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Network Biology, 2017, 7(3): 57-75
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Article

Reconstruction, visualization and explorative analysis of human pluripotency network

Priyanka Narad1, Kailash C.Upadhyaya2, Anup Som3
1Amity Institute of Biotechnology, Amity University, Uttar Pradesh, India
2Amity Institute of Molecular Biology and Genomics, Amity University, Uttar Pradesh, India
3Centre of Bioinformatics, Institute of Interdisciplinary Studies, University of Allahabad, Allahabad, India

Received 8 May 2017;Accepted 15 June 2017;Published 1 September 2017
IAEES

Abstract
Identification of genes/proteins involved in pluripotency and their inter-relationships is important for understanding the induction/loss and maintenance of pluripotency. With the availability of large volume of data on interaction/regulation of pluripotency scattered across a large number of biological databases and hundreds of scientific journals, it is required a systematic integration of data which will create a complete view of pluripotency network. Describing and interpreting such a network of interaction and regulation (i.e., stimulation and inhibition) links are essential tasks of computational biology, an important first step in systems-level understanding of the underlying mechanisms of pluripotency. To address this, we have assembled a network of 166 molecular interactions, stimulations and inhibitions, based on a collection of research data from 147 publications, involving 122 human genes/proteins, all in a standard electronic format, enabling analyses by readily available software such as Cytoscape and its Apps (formerly called "Plugins"). The network includes the core circuit of OCT4 (POU5F1), SOX2 and NANOG, its periphery (such as STAT3, KLF4, UTF1, ZIC3, and c-MYC), connections to upstream signaling pathways (such as ACTIVIN, WNT, FGF, and BMP), and epigenetic regulators (such as L1TD1, LSD1 and PRC2). We describe the general properties of the network and compare it with other literature-based networks. Gene Ontology (GO) analysis is being performed to find out the over-represented GO terms in the network. We use several expression datasets to condense the network to a set of network links that identify the key players (genes/proteins) and the pathways involved in transition from one state of pluripotency to other state (i.e., native to primed state, primed to non-pluripotent state and pluripotent to non-pluripotent state).

Keywords human pluripotency network;network layout;network measures;gene enrichment analysis;gene expression data;embryonic stem cell;naive and primed states.


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