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RiceNet v2: an improved network prioritization server for rice genes.

Lee T, Oh T, Yang S, Shin J, Hwang S, Kim CY, Kim H, Shim H, Shim JE, Ronald PC, Lee I - Nucleic Acids Res. (2015)

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.

View Article: PubMed Central - PubMed

Affiliation: Department of Biotechnology, College of Life Sciences and Biotechnology, Yonsei University, Seoul, Korea.

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Validation of new candidate rice genes for root or shoot development based on network direct neighborhood method. Due to the lack of known rice genes for the traits, 60 and 19 Arabidopsis genes known for root and shoot development were submitted as guide genes, respectively. We validated new candidate genes using tissue specific expression atlas data, assuming genes for root development more actively express in root and genes for shoot development more actively express in shoot. We observed that top 100 candidate genes by RiceNet v2 show significantly higher expression levels than random genes in both target tissues: P = 1.3 × 10-12 (Wilcoxon rank sum test) for expression of root development gene candidates in root cells (left two box plots) and P = 7.2 × 10-4 (Wilcoxon rank sum test) for expression of shoot development gene candidates in shoot cells (right two box plots).
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Figure 3: Validation of new candidate rice genes for root or shoot development based on network direct neighborhood method. Due to the lack of known rice genes for the traits, 60 and 19 Arabidopsis genes known for root and shoot development were submitted as guide genes, respectively. We validated new candidate genes using tissue specific expression atlas data, assuming genes for root development more actively express in root and genes for shoot development more actively express in shoot. We observed that top 100 candidate genes by RiceNet v2 show significantly higher expression levels than random genes in both target tissues: P = 1.3 × 10-12 (Wilcoxon rank sum test) for expression of root development gene candidates in root cells (left two box plots) and P = 7.2 × 10-4 (Wilcoxon rank sum test) for expression of shoot development gene candidates in shoot cells (right two box plots).

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).


RiceNet v2: an improved network prioritization server for rice genes.

Lee T, Oh T, Yang S, Shin J, Hwang S, Kim CY, Kim H, Shim H, Shim JE, Ronald PC, Lee I - Nucleic Acids Res. (2015)

Validation of new candidate rice genes for root or shoot development based on network direct neighborhood method. Due to the lack of known rice genes for the traits, 60 and 19 Arabidopsis genes known for root and shoot development were submitted as guide genes, respectively. We validated new candidate genes using tissue specific expression atlas data, assuming genes for root development more actively express in root and genes for shoot development more actively express in shoot. We observed that top 100 candidate genes by RiceNet v2 show significantly higher expression levels than random genes in both target tissues: P = 1.3 × 10-12 (Wilcoxon rank sum test) for expression of root development gene candidates in root cells (left two box plots) and P = 7.2 × 10-4 (Wilcoxon rank sum test) for expression of shoot development gene candidates in shoot cells (right two box plots).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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Figure 3: Validation of new candidate rice genes for root or shoot development based on network direct neighborhood method. Due to the lack of known rice genes for the traits, 60 and 19 Arabidopsis genes known for root and shoot development were submitted as guide genes, respectively. We validated new candidate genes using tissue specific expression atlas data, assuming genes for root development more actively express in root and genes for shoot development more actively express in shoot. We observed that top 100 candidate genes by RiceNet v2 show significantly higher expression levels than random genes in both target tissues: P = 1.3 × 10-12 (Wilcoxon rank sum test) for expression of root development gene candidates in root cells (left two box plots) and P = 7.2 × 10-4 (Wilcoxon rank sum test) for expression of shoot development gene candidates in shoot cells (right two box plots).
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).

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.

View Article: PubMed Central - PubMed

Affiliation: Department of Biotechnology, College of Life Sciences and Biotechnology, Yonsei University, Seoul, Korea.

Show MeSH