RiceNet v2: an improved network prioritization server for rice genes.
Bottom Line: We previously published a genome-scale functional network server called RiceNet, constructed by integrating diverse genomics data and demonstrated the use of the network in genetic dissection of rice biotic stress responses and its usefulness for other grass species.Since the initial construction of the network, there has been a significant increase in the amount of publicly available rice genomics data.We demonstrate that RiceNet v2 effectively identifies candidate genes involved in rice root/shoot development and defense responses, demonstrating its usefulness for the grass research community.
Affiliation: Department of Biotechnology, College of Life Sciences and Biotechnology, Yonsei University, Seoul, Korea.Show MeSH
Mentions: As described above, rice genes annotated with experimental evidences are scarce. For example, as of January 2015, there are only eight rice genes annotated for root development by Gramene GO-BP with a GO evidence code of IMP (inferred from mutant phenotype), while 60 Arabidopsis genes are annotated for root development with IMP. Similarly, only one rice gene is annotated, but 19 Arabidopsis genes are annotated for shoot system development by GO-BP with IMP. Therefore, it is a useful strategy to prioritize novel rice genes for root or shoot development using Arabidopsis orthologs for the equivalent traits. The likelihood of the new candidates could be validated by tissue-specific expression data. This approach assumes that genes for root development are expressed more actively in root cells and that genes for shoot development are more actively expressed in shoots. To test this approach we submitted 60 Arabidopsis genes demonstrated to control root development to the RiceNet v2 server, which returned 6012 new candidate rice genes for the phenotype. For validation, we employed a transcriptome atlas of rice cell types (25) (GEO accession: GSE13161), which provides expression profiles for 40 distinct cell types from rice shoot, root and germinating seed at several developmental stages. We compared expression levels of the top 100 candidates and 100 random genes, and observed significantly higher expression levels of top candidates from root cells (P = 1.3 × 10-12, Wilcoxon rank sum test) (Figure 3, left). We performed a similar analysis for shoot system development using the 19 Arabidopsis genes known to be involved in shoot system development as guide genes. RiceNet v2 server returned 2680 new rice candidate genes for the shoot system development. From comparison of expression levels between top 100 candidates and 100 random genes, we observed that top candidates show significantly higher expression levels than random ones in shoot cells (P = 7.2 × 10-4, Wilcoxon rank sum test) (Figure 3, right).
Affiliation: Department of Biotechnology, College of Life Sciences and Biotechnology, Yonsei University, Seoul, Korea.