistic targets for future studies and for therapeutic interventions.

Anomaly Detection in Host Signaling Pathways for the Early Prognosis of Acute Infection.

PubMed

Wang, Kun; Langevin, Stanley; O'Hern, Corey S; Shattuck, Mark D; Ogle, Serenity; Forero, Adriana; Morrison, Juliet; Slayden, Richard; Katze, Michael G; Kirby, Michael

2016-01-01

Clinical diagnosis of acute infectious diseases during the early stages of infection is critical to administering the appropriate treatment to improve the disease outcome. We present a data driven analysis of the human cellular response to respiratory viruses including influenza, respiratory syncytia virus, and human rhinovirus, and compared this with the response to the bacterial endotoxin, Lipopolysaccharides (LPS). Using an anomaly detection framework we identified pathways that clearly distinguish between asymptomatic and symptomatic patients infected with the four different respiratory viruses and that accurately diagnosed patients exposed to a bacterial infection. Connectivity pathway analysis comparing the viral and bacterial diagnostic signatures identified host cellular pathways that were unique to patients exposed to LPS endotoxin indicating this type of analysis could be used to identify host biomarkers that can differentiate clinical etiologies of acute infection. We applied the Multivariate State Estimation Technique (MSET) on two human influenza (H1N1 and H3N2) gene expression data sets to define host networks perturbed in the asymptomatic phase of infection. Our analysis identified pathways in the respiratory virus diagnostic signature as prognostic biomarkers that triggered prior to clinical presentation of acute symptoms. These early warning pathways correctly predicted that almost half of the subjects would become symptomatic in less than forty hours post-infection and that three of the 18 subjects would become symptomatic after only 8 hours. These results provide a proof-of-concept for utility of anomaly detection algorithms to classify host pathway signatures that can identify presymptomatic signatures of acute diseases and differentiate between etiologies of infection. On a global scale, acute respiratory infections cause a significant proportion of human co-morbidities and account for 4.25 million deaths annually. The development of clinical diagnostic tools to distinguish between acute viral and bacterial respiratory infections is critical to improve patient care and limit the overuse of antibiotics in the medical community. The identification of prognostic respiratory virus biomarkers provides an early warning system that is capable of predicting which subjects will become symptomatic to expand our medical diagnostic capabilities and treatment options for acute infectious diseases. The host response to acute infection may be viewed as a deterministic signaling network responsible for maintaining the health of the host organism. We identify pathway signatures that reflect the very earliest perturbations in the host response to acute infection. These pathways provide a monitor the health state of the host using anomaly detection to quantify and predict health outcomes to pathogens.

Anomaly Detection in Host Signaling Pathways for the Early Prognosis of Acute Infection

PubMed Central

O’Hern, Corey S.; Shattuck, Mark D.; Ogle, Serenity; Forero, Adriana; Morrison, Juliet; Slayden, Richard; Katze, Michael G.

2016-01-01

Clinical diagnosis of acute infectious diseases during the early stages of infection is critical to administering the appropriate treatment to improve the disease outcome. We present a data driven analysis of the human cellular response to respiratory viruses including influenza, respiratory syncytia virus, and human rhinovirus, and compared this with the response to the bacterial endotoxin, Lipopolysaccharides (LPS). Using an anomaly detection framework we identified pathways that clearly distinguish between asymptomatic and symptomatic patients infected with the four different respiratory viruses and that accurately diagnosed patients exposed to a bacterial infection. Connectivity pathway analysis comparing the viral and bacterial diagnostic signatures identified host cellular pathways that were unique to patients exposed to LPS endotoxin indicating this type of analysis could be used to identify host biomarkers that can differentiate clinical etiologies of acute infection. We applied the Multivariate State Estimation Technique (MSET) on two human influenza (H1N1 and H3N2) gene expression data sets to define host networks perturbed in the asymptomatic phase of infection. Our analysis identified pathways in the respiratory virus diagnostic signature as prognostic biomarkers that triggered prior to clinical presentation of acute symptoms. These early warning pathways correctly predicted that almost half of the subjects would become symptomatic in less than forty hours post-infection and that three of the 18 subjects would become symptomatic after only 8 hours. These results provide a proof-of-concept for utility of anomaly detection algorithms to classify host pathway signatures that can identify presymptomatic signatures of acute diseases and differentiate between etiologies of infection. On a global scale, acute respiratory infections cause a significant proportion of human co-morbidities and account for 4.25 million deaths annually. The development of clinical diagnostic tools to distinguish between acute viral and bacterial respiratory infections is critical to improve patient care and limit the overuse of antibiotics in the medical community. The identification of prognostic respiratory virus biomarkers provides an early warning system that is capable of predicting which subjects will become symptomatic to expand our medical diagnostic capabilities and treatment options for acute infectious diseases. The host response to acute infection may be viewed as a deterministic signaling network responsible for maintaining the health of the host organism. We identify pathway signatures that reflect the very earliest perturbations in the host response to acute infection. These pathways provide a monitor the health state of the host using anomaly detection to quantify and predict health outcomes to pathogens. PMID:27532264

International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

PubMed

Cordell, Heather J; Han, Younghun; Mells, George F; Li, Yafang; Hirschfield, Gideon M; Greene, Casey S; Xie, Gang; Juran, Brian D; Zhu, Dakai; Qian, David C; Floyd, James A B; Morley, Katherine I; Prati, Daniele; Lleo, Ana; Cusi, Daniele; Gershwin, M Eric; Anderson, Carl A; Lazaridis, Konstantinos N; Invernizzi, Pietro; Seldin, Michael F; Sandford, Richard N; Amos, Christopher I; Siminovitch, Katherine A

2015-09-22

Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist.

Metabolomic analysis of pancreatic β-cell insulin release in response to glucose.

PubMed

Huang, Mei; Joseph, Jamie W

2012-01-01

Defining the key metabolic pathways that are important for fuel-regulated insulin secretion is critical to providing a complete picture of how nutrients regulate insulin secretion. We have performed a detailed metabolomics study of the clonal β-cell line 832/13 using a gas chromatography-mass spectrometer (GC-MS) to investigate potential coupling factors that link metabolic pathways to insulin secretion. Mid-polar and polar metabolites, extracted from the 832/13 β-cells, were derivatized and then run on a GC/MS to identify and quantify metabolite concentrations. Three hundred fifty-five out of 527 chromatographic peaks could be identified as metabolites by our metabolomic platform. These identified metabolites allowed us to perform a systematic analysis of key pathways involved in glucose-stimulated insulin secretion (GSIS). Of these metabolites, 41 were consistently identified as biomarker for GSIS by orthogonal partial least-squares (OPLS). Most of the identified metabolites are from common metabolic pathways including glycolytic, sorbitol-aldose reductase pathway, pentose phosphate pathway, and the TCA cycle suggesting these pathways play an important role in GSIS. Lipids and related products were also shown to contribute to the clustering of high glucose sample groups. Amino acids lysine, tyrosine, alanine and serine were upregulated by glucose whereas aspartic acid was downregulated by glucose suggesting these amino acids might play a key role in GSIS. In summary, a coordinated signaling cascade elicited by glucose metabolism in pancreatic β-cells is revealed by our metabolomics platform providing a new conceptual framework for future research and/or drug discovery.

Dysregulated Pathway Identification of Alzheimer's Disease Based on Internal Correlation Analysis of Genes and Pathways.

PubMed

Kong, Wei; Mou, Xiaoyang; Di, Benteng; Deng, Jin; Zhong, Ruxing; Wang, Shuaiqun

2017-11-20

Dysregulated pathway identification is an important task which can gain insight into the underlying biological processes of disease. Current pathway-identification methods focus on a set of co-expression genes and single pathways and ignore the correlation between genes and pathways. The method proposed in this study, takes into account the internal correlations not only between genes but also pathways to identifying dysregulated pathways related to Alzheimer's disease (AD), the most common form of dementia. In order to find the significantly differential genes for AD, mutual information (MI) is used to measure interdependencies between genes other than expression valves. Then, by integrating the topology information from KEGG, the significant pathways involved in the feature genes are identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks since DC has the advantage of detecting nonlinear correlations when compared to Pearson correlation. Finally, the pathway pairs with significantly different correlations between normal and AD samples are known as dysregulated pathways. The molecular biology analysis demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered successfully by the internal correlation detection. Furthermore, the insights of the dysregulated pathways in the development and deterioration of AD will help to find new effective target genes and provide important theoretical guidance for drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

PubMed

Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-11-16

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development

PubMed Central

Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-01-01

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968

De novo transcriptome analysis in Dendrobium and identification of critical genes associated with flowering.

PubMed

Chen, Yue; Shen, Qi; Lin, Renan; Zhao, Zhuangliu; Shen, Chenjia; Sun, Chongbo

2017-10-01

Artificial control of flowering time is pivotal for the ornamental value of orchids including the genus Dendrobium. Although various flowering pathways have been revealed in model plants, little information is available on the genetic regualtion of flowering in Dendrobium. To identify the critical genes associated with flowering, transcriptomes from four organs (leaf, root, stem and flower) of D. officinale were analyzed in our study. In total, 2645 flower-specific transcripts were identified. Functional annotation and classification suggested that several metabolic pathways, including four sugar-related pathways and two fatty acid-related pathways, were enriched. A total of 24 flowering-related transcripts were identified in D. officinale according to the similarities to their homologous genes from Arabidopsis, suggesting that most classical flowering pathways existed in D. officinale. Furthermore, phylogenetic analysis suggested that the FLOWERING LOCUS T homologs in orchids are highly conserved during evolution process. In addition, expression changes in nine randomly-selected critical flowering-related transcripts between the vegetative stage and reproductive stage were quantified by qRT-PCR analysis. Our study provided a number of candidate genes and sequence resources for investigating the mechanisms underlying the flowering process of the Dendrobium genus. Copyright © 2017. Published by Elsevier Masson SAS.

Kinase Pathway Dependence in Primary Human Leukemias Determined by Rapid Inhibitor Screening

PubMed Central

Tyner, Jeffrey W.; Yang, Wayne F.; Bankhead, Armand; Fan, Guang; Fletcher, Luke B.; Bryant, Jade; Glover, Jason M.; Chang, Bill H.; Spurgeon, Stephen E.; Fleming, William H.; Kovacsovics, Tibor; Gotlib, Jason R.; Oh, Stephen T.; Deininger, Michael W.; Zwaan, C. Michel; Den Boer, Monique L.; van den Heuvel-Eibrink, Marry M.; O’Hare, Thomas; Druker, Brian J.; Loriaux, Marc M.

2012-01-01

Kinases are dysregulated in most cancer but the frequency of specific kinase mutations is low, indicating a complex etiology in kinase dysregulation. Here we report a strategy to rapidly identify functionally important kinase targets, irrespective of the etiology of kinase pathway dysregulation, ultimately enabling a correlation of patient genetic profiles to clinically effective kinase inhibitors. Our methodology assessed the sensitivity of primary leukemia patient samples to a panel of 66 small-molecule kinase inhibitors over 3 days. Screening of 151 leukemia patient samples revealed a wide diversity of drug sensitivities, with 70% of the clinical specimens exhibiting hypersensitivity to one or more drugs. From this data set, we developed an algorithm to predict kinase pathway dependence based on analysis of inhibitor sensitivity patterns. Applying this algorithm correctly identified pathway dependence in proof-of-principle specimens with known oncogenes, including a rare FLT3 mutation outside regions covered by standard molecular diagnostic tests. Interrogation of all 151 patient specimens with this algorithm identified a diversity of gene targets and signaling pathways that could aid prioritization of deep sequencing data sets, permitting a cumulative analysis to understand kinase pathway dependence within leukemia subsets. In a proof-of-principle case, we showed that in vitro drug sensitivity could predict both a clinical response and the development of drug resistance. Taken together, our results suggested that drug target scores derived from a comprehensive kinase inhibitor panel could predict pathway dependence in cancer cells while simultaneously identifying potential therapeutic options. PMID:23087056

Metabolomics Coupled with Multivariate Data and Pathway Analysis on Potential Biomarkers in Gastric Ulcer and Intervention Effects of Corydalis yanhusuo Alkaloid

PubMed Central

Shuai, Wang; Yongrui, Bao; Shanshan, Guan; Bo, Liu; Lu, Chen; Lei, Wang; Xiaorong, Ran

2014-01-01

Metabolomics, the systematic analysis of potential metabolites in a biological specimen, has been increasingly applied to discovering biomarkers, identifying perturbed pathways, measuring therapeutic targets, and discovering new drugs. By analyzing and verifying the significant difference in metabolic profiles and changes of metabolite biomarkers, metabolomics enables us to better understand substance metabolic pathways which can clarify the mechanism of Traditional Chinese Medicines (TCM). Corydalis yanhusuo alkaloid (CA) is a major component of Qizhiweitong (QZWT) prescription which has been used for treating gastric ulcer for centuries and its mechanism remains unclear completely. Metabolite profiling was performed by high-performance liquid chromatography combined with time-of-flight mass spectrometry (HPLC/ESI-TOF-MS) and in conjunction with multivariate data analysis and pathway analysis. The statistic software Mass Profiller Prossional (MPP) and statistic method including ANOVA and principal component analysis (PCA) were used for discovering novel potential biomarkers to clarify mechanism of CA in treating acid injected rats with gastric ulcer. The changes in metabolic profiling were restored to their base-line values after CA treatment according to the PCA score plots. Ten different potential biomarkers and seven key metabolic pathways contributing to the treatment of gastric ulcer were discovered and identified. Among the pathways, sphingophospholipid metabolism and fatty acid metabolism related network were acutely perturbed. Quantitative real time polymerase chain reaction (RT-PCR) analysis were performed to evaluate the expression of genes related to the two pathways for verifying the above results. The results show that changed biomarkers and pathways may provide evidence to insight into drug action mechanisms and enable us to increase research productivity toward metabolomics drug discovery. PMID:24454691

Harnessing pain heterogeneity and RNA transcriptome to identify blood–based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model

PubMed Central

Grace, Peter M.; Hurley, Daniel; Barratt, Daniel T.; Tsykin, Anna; Watkins, Linda R.; Rolan, Paul E.; Hutchinson, Mark R.

2017-01-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. PMID:22697386

Identification of Significant Gene Signatures and Prognostic Biomarkers for Patients With Cervical Cancer by Integrated Bioinformatic Methods

PubMed Central

Li, Xiaofang; Tian, Run; Gao, Hugh; Yan, Feng; Ying, Le; Yang, Yongkang; Yang, Pei

2018-01-01

Cervical cancer is the leading cause of death with gynecological malignancies. We aimed to explore the molecular mechanism of carcinogenesis and biomarkers for cervical cancer by integrated bioinformatic analysis. We employed RNA-sequencing details of 254 cervical squamous cell carcinomas and 3 normal samples from The Cancer Genome Atlas. To explore the distinct pathways, messenger RNA expression was submitted to a Gene Set Enrichment Analysis. Kyoto Encyclopedia of Genes and Genomes and protein–protein interaction network analysis of differentially expressed genes were performed. Then, we conducted pathway enrichment analysis for modules acquired in protein–protein interaction analysis and obtained a list of pathways in every module. After intersecting the results from the 3 approaches, we evaluated the survival rates of both mutual pathways and genes in the pathway, and 5 survival-related genes were obtained. Finally, Cox hazards ratio analysis of these 5 genes was performed. DNA replication pathway (P < .001; 12 genes included) was suggested to have the strongest association with the prognosis of cervical squamous cancer. In total, 5 of the 12 genes, namely, minichromosome maintenance 2, minichromosome maintenance 4, minichromosome maintenance 5, proliferating cell nuclear antigen, and ribonuclease H2 subunit A were significantly correlated with survival. Minichromosome maintenance 5 was shown as an independent prognostic biomarker for patients with cervical cancer. This study identified a distinct pathway (DNA replication). Five genes which may be prognostic biomarkers and minichromosome maintenance 5 were identified as independent prognostic biomarkers for patients with cervical cancer. PMID:29642758

Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

PubMed

Collins, Mahlon A; An, Jiyan; Hood, Brian L; Conrads, Thomas P; Bowser, Robert P

2015-11-06

Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

Network Analysis of Human Genes Influencing Susceptibility to Mycobacterial Infections

PubMed Central

Lipner, Ettie M.; Garcia, Benjamin J.; Strong, Michael

2016-01-01

Tuberculosis and nontuberculous mycobacterial infections constitute a high burden of pulmonary disease in humans, resulting in over 1.5 million deaths per year. Building on the premise that genetic factors influence the instance, progression, and defense of infectious disease, we undertook a systems biology approach to investigate relationships among genetic factors that may play a role in increased susceptibility or control of mycobacterial infections. We combined literature and database mining with network analysis and pathway enrichment analysis to examine genes, pathways, and networks, involved in the human response to Mycobacterium tuberculosis and nontuberculous mycobacterial infections. This approach allowed us to examine functional relationships among reported genes, and to identify novel genes and enriched pathways that may play a role in mycobacterial susceptibility or control. Our findings suggest that the primary pathways and genes influencing mycobacterial infection control involve an interplay between innate and adaptive immune proteins and pathways. Signaling pathways involved in autoimmune disease were significantly enriched as revealed in our networks. Mycobacterial disease susceptibility networks were also examined within the context of gene-chemical relationships, in order to identify putative drugs and nutrients with potential beneficial immunomodulatory or anti-mycobacterial effects. PMID:26751573

Investigating multiple dysregulated pathways in rheumatoid arthritis based on pathway interaction network.

PubMed

Song, Xian-Dong; Song, Xian-Xu; Liu, Gui-Bo; Ren, Chun-Hui; Sun, Yuan-Bo; Liu, Ke-Xin; Liu, Bo; Liang, Shuang; Zhu, Zhu

2018-03-01

The traditional methods of identifying biomarkers in rheumatoid arthritis (RA) have focussed on the differentially expressed pathways or individual pathways, which however, neglect the interactions between pathways. To better understand the pathogenesis of RA, we aimed to identify dysregulated pathway sets using a pathway interaction network (PIN), which considered interactions among pathways. Firstly, RA-related gene expression profile data, protein-protein interactions (PPI) data and pathway data were taken up from the corresponding databases. Secondly, principal component analysis method was used to calculate the pathway activity of each of the pathway, and then a seed pathway was identified using data gleaned from the pathway activity. A PIN was then constructed based on the gene expression profile, pathway data, and PPI information. Finally, the dysregulated pathways were extracted from the PIN based on the seed pathway using the method of support vector machines and an area under the curve (AUC) index. The PIN comprised of a total of 854 pathways and 1064 pathway interactions. The greatest change in the activity score between RA and control samples was observed in the pathway of epigenetic regulation of gene expression, which was extracted and regarded as the seed pathway. Starting with this seed pathway, one maximum pathway set containing 10 dysregulated pathways was extracted from the PIN, having an AUC of 0.8249, and the result indicated that this pathway set could distinguish RA from the controls. These 10 dysregulated pathways might be potential biomarkers for RA diagnosis and treatment in the future.

Plant MetGenMAP: an integrative analysis system for plant systems biology

USDA-ARS?s Scientific Manuscript database

We have developed a web-based system, Plant MetGenMAP, which can identify significantly altered biochemical pathways and highly affected biological processes, predict functional roles of pathway genes, and potential pathway-related regulatory motifs from transcript and metabolite profile datasets. P...

Major carcinogenic pathways identified by gene expression analysis of peritoneal mesotheliomas following chemical treatment in F344 rats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Yongbaek; Thai-Vu Ton; De Angelo, Anthony B.

2006-07-15

This study was performed to characterize the gene expression profile and to identify the major carcinogenic pathways involved in rat peritoneal mesothelioma (RPM) formation following treatment of Fischer 344 rats with o-nitrotoluene (o-NT) or bromochloracetic acid (BCA). Oligo arrays, with over 20,000 target genes, were used to evaluate o-NT- and BCA-induced RPMs, when compared to a non-transformed mesothelial cell line (Fred-PE). Analysis using Ingenuity Pathway Analysis software revealed 169 cancer-related genes that were categorized into binding activity, growth and proliferation, cell cycle progression, apoptosis, and invasion and metastasis. The microarray data were validated by positive correlation with quantitative real-time RT-PCRmore » on 16 selected genes including igf1, tgfb3 and nov. Important carcinogenic pathways involved in RPM formation included insulin-like growth factor 1 (IGF-1), p38 MAPkinase, Wnt/{beta}-catenin and integrin signaling pathways. This study demonstrated that mesotheliomas in rats exposed to o-NT- and BCA were similar to mesotheliomas in humans, at least at the cellular and molecular level.« less

Pathway analysis of high-throughput biological data within a Bayesian network framework.

PubMed

Isci, Senol; Ozturk, Cengizhan; Jones, Jon; Otu, Hasan H

2011-06-15

Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Proposed method takes into account the connectivity and relatedness between nodes of the pathway through factoring pathway topology in its model. Our simulations using synthetic data demonstrated robustness of our approach. We tested proposed method, Bayesian Pathway Analysis (BPA), on human microarray data regarding renal cell carcinoma (RCC) and compared our results with gene set enrichment analysis. BPA was able to find broader and more specific pathways related to RCC. Accompanying BPA software (BPAS) package is freely available for academic use at http://bumil.boun.edu.tr/bpa.

A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations.

PubMed

Zhang, Han; Wheeler, William; Hyland, Paula L; Yang, Yifan; Shi, Jianxin; Chatterjee, Nilanjan; Yu, Kai

2016-06-01

Meta-analysis of multiple genome-wide association studies (GWAS) has become an effective approach for detecting single nucleotide polymorphism (SNP) associations with complex traits. However, it is difficult to integrate the readily accessible SNP-level summary statistics from a meta-analysis into more powerful multi-marker testing procedures, which generally require individual-level genetic data. We developed a general procedure called Summary based Adaptive Rank Truncated Product (sARTP) for conducting gene and pathway meta-analysis that uses only SNP-level summary statistics in combination with genotype correlation estimated from a panel of individual-level genetic data. We demonstrated the validity and power advantage of sARTP through empirical and simulated data. We conducted a comprehensive pathway-based meta-analysis with sARTP on type 2 diabetes (T2D) by integrating SNP-level summary statistics from two large studies consisting of 19,809 T2D cases and 111,181 controls with European ancestry. Among 4,713 candidate pathways from which genes in neighborhoods of 170 GWAS established T2D loci were excluded, we detected 43 T2D globally significant pathways (with Bonferroni corrected p-values < 0.05), which included the insulin signaling pathway and T2D pathway defined by KEGG, as well as the pathways defined according to specific gene expression patterns on pancreatic adenocarcinoma, hepatocellular carcinoma, and bladder carcinoma. Using summary data from 8 eastern Asian T2D GWAS with 6,952 cases and 11,865 controls, we showed 7 out of the 43 pathways identified in European populations remained to be significant in eastern Asians at the false discovery rate of 0.1. We created an R package and a web-based tool for sARTP with the capability to analyze pathways with thousands of genes and tens of thousands of SNPs.

A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations

PubMed Central

Zhang, Han; Wheeler, William; Hyland, Paula L.; Yang, Yifan; Shi, Jianxin; Chatterjee, Nilanjan; Yu, Kai

2016-01-01

Meta-analysis of multiple genome-wide association studies (GWAS) has become an effective approach for detecting single nucleotide polymorphism (SNP) associations with complex traits. However, it is difficult to integrate the readily accessible SNP-level summary statistics from a meta-analysis into more powerful multi-marker testing procedures, which generally require individual-level genetic data. We developed a general procedure called Summary based Adaptive Rank Truncated Product (sARTP) for conducting gene and pathway meta-analysis that uses only SNP-level summary statistics in combination with genotype correlation estimated from a panel of individual-level genetic data. We demonstrated the validity and power advantage of sARTP through empirical and simulated data. We conducted a comprehensive pathway-based meta-analysis with sARTP on type 2 diabetes (T2D) by integrating SNP-level summary statistics from two large studies consisting of 19,809 T2D cases and 111,181 controls with European ancestry. Among 4,713 candidate pathways from which genes in neighborhoods of 170 GWAS established T2D loci were excluded, we detected 43 T2D globally significant pathways (with Bonferroni corrected p-values < 0.05), which included the insulin signaling pathway and T2D pathway defined by KEGG, as well as the pathways defined according to specific gene expression patterns on pancreatic adenocarcinoma, hepatocellular carcinoma, and bladder carcinoma. Using summary data from 8 eastern Asian T2D GWAS with 6,952 cases and 11,865 controls, we showed 7 out of the 43 pathways identified in European populations remained to be significant in eastern Asians at the false discovery rate of 0.1. We created an R package and a web-based tool for sARTP with the capability to analyze pathways with thousands of genes and tens of thousands of SNPs. PMID:27362418

Mining featured biomarkers associated with prostatic carcinoma based on bioinformatics.

PubMed

Piao, Guanying; Wu, Jiarui

2013-11-01

To analyze the differentially expressed genes and identify featured biomarkers from prostatic carcinoma. The software "Significance Analysis of Microarray" (SAM) was used to identify the differentially coexpressed genes (DCGs). The DCGs existed in two datasets were analyzed by GO (Gene Ontology) functional annotation. A total of 389 DCGs were obtained. By GO analysis, we found these DCGs were closely related with the acinus development, TGF-β receptor and signal transduction pathways. Furthermore, five featured biomarkers were discovered by interaction analysis. These important signal pathways and oncogenes may provide potential therapeutic targets for prostatic carcinoma.

Surprisal analysis of genome-wide transcript profiling identifies differentially expressed genes and pathways associated with four growth conditions in the microalga Chlamydomonas.

PubMed

Bogaert, Kenny A; Manoharan-Basil, Sheeba S; Perez, Emilie; Levine, Raphael D; Remacle, Francoise; Remacle, Claire

2018-01-01

The usual cultivation mode of the green microalga Chlamydomonas is liquid medium and light. However, the microalga can also be grown on agar plates and in darkness. Our aim is to analyze and compare gene expression of cells cultivated in these different conditions. For that purpose, RNA-seq data are obtained from Chlamydomonas samples of two different labs grown in four environmental conditions (agar@light, agar@dark, liquid@light, liquid@dark). The RNA seq data are analyzed by surprisal analysis, which allows the simultaneous meta-analysis of all the samples. First we identify a balance state, which defines a state where the expression levels are similar in all the samples irrespectively of their growth conditions, or lab origin. In addition our analysis identifies additional constraints needed to quantify the deviation with respect to the balance state. The first constraint differentiates the agar samples versus the liquid ones; the second constraint the dark samples versus the light ones. The two constraints are almost of equal importance. Pathways involved in stress responses are found in the agar phenotype while the liquid phenotype comprises ATP and NADH production pathways. Remodeling of membrane is suggested in the dark phenotype while photosynthetic pathways characterize the light phenotype. The same trends are also present when performing purely statistical analysis such as K-means clustering and differentially expressed genes.

Quantitative Proteomics Identifies Activation of Hallmark Pathways of Cancer in Patient Melanoma.

PubMed

Byrum, Stephanie D; Larson, Signe K; Avaritt, Nathan L; Moreland, Linley E; Mackintosh, Samuel G; Cheung, Wang L; Tackett, Alan J

2013-03-01

Molecular pathways regulating melanoma initiation and progression are potential targets of therapeutic development for this aggressive cancer. Identification and molecular analysis of these pathways in patients has been primarily restricted to targeted studies on individual proteins. Here, we report the most comprehensive analysis of formalin-fixed paraffin-embedded human melanoma tissues using quantitative proteomics. From 61 patient samples, we identified 171 proteins varying in abundance among benign nevi, primary melanoma, and metastatic melanoma. Seventy-three percent of these proteins were validated by immunohistochemistry staining of malignant melanoma tissues from the Human Protein Atlas database. Our results reveal that molecular pathways involved with tumor cell proliferation, motility, and apoptosis are mis-regulated in melanoma. These data provide the most comprehensive proteome resource on patient melanoma and reveal insight into the molecular mechanisms driving melanoma progression.

AOP: An R Package For Sufficient Causal Analysis in Pathway ...

EPA Pesticide Factsheets

Summary: How can I quickly find the key events in a pathway that I need to monitor to predict that a/an beneficial/adverse event/outcome will occur? This is a key question when using signaling pathways for drug/chemical screening in pharma-cology, toxicology and risk assessment. By identifying these sufficient causal key events, we have fewer events to monitor for a pathway, thereby decreasing assay costs and time, while maximizing the value of the information. I have developed the “aop” package which uses backdoor analysis of causal net-works to identify these minimal sets of key events that are suf-ficient for making causal predictions. Availability and Implementation: The source and binary are available online through the Bioconductor project (http://www.bioconductor.org/) as an R package titled “aop”. The R/Bioconductor package runs within the R statistical envi-ronment. The package has functions that can take pathways (as directed graphs) formatted as a Cytoscape JSON file as input, or pathways can be represented as directed graphs us-ing the R/Bioconductor “graph” package. The “aop” package has functions that can perform backdoor analysis to identify the minimal set of key events for making causal predictions.Contact: burgoon.lyle@epa.gov This paper describes an R/Bioconductor package that was developed to facilitate the identification of key events within an AOP that are the minimal set of sufficient key events that need to be tested/monit

A method for gene-based pathway analysis using genomewide association study summary statistics reveals nine new type 1 diabetes associations.

PubMed

Evangelou, Marina; Smyth, Deborah J; Fortune, Mary D; Burren, Oliver S; Walker, Neil M; Guo, Hui; Onengut-Gumuscu, Suna; Chen, Wei-Min; Concannon, Patrick; Rich, Stephen S; Todd, John A; Wallace, Chris

2014-12-01

Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed (P=9.85×10-11) with 12 of the 22 SNPs showing P<0.05. Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, P=7.86×10-9), NRP1 (rs722988, 4.88×10-8), BAD (rs694739, 2.37×10-7), CTSB (rs1296023, 2.79×10-7), FYN (rs11964650, P=5.60×10-7), UBE2G1 (rs9906760, 5.08×10-7), MAP3K14 (rs17759555, 9.67×10-7), ITGB1 (rs1557150, 1.93×10-6), and IL7R (rs1445898, 2.76×10-6). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available. © 2014 The Authors. ** Genetic Epidemiology published by Wiley Periodicals, Inc.

Radiogenomics: a systems biology approach to understanding genetic risk factors for radiotherapy toxicity ?

PubMed Central

Herskind, Carsten; Talbot, Christopher J.; Kerns, Sarah L.; Veldwijk, Marlon R.; Rosenstein, Barry S.; West, Catharine M. L.

2016-01-01

Adverse reactions in normal tissue after radiotherapy (RT) limit the dose that can be given to tumour cells. Since 80% of individual variation in clinical response is estimated to be caused by patient-related factors, identifying these factors might allow prediction of patients with increased risk of developing severe reactions. While inactivation of cell renewal is considered a major cause of toxicity in early-reacting normal tissues, complex interactions involving multiple cell types, cytokines, and hypoxia seem important for late reactions. Here, we review ‘omics’ approaches such as screening of genetic polymorphisms or gene expression analysis, and assess the potential of epigenetic factors, posttranslational modification, signal transduction, and metabolism. Furthermore, functional assays have suggested possible associations with clinical risk of adverse reaction. Pathway analysis incorporating different ‘omics’ approaches may be more efficient in identifying critical pathways than pathway analysis based on single ‘omics’ data sets. Integrating these pathways with functional assays may be powerful in identifying multiple subgroups of RT patients characterized by different mechanisms. Thus ‘omics’ and functional approaches may synergize if they are integrated into radiogenomics ‘systems biology’ to facilitate the goal of individualised radiotherapy. PMID:26944314

Comparative analysis of gene expression profiles of hip articular cartilage between non-traumatic necrosis and osteoarthritis.

PubMed

Wang, Wenyu; Liu, Yang; Hao, Jingcan; Zheng, Shuyu; Wen, Yan; Xiao, Xiao; He, Awen; Fan, Qianrui; Zhang, Feng; Liu, Ruiyu

2016-10-10

Hip cartilage destruction is consistently observed in the non-traumatic osteonecrosis of femoral head (NOFH) and accelerates its bone necrosis. The molecular mechanism underlying the cartilage damage of NOFH remains elusive. In this study, we conducted a systematically comparative study of gene expression profiles between NOFH and osteoarthritis (OA). Hip articular cartilage specimens were collected from 12 NOFH patients and 12 controls with traumatic femoral neck fracture for microarray (n=4) and quantitative real-time PCR validation experiments (n=8). Gene expression profiling of articular cartilage was performed using Agilent Human 4×44K Microarray chip. The accuracy of microarray experiment was further validated by qRT-PCR. Gene expression results of OA hip cartilage were derived from previously published study. Significance Analysis of Microarrays (SAM) software was applied for identifying differently expressed genes. Gene ontology (GO) and pathway enrichment analysis were conducted by Gene Set Enrichment Analysis software and DAVID tool, respectively. Totally, 27 differently expressed genes were identified for NOFH. Comparing the gene expression profiles of NOFH cartilage and OA cartilage detected 8 common differently expressed genes, including COL5A1, OGN, ANGPTL4, CRIP1, NFIL3, METRNL, ID2 and STEAP1. GO comparative analysis identified 10 common significant GO terms, mainly implicated in apoptosis and development process. Pathway comparative analysis observed that ECM-receptor interaction pathway and focal adhesion pathway were enriched in the differently expressed genes of both NOFH and hip OA. In conclusion, we identified a set of differently expressed genes, GO and pathways for NOFH articular destruction, some of which were also involved in the hip OA. Our study results may help to reveal the pathogenetic similarities and differences of cartilage damage of NOFH and hip OA. Copyright © 2016 Elsevier B.V. All rights reserved.

MicroRNA meta-signature of oral cancer: evidence from a meta-analysis.

PubMed

Zeljic, Katarina; Jovanovic, Ivan; Jovanovic, Jasmina; Magic, Zvonko; Stankovic, Aleksandra; Supic, Gordana

2018-03-01

It was the aim of the study to identify commonly deregulated miRNAs in oral cancer patients by performing a meta-analysis of previously published miRNA expression profiles in cancer and matched normal non-cancerous tissue in such patients. Meta-analysis included seven independent studies analyzed by a vote-counting method followed by bioinformatic enrichment analysis. Amongst seven independent studies included in the meta-analysis, 20 miRNAs were found to be deregulated in oral cancer when compared with non-cancerous tissue. Eleven miRNAs were consistently up-regulated in three or more studies (miR-21-5p, miR-31-5p, miR-135b-5p, miR-31-3p, miR-93-5p, miR-34b-5p, miR-424-5p, miR-18a-5p, miR-455-3p, miR-450a-5p, miR-21-3p), and nine were down-regulated (miR-139-5p, miR-30a-3p, miR-376c-3p, miR-885-5p, miR-375, miR-486-5p, miR-411-5p, miR-133a-3p, miR-30a-5p). The meta-signature of identified miRNAs was functionally characterized by KEGG enrichment analysis. Twenty-four KEGG pathways were significantly enriched, and TGF-beta signaling was the most enriched signaling pathway. The highest number of meta-signature miRNAs was involved in the sphingolipid signaling pathway. Natural killer cell-mediated cytotoxicity was the pathway with most genes regulated by identified miRNAs. The rest of the enriched pathways in our miRNA list describe different malignancies and signaling. The identified miRNA meta-signature might be considered as a potential battery of biomarkers when distinguishing oral cancer tissue from normal, non-cancerous tissue. Further mechanistic studies are warranted in order to confirm and fully elucidate the role of deregulated miRNAs in oral cancer.

Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing.

PubMed

Chen, Long; Zhang, Chunhua; Wang, Yanling; Li, Yuqian; Han, Qiaoqiao; Yang, Huixin; Zhu, Yuechun

2017-08-01

Human glucose-6-phosphate dehydrogenase (G6PD) is a crucial enzyme in the pentose phosphate pathway, and serves an important role in biosynthesis and the redox balance. G6PD deficiency is a major cause of neonatal jaundice and acute hemolyticanemia, and recently, G6PD has been associated with diseases including inflammation and cancer. The aim of the present study was to conduct a search of the National Center for Biotechnology Information PubMed library for articles discussing G6PD. Genes that were identified to be associated with G6PD were recorded, and the frequency at which each gene appeared was calculated. Gene ontology (GO), pathway and network analyses were then performed. A total of 98 G6PD‑associated genes and 33 microRNAs (miRNAs) that potentially regulate G6PD were identified. The 98 G6PD‑associated genes were then sub‑classified into three functional groups by GO analysis, followed by analysis of function, pathway, network, and disease association. Out of the 47 signaling pathways identified, seven were significantly correlated with G6PD‑associated genes. At least two out of four independent programs identified the 33 miRNAs that were predicted to target G6PD. miR‑1207‑5P, miR‑1 and miR‑125a‑5p were predicted by all four software programs to target G6PD. The results of the present study revealed that dysregulation of G6PD was associated with cancer, autoimmune diseases, and oxidative stress‑induced disorders. These results revealed the potential roles of G6PD‑regulated signaling and metabolic pathways in the etiology of these diseases.

Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing

PubMed Central

Chen, Long; Zhang, Chunhua; Wang, Yanling; Li, Yuqian; Han, Qiaoqiao; Yang, Huixin; Zhu, Yuechun

2017-01-01

Human glucose-6-phosphate dehydrogenase (G6PD) is a crucial enzyme in the pentose phosphate pathway, and serves an important role in biosynthesis and the redox balance. G6PD deficiency is a major cause of neonatal jaundice and acute hemolyticanemia, and recently, G6PD has been associated with diseases including inflammation and cancer. The aim of the present study was to conduct a search of the National Center for Biotechnology Information PubMed library for articles discussing G6PD. Genes that were identified to be associated with G6PD were recorded, and the frequency at which each gene appeared was calculated. Gene ontology (GO), pathway and network analyses were then performed. A total of 98 G6PD-associated genes and 33 microRNAs (miRNAs) that potentially regulate G6PD were identified. The 98 G6PD-associated genes were then sub-classified into three functional groups by GO analysis, followed by analysis of function, pathway, network, and disease association. Out of the 47 signaling pathways identified, seven were significantly correlated with G6PD-associated genes. At least two out of four independent programs identified the 33 miRNAs that were predicted to target G6PD. miR-1207-5P, miR-1 and miR-125a-5p were predicted by all four software programs to target G6PD. The results of the present study revealed that dysregulation of G6PD was associated with cancer, autoimmune diseases, and oxidative stress-induced disorders. These results revealed the potential roles of G6PD-regulated signaling and metabolic pathways in the etiology of these diseases. PMID:28627690

Use of a bovine genome chip to identify new biological pathways for beef quality in cattle.

PubMed

Guifen, Liu; Xiaomu, Liu; Fachun, Wan; Xiuwen, Tan; Haijian, Cheng; Enliang, Song

2012-12-01

The accumulation of muscle is largely influenced by the genetic background of cattle. Muscle tissue was collected from the longissimus muscle of Lilu beef cattle at 12, 18, 24 and 30 months old. Using meat quality analysis, we found that the Lilu beef cattle have good production and slaughter performance, the performance meets the criterion of beef cattle. Microarray analysis was able to identify a total of 4,219 genes that are differentially expressed (P ≤ 0.01) between the two groups of cattle (12 vs 18; 18 vs 24; 24 vs 30). Bioinformatics analysis results suggested that most of the differentially expressed genes are involved in the metabolic pathways and neuroactive ligand-receptor interaction pathways. In the future study that aims to look for genes relating to growth and meat quality, we will focus on the genes that have been shown to have a significant variation between groups and are involved in the two pathways.

The experience of seeking, gaining and maintaining employment after traumatic spinal cord injury and the vocational pathways involved.

PubMed

Hilton, Gillean; Unsworth, Carolyn A; Stuckey, Ruth; Murphy, Gregory C

2018-01-01

Vocational potential in people with spinal cord injury (SCI) are unrealised with rates of employment substantially lower than in the labour force participation of the general population and the pre-injury employment rates. To understand the experience and pathway of people achieving employment outcome after traumatic spinal cord injury by; classifying participants into employment outcome groups of stable, unstable and without employment; identifying pre and post-injury pathways for participants in each group and, exploring the experiences of people of seeking, gaining and maintaining employment. Thirty-one participants were interviewed. Mixed methods approach including interpretive phenomenological analysis and vocational pathway mapping of quantitative data. The most common pathway identified was from study and work pre-injury to stable employment post-injury. Four super-ordinate themes were identified from the interpretive phenomenological analysis; expectations of work, system impacts, worker identity and social supports. Implications for clinical practice include fostering cultural change, strategies for system navigation, promotion of worker identity and optimal use of social supports. The findings increase insight and understanding of the complex experience of employment after spinal cord injury. There is opportunity to guide experimental research, policy development and education concerning the complexity of the return to work experience and factors that influence pathways.

The use of social network analysis to examine the transmission of Salmonella spp. within a vertically integrated broiler enterprise.

PubMed

Crabb, Helen Kathleen; Allen, Joanne Lee; Devlin, Joanne Maree; Firestone, Simon Matthew; Stevenson, Mark Anthony; Gilkerson, James Rudkin

2018-05-01

To better understand factors influencing infectious agent dispersal within a livestock population information is needed on the nature and frequency of contacts between farm enterprises. This study uses social network analysis to describe the contact network within a vertically integrated broiler poultry enterprise to identify the potential horizontal and vertical transmission pathways for Salmonella spp. Nodes (farms, sheds, production facilities) were identified and the daily movement of commodities (eggs, birds, feed, litter) and people between nodes were extracted from routinely kept farm records. Three time periods were examined in detail, 1- and 8- and 17-weeks of the production cycle and contact networks were described for all movements, and by commodity and production type. All nodes were linked by at least one movement during the study period but network density was low indicating that all potential pathways between nodes did not exist. Salmonella spp. transmission via vertical or horizontal pathways can only occur along directed pathways when those pathways are present. Only two locations (breeder or feed nodes) were identified where the transmission of a single Salmonella spp. clone could theoretically percolate through the network to the broiler or processing nodes. Only the feed transmission pathway directly connected all parts of the network. Copyright © 2017 Elsevier Ltd. All rights reserved.

A hierarchical approach employing metabolic and gene expression profiles to identify the pathways that confer cytotoxicity in HepG2 cells

PubMed Central

Li, Zheng; Srivastava, Shireesh; Yang, Xuerui; Mittal, Sheenu; Norton, Paul; Resau, James; Haab, Brian; Chan, Christina

2007-01-01

Background Free fatty acids (FFA) and tumor necrosis factor alpha (TNF-α) have been implicated in the pathogenesis of many obesity-related metabolic disorders. When human hepatoblastoma cells (HepG2) were exposed to different types of FFA and TNF-α, saturated fatty acid was found to be cytotoxic and its toxicity was exacerbated by TNF-α. In order to identify the processes associated with the toxicity of saturated FFA and TNF-α, the metabolic and gene expression profiles were measured to characterize the cellular states. A computational model was developed to integrate these disparate data to reveal the underlying pathways and mechanisms involved in saturated fatty acid toxicity. Results A hierarchical framework consisting of three stages was developed to identify the processes and genes that regulate the toxicity. First, discriminant analysis identified that fatty acid oxidation and intracellular triglyceride accumulation were the most relevant in differentiating the cytotoxic phenotype. Second, gene set enrichment analysis (GSEA) was applied to the cDNA microarray data to identify the transcriptionally altered pathways and processes. Finally, the genes and gene sets that regulate the metabolic responses identified in step 1 were identified by integrating the expression of the enriched gene sets and the metabolic profiles with a multi-block partial least squares (MBPLS) regression model. Conclusion The hierarchical approach suggested potential mechanisms involved in mediating the cytotoxic and cytoprotective pathways, as well as identified novel targets, such as NADH dehydrogenases, aldehyde dehydrogenases 1A1 (ALDH1A1) and endothelial membrane protein 3 (EMP3) as modulator of the toxic phenotypes. These predictions, as well as, some specific targets that were suggested by the analysis were experimentally validated. PMID:17498300

High-throughput sequencing of mGluR signaling pathway genes reveals enrichment of rare variants in autism.

PubMed

Kelleher, Raymond J; Geigenmüller, Ute; Hovhannisyan, Hayk; Trautman, Edwin; Pinard, Robert; Rathmell, Barbara; Carpenter, Randall; Margulies, David

2012-01-01

Identification of common molecular pathways affected by genetic variation in autism is important for understanding disease pathogenesis and devising effective therapies. Here, we test the hypothesis that rare genetic variation in the metabotropic glutamate-receptor (mGluR) signaling pathway contributes to autism susceptibility. Single-nucleotide variants in genes encoding components of the mGluR signaling pathway were identified by high-throughput multiplex sequencing of pooled samples from 290 non-syndromic autism cases and 300 ethnically matched controls on two independent next-generation platforms. This analysis revealed significant enrichment of rare functional variants in the mGluR pathway in autism cases. Higher burdens of rare, potentially deleterious variants were identified in autism cases for three pathway genes previously implicated in syndromic autism spectrum disorder, TSC1, TSC2, and SHANK3, suggesting that genetic variation in these genes also contributes to risk for non-syndromic autism. In addition, our analysis identified HOMER1, which encodes a postsynaptic density-localized scaffolding protein that interacts with Shank3 to regulate mGluR activity, as a novel autism-risk gene. Rare, potentially deleterious HOMER1 variants identified uniquely in the autism population affected functionally important protein regions or regulatory sequences and co-segregated closely with autism among children of affected families. We also identified rare ASD-associated coding variants predicted to have damaging effects on components of the Ras/MAPK cascade. Collectively, these findings suggest that altered signaling downstream of mGluRs contributes to the pathogenesis of non-syndromic autism.

High-Throughput Sequencing of mGluR Signaling Pathway Genes Reveals Enrichment of Rare Variants in Autism

PubMed Central

Hovhannisyan, Hayk; Trautman, Edwin; Pinard, Robert; Rathmell, Barbara; Carpenter, Randall; Margulies, David

2012-01-01

Identification of common molecular pathways affected by genetic variation in autism is important for understanding disease pathogenesis and devising effective therapies. Here, we test the hypothesis that rare genetic variation in the metabotropic glutamate-receptor (mGluR) signaling pathway contributes to autism susceptibility. Single-nucleotide variants in genes encoding components of the mGluR signaling pathway were identified by high-throughput multiplex sequencing of pooled samples from 290 non-syndromic autism cases and 300 ethnically matched controls on two independent next-generation platforms. This analysis revealed significant enrichment of rare functional variants in the mGluR pathway in autism cases. Higher burdens of rare, potentially deleterious variants were identified in autism cases for three pathway genes previously implicated in syndromic autism spectrum disorder, TSC1, TSC2, and SHANK3, suggesting that genetic variation in these genes also contributes to risk for non-syndromic autism. In addition, our analysis identified HOMER1, which encodes a postsynaptic density-localized scaffolding protein that interacts with Shank3 to regulate mGluR activity, as a novel autism-risk gene. Rare, potentially deleterious HOMER1 variants identified uniquely in the autism population affected functionally important protein regions or regulatory sequences and co-segregated closely with autism among children of affected families. We also identified rare ASD-associated coding variants predicted to have damaging effects on components of the Ras/MAPK cascade. Collectively, these findings suggest that altered signaling downstream of mGluRs contributes to the pathogenesis of non-syndromic autism. PMID:22558107

Pathway-based discovery of genetic interactions in breast cancer

PubMed Central

Xu, Zack Z.; Boone, Charles; Lange, Carol A.

2017-01-01

Breast cancer is the second largest cause of cancer death among U.S. women and the leading cause of cancer death among women worldwide. Genome-wide association studies (GWAS) have identified several genetic variants associated with susceptibility to breast cancer, but these still explain less than half of the estimated genetic contribution to the disease. Combinations of variants (i.e. genetic interactions) may play an important role in breast cancer susceptibility. However, due to a lack of statistical power, the current tests for genetic interactions from GWAS data mainly leverage prior knowledge to focus on small sets of genes or SNPs that are known to have an association with breast cancer. Thus, many genetic interactions, particularly among novel variants, remain understudied. Reverse-genetic interaction screens in model organisms have shown that genetic interactions frequently cluster into highly structured motifs, where members of the same pathway share similar patterns of genetic interactions. Based on this key observation, we recently developed a method called BridGE to search for such structured motifs in genetic networks derived from GWAS studies and identify pathway-level genetic interactions in human populations. We applied BridGE to six independent breast cancer cohorts and identified significant pathway-level interactions in five cohorts. Joint analysis across all five cohorts revealed a high confidence consensus set of genetic interactions with support in multiple cohorts. The discovered interactions implicated the glutathione conjugation, vitamin D receptor, purine metabolism, mitotic prometaphase, and steroid hormone biosynthesis pathways as major modifiers of breast cancer risk. Notably, while many of the pathways identified by BridGE show clear relevance to breast cancer, variants in these pathways had not been previously discovered by traditional single variant association tests, or single pathway enrichment analysis that does not consider SNP-SNP interactions. PMID:28957314

Time course of gene expression during mouse skeletal muscle hypertrophy

PubMed Central

Lee, Jonah D.; England, Jonathan H.; Esser, Karyn A.; McCarthy, John J.

2013-01-01

The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy. PMID:23869057

Time course of gene expression during mouse skeletal muscle hypertrophy.

PubMed

Chaillou, Thomas; Lee, Jonah D; England, Jonathan H; Esser, Karyn A; McCarthy, John J

2013-10-01

The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy.

Prioritizing biological pathways by recognizing context in time-series gene expression data.

PubMed

Lee, Jusang; Jo, Kyuri; Lee, Sunwon; Kang, Jaewoo; Kim, Sun

2016-12-23

The primary goal of pathway analysis using transcriptome data is to find significantly perturbed pathways. However, pathway analysis is not always successful in identifying pathways that are truly relevant to the context under study. A major reason for this difficulty is that a single gene is involved in multiple pathways. In the KEGG pathway database, there are 146 genes, each of which is involved in more than 20 pathways. Thus activation of even a single gene will result in activation of many pathways. This complex relationship often makes the pathway analysis very difficult. While we need much more powerful pathway analysis methods, a readily available alternative way is to incorporate the literature information. In this study, we propose a novel approach for prioritizing pathways by combining results from both pathway analysis tools and literature information. The basic idea is as follows. Whenever there are enough articles that provide evidence on which pathways are relevant to the context, we can be assured that the pathways are indeed related to the context, which is termed as relevance in this paper. However, if there are few or no articles reported, then we should rely on the results from the pathway analysis tools, which is termed as significance in this paper. We realized this concept as an algorithm by introducing Context Score and Impact Score and then combining the two into a single score. Our method ranked truly relevant pathways significantly higher than existing pathway analysis tools in experiments with two data sets. Our novel framework was implemented as ContextTRAP by utilizing two existing tools, TRAP and BEST. ContextTRAP will be a useful tool for the pathway based analysis of gene expression data since the user can specify the context of the biological experiment in a set of keywords. The web version of ContextTRAP is available at http://biohealth.snu.ac.kr/software/contextTRAP .

Systems Genetics Analysis of GWAS reveals Novel Associations between Key Biological Processes and Coronary Artery Disease

PubMed Central

Ghosh, Sujoy; Vivar, Juan; Nelson, Christopher P; Willenborg, Christina; Segrè, Ayellet V; Mäkinen, Ville-Petteri; Nikpay, Majid; Erdmann, Jeannette; Blankenberg, Stefan; O'Donnell, Christopher; März, Winfried; Laaksonen, Reijo; Stewart, Alexandre FR; Epstein, Stephen E; Shah, Svati H; Granger, Christopher B; Hazen, Stanley L; Kathiresan, Sekar; Reilly, Muredach P; Yang, Xia; Quertermous, Thomas; Samani, Nilesh J; Schunkert, Heribert; Assimes, Themistocles L; McPherson, Ruth

2016-01-01

Objective Genome-wide association (GWA) studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks. Approaches and Results Employing pathways (gene sets) from Reactome, we carried out a two-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CADGWAS data sets (9,889 cases/11,089 controls), nominally significant gene-sets were tested for replication in a meta-analysis of 9 additional studies (15,502 cases/55,730 controls) from the CARDIoGRAM Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication p<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix integrity, innate immunity, axon guidance, and signaling by PDRF, NOTCH, and the TGF-β/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (e.g. semaphorin regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared to random networks (p<0.001). Network centrality analysis (‘degree’ and ‘betweenness’) further identified genes (e.g. NCAM1, FYN, FURIN etc.) likely to play critical roles in the maintenance and functioning of several of the replicated pathways. Conclusions These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD. PMID:25977570

Emergence of differentially regulated pathways associated with the development of regional specificity in chicken skin.

PubMed

Chang, Kai-Wei; Huang, Nancy A; Liu, I-Hsuan; Wang, Yi-Hui; Wu, Ping; Tseng, Yen-Tzu; Hughes, Michael W; Jiang, Ting Xin; Tsai, Mong-Hsun; Chen, Chien-Yu; Oyang, Yen-Jen; Lin, En-Chung; Chuong, Cheng-Ming; Lin, Shau-Ping

2015-01-23

Regional specificity allows different skin regions to exhibit different characteristics, enabling complementary functions to make effective use of the integumentary surface. Chickens exhibit a high degree of regional specificity in the skin and can serve as a good model for when and how these regional differences begin to emerge. We used developing feather and scale regions in embryonic chickens as a model to gauge the differences in their molecular pathways. We employed cosine similarity analysis to identify the differentially regulated and co-regulated genes. We applied low cell techniques for expression validation and chromatin immunoprecipitation (ChIP)-based enhancer identification to overcome limited cell availabilities from embryonic chicken skin. We identified a specific set of genes demonstrating a high correlation as being differentially expressed during feather and scale development and maturation. Some members of the WNT, TGF-beta/BMP, and Notch family known to be involved in feathering skin differentiation were found to be differentially regulated. Interestingly, we also found genes along calcium channel pathways that are differentially regulated. From the analysis of differentially regulated pathways, we used calcium signaling pathways as an example for further verification. Some voltage-gated calcium channel subunits, particularly CACNA1D, are expressed spatio-temporally in the skin epithelium. These calcium signaling pathway members may be involved in developmental decisions, morphogenesis, or epithelial maturation. We further characterized enhancers associated with histone modifications, including H3K4me1, H3K27ac, and H3K27me3, near calcium channel-related genes and identified signature intensive hotspots that may be correlated with certain voltage-gated calcium channel genes. We demonstrated the applicability of cosine similarity analysis for identifying novel regulatory pathways that are differentially regulated during development. Our study concerning the effects of signaling pathways and histone signatures on enhancers suggests that voltage-gated calcium signaling may be involved in early skin development. This work lays the foundation for studying the roles of these gene pathways and their genomic regulation during the establishment of skin regional specificity.

Skin sensitizers differentially regulate signaling pathways in MUTZ-3 cells in relation to their individual potency

PubMed Central

2014-01-01

Background Due to the recent European legislations posing a ban of animal tests for safety assessment within the cosmetic industry, development of in vitro alternatives for assessment of skin sensitization is highly prioritized. To date, proposed in vitro assays are mainly based on single biomarkers, which so far have not been able to classify and stratify chemicals into subgroups, related to risk or potency. Methods Recently, we presented the Genomic Allergen Rapid Detection (GARD) assay for assessment of chemical sensitizers. In this paper, we show how the genome wide readout of GARD can be expanded and used to identify differentially regulated pathways relating to individual chemical sensitizers. In this study, we investigated the mechanisms of action of a range of skin sensitizers through pathway identification, pathway classification and transcription factor analysis and related this to the reactive mechanisms and potency of the sensitizing agents. Results By transcriptional profiling of chemically stimulated MUTZ-3 cells, 33 canonical pathways intimately involved in sensitization to chemical substances were identified. The results showed that metabolic processes, cell cycling and oxidative stress responses are the key events activated during skin sensitization, and that these functions are engaged differently depending on the reactivity mechanisms of the sensitizing agent. Furthermore, the results indicate that the chemical reactivity groups seem to gradually engage more pathways and more molecules in each pathway with increasing sensitizing potency of the chemical used for stimulation. Also, a switch in gene regulation from up to down regulation, with increasing potency, was seen both in genes involved in metabolic functions and cell cycling. These observed pathway patterns were clearly reflected in the regulatory elements identified to drive these processes, where 33 regulatory elements have been proposed for further analysis. Conclusions This study demonstrates that functional analysis of biomarkers identified from our genomics study of human MUTZ-3 cells can be used to assess sensitizing potency of chemicals in vitro, by the identification of key cellular events, such as metabolic and cell cycling pathways. PMID:24517095

Energy transport pathway in proteins: Insights from non-equilibrium molecular dynamics with elastic network model.

PubMed

Wang, Wei Bu; Liang, Yu; Zhang, Jing; Wu, Yi Dong; Du, Jian Jun; Li, Qi Ming; Zhu, Jian Zhuo; Su, Ji Guo

2018-06-22

Intra-molecular energy transport between distant functional sites plays important roles in allosterically regulating the biochemical activity of proteins. How to identify the specific intra-molecular signaling pathway from protein tertiary structure remains a challenging problem. In the present work, a non-equilibrium dynamics method based on the elastic network model (ENM) was proposed to simulate the energy propagation process and identify the specific signaling pathways within proteins. In this method, a given residue was perturbed and the propagation of energy was simulated by non-equilibrium dynamics in the normal modes space of ENM. After that, the simulation results were transformed from the normal modes space to the Cartesian coordinate space to identify the intra-protein energy transduction pathways. The proposed method was applied to myosin and the third PDZ domain (PDZ3) of PSD-95 as case studies. For myosin, two signaling pathways were identified, which mediate the energy transductions form the nucleotide binding site to the 50 kDa cleft and the converter subdomain, respectively. For PDZ3, one specific signaling pathway was identified, through which the intra-protein energy was transduced from ligand binding site to the distant opposite side of the protein. It is also found that comparing with the commonly used cross-correlation analysis method, the proposed method can identify the anisotropic energy transduction pathways more effectively.

Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis

PubMed Central

Zhu, Zonghao; Shen, Qiang; Zhu, Liang; Wei, Xiaokang

2017-01-01

The present study aimed to identify key genes and pathways associated with spinal cord injury (SCI) and subsequently investigate possible therapeutic targets for the condition. The array data of GSE20907 was downloaded from the Gene Expression Omnibus database and 24 gene chips, including 3-day, 4-day, 1-week, 2-week and 1-month post-SCI together with control propriospinal neurons, were used for the analysis. The raw data was normalized and then the differentially expressed genes (DEGs) in the (A) 2-week post-SCI group vs. control group, (B) 1-month post-SCI group vs. control group, (C) 1-month and 2-week post-SCI group vs. control group, and (D) all post-SCI groups vs. all control groups, were analyzed with a limma package. Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for DEGs were performed. Cluster analysis was performed using ClusterOne plugins. All the DEGs identified were associated with immune and inflammatory responses. Signal transducer and activator of transcription 3 (STAT3), erb-B2 receptor tyrosine kinase 4 (ERBB4) and cytochrome B-245, α polypeptide (CYBA) were in the network diagrams of (A), (C) and (D), respectively. The enrichment analysis of DEGs identified in all samples demonstrated that the DEGs were also enriched in the chemokine signaling pathway (enriched in STAT3) and the high-affinity immunoglobulin E receptor (FcεRI) signaling pathway [enriched in proto-oncogene, src family tyrosine kinase (LYN)]. Immune and inflammatory responses serve significant roles in SCI. STAT3, ERBB4 and CYBA may be key genes associated with SCI at certain stages. Furthermore, STAT3 and LYN may be involved in the development of SCI via the chemokine and FcεRI signaling pathways, respectively. PMID:28731189

Neural pathways for colorectal control, relevance to spinal cord injury and treatment: a narrative review.

PubMed

Callaghan, Brid; Furness, John B; Pustovit, Ruslan V

2018-03-01

Narrative review. The purpose is to review the organisation of the nerve pathways that control defecation and to relate this knowledge to the deficits in colorectal function after SCI. A literature review was conducted to identify salient features of defecation control pathways and the functional consequences of damage to these pathways in SCI. The control pathways for defecation have separate pontine centres under cortical control that influence defecation. The pontine centres connect, separately, with autonomic preganglionic neurons of the spinal defecation centres and somatic motor neurons of Onuf's nucleus in the sacral spinal cord. Organised propulsive motor patterns can be generated by stimulation of the spinal defecation centres. Activation of the somatic neurons contracts the external sphincter. The analysis aids in interpreting the consequences of SCI and predicts therapeutic strategies. Analysis of the bowel control circuits identifies sites at which bowel function may be modulated after SCI. Colokinetic drugs that elicit propulsive contractions of the colorectum may provide valuable augmentation of non-pharmacological bowel management procedures.

Identification of key microRNAs and genes in preeclampsia by bioinformatics analysis

PubMed Central

Luo, Shouling; Cao, Nannan; Tang, Yao; Gu, Weirong

2017-01-01

Preeclampsia is a leading cause of perinatal maternal–foetal mortality and morbidity. The aim of this study is to identify the key microRNAs and genes in preeclampsia and uncover their potential functions. We downloaded the miRNA expression profile of GSE84260 and the gene expression profile of GSE73374 from the Gene Expression Omnibus database. Differentially expressed miRNAs and genes were identified and compared to miRNA-target information from MiRWalk 2.0, and a total of 65 differentially expressed miRNAs (DEMIs), including 32 up-regulated miRNAs and 33 down-regulated miRNAs, and 91 differentially expressed genes (DEGs), including 83 up-regulated genes and 8 down-regulated genes, were identified. The pathway enrichment analyses of the DEMIs showed that the up-regulated DEMIs were enriched in the Hippo signalling pathway and MAPK signalling pathway, and the down-regulated DEMIs were enriched in HTLV-I infection and miRNAs in cancers. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses of the DEGs were performed using Multifaceted Analysis Tool for Human Transcriptome. The up-regulated DEGs were enriched in biological processes (BPs), including the response to cAMP, response to hydrogen peroxide and cell-cell adhesion mediated by integrin; no enrichment of down-regulated DEGs was identified. KEGG analysis showed that the up-regulated DEGs were enriched in the Hippo signalling pathway and pathways in cancer. A PPI network of the DEGs was constructed by using Cytoscape software, and FOS, STAT1, MMP14, ITGB1, VCAN, DUSP1, LDHA, MCL1, MET, and ZFP36 were identified as the hub genes. The current study illustrates a characteristic microRNA profile and gene profile in preeclampsia, which may contribute to the interpretation of the progression of preeclampsia and provide novel biomarkers and therapeutic targets for preeclampsia. PMID:28594854

Harnessing pain heterogeneity and RNA transcriptome to identify blood-based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model.

PubMed

Grace, Peter M; Hurley, Daniel; Barratt, Daniel T; Tsykin, Anna; Watkins, Linda R; Rolan, Paul E; Hutchinson, Mark R

2012-09-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. © 2012 The Authors. Journal of Neurochemistry © 2012 International Society for Neurochemistry.

Hepatic Proteomic Analysis Revealed Altered Metabolic Pathways in Insulin Resistant Akt1+/-/Akt2-/-Mice

PubMed Central

Pedersen, Brian A; Wang, Weiwen; Taylor, Jared F; Khattab, Omar S; Chen, Yu-Han; Edwards, Robert A; Yazdi, Puya G; Wang, Ping H

2015-01-01

Objective The aim of this study was to identify liver proteome changes in a mouse model of severe insulin resistance and markedly decreased leptin levels. Methods Two-dimensional differential gel electrophoresis was utilized to identify liver proteome changes in AKT1+/-/AKT2-/- mice. Proteins with altered levels were identified with tandem mass spectrometry. Ingenuity Pathway analysis was performed for the interpretation of the biological significance of the observed proteomic changes. Results 11 proteins were identified from 2 biological replicates to be differentially expressed by a ratio of at least 1.3 between age-matched insulin resistant (Akt1+/-/Akt2-/-) and wild type mice. Albumin and mitochondrial ornithine aminotransferase were detected from multiple spots, which suggest post-translational modifications. Enzymes of the urea cycle were common members of top regulated pathways. Conclusion Our results help to unveil the regulation of the liver proteome underlying altered metabolism in an animal model of severe insulin resistance. PMID:26455965

Dynamic regulation of genetic pathways and targets during aging in Caenorhabditis elegans.

PubMed

He, Kan; Zhou, Tao; Shao, Jiaofang; Ren, Xiaoliang; Zhao, Zhongying; Liu, Dahai

2014-03-01

Numerous genetic targets and some individual pathways associated with aging have been identified using the worm model. However, less is known about the genetic mechanisms of aging in genome wide, particularly at the level of multiple pathways as well as the regulatory networks during aging. Here, we employed the gene expression datasets of three time points during aging in Caenorhabditis elegans (C. elegans) and performed the approach of gene set enrichment analysis (GSEA) on each dataset between adjacent stages. As a result, multiple genetic pathways and targets were identified as significantly down- or up-regulated. Among them, 5 truly aging-dependent signaling pathways including MAPK signaling pathway, mTOR signaling pathway, Wnt signaling pathway, TGF-beta signaling pathway and ErbB signaling pathway as well as 12 significantly associated genes were identified with dynamic expression pattern during aging. On the other hand, the continued declines in the regulation of several metabolic pathways have been demonstrated to display age-related changes. Furthermore, the reconstructed regulatory networks based on three of aging related Chromatin immunoprecipitation experiments followed by sequencing (ChIP-seq) datasets and the expression matrices of 154 involved genes in above signaling pathways provide new insights into aging at the multiple pathways level. The combination of multiple genetic pathways and targets needs to be taken into consideration in future studies of aging, in which the dynamic regulation would be uncovered.

Exome Sequencing Identifies Potentially Druggable Mutations in Nasopharyngeal Carcinoma.

PubMed

Chow, Yock Ping; Tan, Lu Ping; Chai, San Jiun; Abdul Aziz, Norazlin; Choo, Siew Woh; Lim, Paul Vey Hong; Pathmanathan, Rajadurai; Mohd Kornain, Noor Kaslina; Lum, Chee Lun; Pua, Kin Choo; Yap, Yoke Yeow; Tan, Tee Yong; Teo, Soo Hwang; Khoo, Alan Soo-Beng; Patel, Vyomesh

2017-03-03

In this study, we first performed whole exome sequencing of DNA from 10 untreated and clinically annotated fresh frozen nasopharyngeal carcinoma (NPC) biopsies and matched bloods to identify somatically mutated genes that may be amenable to targeted therapeutic strategies. We identified a total of 323 mutations which were either non-synonymous (n = 238) or synonymous (n = 85). Furthermore, our analysis revealed genes in key cancer pathways (DNA repair, cell cycle regulation, apoptosis, immune response, lipid signaling) were mutated, of which those in the lipid-signaling pathway were the most enriched. We next extended our analysis on a prioritized sub-set of 37 mutated genes plus top 5 mutated cancer genes listed in COSMIC using a custom designed HaloPlex target enrichment panel with an additional 88 NPC samples. Our analysis identified 160 additional non-synonymous mutations in 37/42 genes in 66/88 samples. Of these, 99/160 mutations within potentially druggable pathways were further selected for validation. Sanger sequencing revealed that 77/99 variants were true positives, giving an accuracy of 78%. Taken together, our study indicated that ~72% (n = 71/98) of NPC samples harbored mutations in one of the four cancer pathways (EGFR-PI3K-Akt-mTOR, NOTCH, NF-κB, DNA repair) which may be potentially useful as predictive biomarkers of response to matched targeted therapies.

Exome Sequencing Identifies Potentially Druggable Mutations in Nasopharyngeal Carcinoma

PubMed Central

Chow, Yock Ping; Tan, Lu Ping; Chai, San Jiun; Abdul Aziz, Norazlin; Choo, Siew Woh; Lim, Paul Vey Hong; Pathmanathan, Rajadurai; Mohd Kornain, Noor Kaslina; Lum, Chee Lun; Pua, Kin Choo; Yap, Yoke Yeow; Tan, Tee Yong; Teo, Soo Hwang; Khoo, Alan Soo-Beng; Patel, Vyomesh

2017-01-01

In this study, we first performed whole exome sequencing of DNA from 10 untreated and clinically annotated fresh frozen nasopharyngeal carcinoma (NPC) biopsies and matched bloods to identify somatically mutated genes that may be amenable to targeted therapeutic strategies. We identified a total of 323 mutations which were either non-synonymous (n = 238) or synonymous (n = 85). Furthermore, our analysis revealed genes in key cancer pathways (DNA repair, cell cycle regulation, apoptosis, immune response, lipid signaling) were mutated, of which those in the lipid-signaling pathway were the most enriched. We next extended our analysis on a prioritized sub-set of 37 mutated genes plus top 5 mutated cancer genes listed in COSMIC using a custom designed HaloPlex target enrichment panel with an additional 88 NPC samples. Our analysis identified 160 additional non-synonymous mutations in 37/42 genes in 66/88 samples. Of these, 99/160 mutations within potentially druggable pathways were further selected for validation. Sanger sequencing revealed that 77/99 variants were true positives, giving an accuracy of 78%. Taken together, our study indicated that ~72% (n = 71/98) of NPC samples harbored mutations in one of the four cancer pathways (EGFR-PI3K-Akt-mTOR, NOTCH, NF-κB, DNA repair) which may be potentially useful as predictive biomarkers of response to matched targeted therapies. PMID:28256603

Systems Biology and Birth Defects Prevention: Blockade of the Glucocorticoid Receptor Prevents Arsenic-Induced Birth Defects

PubMed Central

Ahir, Bhavesh K.; Sanders, Alison P.; Rager, Julia E.

2013-01-01

Background: The biological mechanisms by which environmental metals are associated with birth defects are largely unknown. Systems biology–based approaches may help to identify key pathways that mediate metal-induced birth defects as well as potential targets for prevention. Objectives: First, we applied a novel computational approach to identify a prioritized biological pathway that associates metals with birth defects. Second, in a laboratory setting, we sought to determine whether inhibition of the identified pathway prevents developmental defects. Methods: Seven environmental metals were selected for inclusion in the computational analysis: arsenic, cadmium, chromium, lead, mercury, nickel, and selenium. We used an in silico strategy to predict genes and pathways associated with both metal exposure and developmental defects. The most significant pathway was identified and tested using an in ovo whole chick embryo culture assay. We further evaluated the role of the pathway as a mediator of metal-induced toxicity using the in vitro midbrain micromass culture assay. Results: The glucocorticoid receptor pathway was computationally predicted to be a key mediator of multiple metal-induced birth defects. In the chick embryo model, structural malformations induced by inorganic arsenic (iAs) were prevented when signaling of the glucocorticoid receptor pathway was inhibited. Further, glucocorticoid receptor inhibition demonstrated partial to complete protection from both iAs- and cadmium-induced neurodevelopmental toxicity in vitro. Conclusions: Our findings highlight a novel approach to computationally identify a targeted biological pathway for examining birth defects prevention. PMID:23458687

Multilayer-omics analysis of renal cell carcinoma, including the whole exome, methylome and transcriptome.

PubMed

Arai, Eri; Sakamoto, Hiromi; Ichikawa, Hitoshi; Totsuka, Hirohiko; Chiku, Suenori; Gotoh, Masahiro; Mori, Taisuke; Nakatani, Tamao; Ohnami, Sumiko; Nakagawa, Tohru; Fujimoto, Hiroyuki; Wang, Linghua; Aburatani, Hiroyuki; Yoshida, Teruhiko; Kanai, Yae

2014-09-15

The aim of this study was to identify pathways that have a significant impact during renal carcinogenesis. Sixty-seven paired samples of both noncancerous renal cortex tissue and cancerous tissue from patients with clear cell renal cell carcinomas (RCCs) were subjected to whole-exome, methylome and transcriptome analyses using Agilent SureSelect All Exon capture followed by sequencing on an Illumina HiSeq 2000 platform, Illumina Infinium HumanMethylation27 BeadArray and Agilent SurePrint Human Gene Expression microarray, respectively. Sanger sequencing and quantitative reverse transcription-PCR were performed for technical verification. MetaCore software was used for pathway analysis. Somatic nonsynonymous single-nucleotide mutations, insertions/deletions and intragenic breaks of 2,153, 359 and 8 genes were detected, respectively. Mutations of GCN1L1, MED12 and CCNC, which are members of CDK8 mediator complex directly regulating β-catenin-driven transcription, were identified in 16% of the RCCs. Mutations of MACF1, which functions in the Wnt/β-catenin signaling pathway, were identified in 4% of the RCCs. A combination of methylome and transcriptome analyses further highlighted the significant role of the Wnt/β-catenin signaling pathway in renal carcinogenesis. Genetic aberrations and reduced expression of ERC2 and ABCA13 were frequent in RCCs, and MTOR mutations were identified as one of the major disrupters of cell signaling during renal carcinogenesis. Our results confirm that multilayer-omics analysis can be a powerful tool for revealing pathways that play a significant role in carcinogenesis. © 2014 The Authors. Published by Wiley Periodicals, Inc. on behalf of UICC.

Multilayer-omics analysis of renal cell carcinoma, including the whole exome, methylome and transcriptome

PubMed Central

Arai, Eri; Sakamoto, Hiromi; Ichikawa, Hitoshi; Totsuka, Hirohiko; Chiku, Suenori; Gotoh, Masahiro; Mori, Taisuke; Nakatani, Tamao; Ohnami, Sumiko; Nakagawa, Tohru; Fujimoto, Hiroyuki; Wang, Linghua; Aburatani, Hiroyuki; Yoshida, Teruhiko; Kanai, Yae

2014-01-01

The aim of this study was to identify pathways that have a significant impact during renal carcinogenesis. Sixty-seven paired samples of both noncancerous renal cortex tissue and cancerous tissue from patients with clear cell renal cell carcinomas (RCCs) were subjected to whole-exome, methylome and transcriptome analyses using Agilent SureSelect All Exon capture followed by sequencing on an Illumina HiSeq 2000 platform, Illumina Infinium HumanMethylation27 BeadArray and Agilent SurePrint Human Gene Expression microarray, respectively. Sanger sequencing and quantitative reverse transcription-PCR were performed for technical verification. MetaCore software was used for pathway analysis. Somatic nonsynonymous single-nucleotide mutations, insertions/deletions and intragenic breaks of 2,153, 359 and 8 genes were detected, respectively. Mutations of GCN1L1, MED12 and CCNC, which are members of CDK8 mediator complex directly regulating β-catenin-driven transcription, were identified in 16% of the RCCs. Mutations of MACF1, which functions in the Wnt/β-catenin signaling pathway, were identified in 4% of the RCCs. A combination of methylome and transcriptome analyses further highlighted the significant role of the Wnt/β-catenin signaling pathway in renal carcinogenesis. Genetic aberrations and reduced expression of ERC2 and ABCA13 were frequent in RCCs, and MTOR mutations were identified as one of the major disrupters of cell signaling during renal carcinogenesis. Our results confirm that multilayer-omics analysis can be a powerful tool for revealing pathways that play a significant role in carcinogenesis. PMID:24504440

Pathway analysis from lists of microRNAs: common pitfalls and alternative strategy

PubMed Central

Godard, Patrice; van Eyll, Jonathan

2015-01-01

MicroRNAs (miRNAs) are involved in the regulation of gene expression at a post-transcriptional level. As such, monitoring miRNA expression has been increasingly used to assess their role in regulatory mechanisms of biological processes. In large scale studies, once miRNAs of interest have been identified, the target genes they regulate are often inferred using algorithms or databases. A pathway analysis is then often performed in order to generate hypotheses about the relevant biological functions controlled by the miRNA signature. Here we show that the method widely used in scientific literature to identify these pathways is biased and leads to inaccurate results. In addition to describing the bias and its origin we present an alternative strategy to identify potential biological functions specifically impacted by a miRNA signature. More generally, our study exemplifies the crucial need of relevant negative controls when developing, and using, bioinformatics methods. PMID:25800743

Comparative transcriptomes analysis of the wing disc between two silkworm strains with different size of wings

PubMed Central

Zhang, Jing; Blessing, Danso; Wu, Chenyu; Liu, Na; Li, Juan; Qin, Sheng

2017-01-01

Wings of Bombyx mori (B. mori) develop from the primordium, and different B. mori strains have different wing types. In order to identify the key factors influencing B. mori wing development, we chose strains P50 and U11, which are typical for normal wing and minute wing phenotypes, respectively. We dissected the wing disc on the 1st-day of wandering stage (P50D1 and U11D1), 2nd-day of wandering stage (P50D2 and U11D2), and 3rd-day of wandering stage (P50D3 and U11D3). Subsequently, RNA-sequencing (RNA-Seq) was performed on both strains in order to construct their gene expression profiles. P50 exhibited 628 genes differentially expressed to U11, 324 up-regulated genes, and 304 down-regulated genes. Five enriched gene ontology (GO) terms were identified by GO enrichment analysis based on these differentially expressed genes (DEGs). KEGG enrichment analysis results showed that the DEGs were enriched in five pathways; of these, we identified three pathways related to the development of wings. The three pathways include amino sugar and nucleotide sugar metabolism pathway, proteasome signaling pathway, and the Hippo signaling pathway. The representative genes in the enrichment pathways were further verified by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). The RNA-Seq and qRT-PCR results were largely consistent with each other. Our results also revealed that the significantly different genes obtained in our study might be involved in the development of the size of B. mori wings. In addition, several KEGG enriched pathways might be involved in the regulation of the pathways of wing formation. These results provide a basis for further research of wing development in B. mori. PMID:28617839

Investigating dysregulated pathways in Staphylococcus aureus (SA) exposed macrophages based on pathway interaction network.

PubMed

Zhou, Wei; Zhang, Yan; Li, Yue-Hua; Wang, Shuang; Zhang, Jing-Jing; Zhang, Cui-Xia; Zhang, Zhi-Sheng

2017-02-01

This work aimed to identify dysregulated pathways for Staphylococcus aureus (SA) exposed macrophages based on pathway interaction network (PIN). The inference of dysregulated pathways was comprised of four steps: preparing gene expression data, protein-protein interaction (PPI) data and pathway data; constructing a PIN dependent on the data and Pearson correlation coefficient (PCC); selecting seed pathway from PIN by computing activity score for each pathway according to principal component analysis (PCA) method; and investigating dysregulated pathways in a minimum set of pathways (MSP) utilizing seed pathway and the area under the receiver operating characteristics curve (AUC) index implemented in support vector machines (SVM) model. A total of 20,545 genes, 449,833 interactions and 1189 pathways were obtained in the gene expression data, PPI data and pathway data, respectively. The PIN was consisted of 8388 interactions and 1189 nodes, and Respiratory electron transport, ATP synthesis by chemiosmotic coupling, and heat production by uncoupling proteins was identified as the seed pathway. Finally, 15 dysregulated pathways in MSP (AUC=0.999) were obtained for SA infected samples, such as Respiratory electron transport and DNA Replication. We have identified 15 dysregulated pathways for SA infected macrophages based on PIN. The findings might provide potential biomarkers for early detection and therapy of SA infection, and give insights to reveal the molecular mechanism underlying SA infections. However, how these dysregulated pathways worked together still needs to be studied. Copyright © 2016 Elsevier Ltd. All rights reserved.

Inter-species pathway perturbation prediction via data-driven detection of functional homology.

PubMed

Hafemeister, Christoph; Romero, Roberto; Bilal, Erhan; Meyer, Pablo; Norel, Raquel; Rhrissorrakrai, Kahn; Bonneau, Richard; Tarca, Adi L

2015-02-15

Experiments in animal models are often conducted to infer how humans will respond to stimuli by assuming that the same biological pathways will be affected in both organisms. The limitations of this assumption were tested in the IMPROVER Species Translation Challenge, where 52 stimuli were applied to both human and rat cells and perturbed pathways were identified. In the Inter-species Pathway Perturbation Prediction sub-challenge, multiple teams proposed methods to use rat transcription data from 26 stimuli to predict human gene set and pathway activity under the same perturbations. Submissions were evaluated using three performance metrics on data from the remaining 26 stimuli. We present two approaches, ranked second in this challenge, that do not rely on sequence-based orthology between rat and human genes to translate pathway perturbation state but instead identify transcriptional response orthologs across a set of training conditions. The translation from rat to human accomplished by these so-called direct methods is not dependent on the particular analysis method used to identify perturbed gene sets. In contrast, machine learning-based methods require performing a pathway analysis initially and then mapping the pathway activity between organisms. Unlike most machine learning approaches, direct methods can be used to predict the activation of a human pathway for a new (test) stimuli, even when that pathway was never activated by a training stimuli. Gene expression data are available from ArrayExpress (accession E-MTAB-2091), while software implementations are available from http://bioinformaticsprb.med.wayne.edu?p=50 and http://goo.gl/hJny3h. christoph.hafemeister@nyu.edu or atarca@med.wayne.edu. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Identification of interactive gene networks: a novel approach in gene array profiling of myometrial events during guinea pig pregnancy.

PubMed

Mason, Clifford W; Swaan, Peter W; Weiner, Carl P

2006-06-01

The transition from myometrial quiescence to activation is poorly understood, and the analysis of array data is limited by the available data mining tools. We applied functional analysis and logical operations along regulatory gene networks to identify molecular processes and pathways underlying quiescence and activation. We analyzed some 18,400 transcripts and variants in guinea pig myometrium at stages corresponding to quiescence and activation, and compared them to the nonpregnant (control) counterpart using a functional mapping tool, MetaCore (GeneGo, St Joseph, MI) to identify novel gene networks composed of biological pathways during mid (MP) and late (LP) pregnancy. Genes altered during quiescence and or activation were identified following gene specific comparisons with myometrium from nonpregnant animals, and then linked to curated pathways and formulated networks. The MP and LP networks were subtracted from each other to identify unique genomic events during those periods. For example, changes 2-fold or greater in genes mediating protein biosynthesis, programmed cell death, microtubule polymerization, and microtubule based movement were noted during the transition to LP. We describe a novel approach combining microarrays and genetic data to identify networks associated with normal myometrial events. The resulting insights help identify potential biomarkers and permit future targeted investigations of these pathways or networks to confirm or refute their importance.

RNA-Seq Meta-analysis identifies genes in skeletal muscle associated with gain and intake across a multi-season study of crossbred beef steers.

PubMed

Keel, Brittney N; Zarek, Christina M; Keele, John W; Kuehn, Larry A; Snelling, Warren M; Oliver, William T; Freetly, Harvey C; Lindholm-Perry, Amanda K

2018-06-04

Feed intake and body weight gain are economically important inputs and outputs of beef production systems. The purpose of this study was to discover differentially expressed genes that will be robust for feed intake and gain across a large segment of the cattle industry. Transcriptomic studies often suffer from issues with reproducibility and cross-validation. One way to improve reproducibility is by integrating multiple datasets via meta-analysis. RNA sequencing (RNA-Seq) was performed on longissimus dorsi muscle from 80 steers (5 cohorts, each with 16 animals) selected from the outside fringe of a bivariate gain and feed intake distribution to understand the genes and pathways involved in feed efficiency. In each cohort, 16 steers were selected from one of four gain and feed intake phenotypes (n = 4 per phenotype) in a 2 × 2 factorial arrangement with gain and feed intake as main effect variables. Each cohort was analyzed as a single experiment using a generalized linear model and results from the 5 cohort analyses were combined in a meta-analysis to identify differentially expressed genes (DEG) across the cohorts. A total of 51 genes were differentially expressed for the main effect of gain, 109 genes for the intake main effect, and 11 genes for the gain x intake interaction (P corrected  < 0.05). A jackknife sensitivity analysis showed that, in general, the meta-analysis produced robust DEGs for the two main effects and their interaction. Pathways identified from over-represented genes included mitochondrial energy production and oxidative stress pathways for the main effect of gain due to DEG including GPD1, NDUFA6, UQCRQ, ACTC1, and MGST3. For intake, metabolic pathways including amino acid biosynthesis and degradation were identified, and for the interaction analysis the pathways identified included GADD45, pyridoxal 5'phosphate salvage, and caveolar mediated endocytosis signaling. Variation among DEG identified by cohort suggests that environment and breed may play large roles in the expression of genes associated with feed efficiency in the muscle of beef cattle. Meta-analyses of transcriptome data from groups of animals over multiple cohorts may be necessary to elucidate the genetics contributing these types of biological phenotypes.

[Not Available].

PubMed

Yanashima, Ryoji; Kitagawa, Noriyuki; Matsubara, Yoshiya; Weatheritt, Robert; Oka, Kotaro; Kikuchi, Shinichi; Tomita, Masaru; Ishizaki, Shun

2009-01-01

The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path.

Veterinary Medicine and Multi-Omics Research for Future Nutrition Targets: Metabolomics and Transcriptomics of the Common Degenerative Mitral Valve Disease in Dogs.

PubMed

Li, Qinghong; Freeman, Lisa M; Rush, John E; Huggins, Gordon S; Kennedy, Adam D; Labuda, Jeffrey A; Laflamme, Dorothy P; Hannah, Steven S

2015-08-01

Canine degenerative mitral valve disease (DMVD) is the most common form of heart disease in dogs. The objective of this study was to identify cellular and metabolic pathways that play a role in DMVD by performing metabolomics and transcriptomics analyses on serum and tissue (mitral valve and left ventricle) samples previously collected from dogs with DMVD or healthy hearts. Gas or liquid chromatography followed by mass spectrophotometry were used to identify metabolites in serum. Transcriptomics analysis of tissue samples was completed using RNA-seq, and selected targets were confirmed by RT-qPCR. Random Forest analysis was used to classify the metabolites that best predicted the presence of DMVD. Results identified 41 known and 13 unknown serum metabolites that were significantly different between healthy and DMVD dogs, representing alterations in fat and glucose energy metabolism, oxidative stress, and other pathways. The three metabolites with the greatest single effect in the Random Forest analysis were γ-glutamylmethionine, oxidized glutathione, and asymmetric dimethylarginine. Transcriptomics analysis identified 812 differentially expressed transcripts in left ventricle samples and 263 in mitral valve samples, representing changes in energy metabolism, antioxidant function, nitric oxide signaling, and extracellular matrix homeostasis pathways. Many of the identified alterations may benefit from nutritional or medical management. Our study provides evidence of the growing importance of integrative approaches in multi-omics research in veterinary and nutritional sciences.

Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes

PubMed Central

Biankin, Andrew V.; Waddell, Nicola; Kassahn, Karin S.; Gingras, Marie-Claude; Muthuswamy, Lakshmi B.; Johns, Amber L.; Miller, David K.; Wilson, Peter J.; Patch, Ann-Marie; Wu, Jianmin; Chang, David K.; Cowley, Mark J.; Gardiner, Brooke B.; Song, Sarah; Harliwong, Ivon; Idrisoglu, Senel; Nourse, Craig; Nourbakhsh, Ehsan; Manning, Suzanne; Wani, Shivangi; Gongora, Milena; Pajic, Marina; Scarlett, Christopher J.; Gill, Anthony J.; Pinho, Andreia V.; Rooman, Ilse; Anderson, Matthew; Holmes, Oliver; Leonard, Conrad; Taylor, Darrin; Wood, Scott; Xu, Qinying; Nones, Katia; Fink, J. Lynn; Christ, Angelika; Bruxner, Tim; Cloonan, Nicole; Kolle, Gabriel; Newell, Felicity; Pinese, Mark; Mead, R. Scott; Humphris, Jeremy L.; Kaplan, Warren; Jones, Marc D.; Colvin, Emily K.; Nagrial, Adnan M.; Humphrey, Emily S.; Chou, Angela; Chin, Venessa T.; Chantrill, Lorraine A.; Mawson, Amanda; Samra, Jaswinder S.; Kench, James G.; Lovell, Jessica A.; Daly, Roger J.; Merrett, Neil D.; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q.; Barbour, Andrew; Zeps, Nikolajs; Kakkar, Nipun; Zhao, Fengmei; Wu, Yuan Qing; Wang, Min; Muzny, Donna M.; Fisher, William E.; Brunicardi, F. Charles; Hodges, Sally E.; Reid, Jeffrey G.; Drummond, Jennifer; Chang, Kyle; Han, Yi; Lewis, Lora R.; Dinh, Huyen; Buhay, Christian J.; Beck, Timothy; Timms, Lee; Sam, Michelle; Begley, Kimberly; Brown, Andrew; Pai, Deepa; Panchal, Ami; Buchner, Nicholas; De Borja, Richard; Denroche, Robert E.; Yung, Christina K.; Serra, Stefano; Onetto, Nicole; Mukhopadhyay, Debabrata; Tsao, Ming-Sound; Shaw, Patricia A.; Petersen, Gloria M.; Gallinger, Steven; Hruban, Ralph H.; Maitra, Anirban; Iacobuzio-Donahue, Christine A.; Schulick, Richard D.; Wolfgang, Christopher L.; Morgan, Richard A.; Lawlor, Rita T.; Capelli, Paola; Corbo, Vincenzo; Scardoni, Maria; Tortora, Giampaolo; Tempero, Margaret A.; Mann, Karen M.; Jenkins, Nancy A.; Perez-Mancera, Pedro A.; Adams, David J.; Largaespada, David A.; Wessels, Lodewyk F. A.; Rust, Alistair G.; Stein, Lincoln D.; Tuveson, David A.; Copeland, Neal G.; Musgrove, Elizabeth A.; Scarpa, Aldo; Eshleman, James R.; Hudson, Thomas J.; Sutherland, Robert L.; Wheeler, David A.; Pearson, John V.; McPherson, John D.; Gibbs, Richard A.; Grimmond, Sean M.

2012-01-01

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis. PMID:23103869

Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes.

PubMed

Biankin, Andrew V; Waddell, Nicola; Kassahn, Karin S; Gingras, Marie-Claude; Muthuswamy, Lakshmi B; Johns, Amber L; Miller, David K; Wilson, Peter J; Patch, Ann-Marie; Wu, Jianmin; Chang, David K; Cowley, Mark J; Gardiner, Brooke B; Song, Sarah; Harliwong, Ivon; Idrisoglu, Senel; Nourse, Craig; Nourbakhsh, Ehsan; Manning, Suzanne; Wani, Shivangi; Gongora, Milena; Pajic, Marina; Scarlett, Christopher J; Gill, Anthony J; Pinho, Andreia V; Rooman, Ilse; Anderson, Matthew; Holmes, Oliver; Leonard, Conrad; Taylor, Darrin; Wood, Scott; Xu, Qinying; Nones, Katia; Fink, J Lynn; Christ, Angelika; Bruxner, Tim; Cloonan, Nicole; Kolle, Gabriel; Newell, Felicity; Pinese, Mark; Mead, R Scott; Humphris, Jeremy L; Kaplan, Warren; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chou, Angela; Chin, Venessa T; Chantrill, Lorraine A; Mawson, Amanda; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Daly, Roger J; Merrett, Neil D; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Kakkar, Nipun; Zhao, Fengmei; Wu, Yuan Qing; Wang, Min; Muzny, Donna M; Fisher, William E; Brunicardi, F Charles; Hodges, Sally E; Reid, Jeffrey G; Drummond, Jennifer; Chang, Kyle; Han, Yi; Lewis, Lora R; Dinh, Huyen; Buhay, Christian J; Beck, Timothy; Timms, Lee; Sam, Michelle; Begley, Kimberly; Brown, Andrew; Pai, Deepa; Panchal, Ami; Buchner, Nicholas; De Borja, Richard; Denroche, Robert E; Yung, Christina K; Serra, Stefano; Onetto, Nicole; Mukhopadhyay, Debabrata; Tsao, Ming-Sound; Shaw, Patricia A; Petersen, Gloria M; Gallinger, Steven; Hruban, Ralph H; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Schulick, Richard D; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Capelli, Paola; Corbo, Vincenzo; Scardoni, Maria; Tortora, Giampaolo; Tempero, Margaret A; Mann, Karen M; Jenkins, Nancy A; Perez-Mancera, Pedro A; Adams, David J; Largaespada, David A; Wessels, Lodewyk F A; Rust, Alistair G; Stein, Lincoln D; Tuveson, David A; Copeland, Neal G; Musgrove, Elizabeth A; Scarpa, Aldo; Eshleman, James R; Hudson, Thomas J; Sutherland, Robert L; Wheeler, David A; Pearson, John V; McPherson, John D; Gibbs, Richard A; Grimmond, Sean M

2012-11-15

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.

The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.

PubMed

Zhang, Chaoyang; Peng, Li; Zhang, Yaqin; Liu, Zhaoyang; Li, Wenling; Chen, Shilian; Li, Guancheng

2017-06-01

Liver cancer is a serious threat to public health and has fairly complicated pathogenesis. Therefore, the identification of key genes and pathways is of much importance for clarifying molecular mechanism of hepatocellular carcinoma (HCC) initiation and progression. HCC-associated gene expression dataset was downloaded from Gene Expression Omnibus database. Statistical software R was used for significance analysis of differentially expressed genes (DEGs) between liver cancer samples and normal samples. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, based on R software, were applied for the identification of pathways in which DEGs significantly enriched. Cytoscape software was for the construction of protein-protein interaction (PPI) network and module analysis to find the hub genes and key pathways. Finally, weighted correlation network analysis (WGCNA) was conducted to further screen critical gene modules with similar expression pattern and explore their biological significance. Significance analysis identified 1230 DEGs with fold change >2, including 632 significantly down-regulated DEGs and 598 significantly up-regulated DEGs. GO term enrichment analysis suggested that up-regulated DEG significantly enriched in immune response, cell adhesion, cell migration, type I interferon signaling pathway, and cell proliferation, and the down-regulated DEG mainly enriched in response to endoplasmic reticulum stress and endoplasmic reticulum unfolded protein response. KEGG pathway analysis found DEGs significantly enriched in five pathways including complement and coagulation cascades, focal adhesion, ECM-receptor interaction, antigen processing and presentation, and protein processing in endoplasmic reticulum. The top 10 hub genes in HCC were separately GMPS, ACACA, ALB, TGFB1, KRAS, ERBB2, BCL2, EGFR, STAT3, and CD8A, which resulted from PPI network. The top 3 gene interaction modules in PPI network enriched in immune response, organ development, and response to other organism, respectively. WGCNA revealed that the confirmed eight gene modules significantly enriched in monooxygenase and oxidoreductase activity, response to endoplasmic reticulum stress, type I interferon signaling pathway, processing, presentation and binding of peptide antigen, cellular response to cadmium and zinc ion, cell locomotion and differentiation, ribonucleoprotein complex and RNA processing, and immune system process, respectively. In conclusion, we identified some key genes and pathways closely related with HCC initiation and progression by a series of bioinformatics analysis on DEGs. These screened genes and pathways provided for a more detailed molecular mechanism underlying HCC occurrence and progression, holding promise for acting as biomarkers and potential therapeutic targets.

Plasma metabonomics study of the patients with acute anterior uveitis based on ultra-performance liquid chromatography-mass spectrometry.

PubMed

Guo, Junguo; Yan, Tingqin; Bi, Hongsheng; Xie, Xiaofeng; Wang, Xingrong; Guo, Dadong; Jiang, Haiqiang

2014-06-01

The identification of the biomarkers of patients with acute anterior uveitis (AAU) may allow for a less invasive and more accurate diagnosis, as well as serving as a predictor in AAU progression and treatment response. The aim of this study was to identify the potential biomarkers and the metabolic pathways from plasma in patients with AAU. Both plasma metabolic biomarkers and metabolic pathways in the AAU patients versus healthy volunteers were investigated using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and a metabonomics approach. The principal component analysis (PCA) was used to separate AAU patients from healthy volunteers as well as to identify the different biomarkers between the two groups. Metabolic compounds were matched to the KEGG, METLIN, and HMDB databases, and metabolic pathways associated with AAU were identified. The PCA for UPLC-MS data shows that the metabolites in AAU patients were significantly different from those of healthy volunteers. Of the 4,396 total features detected by UPLC-MS, 102 features were significantly different between AAU patients and healthy volunteers according to the variable importance plot (VIP) values (greater than two) of partial least squares discriminate analysis (PLS-DA). Thirty-three metabolic compounds were identified and were considered as potential biomarkers. Meanwhile, ten metabolic pathways were found that were related to the AAU according to the identified biomarkers. These data suggest that metabolomics study can identify potential metabolites that differ between AAU patients and healthy volunteers. Based on the PCA, PLS-DA, several potential metabolic biomarkers and pathways in AAU patients were found and identified. In addition, the UPLC-MS technique combined with metabonomics could be a suitable systematic biology tool in research in clinical problems in ophthalmology, and can provide further insight into the pathophysiology of AAU.

Shared molecular pathways and gene networks for cardiovascular disease and type 2 diabetes mellitus in women across diverse ethnicities.

PubMed

Chan, Kei Hang K; Huang, Yen-Tsung; Meng, Qingying; Wu, Chunyuan; Reiner, Alexander; Sobel, Eric M; Tinker, Lesley; Lusis, Aldons J; Yang, Xia; Liu, Simin

2014-12-01

Although cardiovascular disease (CVD) and type 2 diabetes mellitus (T2D) share many common risk factors, potential molecular mechanisms that may also be shared for these 2 disorders remain unknown. Using an integrative pathway and network analysis, we performed genome-wide association studies in 8155 blacks, 3494 Hispanic American, and 3697 Caucasian American women who participated in the national Women's Health Initiative single-nucleotide polymorphism (SNP) Health Association Resource and the Genomics and Randomized Trials Network. Eight top pathways and gene networks related to cardiomyopathy, calcium signaling, axon guidance, cell adhesion, and extracellular matrix seemed to be commonly shared between CVD and T2D across all 3 ethnic groups. We also identified ethnicity-specific pathways, such as cell cycle (specific for Hispanic American and Caucasian American) and tight junction (CVD and combined CVD and T2D in Hispanic American). In network analysis of gene-gene or protein-protein interactions, we identified key drivers that included COL1A1, COL3A1, and ELN in the shared pathways for both CVD and T2D. These key driver genes were cross-validated in multiple mouse models of diabetes mellitus and atherosclerosis. Our integrative analysis of American women of 3 ethnicities identified multiple shared biological pathways and key regulatory genes for the development of CVD and T2D. These prospective findings also support the notion that ethnicity-specific susceptibility genes and process are involved in the pathogenesis of CVD and T2D. © 2014 American Heart Association, Inc.

Low levels of serum serotonin and amino acids identified in migraine patients.

PubMed

Ren, Caixia; Liu, Jia; Zhou, Juntuo; Liang, Hui; Wang, Yayun; Sun, Yinping; Ma, Bin; Yin, Yuxin

2018-02-05

Migraine is a highly disabling primary headache associated with a high socioeconomic burden and a generally high prevalence. The clinical management of migraine remains a challenge. This study was undertaken to identify potential serum biomarkers of migraine. Using Liquid Chromatography coupled to Mass Spectrometry (LC-MS), the metabolomic profile of migraine was compared with healthy individuals. Principal component analysis (PCA) and Orthogonal partial least squares-discriminant analysis (orthoPLS-DA) showed the metabolomic profile of migraine is distinguishable from controls. Volcano plot analysis identified 10 serum metabolites significantly decreased during migraine. One of these was serotonin, and the other 9 were amino acids. Pathway analysis and enrichment analysis showed tryptophan metabolism (serotonin metabolism), arginine and proline metabolism, and aminoacyl-tRNA biosynthesis are the three most prominently altered pathways in migraine. ROC curve analysis indicated Glycyl-l-proline, N-Methyl-dl-Alanine and l-Methionine are potential sensitive and specific biomarkers for migraine. Our results show Glycyl-l-proline, N-Methyl-dl-Alanine and l-Methionine may be as specific or more specific for migraine than serotonin which is the traditional biomarker of migraine. We propose that therapeutic manipulation of these metabolites or metabolic pathways may be helpful in the prevention and treatment of migraine. Copyright © 2018 Elsevier Inc. All rights reserved.

Systems Genetics Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease.

PubMed

Ghosh, Sujoy; Vivar, Juan; Nelson, Christopher P; Willenborg, Christina; Segrè, Ayellet V; Mäkinen, Ville-Petteri; Nikpay, Majid; Erdmann, Jeannette; Blankenberg, Stefan; O'Donnell, Christopher; März, Winfried; Laaksonen, Reijo; Stewart, Alexandre F R; Epstein, Stephen E; Shah, Svati H; Granger, Christopher B; Hazen, Stanley L; Kathiresan, Sekar; Reilly, Muredach P; Yang, Xia; Quertermous, Thomas; Samani, Nilesh J; Schunkert, Heribert; Assimes, Themistocles L; McPherson, Ruth

2015-07-01

Genome-wide association studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks. Using pathways (gene sets) from Reactome, we carried out a 2-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CAD genome-wide association study data sets (9889 cases/11 089 controls), nominally significant gene sets were tested for replication in a meta-analysis of 9 additional studies (15 502 cases/55 730 controls) from the Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication P<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix (ECM) integrity, innate immunity, axon guidance, and signaling by PDRF (platelet-derived growth factor), NOTCH, and the transforming growth factor-β/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (eg, semaphoring-regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared with random networks (P<0.001). Network centrality analysis (degree and betweenness) further identified genes (eg, NCAM1, FYN, FURIN, etc) likely to play critical roles in the maintenance and functioning of several of the replicated pathways. These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD. © 2015 American Heart Association, Inc.

Identification of Major Signaling Pathways in Prion Disease Progression Using Network Analysis

PubMed Central

Newaz, Khalique; Sriram, K.; Bera, Debajyoti

2015-01-01

Prion diseases are transmissible neurodegenerative diseases that arise due to conformational change of normal, cellular prion protein (PrPC) to protease-resistant isofrom (rPrPSc). Deposition of misfolded PrpSc proteins leads to an alteration of many signaling pathways that includes immunological and apoptotic pathways. As a result, this culminates in the dysfunction and death of neuronal cells. Earlier works on transcriptomic studies have revealed some affected pathways, but it is not clear which is (are) the prime network pathway(s) that change during the disease progression and how these pathways are involved in crosstalks with each other from the time of incubation to clinical death. We perform network analysis on large-scale transcriptomic data of differentially expressed genes obtained from whole brain in six different mouse strain-prion strain combination models to determine the pathways involved in prion diseases, and to understand the role of crosstalks in disease propagation. We employ a notion of differential network centrality measures on protein interaction networks to identify the potential biological pathways involved. We also propose a crosstalk ranking method based on dynamic protein interaction networks to identify the core network elements involved in crosstalk with different pathways. We identify 148 DEGs (differentially expressed genes) potentially related to the prion disease progression. Functional association of the identified genes implicates a strong involvement of immunological pathways. We extract a bow-tie structure that is potentially dysregulated in prion disease. We also propose an ODE model for the bow-tie network. Predictions related to diseased condition suggests the downregulation of the core signaling elements (PI3Ks and AKTs) of the bow-tie network. In this work, we show using transcriptomic data that the neuronal dysfunction in prion disease is strongly related to the immunological pathways. We conclude that these immunological pathways occupy influential positions in the PFNs (protein functional networks) that are related to prion disease. Importantly, this functional network involvement is prevalent in all the five different mouse strain-prion strain combinations that we studied. We also conclude that the dysregulation of the core elements of the bow-tie structure, which belongs to PI3K-Akt signaling pathway, leads to dysregulation of the downstream components corresponding to other biological pathways. PMID:26646948

Use of RNA-seq to identify cardiac genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy.

PubMed

Friedenberg, Steven G; Chdid, Lhoucine; Keene, Bruce; Sherry, Barbara; Motsinger-Reif, Alison; Meurs, Kathryn M

2016-07-01

OBJECTIVE To identify cardiac tissue genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy (DCM). ANIMALS 8 dogs with and 5 dogs without DCM. PROCEDURES Following euthanasia, samples of left ventricular myocardium were collected from each dog. Total RNA was extracted from tissue samples, and RNA sequencing was performed on each sample. Samples from dogs with and without DCM were grouped to identify genes that were differentially regulated between the 2 populations. Overrepresentation analysis was performed on upregulated and downregulated gene sets to identify altered molecular pathways in dogs with DCM. RESULTS Genes involved in cellular energy metabolism, especially metabolism of carbohydrates and fats, were significantly downregulated in dogs with DCM. Expression of cardiac structural proteins was also altered in affected dogs. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that RNA sequencing may provide important insights into the pathogenesis of DCM in dogs and highlight pathways that should be explored to identify causative mutations and develop novel therapeutic interventions.

Dynamic transcriptomic analysis in hircine longissimus dorsi muscle from fetal to neonatal development stages.

PubMed

Zhan, Siyuan; Zhao, Wei; Song, Tianzeng; Dong, Yao; Guo, Jiazhong; Cao, Jiaxue; Zhong, Tao; Wang, Linjie; Li, Li; Zhang, Hongping

2018-01-01

Muscle growth and development from fetal to neonatal stages consist of a series of delicately regulated and orchestrated changes in expression of genes. In this study, we performed whole transcriptome profiling based on RNA-Seq of caprine longissimus dorsi muscle tissue obtained from prenatal stages (days 45, 60, and 105 of gestation) and neonatal stage (the 3-day-old newborn) to identify genes that are differentially expressed and investigate their temporal expression profiles. A total of 3276 differentially expressed genes (DEGs) were identified (Q value < 0.01). Time-series expression profile clustering analysis indicated that DEGs were significantly clustered into eight clusters which can be divided into two classes (Q value < 0.05), class I profiles with downregulated patterns and class II profiles with upregulated patterns. Based on cluster analysis, GO enrichment analysis found that 75, 25, and 8 terms to be significantly enriched in biological process (BP), cellular component (CC), and molecular function (MF) categories in class I profiles, while 35, 21, and 8 terms to be significantly enriched in BP, CC, and MF in class II profiles. KEGG pathway analysis revealed that DEGs from class I profiles were significantly enriched in 22 pathways and the most enriched pathway was Rap1 signaling pathway. DEGs from class II profiles were significantly enriched in 17 pathways and the mainly enriched pathway was AMPK signaling pathway. Finally, six selected DEGs from our sequencing results were confirmed by qPCR. Our study provides a comprehensive understanding of the molecular mechanisms during goat skeletal muscle development from fetal to neonatal stages and valuable information for future studies of muscle development in goats.

Characterisation of the macrophage transcriptome in glomerulonephritis-susceptible and -resistant rat strains

PubMed Central

Maratou, Klio; Behmoaras, Jacques; Fewings, Chris; Srivastava, Prashant; D’Souza, Zelpha; Smith, Jennifer; Game, Laurence; Cook, Terence; Aitman, Tim

2010-01-01

Crescentic glomerulonephritis (CRGN) is a major cause of rapidly progressive renal failure for which the underlying genetic basis is unknown. WKY rats show marked susceptibility to CRGN, while Lewis rats are resistant. Glomerular injury and crescent formation are macrophage-dependent and mainly explained by seven quantitative trait loci (Crgn1-7). Here, we used microarray analysis in basal and lipopolysaccharide (LPS)-stimulated macrophages to identify genes that reside on pathways predisposing WKY rats to CRGN. We detected 97 novel positional candidates for the uncharacterised Crgn3-7. We identified 10 additional secondary effector genes with profound differences in expression between the two strains (>5-fold change, <1% False Discovery Rate) for basal and LPS-stimulated macrophages. Moreover, we identified 8 genes with differentially expressed alternatively spliced isoforms, by using an in depth analysis at probe-level that allowed us to discard false positives due to polymorphisms between the two rat strains. Pathway analysis identified several common linked pathways, enriched for differentially expressed genes, which affect macrophage activation. In summary, our results identify distinct macrophage transcriptome profiles between two rat strains that differ in susceptibility to glomerulonephritis, provide novel positional candidates for Crgn3-7, and define groups of genes that play a significant role in differential regulation of macrophage activity. PMID:21179115

PathwaySplice: An R package for unbiased pathway analysis of alternative splicing in RNA-Seq data.

PubMed

Yan, Aimin; Ban, Yuguang; Gao, Zhen; Chen, Xi; Wang, Lily

2018-04-24

Pathway analysis of alternative splicing would be biased without accounting for the different number of exons or junctions associated with each gene, because genes with higher number of exons or junctions are more likely to be included in the "significant" gene list in alternative splicing. We present PathwaySplice, an R package that (1) Performs pathway analysis that explicitly adjusts for the number of exons or junctions associated with each gene; (2) Visualizes selection bias due to different number of exons or junctions for each gene and formally tests for presence of bias using logistic regression; (3) Supports gene sets based on the Gene Ontology terms, as well as more broadly defined gene sets (e.g. MSigDB) or user defined gene sets; (4) Identifies the significant genes driving pathway significance and (5) Organizes significant pathways with an enrichment map, where pathways with large number of overlapping genes are grouped together in a network graph. https://bioconductor.org/packages/release/bioc/html/PathwaySplice.html. lily.wangg@gmail.com, xi.steven.chen@gmail.com.

Identification of gene expression profiles and key genes in subchondral bone of osteoarthritis using weighted gene coexpression network analysis.

PubMed

Guo, Sheng-Min; Wang, Jian-Xiong; Li, Jin; Xu, Fang-Yuan; Wei, Quan; Wang, Hai-Ming; Huang, Hou-Qiang; Zheng, Si-Lin; Xie, Yu-Jie; Zhang, Chi

2018-06-15

Osteoarthritis (OA) significantly influences the quality life of people around the world. It is urgent to find an effective way to understand the genetic etiology of OA. We used weighted gene coexpression network analysis (WGCNA) to explore the key genes involved in the subchondral bone pathological process of OA. Fifty gene expression profiles of GSE51588 were downloaded from the Gene Expression Omnibus database. The OA-associated genes and gene ontologies were acquired from JuniorDoc. Weighted gene coexpression network analysis was used to find disease-related networks based on 21756 gene expression correlation coefficients, hub-genes with the highest connectivity in each module were selected, and the correlation between module eigengene and clinical traits was calculated. The genes in the traits-related gene coexpression modules were subject to functional annotation and pathway enrichment analysis using ClusterProfiler. A total of 73 gene modules were identified, of which, 12 modules were found with high connectivity with clinical traits. Five modules were found with enriched OA-associated genes. Moreover, 310 OA-associated genes were found, and 34 of them were among hub-genes in each module. Consequently, enrichment results indicated some key metabolic pathways, such as extracellular matrix (ECM)-receptor interaction (hsa04512), focal adhesion (hsa04510), the phosphatidylinositol 3'-kinase (PI3K)-Akt signaling pathway (PI3K-AKT) (hsa04151), transforming growth factor beta pathway, and Wnt pathway. We intended to identify some core genes, collagen (COL)6A3, COL6A1, ITGA11, BAMBI, and HCK, which could influence downstream signaling pathways once they were activated. In this study, we identified important genes within key coexpression modules, which associate with a pathological process of subchondral bone in OA. Functional analysis results could provide important information to understand the mechanism of OA. © 2018 Wiley Periodicals, Inc.

Transition paths of Met-enkephalin from Markov state modeling of a molecular dynamics trajectory.

PubMed

Banerjee, Rahul; Cukier, Robert I

2014-03-20

Conformational states and their interconversion pathways of the zwitterionic form of the pentapeptide Met-enkephalin (MetEnk) are identified. An explicit solvent molecular dynamics (MD) trajectory is used to construct a Markov state model (MSM) based on dihedral space clustering of the trajectory, and transition path theory (TPT) is applied to identify pathways between open and closed conformers. In the MD trajectory, only four of the eight backbone dihedrals exhibit bistable behavior. Defining a conformer as the string XXXX with X = "+" or "-" denoting, respectively, positive or negative values of a given dihedral angle and obtaining the populations of these conformers shows that only four conformers are highly populated, implying a strong correlation among these dihedrals. Clustering in dihedral space to construct the MSM finds the same four bistable dihedral angles. These state populations are very similar to those found directly from the MD trajectory. TPT is used to obtain pathways, parametrized by committor values, in dihedral state space that are followed in transitioning from closed to open states. Pathway costs are estimated by introducing a kinetics-based procedure that orders pathways from least (shortest) to greater cost paths. The least costly pathways in dihedral space are found to only involve the same XXXX set of dihedral angles, and the conformers accessed in the closed to open transition pathways are identified. For these major pathways, a correlation between reaction path progress (committors) and the end-to-end distance is identified. A dihedral space principal component analysis of the MD trajectory shows that the first three modes capture most of the overall fluctuation, and pick out the same four dihedrals having essentially all the weight in those modes. A MSM based on root-mean-square backbone clustering was also carried out, with good agreement found with dihedral clustering for the static information, but with results that differ significantly for the pathway analysis.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

PubMed

Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions

NASA Astrophysics Data System (ADS)

Roy, Raktim; Phani Shilpa, P.; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level.

Metabolic pathway analysis and kinetic studies for production of nattokinase in Bacillus subtilis.

PubMed

Unrean, Pornkamol; Nguyen, Nhung H A

2013-01-01

We have constructed a reaction network model of Bacillus subtilis. The model was analyzed using a pathway analysis tool called elementary mode analysis (EMA). The analysis tool was used to study the network capabilities and the possible effects of altered culturing conditions on the production of a fibrinolytic enzyme, nattokinase (NK) by B. subtilis. Based on all existing metabolic pathways, the maximum theoretical yield for NK synthesis in B. subtilis under different substrates and oxygen availability was predicted and the optimal culturing condition for NK production was identified. To confirm model predictions, experiments were conducted by testing these culture conditions for their influence on NK activity. The optimal culturing conditions were then applied to batch fermentation, resulting in high NK activity. The EMA approach was also applied for engineering B. subtilis metabolism towards the most efficient pathway for NK synthesis by identifying target genes for deletion and overexpression that enable the cell to produce NK at the maximum theoretical yield. The consistency between experiments and model predictions proves the feasibility of EMA being used to rationally design culture conditions and genetic manipulations for the efficient production of desired products.

Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer

PubMed Central

Duell, Eric J.; Yu, Kai; Risch, Harvey A.; Olson, Sara H.; Kooperberg, Charles; Wolpin, Brian M.; Jiao, Li; Dong, Xiaoqun; Wheeler, Bill; Arslan, Alan A.; Bueno-de-Mesquita, H. Bas; Fuchs, Charles S.; Gallinger, Steven; Gross, Myron; Hartge, Patricia; Hoover, Robert N.; Holly, Elizabeth A.; Jacobs, Eric J.; Klein, Alison P.; LaCroix, Andrea; Mandelson, Margaret T.; Petersen, Gloria; Zheng, Wei; Agalliu, Ilir; Albanes, Demetrius; Boutron-Ruault, Marie-Christine; Bracci, Paige M.; Buring, Julie E.; Canzian, Federico; Chang, Kenneth; Chanock, Stephen J.; Cotterchio, Michelle; Gaziano, J.Michael; Giovannucci, Edward L.; Goggins, Michael; Hallmans, Göran; Hankinson, Susan E.; Hoffman Bolton, Judith A.; Hunter, David J.; Hutchinson, Amy; Jacobs, Kevin B.; Jenab, Mazda; Khaw, Kay-Tee; Kraft, Peter; Krogh, Vittorio; Kurtz, Robert C.; McWilliams, Robert R.; Mendelsohn, Julie B.; Patel, Alpa V.; Rabe, Kari G.; Riboli, Elio; Shu, Xiao-Ou; Tjønneland, Anne; Tobias, Geoffrey S.; Trichopoulos, Dimitrios; Virtamo, Jarmo; Visvanathan, Kala; Watters, Joanne; Yu, Herbert; Zeleniuch-Jacquotte, Anne; Stolzenberg-Solomon, Rachael Z.

2012-01-01

Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case–control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10−6, 1.6 × 10−5, 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10−5), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H. pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer. PMID:22523087

Analysis of the ergosterol biosynthesis pathway cloning, molecular characterization and phylogeny of lanosterol 14 α-demethylase (ERG11) gene of Moniliophthora perniciosa.

PubMed

de Oliveira Ceita, Geruza; Vilas-Boas, Laurival Antônio; Castilho, Marcelo Santos; Carazzolle, Marcelo Falsarella; Pirovani, Carlos Priminho; Selbach-Schnadelbach, Alessandra; Gramacho, Karina Peres; Ramos, Pablo Ivan Pereira; Barbosa, Luciana Veiga; Pereira, Gonçalo Amarante Guimarães; Góes-Neto, Aristóteles

2014-10-01

The phytopathogenic fungus Moniliophthora perniciosa (Stahel) Aime & Philips-Mora, causal agent of witches' broom disease of cocoa, causes countless damage to cocoa production in Brazil. Molecular studies have attempted to identify genes that play important roles in fungal survival and virulence. In this study, sequences deposited in the M. perniciosa Genome Sequencing Project database were analyzed to identify potential biological targets. For the first time, the ergosterol biosynthetic pathway in M. perniciosa was studied and the lanosterol 14α-demethylase gene (ERG11) that encodes the main enzyme of this pathway and is a target for fungicides was cloned, characterized molecularly and its phylogeny analyzed. ERG11 genomic DNA and cDNA were characterized and sequence analysis of the ERG11 protein identified highly conserved domains typical of this enzyme, such as SRS1, SRS4, EXXR and the heme-binding region (HBR). Comparison of the protein sequences and phylogenetic analysis revealed that the M. perniciosa enzyme was most closely related to that of Coprinopsis cinerea.

Analysis of the ergosterol biosynthesis pathway cloning, molecular characterization and phylogeny of lanosterol 14 α-demethylase (ERG11) gene of Moniliophthora perniciosa

PubMed Central

de Oliveira Ceita, Geruza; Vilas-Boas, Laurival Antônio; Castilho, Marcelo Santos; Carazzolle, Marcelo Falsarella; Pirovani, Carlos Priminho; Selbach-Schnadelbach, Alessandra; Gramacho, Karina Peres; Ramos, Pablo Ivan Pereira; Barbosa, Luciana Veiga; Pereira, Gonçalo Amarante Guimarães; Góes-Neto, Aristóteles

2014-01-01

The phytopathogenic fungus Moniliophthora perniciosa (Stahel) Aime & Philips-Mora, causal agent of witches’ broom disease of cocoa, causes countless damage to cocoa production in Brazil. Molecular studies have attempted to identify genes that play important roles in fungal survival and virulence. In this study, sequences deposited in the M. perniciosa Genome Sequencing Project database were analyzed to identify potential biological targets. For the first time, the ergosterol biosynthetic pathway in M. perniciosa was studied and the lanosterol 14α-demethylase gene (ERG11) that encodes the main enzyme of this pathway and is a target for fungicides was cloned, characterized molecularly and its phylogeny analyzed. ERG11 genomic DNA and cDNA were characterized and sequence analysis of the ERG11 protein identified highly conserved domains typical of this enzyme, such as SRS1, SRS4, EXXR and the heme-binding region (HBR). Comparison of the protein sequences and phylogenetic analysis revealed that the M. perniciosa enzyme was most closely related to that of Coprinopsis cinerea. PMID:25505843

Integrated analysis of germline and somatic variants in ovarian cancer.

PubMed

Kanchi, Krishna L; Johnson, Kimberly J; Lu, Charles; McLellan, Michael D; Leiserson, Mark D M; Wendl, Michael C; Zhang, Qunyuan; Koboldt, Daniel C; Xie, Mingchao; Kandoth, Cyriac; McMichael, Joshua F; Wyczalkowski, Matthew A; Larson, David E; Schmidt, Heather K; Miller, Christopher A; Fulton, Robert S; Spellman, Paul T; Mardis, Elaine R; Druley, Todd E; Graubert, Timothy A; Goodfellow, Paul J; Raphael, Benjamin J; Wilson, Richard K; Ding, Li

2014-01-01

We report the first large-scale exome-wide analysis of the combined germline-somatic landscape in ovarian cancer. Here we analyse germline and somatic alterations in 429 ovarian carcinoma cases and 557 controls. We identify 3,635 high confidence, rare truncation and 22,953 missense variants with predicted functional impact. We find germline truncation variants and large deletions across Fanconi pathway genes in 20% of cases. Enrichment of rare truncations is shown in BRCA1, BRCA2 and PALB2. In addition, we observe germline truncation variants in genes not previously associated with ovarian cancer susceptibility (NF1, MAP3K4, CDKN2B and MLL3). Evidence for loss of heterozygosity was found in 100 and 76% of cases with germline BRCA1 and BRCA2 truncations, respectively. Germline-somatic interaction analysis combined with extensive bioinformatics annotation identifies 222 candidate functional germline truncation and missense variants, including two pathogenic BRCA1 and 1 TP53 deleterious variants. Finally, integrated analyses of germline and somatic variants identify significantly altered pathways, including the Fanconi, MAPK and MLL pathways.

Identifying protein biomarkers in predicting disease severity of dengue virus infection using immune-related protein microarray.

PubMed

Soe, Hui Jen; Yong, Yean K; Al-Obaidi, Mazen M Jamil; Raju, Chandramathi Samudi; Gudimella, Ranganath; Manikam, Rishya; Sekaran, Shamala Devi

2018-02-01

Dengue virus is one of the most widespread flaviviruses that re-emerged throughout recent decades. The progression from mild dengue to severe dengue (SD) with the complications such as vascular leakage and hemorrhage increases the fatality rate of dengue. The pathophysiology of SD is not entirely clear. To investigate potential biomarkers that are suggestive of pathogenesis of SD, a small panel of serum samples selected from 1 healthy individual, 2 dengue patients without warning signs (DWS-), 2 dengue patients with warning signs (DWS+), and 5 patients with SD were subjected to a pilot analysis using Sengenics Immunome protein array. The overall fold changes of protein expressions and clustering heat map revealed that PFKFB4, TPM1, PDCL3, and PTPN20A were elevated among patients with SD. Differential expression analysis identified that 29 proteins were differentially elevated greater than 2-fold in SD groups than DWS- and DWS+. From the 29 candidate proteins, pathways enrichment analysis also identified insulin signaling and cytoskeleton pathways were involved in SD, suggesting that the insulin pathway may play a pivotal role in the pathogenesis of SD.

Proteomic analysis of the signaling pathway mediated by the heterotrimeric Gα protein Pga1 of Penicillium chrysogenum.

PubMed

Carrasco-Navarro, Ulises; Vera-Estrella, Rosario; Barkla, Bronwyn J; Zúñiga-León, Eduardo; Reyes-Vivas, Horacio; Fernández, Francisco J; Fierro, Francisco

2016-10-06

The heterotrimeric Gα protein Pga1-mediated signaling pathway regulates the entire developmental program in Penicillium chrysogenum, from spore germination to the formation of conidia. In addition it participates in the regulation of penicillin biosynthesis. We aimed to advance the understanding of this key signaling pathway using a proteomics approach, a powerful tool to identify effectors participating in signal transduction pathways. Penicillium chrysogenum mutants with different levels of activity of the Pga1-mediated signaling pathway were used to perform comparative proteomic analyses by 2D-DIGE and LC-MS/MS. Thirty proteins were identified which showed differences in abundance dependent on Pga1 activity level. By modifying the intracellular levels of cAMP we could establish cAMP-dependent and cAMP-independent pathways in Pga1-mediated signaling. Pga1 was shown to regulate abundance of enzymes in primary metabolic pathways involved in ATP, NADPH and cysteine biosynthesis, compounds that are needed for high levels of penicillin production. An in vivo phosphorylated protein containing a pleckstrin homology domain was identified; this protein is a candidate for signal transduction activity. Proteins with possible roles in purine metabolism, protein folding, stress response and morphogenesis were also identified whose abundance was regulated by Pga1 signaling. Thirty proteins whose abundance was regulated by the Pga1-mediated signaling pathway were identified. These proteins are involved in primary metabolism, stress response, development and signal transduction. A model describing the pathways through which Pga1 signaling regulates different cellular processes is proposed.

Pathway-based outlier method reveals heterogeneous genomic structure of autism in blood transcriptome

PubMed Central

2013-01-01

Background Decades of research strongly suggest that the genetic etiology of autism spectrum disorders (ASDs) is heterogeneous. However, most published studies focus on group differences between cases and controls. In contrast, we hypothesized that the heterogeneity of the disorder could be characterized by identifying pathways for which individuals are outliers rather than pathways representative of shared group differences of the ASD diagnosis. Methods Two previously published blood gene expression data sets – the Translational Genetics Research Institute (TGen) dataset (70 cases and 60 unrelated controls) and the Simons Simplex Consortium (Simons) dataset (221 probands and 191 unaffected family members) – were analyzed. All individuals of each dataset were projected to biological pathways, and each sample’s Mahalanobis distance from a pooled centroid was calculated to compare the number of case and control outliers for each pathway. Results Analysis of a set of blood gene expression profiles from 70 ASD and 60 unrelated controls revealed three pathways whose outliers were significantly overrepresented in the ASD cases: neuron development including axonogenesis and neurite development (29% of ASD, 3% of control), nitric oxide signaling (29%, 3%), and skeletal development (27%, 3%). Overall, 50% of cases and 8% of controls were outliers in one of these three pathways, which could not be identified using group comparison or gene-level outlier methods. In an independently collected data set consisting of 221 ASD and 191 unaffected family members, outliers in the neurogenesis pathway were heavily biased towards cases (20.8% of ASD, 12.0% of control). Interestingly, neurogenesis outliers were more common among unaffected family members (Simons) than unrelated controls (TGen), but the statistical significance of this effect was marginal (Chi squared P < 0.09). Conclusions Unlike group difference approaches, our analysis identified the samples within the case and control groups that manifested each expression signal, and showed that outlier groups were distinct for each implicated pathway. Moreover, our results suggest that by seeking heterogeneity, pathway-based outlier analysis can reveal expression signals that are not apparent when considering only shared group differences. PMID:24063311

minepath.org: a free interactive pathway analysis web server.

PubMed

Koumakis, Lefteris; Roussos, Panos; Potamias, George

2017-07-03

( www.minepath.org ) is a web-based platform that elaborates on, and radically extends the identification of differentially expressed sub-paths in molecular pathways. Besides the network topology, the underlying MinePath algorithmic processes exploit exact gene-gene molecular relationships (e.g. activation, inhibition) and are able to identify differentially expressed pathway parts. Each pathway is decomposed into all its constituent sub-paths, which in turn are matched with corresponding gene expression profiles. The highly ranked, and phenotype inclined sub-paths are kept. Apart from the pathway analysis algorithm, the fundamental innovation of the MinePath web-server concerns its advanced visualization and interactive capabilities. To our knowledge, this is the first pathway analysis server that introduces and offers visualization of the underlying and active pathway regulatory mechanisms instead of genes. Other features include live interaction, immediate visualization of functional sub-paths per phenotype and dynamic linked annotations for the engaged genes and molecular relations. The user can download not only the results but also the corresponding web viewer framework of the performed analysis. This feature provides the flexibility to immediately publish results without publishing source/expression data, and get all the functionality of a web based pathway analysis viewer. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Analysis of aromatic catabolic pathways in Pseudomonas putida KT 2440 using a combined proteomic approach: 2-DE/MS and cleavable isotope-coded affinity tag analysis.

PubMed

Kim, Young Hwan; Cho, Kun; Yun, Sung-Ho; Kim, Jin Young; Kwon, Kyung-Hoon; Yoo, Jong Shin; Kim, Seung Il

2006-02-01

Proteomic analysis of Pseudomonas putida KT2440 cultured in monocyclic aromatic compounds was performed using 2-DE/MS and cleavable isotope-coded affinity tag (ICAT) to determine whether proteins involved in aromatic compound degradation pathways were altered as predicted by genomic analysis (Jiménez et al., Environ Microbiol. 2002, 4, 824-841). Eighty unique proteins were identified by 2-DE/MS or MS/MS analysis from P. putida KT2440 cultured in the presence of six different organic compounds. Benzoate dioxygenase (BenA, BenD) and catechol 1,2-dioxygenase (CatA) were induced by benzoate. Protocatechuate 3,4-dixoygenase (PcaGH) was induced by p-hydroxybenzoate and vanilline. beta-Ketoadipyl CoA thiolase (PcaF) and 3-oxoadipate enol-lactone hydrolase (PcaD) were induced by benzoate, p-hydroxybenzoate and vanilline, suggesting that benzoate, p-hydroxybenzoate and vanilline were degraded by different dioxygenases and then converged in the same beta-ketoadipate degradation pathway. An additional 110 proteins, including 19 proteins from 2-DE analysis, were identified by cleavable ICAT analysis for benzoate-induced proteomes, which complemented the 2-DE results. Phenylethylamine exposure induced beta-ketoacyl CoA thiolase (PhaD) and ring-opening enzyme (PhaL), both enzymes of the phenylacetate (pha) biodegradation pathway. Phenylalanine induced 4-hydroxyphenyl-pyruvate dioxygenase (Hpd) and homogentisate 1,2-dioxygenase (HmgA), key enzymes in the homogentisate degradation pathway. Alkyl hydroperoxide reductase (AphC) was induced under all aromatic compounds conditions. These results suggest that proteome analysis complements and supports predictive information obtained by genomic sequence analysis.

Proteomic Analysis Reveals the Contribution of TGFβ/Smad4 Signaling Pathway to Cell Differentiation During Planarian Tail Regeneration.

PubMed

Chen, Xiaoguang; Xu, Cunshuan

2017-06-01

After planarian tail is cut off, posterior end of the remaining fragment will regenerate a new tail within about 1 week. However, many details of this process remain unclear up to date. For this reason, we performed the dynamic proteomic analysis of the regenerating tail fragments at 6, 12, 24, 72, 120, and 168 h post-amputation (hpa). Using two-dimensional electrophoresis (2-DE) in combination with MALDI-TOF-TOF/MS analysis, a total of 1088 peptides were identified as significantly changed between tail-cutting groups and 0-h group, 482 of which have identifiable protein names. Of these 482 proteins, there were 111 originating from the Turbellaria. Protein functional categorization showed that these 111 proteins are mainly related to differentiation and development, transcription and translation, cell signal transduction, and cell proliferation. The screening of key protein considered the transcription factor Smad4 as important protein for planarian tail regeneration. Cell signaling pathway analysis, combined with proteomic profiling of regenerating tail fragment, showed that TGFβ/Smad4 pathway was activated during planarian tail regeneration. Based on a comprehensive analysis of 2-DE MALDI-TOF-TOF/MS and bioinformatics analyses, it could be concluded that TGFβ/Smad4 pathway perhaps plays an important role in tail regeneration via promoting cell differentiation.

Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

PubMed Central

He, Yue-E; Qiu, Hui-Xian; Jiang, Jian-Bing; Wu, Rong-Zhou; Xiang, Ru-Lian; Zhang, Yuan-Hai

2017-01-01

The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log2 fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF. PMID:28713939

Pathway and network-based analysis of genome-wide association studies and RT-PCR validation in polycystic ovary syndrome

PubMed Central

Shen, Haoran; Liang, Zhou; Zheng, Saihua; Li, Xuelian

2017-01-01

The purpose of this study was to identify promising candidate genes and pathways in polycystic ovary syndrome (PCOS). Microarray dataset GSE345269 obtained from the Gene Expression Omnibus database includes 7 granulosa cell samples from PCOS patients, and 3 normal granulosa cell samples. Differentially expressed genes (DEGs) were screened between PCOS and normal samples. Pathway enrichment analysis was conducted for DEGs using ClueGO and CluePedia plugin of Cytoscape. A Reactome functional interaction (FI) network of the DEGs was built using ReactomeFIViz, and then network modules were extracted, followed by pathway enrichment analysis for the modules. Expression of DEGs in granulosa cell samples was measured using quantitative RT-PCR. A total of 674 DEGs were retained, which were significantly enriched with inflammation and immune-related pathways. Eight modules were extracted from the Reactome FI network. Pathway enrichment analysis revealed significant pathways of each module: module 0, Regulation of RhoA activity and Signaling by Rho GTPases pathways shared ARHGAP4 and ARHGAP9; module 2, GlycoProtein VI-mediated activation cascade pathway was enriched with RHOG; module 3, Thromboxane A2 receptor signaling, Chemokine signaling pathway, CXCR4-mediated signaling events pathways were enriched with LYN, the hub gene of module 3. Results of RT-PCR confirmed the finding of the bioinformatic analysis that ARHGAP4, ARHGAP9, RHOG and LYN were significantly upregulated in PCOS. RhoA-related pathways, GlycoProtein VI-mediated activation cascade pathway, ARHGAP4, ARHGAP9, RHOG and LYN may be involved in the pathogenesis of PCOS. PMID:28949383

A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks.

PubMed

Jambusaria, Ankit; Klomp, Jeff; Hong, Zhigang; Rafii, Shahin; Dai, Yang; Malik, Asrar B; Rehman, Jalees

2018-06-07

The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues. Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database. HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.

Identification of differentially expressed genes in childhood asthma.

PubMed

Zhang, Nian-Zhen; Chen, Xiu-Juan; Mu, Yu-Hua; Wang, Hewen

2018-05-01

Asthma has been the most common chronic disease in children that places a major burden for affected people and their families.An integrated analysis of microarrays studies was performed to identify differentially expressed genes (DEGs) in childhood asthma compared with normal control. We also obtained the differentially methylated genes (DMGs) in childhood asthma according to GEO. The genes that were both differentially expressed and differentially methylated were identified. Functional annotation and protein-protein interaction network construction were performed to interpret biological functions of DEGs. We performed q-RT-PCR to verify the expression of selected DEGs.One DNA methylation and 3 gene expression datasets were obtained. Four hundred forty-one DEGs and 1209 DMGs in childhood asthma were identified. Among which, 16 genes were both differentially expressed and differentially methylated in childhood asthma. Natural killer cell mediated cytotoxicity pathway, Jak-STAT signaling pathway, and Wnt signaling pathway were 3 significantly enriched pathways in childhood asthma according to our KEGG enrichment analysis. The PPI network of top 20 up- and downregulated DEGs consisted of 822 nodes and 904 edges and 2 hub proteins (UBQLN4 and MID2) were identified. The expression of 8 DEGs (GZMB, FGFBP2, CLC, TBX21, ALOX15, IL12RB2, UBQLN4) was verified by qRT-PCR and only the expression of GZMB and FGFBP2 was inconsistent with our integrated analysis.Our finding was helpful to elucidate the underlying mechanism of childhood asthma and develop new potential diagnostic biomarker and provide clues for drug design.

Shared molecular networks in orofacial and neural tube development.

PubMed

Kousa, Youssef A; Mansour, Tamer A; Seada, Haitham; Matoo, Samaneh; Schutte, Brian C

2017-01-30

Single genetic variants can affect multiple tissues during development. Thus it is possible that disruption of shared gene regulatory networks might underlie syndromic presentations. In this study, we explore this idea through examination of two critical developmental programs that control orofacial and neural tube development and identify shared regulatory factors and networks. Identification of these networks has the potential to yield additional candidate genes for poorly understood developmental disorders and assist in modeling and perhaps managing risk factors to prevent morbidly and mortality. We reviewed the literature to identify genes common between orofacial and neural tube defects and development. We then conducted a bioinformatic analysis to identify shared molecular targets and pathways in the development of these tissues. Finally, we examine publicly available RNA-Seq data to identify which of these genes are expressed in both tissues during development. We identify common regulatory factors in orofacial and neural tube development. Pathway enrichment analysis shows that folate, cancer and hedgehog signaling pathways are shared in neural tube and orofacial development. Developing neural tissues differentially express mouse exencephaly and cleft palate genes, whereas developing orofacial tissues were enriched for both clefting and neural tube defect genes. These data suggest that key developmental factors and pathways are shared between orofacial and neural tube defects. We conclude that it might be most beneficial to focus on common regulatory factors and pathways to better understand pathology and develop preventative measures for these birth defects. Birth Defects Research 109:169-179, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Mitochondrial DNA and trade data support multiple origins of Helicoverpa armigera (Lepidoptera, Noctuidae) in Brazil

PubMed Central

Tay, Wee Tek; Walsh, Thomas K.; Downes, Sharon; Anderson, Craig; Jermiin, Lars S.; Wong, Thomas K. F.; Piper, Melissa C.; Chang, Ester Silva; Macedo, Isabella Barony; Czepak, Cecilia; Behere, Gajanan T.; Silvie, Pierre; Soria, Miguel F.; Frayssinet, Marie; Gordon, Karl H. J.

2017-01-01

The Old World bollworm Helicoverpa armigera is now established in Brazil but efforts to identify incursion origin(s) and pathway(s) have met with limited success due to the patchiness of available data. Using international agricultural/horticultural commodity trade data and mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) and cytochrome b (Cyt b) gene markers, we inferred the origins and incursion pathways into Brazil. We detected 20 mtDNA haplotypes from six Brazilian states, eight of which were new to our 97 global COI-Cyt b haplotype database. Direct sequence matches indicated five Brazilian haplotypes had Asian, African, and European origins. We identified 45 parsimoniously informative sites and multiple substitutions per site within the concatenated (945 bp) nucleotide dataset, implying that probabilistic phylogenetic analysis methods are needed. High diversity and signatures of uniquely shared haplotypes with diverse localities combined with the trade data suggested multiple incursions and introduction origins in Brazil. Increasing agricultural/horticultural trade activities between the Old and New Worlds represents a significant biosecurity risk factor. Identifying pest origins will enable resistance profiling that reflects countries of origin to be included when developing a resistance management strategy, while identifying incursion pathways will improve biosecurity protocols and risk analysis at biosecurity hotspots including national ports. PMID:28350004

Mitochondrial DNA and trade data support multiple origins of Helicoverpa armigera (Lepidoptera, Noctuidae) in Brazil.

PubMed

Tay, Wee Tek; Walsh, Thomas K; Downes, Sharon; Anderson, Craig; Jermiin, Lars S; Wong, Thomas K F; Piper, Melissa C; Chang, Ester Silva; Macedo, Isabella Barony; Czepak, Cecilia; Behere, Gajanan T; Silvie, Pierre; Soria, Miguel F; Frayssinet, Marie; Gordon, Karl H J

2017-03-28

The Old World bollworm Helicoverpa armigera is now established in Brazil but efforts to identify incursion origin(s) and pathway(s) have met with limited success due to the patchiness of available data. Using international agricultural/horticultural commodity trade data and mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) and cytochrome b (Cyt b) gene markers, we inferred the origins and incursion pathways into Brazil. We detected 20 mtDNA haplotypes from six Brazilian states, eight of which were new to our 97 global COI-Cyt b haplotype database. Direct sequence matches indicated five Brazilian haplotypes had Asian, African, and European origins. We identified 45 parsimoniously informative sites and multiple substitutions per site within the concatenated (945 bp) nucleotide dataset, implying that probabilistic phylogenetic analysis methods are needed. High diversity and signatures of uniquely shared haplotypes with diverse localities combined with the trade data suggested multiple incursions and introduction origins in Brazil. Increasing agricultural/horticultural trade activities between the Old and New Worlds represents a significant biosecurity risk factor. Identifying pest origins will enable resistance profiling that reflects countries of origin to be included when developing a resistance management strategy, while identifying incursion pathways will improve biosecurity protocols and risk analysis at biosecurity hotspots including national ports.

Mitochondrial DNA and trade data support multiple origins of Helicoverpa armigera (Lepidoptera, Noctuidae) in Brazil

NASA Astrophysics Data System (ADS)

Tay, Wee Tek; Walsh, Thomas K.; Downes, Sharon; Anderson, Craig; Jermiin, Lars S.; Wong, Thomas K. F.; Piper, Melissa C.; Chang, Ester Silva; Macedo, Isabella Barony; Czepak, Cecilia; Behere, Gajanan T.; Silvie, Pierre; Soria, Miguel F.; Frayssinet, Marie; Gordon, Karl H. J.

2017-03-01

The Old World bollworm Helicoverpa armigera is now established in Brazil but efforts to identify incursion origin(s) and pathway(s) have met with limited success due to the patchiness of available data. Using international agricultural/horticultural commodity trade data and mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) and cytochrome b (Cyt b) gene markers, we inferred the origins and incursion pathways into Brazil. We detected 20 mtDNA haplotypes from six Brazilian states, eight of which were new to our 97 global COI-Cyt b haplotype database. Direct sequence matches indicated five Brazilian haplotypes had Asian, African, and European origins. We identified 45 parsimoniously informative sites and multiple substitutions per site within the concatenated (945 bp) nucleotide dataset, implying that probabilistic phylogenetic analysis methods are needed. High diversity and signatures of uniquely shared haplotypes with diverse localities combined with the trade data suggested multiple incursions and introduction origins in Brazil. Increasing agricultural/horticultural trade activities between the Old and New Worlds represents a significant biosecurity risk factor. Identifying pest origins will enable resistance profiling that reflects countries of origin to be included when developing a resistance management strategy, while identifying incursion pathways will improve biosecurity protocols and risk analysis at biosecurity hotspots including national ports.

Extreme Outlier Analysis Identifies Occult Mitogen-Activated Protein Kinase Pathway Mutations in Patients With Low-Grade Serous Ovarian Cancer

PubMed Central

Grisham, Rachel N.; Sylvester, Brooke E.; Won, Helen; McDermott, Gregory; DeLair, Deborah; Ramirez, Ricardo; Yao, Zhan; Shen, Ronglai; Dao, Fanny; Bogomolniy, Faina; Makker, Vicky; Sala, Evis; Soumerai, Tara E.; Hyman, David M.; Socci, Nicholas D.; Viale, Agnes; Gershenson, David M.; Farley, John; Levine, Douglas A.; Rosen, Neal; Berger, Michael F.; Spriggs, David R.; Aghajanian, Carol A.; Solit, David B.; Iyer, Gopa

2015-01-01

Purpose No effective systemic therapy exists for patients with metastatic low-grade serous (LGS) ovarian cancers. BRAF and KRAS mutations are common in serous borderline (SB) and LGS ovarian cancers, and MEK inhibition has been shown to induce tumor regression in a minority of patients; however, no correlation has been observed between mutation status and clinical response. With the goal of identifying biomarkers of sensitivity to MEK inhibitor treatment, we performed an outlier analysis of a patient who experienced a complete, durable, and ongoing (> 5 years) response to selumetinib, a non-ATP competitive MEK inhibitor. Patients and Methods Next-generation sequencing was used to analyze this patient's tumor as well as an additional 28 SB/LGS tumors. Functional characterization of an identified novel alteration of interest was performed. Results Analysis of the extraordinary responder's tumor identified a 15-nucleotide deletion in the negative regulatory helix of the MAP2K1 gene encoding for MEK1. Functional characterization demonstrated that this mutant induced extracellular signal-regulated kinase pathway activation, promoted anchorage-independent growth and tumor formation in mice, and retained sensitivity to selumetinib. Analysis of additional LGS/SB tumors identified mutations predicted to induce extracellular signal-regulated kinase pathway activation in 82% (23 of 28), including two patients with BRAF fusions, one of whom achieved an ongoing complete response to MEK inhibitor–based combination therapy. Conclusion Alterations affecting the mitogen-activated protein kinase pathway are present in the majority of patients with LGS ovarian cancer. Next-generation sequencing analysis revealed deletions and fusions that are not detected by older sequencing approaches. These findings, coupled with the observation that a subset of patients with recurrent LGS ovarian cancer experienced dramatic and durable responses to MEK inhibitor therapy, support additional clinical studies of MEK inhibitors in this disease. PMID:26324360

Expression analysis in response to drought stress in soybean: Shedding light on the regulation of metabolic pathway genes.

PubMed

Guimarães-Dias, Fábia; Neves-Borges, Anna Cristina; Viana, Antonio Americo Barbosa; Mesquita, Rosilene Oliveira; Romano, Eduardo; de Fátima Grossi-de-Sá, Maria; Nepomuceno, Alexandre Lima; Loureiro, Marcelo Ehlers; Alves-Ferreira, Márcio

2012-06-01

Metabolomics analysis of wild type Arabidopsis thaliana plants, under control and drought stress conditions revealed several metabolic pathways that are induced under water deficit. The metabolic response to drought stress is also associated with ABA dependent and independent pathways, allowing a better understanding of the molecular mechanisms in this model plant. Through combining an in silico approach and gene expression analysis by quantitative real-time PCR, the present work aims at identifying genes of soybean metabolic pathways potentially associated with water deficit. Digital expression patterns of Arabidopsis genes, which were selected based on the basis of literature reports, were evaluated under drought stress condition by Genevestigator. Genes that showed strong induction under drought stress were selected and used as bait to identify orthologs in the soybean genome. This allowed us to select 354 genes of putative soybean orthologs of 79 Arabidopsis genes belonging to 38 distinct metabolic pathways. The expression pattern of the selected genes was verified in the subtractive libraries available in the GENOSOJA project. Subsequently, 13 genes from different metabolic pathways were selected for validation by qPCR experiments. The expression of six genes was validated in plants undergoing drought stress in both pot-based and hydroponic cultivation systems. The results suggest that the metabolic response to drought stress is conserved in Arabidopsis and soybean plants.

Dynamic changes in global microRNAome and transcriptome reveal complex miRNA-mRNA regulated host response to Japanese Encephalitis Virus in microglial cells

PubMed Central

Kumari, Bharti; Jain, Pratistha; Das, Shaoli; Ghosal, Suman; Hazra, Bibhabasu; Trivedi, Ashish Chandra; Basu, Anirban; Chakrabarti, Jayprokas; Vrati, Sudhanshu; Banerjee, Arup

2016-01-01

Microglia cells in the brain play essential role during Japanese Encephalitis Virus (JEV) infection and may lead to change in microRNA (miRNA) and mRNA profile. These changes may together control disease outcome. Using Affymetrix microarray platform, we profiled cellular miRNA and mRNA expression at multiple time points during viral infection in human microglial (CHME3) cells. In silico analysis of microarray data revealed a phased pattern of miRNAs expression, associated with JEV replication and provided unique signatures of infection. Target prediction and pathway enrichment analysis identified anti correlation between differentially expressed miRNA and the gene expression at multiple time point which ultimately affected diverse signaling pathways including Notch signaling pathways in microglia. Activation of Notch pathway during JEV infection was demonstrated in vitro and in vivo. The expression of a subset of miRNAs that target multiple genes in Notch signaling pathways were suppressed and their overexpression could affect JEV induced immune response. Further analysis provided evidence for the possible presence of cellular competing endogenous RNA (ceRNA) associated with innate immune response. Collectively, our data provide a uniquely comprehensive view of the changes in the host miRNAs induced by JEV during cellular infection and identify Notch pathway in modulating microglia mediated inflammation. PMID:26838068

Dynamic changes in global microRNAome and transcriptome reveal complex miRNA-mRNA regulated host response to Japanese Encephalitis Virus in microglial cells.

PubMed

Kumari, Bharti; Jain, Pratistha; Das, Shaoli; Ghosal, Suman; Hazra, Bibhabasu; Trivedi, Ashish Chandra; Basu, Anirban; Chakrabarti, Jayprokas; Vrati, Sudhanshu; Banerjee, Arup

2016-02-03

Microglia cells in the brain play essential role during Japanese Encephalitis Virus (JEV) infection and may lead to change in microRNA (miRNA) and mRNA profile. These changes may together control disease outcome. Using Affymetrix microarray platform, we profiled cellular miRNA and mRNA expression at multiple time points during viral infection in human microglial (CHME3) cells. In silico analysis of microarray data revealed a phased pattern of miRNAs expression, associated with JEV replication and provided unique signatures of infection. Target prediction and pathway enrichment analysis identified anti correlation between differentially expressed miRNA and the gene expression at multiple time point which ultimately affected diverse signaling pathways including Notch signaling pathways in microglia. Activation of Notch pathway during JEV infection was demonstrated in vitro and in vivo. The expression of a subset of miRNAs that target multiple genes in Notch signaling pathways were suppressed and their overexpression could affect JEV induced immune response. Further analysis provided evidence for the possible presence of cellular competing endogenous RNA (ceRNA) associated with innate immune response. Collectively, our data provide a uniquely comprehensive view of the changes in the host miRNAs induced by JEV during cellular infection and identify Notch pathway in modulating microglia mediated inflammation.

Impact of a critical pathway on postoperative length of stay and outcomes after infrainguinal bypass.

PubMed

Stanley, A C; Barry, M; Scott, T E; LaMorte, W W; Woodson, J; Menzoian, J O

1998-06-01

To determine the effect of a critical pathway on postoperative length of stay and outcomes after infrainguinal bypass. A critical pathway for care of patients after infrainguinal bypass was introduced in December 1995 to coordinate postoperative care at our institution. We compared care of 67 consecutively treated patients before institution of the pathway with care of 69 consecutively treated patients with the critical pathway in place. Data collection was done by means of chart review. Univariate analyses were used to identify differences between prepathway and postpathway patients and to identify factors influencing postoperative length of stay. Multivariate analysis was used to identify factors that influenced length of stay and to examine the effect of use of the pathway after adjusting for other factors. Patients on the pathway were similar to prepathway controls with respect to comorbid illnesses, vascular risk factors, indications for surgical treatment, type of conduit, and type of operation. Factors associated with longer postoperative stays included distal anastomoses to tibial rather than popliteal vessels (p = 0.02), preexisting cardiac disease (p = 0.005), postoperative complications (p = 0.0003), lower preoperative hematocrit (p = 0.01), and elevated preoperative creatinine level (p = 0.006). Overall, pathway patients had somewhat shorter postoperative lengths of stay (median value 7 days; range 2 to 29 days) than prepathway patients (median value 6 days; range 2 to 35; p = 0.01), and the two groups had similar frequencies of postoperative complications, readmission, and 6-month mortality. However, patients on the pathway were more likely to be discharged to an intermediate-care facility rather than directly home. After 12 patients with extraordinarily prolonged postoperative stays were excluded, multivariate analysis indicated that pathway patients had significantly shorter postoperative stays (p = 0.001). However, the difference was not significant if patients with extraordinarily long postoperative stays were included in the analysis (p = 0.28). Use of a critical pathway was associated with a modest decrease in postoperative length of stay for most patients. This was accomplished without an adverse effect on readmission, complication, or mortality rates. However, the decrease in stay may have been achieved primarily by discharging more patients to intermediate-care facilities. The pathway did not appear to have any effect when the subset of patients with extraordinarily long stays because of complex medical problems was included.

Understanding alternative fluxes/effluxes through comparative metabolic pathway analysis of phylum actinobacteria using a simplified approach.

PubMed

Verma, Mansi; Lal, Devi; Saxena, Anjali; Anand, Shailly; Kaur, Jasvinder; Kaur, Jaspreet; Lal, Rup

2013-12-01

Actinobacteria are known for their diverse metabolism and physiology. Some are dreadful human pathogens whereas some constitute the natural flora for human gut. Therefore, the understanding of metabolic pathways is a key feature for targeting the pathogenic bacteria without disturbing the symbiotic ones. A big challenge faced today is multiple drug resistance by Mycobacterium and other pathogens that utilize alternative fluxes/effluxes. With the availability of genome sequence, it is now feasible to conduct the comparative in silico analysis. Here we present a simplified approach to compare metabolic pathways so that the species specific enzyme may be traced and engineered for future therapeutics. The analyses of four key carbohydrate metabolic pathways, i.e., glycolysis, pyruvate metabolism, tri carboxylic acid cycle and pentose phosphate pathway suggest the presence of alternative fluxes. It was found that the upper pathway of glycolysis was highly variable in the actinobacterial genomes whereas lower glycolytic pathway was highly conserved. Likewise, pentose phosphate pathway was well conserved in contradiction to TCA cycle, which was found to be incomplete in majority of actinobacteria. The clustering based on presence and absence of genes of these metabolic pathways clearly revealed that members of different genera shared identical pathways and, therefore, provided an easy method to identify the metabolic similarities/differences between pathogenic and symbiotic organisms. The analyses could identify isoenzymes and some key enzymes that were found to be missing in some pathogenic actinobacteria. The present work defines a simple approach to explore the effluxes in four metabolic pathways within the phylum actinobacteria. The analysis clearly reflects that actinobacteria exhibit diverse routes for metabolizing substrates. The pathway comparison can help in finding the enzymes that can be used as drug targets for pathogens without effecting symbiotic organisms within the same host. This may help to prevail over the multiple drug resistance, for designing broad spectrum drugs, in food industries and other clinical research areas. © 2013.

De Novo Characterization of the Spleen Transcriptome of the Large Yellow Croaker (Pseudosciaena crocea) and Analysis of the Immune Relevant Genes and Pathways Involved in the Antiviral Response

PubMed Central

Ding, Yang; Ao, Jingqun; Hu, Songnian; Chen, Xinhua

2014-01-01

The large yellow croaker (Pseudosciaena crocea) is an economically important marine fish in China. To understand the molecular basis for antiviral defense in this species, we used Illumia paired-end sequencing to characterize the spleen transcriptome of polyriboinosinic:polyribocytidylic acid [poly(I:C)]-induced large yellow croakers. The library produced 56,355,728 reads and assembled into 108,237 contigs. As a result, 15,192 unigenes were found from this transcriptome. Gene ontology analysis showed that 4,759 genes were involved in three major functional categories: biological process, cellular component, and molecular function. We further ascertained that numerous consensus sequences were homologous to known immune-relevant genes. Kyoto Encyclopedia of Genes and Genomes orthology mapping annotated 5,389 unigenes and identified numerous immune-relevant pathways. These immune-relevant genes and pathways revealed major antiviral immunity effectors, including but not limited to: pattern recognition receptors, adaptors and signal transducers, the interferons and interferon-stimulated genes, inflammatory cytokines and receptors, complement components, and B-cell and T-cell antigen activation molecules. Moreover, the partial genes of Toll-like receptor signaling pathway, RIG-I-like receptors signaling pathway, Janus kinase-Signal Transducer and Activator of Transcription (JAK-STAT) signaling pathway, and T-cell receptor (TCR) signaling pathway were found to be changed after poly(I:C) induction by real-time polymerase chain reaction (PCR) analysis, suggesting that these signaling pathways may be regulated by poly(I:C), a viral mimic. Overall, the antivirus-related genes and signaling pathways that were identified in response to poly(I:C) challenge provide valuable leads for further investigation of the antiviral defense mechanism in the large yellow croaker. PMID:24820969

Pathways for virus assembly around nucleic acids

PubMed Central

Perlmutter, Jason D; Perkett, Matthew R

2014-01-01

Understanding the pathways by which viral capsid proteins assemble around their genomes could identify key intermediates as potential drug targets. In this work we use computer simulations to characterize assembly over a wide range of capsid protein-protein interaction strengths and solution ionic strengths. We find that assembly pathways can be categorized into two classes, in which intermediates are either predominantly ordered or disordered. Our results suggest that estimating the protein-protein and the protein-genome binding affinities may be sufficient to predict which pathway occurs. Furthermore, the calculated phase diagrams suggest that knowledge of the dominant assembly pathway and its relationship to control parameters could identify optimal strategies to thwart or redirect assembly to block infection. Finally, analysis of simulation trajectories suggests that the two classes of assembly pathways can be distinguished in single molecule fluorescence correlation spectroscopy or bulk time resolved small angle x-ray scattering experiments. PMID:25036288

Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.

PubMed

Yang, Wei; Kim, Yongsoo; Kim, Taek-Kyun; Keay, Susan K; Kim, Kwang Pyo; Steen, Hanno; Freeman, Michael R; Hwang, Daehee; Kim, Jayoung

2012-12-01

What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC. • To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed. • To identify more differentially expressed genes with a lower false discovery rate from a previously published microarray data set, an integrative hypothesis-testing statistical approach was applied. • For validation experiments, expression and phosphorylation levels of select proteins were evaluated by western blotting. • Integration analysis of this transcriptomics data set with our own quantitative proteomics data set identified 10 genes that are potentially regulated by APF in vivo from 4140 differentially expressed genes identified with a false discovery rate of 1%. • Of these, five (i.e. JUP, MAPKSP1, GSPT1, PTGS2/COX-2 and XPOT) were found to be prominent after network modelling of the common genes identified in the proteomics and microarray studies. • This molecular signature reflects the biological processes of cell adhesion, cell proliferation and inflammation, which is consistent with the known physiological effects of APF. • Lastly, we found the mammalian target of rapamycin pathway was down-regulated in response to APF. • This unbiased integration analysis of in vitro quantitative proteomics data with in vivo quantitative transcriptomics data led to the identification of potential downstream mediators of the APF signal transduction pathway. © 2012 THE AUTHORS. BJU INTERNATIONAL © 2012 BJU INTERNATIONAL.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jannik, Tim; Hartman, Larry

During the operational history of Savannah River Site, many different radionuclides have been released from site facilities. However, as shown in this analysis, only a relatively small number of the released radionuclides have been significant contributors to doses to the offsite public. This report is an update to the 2011 analysis, Critical Radionuclide and Pathway Analysis for the Savannah River Site. SRS-based Performance Assessments for E-Area, Saltstone, F-Tank Farm, H-Tank Farm, and a Comprehensive SRS Composite Analysis have been completed. The critical radionuclides and pathways identified in those extensive reports are also detailed and included in this analysis.

Flux analysis of cholesterol biosynthesis in vivo reveals multiple tissue and cell-type specific pathways

PubMed Central

Mitsche, Matthew A; McDonald, Jeffrey G; Hobbs, Helen H; Cohen, Jonathan C

2015-01-01

Two parallel pathways produce cholesterol: the Bloch and Kandutsch-Russell pathways. Here we used stable isotope labeling and isotopomer analysis to trace sterol flux through the two pathways in mice. Surprisingly, no tissue used the canonical K–R pathway. Rather, a hybrid pathway was identified that we call the modified K–R (MK–R) pathway. Proportional flux through the Bloch pathway varied from 8% in preputial gland to 97% in testes, and the tissue-specificity observed in vivo was retained in cultured cells. The distribution of sterol isotopomers in plasma mirrored that of liver. Sterol depletion in cultured cells increased flux through the Bloch pathway, whereas overexpression of 24-dehydrocholesterol reductase (DHCR24) enhanced usage of the MK–R pathway. Thus, relative use of the Bloch and MK–R pathways is highly variable, tissue-specific, flux dependent, and epigenetically fixed. Maintenance of two interdigitated pathways permits production of diverse bioactive sterols that can be regulated independently of cholesterol. DOI: http://dx.doi.org/10.7554/eLife.07999.001 PMID:26114596

The exploration of contrasting pathways in Triple Negative Breast Cancer (TNBC).

PubMed

Narrandes, Shavira; Huang, Shujun; Murphy, Leigh; Xu, Wayne

2018-01-04

Triple Negative Breast Cancers (TNBCs) lack the appropriate targets for currently used breast cancer therapies, conferring an aggressive phenotype, more frequent relapse and poorer survival rates. The biological heterogeneity of TNBC complicates the clinical treatment further. We have explored and compared the biological pathways in TNBC and other subtypes of breast cancers, using an in silico approach and the hypothesis that two opposing effects (Yin and Yang) pathways in cancer cells determine the fate of cancer cells. Identifying breast subgroup specific components of these opposing pathways may aid in selecting potential therapeutic targets as well as further classifying the heterogeneous TNBC subtype. Gene expression and patient clinical data from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) were used for this study. Gene Set Enrichment Analysis (GSEA) was used to identify the more active pathways in cancer (Yin) than in normal and the more active pathways in normal (Yang) than in cancer. The clustering analysis was performed to compare pathways of TNBC with other types of breast cancers. The association of pathway classified TNBC sub-groups to clinical outcomes was tested using Cox regression model. Among 4729 curated canonical pathways in GSEA database, 133 Yin pathways (FDR < 0.05) and 71 Yang pathways (p-value <0.05) were discovered in TNBC. The FOXM1 is the top Yin pathway while PPARα is the top Yang pathway in TNBC. The TNBC and other types of breast cancers showed different pathways enrichment significance profiles. Using top Yin and Yang pathways as classifier, the TNBC can be further subtyped into six sub-groups each having different clinical outcomes. We first reported that the FOMX1 pathway is the most upregulated and the PPARα pathway is the most downregulated pathway in TNBC. These two pathways could be simultaneously targeted in further studies. Also the pathway classifier we performed in this study provided insight into the TNBC heterogeneity.

Transcriptome and proteome analysis of tyrosine kinase inhibitor treated canine mast cell tumour cells identifies potentially kit signaling-dependent genes

PubMed Central

2012-01-01

Background Canine mast cell tumour proliferation depends to a large extent on the activity of KIT, a tyrosine kinase receptor. Inhibitors of the KIT tyrosine kinase have recently been introduced and successfully applied as a therapeutic agent for this tumour type. However, little is known on the downstream target genes of this signaling pathway and molecular changes after inhibition. Results Transcriptome analysis of the canine mast cell tumour cell line C2 treated for up to 72 hours with the tyrosine kinase inhibitor masitinib identified significant changes in the expression levels of approximately 3500 genes or 16% of the canine genome. Approximately 40% of these genes had increased mRNA expression levels including genes associated with the pro-proliferative pathways of B- and T-cell receptors, chemokine receptors, steroid hormone receptors and EPO-, RAS and MAP kinase signaling. Proteome analysis of C2 cells treated for 72 hours identified 24 proteins with changed expression levels, most of which being involved in gene transcription, e.g. EIA3, EIA4, TARDBP, protein folding, e.g. HSP90, UCHL3, PDIA3 and protection from oxidative stress, GSTT3, SELENBP1. Conclusions Transcriptome and proteome analysis of neoplastic canine mast cells treated with masitinib confirmed the strong important and complex role of KIT in these cells. Approximately 16% of the total canine genome and thus the majority of the active genes were significantly transcriptionally regulated. Most of these changes were associated with reduced proliferation and metabolism of treated cells. Interestingly, several pro-proliferative pathways were up-regulated, which may represent attempts of masitinib treated cells to activate alternative pro-proliferative pathways. These pathways may contain hypothetical targets for a combination therapy with masitinib to further improve its therapeutic effect. PMID:22747577

The Impact of GFP Reporter Gene Transduction and Expression on Metabolomics of Placental Mesenchymal Stem Cells Determined by UHPLC-Q/TOF-MS.

PubMed

Yang, Jinfeng; Wang, Nan; Chen, Deying; Yu, Jiong; Pan, Qiaoling; Wang, Dan; Liu, Jingqi; Shi, Xiaowei; Dong, Xiaotian; Cao, Hongcui; Li, Liang; Li, Lanjuan

2017-01-01

Green fluorescent protein (GFP) is widely used as a reporter gene in regenerative medicine research to label and track stem cells. Here, we examined whether expressing GFP gene may impact the metabolism of human placental mesenchymal stem cells (hPMSCs). The GFP gene was transduced into hPMSCs using lentiviral-based infection to establish GFP + hPMSCs. A sensitive 13 C/ 12 C-dansyl labeling LC-MS method targeting the amine/phenol submetabolome was used for in-depth cell metabolome profiling. A total of 1151 peak pairs or metabolites were detected from 12 LC-MS runs. Principal component analysis and partial least squares discriminant analysis showed poor separation, and the volcano plots demonstrated that most of the metabolites were not significantly changed when hPMSCs were tagged with GFP. Overall, 739 metabolites were positively or putatively identified. Only 11 metabolites showed significant changes. Metabolic pathway analyses indicated that three of the identified metabolites were involved in nine pathways. However, these metabolites are unlikely to have a large impact on the metabolic pathways due to their nonessential roles and limited hits in pathway analysis. This study indicated that the expression of ectopic GFP reporter gene did not significantly alter the metabolomics pathways covered by the amine/phenol submetabolome.

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

PubMed Central

Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary

2018-01-01

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574

Scholarly Concentration Program Development: A Generalizable, Data-Driven Approach.

PubMed

Burk-Rafel, Jesse; Mullan, Patricia B; Wagenschutz, Heather; Pulst-Korenberg, Alexandra; Skye, Eric; Davis, Matthew M

2016-11-01

Scholarly concentration programs-also known as scholarly projects, pathways, tracks, or pursuits-are increasingly common in U.S. medical schools. However, systematic, data-driven program development methods have not been described. The authors examined scholarly concentration programs at U.S. medical schools that U.S. News & World Report ranked as top 25 for research or primary care (n = 43 institutions), coding concentrations and mission statements. Subsequently, the authors conducted a targeted needs assessment via a student-led, institution-wide survey, eliciting learners' preferences for 10 "Pathways" (i.e., concentrations) and 30 "Topics" (i.e., potential content) augmenting core curricula at their institution. Exploratory factor analysis (EFA) and a capacity optimization algorithm characterized best institutional options for learner-focused Pathway development. The authors identified scholarly concentration programs at 32 of 43 medical schools (74%), comprising 199 distinct concentrations (mean concentrations per program: 6.2, mode: 5, range: 1-16). Thematic analysis identified 10 content domains; most common were "Global/Public Health" (30 institutions; 94%) and "Clinical/Translational Research" (26 institutions; 81%). The institutional needs assessment (n = 468 medical students; response rate 60% overall, 97% among first-year students) demonstrated myriad student preferences for Pathways and Topics. EFA of Topic preferences identified eight factors, systematically related to Pathway preferences, informing content development. Capacity modeling indicated that offering six Pathways could guarantee 95% of first-year students (162/171) their first- or second-choice Pathway. This study demonstrates a generalizable, data-driven approach to scholarly concentration program development that reflects student preferences and institutional strengths, while optimizing program diversity within capacity constraints.

Transcriptomic analysis in the developing zebrafish embryo after compound exposure: Individual gene expression and pathway regulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hermsen, Sanne A.B., E-mail: Sanne.Hermsen@rivm.nl; Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht; Institute for Risk Assessment Sciences

2013-10-01

The zebrafish embryotoxicity test is a promising alternative assay for developmental toxicity. Classically, morphological assessment of the embryos is applied to evaluate the effects of compound exposure. However, by applying differential gene expression analysis the sensitivity and predictability of the test may be increased. For defining gene expression signatures of developmental toxicity, we explored the possibility of using gene expression signatures of compound exposures based on commonly expressed individual genes as well as based on regulated gene pathways. Four developmental toxic compounds were tested in concentration-response design, caffeine, carbamazepine, retinoic acid and valproic acid, and two non-embryotoxic compounds, D-mannitol andmore » saccharin, were included. With transcriptomic analyses we were able to identify commonly expressed genes, which were mostly development related, after exposure to the embryotoxicants. We also identified gene pathways regulated by the embryotoxicants, suggestive of their modes of action. Furthermore, whereas pathways may be regulated by all compounds, individual gene expression within these pathways can differ for each compound. Overall, the present study suggests that the use of individual gene expression signatures as well as pathway regulation may be useful starting points for defining gene biomarkers for predicting embryotoxicity. - Highlights: • The zebrafish embryotoxicity test in combination with transcriptomics was used. • We explored two approaches of defining gene biomarkers for developmental toxicity. • Four compounds in concentration-response design were tested. • We identified commonly expressed individual genes as well as regulated gene pathways. • Both approaches seem suitable starting points for defining gene biomarkers.« less

Global expression analysis of gene regulatory pathways during endocrine pancreatic development.

PubMed

Gu, Guoqiang; Wells, James M; Dombkowski, David; Preffer, Fred; Aronow, Bruce; Melton, Douglas A

2004-01-01

To define genetic pathways that regulate development of the endocrine pancreas, we generated transcriptional profiles of enriched cells isolated from four biologically significant stages of endocrine pancreas development: endoderm before pancreas specification, early pancreatic progenitor cells, endocrine progenitor cells and adult islets of Langerhans. These analyses implicate new signaling pathways in endocrine pancreas development, and identified sets of known and novel genes that are temporally regulated, as well as genes that spatially define developing endocrine cells from their neighbors. The differential expression of several genes from each time point was verified by RT-PCR and in situ hybridization. Moreover, we present preliminary functional evidence suggesting that one transcription factor encoding gene (Myt1), which was identified in our screen, is expressed in endocrine progenitors and may regulate alpha, beta and delta cell development. In addition to identifying new genes that regulate endocrine cell fate, this global gene expression analysis has uncovered informative biological trends that occur during endocrine differentiation.

Metabolic changes associated with papillary thyroid carcinoma: A nuclear magnetic resonance-based metabolomics study.

PubMed

Li, Yanyun; Chen, Minjian; Liu, Cuiping; Xia, Yankai; Xu, Bo; Hu, Yanhui; Chen, Ting; Shen, Meiping; Tang, Wei

2018-05-01

Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. Nuclear magnetic resonance (NMR)‑based metabolomic technique is the gold standard in metabolite structural elucidation, and can provide different coverage of information compared with other metabolomic techniques. Here, we firstly conducted NMR based metabolomics study regarding detailed metabolic changes especially metabolic pathway changes related to PTC pathogenesis. 1H NMR-based metabolomic technique was adopted in conju-nction with multivariate analysis to analyze matched tumor and normal thyroid tissues obtained from 16 patients. The results were further annotated with Kyoto Encyclopedia of Genes and Genomes (KEGG), and Human Metabolome Database, and then were analyzed using modules of pathway analysis and enrichment analysis of MetaboAnalyst 3.0. Based on the analytical techniques, we established the models of principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least-squares discriminant analysis (OPLS‑DA) which could discriminate PTC from normal thyroid tissue, and found 15 robust differentiated metabolites from two OPLS-DA models. We identified 8 KEGG pathways and 3 pathways of small molecular pathway database which were significantly related to PTC by using pathway analysis and enrichment analysis, respectively, through which we identified metabolisms related to PTC including branched chain amino acid metabolism (leucine and valine), other amino acid metabolism (glycine and taurine), glycolysis (lactate), tricarboxylic acid cycle (citrate), choline metabolism (choline, ethanolamine and glycerolphosphocholine) and lipid metabolism (very-low‑density lipoprotein and low-density lipoprotein). In conclusion, the PTC was characterized with increased glycolysis and inhibited tricarboxylic acid cycle, increased oncogenic amino acids as well as abnormal choline and lipid metabolism. The findings in this study provide new insights into detailed metabolic changes of PTC, and hold great potential in the treatment of PTC.

Biosynthetic Pathway for the Epipolythiodioxopiperazine Acetylaranotin in Aspergillus terreus Revealed by Genome-based Deletion Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Chun-Jun; Yeh, Hsu-Hua; Chiang, Yi Ming

2013-04-15

Abstract Epipolythiodioxopiperazines (ETPs) are a class of fungal secondary metabolites derived from cyclic peptides. Acetylaranotin belongs to one structural subgroup of ETPs characterized by the presence of a seven-membered dihydrooxepine ring. Defining the genes involved in acetylaranotin biosynthesis should provide a means to increase production of these compounds and facilitate the engineering of second-generation molecules. The filamentous fungus Aspergillus terreus produces acetylaranotin and related natural products. Using targeted gene deletions, we have identified a cluster of 9 genes including one nonribosomal peptide synthase gene, ataP, that is required for acetylaranotin biosynthesis. Chemical analysis of the wild type and mutant strainsmore » enabled us to isolate seventeen natural products that are either intermediates in the normal biosynthetic pathway or shunt products that are produced when the pathway is interrupted through mutation. Nine of the compounds identified in this study are novel natural products. Our data allow us to propose a complete biosynthetic pathway for acetylaranotin and related natural products.« less

Hysteresis and parent-metabolite analyses unravel characteristic pesticide transport mechanisms in a mixed land use catchment.

PubMed

Tang, Ting; Stamm, Christian; van Griensven, Ann; Seuntjens, Piet; Bronders, Jan

2017-11-01

To properly estimate and manage pesticide occurrence in urban rivers, it is essential, but often highly challenging, to identify the key pesticide transport pathways in association to the main sources. This study examined the concentration-discharge hysteresis behaviour (hysteresis analysis) for three pesticides and the parent-metabolite concentration dynamics for two metabolites at sites with different levels of urban influence in a mixed land use catchment (25 km 2 ) within the Swiss Greifensee area, aiming to identify the dominant pesticide transport pathways. Combining an adapted hysteresis classification framework with prior knowledge of the field conditions and pesticide usage, we demonstrated the possibility of using hysteresis analysis to qualitatively infer the dominant pesticide transport pathway in mixed land-use catchments. The analysis showed that hysteresis types, and therefore the dominant transport pathway, vary among pesticides, sites and rainfall events. Hysteresis loops mostly correspond to dominant transport by flow components with intermediate response time, although pesticide sources indicate that fast transport pathways are responsible in most cases (e.g. urban runoff and combined sewer overflows). The discrepancy suggests the fast transport pathways can be slowed down due to catchment storages, such as topographic depressions in agricultural areas, a wastewater treatment plant (WWTP) and other artificial storage units (e.g. retention basins) in urban areas. Moreover, the WWTP was identified as an important factor modifying the parent-metabolite concentration dynamics during rainfall events. To properly predict and manage pesticide occurrence in catchments of mixed land uses, the hydrological delaying effect and chemical processes within the artificial structures need to be accounted for, in addition to the catchment hydrology and the diversity of pesticide sources. This study demonstrates that in catchments with diverse pesticide sources and complex transport mechanisms, the adapted hysteresis analysis can help to improve our understanding on pesticide transport behaviours and provide a basis for effective management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-membership gene regulation in pathway based microarray analysis

PubMed Central

2011-01-01

Background Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. Results We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. Conclusions We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes. PMID:21939531

Multi-membership gene regulation in pathway based microarray analysis.

PubMed

Pavlidis, Stelios P; Payne, Annette M; Swift, Stephen M

2011-09-22

Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes.

Phosphoproteomic Analysis Identifies Signaling Pathways Regulated by Curcumin in Human Colon Cancer Cells.

PubMed

Sato, Tatsuhiro; Higuchi, Yutaka; Shibagaki, Yoshio; Hattori, Seisuke

2017-09-01

Curcumin, a major polyphenol of the spice turmeric, acts as a potent chemopreventive and chemotherapeutic agent in several cancer types, including colon cancer. Although various proteins have been shown to be affected by curcumin, how curcumin exerts its anticancer activity is not fully understood. Phosphoproteomic analyses were performed using SW480 and SW620 human colon cancer cells to identify curcumin-affected signaling pathways. Curcumin inhibited the growth of the two cell lines in a dose-dependent manner. Thirty-nine curcumin-regulated phosphoproteins were identified, five of which are involved in cancer signaling pathways. Detailed analyses revealed that the mTORC1 and p53 signaling pathways are main targets of curcumin. Our results provide insight into the molecular mechanisms of the anticancer activities of curcumin and future molecular targets for its clinical application. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Genome-wide identification of conserved intronic non-coding sequences using a Bayesian segmentation approach.

PubMed

Algama, Manjula; Tasker, Edward; Williams, Caitlin; Parslow, Adam C; Bryson-Richardson, Robert J; Keith, Jonathan M

2017-03-27

Computational identification of non-coding RNAs (ncRNAs) is a challenging problem. We describe a genome-wide analysis using Bayesian segmentation to identify intronic elements highly conserved between three evolutionarily distant vertebrate species: human, mouse and zebrafish. We investigate the extent to which these elements include ncRNAs (or conserved domains of ncRNAs) and regulatory sequences. We identified 655 deeply conserved intronic sequences in a genome-wide analysis. We also performed a pathway-focussed analysis on genes involved in muscle development, detecting 27 intronic elements, of which 22 were not detected in the genome-wide analysis. At least 87% of the genome-wide and 70% of the pathway-focussed elements have existing annotations indicative of conserved RNA secondary structure. The expression of 26 of the pathway-focused elements was examined using RT-PCR, providing confirmation that they include expressed ncRNAs. Consistent with previous studies, these elements are significantly over-represented in the introns of transcription factors. This study demonstrates a novel, highly effective, Bayesian approach to identifying conserved non-coding sequences. Our results complement previous findings that these sequences are enriched in transcription factors. However, in contrast to previous studies which suggest the majority of conserved sequences are regulatory factor binding sites, the majority of conserved sequences identified using our approach contain evidence of conserved RNA secondary structures, and our laboratory results suggest most are expressed. Functional roles at DNA and RNA levels are not mutually exclusive, and many of our elements possess evidence of both. Moreover, ncRNAs play roles in transcriptional and post-transcriptional regulation, and this may contribute to the over-representation of these elements in introns of transcription factors. We attribute the higher sensitivity of the pathway-focussed analysis compared to the genome-wide analysis to improved alignment quality, suggesting that enhanced genomic alignments may reveal many more conserved intronic sequences.

Use of RNA-seq to identify cardiac genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy

PubMed Central

Friedenberg, Steven G.; Chdid, Lhoucine; Keene, Bruce; Sherry, Barbara; Motsinger-Reif, Alison; Meurs, Kathryn M.

2017-01-01

OBJECTIVE To identify cardiac tissue genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy (DCM). ANIMALS 8 dogs with and 5 dogs without DCM. PROCEDURES Following euthanasia, samples of left ventricular myocardium were collected from each dog. Total RNA was extracted from tissue samples, and RNA sequencing was performed on each sample. Samples from dogs with and without DCM were grouped to identify genes that were differentially regulated between the 2 populations. Overrepresentation analysis was performed on upregulated and downregulated gene sets to identify altered molecular pathways in dogs with DCM. RESULTS Genes involved in cellular energy metabolism, especially metabolism of carbohydrates and fats, were significantly downregulated in dogs with DCM. Expression of cardiac structural proteins was also altered in affected dogs. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that RNA sequencing may provide important insights into the pathogenesis of DCM in dogs and highlight pathways that should be explored to identify causative mutations and develop novel therapeutic interventions. PMID:27347821

Benchmarking pathway interaction network for colorectal cancer to identify dysregulated pathways.

PubMed

Wang, Q; Shi, C-J; Lv, S-H

2017-03-30

Different pathways act synergistically to participate in many biological processes. Thus, the purpose of our study was to extract dysregulated pathways to investigate the pathogenesis of colorectal cancer (CRC) based on the functional dependency among pathways. Protein-protein interaction (PPI) information and pathway data were retrieved from STRING and Reactome databases, respectively. After genes were aligned to the pathways, each pathway activity was calculated using the principal component analysis (PCA) method, and the seed pathway was discovered. Subsequently, we constructed the pathway interaction network (PIN), where each node represented a biological pathway based on gene expression profile, PPI data, as well as pathways. Dysregulated pathways were then selected from the PIN according to classification performance and seed pathway. A PIN including 11,960 interactions was constructed to identify dysregulated pathways. Interestingly, the interaction of mRNA splicing and mRNA splicing-major pathway had the highest score of 719.8167. Maximum change of the activity score between CRC and normal samples appeared in the pathway of DNA replication, which was selected as the seed pathway. Starting with this seed pathway, a pathway set containing 30 dysregulated pathways was obtained with an area under the curve score of 0.8598. The pathway of mRNA splicing, mRNA splicing-major pathway, and RNA polymerase I had the maximum genes of 107. Moreover, we found that these 30 pathways had crosstalks with each other. The results suggest that these dysregulated pathways might be used as biomarkers to diagnose CRC.

Meta-analysis of human gene expression in response to Mycobacterium tuberculosis infection reveals potential therapeutic targets.

PubMed

Wang, Zhang; Arat, Seda; Magid-Slav, Michal; Brown, James R

2018-01-10

With the global emergence of multi-drug resistant strains of Mycobacterium tuberculosis, new strategies to treat tuberculosis are urgently needed such as therapeutics targeting potential human host factors. Here we performed a statistical meta-analysis of human gene expression in response to both latent and active pulmonary tuberculosis infections from nine published datasets. We found 1655 genes that were significantly differentially expressed during active tuberculosis infection. In contrast, no gene was significant for latent tuberculosis. Pathway enrichment analysis identified 90 significant canonical human pathways, including several pathways more commonly related to non-infectious diseases such as the LRRK2 pathway in Parkinson's disease, and PD-1/PD-L1 signaling pathway important for new immuno-oncology therapies. The analysis of human genome-wide association studies datasets revealed tuberculosis-associated genetic variants proximal to several genes in major histocompatibility complex for antigen presentation. We propose several new targets and drug-repurposing opportunities including intravenous immunoglobulin, ion-channel blockers and cancer immuno-therapeutics for development as combination therapeutics with anti-mycobacterial agents. Our meta-analysis provides novel insights into host genes and pathways important for tuberculosis and brings forth potential drug repurposing opportunities for host-directed therapies.

From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.

PubMed

Chen, Yunshun; Lun, Aaron T L; Smyth, Gordon K

2016-01-01

In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims of RNA-seq profiling is to identify genes or molecular pathways that are differentially expressed (DE) between two or more biological conditions. This article demonstrates a computational workflow for the detection of DE genes and pathways from RNA-seq data by providing a complete analysis of an RNA-seq experiment profiling epithelial cell subsets in the mouse mammary gland. The workflow uses R software packages from the open-source Bioconductor project and covers all steps of the analysis pipeline, including alignment of read sequences, data exploration, differential expression analysis, visualization and pathway analysis. Read alignment and count quantification is conducted using the Rsubread package and the statistical analyses are performed using the edgeR package. The differential expression analysis uses the quasi-likelihood functionality of edgeR.

The use of functional chemical-protein associations to identify multi-pathway renoprotectants.

PubMed

Xu, Jia; Meng, Kexin; Zhang, Rui; Yang, He; Liao, Chang; Zhu, Wenliang; Jiao, Jundong

2014-01-01

Typically, most nephropathies can be categorized as complex human diseases in which the cumulative effect of multiple minor genes, combined with environmental and lifestyle factors, determines the disease phenotype. Thus, multi-target drugs would be more likely to facilitate comprehensive renoprotection than single-target agents. In this study, functional chemical-protein association analysis was performed to retrieve multi-target drugs of high pathway wideness from the STITCH 3.1 database. Pathway wideness of a drug evaluated the efficiency of regulation of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in quantity. We identified nine experimentally validated renoprotectants that exerted remarkable impact on KEGG pathways by targeting a limited number of proteins. We selected curcumin as an illustrative compound to display the advantage of multi-pathway drugs on renoprotection. We compared curcumin with hemin, an agonist of heme oxygenase-1 (HO-1), which significantly affects only one KEGG pathway, porphyrin and chlorophyll metabolism (adjusted p = 1.5×10-5). At the same concentration (10 µM), both curcumin and hemin equivalently mitigated oxidative stress in H2O2-treated glomerular mesangial cells. The benefit of using hemin was derived from its agonistic effect on HO-1, providing relief from oxidative stress. Selective inhibition of HO-1 completely blocked the action of hemin but not that of curcumin, suggesting simultaneous multi-pathway intervention by curcumin. Curcumin also increased cellular autophagy levels, enhancing its protective effect; however, hemin had no effects. Based on the fact that the dysregulation of multiple pathways is implicated in the etiology of complex diseases, we proposed a feasible method for identifying multi-pathway drugs from compounds with validated targets. Our efforts will help identify multi-pathway agents capable of providing comprehensive protection against renal injuries.

Pathway and network-based analysis of genome-wide association studies and RT-PCR validation in polycystic ovary syndrome.

PubMed

Shen, Haoran; Liang, Zhou; Zheng, Saihua; Li, Xuelian

2017-11-01

The purpose of this study was to identify promising candidate genes and pathways in polycystic ovary syndrome (PCOS). Microarray dataset GSE345269 obtained from the Gene Expression Omnibus database includes 7 granulosa cell samples from PCOS patients, and 3 normal granulosa cell samples. Differentially expressed genes (DEGs) were screened between PCOS and normal samples. Pathway enrichment analysis was conducted for DEGs using ClueGO and CluePedia plugin of Cytoscape. A Reactome functional interaction (FI) network of the DEGs was built using ReactomeFIViz, and then network modules were extracted, followed by pathway enrichment analysis for the modules. Expression of DEGs in granulosa cell samples was measured using quantitative RT-PCR. A total of 674 DEGs were retained, which were significantly enriched with inflammation and immune-related pathways. Eight modules were extracted from the Reactome FI network. Pathway enrichment analysis revealed significant pathways of each module: module 0, Regulation of RhoA activity and Signaling by Rho GTPases pathways shared ARHGAP4 and ARHGAP9; module 2, GlycoProtein VI-mediated activation cascade pathway was enriched with RHOG; module 3, Thromboxane A2 receptor signaling, Chemokine signaling pathway, CXCR4-mediated signaling events pathways were enriched with LYN, the hub gene of module 3. Results of RT-PCR confirmed the finding of the bioinformatic analysis that ARHGAP4, ARHGAP9, RHOG and LYN were significantly upregulated in PCOS. RhoA-related pathways, GlycoProtein VI-mediated activation cascade pathway, ARHGAP4, ARHGAP9, RHOG and LYN may be involved in the pathogenesis of PCOS.

Identification of ageing-associated naturally occurring peptides in human urine

PubMed Central

Nkuipou-Kenfack, Esther; Bhat, Akshay; Klein, Julie; Jankowski, Vera; Mullen, William; Vlahou, Antonia; Dakna, Mohammed; Koeck, Thomas; Schanstra, Joost P.; Zürbig, Petra; Rudolph, Karl L.; Schumacher, Björn; Pich, Andreas; Mischak, Harald

2015-01-01

To assess normal and pathological peptidomic changes that may lead to an improved understanding of molecular mechanisms underlying ageing, urinary peptidomes of 1227 healthy and 10333 diseased individuals between 20 and 86 years of age were investigated. The diseases thereby comprised diabetes mellitus, renal and cardiovascular diseases. Using age as a continuous variable, 116 peptides were identified that significantly (p < 0.05; |ρ|≥0.2) correlated with age in the healthy cohort. The same approach was applied to the diseased cohort. Upon comparison of the peptide patterns of the two cohorts 112 common age-correlated peptides were identified. These 112 peptides predominantly originated from collagen, uromodulin and fibrinogen. While most fibrillar and basement membrane collagen fragments showed a decreased age-related excretion, uromodulin, beta-2-microglobulin and fibrinogen fragments showed an increase. Peptide-based in silico protease analysis was performed and 32 proteases, including matrix metalloproteinases and cathepsins, were predicted to be involved in ageing. Identified peptides, predicted proteases and patient information were combined in a systems biology pathway analysis to identify molecular pathways associated with normal and/or pathological ageing. While perturbations in collagen homeostasis, trafficking of toll-like receptors and endosomal pathways were commonly identified, degradation of insulin-like growth factor-binding proteins was uniquely identified in pathological ageing. PMID:26431327

LncSubpathway: a novel approach for identifying dysfunctional subpathways associated with risk lncRNAs by integrating lncRNA and mRNA expression profiles and pathway topologies.

PubMed

Xu, Yanjun; Li, Feng; Wu, Tan; Xu, Yingqi; Yang, Haixiu; Dong, Qun; Zheng, Meiyu; Shang, Desi; Zhang, Chunlong; Zhang, Yunpeng; Li, Xia

2017-02-28

Long non-coding RNAs (lncRNAs) play important roles in various biological processes, including the development of many diseases. Pathway analysis is a valuable aid for understanding the cellular functions of these transcripts. We have developed and characterized LncSubpathway, a novel method that integrates lncRNA and protein coding gene (PCG) expression with interactome data to identify disease risk subpathways that functionally associated with risk lncRNAs. LncSubpathway identifies the most relevance regions which are related with risk lncRNA set and implicated with study conditions through simultaneously considering the dysregulation extent of lncRNAs, PCGs and their correlations. Simulation studies demonstrated that the sensitivity and false positive rates of LncSubpathway were within acceptable ranges, and that LncSubpathway could accurately identify dysregulated regions that related with disease risk lncRNAs within pathways. When LncSubpathway was applied to colorectal carcinoma and breast cancer subtype datasets, it identified cancer type- and breast cancer subtype-related meaningful subpathways. Further, analysis of its robustness and reproducibility indicated that LncSubpathway was a reliable means of identifying subpathways that functionally associated with lncRNAs. LncSubpathway is freely available at http://www.bio-bigdata.com/lncSubpathway/.

LncSubpathway: a novel approach for identifying dysfunctional subpathways associated with risk lncRNAs by integrating lncRNA and mRNA expression profiles and pathway topologies

PubMed Central

Wu, Tan; Xu, Yingqi; Yang, Haixiu; Dong, Qun; Zheng, Meiyu; Shang, Desi; Zhang, Chunlong; Zhang, Yunpeng; Li, Xia

2017-01-01

Long non-coding RNAs (lncRNAs) play important roles in various biological processes, including the development of many diseases. Pathway analysis is a valuable aid for understanding the cellular functions of these transcripts. We have developed and characterized LncSubpathway, a novel method that integrates lncRNA and protein coding gene (PCG) expression with interactome data to identify disease risk subpathways that functionally associated with risk lncRNAs. LncSubpathway identifies the most relevance regions which are related with risk lncRNA set and implicated with study conditions through simultaneously considering the dysregulation extent of lncRNAs, PCGs and their correlations. Simulation studies demonstrated that the sensitivity and false positive rates of LncSubpathway were within acceptable ranges, and that LncSubpathway could accurately identify dysregulated regions that related with disease risk lncRNAs within pathways. When LncSubpathway was applied to colorectal carcinoma and breast cancer subtype datasets, it identified cancer type- and breast cancer subtype-related meaningful subpathways. Further, analysis of its robustness and reproducibility indicated that LncSubpathway was a reliable means of identifying subpathways that functionally associated with lncRNAs. LncSubpathway is freely available at http://www.bio-bigdata.com/lncSubpathway/. PMID:28152521

The Genetics of Axon Guidance and Axon Regeneration in Caenorhabditis elegans

PubMed Central

Chisholm, Andrew D.; Hutter, Harald; Jin, Yishi; Wadsworth, William G.

2016-01-01

The correct wiring of neuronal circuits depends on outgrowth and guidance of neuronal processes during development. In the past two decades, great progress has been made in understanding the molecular basis of axon outgrowth and guidance. Genetic analysis in Caenorhabditis elegans has played a key role in elucidating conserved pathways regulating axon guidance, including Netrin signaling, the slit Slit/Robo pathway, Wnt signaling, and others. Axon guidance factors were first identified by screens for mutations affecting animal behavior, and by direct visual screens for axon guidance defects. Genetic analysis of these pathways has revealed the complex and combinatorial nature of guidance cues, and has delineated how cues guide growth cones via receptor activity and cytoskeletal rearrangement. Several axon guidance pathways also affect directed migrations of non-neuronal cells in C. elegans, with implications for normal and pathological cell migrations in situations such as tumor metastasis. The small number of neurons and highly stereotyped axonal architecture of the C. elegans nervous system allow analysis of axon guidance at the level of single identified axons, and permit in vivo tests of prevailing models of axon guidance. C. elegans axons also have a robust capacity to undergo regenerative regrowth after precise laser injury (axotomy). Although such axon regrowth shares some similarities with developmental axon outgrowth, screens for regrowth mutants have revealed regeneration-specific pathways and factors that were not identified in developmental screens. Several areas remain poorly understood, including how major axon tracts are formed in the embryo, and the function of axon regeneration in the natural environment. PMID:28114100

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

PubMed

Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

2017-04-27

Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.

A genome-wide longitudinal transcriptome analysis of the aging model Podospora anserina.

PubMed

Philipp, Oliver; Hamann, Andrea; Servos, Jörg; Werner, Alexandra; Koch, Ina; Osiewacz, Heinz D

2013-01-01

Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression). A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wild-type transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i) present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii) suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii) present testable predictions for subsequent experimental investigations.

Study of Staphylococcus aureus N315 Pathogenic Genes by Text Mining and Enrichment Analysis of Pathways and Operons.

PubMed

Yang, Chun-Feng; Gou, Wei-Hui; Dai, Xin-Lun; Li, Yu-Mei

2018-06-01

Staphylococcus aureus (S. aureus) is a versatile pathogen found in many environments and can cause nosocomial infections in the community and hospitals. S. aureus infection is an increasingly serious threat to global public health that requires action across many government bodies, medical and health sectors, and scientific research institutions. In the present study, S. aureus N315 genes that have been shown in the literature to be pathogenic were extracted using a bibliometric method for functional enrichment analysis of pathways and operons to statistically discover novel pathogenic genes associated with S. aureus N315. A total of 383 pathogenic genes were mined from the literature using bibliometrics, and subsequently a few new pathogenic genes of S. aureus N315 were identified by functional enrichment analysis of pathways and operons. The discovery of these novel S. aureus N315 pathogenic genes is of great significance to treat S. aureus induced diseases and identify potential diagnostic markers, thus providing theoretical fundamentals for epidemiological prevention.

Plasma metabolic profiling analysis of nephrotoxicity induced by acyclovir using metabonomics coupled with multivariate data analysis.

PubMed

Zhang, Xiuxiu; Li, Yubo; Zhou, Huifang; Fan, Simiao; Zhang, Zhenzhu; Wang, Lei; Zhang, Yanjun

2014-08-01

Acyclovir (ACV) is an antiviral agent. However, its use is limited by adverse side effect, particularly by its nephrotoxicity. Metabonomics technology can provide essential information on the metabolic profiles of biofluids and organs upon drug administration. Therefore, in this study, mass spectrometry-based metabonomics coupled with multivariate data analysis was used to identify the plasma metabolites and metabolic pathways related to nephrotoxicity caused by intraperitoneal injection of low (50mg/kg) and high (100mg/kg) doses of acyclovir. Sixteen biomarkers were identified by metabonomics and nephrotoxicity results revealed the dose-dependent effect of acyclovir on kidney tissues. The present study showed that the top four metabolic pathways interrupted by acyclovir included the metabolisms of arachidonic acid, tryptophan, arginine and proline, and glycerophospholipid. This research proves the established metabonomic approach can provide information on changes in metabolites and metabolic pathways, which can be applied to in-depth research on the mechanism of acyclovir-induced kidney injury. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative study on gene set and pathway topology-based enrichment methods.

PubMed

Bayerlová, Michaela; Jung, Klaus; Kramer, Frank; Klemm, Florian; Bleckmann, Annalen; Beißbarth, Tim

2015-10-22

Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis. We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods. In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower. We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both types of methods for enrichment analysis require further improvements in order to deal with the problem of pathway overlaps.

Comparative transcriptome analysis of the swimbladder reveals expression signatures in response to low oxygen stress in channel catfish, Ictalurus punctatus.

PubMed

Yang, Yujia; Fu, Qiang; Wang, Xiaozhu; Liu, Yang; Zeng, Qifan; Li, Yun; Gao, Sen; Bao, Lisui; Liu, Shikai; Gao, Dongya; Dunham, Rex; Liu, Zhanjiang

2018-05-25

Channel catfish is the leading aquaculture species in the US, and one of the reasons for its application in aquaculture is its relatively high tolerance against hypoxia. However, hypoxia can still cause huge economic losses to the catfish industry. Studies on hypoxia tolerance, therefore, are important for aquaculture. Fish swimbladder has been considered as an accessory respiration organ surrounded by a dense capillary countercurrent exchange system. In this regard, we conducted RNA-Seq analysis with swimbladder samples of catfish under hypoxic and normal conditions to determine if swimbladder was responsive to low oxygen treatment, and to reveal genes, their expression patterns and pathways involved in hypoxia responses in catfish. A total of 155 differentially expressed genes (DEGs) were identified from swimbladder of adult catfish, whereas a total of 2,127 DEGs were identified from swimbladder of fingerling catfish, under hypoxic condition as compared to untreated controls. Subsequent pathway analysis revealed that many DEGs under hypoxia were involved in HIF signaling pathway (nos2, eno2, camk2d2, prkcb, cdkn1a, eno1, and tfrc), MAPK signaling pathway (voltage-dependent calcium channel subunit genes), PI3K/Akt/mTOR signaling pathway (itga6, g6pc, and cdkn1a), Ras signaling pathway (efna3 and ksr2), and signaling by VEGF (fn1, wasf3, and hspb1) in catfish swimbladder. This study provided insights into regulation of gene expression and their involved gene pathways in catfish swimbladder in response to low oxygen stresses.

A Novel Hydrolase Identified by Genomic-Proteomic Analysis of Phenylurea Herbicide Mineralization by Variovorax sp. Strain SRS16▿†

PubMed Central

Bers, Karolien; Leroy, Baptiste; Breugelmans, Philip; Albers, Pieter; Lavigne, Rob; Sørensen, Sebastian R.; Aamand, Jens; De Mot, René; Wattiez, Ruddy; Springael, Dirk

2011-01-01

The soil bacterial isolate Variovorax sp. strain SRS16 mineralizes the phenylurea herbicide linuron. The proposed pathway initiates with hydrolysis of linuron to 3,4-dichloroaniline (DCA) and N,O-dimethylhydroxylamine, followed by conversion of DCA to Krebs cycle intermediates. Differential proteomic analysis showed a linuron-dependent upregulation of several enzymes that fit into this pathway, including an amidase (LibA), a multicomponent chloroaniline dioxygenase, and enzymes associated with a modified chlorocatechol ortho-cleavage pathway. Purified LibA is a monomeric linuron hydrolase of ∼55 kDa with a Km and a Vmax for linuron of 5.8 μM and 0.16 nmol min−1, respectively. This novel member of the amidase signature family is unrelated to phenylurea-hydrolyzing enzymes from Gram-positive bacteria and lacks activity toward other tested phenylurea herbicides. Orthologues of libA are present in all other tested linuron-degrading Variovorax strains with the exception of Variovorax strains WDL1 and PBS-H4, suggesting divergent evolution of the linuron catabolic pathway in different Variovorax strains. The organization of the linuron degradation genes identified in the draft SRS16 genome sequence indicates that gene patchwork assembly is at the origin of the pathway. Transcription analysis suggests that a catabolic intermediate, rather than linuron itself, acts as effector in activation of the pathway. Our study provides the first report on the genetic organization of a bacterial pathway for complete mineralization of a phenylurea herbicide and the first report on a linuron hydrolase in Gram-negative bacteria. PMID:22003008

Computational analysis of multimorbidity between asthma, eczema and rhinitis

PubMed Central

Aguilar, Daniel; Pinart, Mariona; Koppelman, Gerard H.; Saeys, Yvan; Nawijn, Martijn C.; Postma, Dirkje S.; Akdis, Mübeccel; Auffray, Charles; Ballereau, Stéphane; Benet, Marta; García-Aymerich, Judith; González, Juan Ramón; Guerra, Stefano; Keil, Thomas; Kogevinas, Manolis; Lambrecht, Bart; Lemonnier, Nathanael; Melen, Erik; Sunyer, Jordi; Valenta, Rudolf; Valverde, Sergi; Wickman, Magnus; Bousquet, Jean; Oliva, Baldo; Antó, Josep M.

2017-01-01

Background The mechanisms explaining the co-existence of asthma, eczema and rhinitis (allergic multimorbidity) are largely unknown. We investigated the mechanisms underlying multimorbidity between three main allergic diseases at a molecular level by identifying the proteins and cellular processes that are common to them. Methods An in silico study based on computational analysis of the topology of the protein interaction network was performed in order to characterize the molecular mechanisms of multimorbidity of asthma, eczema and rhinitis. As a first step, proteins associated to either disease were identified using data mining approaches, and their overlap was calculated. Secondly, a functional interaction network was built, allowing to identify cellular pathways involved in allergic multimorbidity. Finally, a network-based algorithm generated a ranked list of newly predicted multimorbidity-associated proteins. Results Asthma, eczema and rhinitis shared a larger number of associated proteins than expected by chance, and their associated proteins exhibited a significant degree of interconnectedness in the interaction network. There were 15 pathways involved in the multimorbidity of asthma, eczema and rhinitis, including IL4 signaling and GATA3-related pathways. A number of proteins potentially associated to these multimorbidity processes were also obtained. Conclusions These results strongly support the existence of an allergic multimorbidity cluster between asthma, eczema and rhinitis, and suggest that type 2 signaling pathways represent a relevant multimorbidity mechanism of allergic diseases. Furthermore, we identified new candidates contributing to multimorbidity that may assist in identifying new targets for multimorbid allergic diseases. PMID:28598986

Computational analysis of multimorbidity between asthma, eczema and rhinitis.

PubMed

Aguilar, Daniel; Pinart, Mariona; Koppelman, Gerard H; Saeys, Yvan; Nawijn, Martijn C; Postma, Dirkje S; Akdis, Mübeccel; Auffray, Charles; Ballereau, Stéphane; Benet, Marta; García-Aymerich, Judith; González, Juan Ramón; Guerra, Stefano; Keil, Thomas; Kogevinas, Manolis; Lambrecht, Bart; Lemonnier, Nathanael; Melen, Erik; Sunyer, Jordi; Valenta, Rudolf; Valverde, Sergi; Wickman, Magnus; Bousquet, Jean; Oliva, Baldo; Antó, Josep M

2017-01-01

The mechanisms explaining the co-existence of asthma, eczema and rhinitis (allergic multimorbidity) are largely unknown. We investigated the mechanisms underlying multimorbidity between three main allergic diseases at a molecular level by identifying the proteins and cellular processes that are common to them. An in silico study based on computational analysis of the topology of the protein interaction network was performed in order to characterize the molecular mechanisms of multimorbidity of asthma, eczema and rhinitis. As a first step, proteins associated to either disease were identified using data mining approaches, and their overlap was calculated. Secondly, a functional interaction network was built, allowing to identify cellular pathways involved in allergic multimorbidity. Finally, a network-based algorithm generated a ranked list of newly predicted multimorbidity-associated proteins. Asthma, eczema and rhinitis shared a larger number of associated proteins than expected by chance, and their associated proteins exhibited a significant degree of interconnectedness in the interaction network. There were 15 pathways involved in the multimorbidity of asthma, eczema and rhinitis, including IL4 signaling and GATA3-related pathways. A number of proteins potentially associated to these multimorbidity processes were also obtained. These results strongly support the existence of an allergic multimorbidity cluster between asthma, eczema and rhinitis, and suggest that type 2 signaling pathways represent a relevant multimorbidity mechanism of allergic diseases. Furthermore, we identified new candidates contributing to multimorbidity that may assist in identifying new targets for multimorbid allergic diseases.

Genetic overlap between type 2 diabetes and major depressive disorder identified by bioinformatics analysis.

PubMed

Ji, Hong-Fang; Zhuang, Qi-Shuai; Shen, Liang

2016-04-05

Our study investigated the shared genetic etiology underlying type 2 diabetes (T2D) and major depressive disorder (MDD) by analyzing large-scale genome wide association studies statistics. A total of 496 shared SNPs associated with both T2D and MDD were identified at p-value ≤ 1.0E-07. Functional enrichment analysis showed that the enriched pathways pertained to immune responses (Fc gamma R-mediated phagocytosis, T cell and B cell receptors signaling), cell signaling (MAPK, Wnt signaling), lipid metabolism, and cancer associated pathways. The findings will have potential implications for future interventional studies of the two diseases.

Patterns and determinants of pathways to reach comprehensive emergency obstetric and neonatal care (CEmONC) in South Sudan: qualitative diagrammatic pathway analysis.

PubMed

Elmusharaf, Khalifa; Byrne, Elaine; AbuAgla, Ayat; AbdelRahim, Amal; Manandhar, Mary; Sondorp, Egbert; O'Donovan, Diarmuid

2017-08-29

Maternity referral systems have been under-documented, under-researched, and under-theorised. Responsive emergency referral systems and appropriate transportation are cornerstones in the continuum of care and central to the complex health system. The pathways that women follow to reach Emergency Obstetric and Neonatal Care (EmONC) once a decision has been made to seek care have received relatively little attention. The aim of this research was to identify patterns and determinants of the pathways pregnant women follow from the onset of labour or complications until they reach an appropriate health facility. This study was conducted in Renk County in South Sudan between 2010 and 2012. Data was collected using Critical Incident Technique (CIT) and stakeholder interviews. CIT systematically identified pathways to healthcare during labour, and factors associated with an event of maternal mortality or near miss through a series of in-depth interviews with witnesses or those involved. Face-to-face stakeholder interviews were conducted with 28 purposively identified key informants. Diagrammatic pathway and thematic analysis were conducted using NVIVO 10 software. Once the decision is made to seek emergency obstetric care, the pregnant woman may face a series of complex steps before she reaches an appropriate health facility. Four pathway patterns to CEmONC were identified of which three were associated with high rates of maternal death: late referral, zigzagging referral, and multiple referrals. Women who bypassed nonfunctional Basic EmONC facilities and went directly to CEmONC facilities (the fourth pathway pattern) were most likely to survive. Overall, the competencies of the providers and the functionality of the first point of service determine the pathway to further care. Our findings indicate that outcomes are better where there is no facility available than when the woman accesses a non-functioning facility, and the absence of a healthcare provider is better than the presence of a non-competent provider. Visiting non-functioning or partially functioning healthcare facilities on the way to competent providers places the woman at greater risk of dying. Non-functioning facilities and non-competent providers are likely to contribute to the deaths of women.

The low-abundance transcriptome reveals novel biomarkers, specific intracellular pathways and targetable genes associated with advanced gastric cancer.

PubMed

Bizama, Carolina; Benavente, Felipe; Salvatierra, Edgardo; Gutiérrez-Moraga, Ana; Espinoza, Jaime A; Fernández, Elmer A; Roa, Iván; Mazzolini, Guillermo; Sagredo, Eduardo A; Gidekel, Manuel; Podhajcer, Osvaldo L

2014-02-15

Studies on the low-abundance transcriptome are of paramount importance for identifying the intimate mechanisms of tumor progression that can lead to novel therapies. The aim of the present study was to identify novel markers and targetable genes and pathways in advanced human gastric cancer through analyses of the low-abundance transcriptome. The procedure involved an initial subtractive hybridization step, followed by global gene expression analysis using microarrays. We observed profound differences, both at the single gene and gene ontology levels, between the low-abundance transcriptome and the whole transcriptome. Analysis of the low-abundance transcriptome led to the identification and validation by tissue microarrays of novel biomarkers, such as LAMA3 and TTN; moreover, we identified cancer type-specific intracellular pathways and targetable genes, such as IRS2, IL17, IFNγ, VEGF-C, WISP1, FZD5 and CTBP1 that were not detectable by whole transcriptome analyses. We also demonstrated that knocking down the expression of CTBP1 sensitized gastric cancer cells to mainstay chemotherapeutic drugs. We conclude that the analysis of the low-abundance transcriptome provides useful insights into the molecular basis and treatment of cancer. © 2013 UICC.

Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics.

PubMed

Sridharan, Gautham Vivek; Bruinsma, Bote Gosse; Bale, Shyam Sundhar; Swaminathan, Anandh; Saeidi, Nima; Yarmush, Martin L; Uygun, Korkut

2017-11-13

Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses.

Gene expression profiling in whole blood of patients with coronary artery disease

PubMed Central

Taurino, Chiara; Miller, William H.; McBride, Martin W.; McClure, John D.; Khanin, Raya; Moreno, María U.; Dymott, Jane A.; Delles, Christian; Dominiczak, Anna F.

2010-01-01

Owing to the dynamic nature of the transcriptome, gene expression profiling is a promising tool for discovery of disease-related genes and biological pathways. In the present study, we examined gene expression in whole blood of 12 patients with CAD (coronary artery disease) and 12 healthy control subjects. Furthermore, ten patients with CAD underwent whole-blood gene expression analysis before and after the completion of a cardiac rehabilitation programme following surgical coronary revascularization. mRNA and miRNA (microRNA) were isolated for expression profiling. Gene expression analysis identified 365 differentially expressed genes in patients with CAD compared with healthy controls (175 up- and 190 down-regulated in CAD), and 645 in CAD rehabilitation patients (196 up- and 449 down-regulated post-rehabilitation). Biological pathway analysis identified a number of canonical pathways, including oxidative phosphorylation and mitochondrial function, as being significantly and consistently modulated across the groups. Analysis of miRNA expression revealed a number of differentially expressed miRNAs, including hsa-miR-140-3p (control compared with CAD, P=0.017), hsa-miR-182 (control compared with CAD, P=0.093), hsa-miR-92a and hsa-miR-92b (post- compared with pre-exercise, P<0.01). Global analysis of predicted miRNA targets found significantly reduced expression of genes with target regions compared with those without: hsa-miR-140-3p (P=0.002), hsa-miR-182 (P=0.001), hsa-miR-92a and hsa-miR-92b (P=2.2×10−16). In conclusion, using whole blood as a ‘surrogate tissue’ in patients with CAD, we have identified differentially expressed miRNAs, differentially regulated genes and modulated pathways which warrant further investigation in the setting of cardiovascular function. This approach may represent a novel non-invasive strategy to unravel potentially modifiable pathways and possible therapeutic targets in cardiovascular disease. PMID:20528768

Identification and functional analysis of risk-related microRNAs for the prognosis of patients with bladder urothelial carcinoma.

PubMed

Gao, Ji; Li, Hongyan; Liu, Lei; Song, Lide; Lv, Yanting; Han, Yuping

2017-12-01

The aim of the present study was to investigate risk-related microRNAs (miRs) for bladder urothelial carcinoma (BUC) prognosis. Clinical and microRNA expression data downloaded from the Cancer Genome Atlas were utilized for survival analysis. Risk factor estimation was performed using Cox's proportional regression analysis. A microRNA-regulated target gene network was constructed and presented using Cytoscape. In addition, the Database for Annotation, Visualization and Integrated Discovery was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment, followed by protein-protein interaction (PPI) network analysis. Finally, the K-clique method was applied to analyze sub-pathways. A total of 16 significant microRNAs, including hsa-miR-3622a and hsa-miR-29a, were identified (P<0.05). Following Cox's proportional regression analysis, hsa-miR-29a was screened as a prognostic marker of BUC risk (P=0.0449). A regulation network of hsa-miR-29a comprising 417 target genes was constructed. These target genes were primarily enriched in GO terms, including collagen fibril organization, extracellular matrix (ECM) organization and pathways, such as focal adhesion (P<0.05). A PPI network including 197 genes and 510 interactions, was constructed. The top 21 genes in the network module were enriched in GO terms, including collagen fibril organization and pathways, such as ECM receptor interaction (P<0.05). Finally, 4 sub-pathways of cysteine and methionine metabolism, including paths 00270_4, 00270_1, 00270_2 and 00270_5, were obtained (P<0.01) and identified to be enriched through DNA (cytosine-5)-methyltransferase ( DNMT)3A, DNMT3B , methionine adenosyltransferase 2α ( MAT2A ) and spermine synthase ( SMS ). The identified microRNAs, particularly hsa-miR-29a and its 4 associated target genes DNMT3A, DNMT3B, MAT2A and SMS , may participate in the prognostic risk mechanism of BUC.

Transcriptome profiling to identify ATRA-responsive genes in human iPSC-derived endoderm for high-throughput point of departure analysis (SOT Annual Meeting)

EPA Science Inventory

Toxicological tipping points occur at chemical concentrations that overwhelm a cell’s adaptive response leading to permanent effects. We focused on retinoid signaling in differentiating endoderm to identify developmental pathways for tipping point analysis. Human induced pluripot...

Microarray RNA expression analysis of cerebral white matter lesions reveals changes in multiple functional pathways.

PubMed

Simpson, Julie E; Hosny, Ola; Wharton, Stephen B; Heath, Paul R; Holden, Hazel; Fernando, Malee S; Matthews, Fiona; Forster, Gill; O'Brien, John T; Barber, Robert; Kalaria, Raj N; Brayne, Carol; Shaw, Pamela J; Lewis, Claire E; Ince, Paul G

2009-02-01

White matter lesions (WML) in brain aging are linked to dementia and depression. Ischemia contributes to their pathogenesis but other mechanisms may contribute. We used RNA microarray analysis with functional pathway grouping as an unbiased approach to investigate evidence for additional pathogenetic mechanisms. WML were identified by MRI and pathology in brains donated to the Medical Research Council Cognitive Function and Ageing Study Cognitive Function and Aging Study. RNA was extracted to compare WML with nonlesional white matter samples from cases with lesions (WM[L]), and from cases with no lesions (WM[C]) using RNA microarray and pathway analysis. Functional pathways were validated for selected genes by quantitative real-time polymerase chain reaction and immunocytochemistry. We identified 8 major pathways in which multiple genes showed altered RNA transcription (immune regulation, cell cycle, apoptosis, proteolysis, ion transport, cell structure, electron transport, metabolism) among 502 genes that were differentially expressed in WML compared to WM[C]. In WM[L], 409 genes were altered involving the same pathways. Genes selected to validate this microarray data all showed the expected changes in RNA levels and immunohistochemical expression of protein. WML represent areas with a complex molecular phenotype. From this and previous evidence, WML may arise through tissue ischemia but may also reflect the contribution of additional factors like blood-brain barrier dysfunction. Differential expression of genes in WM[L] compared to WM[C] indicate a "field effect" in the seemingly normal surrounding white matter.

Identification of novel biomarker and therapeutic target candidates for acute intracerebral hemorrhage by quantitative plasma proteomics.

PubMed

Li, Guo-Chun; Zhang, Lina; Yu, Ming; Jia, Haiyu; Tian, Ting; Wang, Junqin; Wang, Fuqiang; Zhou, Ling

2017-01-01

The systematic mechanisms of acute intracerebral hemorrhage are still unknown and unverified, although many recent researches have indicated the secondary insults. This study was aimed to disclose the pathological mechanism and identify novel biomarker and therapeutic target candidates by plasma proteome. Patients with AICH (n = 8) who demographically matched healthy controls (n = 4) were prospectively enrolled, and their plasma samples were obtained. The TMT-LC-MS/MS-based proteomics approach was used to quantify the differential proteome across plasma samples, and the results were analyzed by Ingenuity Pathway Analysis to explore canonical pathways and the relationship involved in the uploaded data. Compared with healthy controls, there were 31 differentially expressed proteins in the ICH group ( P  < 0.05), of which 21 proteins increased while 10 proteins decreased in abundance. These proteins are involved in 21 canonical pathways. One network with high confidence level was selected by the function network analysis, in which 23 proteins, P38MAPK and NFκB signaling pathways participated. Upstream regulator analysis found two regulators, IL6 and TNF, with an activation z -score. Seven biomarker candidates: APCS, FGB, LBP, MGMT, IGFBP2, LYZ, and APOA4 were found. Six candidate proteins were selected to assess the validity of the results by subsequent Western blotting analysis. Our analysis provided several intriguing pathways involved in ICH, like LXR/RXR activation, acute phase response signaling, and production of NO and ROS in macrophages pathways. The three upstream regulators: IL-6, TNF, LPS, and seven biomarker candidates: APCS, APOA4, FGB, IGFBP2, LBP, LYZ, and MGMT were uncovered. LPS, APOA4, IGFBP2, LBP, LYZ, and MGMT are novel potential biomarkers in ICH development. The identified proteins and pathways provide new perspectives to the potential pathological mechanism and therapeutic targets underlying ICH.

Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

PubMed

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-03-09

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

Pathway-Based Factor Analysis of Gene Expression Data Produces Highly Heritable Phenotypes That Associate with Age

PubMed Central

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-01-01

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 “pathway phenotypes” that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold (P<5.38×10−5). These phenotypes are more heritable (h2=0.32) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. PMID:25758824

Characterization of Steroid Receptor RNA Activator Protein Function in Modulating the Estrogen Signaling Pathway

DTIC Science & Technology

2007-05-01

Signaling Pathway 5b. GRANT NUMBER W81XWH-05-1-0245 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Yi Yan 5e. TASK NUMBER...negative control to identify proteins non-specifically precipitated. Tandem mass spectrometric analysis of immunoprecipitated samples identified a...immunoprecipitated sample and negative control. It is important to note that, SRAP was present among the remaining specifically precipitated 87 proteins. Using the

Analysis of Geothermal Pathway in the Metamorphic Area, Northeastern Taiwan

NASA Astrophysics Data System (ADS)

Wang, C.; Wu, M. Y.; Song, S. R.; Lo, W.

2016-12-01

A quantitative measure by play fairway analysis in geothermal energy development is an important tool that can present the probability map of potential resources through the uncertainty studies in geology for early phase decision making purpose in the related industries. While source, pathway, and fluid are the three main geologic factors in traditional geothermal systems, identifying the heat paths is critical to reduce drilling cost. Taiwan is in East Asia and the western edge of Pacific Ocean, locating on the convergent boundary of Eurasian Plate and Philippine Sea Plate with many earthquake activities. This study chooses a metamorphic area in the western corner of Yi-Lan plain in northeastern Taiwan with high geothermal potential and several existing exploration sites. Having high subsurface temperature gradient from the mountain belts, and plenty hydrologic systems through thousands of millimeters annual precipitation that would bring up heats closer to the surface, current geothermal conceptual model indicates the importance of pathway distribution which affects the possible concentration of extractable heat location. The study conducts surface lineation analysis using analytic hierarchy process to determine weights among various fracture types for their roles in geothermal pathways, based on the information of remote sensing data, published geologic maps and field work measurements, to produce regional fracture distribution probability map. The results display how the spatial distribution of pathways through various fractures could affect geothermal systems, identify the geothermal plays using statistical data analysis, and compare against the existing drilling data.

Transcriptomic basis for drought-resistance in Brassica napus L.

NASA Astrophysics Data System (ADS)

Wang, Pei; Yang, Cuiling; Chen, Hao; Song, Chunpeng; Zhang, Xiao; Wang, Daojie

2017-01-01

Based on transcriptomic data from four experimental settings with drought-resistant and drought-sensitive cultivars under drought and well-watered conditions, statistical analysis revealed three categories encompassing 169 highly differentially expressed genes (DEGs) in response to drought in Brassica napus L., including 37 drought-resistant cultivar-related genes, 35 drought-sensitive cultivar-related genes and 97 cultivar non-specific ones. We provide evidence that the identified DEGs were fairly uniformly distributed on different chromosomes and their expression patterns are variety specific. Except commonly enriched in response to various stimuli or stresses, different categories of DEGs show specific enrichment in certain biological processes or pathways, which indicated the possibility of functional differences among the three categories. Network analysis revealed relationships among the 169 DEGs, annotated biological processes and pathways. The 169 DEGs can be classified into different functional categories via preferred pathways or biological processes. Some pathways might simultaneously involve a large number of shared DEGs, and these pathways are likely to cross-talk and have overlapping biological functions. Several members of the identified DEGs fit to drought stress signal transduction pathway in Arabidopsis thaliana. Finally, quantitative real-time PCR validations confirmed the reproducibility of the RNA-seq data. These investigations are profitable for the improvement of crop varieties through transgenic engineering.

Exploratory Application of Neuropharmacometabolomics in Severe Childhood Traumatic Brain Injury.

PubMed

Hagos, Fanuel T; Empey, Philip E; Wang, Pengcheng; Ma, Xiaochao; Poloyac, Samuel M; Bayır, Hülya; Kochanek, Patrick M; Bell, Michael J; Clark, Robert S B

2018-05-07

To employ metabolomics-based pathway and network analyses to evaluate the cerebrospinal fluid metabolome after severe traumatic brain injury in children and the capacity of combination therapy with probenecid and N-acetylcysteine to impact glutathione-related and other pathways and networks, relative to placebo treatment. Analysis of cerebrospinal fluid obtained from children enrolled in an Institutional Review Board-approved, randomized, placebo-controlled trial of a combination of probenecid and N-acetylcysteine after severe traumatic brain injury (Trial Registration NCT01322009). Thirty-six-bed PICU in a university-affiliated children's hospital. Twelve children 2-18 years old after severe traumatic brain injury and five age-matched control subjects. Probenecid (25 mg/kg) and N-acetylcysteine (140 mg/kg) or placebo administered via naso/orogastric tube. The cerebrospinal fluid metabolome was analyzed in samples from traumatic brain injury patients 24 hours after the first dose of drugs or placebo and control subjects. Feature detection, retention time, alignment, annotation, and principal component analysis and statistical analysis were conducted using XCMS-online. The software "mummichog" was used for pathway and network analyses. A two-component principal component analysis revealed clustering of each of the groups, with distinct metabolomics signatures. Several novel pathways with plausible mechanistic involvement in traumatic brain injury were identified. A combination of metabolomics and pathway/network analyses showed that seven glutathione-centered pathways and two networks were enriched in the cerebrospinal fluid of traumatic brain injury patients treated with probenecid and N-acetylcysteine versus placebo-treated patients. Several additional pathways/networks consisting of components that are known substrates of probenecid-inhibitable transporters were also identified, providing additional mechanistic validation. This proof-of-concept neuropharmacometabolomics assessment reveals alterations in known and previously unidentified metabolic pathways and supports therapeutic target engagement of the combination of probenecid and N-acetylcysteine treatment after severe traumatic brain injury in children.

A Sleeping Beauty forward genetic screen identifies new genes and pathways driving osteosarcoma development and metastasis

PubMed Central

Moriarity, Branden S; Otto, George M; Rahrmann, Eric P; Rathe, Susan K; Wolf, Natalie K; Weg, Madison T; Manlove, Luke A; LaRue, Rebecca S; Temiz, Nuri A; Molyneux, Sam D; Choi, Kwangmin; Holly, Kevin J; Sarver, Aaron L; Scott, Milcah C; Forster, Colleen L; Modiano, Jaime F; Khanna, Chand; Hewitt, Stephen M; Khokha, Rama; Yang, Yi; Gorlick, Richard; Dyer, Michael A; Largaespada, David A

2016-01-01

Osteosarcomas are sarcomas of the bone, derived from osteoblasts or their precursors, with a high propensity to metastasize. Osteosarcoma is associated with massive genomic instability, making it problematic to identify driver genes using human tumors or prototypical mouse models, many of which involve loss of Trp53 function. To identify the genes driving osteosarcoma development and metastasis, we performed a Sleeping Beauty (SB) transposon-based forward genetic screen in mice with and without somatic loss of Trp53. Common insertion site (CIS) analysis of 119 primary tumors and 134 metastatic nodules identified 232 sites associated with osteosarcoma development and 43 sites associated with metastasis, respectively. Analysis of CIS-associated genes identified numerous known and new osteosarcoma-associated genes enriched in the ErbB, PI3K-AKT-mTOR and MAPK signaling pathways. Lastly, we identified several oncogenes involved in axon guidance, including Sema4d and Sema6d, which we functionally validated as oncogenes in human osteosarcoma. PMID:25961939

Examining the Genetic Background of Porcine Muscle Growth and Development Based on Transcriptome and miRNAome Data.

PubMed

Ropka-Molik, Katarzyna; Pawlina-Tyszko, Klaudia; Żukowski, Kacper; Piórkowska, Katarzyna; Żak, Grzegorz; Gurgul, Artur; Derebecka, Natalia; Wesoły, Joanna

2018-04-16

Recently, selection in pigs has been focused on improving the lean meat content in carcasses; this focus has been most evident in breeds constituting a paternal component in breeding. Such sire-breeds are used to improve the meat quantity of cross-breed pig lines. However, even in one breed, a significant variation in the meatiness level can be observed. In the present study, the comprehensive analysis of genes and microRNA expression profiles in porcine muscle tissue was applied to identify the genetic background of meat content. The comparison was performed between whole gene expression and miRNA profiles of muscle tissue collected from two sire-line pig breeds (Pietrain, Hampshire). The RNA-seq approach allowed the identification of 627 and 416 differentially expressed genes (DEGs) between pig groups differing in terms of loin weight between Pietrain and Hampshire breeds, respectively. The comparison of miRNA profiles showed differential expression of 57 microRNAs for Hampshire and 34 miRNAs for Pietrain pigs. Next, 43 genes and 18 miRNAs were selected as differentially expressed in both breeds and potentially related to muscle development. According to Gene Ontology analysis, identified DEGs and microRNAs were involved in the regulation of the cell cycle, fatty acid biosynthesis and regulation of the actin cytoskeleton. The most deregulated pathways dependent on muscle mass were the Hippo signalling pathway connected with the TGF-β signalling pathway and controlling organ size via the regulation of ubiquitin-mediated proteolysis, cell proliferation and apoptosis. The identified target genes were also involved in pathways such as the FoxO signalling pathway, signalling pathways regulating pluripotency of stem cells and the PI3K-Akt signalling pathway. The obtained results indicate molecular mechanisms controlling porcine muscle growth and development. Identified genes ( SOX2 , SIRT1 , KLF4 , PAX6 and genes belonging to the transforming growth factor beta superfamily) could be considered candidate genes for determining muscle mass in pigs.

In silico pathway analysis in cervical carcinoma reveals potential new targets for treatment

PubMed Central

van Dam, Peter A.; van Dam, Pieter-Jan H. H.; Rolfo, Christian; Giallombardo, Marco; van Berckelaer, Christophe; Trinh, Xuan Bich; Altintas, Sevilay; Huizing, Manon; Papadimitriou, Kostas; Tjalma, Wiebren A. A.; van Laere, Steven

2016-01-01

An in silico pathway analysis was performed in order to improve current knowledge on the molecular drivers of cervical cancer and detect potential targets for treatment. Three publicly available Affymetrix gene expression data-sets (GSE5787, GSE7803, GSE9750) were retrieved, vouching for a total of 9 cervical cancer cell lines (CCCLs), 39 normal cervical samples, 7 CIN3 samples and 111 cervical cancer samples (CCSs). Predication analysis of microarrays was performed in the Affymetrix sets to identify cervical cancer biomarkers. To select cancer cell-specific genes the CCSs were compared to the CCCLs. Validated genes were submitted to a gene set enrichment analysis (GSEA) and Expression2Kinases (E2K). In the CCSs a total of 1,547 probe sets were identified that were overexpressed (FDR < 0.1). Comparing to CCCLs 560 probe sets (481 unique genes) had a cancer cell-specific expression profile, and 315 of these genes (65%) were validated. GSEA identified 5 cancer hallmarks enriched in CCSs (P < 0.01 and FDR < 0.25) showing that deregulation of the cell cycle is a major component of cervical cancer biology. E2K identified a protein-protein interaction (PPI) network of 162 nodes (including 20 drugable kinases) and 1626 edges. This PPI-network consists of 5 signaling modules associated with MYC signaling (Module 1), cell cycle deregulation (Module 2), TGFβ-signaling (Module 3), MAPK signaling (Module 4) and chromatin modeling (Module 5). Potential targets for treatment which could be identified were CDK1, CDK2, ABL1, ATM, AKT1, MAPK1, MAPK3 among others. The present study identified important driver pathways in cervical carcinogenesis which should be assessed for their potential therapeutic drugability. PMID:26701206

Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2014-01-01

Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. This study illustrates that we can improve detection power and discovery consistency through a concordant integrative analysis of multiple large-scale two-sample gene expression data sets.

Unraveling novel broad-spectrum antibacterial targets in food and waterborne pathogens using comparative genomics and protein interaction network analysis.

PubMed

Jadhav, Ankush; Shanmugham, Buvaneswari; Rajendiran, Anjana; Pan, Archana

2014-10-01

Food and waterborne diseases are a growing concern in terms of human morbidity and mortality worldwide, even in the 21st century, emphasizing the need for new therapeutic interventions for these diseases. The current study aims at prioritizing broad-spectrum antibacterial targets, present in multiple food and waterborne bacterial pathogens, through a comparative genomics strategy coupled with a protein interaction network analysis. The pathways unique and common to all the pathogens under study (viz., methane metabolism, d-alanine metabolism, peptidoglycan biosynthesis, bacterial secretion system, two-component system, C5-branched dibasic acid metabolism), identified by comparative metabolic pathway analysis, were considered for the analysis. The proteins/enzymes involved in these pathways were prioritized following host non-homology analysis, essentiality analysis, gut flora non-homology analysis and protein interaction network analysis. The analyses revealed a set of promising broad-spectrum antibacterial targets, present in multiple food and waterborne pathogens, which are essential for bacterial survival, non-homologous to host and gut flora, and functionally important in the metabolic network. The identified broad-spectrum candidates, namely, integral membrane protein/virulence factor (MviN), preprotein translocase subunits SecB and SecG, carbon storage regulator (CsrA), and nitrogen regulatory protein P-II 1 (GlnB), contributed by the peptidoglycan pathway, bacterial secretion systems and two-component systems, were also found to be present in a wide range of other disease-causing bacteria. Cytoplasmic proteins SecG, CsrA and GlnB were considered as drug targets, while membrane proteins MviN and SecB were classified as vaccine targets. The identified broad-spectrum targets can aid in the design and development of antibacterial agents not only against food and waterborne pathogens but also against other pathogens. Copyright © 2014 Elsevier B.V. All rights reserved.

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment

PubMed Central

Uddin, Raihan; Singh, Shiva M.

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in “learning and memory” related functions and pathways. Subsequent differential network analysis of this “learning and memory” module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they provide a new insight and generate new hypotheses into the molecular mechanisms responsible for age associated learning impairment, including spatial learning. PMID:29066959

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

PubMed

Uddin, Raihan; Singh, Shiva M

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they provide a new insight and generate new hypotheses into the molecular mechanisms responsible for age associated learning impairment, including spatial learning.

Genome-Wide Identification and Analysis of Biotic and Abiotic Stress Regulation of C4 Photosynthetic Pathway Genes in Rice.

PubMed

Muthusamy, Senthilkumar K; Lenka, Sangram K; Katiyar, Amit; Chinnusamy, Viswanathan; Singh, Ashok K; Bansal, Kailash C

2018-06-19

Photosynthetic fixation of CO 2 is more efficient in C 4 than in C 3 plants. Rice is a C 3 plant and a potential target for genetic engineering of the C 4 pathway. It is known that genes encoding C 4 enzymes are present in C 3 plants. However, no systematic analysis has been conducted to determine if these C 4 gene family members are expressed in diverse rice genotypes. In this study, we identified 15 genes belonging to the five C 4 gene families in rice genome through BLAST search using known maize C 4 photosynthetic pathway genes. Phylogenetic relationship of rice C 4 photosynthetic pathway genes and their isoforms with other grass genomes (Brachypodium, maize, Sorghum and Setaria), showed that these genes were highly conserved across grass genomes. Spatiotemporal, hormone, and abiotic stress specific expression pattern of the identified genes revealed constitutive as well as inductive responses of the C 4 photosynthetic pathway in different tissues and developmental stages of rice. Expression levels of C 4 specific gene family members in flag leaf during tillering stage were quantitatively analyzed in five rice genotypes covering three species, viz. Oryza sativa, ssp. japonica (cv. Nipponbare), Oryza sativa, ssp. indica (cv IR64, Swarna), and two wild species Oryza barthii and Oryza australiensis. The results showed that all the identified genes expressed in rice and exhibited differential expression pattern during different growth stages, and in response to biotic and abiotic stress conditions and hormone treatments. Our study concludes that C 4 photosynthetic pathway genes present in rice play a crucial role in stress regulation and might act as targets for C 4 pathway engineering via CRISPR-mediated breeding.

Revealing the Bacterial Butyrate Synthesis Pathways by Analyzing (Meta)genomic Data

PubMed Central

Vital, Marius; Howe, Adina Chuang

2014-01-01

ABSTRACT Butyrate-producing bacteria have recently gained attention, since they are important for a healthy colon and when altered contribute to emerging diseases, such as ulcerative colitis and type II diabetes. This guild is polyphyletic and cannot be accurately detected by 16S rRNA gene sequencing. Consequently, approaches targeting the terminal genes of the main butyrate-producing pathway have been developed. However, since additional pathways exist and alternative, newly recognized enzymes catalyzing the terminal reaction have been described, previous investigations are often incomplete. We undertook a broad analysis of butyrate-producing pathways and individual genes by screening 3,184 sequenced bacterial genomes from the Integrated Microbial Genome database. Genomes of 225 bacteria with a potential to produce butyrate were identified, including many previously unknown candidates. The majority of candidates belong to distinct families within the Firmicutes, but members of nine other phyla, especially from Actinobacteria, Bacteroidetes, Fusobacteria, Proteobacteria, Spirochaetes, and Thermotogae, were also identified as potential butyrate producers. The established gene catalogue (3,055 entries) was used to screen for butyrate synthesis pathways in 15 metagenomes derived from stool samples of healthy individuals provided by the HMP (Human Microbiome Project) consortium. A high percentage of total genomes exhibited a butyrate-producing pathway (mean, 19.1%; range, 3.2% to 39.4%), where the acetyl-coenzyme A (CoA) pathway was the most prevalent (mean, 79.7% of all pathways), followed by the lysine pathway (mean, 11.2%). Diversity analysis for the acetyl-CoA pathway showed that the same few firmicute groups associated with several Lachnospiraceae and Ruminococcaceae were dominating in most individuals, whereas the other pathways were associated primarily with Bacteroidetes. PMID:24757212

Deciphering the biological effects of acupuncture treatment modulating multiple metabolism pathways.

PubMed

Zhang, Aihua; Yan, Guangli; Sun, Hui; Cheng, Weiping; Meng, Xiangcai; Liu, Li; Xie, Ning; Wang, Xijun

2016-02-16

Acupuncture is an alternative therapy that is widely used to treat various diseases. However, detailed biological interpretation of the acupuncture stimulations is limited. We here used metabolomics and proteomics technology, thereby identifying the serum small molecular metabolites into the effect and mechanism pathways of standardized acupuncture treatments at 'Zusanli' acupoint which was the most often used acupoint in previous reports. Comprehensive overview of serum metabolic profiles during acupuncture stimulation was investigated. Thirty-four differential metabolites were identified in serum metabolome and associated with ten metabolism pathways. Importantly, we have found that high impact glycerophospholipid metabolism, fatty acid metabolism, ether lipid metabolism were acutely perturbed by acupuncture stimulation. As such, these alterations may be useful to clarify the biological mechanism of acupuncture stimulation. A series of differentially expressed proteins were identified and such effects of acupuncture stimulation were found to play a role in transport, enzymatic activity, signaling pathway or receptor interaction. Pathway analysis further revealed that most of these proteins were found to play a pivotal role in the regulation of multiple metabolism pathways. It demonstrated that the metabolomics coupled with proteomics as a powerful approach for potential applications in understanding the biological effects of acupuncture stimulation.

Path lumping: An efficient algorithm to identify metastable path channels for conformational dynamics of multi-body systems

NASA Astrophysics Data System (ADS)

Meng, Luming; Sheong, Fu Kit; Zeng, Xiangze; Zhu, Lizhe; Huang, Xuhui

2017-07-01

Constructing Markov state models from large-scale molecular dynamics simulation trajectories is a promising approach to dissect the kinetic mechanisms of complex chemical and biological processes. Combined with transition path theory, Markov state models can be applied to identify all pathways connecting any conformational states of interest. However, the identified pathways can be too complex to comprehend, especially for multi-body processes where numerous parallel pathways with comparable flux probability often coexist. Here, we have developed a path lumping method to group these parallel pathways into metastable path channels for analysis. We define the similarity between two pathways as the intercrossing flux between them and then apply the spectral clustering algorithm to lump these pathways into groups. We demonstrate the power of our method by applying it to two systems: a 2D-potential consisting of four metastable energy channels and the hydrophobic collapse process of two hydrophobic molecules. In both cases, our algorithm successfully reveals the metastable path channels. We expect this path lumping algorithm to be a promising tool for revealing unprecedented insights into the kinetic mechanisms of complex multi-body processes.

Quantitative proteomics identifies 38 proteins that are differentially expressed in cucumber in response to cucumber green mottle mosaic virus infection.

PubMed

Liu, Hua-Wei; Liang, Chao-Qiong; Liu, Peng-Fei; Luo, Lai-Xin; Li, Jian-Qiang

2015-12-15

Since it was first reported in 1935, Cucumber green mottle mosaic virus (CGMMV) has become a serious pathogen in a range of cucurbit crops. The virus is generally transmitted by propagation materials, and to date no effective chemical or cultural methods of control have been developed to combat its spread. The current study presents a preliminary analysis of the pathogenic mechanisms from the perspective of protein expression levels in an infected cucumber host, with the objective of elucidating the infection process and potential strategies to reduce both the economic and yield losses associated with CGMMV. Isobaric tags for relative and absolute quantitation (iTRAQ) technology coupled with liquid chromatography-tandem mass spectrometric (LC-MS/MS) were used to identify the differentially expressed proteins in cucumber plants infected with CGMMV compared with mock-inoculated plants. The functions of the proteins were deduced by functional annotation and their involvement in metabolic processes explored by KEGG pathway analysis to identify their interactions during CGMMV infection, while their in vivo expression was further verified by qPCR. Infection by CGMMV altered both the expression level and absolute quantity of 38 proteins (fold change >0.6) in cucumber hosts. Of these, 23 were found to be up-regulated, while 15 were down-regulated. Gene ontology (GO) analysis revealed that 22 of the proteins had a combined function and were associated with molecular function (MF), biological process (BP) and cellular component (CC). Several other proteins had a dual function with 1, 7, and 2 proteins being associated with BP/CC, BP/MF, CC/MF, respectively. The remaining 3 proteins were only involved in MF. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified 18 proteins that were involved in 13 separate metabolic pathways. These pathways were subsequently merged to generate three network diagrams illustrating the interactions between the different pathways, while qPCR was used to track the changes in expression levels of the proteins identified at 3 time points during CGMMV infection. Taken together these results greatly expand our understanding of the relationships between CGMMV and cucumber hosts. The results of the study indicate that CGMMV infection significantly changes the physiology of cucumbers, affecting the expression levels of individual proteins as well as entire metabolic pathways. The bioinformatic analysis also identified several pathogenesis-related (PR) proteins that could be useful in the development of disease-resistant plants.

Revealing common disease mechanisms shared by tumors of different tissues of origin through semantic representation of genomic alterations and topic modeling.

PubMed

Chen, Vicky; Paisley, John; Lu, Xinghua

2017-03-14

Cancer is a complex disease driven by somatic genomic alterations (SGAs) that perturb signaling pathways and consequently cellular function. Identifying patterns of pathway perturbations would provide insights into common disease mechanisms shared among tumors, which is important for guiding treatment and predicting outcome. However, identifying perturbed pathways is challenging, because different tumors can have the same perturbed pathways that are perturbed by different SGAs. Here, we designed novel semantic representations that capture the functional similarity of distinct SGAs perturbing a common pathway in different tumors. Combining this representation with topic modeling would allow us to identify patterns in altered signaling pathways. We represented each gene with a vector of words describing its function, and we represented the SGAs of a tumor as a text document by pooling the words representing individual SGAs. We applied the nested hierarchical Dirichlet process (nHDP) model to a collection of tumors of 5 cancer types from TCGA. We identified topics (consisting of co-occurring words) representing the common functional themes of different SGAs. Tumors were clustered based on their topic associations, such that each cluster consists of tumors sharing common functional themes. The resulting clusters contained mixtures of cancer types, which indicates that different cancer types can share disease mechanisms. Survival analysis based on the clusters revealed significant differences in survival among the tumors of the same cancer type that were assigned to different clusters. The results indicate that applying topic modeling to semantic representations of tumors identifies patterns in the combinations of altered functional pathways in cancer.

Small RNA-Seq analysis reveals microRNA-regulation of the Imd pathway during Escherichia coli infection in Drosophila.

PubMed

Li, Shengjie; Shen, Li; Sun, Lianjie; Xu, Jiao; Jin, Ping; Chen, Liming; Ma, Fei

2017-05-01

Drosophila have served as a model for research on innate immunity for decades. However, knowledge of the post-transcriptional regulation of immune gene expression by microRNAs (miRNAs) remains rudimentary. In the present study, using small RNA-seq and bioinformatics analysis, we identified 67 differentially expressed miRNAs in Drosophila infected with Escherichia coli compared to injured flies at three time-points. Furthermore, we found that 21 of these miRNAs were potentially involved in the regulation of Imd pathway-related genes. Strikingly, based on UAS-miRNAs line screening and Dual-luciferase assay, we identified that miR-9a and miR-981 could both negatively regulate Drosophila antibacterial defenses and decrease the level of the antibacterial peptide, Diptericin. Taken together, these data support the involvement of miRNAs in the regulation of the Drosophila Imd pathway. Copyright © 2017 Elsevier Ltd. All rights reserved.

A proteomics study of hyperhomocysteinemia injury of the hippocampal neurons using iTRAQ.

PubMed

Fang, Min; Wang, Jing; Yan, Han; Zhao, Yan-Xin; Liu, Xue-Yuan

2014-11-01

High levels of homocysteine, caused by abnormal methionine metabolism, can induce degeneration of mouse hippocampal neurons. iTRAQ™ technology has been widely used in the field of proteomics research and through employing this technology, the present study identified that hyperhomocysteinemia induced the downregulation of 52 proteins and upregulation of 44 proteins in the mouse hippocampus. Through gene ontology and pathway analysis, the upregulation of components of the cytoskeleton, actin, regulators of focal adhesion, calcium signaling pathways, tight junctions, ErbB and gonadotrophin‑releasing hormone signaling, leukocyte, transendothelial migration, propanoate and pyruvate metabolism, valine, leucine and isoleucine biosynthesis, synthesis and degradation of ketone bodies and benzoate degradation via CoA ligation pathway, was identified. It was additionally verified that tau protein was highly expressed in the hyperhomocysteinemic neurons. Further analysis revealed that tau network proteins played functional roles in homocysteine‑induced neuronal damage.

A human genome-wide loss-of-function screen identifies effective chikungunya antiviral drugs

PubMed Central

Karlas, Alexander; Berre, Stefano; Couderc, Thérèse; Varjak, Margus; Braun, Peter; Meyer, Michael; Gangneux, Nicolas; Karo-Astover, Liis; Weege, Friderike; Raftery, Martin; Schönrich, Günther; Klemm, Uwe; Wurzlbauer, Anne; Bracher, Franz; Merits, Andres; Meyer, Thomas F.; Lecuit, Marc

2016-01-01

Chikungunya virus (CHIKV) is a globally spreading alphavirus against which there is no commercially available vaccine or therapy. Here we use a genome-wide siRNA screen to identify 156 proviral and 41 antiviral host factors affecting CHIKV replication. We analyse the cellular pathways in which human proviral genes are involved and identify druggable targets. Twenty-one small-molecule inhibitors, some of which are FDA approved, targeting six proviral factors or pathways, have high antiviral activity in vitro, with low toxicity. Three identified inhibitors have prophylactic antiviral effects in mouse models of chikungunya infection. Two of them, the calmodulin inhibitor pimozide and the fatty acid synthesis inhibitor TOFA, have a therapeutic effect in vivo when combined. These results demonstrate the value of loss-of-function screening and pathway analysis for the rational identification of small molecules with therapeutic potential and pave the way for the development of new, host-directed, antiviral agents. PMID:27177310

A human genome-wide loss-of-function screen identifies effective chikungunya antiviral drugs.

PubMed

Karlas, Alexander; Berre, Stefano; Couderc, Thérèse; Varjak, Margus; Braun, Peter; Meyer, Michael; Gangneux, Nicolas; Karo-Astover, Liis; Weege, Friderike; Raftery, Martin; Schönrich, Günther; Klemm, Uwe; Wurzlbauer, Anne; Bracher, Franz; Merits, Andres; Meyer, Thomas F; Lecuit, Marc

2016-05-12

Chikungunya virus (CHIKV) is a globally spreading alphavirus against which there is no commercially available vaccine or therapy. Here we use a genome-wide siRNA screen to identify 156 proviral and 41 antiviral host factors affecting CHIKV replication. We analyse the cellular pathways in which human proviral genes are involved and identify druggable targets. Twenty-one small-molecule inhibitors, some of which are FDA approved, targeting six proviral factors or pathways, have high antiviral activity in vitro, with low toxicity. Three identified inhibitors have prophylactic antiviral effects in mouse models of chikungunya infection. Two of them, the calmodulin inhibitor pimozide and the fatty acid synthesis inhibitor TOFA, have a therapeutic effect in vivo when combined. These results demonstrate the value of loss-of-function screening and pathway analysis for the rational identification of small molecules with therapeutic potential and pave the way for the development of new, host-directed, antiviral agents.

Sterol Composition and Biosynthetic Genes of Vitrella brassicaformis, a Recently Discovered Chromerid: Comparison to Chromera velia and Phylogenetic Relationship with Apicomplexan Parasites.

PubMed

Khadka, Manoj; Salem, Mohamed; Leblond, Jeffrey D

2015-01-01

Vitrella brassicaformis is the second discovered species in the Chromerida, and first in the family Vitrellaceae. Chromera velia, the first discovered species, forms an independent photosynthetic lineage with V. brassicaformis, and both are closely related to peridinin-containing dinoflagellates and nonphotosynthetic apicomplexans; both also show phylogenetic closeness with red algal plastids. We have utilized gas chromatography/mass spectrometry to identify two free sterols, 24-ethylcholest-5-en-3β-ol, and a minor unknown sterol which appeared to be a C(28:4) compound. We have also used RNA Seq analysis to identify seven genes found in the nonmevalonate/methylerythritol pathway (MEP) for sterol biosynthesis. Subsequent genome analysis of V. brassicaformis showed the presence of two mevalonate (MVA) pathway genes, though the genes were not observed in the transcriptome analysis. Transcripts from four genes (dxr, ispf, ispd, and idi) were selected and translated into proteins to study the phylogenetic relationship of sterol biosynthesis in V. brassicaformis and C. velia to other groups of algae and apicomplexans. On the basis of our genomic and transcriptomic analyses, we hypothesize that the MEP pathway was the primary pathway that apicomplexans used for sterol biosynthesis before they lost their sterol biosynthesis ability, although contribution of the MVA pathway cannot be discounted. © 2015 The Author(s) Journal of Eukaryotic Microbiology © 2015 International Society of Protistologists.

Prioritizing GWAS Results: A Review of Statistical Methods and Recommendations for Their Application

PubMed Central

Cantor, Rita M.; Lange, Kenneth; Sinsheimer, Janet S.

2010-01-01

Genome-wide association studies (GWAS) have rapidly become a standard method for disease gene discovery. A substantial number of recent GWAS indicate that for most disorders, only a few common variants are implicated and the associated SNPs explain only a small fraction of the genetic risk. This review is written from the viewpoint that findings from the GWAS provide preliminary genetic information that is available for additional analysis by statistical procedures that accumulate evidence, and that these secondary analyses are very likely to provide valuable information that will help prioritize the strongest constellations of results. We review and discuss three analytic methods to combine preliminary GWAS statistics to identify genes, alleles, and pathways for deeper investigations. Meta-analysis seeks to pool information from multiple GWAS to increase the chances of finding true positives among the false positives and provides a way to combine associations across GWAS, even when the original data are unavailable. Testing for epistasis within a single GWAS study can identify the stronger results that are revealed when genes interact. Pathway analysis of GWAS results is used to prioritize genes and pathways within a biological context. Following a GWAS, association results can be assigned to pathways and tested in aggregate with computational tools and pathway databases. Reviews of published methods with recommendations for their application are provided within the framework for each approach. PMID:20074509

Gene Expression Profiling of Gastric Cancer

PubMed Central

Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

2015-01-01

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis

PubMed Central

Yang, Fang; Wang, Yumei

2018-01-01

Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis. PMID:29805480

Genes and (Common) Pathways Underlying Drug Addiction

PubMed Central

Li, Chuan-Yun; Mao, Xizeng; Wei, Liping

2008-01-01

Drug addiction is a serious worldwide problem with strong genetic and environmental influences. Different technologies have revealed a variety of genes and pathways underlying addiction; however, each individual technology can be biased and incomplete. We integrated 2,343 items of evidence from peer-reviewed publications between 1976 and 2006 linking genes and chromosome regions to addiction by single-gene strategies, microrray, proteomics, or genetic studies. We identified 1,500 human addiction-related genes and developed KARG (http://karg.cbi.pku.edu.cn), the first molecular database for addiction-related genes with extensive annotations and a friendly Web interface. We then performed a meta-analysis of 396 genes that were supported by two or more independent items of evidence to identify 18 molecular pathways that were statistically significantly enriched, covering both upstream signaling events and downstream effects. Five molecular pathways significantly enriched for all four different types of addictive drugs were identified as common pathways which may underlie shared rewarding and addictive actions, including two new ones, GnRH signaling pathway and gap junction. We connected the common pathways into a hypothetical common molecular network for addiction. We observed that fast and slow positive feedback loops were interlinked through CAMKII, which may provide clues to explain some of the irreversible features of addiction. PMID:18179280

Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data.

PubMed

Li, Xiaomei; Dong, Weiwei; Qu, Xueling; Zhao, Huixia; Wang, Shuo; Hao, Yixin; Li, Qiuwen; Zhu, Jianhua; Ye, Min; Xiao, Wenhua

2017-05-01

Gastric cancer (GC) is often diagnosed in the advanced stages and is associated with a poor prognosis. Obtaining an in depth understanding of the molecular mechanisms of GC has lagged behind compared with other cancers. This study aimed to identify candidate biomarkers for GC. An integrated analysis of microarray datasets was performed to identify differentially expressed genes (DEGs) between GC and normal tissues. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then performed to identify the functions of the DEGs. Furthermore, a protein-protein interaction (PPI) network of the DEGs was constructed. The expression levels of the DEGs were validated in human GC tissues using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A set of 689 DEGs were identified in GC tissues, as compared with normal tissues, including 202 upregulated DEGs and 487 downregulated DEGs. The KEGG pathway analysis suggested that various pathways may play important roles in the pathology of GC, including pathways related to protein digestion and absorption, extracellular matrix-receptor interaction, and the metabolism of xenobiotics by cytochrome P450. The PPI network analysis indicated that the significant hub proteins consisted of SPP1, TOP2A and ARPC1B. RT-qPCR validation indicated that the expression levels of the top 10 most significantly dysexpressed genes were consistent with the illustration of the integrated analysis. The present study yielded a reference list of reliable DEGs, which represents a robust pool of candidates for further evaluation of GC pathogenesis and treatment.

The complex genetics of gait speed: genome-wide meta-analysis approach

PubMed Central

Lunetta, Kathryn L.; Smith, Jennifer A.; Eicher, John D.; Vered, Rotem; Deelen, Joris; Arnold, Alice M.; Buchman, Aron S.; Tanaka, Toshiko; Faul, Jessica D.; Nethander, Maria; Fornage, Myriam; Adams, Hieab H.; Matteini, Amy M.; Callisaya, Michele L.; Smith, Albert V.; Yu, Lei; De Jager, Philip L.; Evans, Denis A.; Gudnason, Vilmundur; Hofman, Albert; Pattie, Alison; Corley, Janie; Launer, Lenore J.; Knopman, Davis S.; Parimi, Neeta; Turner, Stephen T.; Bandinelli, Stefania; Beekman, Marian; Gutman, Danielle; Sharvit, Lital; Mooijaart, Simon P.; Liewald, David C.; Houwing-Duistermaat, Jeanine J.; Ohlsson, Claes; Moed, Matthijs; Verlinden, Vincent J.; Mellström, Dan; van der Geest, Jos N.; Karlsson, Magnus; Hernandez, Dena; McWhirter, Rebekah; Liu, Yongmei; Thomson, Russell; Tranah, Gregory J.; Uitterlinden, Andre G.; Weir, David R.; Zhao, Wei; Starr, John M.; Johnson, Andrew D.; Ikram, M. Arfan; Bennett, David A.; Cummings, Steven R.; Deary, Ian J.; Harris, Tamara B.; Kardia, Sharon L. R.; Mosley, Thomas H.; Srikanth, Velandai K.; Windham, Beverly G.; Newman, Ann B.; Walston, Jeremy D.; Davies, Gail; Evans, Daniel S.; Slagboom, Eline P.; Ferrucci, Luigi; Kiel, Douglas P.; Murabito, Joanne M.; Atzmon, Gil

2017-01-01

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging. PMID:28077804

Stool-based biomarkers of interstitial cystitis/bladder pain syndrome.

PubMed

Braundmeier-Fleming, A; Russell, Nathan T; Yang, Wenbin; Nas, Megan Y; Yaggie, Ryan E; Berry, Matthew; Bachrach, Laurie; Flury, Sarah C; Marko, Darlene S; Bushell, Colleen B; Welge, Michael E; White, Bryan A; Schaeffer, Anthony J; Klumpp, David J

2016-05-18

Interstitial cystitis/bladder pain syndrome (IC) is associated with significant morbidity, yet underlying mechanisms and diagnostic biomarkers remain unknown. Pelvic organs exhibit neural crosstalk by convergence of visceral sensory pathways, and rodent studies demonstrate distinct bacterial pain phenotypes, suggesting that the microbiome modulates pelvic pain in IC. Stool samples were obtained from female IC patients and healthy controls, and symptom severity was determined by questionnaire. Operational taxonomic units (OTUs) were identified by16S rDNA sequence analysis. Machine learning by Extended Random Forest (ERF) identified OTUs associated with symptom scores. Quantitative PCR of stool DNA with species-specific primer pairs demonstrated significantly reduced levels of E. sinensis, C. aerofaciens, F. prausnitzii, O. splanchnicus, and L. longoviformis in microbiota of IC patients. These species, deficient in IC pelvic pain (DIPP), were further evaluated by Receiver-operator characteristic (ROC) analyses, and DIPP species emerged as potential IC biomarkers. Stool metabolomic studies identified glyceraldehyde as significantly elevated in IC. Metabolomic pathway analysis identified lipid pathways, consistent with predicted metagenome functionality. Together, these findings suggest that DIPP species and metabolites may serve as candidates for novel IC biomarkers in stool. Functional changes in the IC microbiome may also serve as therapeutic targets for treating chronic pelvic pain.

Global gene expression analysis combined with a genomics approach for the identification of signal transduction networks involved in postnatal mouse myocardial proliferation and development.

PubMed

Wang, Ruoxin; Su, Chao; Wang, Xinting; Fu, Qiang; Gao, Xingjie; Zhang, Chunyan; Yang, Jie; Yang, Xi; Wei, Minxin

2018-01-01

Mammalian cardiomyocytes may permanently lose their ability to proliferate after birth. Therefore, studying the proliferation and growth arrest of cardiomyocytes during the postnatal period may enhance the current understanding regarding this molecular mechanism. The present study identified the differentially expressed genes in hearts obtained from 24 h‑old mice, which contain proliferative cardiomyocytes; 7‑day‑old mice, in which the cardiomyocytes are undergoing a proliferative burst; and 10‑week‑old mice, which contain growth‑arrested cardiomyocytes, using global gene expression analysis. Furthermore, myocardial proliferation and growth arrest were analyzed from numerous perspectives, including Gene Ontology annotation, cluster analysis, pathway enrichment and network construction. The results of a Gene Ontology analysis indicated that, with increasing age, enriched gene function was not only associated with cell cycle, cell division and mitosis, but was also associated with metabolic processes and protein synthesis. In the pathway analysis, 'cell cycle', proliferation pathways, such as the 'PI3K‑AKT signaling pathway', and 'metabolic pathways' were well represented. Notably, the cluster analysis revealed that bone morphogenetic protein (BMP)1, BMP10, cyclin E2, E2F transcription factor 1 and insulin like growth factor 1 exhibited increased expression in hearts obtained from 7‑day‑old mice. In addition, the signal transduction pathway associated with the cell cycle was identified. The present study primarily focused on genes with altered expression, including downregulated anaphase promoting complex subunit 1, cell division cycle (CDC20), cyclin dependent kinase 1, MYC proto-oncogene, bHLH transcription factor and CDC25C, and upregulated growth arrest and DNA damage inducible α in 10-week group, which may serve important roles in postnatal myocardial cell cycle arrest. In conclusion, these data may provide important information regarding myocardial proliferation and development.

Identification of Key Transcription Factors Associated with Lung Squamous Cell Carcinoma

PubMed Central

Zhang, Feng; Chen, Xia; Wei, Ke; Liu, Daoming; Xu, Xiaodong; Zhang, Xing; Shi, Hong

2017-01-01

Background Lung squamous cell carcinoma (lung SCC) is a common type of lung cancer, but its mechanism of pathogenesis is unclear. The aim of this study was to identify key transcription factors in lung SCC and elucidate its mechanism. Material/Methods Six published microarray datasets of lung SCC were downloaded from Gene Expression Omnibus (GEO) for integrated bioinformatics analysis. Significance analysis of microarrays was used to identify differentially expressed genes (DEGs) between lung SCC and normal controls. The biological functions and signaling pathways of DEGs were mapped in the Gene Otology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, respectively. A transcription factor gene regulatory network was used to obtain insights into the functions of DEGs. Results A total of 1,011 genes, including 539 upregulated genes and 462 downregulated genes, were filtered as DEGs between lung SCC and normal controls. DEGs were significantly enriched in cell cycle, DNA replication, p53 signaling pathway, pathways in cancer, adherens junction, and cell adhesion molecules signaling pathways. There were 57 transcription factors identified, which were used to construct a regulatory network. The network consisted of 736 interactions between 49 transcription factors and 486 DEGs. NFIC, BRCA1, and NFATC2 were the top 3 transcription factors that had the highest connectivity with DEGs and that regulated 83, 82, and 75 DEGs in the network, respectively. Conclusions NFIC, BRCA1, and NFATC2 might be the key transcription factors in the development of lung SCC by regulating the genes involved in cell cycle and DNA replication pathways. PMID:28081052

DNA methylation analysis reveals distinct methylation signatures in pediatric germ cell tumors.

PubMed

Amatruda, James F; Ross, Julie A; Christensen, Brock; Fustino, Nicholas J; Chen, Kenneth S; Hooten, Anthony J; Nelson, Heather; Kuriger, Jacquelyn K; Rakheja, Dinesh; Frazier, A Lindsay; Poynter, Jenny N

2013-06-27

Aberrant DNA methylation is a prominent feature of many cancers, and may be especially relevant in germ cell tumors (GCTs) due to the extensive epigenetic reprogramming that occurs in the germ line during normal development. We used the Illumina GoldenGate Cancer Methylation Panel to compare DNA methylation in the three main histologic subtypes of pediatric GCTs (germinoma, teratoma and yolk sac tumor (YST); N = 51) and used recursively partitioned mixture models (RPMM) to test associations between methylation pattern and tumor and demographic characteristics. We identified genes and pathways that were differentially methylated using generalized linear models and Ingenuity Pathway Analysis. We also measured global DNA methylation at LINE1 elements and evaluated methylation at selected imprinted loci using pyrosequencing. Methylation patterns differed by tumor histology, with 18/19 YSTs forming a distinct methylation class. Four pathways showed significant enrichment for YSTs, including a human embryonic stem cell pluripotency pathway. We identified 190 CpG loci with significant methylation differences in mature and immature teratomas (q < 0.05), including a number of CpGs in stem cell and pluripotency-related pathways. Both YST and germinoma showed significantly lower methylation at LINE1 elements compared with normal adjacent tissue while there was no difference between teratoma (mature and immature) and normal tissue. DNA methylation at imprinted loci differed significantly by tumor histology and location. Understanding methylation patterns may identify the developmental stage at which the GCT arose and the at-risk period when environmental exposures could be most harmful. Further, identification of relevant genetic pathways could lead to the development of new targets for therapy.

Comparative Analysis of Argonaute-dependent Small RNA Pathways in Drosophila

PubMed Central

Zhou, Rui; Hotta, Ikuko; Denli, Ahmet M.; Hong, Pengyu; Perrimon, Norbert; Hannon, Gregory J.

2008-01-01

Summary The specificity of RNAi pathways is determined by several classes of small RNAs, which include siRNAs, piRNAs, endo-siRNAs, and microRNAs (miRNAs). These small RNAs are invariably incorporated into large Argonaute (Ago)-containing effector complexes known as RNA-induced silencing complexes (RISCs), which they guide to silencing targets. Both genetic and biochemical strategies have yielded conserved molecular components of small RNA biogenesis and effector machineries. However, given the complexity of these pathways, there are likely to be additional components and regulators that remain to be uncovered. We have undertaken a comparative and comprehensive RNAi screen to identify genes that impact three major Ago-dependent small RNA pathways that operate in Drosophila S2 cells. We identify subsets of candidates that act positively or negatively in siRNA, endo-siRNA and miRNA pathways. Our studies indicate that many components are shared among all three Argonaute-dependent silencing pathways, though each is also impacted by discrete sets of genes. PMID:19026789

Comparative proteomics of umbilical vein blood plasma from normal and gestational diabetes mellitus patients reveals differentially expressed proteins associated with childhood obesity.

PubMed

Miao, Zhijing; Wang, Jianqing; Wang, Fuqiang; Liu, Lan; Ding, Hongjuan; Shi, Zhonghua

2016-11-01

Offspring obesity is one of long-term complications of gestational diabetes mellitus (GDM). The aim of this study is to identify proteins differentially expressed in the umbilical vein blood plasma, which could become markers for early diagnosis of childhood obesity. Umbilical vein plasma samples were collected from 30 control and 30 GDM patients in 2007-2008 whose offspring were suffering from obesity at 6-7 years old. Multiplexed isobaric tandem mass tag labeling combined with LC-MS/MS was used to identify differentially expressed proteins. Ingenuity pathway analysis was performed to identify canonical pathways, biological functions, and networks of interacting proteins. Western blotting was used to verify the expression of three selected proteins. A total of 318 proteins were identified, of which 12 proteins were upregulated in GDM group while 24 downregulated. Lipid metabolism was the top category identified by ingenuity pathway analysis. Three randomly chosen proteins were validated by Western blotting, which were consistent with LC-MS. There are significant differences of protein profile in the umbilical vein blood plasma between normal and GDM patients with obese offspring. The results indicate that a variety of proteins and biological mechanisms may contribute to childhood obesity. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Pathways Impacted by Genomic Alterations in Pulmonary Carcinoid Tumors.

PubMed

Asiedu, Michael K; Thomas, Charles F; Dong, Jie; Schulte, Sandra C; Khadka, Prasidda; Sun, Zhifu; Kosari, Farhad; Jen, Jin; Molina, Julian; Vasmatzis, George; Kuang, Ray; Aubry, Marie Christine; Yang, Ping; Wigle, Dennis A

2018-04-01

Purpose: Pulmonary carcinoid tumors account for up to 5% of all lung malignancies in adults, comprise 30% of all carcinoid malignancies, and are defined histologically as typical carcinoid (TC) and atypical carcinoid (AC) tumors. The role of specific genomic alterations in the pathogenesis of pulmonary carcinoid tumors remains poorly understood. We sought to identify genomic alterations and pathways that are deregulated in these tumors to find novel therapeutic targets for pulmonary carcinoid tumors. Experimental Design: We performed integrated genomic analysis of carcinoid tumors comprising whole genome and exome sequencing, mRNA expression profiling and SNP genotyping of specimens from normal lung, TC and AC, and small cell lung carcinoma (SCLC) to fully represent the lung neuroendocrine tumor spectrum. Results: Analysis of sequencing data found recurrent mutations in cancer genes including ATP1A2, CNNM1, MACF1, RAB38, NF1, RAD51C, TAF1L, EPHB2, POLR3B , and AGFG1 The mutated genes are involved in biological processes including cellular metabolism, cell division cycle, cell death, apoptosis, and immune regulation. The top most significantly mutated genes were TMEM41B, DEFB127, WDYHV1, and TBPL1 Pathway analysis of significantly mutated and cancer driver genes implicated MAPK/ERK and amyloid beta precursor protein (APP) pathways whereas analysis of CNV and gene expression data suggested deregulation of the NF-κB and MAPK/ERK pathways. The mutation signature was predominantly C>T and T>C transitions with a minor contribution of T>G transversions. Conclusions: This study identified mutated genes affecting cancer relevant pathways and biological processes that could provide opportunities for developing targeted therapies for pulmonary carcinoid tumors. Clin Cancer Res; 24(7); 1691-704. ©2018 AACR . ©2018 American Association for Cancer Research.

Carcinogenic Effects of Oil Dispersants: a KEGG Pathway-based RNA-seq Study of Human Airway Epithelial Cells

PubMed Central

Liu, Yao-Zhong; Zhang, Lei; Roy-Engel, Astrid M; Saito, Shigeki; Lasky, Joseph A; Wang, Guangdi; Wang, He

2016-01-01

The health impacts of the BP oil spill are yet to be further revealed as the toxicological effects of oil products and dispersants on human respiratory system may be latent and complex, and hence difficult to study and follow up. Here we performed RNA-seq analyses of a system of human airway epithelial cells treated with the BP crude oil and/or dispersants Corexit 9500 and Corexit 9527 that were used to help break up the oil spill. Based on the RNA-seq data, we then systemically analyzed the transcriptomic perturbations of the cells at the KEGG pathway level using two pathway-based analysis tools, GAGE (generally applicable gene set enrichment) and GSNCA (Gene Sets Net Correlations Analysis). Our results suggested a pattern of change towards carcinogenesis for the treated cells marked by upregulation of ribosomal biosynthesis (hsa03008) (p = 1.97e-13), protein processing (hsa04141) (p = 4.09e-7), Wnt signaling (hsa04310) (p = 6.76e-3), neurotrophin signaling (hsa04722) (p = 7.73e-3) and insulin signaling (hsa04910) (p = 1.16e-2) pathways under the dispersant Corexit 9527 treatment, as identified by GAGE analysis. Furthermore, through GSNCA analysis, we identified gene co-expression changes for several KEGG cancer pathways, including small cell lung cancer pathway (hsa05222, p = 9.99e-5), under various treatments of oil/dispersant, especially the mixture of oil and Corexit 9527. Overall, our results suggested carcinogenic effects of dispersants (in particular Corexit 9527) and their mixtures with the BP crude oil, and provided further support for more stringent safety precautions and regulations for operations involving long-term respiratory exposure to oil and dispersants. PMID:27866042

Transcriptomic analysis on responses of the liver and kidney of finishing pigs fed cadmium contaminated rice.

PubMed

Xia, Yaoyao; Li, Jun; Ren, Wenkai; Feng, Zemeng; Huang, Ruilin; Yin, Yulong

2018-06-01

Cadmium (Cd) is a common harmful substance that has many deleterious effects on the liver and kidney. Most reports about Cd toxic studies focused on its inorganic status, whereas the toxicity of Cd in organic materials is less studied. Here, we performed RNA-seq to explore the influences of Cd contaminated rice on function of the liver and kidney of finishing pigs. The concentration of Cd in liver and kidney of pigs fed Cd contaminated rice increased by 4.00 and 2.94 times, respectively, compared to those in the control group. With transcriptomic analysis, approximately 4-6 × 10 7 clean reads were acquired. Five differently expressed genes (DEGs) were identified in the liver, and 12 DEGs in the kidney. SPHK2 was commonly down-regulated. No significantly enriched gene ontology (GO) terms were identified. By Kyoto encyclopaedia of genes and genomes (KEGG) enrichments, four pathways were identified in hepatic tissue, and five pathways in nephritic tissue. Intriguingly, two pathways (sphingolipid metabolism and VEGF signalling pathway) were altered both in the liver and kidney. Cd contaminated rice may cause liver and kidney damage and inflammation, or even lead to more severe harm to these tissues. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Identification and pathway analysis of microRNAs with no previous involvement in breast cancer.

PubMed

Romero-Cordoba, Sandra; Rodriguez-Cuevas, Sergio; Rebollar-Vega, Rosa; Quintanar-Jurado, Valeria; Maffuz-Aziz, Antonio; Jimenez-Sanchez, Gerardo; Bautista-Piña, Veronica; Arellano-Llamas, Rocio; Hidalgo-Miranda, Alfredo

2012-01-01

microRNA expression signatures can differentiate normal and breast cancer tissues and can define specific clinico-pathological phenotypes in breast tumors. In order to further evaluate the microRNA expression profile in breast cancer, we analyzed the expression of 667 microRNAs in 29 tumors and 21 adjacent normal tissues using TaqMan Low-density arrays. 130 miRNAs showed significant differential expression (adjusted P value = 0.05, Fold Change = 2) in breast tumors compared to the normal adjacent tissue. Importantly, the role of 43 of these microRNAs has not been previously reported in breast cancer, including several evolutionary conserved microRNA*, showing similar expression rates to that of their corresponding leading strand. The expression of 14 microRNAs was replicated in an independent set of 55 tumors. Bioinformatic analysis of mRNA targets of the altered miRNAs, identified oncogenes like ERBB2, YY1, several MAP kinases, and known tumor-suppressors like FOXA1 and SMAD4. Pathway analysis identified that some biological process which are important in breast carcinogenesis are affected by the altered microRNA expression, including signaling through MAP kinases and TP53 pathways, as well as biological processes like cell death and communication, focal adhesion and ERBB2-ERBB3 signaling. Our data identified the altered expression of several microRNAs whose aberrant expression might have an important impact on cancer-related cellular pathways and whose role in breast cancer has not been previously described.

Defining the gene expression signature of rhabdomyosarcoma by meta-analysis

PubMed Central

Romualdi, Chiara; De Pittà, Cristiano; Tombolan, Lucia; Bortoluzzi, Stefania; Sartori, Francesca; Rosolen, Angelo; Lanfranchi, Gerolamo

2006-01-01

Background Rhabdomyosarcoma is a highly malignant soft tissue sarcoma in childhood and arises as a consequence of regulatory disruption of the growth and differentiation pathways of myogenic precursor cells. The pathogenic pathways involved in this tumor are mostly unknown and therefore a better characterization of RMS gene expression profile would represent a considerable advance. The availability of publicly available gene expression datasets have opened up new challenges especially for the integration of data generated by different research groups and different array platforms with the purpose of obtaining new insights on the biological process investigated. Results In this work we performed a meta-analysis on four microarray and two SAGE datasets of gene expression data on RMS in order to evaluate the degree of agreement of the biological results obtained by these different studies and to identify common regulatory pathways that could be responsible of tumor growth. Regulatory pathways and biological processes significantly enriched has been investigated and a list of differentially meta-profiles have been identified as possible candidate of aggressiveness of RMS. Conclusion Our results point to a general down regulation of the energy production pathways, suggesting a hypoxic physiology for RMS cells. This result agrees with the high malignancy of RMS and with its resistance to most of the therapeutic treatments. In this context, different isoforms of the ANT gene have been consistently identified for the first time as differentially expressed in RMS. This gene is involved in anti-apoptotic processes when cells grow in low oxygen conditions. These new insights in the biological processes responsible of RMS growth and development demonstrate the effective advantage of the use of integrated analysis of gene expression studies. PMID:17090319

Global Gene Expression Profiling in Omental Adipose Tissue of Morbidly Obese Diabetic African Americans.

PubMed

Doumatey, Ayo P; Xu, Huichun; Huang, Hanxia; Trivedi, Niraj S; Lei, Lin; Elkahloun, Abdel; Adeyemo, Adebowale; Rotimi, Charles N

2015-06-01

Adipose tissues play important role in the pathophysiology of obesity-related diseases including type 2 diabetes (T2D). To describe gene expression patterns and functional pathways in obesity-related T2D, we performed global transcript profiling of omental adipose tissue (OAT) in morbidly obese individuals with or without T2D. Twenty morbidly obese (mean BMI: about 54 kg/m 2 ) subjects were studied, including 14 morbidly obese individuals with T2D (cases) and 6 morbidly obese individuals without T2D (reference group). Gene expression profiling was performed using the Affymetrix U133 Plus 2.0 human genome expression array. Analysis of covariance was performed to identify differentially expressed genes (DEGs). Bioinformatics tools including PANTHER and Ingenuity Pathway Analysis (IPA) were applied to the DEGs to determine biological functions, networks and canonical pathways that were overrepresented in these individuals. At an absolute fold-change threshold of 2 and false discovery rate (FDR) < 0.05, 68 DEGs were identified in cases compared to the reference group. Myosin X (MYO10) and transforming growth factor beta regulator 1 (TBRG1) were upregulated. MYO10 encodes for an actin-based motor protein that has been associated with T2D. Telomere extension by telomerase ( HNRNPA1, TNKS2 ), D-myo-inositol (1, 4, 5)-trisphosphate biosynthesis (PIP5K1A, PIP4K2A), and regulation of actin-based motility by Rho (ARPC3) were the most significant canonical pathways and overlay with T2D signaling pathway. Upstream regulator analysis predicted 5 miRNAs (miR-320b, miR-381-3p, miR-3679-3p, miR-494-3p, and miR-141-3p,) as regulators of the expression changes identified. This study identified a number of transcripts and miRNAs in OAT as candidate novel players in the pathophysiology of T2D in African Americans.

Whole-exome sequencing in obsessive-compulsive disorder identifies rare mutations in immunological and neurodevelopmental pathways

PubMed Central

Cappi, C; Brentani, H; Lima, L; Sanders, S J; Zai, G; Diniz, B J; Reis, V N S; Hounie, A G; Conceição do Rosário, M; Mariani, D; Requena, G L; Puga, R; Souza-Duran, F L; Shavitt, R G; Pauls, D L; Miguel, E C; Fernandez, T V

2016-01-01

Studies of rare genetic variation have identified molecular pathways conferring risk for developmental neuropsychiatric disorders. To date, no published whole-exome sequencing studies have been reported in obsessive-compulsive disorder (OCD). We sequenced all the genome coding regions in 20 sporadic OCD cases and their unaffected parents to identify rare de novo (DN) single-nucleotide variants (SNVs). The primary aim of this pilot study was to determine whether DN variation contributes to OCD risk. To this aim, we evaluated whether there is an elevated rate of DN mutations in OCD, which would justify this approach toward gene discovery in larger studies of the disorder. Furthermore, to explore functional molecular correlations among genes with nonsynonymous DN SNVs in OCD probands, a protein–protein interaction (PPI) network was generated based on databases of direct molecular interactions. We applied Degree-Aware Disease Gene Prioritization (DADA) to rank the PPI network genes based on their relatedness to a set of OCD candidate genes from two OCD genome-wide association studies (Stewart et al., 2013; Mattheisen et al., 2014). In addition, we performed a pathway analysis with genes from the PPI network. The rate of DN SNVs in OCD was 2.51 × 10−8 per base per generation, significantly higher than a previous estimated rate in unaffected subjects using the same sequencing platform and analytic pipeline. Several genes harboring DN SNVs in OCD were highly interconnected in the PPI network and ranked high in the DADA analysis. Nearly all the DN SNVs in this study are in genes expressed in the human brain, and a pathway analysis revealed enrichment in immunological and central nervous system functioning and development. The results of this pilot study indicate that further investigation of DN variation in larger OCD cohorts is warranted to identify specific risk genes and to confirm our preliminary finding with regard to PPI network enrichment for particular biological pathways and functions. PMID:27023170

Transcriptome Analysis of Three Sheep Intestinal Regions reveals Key Pathways and Hub Regulatory Genes of Large Intestinal Lipid Metabolism.

PubMed

Chao, Tianle; Wang, Guizhi; Ji, Zhibin; Liu, Zhaohua; Hou, Lei; Wang, Jin; Wang, Jianmin

2017-07-13

The large intestine, also known as the hindgut, is an important part of the animal digestive system. Recent studies on digestive system development in ruminants have focused on the rumen and the small intestine, but the molecular mechanisms underlying sheep large intestine metabolism remain poorly understood. To identify genes related to intestinal metabolism and to reveal molecular regulation mechanisms, we sequenced and compared the transcriptomes of mucosal epithelial tissues among the cecum, proximal colon and duodenum. A total of 4,221 transcripts from 3,254 genes were identified as differentially expressed transcripts. Between the large intestine and duodenum, differentially expressed transcripts were found to be significantly enriched in 6 metabolism-related pathways, among which PPAR signaling was identified as a key pathway. Three genes, CPT1A, LPL and PCK1, were identified as higher expression hub genes in the large intestine. Between the cecum and colon, differentially expressed transcripts were significantly enriched in 5 lipid metabolism related pathways, and CEPT1 and MBOAT1 were identified as hub genes. This study provides important information regarding the molecular mechanisms of intestinal metabolism in sheep and may provide a basis for further study.

Detection of Significant Pneumococcal Meningitis Biomarkers by Ego Network.

PubMed

Wang, Qian; Lou, Zhifeng; Zhai, Liansuo; Zhao, Haibin

2017-06-01

To identify significant biomarkers for detection of pneumococcal meningitis based on ego network. Based on the gene expression data of pneumococcal meningitis and global protein-protein interactions (PPIs) data recruited from open access databases, the authors constructed a differential co-expression network (DCN) to identify pneumococcal meningitis biomarkers in a network view. Here EgoNet algorithm was employed to screen the significant ego networks that could accurately distinguish pneumococcal meningitis from healthy controls, by sequentially seeking ego genes, searching candidate ego networks, refinement of candidate ego networks and significance analysis to identify ego networks. Finally, the functional inference of the ego networks was performed to identify significant pathways for pneumococcal meningitis. By differential co-expression analysis, the authors constructed the DCN that covered 1809 genes and 3689 interactions. From the DCN, a total of 90 ego genes were identified. Starting from these ego genes, three significant ego networks (Module 19, Module 70 and Module 71) that could predict clinical outcomes for pneumococcal meningitis were identified by EgoNet algorithm, and the corresponding ego genes were GMNN, MAD2L1 and TPX2, respectively. Pathway analysis showed that these three ego networks were related to CDT1 association with the CDC6:ORC:origin complex, inactivation of APC/C via direct inhibition of the APC/C complex pathway, and DNA strand elongation, respectively. The authors successfully screened three significant ego modules which could accurately predict the clinical outcomes for pneumococcal meningitis and might play important roles in host response to pathogen infection in pneumococcal meningitis.

New Statistics for Testing Differential Expression of Pathways from Microarray Data

NASA Astrophysics Data System (ADS)

Siu, Hoicheong; Dong, Hua; Jin, Li; Xiong, Momiao

Exploring biological meaning from microarray data is very important but remains a great challenge. Here, we developed three new statistics: linear combination test, quadratic test and de-correlation test to identify differentially expressed pathways from gene expression profile. We apply our statistics to two rheumatoid arthritis datasets. Notably, our results reveal three significant pathways and 275 genes in common in two datasets. The pathways we found are meaningful to uncover the disease mechanisms of rheumatoid arthritis, which implies that our statistics are a powerful tool in functional analysis of gene expression data.

The alignment of enzymatic steps reveals similar metabolic pathways and probable recruitment events in Gammaproteobacteria.

PubMed

Poot-Hernandez, Augusto Cesar; Rodriguez-Vazquez, Katya; Perez-Rueda, Ernesto

2015-11-17

It is generally accepted that gene duplication followed by functional divergence is one of the main sources of metabolic diversity. In this regard, there is an increasing interest in the development of methods that allow the systematic identification of these evolutionary events in metabolism. Here, we used a method not based on biomolecular sequence analysis to compare and identify common and variable routes in the metabolism of 40 Gammaproteobacteria species. The metabolic maps deposited in the KEGG database were transformed into linear Enzymatic Step Sequences (ESS) by using the breadth-first search algorithm. These ESS represent subsequent enzymes linked to each other, where their catalytic activities are encoded in the Enzyme Commission numbers. The ESS were compared in an all-against-all (pairwise comparisons) approach by using a dynamic programming algorithm, leaving only a set of significant pairs. From these comparisons, we identified a set of functionally conserved enzymatic steps in different metabolic maps, in which cell wall components and fatty acid and lysine biosynthesis were included. In addition, we found that pathways associated with biosynthesis share a higher proportion of similar ESS than degradation pathways and secondary metabolism pathways. Also, maps associated with the metabolism of similar compounds contain a high proportion of similar ESS, such as those maps from nucleotide metabolism pathways, in particular the inosine monophosphate pathway. Furthermore, diverse ESS associated with the low part of the glycolysis pathway were identified as functionally similar to multiple metabolic pathways. In summary, our comparisons may help to identify similar reactions in different metabolic pathways and could reinforce the patchwork model in the evolution of metabolism in Gammaproteobacteria.

PI3K pathway mutations are associated with longer time to local progression after radioembolization of colorectal liver metastases.

PubMed

Ziv, Etay; Bergen, Michael; Yarmohammadi, Hooman; Boas, F Ed; Petre, E Nadia; Sofocleous, Constantinos T; Yaeger, Rona; Solit, David B; Solomon, Stephen B; Erinjeri, Joseph P

2017-04-04

To establish the relationship between common mutations in the MAPK and PI3K signaling pathways and local progression after radioembolization. Retrospective review of a HIPAA-compliant institutional review-board approved database identified 40 patients with chemo-refractory colorectal liver metastases treated with radioembolization who underwent tumor genotyping for hotspot mutations in 6 key genes in the MAPK/PI3K pathways (KRAS, NRAS, BRAF, MEK1, PIK3CA, and AKT1). Mutation status as well as clinical, tumor, and treatment variables were recorded. These factors were evaluated in relation to time to local progression (TTLP), which was calculated from time of radioembolization to first radiographic evidence of local progression. Predictors of outcome were identified using a proportional hazards model for both univariate and multivariate analysis with death as a competing risk. Sixteen patients (40%) had no mutations in either pathway, eighteen patients (45%) had mutations in the MAPK pathway, ten patients (25%) had mutations in the PI3K pathway and four patients (10%) had mutations in both pathways. The cumulative incidence of progression at 6 and 12 months was 33% and 55% for the PI3K mutated group compared with 76% and 92% in the PI3K wild type group. Mutation in the PI3K pathway was a significant predictor of longer TTLP in both univariate (p=0.031, sHR 0.31, 95% CI: 0.11-0.90) and multivariate (p=0.015, sHR=0.27, 95% CI: 0.096-0.77) analysis. MAPK pathway alterations were not associated with TTLP. PI3K pathway mutation predicts longer time to local progression after radioembolization of colorectal liver metastases.

Diverse Genome-wide Association Studies Associate the IL12/IL23 Pathway with Crohn Disease

PubMed Central

Wang, Kai; Zhang, Haitao; Kugathasan, Subra; Annese, Vito; Bradfield, Jonathan P.; Russell, Richard K.; Sleiman, Patrick M.A.; Imielinski, Marcin; Glessner, Joseph; Hou, Cuiping; Wilson, David C.; Walters, Thomas; Kim, Cecilia; Frackelton, Edward C.; Lionetti, Paolo; Barabino, Arrigo; Van Limbergen, Johan; Guthery, Stephen; Denson, Lee; Piccoli, David; Li, Mingyao; Dubinsky, Marla; Silverberg, Mark; Griffiths, Anne; Grant, Struan F.A.; Satsangi, Jack; Baldassano, Robert; Hakonarson, Hakon

2009-01-01

Previous genome-wide association (GWA) studies typically focus on single-locus analysis, which may not have the power to detect the majority of genuinely associated loci. Here, we applied pathway analysis using Affymetrix SNP genotype data from the Wellcome Trust Case Control Consortium (WTCCC) and uncovered significant association between Crohn Disease (CD) and the IL12/IL23 pathway, harboring 20 genes (p = 8 × 10−5). Interestingly, the pathway contains multiple genes (IL12B and JAK2) or homologs of genes (STAT3 and CCR6) that were recently identified as genuine susceptibility genes only through meta-analysis of several GWA studies. In addition, the pathway contains other susceptibility genes for CD, including IL18R1, JUN, IL12RB1, and TYK2, which do not reach genome-wide significance by single-marker association tests. The observed pathway-specific association signal was subsequently replicated in three additional GWA studies of European and African American ancestry generated on the Illumina HumanHap550 platform. Our study suggests that examination beyond individual SNP hits, by focusing on genetic networks and pathways, is important to unleashing the true power of GWA studies. PMID:19249008

A transcriptional profile of the decidua in preeclampsia

PubMed Central

LØSET, Mari; MUNDAL, Siv B.; JOHNSON, Matthew P.; FENSTAD, Mona H.; FREED, Katherine A.; LIAN, Ingrid A.; EIDE, Irina P.; BJØRGE, Line; BLANGERO, John; MOSES, Eric K.; AUSTGULEN, Rigmor

2010-01-01

OBJECTIVE To obtain insight into possible mechanisms underlying preeclampsia using genome-wide transcriptional profiling in decidua basalis. STUDY DESIGN Genome-wide transcriptional profiling was performed on decidua basalis tissue from preeclamptic (n = 37) and normal pregnancies (n = 58). Differentially expressed genes were identified and merged into canonical pathways and networks. RESULTS Of the 26,504 expressed transcripts detected, 455 were differentially expressed (P <0.05, FDR P <0.1). Both novel (ARL5B, SLITRK4) and previously reported preeclampsia-associated genes (PLA2G7, HMOX1) were identified. Pathway analysis revealed that ‘tryptophan metabolism’, ‘endoplasmic reticulum stress’, ‘linoleic acid metabolism’, ‘notch signaling’, ‘fatty acid metabolism’, ‘arachidonic acid metabolism’ and ‘NRF2-mediated oxidative stress response’ were overrepresented canonical pathways. CONCLUSION In the present study single genes, canonical pathways and gene-gene networks that are likely to play an important role in the pathogenesis of preeclampsia, have been identified. Future functional studies are needed to accomplish a greater understanding of the mechanisms involved. PMID:20934677

MicroRNA-124-3p expression and its prospective functional pathways in hepatocellular carcinoma: A quantitative polymerase chain reaction, gene expression omnibus and bioinformatics study.

PubMed

He, Rong-Quan; Yang, Xia; Liang, Liang; Chen, Gang; Ma, Jie

2018-04-01

The present study aimed to explore the potential clinical significance of microRNA (miR)-124-3p expression in the hepatocarcinogenesis and development of hepatocellular carcinoma (HCC), as well as the potential target genes of functional HCC pathways. Reverse transcription-quantitative polymerase chain reaction was performed to evaluate the expression of miR-124-3p in 101 HCC and adjacent non-cancerous tissue samples. Additionally, the association between miR-124-3p expression and clinical parameters was also analyzed. Differentially expressed genes identified following miR-124-3p transfection, the prospective target genes predicted in silico and the key genes of HCC obtained from Natural Language Processing (NLP) were integrated to obtain potential target genes of miR-124-3p in HCC. Relevant signaling pathways were assessed with protein-protein interaction (PPI) networks, Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Protein Annotation Through Evolutionary Relationships (PANTHER) pathway enrichment analysis. miR-124-3p expression was significantly reduced in HCC tissues compared with expression in adjacent non-cancerous liver tissues. In HCC, miR-124-3p was demonstrated to be associated with clinical stage. The mean survival time of the low miR-124-3p expression group was reduced compared with that of the high expression group. A total of 132 genes overlapped from differentially expressed genes, miR-124-3p predicted target genes and NLP identified genes. PPI network construction revealed a total of 109 nodes and 386 edges, and 20 key genes were identified. The major enriched terms of three GO categories included regulation of cell proliferation, positive regulation of cellular biosynthetic processes, cell leading edge, cytosol and cell projection, protein kinase activity, transcription activator activity and enzyme binding. KEGG analysis revealed pancreatic cancer, prostate cancer and non-small cell lung cancer as the top three terms. Angiogenesis, the endothelial growth factor receptor signaling pathway and the fibroblast growth factor signaling pathway were identified as the most significant terms in the PANTHER pathway analysis. The present study confirmed that miR-124-3p acts as a tumor suppressor in HCC. miR-124-3p may target multiple genes, exerting its effect spatiotemporally, or in combination with a diverse range of processes in HCC. Functional characterization of miR-124-3p targets will offer novel insight into the molecular changes that occur in HCC progression.

Analysis and identification of astaxanthin and its carotenoid precursors from Xanthophyllomyces dendrorhous by high-performance liquid chromatography.

PubMed

Lu, Mingbo; Zhang, Yang'e; Zhao, Chunfang; Zhou, Pengpeng; Yu, Longjiang

2010-01-01

This study presents an HPLC method for simultaneous analysis of astaxanthin and its carotenoid precursors from Xanthophyllomyces dendrorhous. The HPLC method is accomplished by employing a C18 column and the mobile phase methanol/water/acetonitrile/ dichloromethane (70:4:13:13, v/v/v/v). Astaxanthin is quantified by detection at 480 nm. The carotenoid precursors are identified by LC-APCI-MS and UV-vis absorption spectra. Peaks showed in the HPLC chromatogram are identified as carotenoids in the monocyclic biosynthetic pathway or their derivatives. In the monocyclic carotenoid pathway, 3,3'-dihydroxy-beta,psi-carotene-4,4'-dione (DCD) is produced through gamma-carotene and torulene.

Metabolic analyses elucidate non-trivial gene targets for amplifying dihydroartemisinic acid production in yeast

PubMed Central

Misra, Ashish; Conway, Matthew F.; Johnnie, Joseph; Qureshi, Tabish M.; Lige, Bao; Derrick, Anne M.; Agbo, Eddy C.; Sriram, Ganesh

2013-01-01

Synthetic biology enables metabolic engineering of industrial microbes to synthesize value-added molecules. In this, a major challenge is the efficient redirection of carbon to the desired metabolic pathways. Pinpointing strategies toward this goal requires an in-depth investigation of the metabolic landscape of the organism, particularly primary metabolism, to identify precursor and cofactor availability for the target compound. The potent antimalarial therapeutic artemisinin and its precursors are promising candidate molecules for production in microbial hosts. Recent advances have demonstrated the production of artemisinin precursors in engineered yeast strains as an alternative to extraction from plants. We report the application of in silico and in vivo metabolic pathway analyses to identify metabolic engineering targets to improve the yield of the direct artemisinin precursor dihydroartemisinic acid (DHA) in yeast. First, in silico extreme pathway (ExPa) analysis identified NADPH-malic enzyme and the oxidative pentose phosphate pathway (PPP) as mechanisms to meet NADPH demand for DHA synthesis. Next, we compared key DHA-synthesizing ExPas to the metabolic flux distributions obtained from in vivo 13C metabolic flux analysis of a DHA-synthesizing strain. This comparison revealed that knocking out ethanol synthesis and overexpressing glucose-6-phosphate dehydrogenase in the oxidative PPP (gene YNL241C) or the NADPH-malic enzyme ME2 (YKL029C) are vital steps toward overproducing DHA. Finally, we employed in silico flux balance analysis and minimization of metabolic adjustment on a yeast genome-scale model to identify gene knockouts for improving DHA yields. The best strategy involved knockout of an oxaloacetate transporter (YKL120W) and an aspartate aminotransferase (YKL106W), and was predicted to improve DHA yields by 70-fold. Collectively, our work elucidates multiple non-trivial metabolic engineering strategies for improving DHA yield in yeast. PMID:23898325

Magnetic capture of polydopamine-encapsulated Hela cells for the analysis of cell surface proteins.

PubMed

Liu, Yiying; Yan, Guoquan; Gao, Mingxia; Zhang, Xiangmin

2018-02-10

A novel method to characterize cell surface proteins and complexes has been developed. Polydopamine (PDA)-encapsulated Hela cells were prepared for plasma membrane proteome research. Since the PDA protection, the encapsulated cells could be maintained for more than two weeks. Amino groups functionalized magnetic nanoparticles were also used for cell capture by the reaction with the PDA coatings. Plasma membrane fragments were isolated and enriched with assistance of an external magnetic field after disruption of the coated cells by ultrasonic treatment. Plasma membrane proteins (PMPs) and complexes were well preserved on the fragments and identified by shot-gun proteomic analytical strategy. 385 PMPs and 1411 non-PMPs were identified using the method. 85.2% of these PMPs were lipid-raft associated proteins. Ingenuity Pathway Analysis was employed for bio-information extraction from the identified proteins. It was found that 653 non-PMPs had interactions with 140 PMPs. Among them, epidermal growth factor receptor and its complexes, and a series of important pathways including STAT3 pathway were observed. All these results demonstrated that the new approach is of great importance in applying to the research of physiological function and mechanism of the plasma membrane proteins. This work developed a novel strategy for the proteomic analysis of cell surface proteins. According to the results, 73.3% of total identified proteins were lipid-raft associated proteins, which imply that the proposed method is of great potential in the identification of lipid-raft associated proteins. In addition, a series of protein-protein interactions and pathways related to Hela cells were pointed out. All these results demonstrated that our proposed approach is of great importance and could well be applied to the physiological function and mechanism research of plasma membrane proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

TransCONFIRM: Identification of a Genetic Signature of Response to Fulvestrant in Advanced Hormone Receptor-Positive Breast Cancer.

PubMed

Jeselsohn, Rinath; Barry, William T; Migliaccio, Ilenia; Biagioni, Chiara; Zhao, Jin; De Tribolet-Hardy, Jonas; Guarducci, Cristina; Bonechi, Martina; Laing, Naomi; Winer, Eric P; Brown, Myles; Leo, Angelo Di; Malorni, Luca

2016-12-01

Fulvestrant is an estrogen receptor (ER) antagonist and an approved treatment for metastatic estrogen receptor-positive (ER + ) breast cancer. With the exception of ER levels, there are no established predictive biomarkers of response to single-agent fulvestrant. We attempted to identify a gene signature of response to fulvestrant in advanced breast cancer. Primary tumor samples from 134 patients enrolled in the phase III CONFIRM study of patients with metastatic ER + breast cancer comparing treatment with either 250 mg or 500 mg fulvestrant were collected for genome-wide transcriptomic analysis. Gene expression profiling was performed using Affymetrix microarrays. An exploratory analysis was performed to identify biologic pathways and new signatures associated with response to fulvestrant. Pathway analysis demonstrated that increased EGF pathway and FOXA1 transcriptional signaling is associated with decreased response to fulvestrant. Using a multivariate Cox model, we identified a novel set of 37 genes with an expression that is independently associated with progression-free survival (PFS). TFAP2C, a known regulator of ER activity, was ranked second in this gene set, and high expression was associated with a decreased response to fulvestrant. The negative predictive value of TFAP2C expression at the protein level was confirmed by IHC. We identified biologic pathways and a novel gene signature in primary ER + breast cancers that predicts for response to treatment in the CONFIRM study. These results suggest potential new therapeutic targets and warrant further validation as predictive biomarkers of fulvestrant treatment in metastatic breast cancer. Clin Cancer Res; 22(23); 5755-64. ©2016 AACR. ©2016 American Association for Cancer Research.

Identification of key genes and pathways associated with neuropathic pain in uninjured dorsal root ganglion by using bioinformatic analysis.

PubMed

Chen, Chao-Jin; Liu, De-Zhao; Yao, Wei-Feng; Gu, Yu; Huang, Fei; Hei, Zi-Qing; Li, Xiang

2017-01-01

Neuropathic pain is a complex chronic condition occurring post-nervous system damage. The transcriptional reprogramming of injured dorsal root ganglia (DRGs) drives neuropathic pain. However, few comparative analyses using high-throughput platforms have investigated uninjured DRG in neuropathic pain, and potential interactions among differentially expressed genes (DEGs) and pathways were not taken into consideration. The aim of this study was to identify changes in genes and pathways associated with neuropathic pain in uninjured L4 DRG after L5 spinal nerve ligation (SNL) by using bioinformatic analysis. The microarray profile GSE24982 was downloaded from the Gene Expression Omnibus database to identify DEGs between DRGs in SNL and sham rats. The prioritization for these DEGs was performed using the Toppgene database followed by gene ontology and pathway enrichment analyses. The relationships among DEGs from the protein interactive perspective were analyzed using protein-protein interaction (PPI) network and module analysis. Real-time polymerase chain reaction (PCR) and Western blotting were used to confirm the expression of DEGs in the rodent neuropathic pain model. A total of 206 DEGs that might play a role in neuropathic pain were identified in L4 DRG, of which 75 were upregulated and 131 were downregulated. The upregulated DEGs were enriched in biological processes related to transcription regulation and molecular functions such as DNA binding, cell cycle, and the FoxO signaling pathway. Ctnnb1 protein had the highest connectivity degrees in the PPI network. The in vivo studies also validated that mRNA and protein levels of Ctnnb1 were upregulated in both L4 and L5 DRGs. This study provides insight into the functional gene sets and pathways associated with neuropathic pain in L4 uninjured DRG after L5 SNL, which might promote our understanding of the molecular mechanisms underlying the development of neuropathic pain.

Barcode Sequencing Screen Identifies SUB1 as a Regulator of Yeast Pheromone Inducible Genes

PubMed Central

Sliva, Anna; Kuang, Zheng; Meluh, Pamela B.; Boeke, Jef D.

2016-01-01

The yeast pheromone response pathway serves as a valuable model of eukaryotic mitogen-activated protein kinase (MAPK) pathways, and transcription of their downstream targets. Here, we describe application of a screening method combining two technologies: fluorescence-activated cell sorting (FACS), and barcode analysis by sequencing (Bar-Seq). Using this screening method, and pFUS1-GFP as a reporter for MAPK pathway activation, we readily identified mutants in known mating pathway components. In this study, we also include a comprehensive analysis of the FUS1 induction properties of known mating pathway mutants by flow cytometry, featuring single cell analysis of each mutant population. We also characterized a new source of false positives resulting from the design of this screen. Additionally, we identified a deletion mutant, sub1Δ, with increased basal expression of pFUS1-GFP. Here, in the first ChIP-Seq of Sub1, our data shows that Sub1 binds to the promoters of about half the genes in the genome (tripling the 991 loci previously reported), including the promoters of several pheromone-inducible genes, some of which show an increase upon pheromone induction. Here, we also present the first RNA-Seq of a sub1Δ mutant; the majority of genes have no change in RNA, but, of the small subset that do, most show decreased expression, consistent with biochemical studies implicating Sub1 as a positive transcriptional regulator. The RNA-Seq data also show that certain pheromone-inducible genes are induced less in the sub1Δ mutant relative to the wild type, supporting a role for Sub1 in regulation of mating pathway genes. The sub1Δ mutant has increased basal levels of a small subset of other genes besides FUS1, including IMD2 and FIG1, a gene encoding an integral membrane protein necessary for efficient mating. PMID:26837954

Hemorrhage and Subsequent Allogenic Red Blood Cell Transfusion are Associated With Characteristic Monocyte Messenger RNA Expression Patterns in Patients After Multiple Injury—A Genome Wide View

PubMed Central

Bogner, Viktoria; Baker, Henry V.; Kanz, Karl-Georg; Moldawer, L. L.; Mutschler, Wolf; Biberthaler, Peter

2014-01-01

Introduction As outcome to severe trauma is frequently affected by massive blood loss and consecutive hemorrhagic shock, replacement of red blood cell (RBC) units remains indispensable. Administration of RBC units is an independent risk factor for adverse outcome in patients with trauma. The impact of massive blood transfusion or uncrossmatched blood transfusion on the patients’ immune response in the early posttraumatic period remains unclear. Material Thirteen patients presenting with blunt multiple injuries (Injury Severity Score >16) were studied. Monocytes were obtained on admission and at 6, 12, 24, 48, and 72 hours after trauma. Biotinylated complementary RNA targets were hybridized to Affymetrix HG U 133A microarrays. The data were analyzed by a supervised analysis based on whether the patients received massive blood transfusions, and then subsequently, by hierarchical clustering, and by Ingenuity pathway analysis. Results Supervised analysis identified 224 probe sets to be differentially expressed (p < 0.001) in patients who received massive blood transfusion, when compared with those who did not. In addition, 331 probe sets were found differentially expressed (p < 0.001) in patients who received uncrossmatched RBC units in comparison with those who exclusively gained crossmatched ones. Functional pathway analysis of the respectively identified gene expression profiles suggests a contributory role by the AKT/PI3Kinase pathway, the mitogen-activated protein-kinase pathway, the Ubiquitin pathway, and the diverse inflammatory networks. Conclusion We exhibited for the first time a serial, sequential screening analysis of monocyte messenger RNA expression patterns in patients with multiple trauma indicating a strongly significant association between the patients’ genomic response in blood monocytes and massive or uncross-matched RBC substitution. PMID:19820587

New features of triacylglycerol biosynthetic pathways of peanut seeds in early developmental stages.

PubMed

Yu, Mingli; Liu, Fengzhen; Zhu, Weiwei; Sun, Meihong; Liu, Jiang; Li, Xinzheng

2015-11-01

The peanut (Arachis hypogaea L.) is one of the three most important oil crops in the world due to its high average oil content (50 %). To reveal the biosynthetic pathways of seed oil in the early developmental stages of peanut pods with the goal of improving the oil quality, we presented a method combining deep sequencing analysis of the peanut pod transcriptome and quantitative real-time PCR (RT-PCR) verification of seed oil-related genes. From the sequencing data, approximately 1500 lipid metabolism-associated Unigenes were identified. The RT-PCR results quantified the different expression patterns of these triacylglycerol (TAG) synthesis-related genes in the early developmental stages of peanut pods. Based on these results and analysis, we proposed a novel construct of the metabolic pathways involved in the biosynthesis of TAG, including the Kennedy pathway, acyl-CoA-independent pathway and proposed monoacylglycerol pathway. It showed that the biosynthetic pathways of TAG in the early developmental stages of peanut pods were much more complicated than a simple, unidirectional, linear pathway.

Expression profiling and pathway analysis of Krüppel-like factor 4 in mouse embryonic fibroblasts

PubMed Central

Hagos, Engda G; Ghaleb, Amr M; Kumar, Amrita; Neish, Andrew S; Yang, Vincent W

2011-01-01

Background: Krüppel-like factor 4 (KLF4) is a zinc-finger transcription factor with diverse regulatory functions in proliferation, differentiation, and development. KLF4 also plays a role in inflammation, tumorigenesis, and reprogramming of somatic cells to induced pluripotent stem (iPS) cells. To gain insight into the mechanisms by which KLF4 regulates these processes, we conducted DNA microarray analyses to identify differentially expressed genes in mouse embryonic fibroblasts (MEFs) wild type and null for Klf4. Methods: Expression profiles of fibroblasts isolated from mouse embryos wild type or null for the Klf4 alleles were examined by DNA microarrays. Differentially expressed genes were subjected to the Database for Annotation, Visualization and Integrated Discovery (DAVID). The microarray data were also interrogated with the Ingenuity Pathway Analysis (IPA) and Gene Set Enrichment Analysis (GSEA) for pathway identification. Results obtained from the microarray analysis were confirmed by Western blotting for select genes with biological relevance to determine the correlation between mRNA and protein levels. Results: One hundred and sixty three up-regulated and 88 down-regulated genes were identified that demonstrated a fold-change of at least 1.5 and a P-value < 0.05 in Klf4-null MEFs compared to wild type MEFs. Many of the up-regulated genes in Klf4-null MEFs encode proto-oncogenes, growth factors, extracellular matrix, and cell cycle activators. In contrast, genes encoding tumor suppressors and those involved in JAK-STAT signaling pathways are down-regulated in Klf4-null MEFs. IPA and GSEA also identified various pathways that are regulated by KLF4. Lastly, Western blotting of select target genes confirmed the changes revealed by microarray data. Conclusions: These data are not only consistent with previous functional studies of KLF4's role in tumor suppression and somatic cell reprogramming, but also revealed novel target genes that mediate KLF4's functions. PMID:21892412

Expression profiling in canine osteosarcoma: identification of biomarkers and pathways associated with outcome

PubMed Central

2010-01-01

Background Osteosarcoma (OSA) spontaneously arises in the appendicular skeleton of large breed dogs and shares many physiological and molecular biological characteristics with human OSA. The standard treatment for OSA in both species is amputation or limb-sparing surgery, followed by chemotherapy. Unfortunately, OSA is an aggressive cancer with a high metastatic rate. Characterization of OSA with regard to its metastatic potential and chemotherapeutic resistance will improve both prognostic capabilities and treatment modalities. Methods We analyzed archived primary OSA tissue from dogs treated with limb amputation followed by doxorubicin or platinum-based drug chemotherapy. Samples were selected from two groups: dogs with disease free intervals (DFI) of less than 100 days (n = 8) and greater than 300 days (n = 7). Gene expression was assessed with Affymetrix Canine 2.0 microarrays and analyzed with a two-tailed t-test. A subset of genes was confirmed using qRT-PCR and used in classification analysis to predict prognosis. Systems-based gene ontology analysis was conducted on genes selected using a standard J5 metric. The genes identified using this approach were converted to their human homologues and assigned to functional pathways using the GeneGo MetaCore platform. Results Potential biomarkers were identified using gene expression microarray analysis and 11 differentially expressed (p < 0.05) genes were validated with qRT-PCR (n = 10/group). Statistical classification models using the qRT-PCR profiles predicted patient outcomes with 100% accuracy in the training set and up to 90% accuracy upon stratified cross validation. Pathway analysis revealed alterations in pathways associated with oxidative phosphorylation, hedgehog and parathyroid hormone signaling, cAMP/Protein Kinase A (PKA) signaling, immune responses, cytoskeletal remodeling and focal adhesion. Conclusions This profiling study has identified potential new biomarkers to predict patient outcome in OSA and new pathways that may be targeted for therapeutic intervention. PMID:20860831

Metabolomic analysis reveals altered metabolic pathways in a rat model of gastric carcinogenesis.

PubMed

Gu, Jinping; Hu, Xiaomin; Shao, Wei; Ji, Tianhai; Yang, Wensheng; Zhuo, Huiqin; Jin, Zeyu; Huang, Huiying; Chen, Jiacheng; Huang, Caihua; Lin, Donghai

2016-09-13

Gastric cancer (GC) is one of the most malignant tumors with a poor prognosis. Alterations in metabolic pathways are inextricably linked to GC progression. However, the underlying molecular mechanisms remain elusive. We performed NMR-based metabolomic analysis of sera derived from a rat model of gastric carcinogenesis, revealed significantly altered metabolic pathways correlated with the progression of gastric carcinogenesis. Rats were histologically classified into four pathological groups (gastritis, GS; low-grade gastric dysplasia, LGD; high-grade gastric dysplasia, HGD; GC) and the normal control group (CON). The metabolic profiles of the five groups were clearly distinguished from each other. Furthermore, significant inter-metabolite correlations were extracted and used to reconstruct perturbed metabolic networks associated with the four pathological stages compared with the normal stage. Then, significantly altered metabolic pathways were identified by pathway analysis. Our results showed that oxidative stress-related metabolic pathways, choline phosphorylation and fatty acid degradation were continually disturbed during gastric carcinogenesis. Moreover, amino acid metabolism was perturbed dramatically in gastric dysplasia and GC. The GC stage showed more changed metabolite levels and more altered metabolic pathways. Two activated pathways (glycolysis; glycine, serine and threonine metabolism) substantially contributed to the metabolic alterations in GC. These results lay the basis for addressing the molecular mechanisms underlying gastric carcinogenesis and extend our understanding of GC progression.

IRS2 mutations linked to invasion in pleomorphic invasive lobular carcinoma

PubMed Central

Zhu, Sha; Ward, B. Marie; Yu, Jun; Matthew-Onabanjo, Asia N.; Janusis, Jenny; Hsieh, Chung-Cheng; Tomaszewicz, Keith; Hutchinson, Lloyd; Zhu, Lihua Julie; Kandil, Dina; Shaw, Leslie M.

2018-01-01

Pleomorphic invasive lobular carcinoma (PILC) is an aggressive variant of invasive lobular breast cancer that is associated with poor clinical outcomes. Limited molecular data are available to explain the mechanistic basis for PILC behavior. To address this issue, targeted sequencing was performed to identify molecular alterations that define PILC. This sequencing analysis identified genes that distinguish PILC from classic ILC and invasive ductal carcinoma by the incidence of their genomic changes. In particular, insulin receptor substrate 2 (IRS2) is recurrently mutated in PILC, and pathway analysis reveals a role for the insulin receptor (IR)/insulin-like growth factor-1 receptor (IGF1R)/IRS2 signaling pathway in PILC. IRS2 mutations identified in PILC enhance invasion, revealing a role for this signaling adaptor in the aggressive nature of PILC. PMID:29669935

Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database.

PubMed

Wang, Anping; Zhang, Guibin

2017-11-01

The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.

Urinary metabolomics analysis identifies key biomarkers of different stages of nonalcoholic fatty liver disease

PubMed Central

Dong, Shu; Zhan, Zong-Ying; Cao, Hong-Yan; Wu, Chao; Bian, Yan-Qin; Li, Jian-Yuan; Cheng, Gen-Hong; Liu, Ping; Sun, Ming-Yu

2017-01-01

AIM To identify a panel of biomarkers that can distinguish between non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), and explore molecular mechanism involved in the process of developing NASH from NAFLD. METHODS Biomarkers may differ during stages of NAFLD. Urine and blood were obtained from non-diabetic subjects with NAFLD and steatosis, with normal liver function (n = 33), from patients with NASH, with abnormal liver function (n = 45), and from healthy age and sex-matched controls (n = 30). Samples were subjected to metabolomic analysis to identify potential non-invasive biomarkers. Differences in urinary metabolic profiles were analyzed using liquid chromatography tandem mass spectrometry with principal component analysis and partial least squares-discriminate analysis. RESULTS Compared with NAFLD patients, patients with NASH had abnormal liver function and high serum lipid concentrations. Urinary metabonomics found differences in 31 metabolites between these two groups, including differences in nucleic acids and amino acids. Pathway analysis based on overlapping metabolites showed that pathways of energy and amino acid metabolism, as well as the pentose phosphate pathway, were closely associated with pathological processes in NAFLD and NASH. CONCLUSION These findings suggested that a panel of biomarkers could distinguish between NAFLD and NASH, and could help to determine the molecular mechanism involved in the process of developing NASH from NAFLD. Urinary biomarkers may be diagnostic in these patients and could be used to assess responses to therapeutic interventions. PMID:28487615

Serial analysis of gene expression in a rat lung model of asthma.

PubMed

Yin, Lei-Miao; Jiang, Gong-Hao; Wang, Yu; Wang, Yan; Liu, Yan-Yan; Jin, Wei-Rong; Zhang, Zen; Xu, Yu-Dong; Yang, Yong-Qing

2008-11-01

The pathogenesis and molecular mechanism underlying asthma remain undetermined. The purpose of this study was to identify genes and pathways involved in the early airway response (EAR) phase of asthma by using serial analysis of gene expression (SAGE). Two SAGE tag libraries of lung tissues derived from a rat model of asthma and controls were generated. Bioinformatic analyses were carried out using the Database for Annotation, Visualization and IntegratedDiscovery Functional Annotation Tool, Gene Ontology (GO) TreeMachine and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A total of 26 552 SAGE tags of asthmatic rat lung were obtained, of which 12 221 were unique tags. Of the unique tags, 55.5% were matched with known genes. By comparison of the two libraries, 186 differentially expressed tags (P < 0.05) were identified, of which 103 were upregulated and 83 were downregulated. Using the bioinformatic tools these genes were classified into 23 functional groups, 15 KEGG pathways and 37 enriched GO categories. The bioinformatic analyses of gene distribution, enriched categories and the involvement of specific pathways in the SAGE libraries have provided information on regulatory networks of the EAR phase of asthma. Analyses of the regulated genes of interest may inform new hypotheses, increase our understanding of the disease and provide a foundation for future research.

Integrated systems biology analysis of KSHV latent infection reveals viral induction and reliance on peroxisome mediated lipid metabolism

PubMed Central

Sychev, Zoi E.; Hu, Alex; Lagunoff, Michael

2017-01-01

Kaposi’s Sarcoma associated Herpesvirus (KSHV), an oncogenic, human gamma-herpesvirus, is the etiological agent of Kaposi’s Sarcoma the most common tumor of AIDS patients world-wide. KSHV is predominantly latent in the main KS tumor cell, the spindle cell, a cell of endothelial origin. KSHV modulates numerous host cell-signaling pathways to activate endothelial cells including major metabolic pathways involved in lipid metabolism. To identify the underlying cellular mechanisms of KSHV alteration of host signaling and endothelial cell activation, we identified changes in the host proteome, phosphoproteome and transcriptome landscape following KSHV infection of endothelial cells. A Steiner forest algorithm was used to integrate the global data sets and, together with transcriptome based predicted transcription factor activity, cellular networks altered by latent KSHV were predicted. Several interesting pathways were identified, including peroxisome biogenesis. To validate the predictions, we showed that KSHV latent infection increases the number of peroxisomes per cell. Additionally, proteins involved in peroxisomal lipid metabolism of very long chain fatty acids, including ABCD3 and ACOX1, are required for the survival of latently infected cells. In summary, novel cellular pathways altered during herpesvirus latency that could not be predicted by a single systems biology platform, were identified by integrated proteomics and transcriptomics data analysis and when correlated with our metabolomics data revealed that peroxisome lipid metabolism is essential for KSHV latent infection of endothelial cells. PMID:28257516

Genome-wide association study meta-analysis identifies five new loci for systemic lupus erythematosus.

PubMed

Julià, Antonio; López-Longo, Francisco Javier; Pérez Venegas, José J; Bonàs-Guarch, Silvia; Olivé, Àlex; Andreu, José Luís; Aguirre-Zamorano, Mª Ángeles; Vela, Paloma; Nolla, Joan M; de la Fuente, José Luís Marenco; Zea, Antonio; Pego-Reigosa, José María; Freire, Mercedes; Díez, Elvira; Rodríguez-Almaraz, Esther; Carreira, Patricia; Blanco, Ricardo; Taboada, Víctor Martínez; López-Lasanta, María; Corbeto, Mireia López; Mercader, Josep M; Torrents, David; Absher, Devin; Marsal, Sara; Fernández-Nebro, Antonio

2018-05-30

Systemic lupus erythematosus (SLE) is a common systemic autoimmune disease with a complex genetic inheritance. Genome-wide association studies (GWAS) have significantly increased the number of significant loci associated with SLE risk. To date, however, established loci account for less than 30% of the disease heritability and additional risk variants have yet to be identified. Here we performed a GWAS followed by a meta-analysis to identify new genome-wide significant loci for SLE. We genotyped a cohort of 907 patients with SLE (cases) and 1524 healthy controls from Spain and performed imputation using the 1000 Genomes reference data. We tested for association using logistic regression with correction for the principal components of variation. Meta-analysis of the association results was subsequently performed on 7,110,321 variants using genetic data from a large cohort of 4036 patients with SLE and 6959 controls of Northern European ancestry. Genetic association was also tested at the pathway level after removing the effect of known risk loci using PASCAL software. We identified five new loci associated with SLE at the genome-wide level of significance (p < 5 × 10 - 8 ): GRB2, SMYD3, ST8SIA4, LAT2 and ARHGAP27. Pathway analysis revealed several biological processes significantly associated with SLE risk: B cell receptor signaling (p = 5.28 × 10 - 6 ), CTLA4 co-stimulation during T cell activation (p = 3.06 × 10 - 5 ), interleukin-4 signaling (p = 3.97 × 10 - 5 ) and cell surface interactions at the vascular wall (p = 4.63 × 10 - 5 ). Our results identify five novel loci for SLE susceptibility, and biologic pathways associated via multiple low-effect-size loci.

Transcriptome Analysis and Discovery of Genes Involved in Immune Pathways from Coelomocytes of Sea Cucumber (Apostichopus japonicus) after Vibrio splendidus Challenge.

PubMed

Gao, Qiong; Liao, Meijie; Wang, Yingeng; Li, Bin; Zhang, Zheng; Rong, Xiaojun; Chen, Guiping; Wang, Lan

2015-07-17

Vibrio splendidus is identified as one of the major pathogenic factors for the skin ulceration syndrome in sea cucumber (Apostichopus japonicus), which has vastly limited the development of the sea cucumber culture industry. In order to screen the immune genes involving Vibrio splendidus challenge in sea cucumber and explore the molecular mechanism of this process, the related transcriptome and gene expression profiling of resistant and susceptible biotypes of sea cucumber with Vibrio splendidus challenge were collected for analysis. A total of 319,455,942 trimmed reads were obtained, which were assembled into 186,658 contigs. After that, 89,891 representative contigs (without isoform) were clustered. The analysis of the gene expression profiling identified 358 differentially expression genes (DEGs) in the bacterial-resistant group, and 102 DEGs in the bacterial-susceptible group, compared with that in control group. According to the reported references and annotation information from BLAST, GO and KEGG, 30 putative bacterial-resistant genes and 19 putative bacterial-susceptible genes were identified from DEGs. The qRT-PCR results were consistent with the RNA-Seq results. Furthermore, many DGEs were involved in immune signaling related pathways, such as Endocytosis, Lysosome, MAPK, Chemokine and the ERBB signaling pathway.

Transcriptome Analysis and Discovery of Genes Involved in Immune Pathways from Coelomocytes of Sea Cucumber (Apostichopus japonicus) after Vibrio splendidus Challenge

PubMed Central

Gao, Qiong; Liao, Meijie; Wang, Yingeng; Li, Bin; Zhang, Zheng; Rong, Xiaojun; Chen, Guiping; Wang, Lan

2015-01-01

Vibrio splendidus is identified as one of the major pathogenic factors for the skin ulceration syndrome in sea cucumber (Apostichopus japonicus), which has vastly limited the development of the sea cucumber culture industry. In order to screen the immune genes involving Vibrio splendidus challenge in sea cucumber and explore the molecular mechanism of this process, the related transcriptome and gene expression profiling of resistant and susceptible biotypes of sea cucumber with Vibrio splendidus challenge were collected for analysis. A total of 319,455,942 trimmed reads were obtained, which were assembled into 186,658 contigs. After that, 89,891 representative contigs (without isoform) were clustered. The analysis of the gene expression profiling identified 358 differentially expression genes (DEGs) in the bacterial-resistant group, and 102 DEGs in the bacterial-susceptible group, compared with that in control group. According to the reported references and annotation information from BLAST, GO and KEGG, 30 putative bacterial-resistant genes and 19 putative bacterial-susceptible genes were identified from DEGs. The qRT-PCR results were consistent with the RNA-Seq results. Furthermore, many DGEs were involved in immune signaling related pathways, such as Endocytosis, Lysosome, MAPK, Chemokine and the ERBB signaling pathway. PMID:26193268

An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

PubMed

Mallik, Mrinmay Kumar

2018-02-07

Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that is indicative of their strong influence in the protein protein interaction network. Similarly the newly proposed GEADCA helped identify the transcription factors with high centrality values indicative of their key roles in transcriptional regulation. The enrichment studies provided a list of molecular functions, biological processes and biochemical pathways associated with the constructed network. The study shows how pathway based databases may be used to create and analyze a relevant protein interaction network in glioma cancer stem cells and identify the essential elements within it to gather insights into the molecular interactions that regulate the properties of glioma stem cells. How these insights may be utilized to help the development of future research towards formulation of new management strategies have been discussed from a theoretical standpoint. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reliable pre-eclampsia pathways based on multiple independent microarray data sets.

PubMed

Kawasaki, Kaoru; Kondoh, Eiji; Chigusa, Yoshitsugu; Ujita, Mari; Murakami, Ryusuke; Mogami, Haruta; Brown, J B; Okuno, Yasushi; Konishi, Ikuo

2015-02-01

Pre-eclampsia is a multifactorial disorder characterized by heterogeneous clinical manifestations. Gene expression profiling of preeclamptic placenta have provided different and even opposite results, partly due to data compromised by various experimental artefacts. Here we aimed to identify reliable pre-eclampsia-specific pathways using multiple independent microarray data sets. Gene expression data of control and preeclamptic placentas were obtained from Gene Expression Omnibus. Single-sample gene-set enrichment analysis was performed to generate gene-set activation scores of 9707 pathways obtained from the Molecular Signatures Database. Candidate pathways were identified by t-test-based screening using data sets, GSE10588, GSE14722 and GSE25906. Additionally, recursive feature elimination was applied to arrive at a further reduced set of pathways. To assess the validity of the pre-eclampsia pathways, a statistically-validated protocol was executed using five data sets including two independent other validation data sets, GSE30186, GSE44711. Quantitative real-time PCR was performed for genes in a panel of potential pre-eclampsia pathways using placentas of 20 women with normal or severe preeclamptic singleton pregnancies (n = 10, respectively). A panel of ten pathways were found to discriminate women with pre-eclampsia from controls with high accuracy. Among these were pathways not previously associated with pre-eclampsia, such as the GABA receptor pathway, as well as pathways that have already been linked to pre-eclampsia, such as the glutathione and CDKN1C pathways. mRNA expression of GABRA3 (GABA receptor pathway), GCLC and GCLM (glutathione metabolic pathway), and CDKN1C was significantly reduced in the preeclamptic placentas. In conclusion, ten accurate and reliable pre-eclampsia pathways were identified based on multiple independent microarray data sets. A pathway-based classification may be a worthwhile approach to elucidate the pathogenesis of pre-eclampsia. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Use of an activated beta-catenin to identify Wnt pathway target genes in caenorhabditis elegans, including a subset of collagen genes expressed in late larval development.

PubMed

Jackson, Belinda M; Abete-Luzi, Patricia; Krause, Michael W; Eisenmann, David M

2014-04-16

The Wnt signaling pathway plays a fundamental role during metazoan development, where it regulates diverse processes, including cell fate specification, cell migration, and stem cell renewal. Activation of the beta-catenin-dependent/canonical Wnt pathway up-regulates expression of Wnt target genes to mediate a cellular response. In the nematode Caenorhabditis elegans, a canonical Wnt signaling pathway regulates several processes during larval development; however, few target genes of this pathway have been identified. To address this deficit, we used a novel approach of conditionally activated Wnt signaling during a defined stage of larval life by overexpressing an activated beta-catenin protein, then used microarray analysis to identify genes showing altered expression compared with control animals. We identified 166 differentially expressed genes, of which 104 were up-regulated. A subset of the up-regulated genes was shown to have altered expression in mutants with decreased or increased Wnt signaling; we consider these genes to be bona fide C. elegans Wnt pathway targets. Among these was a group of six genes, including the cuticular collagen genes, bli-1 col-38, col-49, and col-71. These genes show a peak of expression in the mid L4 stage during normal development, suggesting a role in adult cuticle formation. Consistent with this finding, reduction of function for several of the genes causes phenotypes suggestive of defects in cuticle function or integrity. Therefore, this work has identified a large number of putative Wnt pathway target genes during larval life, including a small subset of Wnt-regulated collagen genes that may function in synthesis of the adult cuticle.

Microarray Analysis of Long Noncoding RNAs in Female Diabetic Peripheral Neuropathy Patients.

PubMed

Luo, Lin; Ji, Lin-Dan; Cai, Jiang-Jia; Feng, Mei; Zhou, Mi; Hu, Su-Pei; Xu, Jin; Zhou, Wen-Hua

2018-01-01

Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus (DM). Because of its controversial pathogenesis, DPN is still not diagnosed or managed properly in most patients. In this study, human lncRNA microarrays were used to identify the differentially expressed lncRNAs in DM and DPN patients, and some of the discovered lncRNAs were further validated in additional 78 samples by quantitative realtime PCR (qRT-PCR). The microarray analysis identified 446 and 1327 differentially expressed lncRNAs in DM and DPN, respectively. The KEGG pathway analysis further revealed that the differentially expressed lncRNA-coexpressed mRNAs between DPN and DM groups were significantly enriched in the MAPK signaling pathway. The lncRNA/mRNA coexpression network indicated that BDNF and TRAF2 correlated with 6 lncRNAs. The qRT-PCR confirmed the initial microarray results. These findings demonstrated that the interplay between lncRNAs and mRNA may be involved in the pathogenesis of DPN, especially the neurotrophin-MAPK signaling pathway, thus providing relevant information for future studies. © 2018 The Author(s). Published by S. Karger AG, Basel.

Transcriptome analysis of Petunia axillaris flowers reveals genes involved in morphological differentiation and metabolite transport

PubMed Central

Amano, Ikuko; Kitajima, Sakihito; Suzuki, Hideyuki; Koeduka, Takao

2018-01-01

The biosynthesis of plant secondary metabolites is associated with morphological and metabolic differentiation. As a consequence, gene expression profiles can change drastically, and primary and secondary metabolites, including intermediate and end-products, move dynamically within and between cells. However, little is known about the molecular mechanisms underlying differentiation and transport mechanisms. In this study, we performed a transcriptome analysis of Petunia axillaris subsp. parodii, which produces various volatiles in its corolla limbs and emits metabolites to attract pollinators. RNA-sequencing from leaves, buds, and limbs identified 53,243 unigenes. Analysis of differentially expressed genes, combined with gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, showed that many biological processes were highly enriched in limbs. These included catabolic processes and signaling pathways of hormones, such as gibberellins, and metabolic pathways, including phenylpropanoids and fatty acids. Moreover, we identified five transporter genes that showed high expression in limbs, and we performed spatiotemporal expression analyses and homology searches to infer their putative functions. Our systematic analysis provides comprehensive transcriptomic information regarding morphological differentiation and metabolite transport in the Petunia flower and lays the foundation for establishing the specific mechanisms that control secondary metabolite biosynthesis in plants. PMID:29902274

OVCAR-3 Spheroid-Derived Cells Display Distinct Metabolic Profiles

PubMed Central

Vermeersch, Kathleen A.; Wang, Lijuan; Mezencev, Roman; McDonald, John F.; Styczynski, Mark P.

2015-01-01

Introduction Recently, multicellular spheroids were isolated from a well-established epithelial ovarian cancer cell line, OVCAR-3, and were propagated in vitro. These spheroid-derived cells displayed numerous hallmarks of cancer stem cells, which are chemo- and radioresistant cells thought to be a significant cause of cancer recurrence and resultant mortality. Gene set enrichment analysis of expression data from the OVCAR-3 cells and the spheroid-derived putative cancer stem cells identified several metabolic pathways enriched in differentially expressed genes. Before this, there had been little previous knowledge or investigation of systems-scale metabolic differences between cancer cells and cancer stem cells, and no knowledge of such differences in ovarian cancer stem cells. Methods To determine if there were substantial metabolic changes corresponding with these transcriptional differences, we used two-dimensional gas chromatography coupled to mass spectrometry to measure the metabolite profiles of the two cell lines. Results These two cell lines exhibited significant metabolic differences in both intracellular and extracellular metabolite measurements. Principal components analysis, an unsupervised dimensional reduction technique, showed complete separation between the two cell types based on their metabolite profiles. Pathway analysis of intracellular metabolomics data revealed close overlap with metabolic pathways identified from gene expression data, with four out of six pathways found enriched in gene-level analysis also enriched in metabolite-level analysis. Some of those pathways contained multiple metabolites that were individually statistically significantly different between the two cell lines, with one of the most broadly and consistently different pathways, arginine and proline metabolism, suggesting an interesting hypothesis about cancerous and stem-like metabolic phenotypes in this pair of cell lines. Conclusions Overall, we demonstrate for the first time that metabolism in an ovarian cancer stem cell line is distinct from that of more differentiated isogenic cancer cells, supporting the potential importance of metabolism in the differences between cancer cells and cancer stem cells. PMID:25688563

In silico identification of miRNAs and their target genes and analysis of gene co-expression network in saffron (Crocus sativus L.) stigma

PubMed Central

Zinati, Zahra; Shamloo-Dashtpagerdi, Roohollah; Behpouri, Ali

2016-01-01

As an aromatic and colorful plant of substantive taste, saffron (Crocus sativus L.) owes such properties of matter to growing class of the secondary metabolites derived from the carotenoids, apocarotenoids. Regarding the critical role of microRNAs in secondary metabolic synthesis and the limited number of identified miRNAs in C. sativus, on the other hand, one may see the point how the characterization of miRNAs along with the corresponding target genes in C. sativus might expand our perspectives on the roles of miRNAs in carotenoid/apocarotenoid biosynthetic pathway. A computational analysis was used to identify miRNAs and their targets using EST (Expressed Sequence Tag) library from mature saffron stigmas. Then, a gene co- expression network was constructed to identify genes which are potentially involved in carotenoid/apocarotenoid biosynthetic pathways. EST analysis led to the identification of two putative miRNAs (miR414 and miR837-5p) along with the corresponding stem- looped precursors. To our knowledge, this is the first report on miR414 and miR837-5p in C. sativus. Co-expression network analysis indicated that miR414 and miR837-5p may play roles in C. sativus metabolic pathways and led to identification of candidate genes including six transcription factors and one protein kinase probably involved in carotenoid/apocarotenoid biosynthetic pathway. Presence of transcription factors, miRNAs and protein kinase in the network indicated multiple layers of regulation in saffron stigma. The candidate genes from this study may help unraveling regulatory networks underlying the carotenoid/apocarotenoid biosynthesis in saffron and designing metabolic engineering for enhanced secondary metabolites. PMID:28261627

Identification of potential transcriptomic markers in developing pediatric sepsis: a weighted gene co-expression network analysis and a case-control validation study.

PubMed

Li, Yiping; Li, Yanhong; Bai, Zhenjiang; Pan, Jian; Wang, Jian; Fang, Fang

2017-12-13

Sepsis represents a complex disease with the dysregulated inflammatory response and high mortality rate. The goal of this study was to identify potential transcriptomic markers in developing pediatric sepsis by a co-expression module analysis of the transcriptomic dataset. Using the R software and Bioconductor packages, we performed a weighted gene co-expression network analysis to identify co-expression modules significantly associated with pediatric sepsis. Functional interpretation (gene ontology and pathway analysis) and enrichment analysis with known transcription factors and microRNAs of the identified candidate modules were then performed. In modules significantly associated with sepsis, the intramodular analysis was further performed and "hub genes" were identified and validated by quantitative real-time PCR (qPCR) in this study. 15 co-expression modules in total were detected, and four modules ("midnight blue", "cyan", "brown", and "tan") were most significantly associated with pediatric sepsis and suggested as potential sepsis-associated modules. Gene ontology analysis and pathway analysis revealed that these four modules strongly associated with immune response. Three of the four sepsis-associated modules were also enriched with known transcription factors (false discovery rate-adjusted P < 0.05). Hub genes were identified in each of the four modules. Four of the identified hub genes (MYB proto-oncogene like 1, killer cell lectin like receptor G1, stomatin, and membrane spanning 4-domains A4A) were further validated to be differentially expressed between septic children and controls by qPCR. Four pediatric sepsis-associated co-expression modules were identified in this study. qPCR results suggest that hub genes in these modules are potential transcriptomic markers for pediatric sepsis diagnosis. These results provide novel insights into the pathogenesis of pediatric sepsis and promote the generation of diagnostic gene sets.

The expression profiling and ontology analysis of non-coding RNAs in dexamethasone induced steatosis in hepatoma cell.

PubMed

Liu, Fengqiong; Gong, Ruijie; Lv, Xiaofei; Li, Huangyuan

2018-04-15

Increasing amounts of evidence have indicated that non-coding RNAs (ncRNAs) have important regulatory potential in various biological processes. However, the contribution of ncRNAs, especially long non-coding RNAs (lncRNAs) to drug induced steatosis remain largely unknown. The aim of this study is to investigate miRNA, lncRNA and mRNA expression profiles and their potential roles in the process of drug induced steatosis. Microarray expression profiles of miRNAs, lncRNAs and mRNAs were determined in dexamethasone treated HepG2 cell as well as control cell. Differential expression, pathway and gene network analyses were developed to identify possible functional RNA molecules in dexamethasone induced steatosis. Compared with control HepG2 cell, 652 lncRNAs (528 up-regulated and 124 down-regulated), 655 mRNAs (527 upregulated and 128 down-regulated) and 114 miRNAs (55 miRNAs up-regulated and 59 down-regulated) were differentially expressed in dexamethasone treated HepG2 cell. Pathway analysis showed that the fatty acid biosynthesis, insulin resistance, PPAR signaling pathway, regulation of lipolysis in adipocytes, carbohydrate digestion and absorption, steroid hormone biosynthesis signaling pathways had a close relationship with dexamethasone induced steatosis. 10 highly dysregulated mRNAs and 20 miRNAs, which are closely related to lipid metabolism, were identified and validated by PCR, which followed by ceRNA analysis. CeRNA network analysis identified 5 lipid metabolism related genes, including CYP7A1, CYP11A1, PDK4, ABHD5, ACSL1. It also identified 12 miRNAs (miR-23a-3p, miR-519d-3p, miR-4328, miR-15b-5p etc.) and 177 lncRNAs (ENST00000508884, ENST00000608794, ENST00000568457 etc.). Our results provide a foundation and an expansive view of the roles and mechanisms of ncRNAs in dexamethasone induced steatosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis of differential gene expression by bead-based fiber-optic array in growth-hormone-secreting pituitary adenomas.

PubMed

Jiang, Zhiquan; Gui, Songbo; Zhang, Yazhuo

2010-09-01

Growth-hormone-secreting pituitary adenomas (GHomas) account for approximately 20% of all pituitary neoplasms. However, the pathogenesis of GHomas remains to be elucidated. To explore the possible pathogenesis of GHomas, we used bead-based fiber-optic arrays to examine the gene expression in five GHomas and compared them to three healthy pituitaries. Four differentially expressed genes were chosen randomly for validation by quantitative real-time reverse transcription-polymerase chain reaction. We then performed pathway analysis on the identified differentially expressed genes using the Kyoto Encyclopedia of Genes and Genomes. Array analysis showed significant increases in the expression of 353 genes and 206 expressed sequence tags (ESTs) and decreases in 565 genes and 29 ESTs. Bioinformatic analysis showed that the genes HIGD1B, HOXB2, ANGPT2, HPGD and BTG2 may play an important role in the tumorigenesis and progression of GHomas. Pathway analysis showed that the wingless-type signaling pathway and extracellular-matrix receptor interactions may play a key role in the tumorigenesis and progression of GHomas. Our data suggested that there are numerous aberrantly expressed genes and pathways involved in the pathogenesis of GHomas. Bead-based fiber-optic arrays combined with pathway analysis of differentially expressed genes appear to be a valid method for investigating the pathogenesis of tumors.

Analysis of differential gene expression by bead-based fiber-optic array in growth-hormone-secreting pituitary adenomas

PubMed Central

JIANG, ZHIQUAN; GUI, SONGBO; ZHANG, YAZHUO

2010-01-01

Growth-hormone-secreting pituitary adenomas (GHomas) account for approximately 20% of all pituitary neoplasms. However, the pathogenesis of GHomas remains to be elucidated. To explore the possible pathogenesis of GHomas, we used bead-based fiber-optic arrays to examine the gene expression in five GHomas and compared them to three healthy pituitaries. Four differentially expressed genes were chosen randomly for validation by quantitative real-time reverse transcription-polymerase chain reaction. We then performed pathway analysis on the identified differentially expressed genes using the Kyoto Encyclopedia of Genes and Genomes. Array analysis showed significant increases in the expression of 353 genes and 206 expressed sequence tags (ESTs) and decreases in 565 genes and 29 ESTs. Bioinformatic analysis showed that the genes HIGD1B, HOXB2, ANGPT2, HPGD and BTG2 may play an important role in the tumorigenesis and progression of GHomas. Pathway analysis showed that the wingless-type signaling pathway and extracellular-matrix receptor interactions may play a key role in the tumorigenesis and progression of GHomas. Our data suggested that there are numerous aberrantly expressed genes and pathways involved in the pathogenesis of GHomas. Bead-based fiber-optic arrays combined with pathway analysis of differentially expressed genes appear to be a valid method for investigating the pathogenesis of tumors. PMID:22993617

An Optimal Bahadur-Efficient Method in Detection of Sparse Signals with Applications to Pathway Analysis in Sequencing Association Studies.

PubMed

Dai, Hongying; Wu, Guodong; Wu, Michael; Zhi, Degui

2016-01-01

Next-generation sequencing data pose a severe curse of dimensionality, complicating traditional "single marker-single trait" analysis. We propose a two-stage combined p-value method for pathway analysis. The first stage is at the gene level, where we integrate effects within a gene using the Sequence Kernel Association Test (SKAT). The second stage is at the pathway level, where we perform a correlated Lancaster procedure to detect joint effects from multiple genes within a pathway. We show that the Lancaster procedure is optimal in Bahadur efficiency among all combined p-value methods. The Bahadur efficiency,[Formula: see text], compares sample sizes among different statistical tests when signals become sparse in sequencing data, i.e. ε →0. The optimal Bahadur efficiency ensures that the Lancaster procedure asymptotically requires a minimal sample size to detect sparse signals ([Formula: see text]). The Lancaster procedure can also be applied to meta-analysis. Extensive empirical assessments of exome sequencing data show that the proposed method outperforms Gene Set Enrichment Analysis (GSEA). We applied the competitive Lancaster procedure to meta-analysis data generated by the Global Lipids Genetics Consortium to identify pathways significantly associated with high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, and total cholesterol.

A comparative intracellular proteomic profiling of Pseudomonas aeruginosa strain ASP-53 grown on pyrene or glucose as sole source of carbon and identification of some key enzymes of pyrene biodegradation pathway.

PubMed

Mukherjee, Ashis K; Bhagowati, Pabitra; Biswa, Bhim Bahadur; Chanda, Abhishek; Kalita, Bhargab

2017-09-07

Pseudomonas aeruginosa strain ASP-53, isolated from a petroleum oil-contaminated soil sample, was found to be an efficient degrader of pyrene. PCR amplification of selected hydrocarbon catabolic genes (alkB gene, which encodes for monooxygenase, and the C12O, C23O, and PAH-RHDα genes encoding for the dioxygenase enzyme) from the genomic DNA of P. aeruginosa strain ASP-53 suggested its hydrocarbon degradation potential. The GC-MS analysis demonstrated 30.1% pyrene degradation by P. aeruginosa strain ASP-53 after 144h of incubation at pH6.5, 37°C. Expressions of 115 and 196 intracellular proteins were unambiguously identified and quantitated by shotgun proteomics analysis when the isolate was grown in medium containing pyrene and glucose, respectively. The pyrene-induced uniquely expressed and up-regulated proteins in P. aeruginosa strain ASP-53 in addition to substrate (pyrene) metabolism are also likely to be associated with different cellular functions for example-related to protein folding (molecular chaperone), stress response, metabolism of carbohydrate, proteins and amino acids, and fatty acids; transport of metabolites, energy generation such as ATP synthesis, electron transport and nitrate assimilation, and other oxidation-reduction reactions. Proteomic analyses identified some important enzymes involved in pyrene degradation by P. aeruginosa ASP-53 which shows that this bacterium follows the salicylate pathway of pyrene degradation. This study is the first report on proteomic analysis of pyrene biodegradation pathway by Pseudomonas aeruginosa, isolated from a petroleum-oil contaminated soil sample. The pathway displays partial similarity with deduced pyrene degradation mechanisms of Mycobacterium vanbaalenii PYR-1. The GC-MS analysis as well as PCR amplification of hydrocarbon catabolic genes substantiated the potency of the bacterium under study to effectively degrade high molecular weight, toxic PAH such as pyrene for its filed scale bioremediation experiments. The proteomics approach (LC-MS/MS analysis) identified the differentially regulated intracellular proteins of the isolate P. aeruginosa ASP-53 when grown in pyrene medium. This study identified some important pyrene biodegradation enzymes in Pseudomonas aeruginosa ASP-53 and highlights that the bacterium follows salicylate pathway for pyrene degradation. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptation Pathway of Low Impact Development Planning under Climate Change for a Sustainable Rural Community

NASA Astrophysics Data System (ADS)

Chen, P. Y.; Tung, C. P.

2016-12-01

The study focuses on developing the methodology of adaptation pathway for storm water management in a community scale. Following previous results on adaptation procedures including problem and goal setup, current risk assessment and analysis, future risk assessment and analysis, and adaptation options identification and evaluation, the study aims at analyzing adaptation pathway planning and implementation, namely the fifth step, for applying low impact development (LID). Based on the efficacy analyses of the feasible adaptation options, an adaptation pathway map can be build. Each pathway is a combination of the adaptation measures arranged in certain order. The developed adaptation pathway map visualizes the relative effectiveness and the connection of the adaptation measures. In addition, the tipping points of the system can be clearly identified and the triggers can be defined accordingly. There are multiple choices of pathways in an adaptation pathway map, which can be referred as pathway candidates. To ensure the applicability and operability, the methodology of adaptation pathway analysis is applied to a case study. Required information for developing an adaptation pathway map includes the scores of the adaptation options on the criteria, namely the effects, costs, immediacy, and side effect. Feasible adaptation options for the design case are dredging, pipeline expansion, pumping station, LID and detention pond. By ranking the options according to the criteria, LID is found dominating dredging and pumping station in this case. The information of the pathway candidates can be further used by the stakeholders to select the most suitable and promising pathway.

genome-wide association and metabolic pathway analysis of corn earworm resistance in maize

Treesearch

Marilyn L. Warburton; Erika D. Womack; Juliet D. Tang; Adam Thrash; J. Spencer Smith; Wenwei Xu; Seth C. Murray; W. Paul Williams

2018-01-01

Maize (Zea mays mays L.) is a staple crop of economic, industrial, and food security importance. Damage to the growing ears by corn earworm [Helicoverpa zea (Boddie)] is a major economic burden and increases secondary fungal infections and mycotoxin levels. To identify biochemical pathways associated with native resistance mechanisms, a genome-wide...

Uncovering transcription factor and microRNA risk regulatory pathways associated with osteoarthritis by network analysis.

PubMed

Song, Zhenhua; Zhang, Chi; He, Lingxiao; Sui, Yanfang; Lin, Xiafei; Pan, Jingjing

2018-06-12

Osteoarthritis (OA) is the most common form of joint disease. The development of inflammation have been considered to play a key role during the progression of OA. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, deciphering these risk regulatory pathways is critical for elucidating the mechanisms underlying OA. We constructed an OA-specific regulatory network by integrating comprehensive curated transcription and post-transcriptional resource involving transcription factor (TF) and microRNA (miRNA). To deepen our understanding of underlying molecular mechanisms of OA, we developed an integrated systems approach to identify OA-specific risk regulatory pathways. In this study, we identified 89 significantly differentially expressed genes between normal and inflamed areas of OA patients. We found the OA-specific regulatory network was a standard scale-free network with small-world properties. It significant enriched many immune response-related functions including leukocyte differentiation, myeloid differentiation and T cell activation. Finally, 141 risk regulatory pathways were identified based on OA-specific regulatory network, which contains some known regulator of OA. The risk regulatory pathways may provide clues for the etiology of OA and be a potential resource for the discovery of novel OA-associated disease genes. Copyright © 2018 Elsevier Inc. All rights reserved.

Identification of transcriptional factors and key genes in primary osteoporosis by DNA microarray.

PubMed

Xie, Wengui; Ji, Lixin; Zhao, Teng; Gao, Pengfei

2015-05-09

A number of genes have been identified to be related with primary osteoporosis while less is known about the comprehensive interactions between regulating genes and proteins. We aimed to identify the differentially expressed genes (DEGs) and regulatory effects of transcription factors (TFs) involved in primary osteoporosis. The gene expression profile GSE35958 was obtained from Gene Expression Omnibus database, including 5 primary osteoporosis and 4 normal bone tissues. The differentially expressed genes between primary osteoporosis and normal bone tissues were identified by the same package in R language. The TFs of these DEGs were predicted with the Essaghir A method. DAVID (The Database for Annotation, Visualization and Integrated Discovery) was applied to perform the GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis of DEGs. After analyzing regulatory effects, a regulatory network was built between TFs and the related DEGs. A total of 579 DEGs was screened, including 310 up-regulated genes and 269 down-regulated genes in primary osteoporosis samples. In GO terms, more up-regulated genes were enriched in transcription regulator activity, and secondly in transcription factor activity. A total 10 significant pathways were enriched in KEGG analysis, including colorectal cancer, Wnt signaling pathway, Focal adhesion, and MAPK signaling pathway. Moreover, total 7 TFs were enriched, of which CTNNB1, SP1, and TP53 regulated most up-regulated DEGs. The discovery of the enriched TFs might contribute to the understanding of the mechanism of primary osteoporosis. Further research on genes and TFs related to the WNT signaling pathway and MAPK pathway is urgent for clinical diagnosis and directing treatment of primary osteoporosis.

iTRAQ proteomics analysis reveals that PI3K is highly associated with bupivacaine-induced neurotoxicity pathways.

PubMed

Zhao, Wei; Liu, Zhongjie; Yu, Xujiao; Lai, Luying; Li, Haobo; Liu, Zipeng; Li, Le; Jiang, Shan; Xia, Zhengyuan; Xu, Shi-yuan

2016-02-01

Bupivacaine, a commonly used local anesthetic, has potential neurotoxicity through diverse signaling pathways. However, the key mechanism of bupivacaine-induced neurotoxicity remains unclear. Cultured human SH-SY5Y neuroblastoma cells were treated (bupivacaine) or untreated (control) with bupivacaine for 24 h. Compared to the control group, bupivacaine significantly increased cyto-inhibition, cellular reactive oxygen species, DNA damage, mitochondrial injury, apoptosis (increased TUNEL-positive cells, cleaved caspase 3, and Bcl-2/Bax), and activated autophagy (enhanced LC3II/LC3I ratio). To explore changes in protein expression and intercommunication among the pathways involved in bupivacaine-induced neurotoxicity, an 8-plex iTRAQ proteomic technique and bioinformatics analysis were performed. Compared to the control group, 241 differentially expressed proteins were identified, of which, 145 were up-regulated and 96 were down-regulated. Bioinformatics analysis of the cross-talk between the significant proteins with altered expression in bupivacaine-induced neurotoxicity indicated that phosphatidyl-3-kinase (PI3K) was the most frequently targeted protein in each of the interactions. We further confirmed these results by determining the downstream targets of the identified signaling pathways (PI3K, Akt, FoxO1, Erk, and JNK). In conclusion, our study demonstrated that PI3K may play a central role in contacting and regulating the signaling pathways that contribute to bupivacaine-induced neurotoxicity. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterization of the transcriptome profiles related to globin gene switching during in vitro erythroid maturation

PubMed Central

2012-01-01

Background The fetal and adult globin genes in the human β-globin cluster on chromosome 11 are sequentially expressed to achieve normal hemoglobin switching during human development. The pharmacological induction of fetal γ-globin (HBG) to replace abnormal adult sickle βS-globin is a successful strategy to treat sickle cell disease; however the molecular mechanism of γ-gene silencing after birth is not fully understood. Therefore, we performed global gene expression profiling using primary erythroid progenitors grown from human peripheral blood mononuclear cells to characterize gene expression patterns during the γ-globin to β-globin (γ/β) switch observed throughout in vitro erythroid differentiation. Results We confirmed erythroid maturation in our culture system using cell morphologic features defined by Giemsa staining and the γ/β-globin switch by reverse transcription-quantitative PCR (RT-qPCR) analysis. We observed maximal γ-globin expression at day 7 with a switch to a predominance of β-globin expression by day 28 and the γ/β-globin switch occurred around day 21. Expression patterns for transcription factors including GATA1, GATA2, KLF1 and NFE2 confirmed our system produced the expected pattern of expression based on the known function of these factors in globin gene regulation. Subsequent gene expression profiling was performed with RNA isolated from progenitors harvested at day 7, 14, 21, and 28 in culture. Three major gene profiles were generated by Principal Component Analysis (PCA). For profile-1 genes, where expression decreased from day 7 to day 28, we identified 2,102 genes down-regulated > 1.5-fold. Ingenuity pathway analysis (IPA) for profile-1 genes demonstrated involvement of the Cdc42, phospholipase C, NF-Kβ, Interleukin-4, and p38 mitogen activated protein kinase (MAPK) signaling pathways. Transcription factors known to be involved in γ-and β-globin regulation were identified. The same approach was used to generate profile-2 genes where expression was up-regulated over 28 days in culture. IPA for the 2,437 genes with > 1.5-fold induction identified the mitotic roles of polo-like kinase, aryl hydrocarbon receptor, cell cycle control, and ATM (Ataxia Telangiectasia Mutated Protein) signaling pathways; transcription factors identified included KLF1, GATA1 and NFE2 among others. Finally, profile-3 was generated from 1,579 genes with maximal expression at day 21, around the time of the γ/β-globin switch. IPA identified associations with cell cycle control, ATM, and aryl hydrocarbon receptor signaling pathways. Conclusions The transcriptome analysis completed with erythroid progenitors grown in vitro identified groups of genes with distinct expression profiles, which function in metabolic pathways associated with cell survival, hematopoiesis, blood cells activation, and inflammatory responses. This study represents the first report of a transcriptome analysis in human primary erythroid progenitors to identify transcription factors involved in hemoglobin switching. Our results also demonstrate that the in vitro liquid culture system is an excellent model to define mechanisms of global gene expression and the DNA-binding protein and signaling pathways involved in globin gene regulation. PMID:22537182

PaintOmics 3: a web resource for the pathway analysis and visualization of multi-omics data.

PubMed

Hernández-de-Diego, Rafael; Tarazona, Sonia; Martínez-Mira, Carlos; Balzano-Nogueira, Leandro; Furió-Tarí, Pedro; Pappas, Georgios J; Conesa, Ana

2018-05-25

The increasing availability of multi-omic platforms poses new challenges to data analysis. Joint visualization of multi-omics data is instrumental in better understanding interconnections across molecular layers and in fully utilizing the multi-omic resources available to make biological discoveries. We present here PaintOmics 3, a web-based resource for the integrated visualization of multiple omic data types onto KEGG pathway diagrams. PaintOmics 3 combines server-end capabilities for data analysis with the potential of modern web resources for data visualization, providing researchers with a powerful framework for interactive exploration of their multi-omics information. Unlike other visualization tools, PaintOmics 3 covers a comprehensive pathway analysis workflow, including automatic feature name/identifier conversion, multi-layered feature matching, pathway enrichment, network analysis, interactive heatmaps, trend charts, and more. It accepts a wide variety of omic types, including transcriptomics, proteomics and metabolomics, as well as region-based approaches such as ATAC-seq or ChIP-seq data. The tool is freely available at www.paintomics.org.

Applying Multivariate Adaptive Splines to Identify Genes With Expressions Varying After Diagnosis in Microarray Experiments.

PubMed

Duan, Fenghai; Xu, Ye

2017-01-01

To analyze a microarray experiment to identify the genes with expressions varying after the diagnosis of breast cancer. A total of 44 928 probe sets in an Affymetrix microarray data publicly available on Gene Expression Omnibus from 249 patients with breast cancer were analyzed by the nonparametric multivariate adaptive splines. Then, the identified genes with turning points were grouped by K-means clustering, and their network relationship was subsequently analyzed by the Ingenuity Pathway Analysis. In total, 1640 probe sets (genes) were reliably identified to have turning points along with the age at diagnosis in their expression profiling, of which 927 expressed lower after turning points and 713 expressed higher after the turning points. K-means clustered them into 3 groups with turning points centering at 54, 62.5, and 72, respectively. The pathway analysis showed that the identified genes were actively involved in various cancer-related functions or networks. In this article, we applied the nonparametric multivariate adaptive splines method to a publicly available gene expression data and successfully identified genes with expressions varying before and after breast cancer diagnosis.

Applying meta-pathway analyses through metagenomics to identify the functional properties of the major bacterial communities of a single spontaneous cocoa bean fermentation process sample.

PubMed

Illeghems, Koen; Weckx, Stefan; De Vuyst, Luc

2015-09-01

A high-resolution functional metagenomic analysis of a representative single sample of a Brazilian spontaneous cocoa bean fermentation process was carried out to gain insight into its bacterial community functioning. By reconstruction of microbial meta-pathways based on metagenomic data, the current knowledge about the metabolic capabilities of bacterial members involved in the cocoa bean fermentation ecosystem was extended. Functional meta-pathway analysis revealed the distribution of the metabolic pathways between the bacterial members involved. The metabolic capabilities of the lactic acid bacteria present were most associated with the heterolactic fermentation and citrate assimilation pathways. The role of Enterobacteriaceae in the conversion of substrates was shown through the use of the mixed-acid fermentation and methylglyoxal detoxification pathways. Furthermore, several other potential functional roles for Enterobacteriaceae were indicated, such as pectinolysis and citrate assimilation. Concerning acetic acid bacteria, metabolic pathways were partially reconstructed, in particular those related to responses toward stress, explaining their metabolic activities during cocoa bean fermentation processes. Further, the in-depth metagenomic analysis unveiled functionalities involved in bacterial competitiveness, such as the occurrence of CRISPRs and potential bacteriocin production. Finally, comparative analysis of the metagenomic data with bacterial genomes of cocoa bean fermentation isolates revealed the applicability of the selected strains as functional starter cultures. Copyright © 2015 Elsevier Ltd. All rights reserved.

Molten Carbonate and Phosphoric Acid Stationary Fuel Cells: Overview and Gap Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Remick, R.; Wheeler, D.

2010-09-01

This report describes the technical and cost gap analysis performed to identify pathways for reducing the costs of molten carbonate fuel cell (MCFC) and phosphoric acid fuel cell (PAFC) stationary fuel cell power plants.

Application of isotope labeling experiments and (13)C flux analysis to enable rational pathway engineering.

PubMed

McAtee, Allison G; Jazmin, Lara J; Young, Jamey D

2015-12-01

Isotope labeling experiments (ILEs) and (13)C flux analysis provide actionable information for metabolic engineers to identify knockout, overexpression, and/or media optimization targets. ILEs have been used in both academic and industrial labs to increase product formation, discover novel metabolic functions in previously uncharacterized organisms, and enhance the metabolic efficiency of host cell factories. This review highlights specific examples of how ILEs have been used in conjunction with enzyme or metabolic engineering to elucidate host cell metabolism and improve product titer, rate, or yield in a directed manner. We discuss recent progress and future opportunities involving the use of ILEs and (13)C flux analysis to characterize non-model host organisms and to identify and subsequently eliminate wasteful byproduct pathways or metabolic bottlenecks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

PubMed

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

Transcriptomic Analysis of the Association Between Diabetes Mellitus and Myocardial Infarction.

PubMed

Song, Lijuan; You, Wenjun; Wang, Peng; Li, Feng; Liu, Huakun

2018-06-11

Diabetes mellitus (DM) is a major risk factor for coronary artery disease (CAD), and the complications of CAD are the leading cause of deaths among people with DM. Herein, this study aims to identify the common genes and pathways between diabetes and myocardial infarction (MI) to provide more clues for the related mechanism studies. Differentially expressed genes (DEGs) were identified using the cutoff (|log2(fold change)|>0.45 and P value<0.05) by the analysis of online datasets (GSE9006 and GSE48060) related to DM and MI respectively. Moreover, the overlapped DEGs between DM and MI were identified, followed by enriched Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. And the independent patient RNA samples were collected for qRT-PCR validation of the mRNA expression of these overlapped genes. PI3, ACSL1, MMD and MMP were altered in both T1DM and MI, and they were highly related to "regulation of cellular protein metabolic process". Meanwhile, six genes were identified in both T2DM and MI, which are ADM, NFIL3, PI3, SLPI, ACSL1 and MMP9 and significantly related to "negative regulation of endopeptidase activity". And the expression of these genes were validated. In summary, we identified the common DEGs and pathways between T1DM or T2DM and MI, and further validated the changes of those DEGs, providing some clues for mechanism study and potentially therapeutic targets. © Georg Thieme Verlag KG Stuttgart · New York.

Multivariate inference of pathway activity in host immunity and response to therapeutics

PubMed Central

Goel, Gautam; Conway, Kara L.; Jaeger, Martin; Netea, Mihai G.; Xavier, Ramnik J.

2014-01-01

Developing a quantitative view of how biological pathways are regulated in response to environmental factors is central for understanding of disease phenotypes. We present a computational framework, named Multivariate Inference of Pathway Activity (MIPA), which quantifies degree of activity induced in a biological pathway by computing five distinct measures from transcriptomic profiles of its member genes. Statistical significance of inferred activity is examined using multiple independent self-contained tests followed by a competitive analysis. The method incorporates a new algorithm to identify a subset of genes that may regulate the extent of activity induced in a pathway. We present an in-depth evaluation of specificity, robustness, and reproducibility of our method. We benchmarked MIPA's false positive rate at less than 1%. Using transcriptomic profiles representing distinct physiological and disease states, we illustrate applicability of our method in (i) identifying gene–gene interactions in autophagy-dependent response to Salmonella infection, (ii) uncovering gene–environment interactions in host response to bacterial and viral pathogens and (iii) identifying driver genes and processes that contribute to wound healing and response to anti-TNFα therapy. We provide relevant experimental validation that corroborates the accuracy and advantage of our method. PMID:25147207

Differential protein-coding gene and long noncoding RNA expression in smoking-related lung squamous cell carcinoma.

PubMed

Li, Shicheng; Sun, Xiao; Miao, Shuncheng; Liu, Jia; Jiao, Wenjie

2017-11-01

Cigarette smoking is one of the greatest preventable risk factors for developing cancer, and most cases of lung squamous cell carcinoma (lung SCC) are associated with smoking. The pathogenesis mechanism of tumor progress is unclear. This study aimed to identify biomarkers in smoking-related lung cancer, including protein-coding gene, long noncoding RNA, and transcription factors. We selected and obtained messenger RNA microarray datasets and clinical data from the Gene Expression Omnibus database to identify gene expression altered by cigarette smoking. Integrated bioinformatic analysis was used to clarify biological functions of the identified genes, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, the construction of a protein-protein interaction network, transcription factor, and statistical analyses. Subsequent quantitative real-time PCR was utilized to verify these bioinformatic analyses. Five hundred and ninety-eight differentially expressed genes and 21 long noncoding RNA were identified in smoking-related lung SCC. GO and KEGG pathway analysis showed that identified genes were enriched in the cancer-related functions and pathways. The protein-protein interaction network revealed seven hub genes identified in lung SCC. Several transcription factors and their binding sites were predicted. The results of real-time quantitative PCR revealed that AURKA and BIRC5 were significantly upregulated and LINC00094 was downregulated in the tumor tissues of smoking patients. Further statistical analysis indicated that dysregulation of AURKA, BIRC5, and LINC00094 indicated poor prognosis in lung SCC. Protein-coding genes AURKA, BIRC5, and LINC00094 could be biomarkers or therapeutic targets for smoking-related lung SCC. © 2017 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling

PubMed Central

Fang, H; Tong, W; Perkins, R; Shi, L; Hong, H; Cao, X; Xie, Q; Yim, SH; Ward, JM; Pitot, HC; Dragan, YP

2005-01-01

Background The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in animal models. These types of studies have the potential to greatly enhance our understanding of diseases such as liver cancer in humans. Genes co-expressed across multiple species are most likely to have conserved functions. We have used various bioinformatics approaches to examine microarray expression profiles from liver neoplasms that arise in albumin-SV40 transgenic rats to elucidate genes, chromosome aberrations and pathways that might be associated with human liver cancer. Results In this study, we first identified 2223 differentially expressed genes by comparing gene expression profiles for two control, two adenoma and two carcinoma samples using an F-test. These genes were subsequently mapped to the rat chromosomes using a novel visualization tool, the Chromosome Plot. Using the same plot, we further mapped the significant genes to orthologous chromosomal locations in human and mouse. Many genes expressed in rat 1q that are amplified in rat liver cancer map to the human chromosomes 10, 11 and 19 and to the mouse chromosomes 7, 17 and 19, which have been implicated in studies of human and mouse liver cancer. Using Comparative Genomics Microarray Analysis (CGMA), we identified regions of potential aberrations in human. Lastly, a pathway analysis was conducted to predict altered human pathways based on statistical analysis and extrapolation from the rat data. All of the identified pathways have been known to be important in the etiology of human liver cancer, including cell cycle control, cell growth and differentiation, apoptosis, transcriptional regulation, and protein metabolism. Conclusion The study demonstrates that the hepatic gene expression profiles from the albumin-SV40 transgenic rat model revealed genes, pathways and chromosome alterations consistent with experimental and clinical research in human liver cancer. The bioinformatics tools presented in this paper are essential for cross species extrapolation and mapping of microarray data, its analysis and interpretation. PMID:16026603

A Canonical Correlation Analysis of AIDS Restriction Genes and Metabolic Pathways Identifies Purine Metabolism as a Key Cooperator.

PubMed

Ye, Hanhui; Yuan, Jinjin; Wang, Zhengwu; Huang, Aiqiong; Liu, Xiaolong; Han, Xiao; Chen, Yahong

2016-01-01

Human immunodeficiency virus causes a severe disease in humans, referred to as immune deficiency syndrome. Studies on the interaction between host genetic factors and the virus have revealed dozens of genes that impact diverse processes in the AIDS disease. To resolve more genetic factors related to AIDS, a canonical correlation analysis was used to determine the correlation between AIDS restriction and metabolic pathway gene expression. The results show that HIV-1 postentry cellular viral cofactors from AIDS restriction genes are coexpressed in human transcriptome microarray datasets. Further, the purine metabolism pathway comprises novel host factors that are coexpressed with AIDS restriction genes. Using a canonical correlation analysis for expression is a reliable approach to exploring the mechanism underlying AIDS.

Investigating ego modules and pathways in osteosarcoma by integrating the EgoNet algorithm and pathway analysis.

PubMed

Chen, X Y; Chen, Y H; Zhang, L J; Wang, Y; Tong, Z C

2017-02-16

Osteosarcoma (OS) is the most common primary bone malignancy, but current therapies are far from effective for all patients. A better understanding of the pathological mechanism of OS may help to achieve new treatments for this tumor. Hence, the objective of this study was to investigate ego modules and pathways in OS utilizing EgoNet algorithm and pathway-related analysis, and reveal pathological mechanisms underlying OS. The EgoNet algorithm comprises four steps: constructing background protein-protein interaction (PPI) network (PPIN) based on gene expression data and PPI data; extracting differential expression network (DEN) from the background PPIN; identifying ego genes according to topological features of genes in reweighted DEN; and collecting ego modules using module search by ego gene expansion. Consequently, we obtained 5 ego modules (Modules 2, 3, 4, 5, and 6) in total. After applying the permutation test, all presented statistical significance between OS and normal controls. Finally, pathway enrichment analysis combined with Reactome pathway database was performed to investigate pathways, and Fisher's exact test was conducted to capture ego pathways for OS. The ego pathway for Module 2 was CLEC7A/inflammasome pathway, while for Module 3 a tetrasaccharide linker sequence was required for glycosaminoglycan (GAG) synthesis, and for Module 6 was the Rho GTPase cycle. Interestingly, genes in Modules 4 and 5 were enriched in the same pathway, the 2-LTR circle formation. In conclusion, the ego modules and pathways might be potential biomarkers for OS therapeutic index, and give great insight of the molecular mechanism underlying this tumor.

Investigating ego modules and pathways in osteosarcoma by integrating the EgoNet algorithm and pathway analysis

PubMed Central

Chen, X.Y.; Chen, Y.H.; Zhang, L.J.; Wang, Y.; Tong, Z.C.

2017-01-01

Osteosarcoma (OS) is the most common primary bone malignancy, but current therapies are far from effective for all patients. A better understanding of the pathological mechanism of OS may help to achieve new treatments for this tumor. Hence, the objective of this study was to investigate ego modules and pathways in OS utilizing EgoNet algorithm and pathway-related analysis, and reveal pathological mechanisms underlying OS. The EgoNet algorithm comprises four steps: constructing background protein-protein interaction (PPI) network (PPIN) based on gene expression data and PPI data; extracting differential expression network (DEN) from the background PPIN; identifying ego genes according to topological features of genes in reweighted DEN; and collecting ego modules using module search by ego gene expansion. Consequently, we obtained 5 ego modules (Modules 2, 3, 4, 5, and 6) in total. After applying the permutation test, all presented statistical significance between OS and normal controls. Finally, pathway enrichment analysis combined with Reactome pathway database was performed to investigate pathways, and Fisher's exact test was conducted to capture ego pathways for OS. The ego pathway for Module 2 was CLEC7A/inflammasome pathway, while for Module 3 a tetrasaccharide linker sequence was required for glycosaminoglycan (GAG) synthesis, and for Module 6 was the Rho GTPase cycle. Interestingly, genes in Modules 4 and 5 were enriched in the same pathway, the 2-LTR circle formation. In conclusion, the ego modules and pathways might be potential biomarkers for OS therapeutic index, and give great insight of the molecular mechanism underlying this tumor. PMID:28225867

Transcriptome mining and in silico structural and functional analysis of ascorbic acid and tartaric acid biosynthesis pathway enzymes in rose-scanted geranium.

PubMed

Narnoliya, Lokesh K; Sangwan, Rajender S; Singh, Sudhir P

2018-06-01

Rose-scented geranium (Pelargonium sp.) is widely known as aromatic and medicinal herb, accumulating specialized metabolites of high economic importance, such as essential oils, ascorbic acid, and tartaric acid. Ascorbic acid and tartaric acid are multifunctional metabolites of human value to be used as vital antioxidants and flavor enhancing agents in food products. No information is available related to the structural and functional properties of the enzymes involved in ascorbic acid and tartaric acid biosynthesis in rose-scented geranium. In the present study, transcriptome mining was done to identify full-length genes, followed by their bioinformatic and molecular modeling investigations and understanding of in silico structural and functional properties of these enzymes. Evolutionary conserved domains were identified in the pathway enzymes. In silico physicochemical characterization of the catalytic enzymes revealed isoelectric point (pI), instability index, aliphatic index, and grand average hydropathy (GRAVY) values of the enzymes. Secondary structural prediction revealed abundant proportion of alpha helix and random coil confirmations in the pathway enzymes. Three-dimensional homology models were developed for these enzymes. The predicted structures showed significant structural similarity with their respective templates in root mean square deviation analysis. Ramachandran plot analysis of the modeled enzymes revealed that more than 84% of the amino acid residues were within the favored regions. Further, functionally important residues were identified corresponding to catalytic sites located in the enzymes. To, our best knowledge, this is the first report which provides a foundation on functional annotation and structural determination of ascorbic acid and tartaric acid pathway enzymes in rose-scanted geranium.

Transcriptome profiling in engrailed-2 mutant mice reveals common molecular pathways associated with autism spectrum disorders.

PubMed

Sgadò, Paola; Provenzano, Giovanni; Dassi, Erik; Adami, Valentina; Zunino, Giulia; Genovesi, Sacha; Casarosa, Simona; Bozzi, Yuri

2013-12-19

Transcriptome analysis has been used in autism spectrum disorder (ASD) to unravel common pathogenic pathways based on the assumption that distinct rare genetic variants or epigenetic modifications affect common biological pathways. To unravel recurrent ASD-related neuropathological mechanisms, we took advantage of the En2-/- mouse model and performed transcriptome profiling on cerebellar and hippocampal adult tissues. Cerebellar and hippocampal tissue samples from three En2-/- and wild type (WT) littermate mice were assessed for differential gene expression using microarray hybridization followed by RankProd analysis. To identify functional categories overrepresented in the differentially expressed genes, we used integrated gene-network analysis, gene ontology enrichment and mouse phenotype ontology analysis. Furthermore, we performed direct enrichment analysis of ASD-associated genes from the SFARI repository in our differentially expressed genes. Given the limited number of animals used in the study, we used permissive criteria and identified 842 differentially expressed genes in En2-/- cerebellum and 862 in the En2-/- hippocampus. Our functional analysis revealed that the molecular signature of En2-/- cerebellum and hippocampus shares convergent pathological pathways with ASD, including abnormal synaptic transmission, altered developmental processes and increased immune response. Furthermore, when directly compared to the repository of the SFARI database, our differentially expressed genes in the hippocampus showed enrichment of ASD-associated genes significantly higher than previously reported. qPCR was performed for representative genes to confirm relative transcript levels compared to those detected in microarrays. Despite the limited number of animals used in the study, our bioinformatic analysis indicates the En2-/- mouse is a valuable tool for investigating molecular alterations related to ASD.

Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ba, Qian; Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing; Li, Junyang

2015-03-01

Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong tomore » the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.« less

Novel insights into systemic autoimmune rheumatic diseases using shared molecular signatures and an integrative analysis.

PubMed

Hudson, Marie; Bernatsky, Sasha; Colmegna, Ines; Lora, Maximilien; Pastinen, Tomi; Klein Oros, Kathleen; Greenwood, Celia M T

2017-06-03

We undertook this study to identify DNA methylation signatures of three systemic autoimmune rheumatic diseases (SARDs), namely rheumatoid arthritis, systemic lupus erythematosus, and systemic sclerosis, compared to healthy controls. Using a careful design to minimize confounding, we restricted our study to subjects with incident disease and performed our analyses on purified CD4 + T cells, key effector cells in SARD. We identified differentially methylated (using the Illumina Infinium HumanMethylation450 BeadChip array) and expressed (using the Illumina TruSeq stranded RNA-seq protocol) sites between cases and controls, and investigated the biological significance of this SARD signature using gene annotation databases. We recruited 13 seropositive rheumatoid arthritis, 19 systemic sclerosis, 12 systemic lupus erythematosus subjects, and 8 healthy controls. We identified 33 genes that were both differentially methylated and expressed (26 over- and 7 under-expressed) in SARD cases versus controls. The most highly overexpressed gene was CD1C (log fold change in expression = 1.85, adjusted P value = 0.009). In functional analysis (Ingenuity Pathway Analysis), the top network identified was lipid metabolism, molecular transport, small molecule biochemistry. The top canonical pathways included the mitochondrial L-carnitine shuttle pathway (P = 5E-03) and PTEN signaling (P = 8E-03). The top upstream regulator was HNF4A (P = 3E-05). This novel SARD signature contributes to ongoing work to further our understanding of the molecular mechanisms underlying SARD and provides novel targets of interest.

Biomarkers of the Hedgehog/Smoothened pathway in healthy volunteers

PubMed Central

Kadam, Sunil K; Patel, Bharvin K R; Jones, Emma; Nguyen, Tuan S; Verma, Lalit K; Landschulz, Katherine T; Stepaniants, Sergey; Li, Bin; Brandt, John T; Brail, Leslie H

2012-01-01

The Hedgehog (Hh) pathway is involved in oncogenic transformation and tumor maintenance. The primary objective of this study was to select surrogate tissue to measure messenger ribonucleic acid (mRNA) levels of Hh pathway genes for measurement of pharmacodynamic effect. Expression of Hh pathway specific genes was measured by quantitative real time polymerase chain reaction (qRT-PCR) and global gene expression using Affymetrix U133 microarrays. Correlations were made between the expression of specific genes determined by qRT-PCR and normalized microarray data. Gene ontology analysis using microarray data for a broader set of Hh pathway genes was performed to identify additional Hh pathway-related markers in the surrogate tissue. RNA extracted from blood, hair follicle, and skin obtained from healthy subjects was analyzed by qRT-PCR for 31 genes, whereas 8 samples were analyzed for a 7-gene subset. Twelve sample sets, each with ≤500 ng total RNA derived from hair, skin, and blood, were analyzed using Affymetrix U133 microarrays. Transcripts for several Hh pathway genes were undetectable in blood using qRT-PCR. Skin was the most desirable matrix, followed by hair follicle. Whether processed by robust multiarray average or microarray suite 5 (MAS5), expression patterns of individual samples showed co-clustered signals; both normalization methods were equally effective for unsupervised analysis. The MAS5- normalized probe sets appeared better suited for supervised analysis. This work provides the basis for selection of a surrogate tissue and an expression analysis-based approach to evaluate pathway-related genes as markers of pharmacodynamic effect with novel inhibitors of the Hh pathway. PMID:22611475

Joint Identification of Genetic Variants for Physical Activity in Korean Population

PubMed Central

Kim, Jayoun; Kim, Jaehee; Min, Haesook; Oh, Sohee; Kim, Yeonjung; Lee, Andy H.; Park, Taesung

2014-01-01

There has been limited research on genome-wide association with physical activity (PA). This study ascertained genetic associations between PA and 344,893 single nucleotide polymorphism (SNP) markers in 8842 Korean samples. PA data were obtained from a validated questionnaire that included information on PA intensity and duration. Metabolic equivalent of tasks were calculated to estimate the total daily PA level for each individual. In addition to single- and multiple-SNP association tests, a pathway enrichment analysis was performed to identify the biological significance of SNP markers. Although no significant SNP was found at genome-wide significance level via single-SNP association tests, 59 genetic variants mapped to 76 genes were identified via a multiple SNP approach using a bootstrap selection stability measure. Pathway analysis for these 59 variants showed that maturity onset diabetes of the young (MODY) was enriched. Joint identification of SNPs could enable the identification of multiple SNPs with good predictive power for PA and a pathway enriched for PA. PMID:25026172

The Future of Molecular Analysis in Melanoma: Diagnostics to Direct Molecularly Targeted Therapy.

PubMed

Akabane, Hugo; Sullivan, Ryan J

2016-02-01

Melanoma is a malignancy of pigment-producing cells that is driven by a variety of genetic mutations and aberrations. In most cases, this leads to upregulation of the mitogen-activated protein kinase (MAPK) pathway through activating mutations of upstream mediators of the pathway including BRAF and NRAS. With the advent of effective MAPK pathway inhibitors, including the US FDA-approved BRAF inhibitors vemurafenib and dabrafenib and MEK inhibitor trametinib, molecular analysis has become an integral part of the care of patients with metastatic melanoma. In this article, the key molecular targets and strategies to inhibit these targets therapeutically are presented, and the techniques of identifying these targets, in both tissue and blood, are discussed.

Core Proteomic Analysis of Unique Metabolic Pathways of Salmonella enterica for the Identification of Potential Drug Targets.

PubMed

Uddin, Reaz; Sufian, Muhammad

2016-01-01

Infections caused by Salmonella enterica, a Gram-negative facultative anaerobic bacteria belonging to the family of Enterobacteriaceae, are major threats to the health of humans and animals. The recent availability of complete genome data of pathogenic strains of the S. enterica gives new avenues for the identification of drug targets and drug candidates. We have used the genomic and metabolic pathway data to identify pathways and proteins essential to the pathogen and absent from the host. We took the whole proteome sequence data of 42 strains of S. enterica and Homo sapiens along with KEGG-annotated metabolic pathway data, clustered proteins sequences using CD-HIT, identified essential genes using DEG database and discarded S. enterica homologs of human proteins in unique metabolic pathways (UMPs) and characterized hypothetical proteins with SVM-prot and InterProScan. Through this core proteomic analysis we have identified enzymes essential to the pathogen. The identification of 73 enzymes common in 42 strains of S. enterica is the real strength of the current study. We proposed all 73 unexplored enzymes as potential drug targets against the infections caused by the S. enterica. The study is comprehensive around S. enterica and simultaneously considered every possible pathogenic strain of S. enterica. This comprehensiveness turned the current study significant since, to the best of our knowledge it is the first subtractive core proteomic analysis of the unique metabolic pathways applied to any pathogen for the identification of drug targets. We applied extensive computational methods to shortlist few potential drug targets considering the druggability criteria e.g. Non-homologous to the human host, essential to the pathogen and playing significant role in essential metabolic pathways of the pathogen (i.e. S. enterica). In the current study, the subtractive proteomics through a novel approach was applied i.e. by considering only proteins of the unique metabolic pathways of the pathogens and mining the proteomic data of all completely sequenced strains of the pathogen, thus improving the quality and application of the results. We believe that the sharing of the knowledge from this study would eventually lead to bring about novel and unique therapeutic regimens against the infections caused by the S. enterica.

Integrated analysis of miRNA and mRNA expression data identifies multiple miRNAs regulatory networks for the tumorigenesis of colorectal cancer.

PubMed

Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang

2018-06-15

Investigating the potential biological function of differential changed genes through integrating multiple omics data including miRNA and mRNA expression profiles, is always hot topic. However, how to evaluate the repression effect on target genes integrating miRNA and mRNA expression profiles are not fully solved. In this study, we provide an analyzing method by integrating both miRNAs and mRNAs expression data simultaneously. Difference analysis was adopted based on the repression score, then significantly repressed mRNAs were screened out by DEGseq. Pathway analysis for the significantly repressed mRNAs shows that multiple pathways such as MAPK signaling pathway, TGF-beta signaling pathway and so on, may correlated to the colorectal cancer(CRC). Focusing on the MAPK signaling pathway, a miRNA-mRNA network that centering the cell fate genes was constructed. Finally, the miRNA-mRNAs that potentially important in the CRC carcinogenesis were screened out and scored by impact index. Copyright © 2018 Elsevier B.V. All rights reserved.

Integrative Analysis of Longitudinal Metabolomics Data from a Personal Multi-Omics Profile

PubMed Central

Stanberry, Larissa; Mias, George I.; Haynes, Winston; Higdon, Roger; Snyder, Michael; Kolker, Eugene

2013-01-01

The integrative personal omics profile (iPOP) is a pioneering study that combines genomics, transcriptomics, proteomics, metabolomics and autoantibody profiles from a single individual over a 14-month period. The observation period includes two episodes of viral infection: a human rhinovirus and a respiratory syncytial virus. The profile studies give an informative snapshot into the biological functioning of an organism. We hypothesize that pathway expression levels are associated with disease status. To test this hypothesis, we use biological pathways to integrate metabolomics and proteomics iPOP data. The approach computes the pathways’ differential expression levels at each time point, while taking into account the pathway structure and the longitudinal design. The resulting pathway levels show strong association with the disease status. Further, we identify temporal patterns in metabolite expression levels. The changes in metabolite expression levels also appear to be consistent with the disease status. The results of the integrative analysis suggest that changes in biological pathways may be used to predict and monitor the disease. The iPOP experimental design, data acquisition and analysis issues are discussed within the broader context of personal profiling. PMID:24958148

Metabolic Pathways and Networks Associated with Tobacco Use in Military Personnel

PubMed Central

Jones, Dean P.; Walker, Douglas I.; Uppal, Karan; Rohrbeck, Patricia; Mallon, Timothy M.; Go, Young-Mi

2016-01-01

Objective Use high-resolution metabolomics (HRM) to identify metabolic pathways and networks associated with tobacco use in military personnel. Methods Four hundred de-identified samples obtained from the Department of Defense Serum Repository were classified as tobacco users or non-users according to cotinine content. HRM and bioinformatic methods were used to determine pathways and networks associated with classification. Results Eighty individuals were classified as tobacco users compared to 320 non-users based on cotinine levels ≥10 ng/mL. Alterations in lipid and xenobiotic metabolism, and diverse effects on amino acid, sialic acid and purine and pyrimidine metabolism were observed. Importantly, network analysis showed broad effects on metabolic associations not simply linked to well-defined pathways. Conclusions Tobacco use has complex metabolic effects which must be considered in evaluation of deployment-associated environmental exposures in military personnel. PMID:27501098

The effect of Bacopa monnieri on gene expression levels in SH-SY5Y human neuroblastoma cells.

PubMed

Leung, How-Wing; Foo, Gabriel; Banumurthy, Gokulakrishna; Chai, Xiaoran; Ghosh, Sujoy; Mitra-Ganguli, Tora; VanDongen, Antonius M J

2017-01-01

Bacopa monnieri is a plant used as a nootropic in Ayurveda, a 5000-year-old system of traditional Indian medicine. Although both animal and clinical studies supported its role as a memory enhancer, the molecular and cellular mechanism underlying Bacopa's nootropic action are not understood. In this study, we used deep sequencing (RNA-Seq) to identify the transcriptome changes upon Bacopa treatment on SH-SY5Y human neuroblastoma cells. We identified several genes whose expression levels were regulated by Bacopa. Biostatistical analysis of the RNA-Seq data identified biological pathways and molecular functions that were regulated by Bacopa, including regulation of mRNA translation and transmembrane transport, responses to oxidative stress and protein misfolding. Pathway analysis using the Ingenuity platform suggested that Bacopa may protect against brain damage and improve brain development. These newly identified molecular and cellular determinants may contribute to the nootropic action of Bacopa and open up a new direction of investigation into its mechanism of action.

The effect of Bacopa monnieri on gene expression levels in SH-SY5Y human neuroblastoma cells

PubMed Central

Foo, Gabriel; Banumurthy, Gokulakrishna; Chai, Xiaoran; Ghosh, Sujoy

2017-01-01

Bacopa monnieri is a plant used as a nootropic in Ayurveda, a 5000-year-old system of traditional Indian medicine. Although both animal and clinical studies supported its role as a memory enhancer, the molecular and cellular mechanism underlying Bacopa’s nootropic action are not understood. In this study, we used deep sequencing (RNA-Seq) to identify the transcriptome changes upon Bacopa treatment on SH-SY5Y human neuroblastoma cells. We identified several genes whose expression levels were regulated by Bacopa. Biostatistical analysis of the RNA-Seq data identified biological pathways and molecular functions that were regulated by Bacopa, including regulation of mRNA translation and transmembrane transport, responses to oxidative stress and protein misfolding. Pathway analysis using the Ingenuity platform suggested that Bacopa may protect against brain damage and improve brain development. These newly identified molecular and cellular determinants may contribute to the nootropic action of Bacopa and open up a new direction of investigation into its mechanism of action. PMID:28832626

Truncation- and motif-based pan-cancer analysis reveals tumor-suppressing kinases.

PubMed

Hudson, Andrew M; Stephenson, Natalie L; Li, Cynthia; Trotter, Eleanor; Fletcher, Adam J; Katona, Gitta; Bieniasz-Krzywiec, Patrycja; Howell, Matthew; Wirth, Chris; Furney, Simon; Miller, Crispin J; Brognard, John

2018-04-17

A major challenge in cancer genomics is identifying "driver" mutations from the many neutral "passenger" mutations within a given tumor. To identify driver mutations that would otherwise be lost within mutational noise, we filtered genomic data by motifs that are critical for kinase activity. In the first step of our screen, we used data from the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas to identify kinases with truncation mutations occurring within or before the kinase domain. The top 30 tumor-suppressing kinases were aligned, and hotspots for loss-of-function (LOF) mutations were identified on the basis of amino acid conservation and mutational frequency. The functional consequences of new LOF mutations were biochemically validated, and the top 15 hotspot LOF residues were used in a pan-cancer analysis to define the tumor-suppressing kinome. A ranked list revealed MAP2K7, an essential mediator of the c-Jun N-terminal kinase (JNK) pathway, as a candidate tumor suppressor in gastric cancer, despite its mutational frequency falling within the mutational noise for this cancer type. The majority of mutations in MAP2K7 abolished its catalytic activity, and reactivation of the JNK pathway in gastric cancer cells harboring LOF mutations in MAP2K7 or the downstream kinase JNK suppressed clonogenicity and growth in soft agar, demonstrating the functional relevance of inactivating the JNK pathway in gastric cancer. Together, our data highlight a broadly applicable strategy to identify functional cancer driver mutations and define the JNK pathway as tumor-suppressive in gastric cancer. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Pathway-based analysis of GWAs data identifies association of sex determination genes with susceptibility to testicular germ cell tumors.

PubMed

Koster, Roelof; Mitra, Nandita; D'Andrea, Kurt; Vardhanabhuti, Saran; Chung, Charles C; Wang, Zhaoming; Loren Erickson, R; Vaughn, David J; Litchfield, Kevin; Rahman, Nazneen; Greene, Mark H; McGlynn, Katherine A; Turnbull, Clare; Chanock, Stephen J; Nathanson, Katherine L; Kanetsky, Peter A

2014-11-15

Genome-wide association (GWA) studies of testicular germ cell tumor (TGCT) have identified 18 susceptibility loci, some containing genes encoding proteins important in male germ cell development. Deletions of one of these genes, DMRT1, lead to male-to-female sex reversal and are associated with development of gonadoblastoma. To further explore genetic association with TGCT, we undertook a pathway-based analysis of SNP marker associations in the Penn GWAs (349 TGCT cases and 919 controls). We analyzed a custom-built sex determination gene set consisting of 32 genes using three different methods of pathway-based analysis. The sex determination gene set ranked highly compared with canonical gene sets, and it was associated with TGCT (FDRG = 2.28 × 10(-5), FDRM = 0.014 and FDRI = 0.008 for Gene Set Analysis-SNP (GSA-SNP), Meta-Analysis Gene Set Enrichment of Variant Associations (MAGENTA) and Improved Gene Set Enrichment Analysis for Genome-wide Association Study (i-GSEA4GWAS) analysis, respectively). The association remained after removal of DMRT1 from the gene set (FDRG = 0.0002, FDRM = 0.055 and FDRI = 0.009). Using data from the NCI GWA scan (582 TGCT cases and 1056 controls) and UK scan (986 TGCT cases and 4946 controls), we replicated these findings (NCI: FDRG = 0.006, FDRM = 0.014, FDRI = 0.033, and UK: FDRG = 1.04 × 10(-6), FDRM = 0.016, FDRI = 0.025). After removal of DMRT1 from the gene set, the sex determination gene set remains associated with TGCT in the NCI (FDRG = 0.039, FDRM = 0.050 and FDRI = 0.055) and UK scans (FDRG = 3.00 × 10(-5), FDRM = 0.056 and FDRI = 0.044). With the exception of DMRT1, genes in the sex determination gene set have not previously been identified as TGCT susceptibility loci in these GWA scans, demonstrating the complementary nature of a pathway-based approach for genome-wide analysis of TGCT. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Transcriptomic analyses of tributyltin-induced sexual dimorphisms in rare minnow (Gobiocypris rarus) brains.

PubMed

Zhang, Ji-Liang; Liu, Min; Zhang, Chun-Nuan; Li, Er-Chao; Fan, Ming-Zhen; Huang, Mao-Xian

2018-07-30

The brain of fish displays sexual dimorphisms and exhibits remarkable sexual plasticity throughout their life span. Although reproductive toxicity of tributyltin (TBT) in fish is well documented in fish, it remains unknown whether TBT interrupts sexual dimorphisms of fish brains. In this work, brain transcriptomic profiles of rare minnow (Gobiocypris rarus) was characterized and sex-biased genes were identified using RNA sequencing. Functional annotation and enrichment analysis were performed to reveal differences of gene products and pathways between the brains of male and female fish. Furthermore, transcriptomic responses of male and female brains to TBT at 10 ng/L were also investigated to understand effects of TBT on brain sexual dimorphisms. Only 345 male-biased and 273 female-biased genes were found in the brains. However, significant female-biased pathways of circadian rhythm and phototransduction were identified in the brains by enrichment analysis. Interestingly, following TBT exposure in the female fish, the circadian rhythm pathway was significantly disrupted based on enrichment analysis, while in the male fish, the phototransduction pathway was significantly disrupted. In the female fish, expression of genes (Per, Cry, Rev-Erb α, Ror, Dec and CK1δ/ε) in the circadian rhythm pathway was down-regulated after TBT exposure; while in the male fish, expression of genes (Rec, GNAT1_2, GNGT1, Rh/opsin, PDE and Arr) in the phototransduction pathway was up-regulated after TBT exposure. Overall, our results not only provide key data on the molecular basis of brain sexual dimorphisms in fish, but also offer valuable resources for investigating molecular mechanisms by which environmental chemicals might influence brain sexual plasticity. Copyright © 2018 Elsevier Inc. All rights reserved.

Metabolomics and proteomics technologies to explore the herbal preparation affecting metabolic disorders using high resolution mass spectrometry.

PubMed

Zhang, Aihua; Zhou, Xiaohang; Zhao, Hongwei; Zou, Shiyu; Ma, Chung Wah; Liu, Qi; Sun, Hui; Liu, Liang; Wang, Xijun

2017-01-31

An integrative metabolomics and proteomics approach can provide novel insights in the understanding of biological systems. We have integrated proteome and metabolome data sets for a holistic view of the molecular mechanisms in disease. Using quantitative iTRAQ-LC-MS/MS proteomics coupled with UPLC-Q-TOF-HDMS based metabolomics, we determined the protein and metabolite expression changes in the kidney-yang deficiency syndrome (KYDS) rat model and further investigated the intervention effects of the Jinkui Shenqi Pill (JSP). The VIP-plot of the orthogonal PLS-DA (OPLS-DA) was used for discovering the potential biomarkers to clarify the therapeutic mechanisms of JSP in treating KYDS. The results showed that JSP can alleviate the kidney impairment induced by KYDS. Sixty potential biomarkers, including 5-l-glutamyl-taurine, phenylacetaldehyde, 4,6-dihydroxyquinoline, and xanthurenic acid etc., were definitely up- or down-regulated. The regulatory effect of JSP on the disturbed metabolic pathways was proved by the established metabonomic method. Using pathway analyses, we identified the disturbed metabolic pathways such as taurine and hypotaurine metabolism, pyrimidine metabolism, tyrosine metabolism, tryptophan metabolism, histidine metabolism, steroid hormone biosynthesis, etc. Furthermore, using iTRAQ-based quantitative proteomics analysis, seventeen differential proteins were identified and significantly altered by the JSP treatment. These proteins appear to be involved in Wnt, chemokine, PPAR, and MAPK signaling pathways, etc. Functional pathway analysis revealed that most of the proteins were found to play a key role in the regulation of metabolism pathways. Bioinformatics analysis with the IPA software found that these differentially-expressed moleculars had a strong correlation with the α-adrenergic signaling, FGF signaling, etc. Our data indicate that high-throughput metabolomics and proteomics can provide an insight on the herbal preparations affecting the metabolic disorders using high resolution mass spectrometry.

Serum-based six-miRNA signature as a potential marker for EC diagnosis: Comparison with TCGA miRNAseq dataset and identification of miRNA-mRNA target pairs by integrated analysis of TCGA miRNAseq and RNAseq datasets.

PubMed

Sharma, Priyanka; Saraya, Anoop; Sharma, Rinu

2018-01-30

To evaluate the diagnostic potential of a six microRNAs (miRNAs) panel consisting of miR-21, miR-144, miR-107, miR-342, miR-93 and miR-152 for esophageal cancer (EC) detection. The expression of miRNAs was analyzed in EC sera samples using quantitative real-time PCR. Risk score analysis was performed and linear regression models were then fitted to generate the six-miRNA panel. In addition, we made an effort to identify significantly dysregulated miRNAs and mRNAs in EC using the Cancer Genome Atlas (TCGA) miRNAseq and RNAseq datasets, respectively. Further, we identified significantly correlated miRNA-mRNA target pairs by integrating TCGA EC miRNAseq dataset with RNAseq dataset. The panel of circulating miRNAs showed enhanced sensitivity (87.5%) and specificity (90.48%) in terms of discriminating EC patients from normal subjects (area under the curve [AUC] = 0.968). Pathway enrichment analysis for potential targets of six miRNAs revealed 48 significant (P < 0.05) pathways, viz. pathways in cancer, mRNA surveillance, MAPK, Wnt, mTOR signaling, and so on. The expression data for mRNAs and miRNAs, downloaded from TCGA database, lead to identification of 2309 differentially expressed genes and 189 miRNAs. Gene ontology and pathway enrichment analysis showed that cell-cycle processes were most significantly enriched for differentially expressed mRNA. Integrated analysis of TCGA miRNAseq and RNAseq datasets resulted in identification of 53 063 significantly and negatively correlated miRNA-mRNA pairs. In summary, a novel and highly sensitive signature of serum miRNAs was identified for EC detection. Moreover, this is the first report identifying miRNA-mRNA target pairs from EC TCGA dataset, thus providing a comprehensive resource for understanding the interactions existing between miRNA and their target mRNAs in EC. © 2018 John Wiley & Sons Australia, Ltd.

Comparison of tumor related signaling pathways with known compounds to determine potential agents for lung adenocarcinoma.

PubMed

Xu, Song; Liu, Renwang; Da, Yurong

2018-06-05

This study compared tumor-related signaling pathways with known compounds to determine potential agents for lung adenocarcinoma (LUAD) treatment. Kyoto Encyclopedia of Genes and Genomes signaling pathway analyses were performed based on LUAD differentially expressed genes from The Cancer Genome Atlas (TCGA) project and genotype-tissue expression controls. These results were compared to various known compounds using the Connectivity Mapping dataset. The clinical significance of the hub genes identified by overlapping pathway enrichment analysis was further investigated using data mining from multiple sources. A drug-pathway network for LUAD was constructed, and molecular docking was carried out. After the integration of 57 LUAD-related pathways and 35 pathways affected by small molecules, five overlapping pathways were revealed. Among these five pathways, the p53 signaling pathway was the most significant, with CCNB1, CCNB2, CDK1, CDKN2A, and CHEK1 being identified as hub genes. The p53 signaling pathway is implicated as a risk factor for LUAD tumorigenesis and survival. A total of 88 molecules significantly inhibiting the five LUAD-related oncogenic pathways were involved in the LUAD drug-pathway network. Daunorubicin, mycophenolic acid, and pyrvinium could potentially target the hub gene CHEK1 directly. Our study highlights the critical pathways that should be targeted in the search for potential LUAD treatments, most importantly, the p53 signaling pathway. Some compounds, such as ciclopirox and AG-028671, may have potential roles for LUAD treatment but require further experimental verification. © 2018 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

Identification of Biological Targets of Therapeutic Intervention for Hepatocellular Carcinoma by Integrated Bioinformatical Analysis.

PubMed

Hu, Wei Qi; Wang, Wei; Fang, Di Long; Yin, Xue Feng

2018-05-24

BACKGROUND We screened the potential molecular targets and investigated the molecular mechanisms of hepatocellular carcinoma (HCC). MATERIAL AND METHODS Microarray data of GSE47786, including the 40 μM berberine-treated HepG2 human hepatoma cell line and 0.08% DMSO-treated as control cells samples, was downloaded from the GEO database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed; the protein-protein interaction (PPI) networks were constructed using STRING database and Cytoscape; the genetic alteration, neighboring genes networks, and survival analysis of hub genes were explored by cBio portal; and the expression of mRNA level of hub genes was obtained from the Oncomine databases. RESULTS A total of 56 upregulated and 8 downregulated DEGs were identified. The GO analysis results were significantly enriched in cell-cycle arrest, regulation of transcription, DNA-dependent, protein amino acid phosphorylation, cell cycle, and apoptosis. The KEGG pathway analysis showed that DEGs were enriched in MAPK signaling pathway, ErbB signaling pathway, and p53 signaling pathway. JUN, EGR1, MYC, and CDKN1A were identified as hub genes in PPI networks. The genetic alteration of hub genes was mainly concentrated in amplification. TP53, NDRG1, and MAPK15 were found in neighboring genes networks. Altered genes had worse overall survival and disease-free survival than unaltered genes. The expressions of EGR1, MYC, and CDKN1A were significantly increased, but expression of JUN was not, in the Roessler Liver datasets. CONCLUSIONS We found that JUN, EGR1, MYC, and CDKN1A might be used as diagnostic and therapeutic molecular biomarkers and broaden our understanding of the molecular mechanisms of HCC.

MicroRNA-200a suppresses the Wnt/β-catenin signaling pathway by interacting with β-catenin.

PubMed

Su, Juan; Zhang, Anling; Shi, Zhendong; Ma, Feifei; Pu, Peiyu; Wang, Tao; Zhang, Jie; Kang, Chunsheng; Zhang, Qingyu

2012-04-01

The Wnt/β-catenin signaling pathway is crucial for human organ development and is involved in tumor progression of many cancers. Accumulating evidence suggests that the expression of β-catenin is, in part, regulated by specific microRNAs (miRNAs). The purpose of this study was to determine the expression of a recently identified epithelial to mesenchymal transition (EMT)-associated tumor suppressor microRNA (miR)-200a, in cancer cells. We also aimed to identify specific miR-200a target genes and to investigate the antitumor effects of miR-200a on the Wnt/β-catenin signaling pathway. We employed TOP/FOP flash luciferase assays to identify the effect of miR-200a on the Wnt/β-catenin pathway and we confirmed our observations using fluorescence microscopy. To determine target genes of miR-200a, a 3' untranslated region (3' UTR) luciferase assay was performed. Cell viability, invasion and wound healing assays were carried out for functional analysis after miRNA transfection. We further investigated the role of miR-200a in EMT by Western blot analysis. We found fluctuation in the expression of miR-200a that was accompanied by changes in the expression of members of the Wnt/β-catenin signaling pathway. We also determined that miR-200a can directly interact with the 3' UTR of CTNNB1 (the gene that encodes β-catenin) to suppress Wnt/β-catenin signaling. MiR-200a could also influence the biological activities of SGC790 and U251 cells. Our results demonstrate that miR-200a is a new tumor suppressor that can regulate the activity of the Wnt/β-catenin signaling pathway via two mechanisms. MiR-200a is a candidate target for tumor treatment via its regulation of the Wnt/β-catenin signaling pathway.

Molecular Signatures Discriminating the Male and the Female Sexual Pathways in the Pearl Oyster Pinctada margaritifera

PubMed Central

Teaniniuraitemoana, Vaihiti; Huvet, Arnaud; Levy, Peva; Gaertner-Mazouni, Nabila; Gueguen, Yannick; Le Moullac, Gilles

2015-01-01

The genomics of economically important marine bivalves is studied to provide better understanding of the molecular mechanisms underlying their different reproductive strategies. The recently available gonad transcriptome of the black-lip pearl oyster Pinctada margaritifera is a novel and powerful resource to study these mechanisms in marine mollusks displaying hermaphroditic features. In this study, RNAseq quantification data of the P. margaritifera gonad transcriptome were analyzed to identify candidate genes in histologically-characterized gonad samples to provide molecular signatures of the female and male sexual pathway in this pearl oyster. Based on the RNAseq data set, stringent expression analysis identified 1,937 contigs that were differentially expressed between the gonad histological categories. From the hierarchical clustering analysis, a new reproduction model is proposed, based on a dual histo-molecular analytical approach. Nine candidate genes were identified as markers of the sexual pathway: 7 for the female pathway and 2 for the male one. Their mRNA levels were assayed by real-time PCR on a new set of gonadic samples. A clustering method revealed four principal expression patterns based on the relative gene expression ratio. A multivariate regression tree realized on these new samples and validated on the previously analyzed RNAseq samples showed that the sexual pathway of P. margaritifera can be predicted by a 3-gene-pair expression ratio model of 4 different genes: pmarg-43476, pmarg-foxl2, pmarg-54338 and pmarg-fem1-like. This 3-gene-pair expression ratio model strongly suggests only the implication of pmarg-foxl2 and pmarg-fem1-like in the sex inversion of P. margaritifera. This work provides the first histo-molecular model of P. margaritifera reproduction and a gene expression signature of its sexual pathway discriminating the male and female pathways. These represent useful tools for understanding and studying sex inversion, sex differentiation and sex determinism in this species and other related species for aquaculture purposes such as genetic selection programs. PMID:25815473

Proteome reference map and regulation network of neonatal rat cardiomyocyte

PubMed Central

Li, Zi-jian; Liu, Ning; Han, Qi-de; Zhang, You-yi

2011-01-01

Aim: To study and establish a proteome reference map and regulation network of neonatal rat cardiomyocyte. Methods: Cultured cardiomyocytes of neonatal rats were used. All proteins expressed in the cardiomyocytes were separated and identified by two-dimensional polyacrylamide gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). Biological networks and pathways of the neonatal rat cardiomyocytes were analyzed using the Ingenuity Pathway Analysis (IPA) program (www.ingenuity.com). A 2-DE database was made accessible on-line by Make2ddb package on a web server. Results: More than 1000 proteins were separated on 2D gels, and 148 proteins were identified. The identified proteins were used for the construction of an extensible markup language-based database. Biological networks and pathways were constructed to analyze the functions associate with cardiomyocyte proteins in the database. The 2-DE database of rat cardiomyocyte proteins can be accessed at http://2d.bjmu.edu.cn. Conclusion: A proteome reference map and regulation network of the neonatal rat cardiomyocytes have been established, which may serve as an international platform for storage, analysis and visualization of cardiomyocyte proteomic data. PMID:21841810

Identification of key genes associated with the effect of estrogen on ovarian cancer using microarray analysis.

PubMed

Zhang, Shi-tao; Zuo, Chao; Li, Wan-nan; Fu, Xue-qi; Xing, Shu; Zhang, Xiao-ping

2016-02-01

To identify key genes related to the effect of estrogen on ovarian cancer. Microarray data (GSE22600) were downloaded from Gene Expression Omnibus. Eight estrogen and seven placebo treatment samples were obtained using a 2 × 2 factorial designs, which contained 2 cell lines (PEO4 and 2008) and 2 treatments (estrogen and placebo). Differentially expressed genes were identified by Bayesian methods, and the genes with P < 0.05 and |log2FC (fold change)| ≥0.5 were chosen as cut-off criterion. Differentially co-expressed genes (DCGs) and differentially regulated genes (DRGs) were, respectively, identified by DCe function and DRsort function in DCGL package. Topological structure analysis was performed on the important transcriptional factors (TFs) and genes in transcriptional regulatory network using tYNA. Functional enrichment analysis was, respectively, performed for DEGs and the important genes using Gene Ontology and KEGG databases. In total, 465 DEGs were identified. Functional enrichment analysis of DEGs indicated that ACVR2B, LTBP1, BMP7 and MYC involved in TGF-beta signaling pathway. The 2285 DCG pairs and 357 DRGs were identified. Topological structure analysis showed that 52 important TFs and 65 important genes were identified. Functional enrichment analysis of the important genes showed that TP53 and MLH1 participated in DNA damage response and the genes (ACVR2B, LTBP1, BMP7 and MYC) involved in TGF-beta signaling pathway. TP53, MLH1, ACVR2B, LTBP1 and BMP7 might participate in the pathogenesis of ovarian cancer.

A Low Glycaemic Index Diet in Pregnancy Induces DNA Methylation Variation in Blood of Newborns: Results from the ROLO Randomised Controlled Trial.

PubMed

Geraghty, Aisling A; Sexton-Oates, Alexandra; O'Brien, Eileen C; Alberdi, Goiuri; Fransquet, Peter; Saffery, Richard; McAuliffe, Fionnuala M

2018-04-06

The epigenetic profile of the developing fetus is sensitive to environmental influence. Maternal diet has been shown to influence DNA methylation patterns in offspring, but research in humans is limited. We investigated the impact of a low glycaemic index dietary intervention during pregnancy on offspring DNA methylation patterns using a genome-wide methylation approach. Sixty neonates were selected from the ROLO (Randomised cOntrol trial of LOw glycaemic index diet to prevent macrosomia) study: 30 neonates from the low glycaemic index intervention arm and 30 from the control, whose mothers received no specific dietary advice. DNA methylation was investigated in 771,484 CpG sites in free DNA from cord blood serum. Principal component analysis and linear regression were carried out comparing the intervention and control groups. Gene clustering and pathway analysis were also explored. Widespread variation was identified in the newborns exposed to the dietary intervention, accounting for 11% of the total level of DNA methylation variation within the dataset. No association was found with maternal early-pregnancy body mass index (BMI), infant sex, or birthweight. Pathway analysis identified common influences of the intervention on gene clusters plausibly linked to pathways targeted by the intervention, including cardiac and immune functioning. Analysis in 60 additional samples from the ROLO study failed to replicate the original findings. Using a modest-sized discovery sample, we identified preliminary evidence of differential methylation in progeny of mothers exposed to a dietary intervention during pregnancy.

Identifying Likely Transmission Pathways within a 10-Year Community Outbreak of Tuberculosis by High-Depth Whole Genome Sequencing

PubMed Central

Sadsad, Rosemarie; Martinez, Elena; Jelfs, Peter; Hill-Cawthorne, Grant A.; Gilbert, Gwendolyn L.; Marais, Ben J.; Sintchenko, Vitali

2016-01-01

Background Improved tuberculosis control and the need to contain the spread of drug-resistant strains provide a strong rationale for exploring tuberculosis transmission dynamics at the population level. Whole-genome sequencing provides optimal strain resolution, facilitating detailed mapping of potential transmission pathways. Methods We sequenced 22 isolates from a Mycobacterium tuberculosis cluster in New South Wales, Australia, identified during routine 24-locus mycobacterial interspersed repetitive unit typing. Following high-depth paired-end sequencing using the Illumina HiSeq 2000 platform, two independent pipelines were employed for analysis, both employing read mapping onto reference genomes as well as de novo assembly, to control biases in variant detection. In addition to single-nucleotide polymorphisms, the analyses also sought to identify insertions, deletions and structural variants. Results Isolates were highly similar, with a distance of 13 variants between the most distant members of the cluster. The most sensitive analysis classified the 22 isolates into 18 groups. Four of the isolates did not appear to share a recent common ancestor with the largest clade; another four isolates had an uncertain ancestral relationship with the largest clade. Conclusion Whole genome sequencing, with analysis of single-nucleotide polymorphisms, insertions, deletions, structural variants and subpopulations, enabled the highest possible level of discrimination between cluster members, clarifying likely transmission pathways and exposing the complexity of strain origin. The analysis provides a basis for targeted public health intervention and enhanced classification of future isolates linked to the cluster. PMID:26938641

Comparative Analysis and Modeling of the Severity of Steatohepatitis in DDC-Treated Mouse Strains

PubMed Central

Pandey, Vikash; Sultan, Marc; Kashofer, Karl; Ralser, Meryem; Amstislavskiy, Vyacheslav; Starmann, Julia; Osprian, Ingrid; Grimm, Christina; Hache, Hendrik; Yaspo, Marie-Laure; Sültmann, Holger; Trauner, Michael; Denk, Helmut; Zatloukal, Kurt; Lehrach, Hans; Wierling, Christoph

2014-01-01

Background Non-alcoholic fatty liver disease (NAFLD) has a broad spectrum of disease states ranging from mild steatosis characterized by an abnormal retention of lipids within liver cells to steatohepatitis (NASH) showing fat accumulation, inflammation, ballooning and degradation of hepatocytes, and fibrosis. Ultimately, steatohepatitis can result in liver cirrhosis and hepatocellular carcinoma. Methodology and Results In this study we have analyzed three different mouse strains, A/J, C57BL/6J, and PWD/PhJ, that show different degrees of steatohepatitis when administered a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) containing diet. RNA-Seq gene expression analysis, protein analysis and metabolic profiling were applied to identify differentially expressed genes/proteins and perturbed metabolite levels of mouse liver samples upon DDC-treatment. Pathway analysis revealed alteration of arachidonic acid (AA) and S-adenosylmethionine (SAMe) metabolism upon other pathways. To understand metabolic changes of arachidonic acid metabolism in the light of disease expression profiles a kinetic model of this pathway was developed and optimized according to metabolite levels. Subsequently, the model was used to study in silico effects of potential drug targets for steatohepatitis. Conclusions We identified AA/eicosanoid metabolism as highly perturbed in DDC-induced mice using a combination of an experimental and in silico approach. Our analysis of the AA/eicosanoid metabolic pathway suggests that 5-hydroxyeicosatetraenoic acid (5-HETE), 15-hydroxyeicosatetraenoic acid (15-HETE) and prostaglandin D2 (PGD2) are perturbed in DDC mice. We further demonstrate that a dynamic model can be used for qualitative prediction of metabolic changes based on transcriptomics data in a disease-related context. Furthermore, SAMe metabolism was identified as being perturbed due to DDC treatment. Several genes as well as some metabolites of this module show differences between A/J and C57BL/6J on the one hand and PWD/PhJ on the other. PMID:25347188

Comparative analysis and modeling of the severity of steatohepatitis in DDC-treated mouse strains.

PubMed

Pandey, Vikash; Sultan, Marc; Kashofer, Karl; Ralser, Meryem; Amstislavskiy, Vyacheslav; Starmann, Julia; Osprian, Ingrid; Grimm, Christina; Hache, Hendrik; Yaspo, Marie-Laure; Sültmann, Holger; Trauner, Michael; Denk, Helmut; Zatloukal, Kurt; Lehrach, Hans; Wierling, Christoph

2014-01-01

Non-alcoholic fatty liver disease (NAFLD) has a broad spectrum of disease states ranging from mild steatosis characterized by an abnormal retention of lipids within liver cells to steatohepatitis (NASH) showing fat accumulation, inflammation, ballooning and degradation of hepatocytes, and fibrosis. Ultimately, steatohepatitis can result in liver cirrhosis and hepatocellular carcinoma. In this study we have analyzed three different mouse strains, A/J, C57BL/6J, and PWD/PhJ, that show different degrees of steatohepatitis when administered a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) containing diet. RNA-Seq gene expression analysis, protein analysis and metabolic profiling were applied to identify differentially expressed genes/proteins and perturbed metabolite levels of mouse liver samples upon DDC-treatment. Pathway analysis revealed alteration of arachidonic acid (AA) and S-adenosylmethionine (SAMe) metabolism upon other pathways. To understand metabolic changes of arachidonic acid metabolism in the light of disease expression profiles a kinetic model of this pathway was developed and optimized according to metabolite levels. Subsequently, the model was used to study in silico effects of potential drug targets for steatohepatitis. We identified AA/eicosanoid metabolism as highly perturbed in DDC-induced mice using a combination of an experimental and in silico approach. Our analysis of the AA/eicosanoid metabolic pathway suggests that 5-hydroxyeicosatetraenoic acid (5-HETE), 15-hydroxyeicosatetraenoic acid (15-HETE) and prostaglandin D2 (PGD2) are perturbed in DDC mice. We further demonstrate that a dynamic model can be used for qualitative prediction of metabolic changes based on transcriptomics data in a disease-related context. Furthermore, SAMe metabolism was identified as being perturbed due to DDC treatment. Several genes as well as some metabolites of this module show differences between A/J and C57BL/6J on the one hand and PWD/PhJ on the other.

Genetic Correction of SOD1 Mutant iPSCs Reveals ERK and JNK Activated AP1 as a Driver of Neurodegeneration in Amyotrophic Lateral Sclerosis.

PubMed

Bhinge, Akshay; Namboori, Seema C; Zhang, Xiaoyu; VanDongen, Antonius M J; Stanton, Lawrence W

2017-04-11

Although mutations in several genes with diverse functions have been known to cause amyotrophic lateral sclerosis (ALS), it is unknown to what extent causal mutations impinge on common pathways that drive motor neuron (MN)-specific neurodegeneration. In this study, we combined induced pluripotent stem cells-based disease modeling with genome engineering and deep RNA sequencing to identify pathways dysregulated by mutant SOD1 in human MNs. Gene expression profiling and pathway analysis followed by pharmacological screening identified activated ERK and JNK signaling as key drivers of neurodegeneration in mutant SOD1 MNs. The AP1 complex member JUN, an ERK/JNK downstream target, was observed to be highly expressed in MNs compared with non-MNs, providing a mechanistic insight into the specific degeneration of MNs. Importantly, investigations of mutant FUS MNs identified activated p38 and ERK, indicating that network perturbations induced by ALS-causing mutations converge partly on a few specific pathways that are drug responsive and provide immense therapeutic potential. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Multiple intracellular signaling pathways orchestrate adipocytic differentiation of human bone marrow stromal stem cells.

PubMed

Ali, Dalia; Abuelreich, Sarah; Alkeraishan, Nora; Shwish, Najla Bin; Hamam, Rimi; Kassem, Moustapha; Alfayez, Musaad; Aldahmash, Abdullah; Alajez, Nehad M

2018-02-28

Bone marrow adipocyte formation plays a role in bone homeostasis and whole body energy metabolism. However, the transcriptional landscape and signaling pathways associated with adipocyte lineage commitment and maturation are not fully delineated. Thus, we performed global gene expression profiling during adipocyte differentiation of human bone marrow stromal (mesenchymal) stem cells (hMSCs) and identified 2,589 up-regulated and 2,583 down-regulated mRNA transcripts. Pathway analysis on the up-regulated gene list untraveled enrichment in multiple signaling pathways including insulin receptor signaling, focal Adhesion, metapathway biotransformation, a number of metabolic pathways e.g. selenium metabolism, Benzo(a)pyrene metabolism, fatty acid, triacylglycerol, ketone body metabolism, tryptophan metabolism, and catalytic cycle of mammalian flavin-containing monooxygenase (FMOs). On the other hand, pathway analysis on the down-regulated genes revealed significant enrichment in pathways related to cell cycle regulation. Based on these data, we assessed the effect of pharmacological inhibition of FAK signaling using PF-573228, PF-562271, and InsR/IGF-1R using NVP-AEW541 and GSK-1904529A on adipocyte differentiation. hMSCs exposed to FAK or IGF-1R/InsR inhibitors exhibited fewer adipocyte formation (27-58% inhibition, P <0005). Concordantly, the expression of adipocyte-specific genes AP2, AdipoQ, and CEBPα was significantly reduced. On the other hand, we did not detect significant effects on cell viability as a result of FAK or IGF-1R/InsR inhibition. Our data identified FAK and insulin signaling as important intracellular signaling pathways relevant to bone marrow adipogenesis. © 2018 The Author(s).

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.

Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

DOE PAGES

Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.; ...

2016-06-24

Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

'I do the best I can': an in-depth exploration of the aphasia management pathway in the acute hospital setting.

PubMed

Foster, Abby M; Worrall, Linda E; Rose, Miranda L; O'Halloran, Robyn

2016-09-01

While research has begun to explore the management of aphasia across the continuum of care, to date there is little in-depth, context specific knowledge relating to the speech pathology aphasia management pathway. This research aimed to provide an in-depth understanding of the current aphasia management pathway in the acute hospital setting, from the perspective of speech pathologists. Underpinned by a social constructivist paradigm, the researchers implemented an interpretive phenomenological method when conducting in-depth interviews with 14 Australian speech pathologists working in the acute hospital setting. Interview transcripts and interviewer field notes were subjected to a qualitative content analysis. Analysis identified a single guiding construct and five main categories to describe the management of aphasia in the acute hospital setting. The guiding construct, First contact with the profession, informed the entire management pathway. Five additional main categories were identified: Referral processes; Screening and assessment; Therapeutic intervention; Educational and affective counselling; and Advocacy. Findings suggest significant diversity in the pathways of care for people with aphasia and their families in the acute hospital setting. Additional support mechanisms are required in order to support speech pathologists to minimise the evidence-practice gap. Implications for Rehabilitation Significant diversity exists in the current aphasia management pathway for people with acute post-stroke aphasia and their families in the acute hospital setting. Mechanisms that support speech pathologists to minimise the evidence-practice gap, and consequently reduce their sense of professional dissonance, are required.

Use of natural variation to identify loci associated with relevant agronomic phenotypic traits

USDA-ARS?s Scientific Manuscript database

Analysis of natural allelic variation is a useful discovery tool to identify novel alleles in genes and pathways that are consistent with agronomic productivity and environmental stability. Switchgrass, a native perennial North American prairie grass and emerging biofuel feedstock species, is divide...

RNA sequencing-based longitudinal transcriptomic profiling gives novel insights into the disease mechanism of generalized pustular psoriasis.

PubMed

Wang, Lingyan; Yu, Xiaoling; Wu, Chao; Zhu, Teng; Wang, Wenming; Zheng, Xiaofeng; Jin, Hongzhong

2018-06-05

Generalized pustular psoriasis (GPP) is a rare, episodic, potentially life-threatening inflammatory disease. However, the pathogenesis of GPP, and universally accepted therapies for treating it, remain undefined. To better understand the disease mechanism of GPP, we performed a transcriptome analysis to profile the gene expression of peripheral blood mononuclear cells (PBMCs) from patients enrolled at the time of diagnosis and receiving follow-up treatment for up to 6 months. RNA sequencing data revealed that gene expression in five GPP patients' PBMCs was profoundly altered following acitretin treatment. Differentially expressed gene (DEG) analysis suggested that genes related to psoriatic inflammation, including CXCL1, CXCL8 (IL-8), S100A8, S100A9, S100A12 and LCN2, were significantly downregulated in patients in remission from GPP. Functional enrichment and annotation analysis unveiled a cluster of DEGs significantly associated with the function of leukocytes, particularly neutrophils. Pathway analysis suggested that a variety of pro-inflammatory pathways were inhibited in patients in remission. This analysis not only reaffirmed known signaling pathways in GPP pathogenesis, but also implicated novel factors and pathways, such as cell cycle regulation pathways. Furthermore, regulator network analysis provided bioinformatics-based support for upstream molecules as potential therapeutic targets such as oncostatin M. This longitudinal analysis of blood transcriptomes provides the first evidence that dysregulated gene expression in peripheral blood may significantly contribute to psoriatic inflammation in GPP patients. Novel canonical pathways and biomarkers identified in the current research may provide insights to help understand GPP pathobiology and advance novel therapeutics.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome.

PubMed

Morine, Melissa J; McMonagle, Jolene; Toomey, Sinead; Reynolds, Clare M; Moloney, Aidan P; Gormley, Isobel C; Gaora, Peadar O; Roche, Helen M

2010-10-07

Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways--selenoamino acid metabolism and steroid biosynthesis--illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

PubMed Central

2010-01-01

Background Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Results Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways - selenoamino acid metabolism and steroid biosynthesis - illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. Conclusion Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease. PMID:20929581

Metabolomics study on the toxicity of aconite root and its processed products using ultraperformance liquid-chromatography/electrospray-ionization synapt high-definition mass spectrometry coupled with pattern recognition approach and ingenuity pathways analysis.

PubMed

Wang, Xijun; Wang, Huiyu; Zhang, Aihua; Lu, Xin; Sun, Hui; Dong, Hui; Wang, Ping

2012-02-03

The mother and lateral root of Aconitum carmichaelii Debx, named "Chuanwu" (CW) and "Fuzi", respectively, has been used to relieve joint pain and treat rheumatic diseases for over 2000 years. However, it has a very narrow therapeutic range, and the toxicological risk of its usage remains very high. The traditional Chinese processing approach, Paozhi (detoxifying measure),can decompose poisonous Aconitum alkaloids into less or nontoxic derivatives and plays an important role in detoxification. The difference in metabolomic characters among the crude and processed preparations is still unclear, limited by the lack of sensitive and reliable biomarkers. Therefore, this paper was designed to investigate comprehensive metabolomic characters of the crude and its processed products by UPLC-Q-TOF-HDMS combined with pattern recognition methods and ingenuity pathway analysis (IPA). The significant difference in metabolic profiles and changes of metabolite biomarkers of interest between the crude and processed preparations were well observed. The underlying regulations of Paozhi-perturbed metabolic pathways are discussed according to the identified metabolites, and four metabolic pathways are identified using IPA. The present study demonstrates that metabolomic analysis could greatly facilitate and provide useful information to further comprehensively understand the pharmacological activity and potential toxicity of processed Aconite roots in the clinic.

Source identification of nitrous oxide emission pathways from a single-stage nitritation-anammox granular reactor.

PubMed

Ali, Muhammad; Rathnayake, Rathnayake M L D; Zhang, Lei; Ishii, Satoshi; Kindaichi, Tomonori; Satoh, Hisashi; Toyoda, Sakae; Yoshida, Naohiro; Okabe, Satoshi

2016-10-01

Nitrous oxide (N2O) production pathway in a signal-stage nitritation-anammox sequencing batch reactor (SBR) was investigated based on a multilateral approach including real-time N2O monitoring, N2O isotopic composition analysis, and in-situ analyses of spatial distribution of N2O production rate and microbial populations in granular biomass. N2O emission rate was high in the initial phase of the operation cycle and gradually decreased with decreasing NH4(+) concentration. The average emission of N2O was 0.98 ± 0.42% and 1.35 ± 0.72% of the incoming nitrogen load and removed nitrogen, respectively. The N2O isotopic composition analysis revealed that N2O was produced via NH2OH oxidation and NO2(-) reduction pathways equally, although there is an unknown influence from N2O reduction and/or anammox N2O production. However, the N2O isotopomer analysis could not discriminate the relative contribution of nitrifier denitrification and heterotrophic denitrification in the NO2(-) reduction pathway. Various in-situ techniques (e.g. microsensor measurements and FISH (fluorescent in-situ hybridization) analysis) were therefore applied to further identify N2O producers. Microsensor measurements revealed that approximately 70% of N2O was produced in the oxic surface zone, where nitrifiers were predominantly localized. Thus, NH2OH oxidation and NO2 reduction by nitrifiers (nitrifier-denitrification) could be responsible for the N2O production in the oxic zone. The rest of N2O (ca. 30%) was produced in the anammox bacteria-dominated anoxic zone, probably suggesting that NO2(-) reduction by coexisting putative heterotrophic denitrifiers and some other unknown pathway(s) including the possibility of anammox process account for the anaerobic N2O production. Further study is required to identify the anaerobic N2O production pathways. Our multilateral approach can be useful to quantitatively examine the relative contributions of N2O production pathways. Good understanding of the key N2O production pathways is essential to establish a strategy to mitigate N2O emission from biological nitrogen removal processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Methoxychlor affects multiple hormone signaling pathways in the largemouth bass (Micropterus salmoides) liver

PubMed Central

Martyniuk, Christopher J.; Spade, Daniel J.; Blum, Jason L.; Kroll, Kevin J.; Denslow, Nancy D.

2011-01-01

Methoxychlor (MXC) is an organochlorine pesticide that has been shown to have estrogenic activity by activating estrogen receptors and inducing vitellogenin production in male fish. Previous studies report that exposure to MXC induces changes in mRNA abundance of reproductive genes in the liver and testes of largemouth bass (Micropterus salmoides). The objective of the present study was to better characterize the mode of action of MXC by measuring the global transcriptomic response in the male largemouth liver using an oligonucleotide microarray. Microarray analysis identified highly significant changes in the expression of 37 transcripts (p<0.001) (20 induced and 17 decreased) in the liver after MXC injection and a total of 900 expression changes (p<0.05) in transcripts with high homology to known genes. Largemouth bass estrogen receptor alpha (esr1) and androgen receptor (ar) were among the transcripts that were increased in the liver after MXC treatment. Functional enrichment analysis identified the molecular functions of steroid binding and androgen receptor activity as well as steroid hormone receptor activity as being significantly over-represented gene ontology terms. Pathway analysis identified c-fos signaling as being putatively affected through both estrogen and androgen signaling. This study provides evidence that MXC elicits transcriptional effects through the estrogen receptor as well as androgen receptor-mediated pathways in the liver. PMID:21276474

Integrative molecular network analysis identifies emergent enzalutamide resistance mechanisms in prostate cancer

PubMed Central

King, Carly J.; Woodward, Josha; Schwartzman, Jacob; Coleman, Daniel J.; Lisac, Robert; Wang, Nicholas J.; Van Hook, Kathryn; Gao, Lina; Urrutia, Joshua; Dane, Mark A.; Heiser, Laura M.; Alumkal, Joshi J.

2017-01-01

Recent work demonstrates that castration-resistant prostate cancer (CRPC) tumors harbor countless genomic aberrations that control many hallmarks of cancer. While some specific mutations in CRPC may be actionable, many others are not. We hypothesized that genomic aberrations in cancer may operate in concert to promote drug resistance and tumor progression, and that organization of these genomic aberrations into therapeutically targetable pathways may improve our ability to treat CRPC. To identify the molecular underpinnings of enzalutamide-resistant CRPC, we performed transcriptional and copy number profiling studies using paired enzalutamide-sensitive and resistant LNCaP prostate cancer cell lines. Gene networks associated with enzalutamide resistance were revealed by performing an integrative genomic analysis with the PAthway Representation and Analysis by Direct Reference on Graphical Models (PARADIGM) tool. Amongst the pathways enriched in the enzalutamide-resistant cells were those associated with MEK, EGFR, RAS, and NFKB. Functional validation studies of 64 genes identified 10 candidate genes whose suppression led to greater effects on cell viability in enzalutamide-resistant cells as compared to sensitive parental cells. Examination of a patient cohort demonstrated that several of our functionally-validated gene hits are deregulated in metastatic CRPC tumor samples, suggesting that they may be clinically relevant therapeutic targets for patients with enzalutamide-resistant CRPC. Altogether, our approach demonstrates the potential of integrative genomic analyses to clarify determinants of drug resistance and rational co-targeting strategies to overcome resistance. PMID:29340039

cPath: open source software for collecting, storing, and querying biological pathways.

PubMed

Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris

2006-11-13

Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling.

Conserved and species-specific molecular denominators in mammalian skeletal muscle aging.

PubMed

Mercken, Evi M; Capri, Miriam; Carboneau, Bethany A; Conte, Maria; Heidler, Juliana; Santoro, Aurelia; Martin-Montalvo, Alejandro; Gonzalez-Freire, Marta; Khraiwesh, Husam; González-Reyes, José A; Moaddel, Ruin; Zhang, Yongqing; Becker, Kevin G; Villalba, José M; Mattison, Julie A; Wittig, Ilka; Franceschi, Claudio; de Cabo, Rafael

2017-01-01

Aging is a complex phenomenon involving functional decline in multiple physiological systems. We undertook a comparative analysis of skeletal muscle from four different species, i.e. mice, rats, rhesus monkeys, and humans, at three different representative stages during their lifespan (young, middle, and old) to identify pathways that modulate function and healthspan. Gene expression profiling and computational analysis revealed that pathway complexity increases from mice to humans, and as mammals age, there is predominantly an upregulation of pathways in all species. Two downregulated pathways, the electron transport chain and oxidative phosphorylation, were common among all four species in response to aging. Quantitative PCR, biochemical analysis, mitochondrial DNA measurements, and electron microscopy revealed a conserved age-dependent decrease in mitochondrial content, and a reduction in oxidative phosphorylation complexes in monkeys and humans. Western blot analysis of key proteins in mitochondrial biogenesis discovered that (i) an imbalance toward mitochondrial fusion occurs in aged skeletal muscle and (ii) mitophagy is not overtly affected, presumably leading to the observed accumulation of abnormally large, damaged mitochondria with age. Select transcript expression analysis uncovered that the skeletal inflammatory profile differentially increases with age, but is most pronounced in humans, while increased oxidative stress (as assessed by protein carbonyl adducts and 4-hydroxynonenal) is common among all species. Expression studies also found that there is unique dysregulation of the nutrient sensing pathways among the different species with age. The identification of conserved pathways indicates common molecular mechanisms intrinsic to health and lifespan, whereas the recognition of species-specific pathways emphasizes the importance of human studies for devising optimal therapeutic modalities to slow the aging process.

atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

PubMed

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

A Mechanistic Understanding of Allosteric Immune Escape Pathways in the HIV-1 Envelope Glycoprotein

PubMed Central

Sethi, Anurag; Tian, Jianhui; Derdeyn, Cynthia A.; Korber, Bette; Gnanakaran, S.

2013-01-01

The HIV-1 envelope (Env) spike, which consists of a compact, heterodimeric trimer of the glycoproteins gp120 and gp41, is the target of neutralizing antibodies. However, the high mutation rate of HIV-1 and plasticity of Env facilitates viral evasion from neutralizing antibodies through various mechanisms. Mutations that are distant from the antibody binding site can lead to escape, probably by changing the conformation or dynamics of Env; however, these changes are difficult to identify and define mechanistically. Here we describe a network analysis-based approach to identify potential allosteric immune evasion mechanisms using three known HIV-1 Env gp120 protein structures from two different clades, B and C. First, correlation and principal component analyses of molecular dynamics (MD) simulations identified a high degree of long-distance coupled motions that exist between functionally distant regions within the intrinsic dynamics of the gp120 core, supporting the presence of long-distance communication in the protein. Then, by integrating MD simulations with network theory, we identified the optimal and suboptimal communication pathways and modules within the gp120 core. The results unveil both strain-dependent and -independent characteristics of the communication pathways in gp120. We show that within the context of three structurally homologous gp120 cores, the optimal pathway for communication is sequence sensitive, i.e. a suboptimal pathway in one strain becomes the optimal pathway in another strain. Yet the identification of conserved elements within these communication pathways, termed inter-modular hotspots, could present a new opportunity for immunogen design, as this could be an additional mechanism that HIV-1 uses to shield vulnerable antibody targets in Env that induce neutralizing antibody breadth. PMID:23696718

A high throughput screening for TLR3-IRF3 signaling pathway modulators identifies several antipsychotic drugs as TLR inhibitors1

PubMed Central

Zhu, Jianzhong; Smith, Kevin; Hsieh, Paishiun N.; Mburu, Yvonne K.; Chattopadhyay, Saurabh; Sen, Ganes C.; Sarkar, Saumendra N.

2010-01-01

Toll-like Receptor 3 (TLR3) is one of the major innate immune sensors of double stranded RNA (dsRNA). The signal transduction pathway activated by TLR3, upon binding to dsRNA, leads to the activation of two major transcription factors: NF-κB and IRF3. In an effort to identify specific chemical modulators of TLR3-IRF3 signal transduction pathway we developed a cell-based read out system. Using the interferon stimulated gene 56 (ISG56) promoter driven firefly luciferase gene stably integrated in a TLR3 expressing HEK293 cell line, we were able to generate a cell line where treatment with dsRNA resulted in a dose dependent induction of luciferase activity. A screen of two pharmacologically active compound libraries using this system, identified a number of TLR3-IRF3 signaling pathway modulators. Among them we focused on a subset of inhibitors and characterized their mode of action. Several antipsychotic drugs, such as Sertraline, Trifluoperazine and Fluphenazine were found to be direct inhibitors of the innate immune signaling pathway. These inhibitors also showed the ability to inhibit ISG56 induction mediated by TLR4 and TLR7/8 pathways. Interestingly, they did not show significant effect on TLR3, TLR7 and TLR8 mediated NF-κB activation. Detailed analysis of the signaling pathway indicated that these drugs may be exerting their inhibitory effects on IRF3 via PI3K signaling pathway. The data presented here provides mechanistic explanation of possible anti-inflammatory roles of some antipsychotic drugs. PMID:20382888

Combined analysis of DNA methylome and transcriptome reveal novel candidate genes with susceptibility to bovine Staphylococcus aureus subclinical mastitis.

PubMed

Song, Minyan; He, Yanghua; Zhou, Huangkai; Zhang, Yi; Li, Xizhi; Yu, Ying

2016-07-14

Subclinical mastitis is a widely spread disease of lactating cows. Its major pathogen is Staphylococcus aureus (S. aureus). In this study, we performed genome-wide integrative analysis of DNA methylation and transcriptional expression to identify candidate genes and pathways relevant to bovine S. aureus subclinical mastitis. The genome-scale DNA methylation profiles of peripheral blood lymphocytes in cows with S. aureus subclinical mastitis (SA group) and healthy controls (CK) were generated by methylated DNA immunoprecipitation combined with microarrays. We identified 1078 differentially methylated genes in SA cows compared with the controls. By integrating DNA methylation and transcriptome data, 58 differentially methylated genes were shared with differently expressed genes, in which 20.7% distinctly hypermethylated genes showed down-regulated expression in SA versus CK, whereas 14.3% dramatically hypomethylated genes showed up-regulated expression. Integrated pathway analysis suggested that these genes were related to inflammation, ErbB signalling pathway and mismatch repair. Further functional analysis revealed that three genes, NRG1, MST1 and NAT9, were strongly correlated with the progression of S. aureus subclinical mastitis and could be used as powerful biomarkers for the improvement of bovine mastitis resistance. Our studies lay the groundwork for epigenetic modification and mechanistic studies on susceptibility of bovine mastitis.

Combined analysis of DNA methylome and transcriptome reveal novel candidate genes with susceptibility to bovine Staphylococcus aureus subclinical mastitis

PubMed Central

Song, Minyan; He, Yanghua; Zhou, Huangkai; Zhang, Yi; Li, Xizhi; Yu, Ying

2016-01-01

Subclinical mastitis is a widely spread disease of lactating cows. Its major pathogen is Staphylococcus aureus (S. aureus). In this study, we performed genome-wide integrative analysis of DNA methylation and transcriptional expression to identify candidate genes and pathways relevant to bovine S. aureus subclinical mastitis. The genome-scale DNA methylation profiles of peripheral blood lymphocytes in cows with S. aureus subclinical mastitis (SA group) and healthy controls (CK) were generated by methylated DNA immunoprecipitation combined with microarrays. We identified 1078 differentially methylated genes in SA cows compared with the controls. By integrating DNA methylation and transcriptome data, 58 differentially methylated genes were shared with differently expressed genes, in which 20.7% distinctly hypermethylated genes showed down-regulated expression in SA versus CK, whereas 14.3% dramatically hypomethylated genes showed up-regulated expression. Integrated pathway analysis suggested that these genes were related to inflammation, ErbB signalling pathway and mismatch repair. Further functional analysis revealed that three genes, NRG1, MST1 and NAT9, were strongly correlated with the progression of S. aureus subclinical mastitis and could be used as powerful biomarkers for the improvement of bovine mastitis resistance. Our studies lay the groundwork for epigenetic modification and mechanistic studies on susceptibility of bovine mastitis. PMID:27411928

Treatment of obstructive sleep apnea alters cancer-associated transcriptional signatures in circulating leukocytes.

PubMed

Gharib, Sina A; Seiger, Ashley N; Hayes, Amanda L; Mehra, Reena; Patel, Sanjay R

2014-04-01

Obstructive sleep apnea (OSA) has been associated with a number of chronic disorders that may improve with effective therapy. However, the molecular pathways affected by continuous positive airway pressure (CPAP) treatment are largely unknown. We sought to assess the system-wide consequences of CPAP therapy by transcriptionally profiling peripheral blood leukocytes (PBLs). Subjects in whom severe OSA was diagnosed were treated with CPAP, and whole-genome expression measurement of PBLs was performed at baseline and following therapy. We used gene set enrichment analysis (GSEA) to identify pathways that were differentially enriched. Network analysis was then applied to highlight key drivers of processes influenced by CPAP. Eighteen subjects with significant OSA underwent CPAP therapy and microarray analysis of their PBLs. Treatment with CPAP improved apnea-hypopnea index (AHI), daytime sleepiness, and blood pressure, but did not affect anthropometric measures. GSEA revealed a number of enriched gene sets, many of which were involved in neoplastic processes and displayed downregulated expression patterns in response to CPAP. Network analysis identified several densely connected genes that are important modulators of cancer and tumor growth. Effective therapy of OSA with CPAP is associated with alterations in circulating leukocyte gene expression. Functional enrichment and network analyses highlighted transcriptional suppression in cancer-related pathways, suggesting potentially novel mechanisms linking OSA with neoplastic signatures.

Use of eQTL Analysis for the Discovery of Target Genes Identified by GWAS

DTIC Science & Technology

2013-04-01

the biologic pathways affected by these inherited factors, and ultimately to identify targets for disease prediction, risk stratification and...quality using an Agilent chip technology. Cases having a RIN number of 7.0 or greater were considered good quality. Once completed, the optimum set of...AD_________________ Award Number: W81XWH-11-1-0261 TITLE: Use of eQTL Analysis for the Discovery of

Cerebrospinal fluid metabolomic profiling in tuberculous and viral meningitis: Screening potential markers for differential diagnosis.

PubMed

Li, Zihui; Du, Boping; Li, Jing; Zhang, Jinli; Zheng, Xiaojing; Jia, Hongyan; Xing, Aiying; Sun, Qi; Liu, Fei; Zhang, Zongde

2017-03-01

Tuberculous meningitis (TBM) is the most severe and frequent form of central nervous system tuberculosis. The current lack of efficient diagnostic tests makes it difficult to differentiate TBM from other common types of meningitis, especially viral meningitis (VM). Metabolomics is an important tool to identify disease-specific biomarkers. However, little metabolomic information is available on adult TBM. We used 1 H nuclear magnetic resonance-based metabolomics to investigate the metabolic features of the CSF from 18 TBM and 20 VM patients. Principal component analysis and orthogonal signal correction-partial least squares-discriminant analysis (OSC-PLS-DA) were applied to analyze profiling data. Metabolites were identified using the Human Metabolome Database and pathway analysis was performed with MetaboAnalyst 3.0. The OSC-PLS-DA model could distinguish TBM from VM with high reliability. A total of 25 key metabolites that contributed to their discrimination were identified, including some, such as betaine and cyclohexane, rarely reported before in TBM. Pathway analysis indicated that amino acid and energy metabolism was significantly different in the CSF of TBM compared with VM. Twenty-five key metabolites identified in our study may be potential biomarkers for TBM differential diagnosis and are worthy of further investigation. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification and Characteristics of microRNAs from Army Worm, Spodoptera frugiperda Cell Line Sf21

PubMed Central

Kakumani, Pavan Kumar; Chinnappan, Mahendran; Singh, Ashok K.; Malhotra, Pawan; Mukherjee, Sunil K.; Bhatnagar, Raj K.

2015-01-01

microRNAs play important regulatory role in all intrinsic cellular functions. Amongst lepidopteran insects, miRNAs from only Bombyx mori have been studied extensively with a little focus on Spodoptera sp. In the present study, we identified a total of 226 miRNAs from Spodoptera frugiperda cell line Sf21. Of the total, 116 miRNAs were well conserved within other insects, like B. mori, Drosophila melanogaster and Tribolium castenum while the remaining 110 miRNAs were identified as novel based on comparative analysis with the insect miRNA data set. Landscape distribution analysis based on Sf21 genome assembly revealed clustering of few novel miRNAs. A total of 5 miRNA clusters were identified and the largest one encodes 5 miRNA genes. In addition, 12 miRNAs were validated using northern blot analysis and putative functional role assignment for 6 Sf miRNAs was investigated by examining their relative abundance at different developmental stages of Spodoptera litura and body parts of 6th instar larvae. Further, we identified a total of 809 potential target genes with GO terms for selected miRNAs, involved in different metabolic and signalling pathways of the insect. The newly identified miRNAs greatly enrich the repertoire of insect miRNAs and analysis of expression profiles reveal their involvement at various steps of biochemical pathways of the army worm. PMID:25693181

Identification and characteristics of microRNAs from army worm, Spodoptera frugiperda cell line Sf21.

PubMed

Kakumani, Pavan Kumar; Chinnappan, Mahendran; Singh, Ashok K; Malhotra, Pawan; Mukherjee, Sunil K; Bhatnagar, Raj K

2015-01-01

microRNAs play important regulatory role in all intrinsic cellular functions. Amongst lepidopteran insects, miRNAs from only Bombyx mori have been studied extensively with a little focus on Spodoptera sp. In the present study, we identified a total of 226 miRNAs from Spodoptera frugiperda cell line Sf21. Of the total, 116 miRNAs were well conserved within other insects, like B. mori, Drosophila melanogaster and Tribolium castenum while the remaining 110 miRNAs were identified as novel based on comparative analysis with the insect miRNA data set. Landscape distribution analysis based on Sf21 genome assembly revealed clustering of few novel miRNAs. A total of 5 miRNA clusters were identified and the largest one encodes 5 miRNA genes. In addition, 12 miRNAs were validated using northern blot analysis and putative functional role assignment for 6 Sf miRNAs was investigated by examining their relative abundance at different developmental stages of Spodoptera litura and body parts of 6th instar larvae. Further, we identified a total of 809 potential target genes with GO terms for selected miRNAs, involved in different metabolic and signalling pathways of the insect. The newly identified miRNAs greatly enrich the repertoire of insect miRNAs and analysis of expression profiles reveal their involvement at various steps of biochemical pathways of the army worm.

Characterization of Folding Mechanisms of Trp-cage and WW-domain by Network Analysis of Simulations with a Hybrid-resolution Model

PubMed Central

Han, Wei; Schulten, Klaus

2013-01-01

In this study, we apply a hybrid-resolution model, namely PACE, to characterize the free energy surfaces (FESs) of trp-cage and a WW domain variant along with the respective folding mechanisms. Unbiased, independent simulations with PACE are found to achieve together multiple folding and unfolding events for both proteins, allowing us to perform network analysis of the FESs to identify folding pathways. PACE reproduces for both proteins expected complexity hidden in the folding FESs, in particular, meta-stable non-native intermediates. Pathway analysis shows that some of these intermediates are, actually, on-pathway folding intermediates and that intermediates kinetically closest to the native states can be either critical on-pathway or off-pathway intermediates, depending on the protein. Apart from general insights into folding, specific folding mechanisms of the proteins are resolved. We find that trp-cage folds via a dominant pathway in which hydrophobic collapse occurs before the N-terminal helix forms; full incorporation of Trp6 into the hydrophobic core takes place as the last step of folding, which, however, may not be the rate-limiting step. For the WW domain variant studied we observe two main folding pathways with opposite orders of formation of the two hairpins involved in the structure; for either pathway, formation of hairpin 1 is more likely to be the rate-limiting step. Altogether, our results suggest that PACE combined with network analysis is a computationally efficient and valuable tool for the study of protein folding. PMID:23915394

Analysis of transcriptome in hickory (Carya cathayensis), and uncover the dynamics in the hormonal signaling pathway during graft process.

PubMed

Qiu, Lingling; Jiang, Bo; Fang, Jia; Shen, Yike; Fang, Zhongxiang; Rm, Saravana Kumar; Yi, Keke; Shen, Chenjia; Yan, Daoliang; Zheng, Bingsong

2016-11-17

Hickory (Carya cathayensis), a woody plant with high nutritional and economic value, is widely planted in China. Due to its long juvenile phase, grafting is a useful technique for large-scale cultivation of hickory. To reveal the molecular mechanism during the graft process, we sequenced the transcriptomes of graft union in hickory. In our study, six RNA-seq libraries yielded a total of 83,676,860 clean short reads comprising 4.19 Gb of sequence data. A large number of differentially expressed genes (DEGs) at three time points during the graft process were identified. In detail, 777 DEGs in the 7 d vs 0 d (day after grafting) comparison were classified into 11 enriched Gene Ontology (GO) categories, and 262 DEGs in the 14 d vs 0 d comparison were classified into 15 enriched GO categories. Furthermore, an overview of the PPI network was constructed by these DEGs. In addition, 20 genes related to the auxin-and cytokinin-signaling pathways were identified, and some were validated by qRT-PCR analysis. Our comprehensive analysis provides basic information on the candidate genes and hormone signaling pathways involved in the graft process in hickory and other woody plants.

Backdoor pathway for dihydrotestosterone biosynthesis: implications for normal and abnormal human sex development.

PubMed

Fukami, Maki; Homma, Keiko; Hasegawa, Tomonobu; Ogata, Tsutomu

2013-04-01

We review the current knowledge about the "backdoor" pathway for the biosynthesis of dihydrotestosterone (DHT). While DHT is produced from cholesterol through the conventional "frontdoor" pathway via testosterone, recent studies have provided compelling evidence for the presence of an alternative "backdoor" pathway to DHT without testosterone intermediacy. This backdoor pathway is known to exist in the tammar wallaby pouch young testis and the immature mouse testis, and has been suggested to be present in the human as well. Indeed, molecular analysis has identified pathologic mutations of genes involved in the backdoor pathway in genetic male patients with undermasculinized external genitalia, and urine steroid profile analysis has argued for the relevance of the activated backdoor pathway to abnormal virilization in genetic females with cytochrome P450 oxidoreductase deficiency and 21-hydroxylase deficiency. It is likely that the backdoor pathway is primarily operating in the fetal testis in a physiological condition to produce a sufficient amount of DHT for male sex development, and that the backdoor pathway is driven with a possible interaction between fetal and permanent adrenals in pathologic conditions with increased 17-hydroxyprogesterone levels. These findings provide novel insights into androgen biosynthesis in both physiological and pathological conditions. Copyright © 2012 Wiley Periodicals, Inc., a Wiley company.

Analysis of PIK3CA Mutations and Activation Pathways in Triple Negative Breast Cancer

PubMed Central

Muroni, Maria Rosaria; Sanges, Francesca; Sotgiu, Giovanni; Ena, Sara; Pira, Giovanna; Murgia, Luciano; Manca, Alessandra; Uras, Maria Gabriela; Sarobba, Maria Giuseppina; Urru, Silvana; De Miglio, Maria Rosaria

2015-01-01

Background Triple Negative Breast Cancer (TNBC) accounts for 12–24% of all breast carcinomas, and shows worse prognosis compared to other breast cancer subtypes. Molecular studies demonstrated that TNBCs are a heterogeneous group of tumors with different clinical and pathologic features, prognosis, genetic-molecular alterations and treatment responsivity. The PI3K/AKT is a major pathway involved in the regulation of cell survival and proliferation, and is the most frequently altered pathway in breast cancer, apparently with different biologic impact on specific cancer subtypes. The most common genetic abnormality is represented by PIK3CA gene activating mutations, with an overall frequency of 20–40%. The aims of our study were to investigate PIK3CA gene mutations on a large series of TNBC, to perform a wider analysis on genetic alterations involving PI3K/AKT and BRAF/RAS/MAPK pathways and to correlate the results with clinical-pathologic data. Materials and Methods PIK3CA mutation analysis was performed by using cobas® PIK3CA Mutation Test. EGFR, AKT1, BRAF, and KRAS genes were analyzed by sequencing. Immunohistochemistry was carried out to identify PTEN loss and to investigate for PI3K/AKT pathways components. Results PIK3CA mutations were detected in 23.7% of TNBC, whereas no mutations were identified in EGFR, AKT1, BRAF, and KRAS genes. Moreover, we observed PTEN loss in 11.3% of tumors. Deregulation of PI3K/AKT pathways was revealed by consistent activation of pAKT and p-p44/42 MAPK in all PIK3CA mutated TNBC. Conclusions Our data shows that PIK3CA mutations and PI3K/AKT pathway activation are common events in TNBC. A deeper investigation on specific TNBC genomic abnormalities might be helpful in order to select patients who would benefit from current targeted therapy strategies. PMID:26540293

Analysis of PIK3CA Mutations and Activation Pathways in Triple Negative Breast Cancer.

PubMed

Cossu-Rocca, Paolo; Orrù, Sandra; Muroni, Maria Rosaria; Sanges, Francesca; Sotgiu, Giovanni; Ena, Sara; Pira, Giovanna; Murgia, Luciano; Manca, Alessandra; Uras, Maria Gabriela; Sarobba, Maria Giuseppina; Urru, Silvana; De Miglio, Maria Rosaria

2015-01-01

Triple Negative Breast Cancer (TNBC) accounts for 12-24% of all breast carcinomas, and shows worse prognosis compared to other breast cancer subtypes. Molecular studies demonstrated that TNBCs are a heterogeneous group of tumors with different clinical and pathologic features, prognosis, genetic-molecular alterations and treatment responsivity. The PI3K/AKT is a major pathway involved in the regulation of cell survival and proliferation, and is the most frequently altered pathway in breast cancer, apparently with different biologic impact on specific cancer subtypes. The most common genetic abnormality is represented by PIK3CA gene activating mutations, with an overall frequency of 20-40%. The aims of our study were to investigate PIK3CA gene mutations on a large series of TNBC, to perform a wider analysis on genetic alterations involving PI3K/AKT and BRAF/RAS/MAPK pathways and to correlate the results with clinical-pathologic data. PIK3CA mutation analysis was performed by using cobas® PIK3CA Mutation Test. EGFR, AKT1, BRAF, and KRAS genes were analyzed by sequencing. Immunohistochemistry was carried out to identify PTEN loss and to investigate for PI3K/AKT pathways components. PIK3CA mutations were detected in 23.7% of TNBC, whereas no mutations were identified in EGFR, AKT1, BRAF, and KRAS genes. Moreover, we observed PTEN loss in 11.3% of tumors. Deregulation of PI3K/AKT pathways was revealed by consistent activation of pAKT and p-p44/42 MAPK in all PIK3CA mutated TNBC. Our data shows that PIK3CA mutations and PI3K/AKT pathway activation are common events in TNBC. A deeper investigation on specific TNBC genomic abnormalities might be helpful in order to select patients who would benefit from current targeted therapy strategies.

Work and family transitions and the self-rated health of young women in South Africa.

PubMed

Bennett, Rachel; Waterhouse, Philippa

2018-04-01

Understanding the transition to adulthood has important implications for supporting young adults and understanding the roots of diversity in wellbeing later in life. In South Africa, the end of Apartheid means today's youth are experiencing their transition to adulthood in a changed social and political context which offers opportunities compared to the past but also threats. This paper presents the first national level analysis of the patterning of key transitions (completion of education, entry into the labour force, motherhood and marriage or cohabitation), and the association between the different pathways and health amongst young women. With the use of longitudinal data from the South African National Income Dynamics Study (2008-2015), this paper employs sequence analysis to identify common pathways to adulthood amongst women aged 15-17 years at baseline (n = 429) and logistic regression modelling to examine the association between these pathways and self-rated health. The sequence analysis identified five pathways: 1. 'Non-activity commonly followed by motherhood', 2. 'Pathway from school, motherhood then work', 3. 'Motherhood combined with schooling', 4. 'Motherhood after schooling', and 5. 'Schooling to non-activity'. After controlling for baseline socio-economic and demographic characteristics and health, the regression results show young women who followed pathways characterised by early motherhood and economic inactivity (1, 3 and 4) had poorer self-rated health compared to women whose pathways were characterised by combining motherhood and economic activity (2) and young women who were yet to become economically active or mothers (5). Therefore, policies should seek to prevent adolescent childbearing, support young mothers to continue their educational careers and enable mothers in work and seeking work to balance their work and care responsibilities. Further, the findings highlight the value of taking a holistic approach to health and provide further evidence for the need to consider work-family balance in the development agenda. Copyright © 2018 Elsevier Ltd. All rights reserved.

Screening key candidate genes and pathways involved in insulinoma by microarray analysis.

PubMed

Zhou, Wuhua; Gong, Li; Li, Xuefeng; Wan, Yunyan; Wang, Xiangfei; Li, Huili; Jiang, Bin

2018-06-01

Insulinoma is a rare type tumor and its genetic features remain largely unknown. This study aimed to search for potential key genes and relevant enriched pathways of insulinoma.The gene expression data from GSE73338 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified between insulinoma tissues and normal pancreas tissues, followed by pathway enrichment analysis, protein-protein interaction (PPI) network construction, and module analysis. The expressions of candidate key genes were validated by quantitative real-time polymerase chain reaction (RT-PCR) in insulinoma tissues.A total of 1632 DEGs were obtained, including 1117 upregulated genes and 514 downregulated genes. Pathway enrichment results showed that upregulated DEGs were significantly implicated in insulin secretion, and downregulated DEGs were mainly enriched in pancreatic secretion. PPI network analysis revealed 7 hub genes with degrees more than 10, including GCG (glucagon), GCGR (glucagon receptor), PLCB1 (phospholipase C, beta 1), CASR (calcium sensing receptor), F2R (coagulation factor II thrombin receptor), GRM1 (glutamate metabotropic receptor 1), and GRM5 (glutamate metabotropic receptor 5). DEGs involved in the significant modules were enriched in calcium signaling pathway, protein ubiquitination, and platelet degranulation. Quantitative RT-PCR data confirmed that the expression trends of these hub genes were similar to the results of bioinformatic analysis.The present study demonstrated that candidate DEGs and enriched pathways were the potential critical molecule events involved in the development of insulinoma, and these findings were useful for better understanding of insulinoma genesis.

An analysis of gene expression data involving examination of signaling pathways activation reveals new insights into the mechanism of action of minoxidil topical foam in men with androgenetic alopecia

PubMed Central

Wu, Jeff; Pappas, Apostolos; Mirmirani, Paradi; McCormick, Thomas S.; Cooper, Kevin D.; Schastnaya, Jane; Ozerov, Ivan V.; Aliper, Alexander; Zhavoronkov, Alex

2017-01-01

ABSTRACT Androgenetic alopecia is the most common form of hair loss. Minoxidil has been approved for the treatment of hair loss, however its mechanism of action is still not fully clarified. In this study, we aimed to elucidate the effects of 5% minoxidil topical foam on gene expression and activation of signaling pathways in vertex and frontal scalp of men with androgenetic alopecia. We identified regional variations in gene expression and perturbed signaling pathways using in silico Pathway Activation Network Decomposition Analysis (iPANDA) before and after treatment with minoxidil. Vertex and frontal scalp of patients showed a generally similar response to minoxidil. Both scalp regions showed upregulation of genes that encode keratin associated proteins and downregulation of ILK, Akt, and MAPK signaling pathways after minoxidil treatment. Our results provide new insights into the mechanism of action of minoxidil topical foam in men with androgenetic alopecia. PMID:28594262

An analysis of gene expression data involving examination of signaling pathways activation reveals new insights into the mechanism of action of minoxidil topical foam in men with androgenetic alopecia.

PubMed

Stamatas, Georgios N; Wu, Jeff; Pappas, Apostolos; Mirmirani, Paradi; McCormick, Thomas S; Cooper, Kevin D; Consolo, Mary; Schastnaya, Jane; Ozerov, Ivan V; Aliper, Alexander; Zhavoronkov, Alex

2017-01-01

Androgenetic alopecia is the most common form of hair loss. Minoxidil has been approved for the treatment of hair loss, however its mechanism of action is still not fully clarified. In this study, we aimed to elucidate the effects of 5% minoxidil topical foam on gene expression and activation of signaling pathways in vertex and frontal scalp of men with androgenetic alopecia. We identified regional variations in gene expression and perturbed signaling pathways using in silico Pathway Activation Network Decomposition Analysis (iPANDA) before and after treatment with minoxidil. Vertex and frontal scalp of patients showed a generally similar response to minoxidil. Both scalp regions showed upregulation of genes that encode keratin associated proteins and downregulation of ILK, Akt, and MAPK signaling pathways after minoxidil treatment. Our results provide new insights into the mechanism of action of minoxidil topical foam in men with androgenetic alopecia.

Pathway redundancy and protein essentiality revealed in the Saccharomyces cerevisiae interaction networks

PubMed Central

Ulitsky, Igor; Shamir, Ron

2007-01-01

The biological interpretation of genetic interactions is a major challenge. Recently, Kelley and Ideker proposed a method to analyze together genetic and physical networks, which explains many of the known genetic interactions as linking different pathways in the physical network. Here, we extend this method and devise novel analytic tools for interpreting genetic interactions in a physical context. Applying these tools on a large-scale Saccharomyces cerevisiae data set, our analysis reveals 140 between-pathway models that explain 3765 genetic interactions, roughly doubling those that were previously explained. Model genes tend to have short mRNA half-lives and many phosphorylation sites, suggesting that their stringent regulation is linked to pathway redundancy. We also identify ‘pivot' proteins that have many physical interactions with both pathways in our models, and show that pivots tend to be essential and highly conserved. Our analysis of models and pivots sheds light on the organization of the cellular machinery as well as on the roles of individual proteins. PMID:17437029

Characterizing biomarkers in osteosarcoma metastasis based on an ego-network.

PubMed

Liu, Zhen; Song, Yan

2017-06-01

To characterize biomarkers that underlie osteosarcoma (OS) metastasis based on an ego-network. From the microarray data, we obtained 13,326 genes. By combining PPI data and microarray data, 10,520 shared genes were found and constructed into ego-networks. 17 significant ego-networks were identified with p < 0.05. In the pathway enrichment analysis, seven ego-networks were identified with the most significant pathway. These significant ego-modules were potential biomarkers that reveal the potential mechanisms in OS metastasis, which may contribute to understanding cancer prognoses and providing new perspectives in the treatment of cancer.

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma

PubMed Central

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-01-01

Objective This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Methods Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Results Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification (P=0.009) or deletion (P=0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly (P=1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Conclusion Chromosomal CNVs may contribute to their transcript expression in cervical cancer. PMID:29312578

Identification of Potential Anticancer Activities of Novel Ganoderma lucidum Extracts Using Gene Expression and Pathway Network Analysis

PubMed Central

Kao, Chi H.J.; Bishop, Karen S.; Xu, Yuanye; Han, Dug Yeo; Murray, Pamela M.; Marlow, Gareth J.; Ferguson, Lynnette R.

2016-01-01

Ganoderma lucidum (lingzhi) has been used for the general promotion of health in Asia for many centuries. The common method of consumption is to boil lingzhi in water and then drink the liquid. In this study, we examined the potential anticancer activities of G. lucidum submerged in two commonly consumed forms of alcohol in East Asia: malt whiskey and rice wine. The anticancer effect of G. lucidum, using whiskey and rice wine-based extraction methods, has not been previously reported. The growth inhibition of G. lucidum whiskey and rice wine extracts on the prostate cancer cell lines, PC3 and DU145, was determined. Using Affymetrix gene expression assays, several biologically active pathways associated with the anticancer activities of G. lucidum extracts were identified. Using gene expression analysis (real-time polymerase chain reaction [RT-PCR]) and protein analysis (Western blotting), we confirmed the expression of key genes and their associated proteins that were initially identified with Affymetrix gene expression analysis. PMID:27006591

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma.

PubMed

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-12-12

This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification ( P =0.009) or deletion ( P =0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly ( P =1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Chromosomal CNVs may contribute to their transcript expression in cervical cancer.

Jejunal long noncoding RNAs are associated with glycemic control via gut-brain axis after bariatric surgery in diabetic mice.

PubMed

Liang, Yongjun; Yu, Bo; Wang, Yueqian; Qiao, Zhengdong; Cao, Ting; Zhang, Peng

2018-06-01

Metabolic and bariatric surgery is effective in ameliorating type 2 diabetes, although its underlying mechanisms are largely unknown. Our previous study indicated that the distinctly expressed duodenal long noncoding RNAs (lncRNAs) induced by the duodenal-jejunal bypass (DJB) might play a role in improving glycemic control via the enteropancreatic axis. Therefore, the physiologic role of the jejunum in metabolic regulation after DJB requires investigation. To investigate the alterations in the jejunal Roux limb lncRNA expression signatures after DJB and analyze the functional pathways associated with metabolic improvement on a genome-wide scale in high-fat diet-induced diabetic mice. University medical center. Diabetic mice induced by high-fat diet were randomly assigned into 2 groups undergoing either DJB or sham surgery. The lncRNA and messenger (m)RNA expression profiles of the Roux limb segment of the jejunum in both groups were investigated using microarray. To identify the functional characteristics of the distinctly expressed lncRNAs, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted. The lncRNA-mRNA and lncRNA-transcription factor interaction networks were constructed based on Pearson correlation analysis. Compared with the sham group, 827 dysregulated (fold change ≥2.0) jejunal lncRNAs were identified in the DJB group. Both Kyoto Encyclopedia of Genes and Genomes pathway and gene ontology enrichment analysis revealed that 601 lncRNA-co-expressed mRNAs (fold change ≥2.0) were associated with neuromodulation-related pathways or biological processes, including serotonergic, glutamatergic, and dopaminergic synapses. In addition, hormonal regulation-related pathways, especially steroid biosynthesis, were also enriched. The results were further confirmed by bioinformatic analysis of target genes or transcription factors predicted on the basis of dysregulated jejunal lncRNAs. Furthermore, the NONMMUT023781 lncRNA may simultaneously target the Adcy8 mRNA both in cis and in trans and participate in neuromodulation and hormonal regulation. Alterations of jejunal Roux limb lncRNA and mRNA expression profiles trigger both neuromodulation and endocrine-related pathways, which play a critical role in type 2 diabetes remission after metabolic and bariatric surgery via the gut-brain axis. NONMMTU023781 and Adcy8 were identified as potential targets, which warrant further research. Copyright © 2018 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Endothelial Inflammatory Transcriptional Responses Induced by Plasma Following Inhalation of Diesel Emissions

PubMed Central

Schisler, Jonathan C.; Ronnebaum, Sarah M.; Madden, Michael; Channell, Meghan M.; Campen, Matthew J.; Willis, Monte S.

2016-01-01

Background Air pollution, especially emissions derived from traffic sources, is associated with adverse cardiovascular outcomes. However, it remains unclear how inhaled factors drive extrapulmonary pathology. Objectives Previously, we found that canonical inflammatory response transcripts were elevated in cultured endothelial cells treated with plasma obtained after exposure compared with pre-exposure samples or filtered air (sham) exposures. While the findings confirmed the presence of bioactive factor(s) in the plasma after diesel inhalation, we wanted to better examine the complete genomic response to investigate 1) major responsive transcripts and 2) collected response pathways and ontogeny that may help to refine this method and inform the pathogenesis. Methods We assayed endothelial RNA with gene expression microarrays, examining the responses of cultured endothelial cells to plasma obtained from 6 healthy human subjects exposed to 100 μg/m3 diesel exhaust or filtered air for 2 h on separate occasions. In addition to pre-exposure baseline samples, we investigated samples obtained immediately-post and 24h-post exposure. Results Microarray analysis of the coronary artery endothelial cells challenged with plasma identified 855 probes that changed over time following diesel exhaust exposure. Over-representation analysis identified inflammatory cytokine pathways were upregulated both at the 2 and 24 h condition. Novel pathways related to FOX transcription factors and secreted extracellular factors were also identified in the microarray analysis. Conclusions These outcomes are consistent with our recent findings that plasma contains bioactive and inflammatory factors following pollutant inhalation. The specific study design implicates a novel pathway related to inflammatory blood borne components that may drive the extrapulmonary toxicity of ambient air pollutants. PMID:25942053

Transcriptome-Wide Analysis of Hepatitis B Virus-Mediated Changes to Normal Hepatocyte Gene Expression.

PubMed

Lamontagne, Jason; Mell, Joshua C; Bouchard, Michael J

2016-02-01

Globally, a chronic hepatitis B virus (HBV) infection remains the leading cause of primary liver cancer. The mechanisms leading to the development of HBV-associated liver cancer remain incompletely understood. In part, this is because studies have been limited by the lack of effective model systems that are both readily available and mimic the cellular environment of a normal hepatocyte. Additionally, many studies have focused on single, specific factors or pathways that may be affected by HBV, without addressing cell physiology as a whole. Here, we apply RNA-seq technology to investigate transcriptome-wide, HBV-mediated changes in gene expression to identify single factors and pathways as well as networks of genes and pathways that are affected in the context of HBV replication. Importantly, these studies were conducted in an ex vivo model of cultured primary hepatocytes, allowing for the transcriptomic characterization of this model system and an investigation of early HBV-mediated effects in a biologically relevant context. We analyzed differential gene expression within the context of time-mediated gene-expression changes and show that in the context of HBV replication a number of genes and cellular pathways are altered, including those associated with metabolism, cell cycle regulation, and lipid biosynthesis. Multiple analysis pipelines, as well as qRT-PCR and an independent, replicate RNA-seq analysis, were used to identify and confirm differentially expressed genes. HBV-mediated alterations to the transcriptome that we identified likely represent early changes to hepatocytes following an HBV infection, suggesting potential targets for early therapeutic intervention. Overall, these studies have produced a valuable resource that can be used to expand our understanding of the complex network of host-virus interactions and the impact of HBV-mediated changes to normal hepatocyte physiology on viral replication.

SFRP1 is a possible candidate for epigenetic therapy in non-small cell lung cancer.

PubMed

Taguchi, Y-H; Iwadate, Mitsuo; Umeyama, Hideaki

2016-08-12

Non-small cell lung cancer (NSCLC) remains a lethal disease despite many proposed treatments. Recent studies have indicated that epigenetic therapy, which targets epigenetic effects, might be a new therapeutic methodology for NSCLC. However, it is not clear which objects (e.g., genes) this treatment specifically targets. Secreted frizzled-related proteins (SFRPs) are promising candidates for epigenetic therapy in many cancers, but there have been no reports of SFRPs targeted by epigenetic therapy for NSCLC. This study performed a meta-analysis of reprogrammed NSCLC cell lines instead of the direct examination of epigenetic therapy treatment to identify epigenetic therapy targets. In addition, mRNA expression/promoter methylation profiles were processed by recently proposed principal component analysis based unsupervised feature extraction and categorical regression analysis based feature extraction. The Wnt/β-catenin signalling pathway was extensively enriched among 32 genes identified by feature extraction. Among the genes identified, SFRP1 was specifically indicated to target β-catenin, and thus might be targeted by epigenetic therapy in NSCLC cell lines. A histone deacetylase inhibitor might reactivate SFRP1 based upon the re-analysis of a public domain data set. Numerical computation validated the binding of SFRP1 to WNT1 to suppress Wnt signalling pathway activation in NSCLC. The meta-analysis of reprogrammed NSCLC cell lines identified SFRP1 as a promising target of epigenetic therapy for NSCLC.

Pathway analyses and understanding disease associations

PubMed Central

Liu, Yu; Chance, Mark R

2013-01-01

High throughput technologies have been applied to investigate the underlying mechanisms of complex diseases, identify disease-associations and help to improve treatment. However it is challenging to derive biological insight from conventional single gene based analysis of “omics” data from high throughput experiments due to sample and patient heterogeneity. To address these challenges, many novel pathway and network based approaches were developed to integrate various “omics” data, such as gene expression, copy number alteration, Genome Wide Association Studies, and interaction data. This review will cover recent methodological developments in pathway analysis for the detection of dysregulated interactions and disease-associated subnetworks, prioritization of candidate disease genes, and disease classifications. For each application, we will also discuss the associated challenges and potential future directions. PMID:24319650

SASD: the Synthetic Alternative Splicing Database for identifying novel isoform from proteomics

PubMed Central

2013-01-01

Background Alternative splicing is an important and widespread mechanism for generating protein diversity and regulating protein expression. High-throughput identification and analysis of alternative splicing in the protein level has more advantages than in the mRNA level. The combination of alternative splicing database and tandem mass spectrometry provides a powerful technique for identification, analysis and characterization of potential novel alternative splicing protein isoforms from proteomics. Therefore, based on the peptidomic database of human protein isoforms for proteomics experiments, our objective is to design a new alternative splicing database to 1) provide more coverage of genes, transcripts and alternative splicing, 2) exclusively focus on the alternative splicing, and 3) perform context-specific alternative splicing analysis. Results We used a three-step pipeline to create a synthetic alternative splicing database (SASD) to identify novel alternative splicing isoforms and interpret them at the context of pathway, disease, drug and organ specificity or custom gene set with maximum coverage and exclusive focus on alternative splicing. First, we extracted information on gene structures of all genes in the Ensembl Genes 71 database and incorporated the Integrated Pathway Analysis Database. Then, we compiled artificial splicing transcripts. Lastly, we translated the artificial transcripts into alternative splicing peptides. The SASD is a comprehensive database containing 56,630 genes (Ensembl gene IDs), 95,260 transcripts (Ensembl transcript IDs), and 11,919,779 Alternative Splicing peptides, and also covering about 1,956 pathways, 6,704 diseases, 5,615 drugs, and 52 organs. The database has a web-based user interface that allows users to search, display and download a single gene/transcript/protein, custom gene set, pathway, disease, drug, organ related alternative splicing. Moreover, the quality of the database was validated with comparison to other known databases and two case studies: 1) in liver cancer and 2) in breast cancer. Conclusions The SASD provides the scientific community with an efficient means to identify, analyze, and characterize novel Exon Skipping and Intron Retention protein isoforms from mass spectrometry and interpret them at the context of pathway, disease, drug and organ specificity or custom gene set with maximum coverage and exclusive focus on alternative splicing. PMID:24267658

A proteomic analysis of LRRK2 binding partners reveals interactions with multiple signaling components of the WNT/PCP pathway.

PubMed

Salašová, Alena; Yokota, Chika; Potěšil, David; Zdráhal, Zbyněk; Bryja, Vítězslav; Arenas, Ernest

2017-07-11

Autosomal-dominant mutations in the Park8 gene encoding Leucine-rich repeat kinase 2 (LRRK2) have been identified to cause up to 40% of the genetic forms of Parkinson's disease. However, the function and molecular pathways regulated by LRRK2 are largely unknown. It has been shown that LRRK2 serves as a scaffold during activation of WNT/β-catenin signaling via its interaction with the β-catenin destruction complex, DVL1-3 and LRP6. In this study, we examine whether LRRK2 also interacts with signaling components of the WNT/Planar Cell Polarity (WNT/PCP) pathway, which controls the maturation of substantia nigra dopaminergic neurons, the main cell type lost in Parkinson's disease patients. Co-immunoprecipitation and tandem mass spectrometry was performed in a mouse substantia nigra cell line (SN4741) and human HEK293T cell line in order to identify novel LRRK2 binding partners. Inhibition of the WNT/β-catenin reporter, TOPFlash, was used as a read-out of WNT/PCP pathway activation. The capacity of LRRK2 to regulate WNT/PCP signaling in vivo was tested in Xenopus laevis' early development. Our proteomic analysis identified that LRRK2 interacts with proteins involved in WNT/PCP signaling such as the PDZ domain-containing protein GIPC1 and Integrin-linked kinase (ILK) in dopaminergic cells in vitro and in the mouse ventral midbrain in vivo. Moreover, co-immunoprecipitation analysis revealed that LRRK2 binds to two core components of the WNT/PCP signaling pathway, PRICKLE1 and CELSR1, as well as to FLOTILLIN-2 and CULLIN-3, which regulate WNT secretion and inhibit WNT/β-catenin signaling, respectively. We also found that PRICKLE1 and LRRK2 localize in signalosomes and act as dual regulators of WNT/PCP and β-catenin signaling. Accordingly, analysis of the function of LRRK2 in vivo, in X. laevis revelaed that LRKK2 not only inhibits WNT/β-catenin pathway, but induces a classical WNT/PCP phenotype in vivo. Our study shows for the first time that LRRK2 activates the WNT/PCP signaling pathway through its interaction to multiple WNT/PCP components. We suggest that LRRK2 regulates the balance between WNT/β-catenin and WNT/PCP signaling, depending on the binding partners. Since this balance is crucial for homeostasis of midbrain dopaminergic neurons, we hypothesize that its alteration may contribute to the pathophysiology of Parkinson's disease.

Identification of senescence-associated genes in human bone marrow mesenchymal stem cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ryu, Eunsook; Hong, Su; Kang, Jaeku

2008-07-04

Human bone marrow mesenchymal stem cells (hBMMSCs) are multipotent stem cells that can differentiate into several specialized cell types, including bone, cartilage, and fat cells. The proliferative capacity of hBMMSCs paves the way for the development of regenerative medicine and tissue engineering. However, long-term in vitro culture of hBMMSCs leads to a reduced life span of the cells due to senescence, which leads eventually to growth arrest. To investigate the molecular mechanism behind the cellular senescence of hBMMSCs, microarray analysis was used to compare the expression profiles of early passage hBMMSCs, late passage hBMMSCs and hBMMSCs ectopically expressing human telomerasemore » reverse transcriptase (hTERT). Using an intersection analysis of 3892 differentially expressed genes (DEGs) out of 27,171 total genes analyzed, we identified 338 senescence-related DEGs. GO term categorization and pathway network analysis revealed that the identified genes are strongly related to known senescence pathways and mechanisms. The genes identified using this approach will facilitate future studies of the mechanisms underlying the cellular senescence of hBMMSCs.« less

Identification of core pathways based on attractor and crosstalk in ischemic stroke.

PubMed

Diao, Xiufang; Liu, Aijuan

2018-02-01

Ischemic stroke is a leading cause of mortality and disability around the world. It is an important task to identify dysregulated pathways which infer molecular and functional insights existing in high-throughput experimental data. Gene expression profile of E-GEOD-16561 was collected. Pathways were obtained from the database of Kyoto Encyclopedia of Genes and Genomes and Retrieval of Interacting Genes was used to download protein-protein interaction sets. Attractor and crosstalk approaches were applied to screen dysregulated pathways. A total of 20 differentially expressed genes were identified in ischemic stroke. Thirty-nine significant differential pathways were identified according to P<0.01 and 28 pathways were identified with RP<0.01 and 17 pathways were identified with impact factor >250. On the basis of the three criteria, 11 significant dysfunctional pathways were identified. Among them, Epstein-Barr virus infection was the most significant differential pathway. In conclusion, with the method based on attractor and crosstalk, significantly dysfunctional pathways were identified. These pathways are expected to provide molecular mechanism of ischemic stroke and represents a novel potential therapeutic target for ischemic stroke treatment.

Comprehensive detection of genes causing a phenotype using phenotype sequencing and pathway analysis.

PubMed

Harper, Marc; Gronenberg, Luisa; Liao, James; Lee, Christopher

2014-01-01

Discovering all the genetic causes of a phenotype is an important goal in functional genomics. We combine an experimental design for detecting independent genetic causes of a phenotype with a high-throughput sequencing analysis that maximizes sensitivity for comprehensively identifying them. Testing this approach on a set of 24 mutant strains generated for a metabolic phenotype with many known genetic causes, we show that this pathway-based phenotype sequencing analysis greatly improves sensitivity of detection compared with previous methods, and reveals a wide range of pathways that can cause this phenotype. We demonstrate our approach on a metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli, which is crucial to a substantial number of metabolic pathways and under renewed interest for biofuel research. Out of 2157 mutations in these strains, pathway-phenoseq discriminated just five gene groups (12 genes) as statistically significant causes of the phenotype. Experimentally, these five gene groups, and the next two high-scoring pathway-phenoseq groups, either have a clear connection to the PEP metabolite level or offer an alternative path of producing oxaloacetate (OAA), and thus clearly explain the phenotype. These high-scoring gene groups also show strong evidence of positive selection pressure, compared with strictly neutral selection in the rest of the genome.

Comparative Proteomics Analysis Reveals L-Arginine Activates Ethanol Degradation Pathways in HepG2 Cells.

PubMed

Yan, Guokai; Lestari, Retno; Long, Baisheng; Fan, Qiwen; Wang, Zhichang; Guo, Xiaozhen; Yu, Jie; Hu, Jun; Yang, Xingya; Chen, Changqing; Liu, Lu; Li, Xiuzhi; Purnomoadi, Agung; Achmadi, Joelal; Yan, Xianghua

2016-03-17

L-Arginine (Arg) is a versatile amino acid that plays crucial roles in a wide range of physiological and pathological processes. In this study, to investigate the alteration induced by Arg supplementation in proteome scale, isobaric tags for relative and absolute quantification (iTRAQ) based proteomic approach was employed to comparatively characterize the differentially expressed proteins between Arg deprivation (Ctrl) and Arg supplementation (+Arg) treated human liver hepatocellular carcinoma (HepG2) cells. A total of 21 proteins were identified as differentially expressed proteins and these 21 proteins were all up-regulated by Arg supplementation. Six amino acid metabolism-related proteins, mostly metabolic enzymes, showed differential expressions. Intriguingly, Ingenuity Pathway Analysis (IPA) based pathway analysis suggested that the three ethanol degradation pathways were significantly altered between Ctrl and +Arg. Western blotting and enzymatic activity assays validated that the key enzymes ADH1C, ALDH1A1, and ALDH2, which are mainly involved in ethanol degradation pathways, were highly differentially expressed, and activated between Ctrl and +Arg in HepG2 cells. Furthermore, 10 mM Arg significantly attenuated the cytotoxicity induced by 100 mM ethanol treatment (P < 0.0001). This study is the first time to reveal that Arg activates ethanol degradation pathways in HepG2 cells.

[Endoplasmic reticulum stress in INS-1-3 cell associated with the expression changes of MODY gene pathway].

PubMed

Liu, Y T; Li, S R; Wang, Z; Xiao, J Z

2016-09-13

Objective: To profile the gene expression changes associated with endoplasmic reticulum stress in INS-1-3 cells induced by thapsigargin (TG) and tunicamycin (TM). Methods: Normal cultured INS-1-3 cells were used as a control. TG and TM were used to induce endoplasmic reticulum stress in INS-1-3 cells. Digital gene expression profiling technique was used to detect differentially expressed gene. The changes of gene expression were detected by expression pattern clustering analysis, gene ontology (GO) function and pathway enrichment analysis. Real time polymerase chain reaction (RT-PCR) was used to verify the key changes of gene expression. Results: Compared with the control group, there were 57 (45 up-regulated, 12 down-regulated) and 135 (99 up-regulated, 36 down-regulated) differentially expressed genes in TG and TM group, respectively. GO function enrichment analyses indicated that the main enrichment was in the endoplasmic reticulum. In signaling pathway analysis, the identified pathways were related with endoplasmic reticulum stress, antigen processing and presentation, protein export, and most of all, the maturity onset diabetes of the young (MODY) pathway. Conclusion: Under the condition of endoplasmic reticulum stress, the related expression changes of transcriptional factors in MODY signaling pathway may be related with the impaired function in islet beta cells.

Computational analysis of microRNA function in heart development.

PubMed

Liu, Ganqiang; Ding, Min; Chen, Jiajia; Huang, Jinyan; Wang, Haiyun; Jing, Qing; Shen, Bairong

2010-09-01

Emerging evidence suggests that specific spatio-temporal microRNA (miRNA) expression is required for heart development. In recent years, hundreds of miRNAs have been discovered. In contrast, functional annotations are available only for a very small fraction of these regulatory molecules. In order to provide a global perspective for the biologists who study the relationship between differentially expressed miRNAs and heart development, we employed computational analysis to uncover the specific cellular processes and biological pathways targeted by miRNAs in mouse heart development. Here, we utilized Gene Ontology (GO) categories, KEGG Pathway, and GeneGo Pathway Maps as a gene functional annotation system for miRNA target enrichment analysis. The target genes of miRNAs were found to be enriched in functional categories and pathway maps in which miRNAs could play important roles during heart development. Meanwhile, we developed miRHrt (http://sysbio.suda.edu.cn/mirhrt/), a database aiming to provide a comprehensive resource of miRNA function in regulating heart development. These computational analysis results effectively illustrated the correlation of differentially expressed miRNAs with cellular functions and heart development. We hope that the identified novel heart development-associated pathways and the database presented here would facilitate further understanding of the roles and mechanisms of miRNAs in heart development.

Genome-wide analysis of long non-coding RNAs and their role in postnatal porcine testis development.

PubMed

Weng, Bo; Ran, Maoliang; Chen, Bin; He, Changqing; Dong, Lianhua; Peng, Fuzhi

2017-10-01

A comprehensive and systematic understanding of the roles of lncRNAs in the postnatal development of the pig testis has still not been achieved. In the present study, we obtained more than one billion clean reads and identified 15,528 lncRNA transcripts; these transcripts included 5032 known and 10,496 novel porcine lncRNA transcripts and corresponded to 10,041 lncRNA genes. Pairwise comparisons identified 449 known and 324 novel lncRNAs that showed differential expression patterns. GO and KEGG pathway enrichment analyses revealed that the targeted genes were involved in metabolic pathways regulating testis development and spermatogenesis, such as the TGF-beta pathway, the PI3K-Akt pathway, the Wnt/β-catenin pathway, and the AMPK pathway. Using this information, we predicted some lncRNAs and coding gene pairs were predicted that may function in testis development and spermatogenesis; these are listed in detail. This study has provided the most comprehensive catalog to date of lncRNAs in the postnatal pig testis and will aid our understanding of their functional roles in testis development and spermatogenesis. Copyright © 2017. Published by Elsevier Inc.

Intercellular signaling pathways active during intervertebral disc growth, differentiation, and aging.

PubMed

Dahia, Chitra Lekha; Mahoney, Eric J; Durrani, Atiq A; Wylie, Christopher

2009-03-01

Intervertebral discs at different postnatal ages were assessed for active intercellular signaling pathways. To generate a spatial and temporal map of the signaling pathways active in the postnatal intervertebral disc (IVD). The postnatal IVD is a complex structure, consisting of 3 histologically distinct components, the nucleus pulposus, fibrous anulus fibrosus, and endplate. These differentiate and grow during the first 9 weeks of age in the mouse. Identification of the major signaling pathways active during and after the growth and differentiation period will allow functional analysis using mouse genetics and identify targets for therapy for individual components of the disc. Antibodies specific for individual cell signaling pathways were used on cryostat sections of IVD at different postnatal ages to identify which components of the IVD were responding to major classes of intercellular signal, including sonic hedgehog, Wnt, TGFbeta, FGF, and BMPs. We present a spatial/temporal map of these signaling pathways during growth, differentiation, and aging of the disc. During growth and differentiation of the disc, its different components respond at different times to different intercellular signaling ligands. Most of these are dramatically downregulated at the end of disc growth.

Sho-saiko-to, a traditional herbal medicine, regulates gene expression and biological function by way of microRNAs in primary mouse hepatocytes

PubMed Central

2014-01-01

Background Sho-saiko-to (SST) (also known as so-shi-ho-tang or xiao-chai-hu-tang) has been widely prescribed for chronic liver diseases in traditional Oriental medicine. Despite the substantial amount of clinical evidence for SST, its molecular mechanism has not been clearly identified at a genome-wide level. Methods By using a microarray, we analyzed the temporal changes of messenger RNA (mRNA) and microRNA expression in primary mouse hepatocytes after SST treatment. The pattern of genes regulated by SST was identified by using time-series microarray analysis. The biological function of genes was measured by pathway analysis. For the identification of the exact targets of the microRNAs, a permutation-based correlation method was implemented in which the temporal expression of mRNAs and microRNAs were integrated. The similarity of the promoter structure between temporally regulated genes was measured by analyzing the transcription factor binding sites in the promoter region. Results The SST-regulated gene expression had two major patterns: (1) a temporally up-regulated pattern (463 genes) and (2) a temporally down-regulated pattern (177 genes). The integration of the genes and microRNA demonstrated that 155 genes could be the targets of microRNAs from the temporally up-regulated pattern and 19 genes could be the targets of microRNAs from the temporally down-regulated pattern. The temporally up-regulated pattern by SST was associated with signaling pathways such as the cell cycle pathway, whereas the temporally down-regulated pattern included drug metabolism-related pathways and immune-related pathways. All these pathways could be possibly associated with liver regenerative activity of SST. Genes targeted by microRNA were moreover associated with different biological pathways from the genes not targeted by microRNA. An analysis of promoter similarity indicated that co-expressed genes after SST treatment were clustered into subgroups, depending on the temporal expression patterns. Conclusions We are the first to identify that SST regulates temporal gene expression by way of microRNA. MicroRNA targets and non-microRNA targets moreover have different biological roles. This functional segregation by microRNA would be critical for the elucidation of the molecular activities of SST. PMID:24410935

Sho-saiko-to, a traditional herbal medicine, regulates gene expression and biological function by way of microRNAs in primary mouse hepatocytes.

PubMed

Song, Kwang Hoon; Kim, Yun Hee; Kim, Bu-Yeo

2014-01-11

Sho-saiko-to (SST) (also known as so-shi-ho-tang or xiao-chai-hu-tang) has been widely prescribed for chronic liver diseases in traditional Oriental medicine. Despite the substantial amount of clinical evidence for SST, its molecular mechanism has not been clearly identified at a genome-wide level. By using a microarray, we analyzed the temporal changes of messenger RNA (mRNA) and microRNA expression in primary mouse hepatocytes after SST treatment. The pattern of genes regulated by SST was identified by using time-series microarray analysis. The biological function of genes was measured by pathway analysis. For the identification of the exact targets of the microRNAs, a permutation-based correlation method was implemented in which the temporal expression of mRNAs and microRNAs were integrated. The similarity of the promoter structure between temporally regulated genes was measured by analyzing the transcription factor binding sites in the promoter region. The SST-regulated gene expression had two major patterns: (1) a temporally up-regulated pattern (463 genes) and (2) a temporally down-regulated pattern (177 genes). The integration of the genes and microRNA demonstrated that 155 genes could be the targets of microRNAs from the temporally up-regulated pattern and 19 genes could be the targets of microRNAs from the temporally down-regulated pattern. The temporally up-regulated pattern by SST was associated with signaling pathways such as the cell cycle pathway, whereas the temporally down-regulated pattern included drug metabolism-related pathways and immune-related pathways. All these pathways could be possibly associated with liver regenerative activity of SST. Genes targeted by microRNA were moreover associated with different biological pathways from the genes not targeted by microRNA. An analysis of promoter similarity indicated that co-expressed genes after SST treatment were clustered into subgroups, depending on the temporal expression patterns. We are the first to identify that SST regulates temporal gene expression by way of microRNA. MicroRNA targets and non-microRNA targets moreover have different biological roles. This functional segregation by microRNA would be critical for the elucidation of the molecular activities of SST.

A Network Pharmacology Approach to Determine the Active Components and Potential Targets of Curculigo Orchioides in the Treatment of Osteoporosis.

PubMed

Wang, Nani; Zhao, Guizhi; Zhang, Yang; Wang, Xuping; Zhao, Lisha; Xu, Pingcui; Shou, Dan

2017-10-27

BACKGROUND Osteoporosis is a complex bone disorder with a genetic predisposition, and is a cause of health problems worldwide. In China, Curculigo orchioides (CO) has been widely used as a herbal medicine in the prevention and treatment of osteoporosis. However, research on the mechanism of action of CO is still lacking. The aim of this study was to identify the absorbable components, potential targets, and associated treatment pathways of CO using a network pharmacology approach. MATERIAL AND METHODS We explored the chemical components of CO and used the five main principles of drug absorption to identify absorbable components. Targets for the therapeutic actions of CO were obtained from the PharmMapper server database. Pathway enrichment analysis was performed using the Comparative Toxicogenomics Database (CTD). Cytoscape was used to visualize the multiple components-multiple target-multiple pathways-multiple disease network for CO. RESULTS We identified 77 chemical components of CO, of which 32 components could be absorbed in the blood. These potential active components of CO regulated 83 targets and affected 58 pathways. Data analysis showed that the genes for estrogen receptor alpha (ESR1) and beta (ESR2), and the gene for 11 beta-hydroxysteroid dehydrogenase type 1, or cortisone reductase (HSD11B1) were the main targets of CO. Endocrine regulatory factors and factors regulating calcium reabsorption, steroid hormone biosynthesis, and metabolic pathways were related to these main targets and to ten corresponding compounds. CONCLUSIONS The network pharmacology approach used in our study has attempted to explain the mechanisms for the effects of CO in the prevention and treatment of osteoporosis, and provides an alternative approach to the investigation of the effects of this complex compound.

Transcriptomic profile of leg muscle during early growth in chicken

PubMed Central

Zhang, Genxi; Li, Tingting; Ling, Jiaojiao; Zhang, Xiangqian; Wang, Jinyu

2017-01-01

The early growth pattern, especially the age of peak growth, of broilers affects the time to market and slaughter weight, which in turn affect the profitability of the poultry industry. However, the underlying mechanisms regulating chicken growth and development have rarely been studied. This study aimed to identify candidate genes involved in chicken growth and investigated the potential regulatory mechanisms of early growth in chicken. RNA sequencing was applied to compare the transcriptomes of chicken muscle tissues at three developmental stages during early growth. In total, 978 differentially expressed genes (DEGs) (fold change ≥ 2; false discovery rate < 0.05) were detected by pairwise comparison. Functional analysis showed that the DEGs are mainly involved in the processes of cell growth, muscle development, and cellular activities (such as junction, migration, assembly, differentiation, and proliferation). Many of the DEGs are well known to be related to chicken growth, such as MYOD1, GH, IGF2BP2, IGFBP3, SMYD1, CEBPB, FGF2, and IGFBP5. KEGG pathway analysis identified that the DEGs were significantly enriched in five pathways (P < 0.1) related to growth and development: extracellular matrix–receptor interaction, focal adhesion, tight junction, insulin signaling pathway, and regulation of the actin cytoskeleton. A total of 42 DEGs assigned to these pathways are potential candidate genes inducing the difference in growth among the three developmental stages, such as MYH10, FGF2, FGF16, FN1, CFL2, MAPK9, IRS1, PHKA1, PHKB, and PHKG1. Thus, our study identified a series of genes and several pathways that may participate in the regulation of early growth in chicken. These results should serve as an important resource revealing the molecular basis of chicken growth and development. PMID:28291821

Transcriptome analysis of the tea oil camellia (Camellia oleifera) reveals candidate drought stress genes.

PubMed

Dong, Bin; Wu, Bin; Hong, Wenhong; Li, Xiuping; Li, Zhuo; Xue, Li; Huang, Yongfang

2017-01-01

The tea-oil camellia (Camellia oleifera) is the most important oil plant in southern China, and has a strong resistance to drought and barren soil. Understanding the molecular mechanisms of drought tolerance would greatly promote its cultivation and molecular breeding. In total, we obtained 76,585 unigenes with an average length of 810 bp and an N50 of 1,092 bp. We mapped all the unigenes to the NCBI 'nr' (non-redundant), SwissProt, KEGG, and clusters of orthologous groups (COG) databases, where 52,531 (68.6%) unigenes were functionally annotated. According to the annotation, 46,171 (60.8%) unigenes belong to 338 KEGG pathways. We identified a series of unigenes that are related to the synthesis and regulation of abscisic acid (ABA), the activity of protective enzymes, vitamin B6 metabolism, the metabolism of osmolytes, and pathways related to the biosynthesis of secondary metabolites. After exposed to drought for 12 hours, the number of differentially-expressed genes (DEGs) between treated plants and control plants increased in the G4 cultivar, while there was no significant increase in the drought-tolerant C3 cultivar. DEGs associated with drought stress responsive pathways were identified by KEGG pathway enrichment analysis. Moreover, we found 789 DEGs related to transcription factors. Finally, according to the results of qRT-PCR, the expression levels of the 20 unigenes tested were consistent with the results of next-generation sequencing. In the present study, we identified a large set of cDNA unigenes from C. oleifera annotated using public databases. Further studies of DEGs involved in metabolic pathways related to drought stress and transcription will facilitate the discovery of novel genes involved in resistance to drought stress in this commercially important plant.

Transcriptome analysis of the tea oil camellia (Camellia oleifera) reveals candidate drought stress genes

PubMed Central

Wu, Bin; Hong, Wenhong; Li, Xiuping; Li, Zhuo; Xue, Li; Huang, Yongfang

2017-01-01

Background The tea-oil camellia (Camellia oleifera) is the most important oil plant in southern China, and has a strong resistance to drought and barren soil. Understanding the molecular mechanisms of drought tolerance would greatly promote its cultivation and molecular breeding. Results In total, we obtained 76,585 unigenes with an average length of 810 bp and an N50 of 1,092 bp. We mapped all the unigenes to the NCBI ‘nr’ (non-redundant), SwissProt, KEGG, and clusters of orthologous groups (COG) databases, where 52,531 (68.6%) unigenes were functionally annotated. According to the annotation, 46,171 (60.8%) unigenes belong to 338 KEGG pathways. We identified a series of unigenes that are related to the synthesis and regulation of abscisic acid (ABA), the activity of protective enzymes, vitamin B6 metabolism, the metabolism of osmolytes, and pathways related to the biosynthesis of secondary metabolites. After exposed to drought for 12 hours, the number of differentially-expressed genes (DEGs) between treated plants and control plants increased in the G4 cultivar, while there was no significant increase in the drought-tolerant C3 cultivar. DEGs associated with drought stress responsive pathways were identified by KEGG pathway enrichment analysis. Moreover, we found 789 DEGs related to transcription factors. Finally, according to the results of qRT-PCR, the expression levels of the 20 unigenes tested were consistent with the results of next-generation sequencing. Conclusions In the present study, we identified a large set of cDNA unigenes from C. oleifera annotated using public databases. Further studies of DEGs involved in metabolic pathways related to drought stress and transcription will facilitate the discovery of novel genes involved in resistance to drought stress in this commercially important plant. PMID:28759610

Large-Scale Evolutionary Analysis of Genes and Supergene Clusters from Terpenoid Modular Pathways Provides Insights into Metabolic Diversification in Flowering Plants

PubMed Central

Hofberger, Johannes A.; Ramirez, Aldana M.; van den Bergh, Erik; Zhu, Xinguang; Bouwmeester, Harro J.; Schuurink, Robert C.; Schranz, M. Eric

2015-01-01

An important component of plant evolution is the plethora of pathways producing more than 200,000 biochemically diverse specialized metabolites with pharmacological, nutritional and ecological significance. To unravel dynamics underlying metabolic diversification, it is critical to determine lineage-specific gene family expansion in a phylogenomics framework. However, robust functional annotation is often only available for core enzymes catalyzing committed reaction steps within few model systems. In a genome informatics approach, we extracted information from early-draft gene-space assemblies and non-redundant transcriptomes to identify protein families involved in isoprenoid biosynthesis. Isoprenoids comprise terpenoids with various roles in plant-environment interaction, such as pollinator attraction or pathogen defense. Combining lines of evidence provided by synteny, sequence homology and Hidden-Markov-Modelling, we screened 17 genomes including 12 major crops and found evidence for 1,904 proteins associated with terpenoid biosynthesis. Our terpenoid genes set contains evidence for 840 core terpene-synthases and 338 triterpene-specific synthases. We further identified 190 prenyltransferases, 39 isopentenyl-diphosphate isomerases as well as 278 and 219 proteins involved in mevalonate and methylerithrol pathways, respectively. Assessing the impact of gene and genome duplication to lineage-specific terpenoid pathway expansion, we illustrated key events underlying terpenoid metabolic diversification within 250 million years of flowering plant radiation. By quantifying Angiosperm-wide versatility and phylogenetic relationships of pleiotropic gene families in terpenoid modular pathways, our analysis offers significant insight into evolutionary dynamics underlying diversification of plant secondary metabolism. Furthermore, our data provide a blueprint for future efforts to identify and more rapidly clone terpenoid biosynthetic genes from any plant species. PMID:26046541

Enhancement of anti-inflammatory activity of Aloe vera adventitious root extracts through the alteration of primary and secondary metabolites via salicylic acid elicitation.

PubMed

Lee, Yun Sun; Ju, Hyun Kyoung; Kim, Yeon Jeong; Lim, Tae-Gyu; Uddin, Md Romij; Kim, Yeon Bok; Baek, Jin Hong; Kwon, Sung Won; Lee, Ki Won; Seo, Hak Soo; Park, Sang Un; Yang, Tae-Jin

2013-01-01

Aloe vera (Asphodeloideae) is a medicinal plant in which useful secondary metabolites are plentiful. Among the representative secondary metabolites of Aloe vera are the anthraquinones including aloe emodin and chrysophanol, which are tricyclic aromatic quinones synthesized via a plant-specific type III polyketide biosynthesis pathway. However, it is not yet clear which cellular responses can induce the pathway, leading to production of tricyclic aromatic quinones. In this study, we examined the effect of endogenous elicitors on the type III polyketide biosynthesis pathway and identified the metabolic changes induced in elicitor-treated Aloe vera adventitious roots. Salicylic acid, methyl jasmonate, and ethephon were used to treat Aloe vera adventitious roots cultured on MS liquid media with 0.3 mg/L IBA for 35 days. Aloe emodin and chrysophanol were remarkably increased by the SA treatment, more than 10-11 and 5-13 fold as compared with untreated control, respectively. Ultra-performance liquid chromatography-electrospray ionization mass spectrometry analysis identified a total of 37 SA-induced compounds, including aloe emodin and chrysophanol, and 3 of the compounds were tentatively identified as tricyclic aromatic quinones. Transcript accumulation analysis of polyketide synthase genes and gas chromatography mass spectrometry showed that these secondary metabolic changes resulted from increased expression of octaketide synthase genes and decreases in malonyl-CoA, which is the precursor for the tricyclic aromatic quinone biosynthesis pathway. In addition, anti-inflammatory activity was enhanced in extracts of SA-treated adventitious roots. Our results suggest that SA has an important role in activation of the plant specific-type III polyketide biosynthetic pathway, and therefore that the efficacy of Aloe vera as medicinal agent can be improved through SA treatment.

Enhancement of Anti-Inflammatory Activity of Aloe vera Adventitious Root Extracts through the Alteration of Primary and Secondary Metabolites via Salicylic Acid Elicitation

PubMed Central

Lee, Yun Sun; Ju, Hyun Kyoung; Kim, Yeon Jeong; Lim, Tae-Gyu; Uddin, Md Romij; Kim, Yeon Bok; Baek, Jin Hong; Kwon, Sung Won; Lee, Ki Won; Seo, Hak Soo; Park, Sang Un; Yang, Tae-Jin

2013-01-01

Aloe vera (Asphodeloideae) is a medicinal plant in which useful secondary metabolites are plentiful. Among the representative secondary metabolites of Aloe vera are the anthraquinones including aloe emodin and chrysophanol, which are tricyclic aromatic quinones synthesized via a plant-specific type III polyketide biosynthesis pathway. However, it is not yet clear which cellular responses can induce the pathway, leading to production of tricyclic aromatic quinones. In this study, we examined the effect of endogenous elicitors on the type III polyketide biosynthesis pathway and identified the metabolic changes induced in elicitor-treated Aloe vera adventitious roots. Salicylic acid, methyl jasmonate, and ethephon were used to treat Aloe vera adventitious roots cultured on MS liquid media with 0.3 mg/L IBA for 35 days. Aloe emodin and chrysophanol were remarkably increased by the SA treatment, more than 10–11 and 5–13 fold as compared with untreated control, respectively. Ultra-performance liquid chromatography-electrospray ionization mass spectrometry analysis identified a total of 37 SA-induced compounds, including aloe emodin and chrysophanol, and 3 of the compounds were tentatively identified as tricyclic aromatic quinones. Transcript accumulation analysis of polyketide synthase genes and gas chromatography mass spectrometry showed that these secondary metabolic changes resulted from increased expression of octaketide synthase genes and decreases in malonyl-CoA, which is the precursor for the tricyclic aromatic quinone biosynthesis pathway. In addition, anti-inflammatory activity was enhanced in extracts of SA-treated adventitious roots. Our results suggest that SA has an important role in activation of the plant specific-type III polyketide biosynthetic pathway, and therefore that the efficacy of Aloe vera as medicinal agent can be improved through SA treatment. PMID:24358188

Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake

PubMed Central

Do, Duy N.; Strathe, Anders B.; Ostersen, Tage; Pant, Sameer D.; Kadarmideen, Haja N.

2014-01-01

Residual feed intake (RFI) is a complex trait that is economically important for livestock production; however, the genetic and biological mechanisms regulating RFI are largely unknown in pigs. Therefore, the study aimed to identify single nucleotide polymorphisms (SNPs), candidate genes and biological pathways involved in regulating RFI using Genome-wide association (GWA) and pathway analyses. A total of 596 Yorkshire boars with phenotypes for two different measures of RFI (RFI1 and 2) and 60k genotypic data was used. GWA analysis was performed using a univariate mixed model and 12 and 7 SNPs were found to be significantly associated with RFI1 and RFI2, respectively. Several genes such as xin actin-binding repeat-containing protein 2 (XIRP2),tetratricopeptide repeat domain 29 (TTC29),suppressor of glucose, autophagy associated 1 (SOGA1),MAS1,G-protein-coupled receptor (GPCR) kinase 5 (GRK5),prospero-homeobox protein 1 (PROX1),GPCR 155 (GPR155), and FYVE domain containing the 26 (ZFYVE26) were identified as putative candidates for RFI based on their genomic location in the vicinity of these SNPs. Genes located within 50 kbp of SNPs significantly associated with RFI and RFI2 (q-value ≤ 0.2) were subsequently used for pathway analyses. These analyses were performed by assigning genes to biological pathways and then testing the association of individual pathways with RFI using a Fisher’s exact test. Metabolic pathway was significantly associated with both RFIs. Other biological pathways regulating phagosome, tight junctions, olfactory transduction, and insulin secretion were significantly associated with both RFI traits when relaxed threshold for cut-off p-value was used (p ≤ 0.05). These results implied porcine RFI is regulated by multiple biological mechanisms, although the metabolic processes might be the most important. Olfactory transduction pathway controlling the perception of feed via smell, insulin pathway controlling food intake might be important pathways for RFI. Furthermore, our study revealed key genes and genetic variants that control feed efficiency that could potentially be useful for genetic selection of more feed efficient pigs. PMID:25250046

Qualitative evaluation of a local coronary heart disease treatment pathway: practical implications and theoretical framework

PubMed Central

2012-01-01

Background Coronary heart disease (CHD) is a common medical problem in general practice. Due to its chronic character, shared care of the patient between general practitioner (GP) and cardiologist (C) is required. In order to improve the cooperation between both medical specialists for patients with CHD, a local treatment pathway was developed. The objective of this study was first to evaluate GPs’ opinions regarding the pathway and its practical implications, and secondly to suggest a theoretical framework of the findings by feeding the identified key factors influencing the pathway implementation into a multi-dimensional model. Methods The evaluation of the pathway was conducted in a qualitative design on a sample of 12 pathway developers (8 GPs and 4 cardiologists) and 4 pathway users (GPs). Face-to face interviews, which were aligned with previously conducted studies of the department and assumptions of the theory of planned behaviour (TPB), were performed following a semi-structured interview guideline. These were audio-taped, transcribed verbatim, coded, and analyzed according to the standards of qualitative content analysis. Results We identified 10 frequently mentioned key factors having an impact on the implementation success of the CHD treatment pathway. We thereby differentiated between pathway related (pathway content, effort, individual flexibility, ownership), behaviour related (previous behaviour, support), interaction related (patient, shared care/colleagues), and system related factors (context, health care system). The overall evaluation of the CHD pathway was positive, but did not automatically lead to a change of clinical behaviour as some GPs felt to have already acted as the pathway recommends. Conclusions By providing an account of our experience creating and implementing an intersectoral care pathway for CHD, this study contributes to our knowledge of factors that may influence physicians’ decisions regarding the use of a local treatment pathway. An improved adaptation of the pathway in daily practice might be best achieved by a combined implementation strategy addressing internal and external factors. A simple, direct adaptation regards the design of the pathway material (e.g. layout, PC version), or the embedding of the pathway in another programme, like a Disease Management Programme (DMP). In addition to these practical implications, we propose a theoretical framework to understand the key factors’ influence on the pathway implementation, with the identified factors along the microlevel (pathway related factors), the mesolevel (interaction related factors), and system- related factors along the macrolevel. PMID:22584032

Qualitative evaluation of a local coronary heart disease treatment pathway: practical implications and theoretical framework.

PubMed

Kramer, Lena; Schlößler, Kathrin; Träger, Susanne; Donner-Banzhoff, Norbert

2012-05-14

Coronary heart disease (CHD) is a common medical problem in general practice. Due to its chronic character, shared care of the patient between general practitioner (GP) and cardiologist (C) is required. In order to improve the cooperation between both medical specialists for patients with CHD, a local treatment pathway was developed. The objective of this study was first to evaluate GPs' opinions regarding the pathway and its practical implications, and secondly to suggest a theoretical framework of the findings by feeding the identified key factors influencing the pathway implementation into a multi-dimensional model. The evaluation of the pathway was conducted in a qualitative design on a sample of 12 pathway developers (8 GPs and 4 cardiologists) and 4 pathway users (GPs). Face-to face interviews, which were aligned with previously conducted studies of the department and assumptions of the theory of planned behaviour (TPB), were performed following a semi-structured interview guideline. These were audio-taped, transcribed verbatim, coded, and analyzed according to the standards of qualitative content analysis. We identified 10 frequently mentioned key factors having an impact on the implementation success of the CHD treatment pathway. We thereby differentiated between pathway related (pathway content, effort, individual flexibility, ownership), behaviour related (previous behaviour, support), interaction related (patient, shared care/colleagues), and system related factors (context, health care system). The overall evaluation of the CHD pathway was positive, but did not automatically lead to a change of clinical behaviour as some GPs felt to have already acted as the pathway recommends. By providing an account of our experience creating and implementing an intersectoral care pathway for CHD, this study contributes to our knowledge of factors that may influence physicians' decisions regarding the use of a local treatment pathway. An improved adaptation of the pathway in daily practice might be best achieved by a combined implementation strategy addressing internal and external factors. A simple, direct adaptation regards the design of the pathway material (e.g. layout, PC version), or the embedding of the pathway in another programme, like a Disease Management Programme (DMP). In addition to these practical implications, we propose a theoretical framework to understand the key factors' influence on the pathway implementation, with the identified factors along the microlevel (pathway related factors), the mesolevel (interaction related factors), and system- related factors along the macrolevel.

Differential metabolome analysis of field-grown maize kernels in response to drought stress

USDA-ARS?s Scientific Manuscript database

Drought stress constrains maize kernel development and can exacerbate aflatoxin contamination. In order to identify drought responsive metabolites and explore pathways involved in kernel responses, a metabolomics analysis was conducted on kernels from a drought tolerant line, Lo964, and a sensitive ...

De Novo Transcriptome Assembly and Characterization of Lithospermum officinale to Discover Putative Genes Involved in Specialized Metabolites Biosynthesis.

PubMed

Rai, Amit; Nakaya, Taiki; Shimizu, Yohei; Rai, Megha; Nakamura, Michimi; Suzuki, Hideyuki; Saito, Kazuki; Yamazaki, Mami

2018-05-29

Lithospermum officinale is a valuable source of bioactive metabolites with medicinal and industrial values. However, little is known about genes involved in the biosynthesis of these metabolites, primarily due to the lack of genome or transcriptome resources. This study presents the first effort to establish and characterize de novo transcriptome assembly resource for L. officinale and expression analysis for three of its tissues, namely leaf, stem, and root. Using over 4Gbps of RNA-sequencing datasets, we obtained de novo transcriptome assembly of L. officinale , consisting of 77,047 unigenes with assembly N50 value as 1524 bps. Based on transcriptome annotation and functional classification, 52,766 unigenes were assigned with putative genes functions, gene ontology terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. KEGG pathway and gene ontology enrichment analysis using highly expressed unigenes across three tissues and targeted metabolome analysis showed active secondary metabolic processes enriched specifically in the root of L. officinale . Using co-expression analysis, we also identified 20 and 48 unigenes representing different enzymes of lithospermic/chlorogenic acid and shikonin biosynthesis pathways, respectively. We further identified 15 candidate unigenes annotated as cytochrome P450 with the highest expression in the root of L. officinale as novel genes with a role in key biochemical reactions toward shikonin biosynthesis. Thus, through this study, we not only generated a high-quality genomic resource for L. officinale but also propose candidate genes to be involved in shikonin biosynthesis pathways for further functional characterization. Georg Thieme Verlag KG Stuttgart · New York.

Distinct herpesvirus resistances and immune responses of three gynogenetic clones of gibel carp revealed by comprehensive transcriptomes.

PubMed

Gao, Fan-Xiang; Wang, Yang; Zhang, Qi-Ya; Mou, Cheng-Yan; Li, Zhi; Deng, Yuan-Sheng; Zhou, Li; Gui, Jian-Fang

2017-07-24

Gibel carp is an important aquaculture species in China, and a herpesvirus, called as Carassius auratus herpesvirus (CaHV), has hampered the aquaculture development. Diverse gynogenetic clones of gibel carp have been identified or created, and some of them have been used as aquaculture varieties, but their resistances to herpesvirus and the underlying mechanism remain unknown. To reveal their susceptibility differences, we firstly performed herpesvirus challenge experiments in three gynogenetic clones of gibel carp, including the leading variety clone A + , candidate variety clone F and wild clone H. Three clones showed distinct resistances to CaHV. Moreover, 8772, 8679 and 10,982 differentially expressed unigenes (DEUs) were identified from comparative transcriptomes between diseased individuals and control individuals of clone A + , F and H, respectively. Comprehensive analysis of the shared DEUs in all three clones displayed common defense pathways to the herpesvirus infection, activating IFN system and suppressing complements. KEGG pathway analysis of specifically changed DEUs in respective clones revealed distinct immune responses to the herpesvirus infection. The DEU numbers identified from clone H in KEGG immune-related pathways, such as "chemokine signaling pathway", "Toll-like receptor signaling pathway" and others, were remarkably much more than those from clone A + and F. Several IFN-related genes, including Mx1, viperin, PKR and others, showed higher increases in the resistant clone H than that in the others. IFNphi3, IFI44-like and Gig2 displayed the highest expression in clone F and IRF1 uniquely increased in susceptible clone A + . In contrast to strong immune defense in resistant clone H, susceptible clone A + showed remarkable up-regulation of genes related to apoptosis or death, indicating that clone A + failed to resist virus offensive and evidently induced apoptosis or death. Our study is the first attempt to screen distinct resistances and immune responses of three gynogenetic gibel carp clones to herpesvirus infection by comprehensive transcriptomes. These differential DEUs, immune-related pathways and IFN system genes identified from susceptible and resistant clones will be beneficial to marker-assisted selection (MAS) breeding or molecular module-based resistance breeding in gibel carp.

Expression Profile of Long Noncoding RNAs in Human Earlobe Keloids: A Microarray Analysis

PubMed Central

Guo, Liang; Xu, Kai; Yan, Hongbo; Feng, Haifeng

2016-01-01

Background. Long noncoding RNAs (lncRNAs) play key roles in a wide range of biological processes and their deregulation results in human disease, including keloids. Earlobe keloid is a type of pathological skin scar, and the molecular pathogenesis of this disease remains largely unknown. Methods. In this study, microarray analysis was used to determine the expression profiles of lncRNAs and mRNAs between 3 pairs of earlobe keloid and normal specimens. Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to identify the main functions of the differentially expressed genes and earlobe keloid-related pathways. Results. A total of 2068 lncRNAs and 1511 mRNAs were differentially expressed between earlobe keloid and normal tissues. Among them, 1290 lncRNAs and 1092 mRNAs were upregulated, and 778 lncRNAs and 419 mRNAs were downregulated. Pathway analysis revealed that 24 pathways were correlated to the upregulated transcripts, while 11 pathways were associated with the downregulated transcripts. Conclusion. We characterized the expression profiles of lncRNA and mRNA in earlobe keloids and suggest that lncRNAs may serve as diagnostic biomarkers for the therapy of earlobe keloid. PMID:28101509

Quantitative proteomic analysis of milk fat globule membrane (MFGM) proteins in human and bovine colostrum and mature milk samples through iTRAQ labeling.

PubMed

Yang, Mei; Cong, Min; Peng, Xiuming; Wu, Junrui; Wu, Rina; Liu, Biao; Ye, Wenhui; Yue, Xiqing

2016-05-18

Milk fat globule membrane (MFGM) proteins have many functions. To explore the different proteomics of human and bovine MFGM, MFGM proteins were separated from human and bovine colostrum and mature milk, and analyzed by the iTRAQ proteomic approach. A total of 411 proteins were recognized and quantified. Among these, 232 kinds of differentially expressed proteins were identified. These differentially expressed proteins were analyzed based on multivariate analysis, gene ontology (GO) annotation and KEGG pathway. Biological processes involved were response to stimulus, localization, establishment of localization, and the immune system process. Cellular components engaged were the extracellular space, extracellular region parts, cell fractions, and vesicles. Molecular functions touched upon were protein binding, nucleotide binding, and enzyme inhibitor activity. The KEGG pathway analysis showed several pathways, including regulation of the actin cytoskeleton, focal adhesion, neurotrophin signaling pathway, leukocyte transendothelial migration, tight junction, complement and coagulation cascades, vascular endothelial growth factor signaling pathway, and adherens junction. These results enhance our understanding of different proteomes of human and bovine MFGM across different lactation phases, which could provide important information and potential directions for the infant milk powder and functional food industries.

Heading in the right direction: thermodynamics-based network analysis and pathway engineering.

PubMed

Ataman, Meric; Hatzimanikatis, Vassily

2015-12-01

Thermodynamics-based network analysis through the introduction of thermodynamic constraints in metabolic models allows a deeper analysis of metabolism and guides pathway engineering. The number and the areas of applications of thermodynamics-based network analysis methods have been increasing in the last ten years. We review recent applications of these methods and we identify the areas that such analysis can contribute significantly, and the needs for future developments. We find that organisms with multiple compartments and extremophiles present challenges for modeling and thermodynamics-based flux analysis. The evolution of current and new methods must also address the issues of the multiple alternatives in flux directionalities and the uncertainties and partial information from analytical methods. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A novel analysis strategy for integrating methylation and expression data reveals core pathways for thyroid cancer aetiology

PubMed Central

2015-01-01

Background Recently, a wide range of diseases have been associated with changes in DNA methylation levels, which play a vital role in gene expression regulation. With ongoing developments in technology, attempts to understand disease mechanism have benefited greatly from epigenetics and transcriptomics studies. In this work, we have used expression and methylation data of thyroid carcinoma as a case study and explored how to optimally incorporate expression and methylation information into the disease study when both data are available. Moreover, we have also investigated whether there are important post-translational modifiers which could drive critical insights on thyroid cancer genetics. Results In this study, we have conducted a threshold analysis for varying methylation levels to identify whether setting a methylation level threshold increases the performance of functional enrichment. Moreover, in order to decide on best-performing analysis strategy, we have performed data integration analysis including comparison of 10 different analysis strategies. As a result, combining methylation with expression and using genes with more than 15% methylation change led to optimal detection rate of thyroid-cancer associated pathways in top 20 functional enrichment results. Furthermore, pooling the data from different experiments increased analysis confidence by improving the data range. Consequently, we have identified 207 transcription factors and 245 post-translational modifiers with more than 15% methylation change which may be important in understanding underlying mechanisms of thyroid cancer. Conclusion While only expression or only methylation information would not reveal both primary and secondary mechanisms involved in disease state, combining expression and methylation led to a better detection of thyroid cancer-related genes and pathways that are found in the recent literature. Moreover, focusing on genes that have certain level of methylation change improved the functional enrichment results, revealing the core pathways involved in disease development such as; endocytosis, apoptosis, glutamatergic synapse, MAPK, ErbB, TGF-beta and Toll-like receptor pathways. Overall, in addition to novel analysis framework, our study reveals important thyroid-cancer related mechanisms, secondary molecular alterations and contributes to better knowledge of thyroid cancer aetiology. PMID:26678064

A Systematic Genetic Screen to Dissect the MicroRNA Pathway in Drosophila.

PubMed

Pressman, Sigal; Reinke, Catherine A; Wang, Xiaohong; Carthew, Richard W

2012-04-01

A central goal of microRNA biology is to elucidate the genetic program of miRNA function and regulation. However, relatively few of the effectors that execute miRNA repression have been identified. Because such genes may function in many developmental processes, mutations in them are expected to be pleiotropic and thus are discarded in most standard genetic screens. Here, we describe a systematic screen designed to identify all Drosophila genes in ∼40% of the genome that function in the miRNA pathway. To identify potentially pleiotropic genes, the screen analyzed clones of homozygous mutant cells in heterozygous animals. We identified 45 mutations representing 24 genes, and we molecularly characterized 9 genes. These include 4 previously known genes that encode core components of the miRNA pathway, including Drosha, Pasha, Dicer-1, and Ago1. The rest are new genes that function through chromatin remodeling, signaling, and mRNA decapping. The results suggest genetic screens that use clonal analysis can elucidate the miRNA program and that ∼100 genes are required to execute the miRNA program.

Microarray analysis of peripheral blood lymphocytes from ALS patients and the SAFE detection of the KEGG ALS pathway

PubMed Central

2011-01-01

Background Sporadic amyotrophic lateral sclerosis (sALS) is a motor neuron disease with poorly understood etiology. Results of gene expression profiling studies of whole blood from ALS patients have not been validated and are difficult to relate to ALS pathogenesis because gene expression profiles depend on the relative abundance of the different cell types present in whole blood. We conducted microarray analyses using Agilent Human Whole Genome 4 × 44k Arrays on a more homogeneous cell population, namely purified peripheral blood lymphocytes (PBLs), from ALS patients and healthy controls to identify molecular signatures possibly relevant to ALS pathogenesis. Methods Differentially expressed genes were determined by LIMMA (Linear Models for MicroArray) and SAM (Significance Analysis of Microarrays) analyses. The SAFE (Significance Analysis of Function and Expression) procedure was used to identify molecular pathway perturbations. Proteasome inhibition assays were conducted on cultured peripheral blood mononuclear cells (PBMCs) from ALS patients to confirm alteration of the Ubiquitin/Proteasome System (UPS). Results For the first time, using SAFE in a global gene ontology analysis (gene set size 5-100), we show significant perturbation of the KEGG (Kyoto Encyclopedia of Genes and Genomes) ALS pathway of motor neuron degeneration in PBLs from ALS patients. This was the only KEGG disease pathway significantly upregulated among 25, and contributing genes, including SOD1, represented 54% of the encoded proteins or protein complexes of the KEGG ALS pathway. Further SAFE analysis, including gene set sizes >100, showed that only neurodegenerative diseases (4 out of 34 disease pathways) including ALS were significantly upregulated. Changes in UBR2 expression correlated inversely with time since onset of disease and directly with ALSFRS-R, implying that UBR2 was increased early in the course of ALS. Cultured PBMCs from ALS patients accumulated more ubiquitinated proteins than PBMCs from healthy controls in a serum-dependent manner confirming changes in this pathway. Conclusions Our study indicates that PBLs from sALS patients are strong responders to systemic signals or local signals acquired by cell trafficking, representing changes in gene expression similar to those present in brain and spinal cord of sALS patients. PBLs may provide a useful means to study ALS pathogenesis. PMID:22027401

Morphological covariance in anatomical MRI scans can identify discrete neural pathways in the brain and their disturbances in persons with neuropsychiatric disorders.

PubMed

Bansal, Ravi; Hao, Xuejun; Peterson, Bradley S

2015-05-01

We hypothesize that coordinated functional activity within discrete neural circuits induces morphological organization and plasticity within those circuits. Identifying regions of morphological covariation that are independent of morphological covariation in other regions therefore may therefore allow us to identify discrete neural systems within the brain. Comparing the magnitude of these variations in individuals who have psychiatric disorders with the magnitude of variations in healthy controls may allow us to identify aberrant neural pathways in psychiatric illnesses. We measured surface morphological features by applying nonlinear, high-dimensional warping algorithms to manually defined brain regions. We transferred those measures onto the surface of a unit sphere via conformal mapping and then used spherical wavelets and their scaling coefficients to simplify the data structure representing these surface morphological features of each brain region. We used principal component analysis (PCA) to calculate covariation in these morphological measures, as represented by their scaling coefficients, across several brain regions. We then assessed whether brain subregions that covaried in morphology, as identified by large eigenvalues in the PCA, identified specific neural pathways of the brain. To do so, we spatially registered the subnuclei for each eigenvector into the coordinate space of a Diffusion Tensor Imaging dataset; we used these subnuclei as seed regions to track and compare fiber pathways with known fiber pathways identified in neuroanatomical atlases. We applied these procedures to anatomical MRI data in a cohort of 82 healthy participants (42 children, 18 males, age 10.5 ± 2.43 years; 40 adults, 22 males, age 32.42 ± 10.7 years) and 107 participants with Tourette's Syndrome (TS) (71 children, 59 males, age 11.19 ± 2.2 years; 36 adults, 21 males, age 37.34 ± 10.9 years). We evaluated the construct validity of the identified covariation in morphology using DTI data from a different set of 20 healthy adults (10 males, mean age 29.7 ± 7.7 years). The PCA identified portions of structures that covaried across the brain, the eigenvalues measuring the magnitude of the covariation in morphology along the respective eigenvectors. Our results showed that the eigenvectors, and the DTI fibers tracked from their associated brain regions, corresponded with known neural pathways in the brain. In addition, the eigenvectors that captured morphological covariation across regions, and the principal components along those eigenvectors, identified neural pathways with aberrant morphological features associated with TS. These findings suggest that covariations in brain morphology can identify aberrant neural pathways in specific neuropsychiatric disorders. Copyright © 2015. Published by Elsevier Inc.

Premetazoan origin of the Hippo signaling pathway

PubMed Central

Sebé-Pedrós, Arnau; Zheng, Yonggang; Ruiz-Trillo, Iñaki; Pan, Duojia

2012-01-01

Summary Non-aggregative multicellularity requires strict control of cell number. The Hippo signaling pathway coordinates cell proliferation and apoptosis and is a central regulator of organ size in animals. Recent studies have shown the presence of key members of the Hippo pathway in non-bilaterian animals, but failed to identify this pathway outside Metazoa. Through comparative analyses of recently sequenced holozoan genomes, we show that Hippo pathway components, such as the kinases Hippo and Warts, the co-activator Yorkie and the transcription factor Scalloped, were already present in the unicellular ancestors of animals. Remarkably, functional analysis of Hippo components of the amoeboid holozoan Capsaspora owczarzaki, performed in Drosophila, demonstrate that the growth-regulatory activity of the Hippo pathway is conserved in this unicellular lineage. Our findings show that the Hippo pathway evolved well before the origin of Metazoa and highlight the importance of Hippo signaling as a key developmental mechanism pre-dating the origin of Metazoa. PMID:22832104

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata.

PubMed

Escandón, Mónica; Meijón, Mónica; Valledor, Luis; Pascual, Jesús; Pinto, Gloria; Cañal, María Jesús

2018-01-01

The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata , identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata , with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata , as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature.

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata

PubMed Central

Escandón, Mónica; Meijón, Mónica; Valledor, Luis; Pascual, Jesús; Pinto, Gloria; Cañal, María Jesús

2018-01-01

The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata, identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata, with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata, as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature. PMID:29719546

Identification of miR-194-5p as a potential biomarker for postmenopausal osteoporosis

PubMed Central

Pan, Nanan; Sun, Ning; Wang, Qiujun; Fan, Jingxue; Zhou, Ping

2015-01-01

The incidence of osteoporosis is high in postmenopausal women due to altered estrogen levels and continuous calcium loss that occurs with aging. Recent studies have shown that microRNAs (miRNAs) are involved in the development of osteoporosis. These miRNAs may be used as potential biomarkers to identify women at a high risk for developing the disease. In this study, whole blood samples were collected from 48 postmenopausal Chinese women with osteopenia or osteoporosis and pooled into six groups according to individual T-scores. A miRNA microarray analysis was performed on pooled blood samples to identify potential miRNA biomarkers for postmenopausal osteoporosis. Five miRNAs (miR-130b-3p, -151a-3p, -151b, -194-5p, and -590-5p) were identified in the microarray analysis. These dysregulated miRNAs were subjected to a pathway analysis investigating whether they were involved in regulating osteoporosis-related pathways. Among them, only miR-194-5p was enriched in multiple osteoporosis-related pathways. Enhanced miR-194-5p expression in women with osteoporosis was confirmed by quantitative reverse transcription–polymerase chain reaction analysis. For external validation, a significant correlation between the expression of miR-194-5p and T-scores was found in an independent patient collection comprised of 24 postmenopausal women with normal bone mineral density, 30 postmenopausal women with osteopenia, and 32 postmenopausal women with osteoporosis (p < 0.05). Taken together, the present findings suggest that miR-194-5p may be a viable miRNA biomarker for postmenopausal osteoporosis. PMID:26038726

Identification of miR-194-5p as a potential biomarker for postmenopausal osteoporosis.

PubMed

Meng, Jia; Zhang, Dapeng; Pan, Nanan; Sun, Ning; Wang, Qiujun; Fan, Jingxue; Zhou, Ping; Zhu, Wenliang; Jiang, Lihong

2015-01-01

The incidence of osteoporosis is high in postmenopausal women due to altered estrogen levels and continuous calcium loss that occurs with aging. Recent studies have shown that microRNAs (miRNAs) are involved in the development of osteoporosis. These miRNAs may be used as potential biomarkers to identify women at a high risk for developing the disease. In this study, whole blood samples were collected from 48 postmenopausal Chinese women with osteopenia or osteoporosis and pooled into six groups according to individual T-scores. A miRNA microarray analysis was performed on pooled blood samples to identify potential miRNA biomarkers for postmenopausal osteoporosis. Five miRNAs (miR-130b-3p, -151a-3p, -151b, -194-5p, and -590-5p) were identified in the microarray analysis. These dysregulated miRNAs were subjected to a pathway analysis investigating whether they were involved in regulating osteoporosis-related pathways. Among them, only miR-194-5p was enriched in multiple osteoporosis-related pathways. Enhanced miR-194-5p expression in women with osteoporosis was confirmed by quantitative reverse transcription-polymerase chain reaction analysis. For external validation, a significant correlation between the expression of miR-194-5p and T-scores was found in an independent patient collection comprised of 24 postmenopausal women with normal bone mineral density, 30 postmenopausal women with osteopenia, and 32 postmenopausal women with osteoporosis (p < 0.05). Taken together, the present findings suggest that miR-194-5p may be a viable miRNA biomarker for postmenopausal osteoporosis.

Gene expression profile analysis of Ligon lintless-1 (Li1) mutant reveals important genes and pathways in cotton leaf and fiber development.

PubMed

Ding, Mingquan; Jiang, Yurong; Cao, Yuefen; Lin, Lifeng; He, Shae; Zhou, Wei; Rong, Junkang

2014-02-10

Ligon lintless-1 (Li1) is a monogenic dominant mutant of Gossypium hirsutum (upland cotton) with a phenotype of impaired vegetative growth and short lint fibers. Despite years of research involving genetic mapping and gene expression profile analysis of Li1 mutant ovule tissues, the gene remains uncloned and the underlying pathway of cotton fiber elongation is still unclear. In this study, we report the whole genome-level deep-sequencing analysis of leaf tissues of the Li1 mutant. Differentially expressed genes in leaf tissues of mutant versus wild-type (WT) plants are identified, and the underlying pathways and potential genes that control leaf and fiber development are inferred. The results show that transcription factors AS2, YABBY5, and KANDI-like are significantly differentially expressed in mutant tissues compared with WT ones. Interestingly, several fiber development-related genes are found in the downregulated gene list of the mutant leaf transcriptome. These genes include heat shock protein family, cytoskeleton arrangement, cell wall synthesis, energy, H2O2 metabolism-related genes, and WRKY transcription factors. This finding suggests that the genes are involved in leaf morphology determination and fiber elongation. The expression data are also compared with the previously published microarray data of Li1 ovule tissues. Comparative analysis of the ovule transcriptomes of Li1 and WT reveals that a number of pathways important for fiber elongation are enriched in the downregulated gene list at different fiber development stages (0, 6, 9, 12, 15, 18dpa). Differentially expressed genes identified in both leaf and fiber samples are aligned with cotton whole genome sequences and combined with the genetic fine mapping results to identify a list of candidate genes for Li1. Copyright © 2013 Elsevier B.V. All rights reserved.

Candidate genetic pathways for attention-deficit/hyperactivity disorder (ADHD) show association to hyperactive/impulsive symptoms in children with ADHD.

PubMed

Bralten, Janita; Franke, Barbara; Waldman, Irwin; Rommelse, Nanda; Hartman, Catharina; Asherson, Philip; Banaschewski, Tobias; Ebstein, Richard P; Gill, Michael; Miranda, Ana; Oades, Robert D; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph A; Oosterlaan, Jaap; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Faraone, Stephen V; Buitelaar, Jan K; Arias-Vásquez, Alejandro

2013-11-01

Because multiple genes with small effect sizes are assumed to play a role in attention-deficit/hyperactivity disorder (ADHD) etiology, considering multiple variants within the same analysis likely increases the total explained phenotypic variance, thereby boosting the power of genetic studies. This study investigated whether pathway-based analysis could bring scientists closer to unraveling the biology of ADHD. The pathway was described as a predefined gene selection based on a well-established database or literature data. Common genetic variants in pathways involved in dopamine/norepinephrine and serotonin neurotransmission and genes involved in neuritic outgrowth were investigated in cases from the International Multicentre ADHD Genetics (IMAGE) study. Multivariable analysis was performed to combine the effects of single genetic variants within the pathway genes. Phenotypes were DSM-IV symptom counts for inattention and hyperactivity/impulsivity (n = 871) and symptom severity measured with the Conners Parent (n = 930) and Teacher (n = 916) Rating Scales. Summing genetic effects of common genetic variants within the pathways showed a significant association with hyperactive/impulsive symptoms ((p)empirical = .007) but not with inattentive symptoms ((p)empirical = .73). Analysis of parent-rated Conners hyperactive/impulsive symptom scores validated this result ((p)empirical = .0018). Teacher-rated Conners scores were not associated. Post hoc analyses showed a significant contribution of all pathways to the hyperactive/impulsive symptom domain (dopamine/norepinephrine, (p)empirical = .0004; serotonin, (p)empirical = .0149; neuritic outgrowth, (p)empirical = .0452). The present analysis shows an association between common variants in 3 genetic pathways and the hyperactive/impulsive component of ADHD. This study demonstrates that pathway-based association analyses, using quantitative measurements of ADHD symptom domains, can increase the power of genetic analyses to identify biological risk factors involved in this disorder. Copyright © 2013 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

The genes and enzymes of the carotenoid metabolic pathway in Vitis vinifera L.

PubMed Central

2012-01-01

Background Carotenoids are a heterogeneous group of plant isoprenoids primarily involved in photosynthesis. In plants the cleavage of carotenoids leads to the formation of the phytohormones abscisic acid and strigolactone, and C13-norisoprenoids involved in the characteristic flavour and aroma compounds in flowers and fruits and are of specific importance in the varietal character of grapes and wine. This work extends the previous reports of carotenoid gene expression and photosynthetic pigment analysis by providing an up-to-date pathway analysis and an important framework for the analysis of carotenoid metabolic pathways in grapevine. Results Comparative genomics was used to identify 42 genes putatively involved in carotenoid biosynthesis/catabolism in grapevine. The genes are distributed on 16 of the 19 chromosomes and have been localised to the physical map of the heterozygous ENTAV115 grapevine sequence. Nine of the genes occur as single copies whereas the rest of the carotenoid metabolic genes have more than one paralogue. The cDNA copies of eleven corresponding genes from Vitis vinifera L. cv. Pinotage were characterised, and four where shown to be functional. Microarrays provided expression profiles of 39 accessions in the metabolic pathway during three berry developmental stages in Sauvignon blanc, whereas an optimised HPLC analysis provided the concentrations of individual carotenoids. This provides evidence of the functioning of the lutein epoxide cycle and the respective genes in grapevine. Similarly, orthologues of genes leading to the formation of strigolactone involved in shoot branching inhibition were identified: CCD7, CCD8 and MAX1. Moreover, the isoforms typically have different expression patterns, confirming the complex regulation of the pathway. Of particular interest is the expression pattern of the three VvNCEDs: Our results support previous findings that VvNCED3 is likely the isoform linked to ABA content in berries. Conclusions The carotenoid metabolic pathway is well characterised, and the genes and enzymes have been studied in a number of plants. The study of the 42 carotenoid pathway genes of grapevine showed that they share a high degree of similarity with other eudicots. Expression and pigment profiling of developing berries provided insights into the most complete grapevine carotenoid pathway representation. This study represents an important reference study for further characterisation of carotenoid biosynthesis and catabolism in grapevine. PMID:22702718

Integrated pathway analysis of nasopharyngeal carcinoma implicates the axonemal dynein complex in the Malaysian cohort.

PubMed

Chin, Yoon-Ming; Tan, Lu Ping; Abdul Aziz, Norazlin; Mushiroda, Taisei; Kubo, Michiaki; Mohd Kornain, Noor Kaslina; Tan, Geok Wee; Khoo, Alan Soo-Beng; Krishnan, Gopala; Pua, Kin-Choo; Yap, Yoke-Yeow; Teo, Soo-Hwang; Lim, Paul Vey-Hong; Nakamura, Yusuke; Lum, Chee Lun; Ng, Ching-Ching

2016-10-15

Nasopharyngeal carcinoma (NPC) is an epithelial squamous cell carcinoma on the mucosal lining of the nasopharynx. The etiology of NPC remains elusive despite many reported studies. Most studies employ a single platform approach, neglecting the cumulative influence of both the genome and transcriptome toward NPC development. We aim to employ an integrated pathway approach to identify dysregulated pathways linked to NPC. Our approach combines imputation NPC GWAS data from a Malaysian cohort as well as published expression data GSE12452 from both NPC and non-NPC nasopharynx tissues. Pathway association for GWAS data was performed using MAGENTA while for expression data, GSA-SNP was used with gene p values derived from differential expression values from GEO2R. Our study identified NPC association in the gene ontology (GO) axonemal dynein complex pathway (pGWAS-GSEA  = 1.98 × 10(-2) ; pExpr-GSEA  = 1.27 × 10(-24) ; pBonf-Combined  = 4.15 × 10(-21) ). This association was replicated in a separate cohort using gene expression data from NPC and non-NPC nasopharynx tissues (pAmpliSeq-GSEA  = 6.56 × 10(-4) ). Loss of function in the axonemal dynein complex causes impaired cilia function, leading to poor mucociliary clearance and subsequently upper or lower respiratory tract infection, the former of which includes the nasopharynx. Our approach illustrates the potential use of integrated pathway analysis in detecting gene sets involved in the development of NPC in the Malaysian cohort. © 2016 UICC.

Transcriptome analysis reveals enrichment of genes associated with auditory system in swimbladder of channel catfish.

PubMed

Yang, Yujia; Wang, Xiaozhu; Liu, Yang; Fu, Qiang; Tian, Changxu; Wu, Chenglong; Shi, Huitong; Yuan, Zihao; Tan, Suxu; Liu, Shikai; Gao, Dongya; Dunham, Rex; Liu, Zhanjiang

2018-04-30

In aquatic organisms, hearing is an important sense for acoustic communications and detection of sound-emitting predators and prey. Channel catfish is a dominant aquaculture species in the United States. As channel catfish can hear sounds of relatively high frequency, it serves as a good model for study auditory mechanisms. In catfishes, Weberian ossicles connect the swimbladder to the inner ear to transfer the forced vibrations and improve hearing ability. In this study, we examined the transcriptional profiles of channel catfish swimbladder and other four tissues (gill, liver, skin, and intestine). We identified a total of 1777 genes that exhibited preferential expression pattern in swimbladder of channel catfish. Based on Gene Ontology enrichment analysis, many of swimbladder-enriched genes were categorized into sensory perception of sound, auditory behavior, response to auditory stimulus, or detection of mechanical stimulus involved in sensory perception of sound, such as coch, kcnq4, sptbn1, sptbn4, dnm1, ush2a, and col11a1. Six signaling pathways associated with hearing (Glutamatergic synapse, GABAergic synapse pathways, Axon guidance, cAMP signaling pathway, Ionotropic glutamate receptor pathway, and Metabotropic glutamate receptor group III pathway) were over-represented in KEGG and PANTHER databases. Protein interaction prediction revealed an interactive relationship among the swimbladder-enriched genes and genes involved in sensory perception of sound. This study identified a set of genes and signaling pathways associated with auditory system in the swimbladder of channel catfish and provide resources for further study on the biological and physiological roles in catfish swimbladder. Copyright © 2018 Elsevier Inc. All rights reserved.

cPath: open source software for collecting, storing, and querying biological pathways

PubMed Central

Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris

2006-01-01

Background Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. Results We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. Conclusion cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling. PMID:17101041

Genome-Wide Identification of Destruxin A-Responsive Immunity-Related MicroRNAs in Diamondback Moth, Plutella xylostella.

PubMed

Shakeel, Muhammad; Xu, Xiaoxia; Xu, Jin; Li, Shuzhong; Yu, Jialin; Zhou, Xianqiang; Xu, Xiaojing; Hu, Qiongbo; Yu, Xiaoqiang; Jin, Fengliang

2018-01-01

Plutella xylostella , a global key pest, is one of the major lepidopteran pests of cruciferous vegetables owing to its strong ability of resistance development to a wide range of insecticides. Destruxin A, a mycotoxin of the entomopathogenic fungus, Metarhizium anisopliae , has broad-spectrum insecticidal effects and has been used as an alternative control strategy to reduce harmful effects of insecticides. However, microRNA (miRNA)-regulated reactions against destruxin A have not been elucidated yet. Therefore, here, to identify immunity-related miRNAs, we constructed four small RNA libraries from destruxin A-injected larvae of P. xylostella at three different time courses (2, 4, and 6 h) with a control, and sequenced by Illumina. Our results showed that totally 187 known and 44 novel miRNAs were identified in four libraries by bioinformatic analysis. Interestingly, among differentially expressed known miRNAs, some conserved miRNAs, such as miR-263, miR-279, miR-306, miR-2a, and miR-308, predicted to be involved in regulating immunity-related genes, were also identified. Worthy to mention, miR-306 and miR-279 were also listed as common abundantly expressed miRNA in all treatments. The Kyoto Encyclopedia of Genes and Genomes pathway analysis also indicated that differentially expressed miRNAs were involved in several immunity-related signaling pathways, including toll signaling pathway, IMD signaling pathway, JAK-STAT signaling pathway, and cell adhesion molecules signaling pathway. To the best of our knowledge, this is the first comprehensive report of destruxin A-responsive immunity-related miRNAs in P. xylostella . Our findings will improve in understanding the role of destruxin A-responsive miRNAs in the host immune system and would be useful to develop biological control strategies for controlling P. xylostella .

Genome-Wide Identification of Destruxin A-Responsive Immunity-Related MicroRNAs in Diamondback Moth, Plutella xylostella

PubMed Central

Shakeel, Muhammad; Xu, Xiaoxia; Xu, Jin; Li, Shuzhong; Yu, Jialin; Zhou, Xianqiang; Xu, Xiaojing; Hu, Qiongbo; Yu, Xiaoqiang; Jin, Fengliang

2018-01-01

Plutella xylostella, a global key pest, is one of the major lepidopteran pests of cruciferous vegetables owing to its strong ability of resistance development to a wide range of insecticides. Destruxin A, a mycotoxin of the entomopathogenic fungus, Metarhizium anisopliae, has broad-spectrum insecticidal effects and has been used as an alternative control strategy to reduce harmful effects of insecticides. However, microRNA (miRNA)-regulated reactions against destruxin A have not been elucidated yet. Therefore, here, to identify immunity-related miRNAs, we constructed four small RNA libraries from destruxin A-injected larvae of P. xylostella at three different time courses (2, 4, and 6 h) with a control, and sequenced by Illumina. Our results showed that totally 187 known and 44 novel miRNAs were identified in four libraries by bioinformatic analysis. Interestingly, among differentially expressed known miRNAs, some conserved miRNAs, such as miR-263, miR-279, miR-306, miR-2a, and miR-308, predicted to be involved in regulating immunity-related genes, were also identified. Worthy to mention, miR-306 and miR-279 were also listed as common abundantly expressed miRNA in all treatments. The Kyoto Encyclopedia of Genes and Genomes pathway analysis also indicated that differentially expressed miRNAs were involved in several immunity-related signaling pathways, including toll signaling pathway, IMD signaling pathway, JAK–STAT signaling pathway, and cell adhesion molecules signaling pathway. To the best of our knowledge, this is the first comprehensive report of destruxin A-responsive immunity-related miRNAs in P. xylostella. Our findings will improve in understanding the role of destruxin A-responsive miRNAs in the host immune system and would be useful to develop biological control strategies for controlling P. xylostella. PMID:29472927

Microarray analysis of gene expression in the cyclooxygenase knockout mice - a connection to autism spectrum disorder.

PubMed

Rai-Bhogal, Ravneet; Ahmad, Eizaaz; Li, Hongyan; Crawford, Dorota A

2018-03-01

The cellular and molecular events that take place during brain development play an important role in governing function of the mature brain. Lipid-signalling molecules such as prostaglandin E 2 (PGE 2 ) play an important role in healthy brain development. Abnormalities along the COX-PGE 2 signalling pathway due to genetic or environmental causes have been linked to autism spectrum disorder (ASD). This study aims to evaluate the effect of altered COX-PGE 2 signalling on development and function of the prenatal brain using male mice lacking cyclooxygenase-1 and cyclooxygenase-2 (COX-1 -/- and COX-2 -/- ) as potential model systems of ASD. Microarray analysis was used to determine global changes in gene expression during embryonic days 16 (E16) and 19 (E19). Gene Ontology: Biological Process (GO:BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were implemented to identify affected developmental genes and cellular processes. We found that in both knockouts the brain at E16 had nearly twice as many differentially expressed genes, and affected biological pathways containing various ASD-associated genes important in neuronal function. Interestingly, using GeneMANIA and Cytoscape we also show that the ASD-risk genes identified in both COX-1 -/- and COX-2 -/- models belong to protein-interaction networks important for brain development despite of different cellular localization of these enzymes. Lastly, we identified eight genes that belong to the Wnt signalling pathways exclusively in the COX-2 -/- mice at E16. The level of PKA-phosphorylated β-catenin (S552), a major activator of the Wnt pathway, was increased in this model, suggesting crosstalk between the COX-2-PGE 2 and Wnt pathways during early brain development. Overall, these results provide further molecular insight into the contribution of the COX-PGE 2 pathways to ASD and demonstrate that COX-1 -/- and COX-2 -/- animals might be suitable new model systems for studying the disorders. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Proteome-wide prediction of targets for aspirin: new insight into the molecular mechanism of aspirin

PubMed Central

Dai, Shao-Xing; Li, Wen-Xing

2016-01-01

Besides its anti-inflammatory, analgesic and anti-pyretic properties, aspirin is used for the prevention of cardiovascular disease and various types of cancer. The multiple activities of aspirin likely involve several molecular targets and pathways rather than a single target. Therefore, systematic identification of these targets of aspirin can help us understand the underlying mechanisms of the activities. In this study, we identified 23 putative targets of aspirin in the human proteome by using binding pocket similarity detecting tool combination with molecular docking, free energy calculation and pathway analysis. These targets have diverse folds and are derived from different protein family. However, they have similar aspirin-binding pockets. The binding free energy with aspirin for newly identified targets is comparable to that for the primary targets. Pathway analysis revealed that the targets were enriched in several pathways such as vascular endothelial growth factor (VEGF) signaling, Fc epsilon RI signaling and arachidonic acid metabolism, which are strongly involved in inflammation, cardiovascular disease and cancer. Therefore, the predicted target profile of aspirin suggests a new explanation for the disease prevention ability of aspirin. Our findings provide a new insight of aspirin and its efficacy of disease prevention in a systematic and global view. PMID:26989626

Field protocol and GIS analysis of connectivity in semiarid headwaters: metrics and evidences from Carcavo Basin (SE Spain)

NASA Astrophysics Data System (ADS)

Marchamalo, Miguel; Hooke, Janet; Gonzalez-Rodrigo, Beatriz; Sandercock, Peter

2017-04-01

Soil erosion and land degradation are severe problems in headwaters of ephemeral streams in semiarid Mediterranean regions, particularly in marginal upland areas over erodible parent material. Field-based information is required about the main pathways of sediment movement, the identification of sources and sinks and the influence of relevant factors. The EU-funded project RECONDES approached this reality by monitoring connectivity pathways of water and sediment movement in the landscape with the aim of identifying hotspots that could then be strategically targeted to reduce soil erosion and off-site effects. A protocol including field work and GIS analysis was developed and applied to a set of microcatchments in Carcavo Basin (Spain). The philosophy of the protocol was based on the repeated mapping after rainfall events so that frequency of activity of pathways could be evaluated. Connectivity was evaluated for each site and event using specific metrics: maximum mapped connectivity (corresponding to the largest recorded event), density of connected pathway links (m/ha) and frequency of activity (times active/total). Repeated connectivity mapping allowed identifying hotspots of erosion. The effect of structural and functional factors on connectivity was investigated. Field data is also valuable for validating future connectivity models in semiarid landscapes under highly variable and unpredictable conditions.

Proteome-wide prediction of targets for aspirin: new insight into the molecular mechanism of aspirin.

PubMed

Dai, Shao-Xing; Li, Wen-Xing; Li, Gong-Hua; Huang, Jing-Fei

2016-01-01

Besides its anti-inflammatory, analgesic and anti-pyretic properties, aspirin is used for the prevention of cardiovascular disease and various types of cancer. The multiple activities of aspirin likely involve several molecular targets and pathways rather than a single target. Therefore, systematic identification of these targets of aspirin can help us understand the underlying mechanisms of the activities. In this study, we identified 23 putative targets of aspirin in the human proteome by using binding pocket similarity detecting tool combination with molecular docking, free energy calculation and pathway analysis. These targets have diverse folds and are derived from different protein family. However, they have similar aspirin-binding pockets. The binding free energy with aspirin for newly identified targets is comparable to that for the primary targets. Pathway analysis revealed that the targets were enriched in several pathways such as vascular endothelial growth factor (VEGF) signaling, Fc epsilon RI signaling and arachidonic acid metabolism, which are strongly involved in inflammation, cardiovascular disease and cancer. Therefore, the predicted target profile of aspirin suggests a new explanation for the disease prevention ability of aspirin. Our findings provide a new insight of aspirin and its efficacy of disease prevention in a systematic and global view.

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

PubMed

Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

2018-04-23

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis and benefit the therapy improvement.

Comparative 2D-DIGE proteomic analysis of bovine mammary epithelial cells during lactation reveals protein signatures for lactation persistency and milk yield.

PubMed

Janjanam, Jagadeesh; Singh, Surender; Jena, Manoj K; Varshney, Nishant; Kola, Srujana; Kumar, Sudarshan; Kaushik, Jai K; Grover, Sunita; Dang, Ajay K; Mukesh, Manishi; Prakash, B S; Mohanty, Ashok K

2014-01-01

Mammary gland is made up of a branching network of ducts that end with alveoli which surrounds the lumen. These alveolar mammary epithelial cells (MEC) reflect the milk producing ability of farm animals. In this study, we have used 2D-DIGE and mass spectrometry to identify the protein changes in MEC during immediate early, peak and late stages of lactation and also compared differentially expressed proteins in MEC isolated from milk of high and low milk producing cows. We have identified 41 differentially expressed proteins during lactation stages and 22 proteins in high and low milk yielding cows. Bioinformatics analysis showed that a majority of the differentially expressed proteins are associated in metabolic process, catalytic and binding activity. The differentially expressed proteins were mapped to the available biological pathways and networks involved in lactation. The proteins up-regulated during late stage of lactation are associated with NF-κB stress induced signaling pathways and whereas Akt, PI3K and p38/MAPK signaling pathways are associated with high milk production mediated through insulin hormone signaling.

Altered metabolic pathways in clear cell renal cell carcinoma: A meta-analysis and validation study focused on the deregulated genes and their associated networks

PubMed Central

Zaravinos, Apostolos; Pieri, Myrtani; Mourmouras, Nikos; Anastasiadou, Natassa; Zouvani, Ioanna; Delakas, Dimitris; Deltas, Constantinos

2014-01-01

Clear cell renal cell carcinoma (ccRCC) is the predominant subtype of renal cell carcinoma (RCC). It is one of the most therapy-resistant carcinomas, responding very poorly or not at all to radiotherapy, hormonal therapy and chemotherapy. A more comprehensive understanding of the deregulated pathways in ccRCC can lead to the development of new therapies and prognostic markers. We performed a meta- analysis of 5 publicly available gene expression datasets and identified a list of co- deregulated genes, for which we performed extensive bioinformatic analysis coupled with experimental validation on the mRNA level. Gene ontology enrichment showed that many proteins are involved in response to hypoxia/oxygen levels and positive regulation of the VEGFR signaling pathway. KEGG analysis revealed that metabolic pathways are mostly altered in ccRCC. Similarly, Ingenuity Pathway Analysis showed that the antigen presentation, inositol metabolism, pentose phosphate, glycolysis/gluconeogenesis and fructose/mannose metabolism pathways are altered in the disease. Cellular growth, proliferation and carbohydrate metabolism, were among the top molecular and cellular functions of the co-deregulated genes. qRT-PCR validated the deregulated expression of several genes in Caki-2 and ACHN cell lines and in a cohort of ccRCC tissues. NNMT and NR3C1 increased expression was evident in ccRCC biopsies from patients using immunohistochemistry. ROC curves evaluated the diagnostic performance of the top deregulated genes in each dataset. We show that metabolic pathways are mostly deregulated in ccRCC and we highlight those being most responsible in its formation. We suggest that these genes are candidate predictive markers of the disease. PMID:25594006

Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.

PubMed

Pattaro, Cristian; Teumer, Alexander; Gorski, Mathias; Chu, Audrey Y; Li, Man; Mijatovic, Vladan; Garnaas, Maija; Tin, Adrienne; Sorice, Rossella; Li, Yong; Taliun, Daniel; Olden, Matthias; Foster, Meredith; Yang, Qiong; Chen, Ming-Huei; Pers, Tune H; Johnson, Andrew D; Ko, Yi-An; Fuchsberger, Christian; Tayo, Bamidele; Nalls, Michael; Feitosa, Mary F; Isaacs, Aaron; Dehghan, Abbas; d'Adamo, Pio; Adeyemo, Adebowale; Dieffenbach, Aida Karina; Zonderman, Alan B; Nolte, Ilja M; van der Most, Peter J; Wright, Alan F; Shuldiner, Alan R; Morrison, Alanna C; Hofman, Albert; Smith, Albert V; Dreisbach, Albert W; Franke, Andre; Uitterlinden, Andre G; Metspalu, Andres; Tonjes, Anke; Lupo, Antonio; Robino, Antonietta; Johansson, Åsa; Demirkan, Ayse; Kollerits, Barbara; Freedman, Barry I; Ponte, Belen; Oostra, Ben A; Paulweber, Bernhard; Krämer, Bernhard K; Mitchell, Braxton D; Buckley, Brendan M; Peralta, Carmen A; Hayward, Caroline; Helmer, Catherine; Rotimi, Charles N; Shaffer, Christian M; Müller, Christian; Sala, Cinzia; van Duijn, Cornelia M; Saint-Pierre, Aude; Ackermann, Daniel; Shriner, Daniel; Ruggiero, Daniela; Toniolo, Daniela; Lu, Yingchang; Cusi, Daniele; Czamara, Darina; Ellinghaus, David; Siscovick, David S; Ruderfer, Douglas; Gieger, Christian; Grallert, Harald; Rochtchina, Elena; Atkinson, Elizabeth J; Holliday, Elizabeth G; Boerwinkle, Eric; Salvi, Erika; Bottinger, Erwin P; Murgia, Federico; Rivadeneira, Fernando; Ernst, Florian; Kronenberg, Florian; Hu, Frank B; Navis, Gerjan J; Curhan, Gary C; Ehret, George B; Homuth, Georg; Coassin, Stefan; Thun, Gian-Andri; Pistis, Giorgio; Gambaro, Giovanni; Malerba, Giovanni; Montgomery, Grant W; Eiriksdottir, Gudny; Jacobs, Gunnar; Li, Guo; Wichmann, H-Erich; Campbell, Harry; Schmidt, Helena; Wallaschofski, Henri; Völzke, Henry; Brenner, Hermann; Kroemer, Heyo K; Kramer, Holly; Lin, Honghuang; Leach, I Mateo; Ford, Ian; Guessous, Idris; Rudan, Igor; Prokopenko, Inga; Borecki, Ingrid; Heid, Iris M; Kolcic, Ivana; Persico, Ivana; Jukema, J Wouter; Wilson, James F; Felix, Janine F; Divers, Jasmin; Lambert, Jean-Charles; Stafford, Jeanette M; Gaspoz, Jean-Michel; Smith, Jennifer A; Faul, Jessica D; Wang, Jie Jin; Ding, Jingzhong; Hirschhorn, Joel N; Attia, John; Whitfield, John B; Chalmers, John; Viikari, Jorma; Coresh, Josef; Denny, Joshua C; Karjalainen, Juha; Fernandes, Jyotika K; Endlich, Karlhans; Butterbach, Katja; Keene, Keith L; Lohman, Kurt; Portas, Laura; Launer, Lenore J; Lyytikäinen, Leo-Pekka; Yengo, Loic; Franke, Lude; Ferrucci, Luigi; Rose, Lynda M; Kedenko, Lyudmyla; Rao, Madhumathi; Struchalin, Maksim; Kleber, Marcus E; Cavalieri, Margherita; Haun, Margot; Cornelis, Marilyn C; Ciullo, Marina; Pirastu, Mario; de Andrade, Mariza; McEvoy, Mark A; Woodward, Mark; Adam, Martin; Cocca, Massimiliano; Nauck, Matthias; Imboden, Medea; Waldenberger, Melanie; Pruijm, Menno; Metzger, Marie; Stumvoll, Michael; Evans, Michele K; Sale, Michele M; Kähönen, Mika; Boban, Mladen; Bochud, Murielle; Rheinberger, Myriam; Verweij, Niek; Bouatia-Naji, Nabila; Martin, Nicholas G; Hastie, Nick; Probst-Hensch, Nicole; Soranzo, Nicole; Devuyst, Olivier; Raitakari, Olli; Gottesman, Omri; Franco, Oscar H; Polasek, Ozren; Gasparini, Paolo; Munroe, Patricia B; Ridker, Paul M; Mitchell, Paul; Muntner, Paul; Meisinger, Christa; Smit, Johannes H; Kovacs, Peter; Wild, Philipp S; Froguel, Philippe; Rettig, Rainer; Mägi, Reedik; Biffar, Reiner; Schmidt, Reinhold; Middelberg, Rita P S; Carroll, Robert J; Penninx, Brenda W; Scott, Rodney J; Katz, Ronit; Sedaghat, Sanaz; Wild, Sarah H; Kardia, Sharon L R; Ulivi, Sheila; Hwang, Shih-Jen; Enroth, Stefan; Kloiber, Stefan; Trompet, Stella; Stengel, Benedicte; Hancock, Stephen J; Turner, Stephen T; Rosas, Sylvia E; Stracke, Sylvia; Harris, Tamara B; Zeller, Tanja; Zemunik, Tatijana; Lehtimäki, Terho; Illig, Thomas; Aspelund, Thor; Nikopensius, Tiit; Esko, Tonu; Tanaka, Toshiko; Gyllensten, Ulf; Völker, Uwe; Emilsson, Valur; Vitart, Veronique; Aalto, Ville; Gudnason, Vilmundur; Chouraki, Vincent; Chen, Wei-Min; Igl, Wilmar; März, Winfried; Koenig, Wolfgang; Lieb, Wolfgang; Loos, Ruth J F; Liu, Yongmei; Snieder, Harold; Pramstaller, Peter P; Parsa, Afshin; O'Connell, Jeffrey R; Susztak, Katalin; Hamet, Pavel; Tremblay, Johanne; de Boer, Ian H; Böger, Carsten A; Goessling, Wolfram; Chasman, Daniel I; Köttgen, Anna; Kao, W H Linda; Fox, Caroline S

2016-01-21

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.

Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function

PubMed Central

Pattaro, Cristian; Teumer, Alexander; Gorski, Mathias; Chu, Audrey Y.; Li, Man; Mijatovic, Vladan; Garnaas, Maija; Tin, Adrienne; Sorice, Rossella; Li, Yong; Taliun, Daniel; Olden, Matthias; Foster, Meredith; Yang, Qiong; Chen, Ming-Huei; Pers, Tune H.; Johnson, Andrew D.; Ko, Yi-An; Fuchsberger, Christian; Tayo, Bamidele; Nalls, Michael; Feitosa, Mary F.; Isaacs, Aaron; Dehghan, Abbas; d'Adamo, Pio; Adeyemo, Adebowale; Dieffenbach, Aida Karina; Zonderman, Alan B.; Nolte, Ilja M.; van der Most, Peter J.; Wright, Alan F.; Shuldiner, Alan R.; Morrison, Alanna C.; Hofman, Albert; Smith, Albert V.; Dreisbach, Albert W.; Franke, Andre; Uitterlinden, Andre G.; Metspalu, Andres; Tonjes, Anke; Lupo, Antonio; Robino, Antonietta; Johansson, Åsa; Demirkan, Ayse; Kollerits, Barbara; Freedman, Barry I.; Ponte, Belen; Oostra, Ben A.; Paulweber, Bernhard; Krämer, Bernhard K.; Mitchell, Braxton D.; Buckley, Brendan M.; Peralta, Carmen A.; Hayward, Caroline; Helmer, Catherine; Rotimi, Charles N.; Shaffer, Christian M.; Müller, Christian; Sala, Cinzia; van Duijn, Cornelia M.; Saint-Pierre, Aude; Ackermann, Daniel; Shriner, Daniel; Ruggiero, Daniela; Toniolo, Daniela; Lu, Yingchang; Cusi, Daniele; Czamara, Darina; Ellinghaus, David; Siscovick, David S.; Ruderfer, Douglas; Gieger, Christian; Grallert, Harald; Rochtchina, Elena; Atkinson, Elizabeth J.; Holliday, Elizabeth G.; Boerwinkle, Eric; Salvi, Erika; Bottinger, Erwin P.; Murgia, Federico; Rivadeneira, Fernando; Ernst, Florian; Kronenberg, Florian; Hu, Frank B.; Navis, Gerjan J.; Curhan, Gary C.; Ehret, George B.; Homuth, Georg; Coassin, Stefan; Thun, Gian-Andri; Pistis, Giorgio; Gambaro, Giovanni; Malerba, Giovanni; Montgomery, Grant W.; Eiriksdottir, Gudny; Jacobs, Gunnar; Li, Guo; Wichmann, H-Erich; Campbell, Harry; Schmidt, Helena; Wallaschofski, Henri; Völzke, Henry; Brenner, Hermann; Kroemer, Heyo K.; Kramer, Holly; Lin, Honghuang; Leach, I. Mateo; Ford, Ian; Guessous, Idris; Rudan, Igor; Prokopenko, Inga; Borecki, Ingrid; Heid, Iris M.; Kolcic, Ivana; Persico, Ivana; Jukema, J. Wouter; Wilson, James F.; Felix, Janine F.; Divers, Jasmin; Lambert, Jean-Charles; Stafford, Jeanette M.; Gaspoz, Jean-Michel; Smith, Jennifer A.; Faul, Jessica D.; Wang, Jie Jin; Ding, Jingzhong; Hirschhorn, Joel N.; Attia, John; Whitfield, John B.; Chalmers, John; Viikari, Jorma; Coresh, Josef; Denny, Joshua C.; Karjalainen, Juha; Fernandes, Jyotika K.; Endlich, Karlhans; Butterbach, Katja; Keene, Keith L.; Lohman, Kurt; Portas, Laura; Launer, Lenore J.; Lyytikäinen, Leo-Pekka; Yengo, Loic; Franke, Lude; Ferrucci, Luigi; Rose, Lynda M.; Kedenko, Lyudmyla; Rao, Madhumathi; Struchalin, Maksim; Kleber, Marcus E.; Cavalieri, Margherita; Haun, Margot; Cornelis, Marilyn C.; Ciullo, Marina; Pirastu, Mario; de Andrade, Mariza; McEvoy, Mark A.; Woodward, Mark; Adam, Martin; Cocca, Massimiliano; Nauck, Matthias; Imboden, Medea; Waldenberger, Melanie; Pruijm, Menno; Metzger, Marie; Stumvoll, Michael; Evans, Michele K.; Sale, Michele M.; Kähönen, Mika; Boban, Mladen; Bochud, Murielle; Rheinberger, Myriam; Verweij, Niek; Bouatia-Naji, Nabila; Martin, Nicholas G.; Hastie, Nick; Probst-Hensch, Nicole; Soranzo, Nicole; Devuyst, Olivier; Raitakari, Olli; Gottesman, Omri; Franco, Oscar H.; Polasek, Ozren; Gasparini, Paolo; Munroe, Patricia B.; Ridker, Paul M.; Mitchell, Paul; Muntner, Paul; Meisinger, Christa; Smit, Johannes H.; Abecasis, Goncalo R.; Adair, Linda S.; Alexander, Myriam; Altshuler, David; Amin, Najaf; Arking, Dan E.; Arora, Pankaj; Aulchenko, Yurii; Bakker, Stephan J. L.; Bandinelli, Stefania; Barroso, Ines; Beckmann, Jacques S.; Beilby, John P.; Bergman, Richard N.; Bergmann, Sven; Bis, Joshua C.; Boehnke, Michael; Bonnycastle, Lori L.; Bornstein, Stefan R.; Bots, Michiel L.; Bragg-Gresham, Jennifer L.; Brand, Stefan-Martin; Brand, Eva; Braund, Peter S.; Brown, Morris J.; Burton, Paul R.; Casas, Juan P.; Caulfield, Mark J.; Chakravarti, Aravinda; Chambers, John C.; Chandak, Giriraj R.; Chang, Yen-Pei C.; Charchar, Fadi J.; Chaturvedi, Nish; Shin Cho, Yoon; Clarke, Robert; Collins, Francis S.; Collins, Rory; Connell, John M.; Cooper, Jackie A.; Cooper, Matthew N.; Cooper, Richard S.; Corsi, Anna Maria; Dörr, Marcus; Dahgam, Santosh; Danesh, John; Smith, George Davey; Day, Ian N. M.; Deloukas, Panos; Denniff, Matthew; Dominiczak, Anna F.; Dong, Yanbin; Doumatey, Ayo; Elliott, Paul; Elosua, Roberto; Erdmann, Jeanette; Eyheramendy, Susana; Farrall, Martin; Fava, Cristiano; Forrester, Terrence; Fowkes, F. Gerald R.; Fox, Ervin R.; Frayling, Timothy M.; Galan, Pilar; Ganesh, Santhi K.; Garcia, Melissa; Gaunt, Tom R.; Glazer, Nicole L.; Go, Min Jin; Goel, Anuj; Grässler, Jürgen; Grobbee, Diederick E.; Groop, Leif; Guarrera, Simonetta; Guo, Xiuqing; Hadley, David; Hamsten, Anders; Han, Bok-Ghee; Hardy, Rebecca; Hartikainen, Anna-Liisa; Heath, Simon; Heckbert, Susan R.; Hedblad, Bo; Hercberg, Serge; Hernandez, Dena; Hicks, Andrew A.; Hilton, Gina; Hingorani, Aroon D.; Bolton, Judith A Hoffman; Hopewell, Jemma C.; Howard, Philip; Humphries, Steve E.; Hunt, Steven C.; Hveem, Kristian; Ikram, M. Arfan; Islam, Muhammad; Iwai, Naoharu; Jarvelin, Marjo-Riitta; Jackson, Anne U.; Jafar, Tazeen H.; Janipalli, Charles S.; Johnson, Toby; Kathiresan, Sekar; Khaw, Kay-Tee; Kim, Hyung-Lae; Kinra, Sanjay; Kita, Yoshikuni; Kivimaki, Mika; Kooner, Jaspal S.; Kumar, M. J. Kranthi; Kuh, Diana; Kulkarni, Smita R.; Kumari, Meena; Kuusisto, Johanna; Kuznetsova, Tatiana; Laakso, Markku; Laan, Maris; Laitinen, Jaana; Lakatta, Edward G.; Langefeld, Carl D.; Larson, Martin G.; Lathrop, Mark; Lawlor, Debbie A.; Lawrence, Robert W.; Lee, Jong-Young; Lee, Nanette R.; Levy, Daniel; Li, Yali; Longstreth, Will T.; Luan, Jian'an; Lucas, Gavin; Ludwig, Barbara; Mangino, Massimo; Mani, K. Radha; Marmot, Michael G.; Mattace-Raso, Francesco U. S.; Matullo, Giuseppe; McArdle, Wendy L.; McKenzie, Colin A.; Meitinger, Thomas; Melander, Olle; Meneton, Pierre; Meschia, James F.; Miki, Tetsuro; Milaneschi, Yuri; Mohlke, Karen L.; Mooser, Vincent; Morken, Mario A.; Morris, Richard W.; Mosley, Thomas H.; Najjar, Samer; Narisu, Narisu; Newton-Cheh, Christopher; Nguyen, Khanh-Dung Hoang; Nilsson, Peter; Nyberg, Fredrik; O'Donnell, Christopher J.; Ogihara, Toshio; Ohkubo, Takayoshi; Okamura, Tomonori; Ong, RickTwee-Hee; Ongen, Halit; Onland-Moret, N. Charlotte; O'Reilly, Paul F.; Org, Elin; Orru, Marco; Palmas, Walter; Palmen, Jutta; Palmer, Lyle J.; Palmer, Nicholette D.; Parker, Alex N.; Peden, John F.; Peltonen, Leena; Perola, Markus; Pihur, Vasyl; Platou, Carl G. P.; Plump, Andrew; Prabhakaran, Dorairajan; Psaty, Bruce M.; Raffel, Leslie J.; Rao, Dabeeru C.; Rasheed, Asif; Ricceri, Fulvio; Rice, Kenneth M.; Rosengren, Annika; Rotter, Jerome I.; Rudock, Megan E.; Sõber, Siim; Salako, Tunde; Saleheen, Danish; Salomaa, Veikko; Samani, Nilesh J.; Schwartz, Steven M.; Schwarz, Peter E. H.; Scott, Laura J.; Scott, James; Scuteri, Angelo; Sehmi, Joban S.; Seielstad, Mark; Seshadri, Sudha; Sharma, Pankaj; Shaw-Hawkins, Sue; Shi, Gang; Shrine, Nick R. G.; Sijbrands, Eric J. G.; Sim, Xueling; Singleton, Andrew; Sjögren, Marketa; Smith, Nicholas L.; Artigas, Maria Soler; Spector, Tim D.; Staessen, Jan A.; Stancakova, Alena; Steinle, Nanette I.; Strachan, David P.; Stringham, Heather M.; Sun, Yan V.; Swift, Amy J.; Tabara, Yasuharu; Tai, E-Shyong; Talmud, Philippa J.; Taylor, Andrew; Terzic, Janos; Thelle, Dag S.; Tobin, Martin D.; Tomaszewski, Maciej; Tripathy, Vikal; Tuomilehto, Jaakko; Tzoulaki, Ioanna; Uda, Manuela; Ueshima, Hirotsugu; Uiterwaal, Cuno S. P. M.; Umemura, Satoshi; van der Harst, Pim; van der Schouw, Yvonne T.; van Gilst, Wiek H.; Vartiainen, Erkki; Vasan, Ramachandran S.; Veldre, Gudrun; Verwoert, Germaine C.; Viigimaa, Margus; Vinay, D. G.; Vineis, Paolo; Voight, Benjamin F.; Vollenweider, Peter; Wagenknecht, Lynne E.; Wain, Louise V.; Wang, Xiaoling; Wang, Thomas J.; Wareham, Nicholas J.; Watkins, Hugh; Weder, Alan B.; Whincup, Peter H.; Wiggins, Kerri L.; Witteman, Jacqueline C. M.; Wong, Andrew; Wu, Ying; Yajnik, Chittaranjan S.; Yao, Jie; Young, J. H.; Zelenika, Diana; Zhai, Guangju; Zhang, Weihua; Zhang, Feng; Zhao, Jing Hua; Zhu, Haidong; Zhu, Xiaofeng; Zitting, Paavo; Zukowska-Szczechowska, Ewa; Okada, Yukinori; Wu, Jer-Yuarn; Gu, Dongfeng; Takeuchi, Fumihiko; Takahashi, Atsushi; Maeda, Shiro; Tsunoda, Tatsuhiko; Chen, Peng; Lim, Su-Chi; Wong, Tien-Yin; Liu, Jianjun; Young, Terri L.; Aung, Tin; Teo, Yik-Ying; Kim, Young Jin; Kang, Daehee; Chen, Chien-Hsiun; Tsai, Fuu-Jen; Chang, Li-Ching; Fann, S. -J. Cathy; Mei, Hao; Hixson, James E.; Chen, Shufeng; Katsuya, Tomohiro; Isono, Masato; Albrecht, Eva; Yamamoto, Kazuhiko; Kubo, Michiaki; Nakamura, Yusuke; Kamatani, Naoyuki; Kato, Norihiro; He, Jiang; Chen, Yuan-Tsong; Tanaka, Toshihiro; Reilly, Muredach P; Schunkert, Heribert; Assimes, Themistocles L.; Hall, Alistair; Hengstenberg, Christian; König, Inke R.; Laaksonen, Reijo; McPherson, Ruth; Thompson, John R.; Thorsteinsdottir, Unnur; Ziegler, Andreas; Absher, Devin; Chen, Li; Cupples13, L. Adrienne; Halperin, Eran; Li, Mingyao; Musunuru, Kiran; Preuss, Michael; Schillert, Arne; Thorleifsson, Gudmar; Wells, George A.; Holm, Hilma; Roberts, Robert; Stewart, Alexandre F. R.; Fortmann, Stephen; Go, Alan; Hlatky, Mark; Iribarren, Carlos; Knowles, Joshua; Myers, Richard; Quertermous, Thomas; Sidney, Steven; Risch, Neil; Tang, Hua; Blankenberg, Stefan; Schnabel, Renate; Sinning, Christoph; Lackner, Karl J.; Tiret, Laurence; Nicaud, Viviane; Cambien, Francois; Bickel, Christoph; Rupprecht, Hans J.; Perret, Claire; Proust, Carole; Münzel, Thomas F.; Barbalic, Maja; Chen, Ida Yii-Der; Demissie-Banjaw, Serkalem; Folsom, Aaron; Lumley, Thomas; Marciante, Kristin; Taylor, Kent D.; Volcik, Kelly; Gretarsdottir, Solveig; Gulcher, Jeffrey R.; Kong, Augustine; Stefansson, Kari; Thorgeirsson, Gudmundur; Andersen, Karl; Fischer, Marcus; Grosshennig, Anika; Linsel-Nitschke, Patrick; Stark, Klaus; Schreiber, Stefan; Aherrahrou, Zouhair; Bruse, Petra; Doering, Angela; Klopp, Norman; Diemert, Patrick; Loley, Christina; Medack, Anja; Nahrstedt, Janja; Peters, Annette; Wagner, Arnika K.; Willenborg, Christina; Böhm, Bernhard O.; Dobnig, Harald; Grammer, Tanja B.; Hoffmann, Michael M.; Meinitzer, Andreas; Winkelmann, Bernhard R.; Pilz, Stefan; Renner, Wilfried; Scharnagl, Hubert; Stojakovic, Tatjana; Tomaschitz, Andreas; Winkler, Karl; Guiducci, Candace; Burtt, Noel; Gabriel, Stacey B.; Dandona, Sonny; Jarinova, Olga; Qu, Liming; Wilensky, Robert; Matthai, William; Hakonarson, Hakon H.; Devaney, Joe; Burnett, Mary Susan; Pichard, Augusto D.; Kent, Kenneth M.; Satler, Lowell; Lindsay, Joseph M.; Waksman, Ron; Knouff, Christopher W.; Waterworth, Dawn M.; Walker, Max C.; Epstein, Stephen E.; Rader, Daniel J.; Nelson, Christopher P.; Wright, Benjamin J.; Balmforth, Anthony J.; Ball, Stephen G.; Loehr, Laura R.; Rosamond, Wayne D.; Benjamin, Emelia; Haritunians, Talin; Couper, David; Murabito, Joanne; Wang, Ying A.; Stricker, Bruno H.; Chang, Patricia P.; Willerson, James T.; Felix, Stephan B.; Watzinger, Norbert; Aragam, Jayashri; Zweiker, Robert; Lind, Lars; Rodeheffer, Richard J.; Greiser, Karin Halina; Deckers, Jaap W.; Stritzke, Jan; Ingelsson, Erik; Kullo, Iftikhar; Haerting, Johannes; Reffelmann, Thorsten; Redfield, Margaret M.; Werdan, Karl; Mitchell, Gary F.; Arnett, Donna K.; Gottdiener, John S.; Blettner, Maria; Friedrich, Nele; Kovacs, Peter; Wild, Philipp S.; Froguel, Philippe; Rettig, Rainer; Mägi, Reedik; Biffar, Reiner; Schmidt, Reinhold; Middelberg, Rita P. S.; Carroll, Robert J.; Penninx, Brenda W.; Scott, Rodney J.; Katz, Ronit; Sedaghat, Sanaz; Wild, Sarah H.; Kardia, Sharon L. R.; Ulivi, Sheila; Hwang, Shih-Jen; Enroth, Stefan; Kloiber, Stefan; Trompet, Stella; Stengel, Benedicte; Hancock, Stephen J.; Turner, Stephen T.; Rosas, Sylvia E.; Stracke, Sylvia; Harris, Tamara B.; Zeller, Tanja; Zemunik, Tatijana; Lehtimäki, Terho; Illig, Thomas; Aspelund, Thor; Nikopensius, Tiit; Esko, Tonu; Tanaka, Toshiko; Gyllensten, Ulf; Völker, Uwe; Emilsson, Valur; Vitart, Veronique; Aalto, Ville; Gudnason, Vilmundur; Chouraki, Vincent; Chen, Wei-Min; Igl, Wilmar; März, Winfried; Koenig, Wolfgang; Lieb, Wolfgang; Loos, Ruth J. F.; Liu, Yongmei; Snieder, Harold; Pramstaller, Peter P.; Parsa, Afshin; O'Connell, Jeffrey R.; Susztak, Katalin; Hamet, Pavel; Tremblay, Johanne; de Boer, Ian H.; Böger, Carsten A.; Goessling, Wolfram; Chasman, Daniel I.; Köttgen, Anna; Kao, W. H. Linda; Fox, Caroline S.

2016-01-01

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways. PMID:26831199

Combining medical informatics and bioinformatics toward tools for personalized medicine.

PubMed

Sarachan, B D; Simmons, M K; Subramanian, P; Temkin, J M

2003-01-01

Key bioinformatics and medical informatics research areas need to be identified to advance knowledge and understanding of disease risk factors and molecular disease pathology in the 21 st century toward new diagnoses, prognoses, and treatments. Three high-impact informatics areas are identified: predictive medicine (to identify significant correlations within clinical data using statistical and artificial intelligence methods), along with pathway informatics and cellular simulations (that combine biological knowledge with advanced informatics to elucidate molecular disease pathology). Initial predictive models have been developed for a pilot study in Huntington's disease. An initial bioinformatics platform has been developed for the reconstruction and analysis of pathways, and work has begun on pathway simulation. A bioinformatics research program has been established at GE Global Research Center as an important technology toward next generation medical diagnostics. We anticipate that 21 st century medical research will be a combination of informatics tools with traditional biology wet lab research, and that this will translate to increased use of informatics techniques in the clinic.

Whole transcriptome profiling of taste bud cells.

PubMed

Sukumaran, Sunil K; Lewandowski, Brian C; Qin, Yumei; Kotha, Ramana; Bachmanov, Alexander A; Margolskee, Robert F

2017-08-08

Analysis of single-cell RNA-Seq data can provide insights into the specific functions of individual cell types that compose complex tissues. Here, we examined gene expression in two distinct subpopulations of mouse taste cells: Tas1r3-expressing type II cells and physiologically identified type III cells. Our RNA-Seq libraries met high quality control standards and accurately captured differential expression of marker genes for type II (e.g. the Tas1r genes, Plcb2, Trpm5) and type III (e.g. Pkd2l1, Ncam, Snap25) taste cells. Bioinformatics analysis showed that genes regulating responses to stimuli were up-regulated in type II cells, while pathways related to neuronal function were up-regulated in type III cells. We also identified highly expressed genes and pathways associated with chemotaxis and axon guidance, providing new insights into the mechanisms underlying integration of new taste cells into the taste bud. We validated our results by immunohistochemically confirming expression of selected genes encoding synaptic (Cplx2 and Pclo) and semaphorin signalling pathway (Crmp2, PlexinB1, Fes and Sema4a) components. The approach described here could provide a comprehensive map of gene expression for all taste cell subpopulations and will be particularly relevant for cell types in taste buds and other tissues that can be identified only by physiological methods.

Pathways to Lean Software Development: An Analysis of Effective Methods of Change

ERIC Educational Resources Information Center

Hanson, Richard D.

2014-01-01

This qualitative Delphi study explored the challenges that exist in delivering software on time, within budget, and with the original scope identified. The literature review identified many attempts over the past several decades to reform the methods used to develop software. These attempts found that the classical waterfall method, which is…

Co-factors Required for TLR7- and TLR9- dependent Innate Immune Responses

PubMed Central

Chiang, Chih-yuan; Engel, Alex; Opaluch, Amanda M.; Ramos, Irene; Maestre, Ana M.; Secundino, Ismael; De Jesus, Paul D.; Nguyen, Quy T.; Welch, Genevieve; Bonamy, Ghislain M.C.; Miraglia, Loren J.; Orth, Anthony P.; Nizet, Victor; Fernandez-Sesma, Ana; Zhou, Yingyao; Barton, Gregory M.; Chanda, Sumit K.

2012-01-01

SUMMARY Pathogens commonly utilize endocytic pathways to gain cellular access. The endosomal pattern recognition receptors TLR7 and TLR9 detect pathogen-encoded nucleic acids to initiate MyD88-dependent pro-inflammatory responses to microbial infection. Using genome-wide RNAi screening and integrative systems-based analysis we identify 190 co-factors required for TLR7- and TLR9-directed signaling responses. A set of co-factors were cross-profiled for their activities downstream of several immunoreceptors, and then functionally mapped based on the known architecture of NF-κB signaling pathways. Protein complexes and pathways involved in ubiquitin-protein ligase activities, sphingolipid metabolism, chromatin modifications, and ancient stress responses were found to modulate innate recognition of endosomal nucleic acids. Additionally, hepatocyte growth factor-regulated tyrosine kinase substrate (HRS) was characterized as necessary for ubiquitin-dependent TLR9 targeting to the endolysosome. Proteins and pathways identified here should prove useful in delineating strategies to manipulate innate responses for treatment of autoimmune disorders and microbial infection. PMID:22423970

Effects of imatinib and nilotinib on the whole transcriptome of cultured murine osteoblasts.

PubMed

Kirschner, Gyöngyi; Balla, Bernadett; Horváth, Péter; Kövesdi, Andrea; Lakatos, Gergely; Takács, István; Nagy, Zsolt; Tóbiás, Bálint; Árvai, Kristóf; Kósa, János Pál; Lakatos, Péter

2016-09-01

Numerous clinical observations have confirmed that breakpoint cluster region-abelson fusion oncoprotein tyrosine kinase inhibitors used in leukemia treatment alter bone physiology in a complex manner. The aim of the present study was to analyze the whole transcriptome of cultured murine osteoblasts and determine the changes following treatment with imatinib and nilotinib using Sequencing by Oligonucleotide Ligation and Detection next generation RNA sequencing. This study also aimed to identify candidate signaling pathways and network regulators by multivariate Ingenuity Pathway Analysis. Based on the right-tailed Fisher's exact test, significantly altered pathways including upstream regulators were defined for each drug. The correlation between these pathways and bone metabolism was also examined. The preliminary results suggest the two drugs have different mechanisms of action on osteoblasts, and imatinib was shown to have a greater effect on gene expression. Data also indicated the potential role of a number of genes and signaling cascades that may contribute to identifying novel targets for the treatment of metabolic bone diseases.

A proposed model for the flowering signaling pathway of sugarcane under photoperiodic control.

PubMed

Coelho, C P; Costa Netto, A P; Colasanti, J; Chalfun-Júnior, A

2013-04-25

Molecular analysis of floral induction in Arabidopsis has identified several flowering time genes related to 4 response networks defined by the autonomous, gibberellin, photoperiod, and vernalization pathways. Although grass flowering processes include ancestral functions shared by both mono- and dicots, they have developed their own mechanisms to transmit floral induction signals. Despite its high production capacity and its important role in biofuel production, almost no information is available about the flowering process in sugarcane. We searched the Sugarcane Expressed Sequence Tags database to look for elements of the flowering signaling pathway under photoperiodic control. Sequences showing significant similarity to flowering time genes of other species were clustered, annotated, and analyzed for conserved domains. Multiple alignments comparing the sequences found in the sugarcane database and those from other species were performed and their phylogenetic relationship assessed using the MEGA 4.0 software. Electronic Northerns were run with Cluster and TreeView programs, allowing us to identify putative members of the photoperiod-controlled flowering pathway of sugarcane.

Inactivation of Hippo Pathway Is Significantly Associated with Poor Prognosis in Hepatocellular Carcinoma.

PubMed

Sohn, Bo Hwa; Shim, Jae-Jun; Kim, Sang-Bae; Jang, Kyu Yun; Kim, Soo Mi; Kim, Ji Hoon; Hwang, Jun Eul; Jang, Hee-Jin; Lee, Hyun-Sung; Kim, Sang-Cheol; Jeong, Woojin; Kim, Sung Soo; Park, Eun Sung; Heo, Jeonghoon; Kim, Yoon Jun; Kim, Dae-Ghon; Leem, Sun-Hee; Kaseb, Ahmed; Hassan, Manal M; Cha, Minse; Chu, In-Sun; Johnson, Randy L; Park, Yun-Yong; Lee, Ju-Seog

2016-03-01

The Hippo pathway is a tumor suppressor in the liver. However, the clinical significance of Hippo pathway inactivation in HCC is not clearly defined. We analyzed genomic data from human and mouse tissues to determine clinical relevance of Hippo pathway inactivation in HCC. We analyzed gene expression data from Mst1/2(-/-) and Sav1(-/-) mice and identified a 610-gene expression signature reflecting Hippo pathway inactivation in the liver [silence of Hippo (SOH) signature]. By integrating gene expression data from mouse models with those from human HCC tissues, we developed a prediction model that could identify HCC patients with an inactivated Hippo pathway and used it to test its significance in HCC patients, via univariate and multivariate Cox analyses. HCC patients (National Cancer Institute cohort, n = 113) with the SOH signature had a significantly poorer prognosis than those without the SOH signature [P < 0.001 for overall survival (OS)]. The significant association of the signature with poor prognosis was further validated in the Korean (n = 100, P = 0.006 for OS) and Fudan University cohorts (n = 242, P = 0.001 for OS). On multivariate analysis, the signature was an independent predictor of recurrence-free survival (HR, 1.6; 95% confidence interval, 1.12-2.28: P = 0.008). We also demonstrated significant concordance between the SOH HCC subtype and the hepatic stem cell HCC subtype that had been identified in a previous study (P < 0.001). Inactivation of the Hippo pathway in HCC is significantly associated with poor prognosis. ©2015 American Association for Cancer Research.

Integrating emotional and psychological support into the end-stage renal disease pathway: a protocol for mixed methods research to identify patients' lower-level support needs and how these can most effectively be addressed.

PubMed

Taylor, Francesca; Taylor, Celia; Baharani, Jyoti; Nicholas, Johann; Combes, Gill

2016-08-02

As a result of difficulties related to their illness, diagnosis and treatment, patients with end-stage renal disease experience significant emotional and psychological problems, which untreated can have considerable negative impact on their health and wellbeing. Despite evidence that patients desire improved support, management of their psychosocial problems, particularly at the lower-level, remains sub-optimal. There is limited understanding of the specific support that patients need and want, from whom, and when, and also a lack of data on what helps and hinders renal staff in identifying and responding to their patients' support needs, and how barriers to doing so might be overcome. Through this research we therefore seek to determine what, when, and how, support for patients with lower-level emotional and psychological problems should be integrated into the end-stage renal disease pathway. The research will involve two linked, multicentre studies, designed to identify and consider the perspectives of patients at five different stages of the end-stage renal disease pathway (Study 1), and renal staff working with them (Study 2). A convergent, parallel mixed methods design will be employed for both studies, with quantitative and qualitative data collected separately. For each study, the data sets will be analysed separately and the results then compared or combined using interpretive analysis. A further stage of synthesis will employ data-driven thematic analysis to identify: triangulation and frequency of themes across pathway stages; patterns and plausible explanations of effects. There is an important need for this research given the high frequency of lower-level distress experienced by end-stage renal disease patients and lack of progress to date in integrating support for their lower-level psychosocial needs into the care pathway. Use of a mixed methods design across the two studies will generate a holistic patient and healthcare professional perspective that is more likely to identify viable solutions to enable implementation of timely and integrated care. Based on the research outputs, appropriate support interventions will be developed, implemented and evaluated in a linked follow-on study.

Pathways to adolescent childbearing among Kaqchikel women in Guatemala.

PubMed

Lemon, Emily; Hennink, Monique; Can Saquic, Nely Amparo

2017-10-01

One-in-five children in Guatemala is born to a mother aged 15-19 years, which poses social, economic and health risks to both mother and child. In Guatemala, adolescent childbearing is directly associated with education, ethnicity and poverty, which increases vulnerability among Indigenous young women living in poverty. This study examines the context and experiences of adolescent childbearing from the perspectives of young mothers in the Kaqchikel Indigenous ethnic group of Sololá, Guatemala. Data were collected in 19 qualitative in-depth interviews with women who had given birth to one or more children when aged 15 to 19 years. Grounded theory and narrative analysis were used to develop a conceptual framework of the process and influences on childbearing. Four distinct pathways were identified, which were influenced by gender expectations, limited communication about sex and stigma around sex. The study identifies key sociocultural influences that lead to adolescent childbearing and reveals variability within these. Identifying distinct pathways to early childbearing and their influences enables a clearer understanding of potential opportunities to interrupt these pathways with culturally relevant policies and programmes, in particular those that promote gender equality and intergenerational communication about sex.

Characterization of gossypol biosynthetic pathway

PubMed Central

Tian, Xiu; Ruan, Ju-Xin; Huang, Jin-Quan; Fang, Xin; Chen, Zhi-Wen; Hong, Hui; Wang, Ling-Jian; Mao, Ying-Bo; Lu, Shan; Zhang, Tian-Zhen; Chen, Xiao-Ya

2018-01-01

Gossypol and related sesquiterpene aldehydes in cotton function as defense compounds but are antinutritional in cottonseed products. By transcriptome comparison and coexpression analyses, we identified 146 candidates linked to gossypol biosynthesis. Analysis of metabolites accumulated in plants subjected to virus-induced gene silencing (VIGS) led to the identification of four enzymes and their supposed substrates. In vitro enzymatic assay and reconstitution in tobacco leaves elucidated a series of oxidative reactions of the gossypol biosynthesis pathway. The four functionally characterized enzymes, together with (+)-δ-cadinene synthase and the P450 involved in 7-hydroxy-(+)-δ-cadinene formation, convert farnesyl diphosphate (FPP) to hemigossypol, with two gaps left that each involves aromatization. Of six intermediates identified from the VIGS-treated leaves, 8-hydroxy-7-keto-δ-cadinene exerted a deleterious effect in dampening plant disease resistance if accumulated. Notably, CYP71BE79, the enzyme responsible for converting this phytotoxic intermediate, exhibited the highest catalytic activity among the five enzymes of the pathway assayed. In addition, despite their dispersed distribution in the cotton genome, all of the enzyme genes identified show a tight correlation of expression. Our data suggest that the enzymatic steps in the gossypol pathway are highly coordinated to ensure efficient substrate conversion. PMID:29784821

Temporal profiling of gene networks associated with the late phase of long-term potentiation in vivo.

PubMed

Ryan, Margaret M; Ryan, Brigid; Kyrke-Smith, Madeleine; Logan, Barbara; Tate, Warren P; Abraham, Wickliffe C; Williams, Joanna M

2012-01-01

Long-term potentiation (LTP) is widely accepted as a cellular mechanism underlying memory processes. It is well established that LTP persistence is strongly dependent on activation of constitutive and inducible transcription factors, but there is limited information regarding the downstream gene networks and controlling elements that coalesce to stabilise LTP. To identify these gene networks, we used Affymetrix RAT230.2 microarrays to detect genes regulated 5 h and 24 h (n = 5) after LTP induction at perforant path synapses in the dentate gyrus of awake adult rats. The functional relationships of the differentially expressed genes were examined using DAVID and Ingenuity Pathway Analysis, and compared with our previous data derived 20 min post-LTP induction in vivo. This analysis showed that LTP-related genes are predominantly upregulated at 5 h but that there is pronounced downregulation of gene expression at 24 h after LTP induction. Analysis of the structure of the networks and canonical pathways predicted a regulation of calcium dynamics via G-protein coupled receptors, dendritogenesis and neurogenesis at the 5 h time-point. By 24 h neurotrophin-NFKB driven pathways of neuronal growth were identified. The temporal shift in gene expression appears to be mediated by regulation of protein synthesis, ubiquitination and time-dependent regulation of specific microRNA and histone deacetylase expression. Together this programme of genomic responses, marked by both homeostatic and growth pathways, is likely to be critical for the consolidation of LTP in vivo.

Quantitative proteomic analysis of paired colorectal cancer and non-tumorigenic tissues reveals signature proteins and perturbed pathways involved in CRC progression and metastasis.

PubMed

Sethi, Manveen K; Thaysen-Andersen, Morten; Kim, Hoguen; Park, Cheol Keun; Baker, Mark S; Packer, Nicolle H; Paik, Young-Ki; Hancock, William S; Fanayan, Susan

2015-08-03

Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P<0.05, fold change>1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers. Copyright © 2015 Elsevier B.V. All rights reserved.

RNA sequencing and pathway analysis identify tumor necrosis factor alpha driven small proline-rich protein dysregulation in chronic rhinosinusitis.

PubMed

Ramakrishnan, Vijay R; Gonzalez, Joseph R; Cooper, Sarah E; Barham, Henry P; Anderson, Catherine B; Larson, Eric D; Cool, Carlyne D; Diller, John D; Jones, Kenneth; Kinnamon, Sue C

2017-09-01

Chronic rhinosinusitis (CRS) is a heterogeneous inflammatory disorder in which many pathways contribute to end-organ disease. Small proline-rich proteins (SPRR) are polypeptides that have recently been shown to contribute to epithelial biomechanical properties relevant in T-helper type 2 inflammation. There is evidence that genetic polymorphism in SPRR genes may predict the development of asthma in children with atopy and, correlatively, that expression of SPRRs is increased under allergic conditions, which leads to epithelial barrier dysfunction in atopic disease. RNAs from uncinate tissue specimens from patients with CRS and control subjects were compared by RNA sequencing by using Ingenuity Pathway Analysis (n = 4 each), and quantitative polymerase chain reaction (PCR) (n = 15). A separate cohort of archived sinus tissue was examined by immunohistochemistry (n = 19). A statistically significant increase of SPRR expression in CRS sinus tissue was identified that was not a result of atopic presence. SPRR1 and SPRR2A expressions were markedly increased in patients with CRS (p < 0.01) on RNA sequencing, with confirmation by using real-time PCR. Immunohistochemistry of archived surgical samples demonstrated staining of SPRR proteins within squamous epithelium of both groups. Pathway analysis indicated tumor necrosis factor (TNF) alpha as a master regulator of the SPRR gene products. Expression of SPRR1 and of SPRR2A is increased in mucosal samples from patients with CRS and appeared as a downstream result of TNF alpha modulation, which possibly resulted in epithelial barrier dysfunction.

Analysis of molecular pathways in pancreatic ductal adenocarcinomas with a bioinformatics approach.

PubMed

Wang, Yan; Li, Yan

2015-01-01

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death worldwide. Our study aimed to reveal molecular mechanisms. Microarray data of GSE15471 (including 39 matching pairs of pancreatic tumor tissues and patient-matched normal tissues) was downloaded from Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in PDAC tissues compared with normal tissues by limma package in R language. Then GO and KEGG pathway enrichment analyses were conducted with online DAVID. In addition, principal component analysis was performed and a protein-protein interaction network was constructed to study relationships between the DEGs through database STRING. A total of 532 DEGs were identified in the 38 PDAC tissues compared with 33 normal tissues. The results of principal component analysis of the top 20 DEGs could differentiate the PDAC tissues from normal tissues directly. In the PPI network, 8 of the 20 DEGs were all key genes of the collagen family. Additionally, FN1 (fibronectin 1) was also a hub node in the network. The genes of the collagen family as well as FN1 were significantly enriched in complement and coagulation cascades, ECM-receptor interaction and focal adhesion pathways. Our results suggest that genes of collagen family and FN1 may play an important role in PDAC progression. Meanwhile, these DEGs and enriched pathways, such as complement and coagulation cascades, ECM-receptor interaction and focal adhesion may be important molecular mechanisms involved in the development and progression of PDAC.

Transcriptional Profiling of Hypoxic Neural Stem Cells Identifies Calcineurin-NFATc4 Signaling as a Major Regulator of Neural Stem Cell Biology

PubMed Central

Moreno, Marta; Fernández, Virginia; Monllau, Josep M.; Borrell, Víctor; Lerin, Carles; de la Iglesia, Núria

2015-01-01

Summary Neural stem cells (NSCs) reside in a hypoxic microenvironment within the brain. However, the crucial transcription factors (TFs) that regulate NSC biology under physiologic hypoxia are poorly understood. Here we have performed gene set enrichment analysis (GSEA) of microarray datasets from hypoxic versus normoxic NSCs with the aim of identifying pathways and TFs that are activated under oxygen concentrations mimicking normal brain tissue microenvironment. Integration of TF target (TFT) and pathway enrichment analysis identified the calcium-regulated TF NFATc4 as a major candidate to regulate hypoxic NSC functions. Nfatc4 expression was coordinately upregulated by top hypoxia-activated TFs, while NFATc4 target genes were enriched in hypoxic NSCs. Loss-of-function analyses further revealed that the calcineurin-NFATc4 signaling axis acts as a major regulator of NSC self-renewal and proliferation in vitro and in vivo by promoting the expression of TFs, including Id2, that contribute to the maintenance of the NSC state. PMID:26235896

Metabolomic profiling and genomic analysis of wheat aneuploid lines to identify genes controlling biochemical pathways in mature grain.

PubMed

Francki, Michael G; Hayton, Sarah; Gummer, Joel P A; Rawlinson, Catherine; Trengove, Robert D

2016-02-01

Metabolomics is becoming an increasingly important tool in plant genomics to decipher the function of genes controlling biochemical pathways responsible for trait variation. Although theoretical models can integrate genes and metabolites for trait variation, biological networks require validation using appropriate experimental genetic systems. In this study, we applied an untargeted metabolite analysis to mature grain of wheat homoeologous group 3 ditelosomic lines, selected compounds that showed significant variation between wheat lines Chinese Spring and at least one ditelosomic line, tracked the genes encoding enzymes of their biochemical pathway using the wheat genome survey sequence and determined the genetic components underlying metabolite variation. A total of 412 analytes were resolved in the wheat grain metabolome, and principal component analysis indicated significant differences in metabolite profiles between Chinese Spring and each ditelosomic lines. The grain metabolome identified 55 compounds positively matched against a mass spectral library where the majority showed significant differences between Chinese Spring and at least one ditelosomic line. Trehalose and branched-chain amino acids were selected for detailed investigation, and it was expected that if genes encoding enzymes directly related to their biochemical pathways were located on homoeologous group 3 chromosomes, then corresponding ditelosomic lines would have a significant reduction in metabolites compared with Chinese Spring. Although a proportion showed a reduction, some lines showed significant increases in metabolites, indicating that genes directly and indirectly involved in biosynthetic pathways likely regulate the metabolome. Therefore, this study demonstrated that wheat aneuploid lines are suitable experimental genetic system to validate metabolomics-genomics networks. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Pathway-Based Analysis of Genome-Wide siRNA Screens Reveals the Regulatory Landscape of App Processing

PubMed Central

Camargo, Luiz Miguel; Zhang, Xiaohua Douglas; Loerch, Patrick; Caceres, Ramon Miguel; Marine, Shane D.; Uva, Paolo; Ferrer, Marc; de Rinaldis, Emanuele; Stone, David J.; Majercak, John; Ray, William J.; Yi-An, Chen; Shearman, Mark S.; Mizuguchi, Kenji

2015-01-01

The progressive aggregation of Amyloid-β (Aβ) in the brain is a major trait of Alzheimer's Disease (AD). Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP). Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPPα. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A) recently implicated with AD through genome wide association studies (GWAS) and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the “regulatory landscape” of APP. PMID:25723573

[Comparative analysis of methylation profiles in tissues of oral leukoplakia and oral squamous cell carcinoma].

PubMed

Fu, J; Su, Y; Liu, Y; Zhang, X Y

2018-04-09

Objective: To compare the methylation profiles in tissues of oral leukoplakia (OLK) and oral squamous cell carcinoma (OSCC) with healthy tissues of oral mucosa, in order to identify the role of DNA methylation played in tumorigenesis. Methods: DNA samples extracted from tissues of 4 healthy oral mucosa, 4 OSCC and 4 OLK collected from patients of the Department of Oral Medicine, Capital Medical University School of Stomatology were examined and compared using Methylation 450 Bead Chip. The genes associated with differentially methylated CpG sites were selected for gene ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment. Results: Multiple differentially methylated CpG sites were identified by using the above mentioned assay. Hypermethylation constitutes 86.18% (23 290/27 025) of methylation changes in OLK and hypomethylation accounts for 13.82% (3 734/27 025) of methylation changes. Both hypermethylated and hypomethylated CpG sites were markedly increased in OSCC tissue compared with OLK tissue. The majority of differentially methylated CpG sites were located outside CpG islands, with approximately one-fourth in CpG shores flanking the islands, which were considered highly important for gene regulation and tumorigenesis. Pathway analysis revealed that differentially methylated CpG sites in both OLK and OSCC patients shared the same pathway enrichments, most of which were correlated with carcinogenesis and cancer progression (e.g., DNA repair, cell cycle, and apoptosis). Conclusions: In the present study, methylation-associated alterations affect almost all pathways in the cellular network in both OLK and OSCC. OLK and OSCC shared similar methylation changes whether in pathways or genes, indicating that epigenetically they might have the same molecular basis for disease progression.

AURKA induces EMT by regulating histone modification through Wnt/β-catenin and PI3K/Akt signaling pathway in gastric cancer

PubMed Central

Liu, Xi; Li, Zhaoxia; Song, Yue; Wang, Rui; Han, Lei; Wang, Qixue; Jiang, Kui; Kang, Chunsheng; Zhang, Qingyu

2016-01-01

Gastric cancer, a highly invasive and aggressive malignancy, is the third leading cause of death from cancer worldwide. Genetic association studies have successfully revealed several important genes consistently associated with gastric cancer to date. However, these robust gastric cancer-associated genes do not fully elucidate the mechanisms underlying the development and progression of the disease. In the present study, we performed an alternative approach, a gene expression-based genome-wide association study (eGWAS) across 13 independent microarray experiments (including 251 gastric cancer cases and 428 controls), to identify top candidates (p<0.00001). Additionally, we conducted gene ontology analysis, pathway analysis and network analysis and identified aurora kinase A (AURKA) as our candidate. We observed that MLN8237, which is a specific inhibitor of AURKA, decreased the β-catenin and the phosphorylation of Akt1 and GSK-3β, as well as blocked the Akt and Wnt signaling pathways. Furthermore, MLN8237 arrested the cells in the G2/M phase. The activity of Wnt and Akt signaling pathways affected the level of histone methylation significantly, and we supposed that MLN8237 affected the level of histone methylation through these two signaling pathways. Additionally, the treatment of MLN8237 influenced the level of H3K4 me1/2/3 and H3K27 me1/2/3. Chip data on cell lines suggested that MLN8237 increases the level of H3K27 me3 on the promoter of Twist and inhibits EMT (epithelial-mesenchymal transition). In summary, AURKA is a potential therapeutic target in gastric cancer and induces EMT through histone methylation. PMID:27121204

Explore the Features of Brain-Derived Neurotrophic Factor in Mood Disorders

PubMed Central

Yeh, Fan-Chi; Kao, Chung-Feng; Kuo, Po-Hsiu

2015-01-01

Objectives Brain-derived neurotrophic factor (BDNF) plays important roles in neuronal survival and differentiation; however, the effects of BDNF on mood disorders remain unclear. We investigated BDNF from the perspective of various aspects of systems biology, including its molecular evolution, genomic studies, protein functions, and pathway analysis. Methods We conducted analyses examining sequences, multiple alignments, phylogenetic trees and positive selection across 12 species and several human populations. We summarized the results of previous genomic and functional studies of pro-BDNF and mature-BDNF (m-BDNF) found in a literature review. We identified proteins that interact with BDNF and performed pathway-based analysis using large genome-wide association (GWA) datasets obtained for mood disorders. Results BDNF is encoded by a highly conserved gene. The chordate BDNF genes exhibit an average of 75% identity with the human gene, while vertebrate orthologues are 85.9%-100% identical to human BDNF. No signs of recent positive selection were found. Associations between BDNF and mood disorders were not significant in most of the genomic studies (e.g., linkage, association, gene expression, GWA), while relationships between serum/plasma BDNF level and mood disorders were consistently reported. Pro-BDNF is important in the response to stress; the literature review suggests the necessity of studying both pro- and m-BDNF with regard to mood disorders. In addition to conventional pathway analysis, we further considered proteins that interact with BDNF (I-Genes) and identified several biological pathways involved with BDNF or I-Genes to be significantly associated with mood disorders. Conclusions Systematically examining the features and biological pathways of BDNF may provide opportunities to deepen our understanding of the mechanisms underlying mood disorders. PMID:26091093

Analysis of cancer-related lncRNAs using gene ontology and KEGG pathways.

PubMed

Chen, Lei; Zhang, Yu-Hang; Lu, Guohui; Huang, Tao; Cai, Yu-Dong

2017-02-01

Cancer is a disease that involves abnormal cell growth and can invade or metastasize to other tissues. It is known that several factors are related to its initiation, proliferation, and invasiveness. Recently, it has been reported that long non-coding RNAs (lncRNAs) can participate in specific functional pathways and further regulate the biological function of cancer cells. Studies on lncRNAs are therefore helpful for uncovering the underlying mechanisms of cancer biological processes. We investigated cancer-related lncRNAs using gene ontology (GO) terms and KEGG pathway enrichment scores of neighboring genes that are co-expressed with the lncRNAs by extracting important GO terms and KEGG pathways that can help us identify cancer-related lncRNAs. The enrichment theory of GO terms and KEGG pathways was adopted to encode each lncRNA. Then, feature selection methods were employed to analyze these features and obtain the key GO terms and KEGG pathways. The analysis indicated that the extracted GO terms and KEGG pathways are closely related to several cancer associated processes, such as hormone associated pathways, energy associated pathways, and ribosome associated pathways. And they can accurately predict cancer-related lncRNAs. This study provided novel insight of how lncRNAs may affect tumorigenesis and which pathways may play important roles during it. These results could help understanding the biological mechanisms of lncRNAs and treating cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

Differentiating Human Multipotent Mesenchymal Stromal Cells Regulate microRNAs: Prediction of microRNA Regulation by PDGF During Osteogenesis

PubMed Central

Goff, Loyal A.; Boucher, Shayne; Ricupero, Christopher L.; Fenstermacher, Sara; Swerdel, Mavis; Chase, Lucas; Adams, Christopher; Chesnut, Jonathan; Lakshmipathy, Uma; Hart, Ronald P.

2009-01-01

Objective Human multipotent mesenchymal stromal cells (MSC) have the potential to differentiate into multiple cell types, although little is known about factors that control their fate. Differentiation-specific microRNAs may play a key role in stem cell self renewal and differentiation. We propose that specific intracellular signalling pathways modulate gene expression during differentiation by regulating microRNA expression. Methods Illumina mRNA and NCode microRNA expression analyses were performed on MSC and their differentiated progeny. A combination of bioinformatic prediction and pathway inhibition was used to identify microRNAs associated with PDGF signalling. Results The pattern of microRNA expression in MSC is distinct from that in pluripotent stem cells such as human embryonic stem cells. Specific populations of microRNAs are regulated in MSC during differentiation targeted towards specific cell types. Complementary mRNA expression analysis increases the pool of markers characteristic of MSC or differentiated progeny. To identify microRNA expression patterns affected by signalling pathways, we examined the PDGF pathway found to be regulated during osteogenesis by microarray studies. A set of microRNAs bioinformatically predicted to respond to PDGF signalling was experimentally confirmed by direct PDGF inhibition. Conclusion Our results demonstrate that a subset of microRNAs regulated during osteogenic differentiation of MSCs is responsive to perturbation of the PDGF pathway. This approach not only identifies characteristic classes of differentiation-specific mRNAs and microRNAs, but begins to link regulated molecules with specific cellular pathways. PMID:18657893

Bioinformatics Analysis Reveals Distinct Molecular Characteristics of Hepatitis B-Related Hepatocellular Carcinomas from Very Early to Advanced Barcelona Clinic Liver Cancer Stages.

PubMed

Kong, Fan-Yun; Wei, Xiao; Zhou, Kai; Hu, Wei; Kou, Yan-Bo; You, Hong-Juan; Liu, Xiao-Mei; Zheng, Kui-Yang; Tang, Ren-Xian

2016-01-01

Hepatocellular carcinoma (HCC)is the fifth most common malignancy associated with high mortality. One of the risk factors for HCC is chronic hepatitis B virus (HBV) infection. The treatment strategy for the disease is dependent on the stage of HCC, and the Barcelona clinic liver cancer (BCLC) staging system is used in most HCC cases. However, the molecular characteristics of HBV-related HCC in different BCLC stages are still unknown. Using GSE14520 microarray data from HBV-related HCC cases with BCLC stages from 0 (very early stage) to C (advanced stage) in the gene expression omnibus (GEO) database, differentially expressed genes (DEGs), including common DEGs and unique DEGs in different BCLC stages, were identified. These DEGs were located on different chromosomes. The molecular functions and biology pathways of DEGs were identified by gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the interactome networks of DEGs were constructed using the NetVenn online tool. The results revealed that both common DEGs and stage-specific DEGs were associated with various molecular functions and were involved in special biological pathways. In addition, several hub genes were found in the interactome networks of DEGs. The identified DEGs and hub genes promote our understanding of the molecular mechanisms underlying the development of HBV-related HCC through the different BCLC stages, and might be used as staging biomarkers or molecular targets for the treatment of HCC with HBV infection.

Modelling and performance analysis of clinical pathways using the stochastic process algebra PEPA.

PubMed

Yang, Xian; Han, Rui; Guo, Yike; Bradley, Jeremy; Cox, Benita; Dickinson, Robert; Kitney, Richard

2012-01-01

Hospitals nowadays have to serve numerous patients with limited medical staff and equipment while maintaining healthcare quality. Clinical pathway informatics is regarded as an efficient way to solve a series of hospital challenges. To date, conventional research lacks a mathematical model to describe clinical pathways. Existing vague descriptions cannot fully capture the complexities accurately in clinical pathways and hinders the effective management and further optimization of clinical pathways. Given this motivation, this paper presents a clinical pathway management platform, the Imperial Clinical Pathway Analyzer (ICPA). By extending the stochastic model performance evaluation process algebra (PEPA), ICPA introduces a clinical-pathway-specific model: clinical pathway PEPA (CPP). ICPA can simulate stochastic behaviours of a clinical pathway by extracting information from public clinical databases and other related documents using CPP. Thus, the performance of this clinical pathway, including its throughput, resource utilisation and passage time can be quantitatively analysed. A typical clinical pathway on stroke extracted from a UK hospital is used to illustrate the effectiveness of ICPA. Three application scenarios are tested using ICPA: 1) redundant resources are identified and removed, thus the number of patients being served is maintained with less cost; 2) the patient passage time is estimated, providing the likelihood that patients can leave hospital within a specific period; 3) the maximum number of input patients are found, helping hospitals to decide whether they can serve more patients with the existing resource allocation. ICPA is an effective platform for clinical pathway management: 1) ICPA can describe a variety of components (state, activity, resource and constraints) in a clinical pathway, thus facilitating the proper understanding of complexities involved in it; 2) ICPA supports the performance analysis of clinical pathway, thereby assisting hospitals to effectively manage time and resources in clinical pathway.

Defining the Protein–Protein Interaction Network of the Human Hippo Pathway*

PubMed Central

Wang, Wenqi; Li, Xu; Huang, Jun; Feng, Lin; Dolinta, Keithlee G.; Chen, Junjie

2014-01-01

The Hippo pathway, which is conserved from Drosophila to mammals, has been recognized as a tumor suppressor signaling pathway governing cell proliferation and apoptosis, two key events involved in organ size control and tumorigenesis. Although several upstream regulators, the conserved kinase cascade and key downstream effectors including nuclear transcriptional factors have been defined, the global organization of this signaling pathway is not been fully understood. Thus, we conducted a proteomic analysis of human Hippo pathway, which revealed the involvement of an extensive protein–protein interaction network in this pathway. The mass spectrometry data were deposited to ProteomeXchange with identifier PXD000415. Our data suggest that 550 interactions within 343 unique protein components constitute the central protein–protein interaction landscape of human Hippo pathway. Our study provides a glimpse into the global organization of Hippo pathway, reveals previously unknown interactions within this pathway, and uncovers new potential components involved in the regulation of this pathway. Understanding these interactions will help us further dissect the Hippo signaling-pathway and extend our knowledge of organ size control. PMID:24126142

A Novel Method to Identify Differential Pathways in Hippocampus Alzheimer's Disease.

PubMed

Liu, Chun-Han; Liu, Lian

2017-05-08

BACKGROUND Alzheimer's disease (AD) is the most common type of dementia. The objective of this paper is to propose a novel method to identify differential pathways in hippocampus AD. MATERIAL AND METHODS We proposed a combined method by merging existed methods. Firstly, pathways were identified by four known methods (DAVID, the neaGUI package, the pathway-based co-expressed method, and the pathway network approach), and differential pathways were evaluated through setting weight thresholds. Subsequently, we combined all pathways by a rank-based algorithm and called the method the combined method. Finally, common differential pathways across two or more of five methods were selected. RESULTS Pathways obtained from different methods were also different. The combined method obtained 1639 pathways and 596 differential pathways, which included all pathways gained from the four existing methods; hence, the novel method solved the problem of inconsistent results. Besides, a total of 13 common pathways were identified, such as metabolism, immune system, and cell cycle. CONCLUSIONS We have proposed a novel method by combining four existing methods based on a rank product algorithm, and identified 13 significant differential pathways based on it. These differential pathways might provide insight into treatment and diagnosis of hippocampus AD.

Global iTRAQ-based proteomic profiling of Toxoplasma gondii oocysts during sporulation.

PubMed

Zhou, Chun-Xue; Zhu, Xing-Quan; Elsheikha, Hany M; He, Shuai; Li, Qian; Zhou, Dong-Hui; Suo, Xun

2016-10-04

Toxoplasma gondii is a medically and economically important protozoan parasite. However, the molecular mechanisms of its sporulation remain largely unknown. Here, we applied iTRAQ coupled with 2D LC-MS/MS proteomic analysis to investigate the proteomic expression profile of T. gondii oocysts during sporulation. Of the 2095 non-redundant proteins identified, 587 were identified as differentially expressed proteins (DEPs). Based on Gene Ontology enrichment and KEGG pathway analyses the majority of these DEPs were found related to the metabolism of amino acids, carbon and energy. Protein interaction network analysis generated by STRING identified ATP-citrate lyase (ACL), GMP synthase, IMP dehydrogenase (IMPDH), poly (ADP-ribose) glycohydrolase (PARG), and bifunctional dihydrofolate reductase-thymidylate synthase (DHFR-TS) as the top five hubs. We also identified 25 parasite virulence factors that were expressed at relatively high levels in sporulated oocysts compared to non-sporulated oocysts, which might contribute to the infectivity of mature oocysts. Considering the importance of oocysts in the dissemination of toxoplasmosis these findings may help in the search of protein targets with a key role in infectiousness and ecological success of oocysts, creating new opportunities for the development of better means for disease prevention. The development of new preventative interventions against T. gondii infection relies on an improved understanding of the proteome and chemical pathways of this parasite. To identify proteins required for the development of environmentally resistant and infective T. gondii oocysts, we compared the proteome of non-sporulated (immature) oocysts with the proteome of sporulated (mature, infective) oocysts. iTRAQ 2D-LC-MS/MS analysis revealed proteomic changes that distinguish non-sporulated from sporulated oocysts. Many of the differentially expressed proteins were involved in metabolic pathways and 25 virulence factors were identified upregulated in the sporulated oocysts. This work provides the first quantitative characterization of the proteomic variations that occur in T. gondii oocyst stage during sporulation. Copyright © 2016. Published by Elsevier B.V.

RNA-Seq Expression Analysis of Enteric Neuron Cells with Rotenone Treatment and Prediction of Regulated Pathways.

PubMed

Guan, Qiang; Wang, Xijin; Jiang, Yanyan; Zhao, Lijuan; Nie, Zhiyu; Jin, Lingjing

2017-02-01

The enteric nervous system (ENS) is involved in the initiation and development of the pathological process of Parkinson's disease (PD). The effect of rotenone on the ENS may trigger the progression of PD through the central nervous system (CNS). In this study, we used RNA-sequencing (RNA-seq) analysis to examine differential expression genes (DEGs) and pathways induced by in vitro treatment of rotenone in the enteric nervous cells isolated from rats. We identified 45 up-regulated and 30 down-regulated genes. The functional categorization revealed that the DEGs were involved in the regulation of cell differentiation and development, response to various stimuli, and regulation of neurogenesis. In addition, the pathway and network analysis showed that the Mitogen Activated Protein Kinase (MAPK), Toll-like receptor, Wnt, and Ras signaling pathways were intensively involved in the effect of rotenone on the ENS. Additionally, the quantitative real-time polymerase chain reaction result for the selected seven DEGs matched those of the RNA-seq analysis. Our results present a significant step in the identification of DEGs and provide new insight into the progression of PD in the rotenone-induced model.

Genome-Wide Analysis Reveals Novel Regulators of Growth in Drosophila melanogaster

PubMed Central

Vonesch, Sibylle Chantal; Lamparter, David; Mackay, Trudy F. C.; Bergmann, Sven; Hafen, Ernst

2016-01-01

Organismal size depends on the interplay between genetic and environmental factors. Genome-wide association (GWA) analyses in humans have implied many genes in the control of height but suffer from the inability to control the environment. Genetic analyses in Drosophila have identified conserved signaling pathways controlling size; however, how these pathways control phenotypic diversity is unclear. We performed GWA of size traits using the Drosophila Genetic Reference Panel of inbred, sequenced lines. We find that the top associated variants differ between traits and sexes; do not map to canonical growth pathway genes, but can be linked to these by epistasis analysis; and are enriched for genes and putative enhancers. Performing GWA on well-studied developmental traits under controlled conditions expands our understanding of developmental processes underlying phenotypic diversity. PMID:26751788

A multi-pathway hypothesis for human visual fear signaling

PubMed Central

Silverstein, David N.; Ingvar, Martin

2015-01-01

A hypothesis is proposed for five visual fear signaling pathways in humans, based on an analysis of anatomical connectivity from primate studies and human functional connectvity and tractography from brain imaging studies. Earlier work has identified possible subcortical and cortical fear pathways known as the “low road” and “high road,” which arrive at the amygdala independently. In addition to a subcortical pathway, we propose four cortical signaling pathways in humans along the visual ventral stream. All four of these traverse through the LGN to the visual cortex (VC) and branching off at the inferior temporal area, with one projection directly to the amygdala; another traversing the orbitofrontal cortex; and two others passing through the parietal and then prefrontal cortex, one excitatory pathway via the ventral-medial area and one regulatory pathway via the ventral-lateral area. These pathways have progressively longer propagation latencies and may have progressively evolved with brain development to take advantage of higher-level processing. Using the anatomical path lengths and latency estimates for each of these five pathways, predictions are made for the relative processing times at selective ROIs and arrival at the amygdala, based on the presentation of a fear-relevant visual stimulus. Partial verification of the temporal dynamics of this hypothesis might be accomplished using experimental MEG analysis. Possible experimental protocols are suggested. PMID:26379513