BarleyNet: A Network-Based Functional Omics Analysis Server for Cultivated Barley, Hordeum vulgare L

Cultivated barley ( L.) is one of the most produced cereal crops worldwide after maize, bread wheat, and rice. Barley is an important crop species not only as a food source, but also in plant genetics because it harbors numerous stress response alleles in its genome that can be exploited for crop en...

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Published in:Frontiers in plant science Vol. 11; p. 98
Main Authors: Lee, Sungho, Lee, Tak, Yang, Sunmo, Lee, Insuk
Format: Journal Article
Language:English
Published: Switzerland Frontiers Media S.A 18-02-2020
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Summary:Cultivated barley ( L.) is one of the most produced cereal crops worldwide after maize, bread wheat, and rice. Barley is an important crop species not only as a food source, but also in plant genetics because it harbors numerous stress response alleles in its genome that can be exploited for crop engineering. However, the functional annotation of its genome is relatively poor compared with other major crops. Moreover, bioinformatics tools for system-wide analyses of omics data from barley are not yet available. We have thus developed BarleyNet, a co-functional network of 26,145 barley genes, along with a web server for network-based predictions (http://www.inetbio.org/barleynet). We demonstrated that BarleyNet's prediction of biological processes is more accurate than that of an existing barley gene network. We implemented three complementary network-based algorithms for prioritizing genes or functional concepts to study genetic components of complex traits such as environmental stress responses: (i) a pathway-centric search for candidate genes of pathways or complex traits; (ii) a gene-centric search to infer novel functional concepts for genes; and (iii) a context-centric search for novel genes associated with stress response. We demonstrated the usefulness of these network analysis tools in the study of stress response using proteomics and transcriptomics data from barley leaves and roots upon drought or heat stresses. These results suggest that BarleyNet will facilitate our understanding of the underlying genetic components of complex traits in barley.
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This article was submitted to Bioinformatics and Computational Biology, a section of the journal Frontiers in Plant Science
Edited by: Xiyin Wang, North China University of Science and Technology, China
These authors have contributed equally to this work
Reviewed by: Le Shu, University of California, Los Angeles, United States; Margaret Woodhouse, Iowa State University, United States; Nils Stein, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Germany
Present address: Tak Lee, Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
ISSN:1664-462X
1664-462X
DOI:10.3389/fpls.2020.00098