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Identifcation of Immunity-related Genes in Arabidopsis and Cassava Using Genomic Data

Genomics, Proteomics & Bioinformatics 2013年第6期11卷 345-353页

作者： Luis Guillermo Leal A'lvaro Perez Andre's Quintero A'ngela Bayona Juan Felipe Ortiz anju gangadharan David Mackey Camilo Lo'pez Liliana Lo'pez-Kleine Department of Statistics Universidad Nacional de Colombia Department of Biology Universidad Nacional de Colombia Department of Molecular Genetics The Ohio State University

Recent advances in genomic and post-genomic technologies have provided the opportu- nity to generate a previously unimaginable amount of information. However, biological knowledge is still needed to improve the understanding of complex mechanisms such as plant immune responses. Better knowledge of this process could improve crop production and management. Here, we used holistic analysis to combine our own microarray and RNA-seq data with public genomic data from Arabidopsis and cassava in order to acquire biological knowledge about the relationships between proteins encoded by immunity-related genes （IRGs） and other genes. This approach was based on a kernel method adapted for the construction of gene networks. The obtained results allowed us to propose a list of new IRGs. A putative function in the immunity pathway was predicted for the new IRGs. The analysis of networks revealed that our predicted IRGs are either well documented or recognized in previous co-expression studies. In addition to robust relationships between IRGs, there is evidence suggesting that other cellular processes may be also strongly related to immunity.

关键词： Arabidopsis Cassava Functional gene prediction Genomic data Kernel canonical correlation ajalysi Plant immunity

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