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Feng, Yaping,Syrkin-Nikolau, Judith A.,Wurtele, Eve S. Korean Society for Bioinformatics 2013 Interdisciplinary Bio Central (IBC) Vol.5 No.1
High quality publicly-available transcriptomic data representing relationships in gene expression across a diverse set of biological conditions is used as a context network to explore transcriptomics of the CNS. The context network, 18367Hu-matrix, contains pairwise Pearson correlations for 22,215 human genes across18,637 human tissue samples1. To do this, we compute a network derived from biological samples from CNS cells and tissues, calculate clusters of co-expressed genes from this network, and compare the significance of these to clusters derived from the larger 18367Hu-matrix network. Sorting and visualization uses the publicly available software, MetaOmGraph (http://www.metnetdb.org/MetNet_MetaOm-Graph.htm). This identifies genes that characterize particular disease conditions. Specifically, differences in gene expression within and between two designations of glial cancer, astrocytoma and glioblastoma, are evaluated in the context of the broader network. Such gene groups, which we term outlier-networks, tease out abnormally expressed genes and the samples in which this expression occurs. This approach distinguishes 48 subnetworks of outlier genes associated with astrocytoma and glioblastoma. As a case study, we investigate the relationships among the genes of a small astrocytoma-only subnetwork. This astrocytoma-only subnetwork consists of SVEP1, IGF1, CHRNA3, and SPAG6. All of these genes are highly coexpressed in a single sample of anaplastic astrocytoma tumor (grade III) and a sample of juvenile pilocytic astrocytoma. Three of these genes are also associated with nicotine. This data lead us to formulate a testable hypothesis that this astrocytoma outlier-network provides a link between some gliomas/astrocytomas and nicotine.
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김상곤,배환희,이진석,손범영,백성범,BasilJ.Nikolau,김정태 한국국제농업개발학회 2017 韓國國際農業開發學會誌 Vol.29 No.2
Teosinte, commonly known as wild species of corn, has distributed in Central and South America. It is believed that teosinte contains genes for resistance to flooding because of the climate characteristics of the collected countries. Recent studies have shown that teosinte has the ability to form adventitious roots, to develop aerenchyma tissues of teosinte, and the resistance to toxic substances under flooding soil condition. Therefore, development of corn varieties to cope with climate change and the growing corn at paddy field in Korea are required to introduce the characteristics of teosinte. However, in order to utilize teosinte resources, preconditions must be settled such as photoperiodic responsibility, physiological and ecological characteristics. Also if the preconditions are studied together with the metabolic level studies, the possibility of utilization for flooding resistant varieties will be even higher.
Kim, Taehyong,Dreher, Kate,Nilo-Poyanco, Ricardo,Lee, Insuk,Fiehn, Oliver,Lange, Bernd Markus,Nikolau, Basil J.,Sumner, Lloyd,Welti, Ruth,Wurtele, Eve S.,Rhee, Seung Y. American Society of Plant Biologists 2015 Plant Physiology Vol.167 No.4
<P><I>Global patterns of metabolic responses upon single gene perturbations are specific to gene functions, but they are coordinated with characteristics of the perturbed genes.</I></P><P>Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (<I>Arabidopsis thaliana</I>) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes.</P>