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SFGD: a comprehensive platform for mining functional information from soybean transcriptome data and its use in identifying acyl-lipid metabolism pathways

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BMC GENOMICS 2014年第1期15卷 271-271页

作者： Yu, Juan Zhang, Zhenhai Wei, Jiangang Ling, Yi Xu, Wenying Su, Zhen China Agr Univ State Key Lab Plant Physiol & Biochem Coll Biol Sci Beijing 100193 Peoples R China

Background: Soybean (Glycine max L.) is one of the world's most important leguminous crops producing high-quality protein and oil. Increasing the relative oil concentration in soybean seeds is many researchers' goal, but a complete analysis platform of functional annotation for the genes involved in the soybean acyl-lipid pathway is still lacking. Following the success of soybean whole-genome sequencing, functional annotation has become a major challenge for the scientific community. Whole-genome transcriptome analysis is a powerful way to predict genes with biological functions. It is essential to build a comprehensive analysis platform for integrating soybean whole-genome sequencing data, the available transcriptome data and protein information. This platform could also be used to identify acyl-lipid metabolism pathways. Description: In this study, we describe our construction of the Soybean Functional Genomics database (SFGD) using Generic Genome Browser (Gbrowse) as the core platform. We integrated microarray expression profiling with 255 samples from 14 groups' experiments and mRNA-seq data with 30 samples from four groups' experiments, including spatial and temporal transcriptome data for different soybean development stages and environmental stresses. The SFGD includes a gene co-expression regulatory network containing 23,267 genes and 1873 miRNA-target pairs, and a group of acyl-lipid pathways containing 221 enzymes and more than 1550 genes. The SFGD also provides some key analysis tools, i. e. BLAST search, expression pattern search and cis-element significance analysis, as well as gene ontology information search and single nucleotide polymorphism display. Conclusion: The SFGD is a comprehensive database integrating genome and transcriptome data, and also for soybean acyl-lipid metabolism pathways. It provides useful toolboxes for biologists to improve the accuracy and robustness of soybean functional genomics analysis, further improving understanding of g

关键词： microarray expression data Deep Sequencing data microarray expression Experiment Plant Metabolic Network Generic Genome Browser

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Reconstruction of metabolic network in the bovine mammary gland tissue

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MOLECULAR BIOLOGY REPORTS 2012年第7期39卷 7311-7318页

作者： Wang, Changfa Wang, Ji Ju, Zhihua Zhai, Ruiyan Zhou, Lei Li, Qiuling Li, Jianbin Li, Rongling Huang, Jinming Zhong, Jifeng Shandong Acad Agr Sci Dairy Cattle Res Ctr Jinan 250100 Shandong Peoples R China

Understanding bovine metabolism and its relationship with milk products is important in cow breeding. In the present work, the metabolic network in the mammary gland tissue of cattle was reconstructed with the available bovine genome information using several public datasets from NCBI, Uniprot, and KEGG. The network consisted of 1,743 metabolites named by KEGG compound numbers as nodes and 657 enzymes that catalyzed the corresponding reactions as edges. The characteristics of the network were analyzed. The top 20 hub metabolites were determined, and the mean path length was identified to be 6.52. Moreover, 11 key enzymes with significant changes in expression under the condition of mastitis were identified and analyzed by integrating the microarray expression data of normal and clinical mastitis. Aside from the GATM gene, 10 downregulated enzymes were detected in bovine with mastitis. In addition, many of the identified enzymes were involved in amino acid metabolisms or had a direct connection to amino acid metabolisms. These results indicate that mastitis could affect the expression of enzymes, which is vital in some amino acid metabolisms, resulting in the reduction of milk proteins. The present work provides information that may improve the understanding on bovine milk production and mastitis.

关键词： Bovine Mammary gland Metabolic network microarray expression data Mastitis

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An update on the ABCC transporter family in plants: many genes, many proteins, but how many functions?

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PLANT BIOLOGY 2010年第Sup1期12卷 15-25页

作者： Wanke, D. Kolukisaoglu, H. Uener Univ Rostock CELISCA Ctr Life Sci Automat D-18119 Rostock Germany Univ Tubingen Ctr Plant Mol Biol ZMBP Tubingen Germany

The ABCC subfamily of the ATP binding cassette (ABC) transporters, which were formerly known as multidrug resistance-related proteins (MRPs), consists of closely related members found in all eukaryotic organisms. Although more than a decade of intensive research has elapsed since the first MRP protein was functionally characterised in Arabidopsis thaliana, knowledge of this particular transporter family is still limited in plants. Although ABCC proteins were originally defined as vacuolar pumps of glutathione-S (GS) conjugates, evidence, as well as speculation, on their endogenous functions inside the cell ranges from detoxification and heavy metal sequestration, to chlorophyll catabolite transport and ion channel regulation. The characterisation of knockout mutants in Arabidopsis has been pivotal for elucidation of different roles of ABCC transporters. However, a functional annotation for the majority of these transport proteins is still lacking, even in this model plant. On the one hand, this problem seems to be caused by functional redundancy between family members, which might lead to physiological complementation by a highly homologous gene in the mutant lines. On the other hand, there is growing evidence that the functional diversity of ABCC genes in Arabidopsis and other plants is far greater than previously assumed. For example, analysis of microarray expression data supports involvement of ABCC transporters in the response to biotic stress: particular changes in ABCC transcript levels are found, which are pathogen-specific and evoke distinct signalling cascades. Current knowledge about plant ABCC transporters indicates that novel and unexpected functions and substrates of these proteins are still waiting to be elucidated.

关键词： Arabidopsis knockout mutants microarray expression data signalling cascades

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Array2BIO: from microarray expression data to functional annotation of co-regulated genes

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BMC BIOINFORMATICS 2006年第1期7卷 307-307页

作者： Loots, Gabriela G. Chain, Patrick S. G. Mabery, Shalini Rasley, Amy Garcia, Emilio Ovcharenko, Ivan Lawrence Livermore Natl Lab Biosci Directorate Livermore CA 94550 USA Lawrence Livermore Natl Lab Computat Directorate Livermore CA 94550 USA Dept Energy Joint Genome Inst Walnut Creek CA 94598 USA

Background: There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. Results: Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1) comparative analysis of signal versus control and ( 2) clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Creme allows prediction of gene regulatory elements that underlie observed expression patterns. Conclusion: We have developed Array2BIO-a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to *** comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available at http://***.

关键词： Gene Ontology Transcription Factor Binding Site microarray expression data Human Dendritic Cell Yersinia Pestis

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A-MADMAN: Annotation-based microarray data meta-analysis tool

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BMC BIOINFORMATICS 2009年第1期10卷 1-11页

作者： Bisognin, Andrea Coppe, Alessandro Ferrari, Francesco Risso, Davide Romualdi, Chiara Bicciato, Silvio Bortoluzzi, Stefania Univ Padua Dept Biol I-35121 Padua Italy Univ Padua Dept Stat Sci I-35121 Padua Italy Univ Modena & Reggio Emilia Dept Biomed Sci I-41100 Modena Italy

Background: Publicly available datasets of microarray gene expression signals represent an unprecedented opportunity for extracting genomic relevant information and validating biological hypotheses. However, the exploitation of this exceptionally rich mine of information is still hampered by the lack of appropriate computational tools, able to overcome the critical issues raised by meta-analysis. Results: This work presents A-MADMAN, an open source web application which allows the retrieval, annotation, organization and meta-analysis of gene expression datasets obtained from Gene expression Omnibus. A-MADMAN addresses and resolves several open issues in the meta-analysis of gene expression data. Conclusion: A-MADMAN allows i) the batch retrieval from Gene expression Omnibus and the local organization of raw data files and of any related meta-information, ii) the re-annotation of samples to fix incomplete, or otherwise inadequate, metadata and to create user-defined batches of data, iii) the integrative analysis of data obtained from different Affymetrix platforms through custom chip definition files and meta-normalization. Software and documentation are available online at http://***/bioinfo/amadman/.

关键词： Gene expression Omnibus Gene expression dataset microarray expression data Affymetrix Array Platform Integration

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TRUNCATULIX - a data warehouse for the legume community

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BMC PLANT BIOLOGY 2009年第1期9卷 19-19页

作者： Henckel, Kolja Runte, Kai J. Bekel, Thomas Dondrup, Michael Jakobi, Tobias Kuester, Helge Goesmann, Alexander Univ Bielefeld Ctr Biotechnol Inst Genome Res & Syst Biol Bielefeld Germany Univ Bielefeld Int Grad Sch Bioinformat & Genome Res Bielefeld Germany Univ Bielefeld Tech Fac Bielefeld Germany Univ Bielefeld Fac Biol & Genet Bielefeld Germany Leibniz Univ Hannover Inst Plant Genet Unit Plant Genom 4 D-30167 Hannover Germany

Background: databases for either sequence, annotation, or microarray experiments data are extremely beneficial to the research community, as they centrally gather information from experiments performed by different scientists. However, data from different sources develop their full capacities only when combined. The idea of a data warehouse directly adresses this problem and solves it by integrating all required data into one single database - hence there are already many data warehouses available to genetics. For the model legume Medicago truncatula, there is currently no such single data warehouse that integrates all freely available gene sequences, the corresponding gene expression data, and annotation information. Thus, we created the data warehouse TRUNCATULIX, an integrative database of Medicago truncatula sequence and expression data. Results: The TRUNCATULIX data warehouse integrates five public databases for gene sequences, and gene annotations, as well as a database for microarray expression data covering raw data, normalized datasets, and complete expression profiling experiments. It can be accessed via an AJAX- based web interface using a standard web browser. For the first time, users can now quickly search for specific genes and gene expression data in a huge database based on high-quality annotations. The results can be exported as Excel, HTML, or as csv files for further usage. Conclusion: The integration of sequence, annotation, and gene expression data from several Medicago truncatula databases in TRUNCATULIX provides the legume community with access to data and data mining capability not previously available. TRUNCATULIX is freely available at http://***/truncatulix/.

关键词： Arbuscular Mycorrhiza data Warehouse Affymetrix GeneChip microarray expression data Medicago Truncatula

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Pathway analysis tools and toxicogenomics reference databases for risk assessment

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PHARMACOGENOMICS 2008年第1期9卷 35-54页

作者： Ganter, Brigitte Zidek, Nadine Hewitt, Philip R. Mueller, Dieter Vladimirova, Antoaneta Ingenu Syst Redwood City CA 94063 USA Merck KGaA D-64293 Darmstadt Germany Univ Jena Inst Pharmacol & Toxicol D-07743 Jena Germany Entelos Inc Foster City CA 94404 USA

The pharmaceutical industry has begun to leverage a range of new technologies (proteomics, pharmacogenomics, metabolomics and molecular toxicology [e.g., toxicogenomics]) and analysis tools that are becoming increasingly integrated in the area of drug discovery and development. The approach of analyzing the vast amount of toxicogenomics data generated using molecular pathway and networks analysis tools in combination with analysis of reference data will be the main focus of this review. We will demonstrate how this combined approach can increase the understanding of the molecular mechanisms that lead to chemical-induced toxicity and application of this knowledge to compound risk assessment. We will provide an example of the insights achieved through a molecular toxicology analysis based on the well-known hepatotoxicant lipopolysaccharide to illustrate the utility of these new tools in the analysis of complex data sets, both in vivo and in vitro. The ultimate objective is a better lead selection process that improves the chances for success across the different stages of drug discovery and development.

关键词： drug discovery and development lipopolysacharide mechanism of action mechanism of toxicity microarray expression data molecular toxicoiogy pathways analysis proteomics toxicogenomics

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A systems biology analysis of protein-protein interactions in the APOBEC family

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LIFE SCIENCES 2008年第15-16期83卷 521-530页

作者： Wang, Yi Chen, Guoping Yang, Yuxin Hu, Zongli Chen, Xuqing Chongqing Univ Coll Bioengn Chongqing 400044 Peoples R China Beijing Res Ctr Agro Biotechnol Beijing 100089 Peoples R China

Aims: The APOBEC (apolipoprotein B mRNA-editing catalytic polypeptide) family of cytidine deaminases inhibits the mobility of diverse retroviruses, retrotransposons and other viruses. This group of apolipoproteins is widely distributed in living organisms and plays a central role in diverse enzymatic pathways. Nevertheless, the interplay between APOBECs in protecting the host cell from viral infection are poorly understood. To elucidate the association between human APOBECs and immune system, a systems biology study was performed to identify various proteins involved in the function of APOBEC proteins. Main methods: This identification utilized an integrated database and literature network of protein-protein interactions combined with nine microarray experiments. Key findings: Considering our systems biology data, we can infer some modes of action of APOBECs through interactions with proteins associated with the immune system. Significance: This study presents a comprehensive analysis of the APOBEC network, highlighting those proteins that have a higher probability of playing an important role with APOBECs in the innate immune system. (C) 2008 Elsevier Inc. All rights reserved.

关键词： APOBECs Innate immune System biology Protein-protein network Literature data mining microarray expression data Virus infection

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T2D-Db: An integrated platform to study the molecular basis of Type 2 diabetes

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BMC GENOMICS 2008年第1期9卷 320-320页

作者： Agrawal, Shipra Dimitrova, Nevenka Nathan, Prasanthi Udayakumar, K. Lakshmi, S. Sai Sriram, S. Manjusha, N. Sengupta, Urmi Inst Bioinformat & Appl Biotechnol Bangalore Karnataka India Philips Res Asia Bangalore Karnataka India

Background: Type 2 Diabetes Mellitus (T2DM) is a non insulin dependent, complex trait disease that develops due to genetic predisposition and environmental factors. The advanced stage in type 2 diabetes mellitus leads to several micro and macro vascular complications like nephropathy, neuropathy, retinopathy, heart related problems etc. Studies performed on the genetics, biochemistry and molecular biology of this disease to understand the pathophysiology of type 2 diabetes mellitus has led to the generation of a surfeit of data on candidate genes and related aspects. The research is highly progressive towards defining the exact etiology of this disease. Results: T2D-Db (Type 2 diabetes database) is a comprehensive web resource, which provides integrated and curated information on almost all known molecular components involved in the pathogenesis of type 2 diabetes mellitus in the three widely studied mammals namely human, mouse and rat. Information on candidate genes, SNPs (Single Nucleotide Polymorphism) in candidate genes or candidate regions, genome wide association studies (GWA), tissue specific gene expression patterns, EST (Expressed Sequence Tag) data, expression information from microarray data, pathways, protein-protein interactions and disease associated risk factors or complications have been structured in this on line resource. Conclusion: Information available in T2D-Db provides an integrated platform for the better molecular level understanding of type 2 diabetes mellitus and its pathogenesis. Importantly, the resource facilitates graphical presentation of the gene/genome wide map of SNP markers and protein-protein interaction networks, besides providing the heat map diagram of the selected gene(s) in an organism across microarray expression experiments from either single or multiple studies. These features aid to the data interpretation in an integrative way. T2D-Db is to our knowledge the first publicly available resource that can cater to the needs

关键词： Candidate Gene microarray expression data Search Option External Link Entrez Gene database

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Genomic characterization of multiple clinical phenotypes of cancer using multivariate linear regression models

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BIOINFORMATICS 2007年第6期23卷 732-738页

作者： Matsui, Shigeyuki Ito, Masaaki Nishiyama, Hiroyuki Uno, Hajime Kotani, Hirokazu Watanabe, Jun Guilford, Parry Reeve, Anthony Fukushima, Masanori Ogawa, Osamu Kyoto Univ Dept Pham Epidemiol Grad Sch Publ Hlth Kyoto Japan Fdn Biomed Res & Innovat Translat Res Informat Ctr Kobe Hyogo Japan Kyoto Univ Grad Sch Med Dept Urol Kyoto Japan Kitasato Univ Sch Pharmaceut Sci Div Biostat Kyoto Japan Kyoto Univ Grad Sch Med Dept Pathol Kyoto Japan Univ Otago Canc Genet Lab Dept Biochem Dunedin New Zealand Kyoto Univ Hosp Translat Res Ctr Div Clin Trial Design & Management Kyoto 606 Japan

Motivation: The development of gene expression microarray technology has allowed the identification of differentially expressed genes between different clinical phenotypic classes of cancer from a large pool of candidate genes. Although many class comparisons concerned only a single phenotype, simultaneous assessment of the relationship between gene expression and multiple phenotypes would be warranted to better understand the underlying biological structure. Results: We develop a method to select genes related to multiple clinical phenotypes based on a set of multivariate linear regression models. For each gene, we perform model selection based on the doubly-adjusted R-square statistic and use the maximum of this statistic for gene selection. The method can substantially improve the power in gene selection, compared with a conventional method that uses a single model exclusively for gene selection. Application to a bladder cancer study to correlate pre-treatment gene expressions with pathological stage and grade is given. The methods would be useful for screening for genes related to multiple clinical phenotypes.

关键词： microarray expression data GENE-expression DISCOVERY BLADDER VARIANCE

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