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Systematic prediction of gene function in Arabidopsis thaliana using a probabilistic functional gene network

Abstract

AraNet is a functional gene network for the reference plant Arabidopsis and has been constructed in order to identify new genes associated with plant traits. It is highly predictive for diverse biological pathways and can be used to prioritize genes for functional screens. Moreover, AraNet provides a web-based tool with which plant biologists can efficiently discover novel functions of Arabidopsis genes (http://www.functionalnet.org/aranet/). This protocol explains how to conduct network-based prediction of gene functions using AraNet and how to interpret the prediction results. Functional discovery in plant biology is facilitated by combining candidate prioritization by AraNet with focused experimental tests.

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Figure 1: Overview of the method of using AraNet to discover gene function.
Figure 2: A report from a 'Find new members of a pathway' search showing an analysis of query genes (e.
Figure 3: An example of ROC analysis of predictive power of query genes for the 'Find new members of a pathway' search in AraNet.
Figure 4: An example list of candidate pathway genes from a 'Find new members of a pathway' search.
Figure 5: An example of a network layout view page in a new web browser window.
Figure 6: The 'Infer function from network neighbors' search.
Figure 7: A report from a 'Find new members of a pathway' search.
Figure 8: Functional gene set enrichment analysis (e.

References

  1. 1

    McGary, K.L., Lee, I. & Marcotte, E.M. Broad network-based predictability of Saccharomyces cerevisiae gene loss-of-function phenotypes. Genome Biol. 8, R258 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  2. 2

    Lehner, B. & Lee, I. Network-guided genetic screening: building, testing and using gene networks to predict gene function. Brief Funct. Genomic Proteomic 7, 217–227 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  3. 3

    Alonso, J.M. et al. Genome-wide insertional mutagenesis of Arabidopsis thaliana. Science 301, 653–657 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  4. 4

    Lee, I., Date, S.V., Adai, A.T. & Marcotte, E.M. A probabilistic functional network of yeast genes. Science 306, 1555–1558 (2004).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  5. 5

    Marcotte, E.M., Pellegrini, M., Thompson, M.J., Yeates, T.O. & Eisenberg, D. A combined algorithm for genome-wide prediction of protein function. Nature 402, 83–86 (1999).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  6. 6

    Fraser, H.B. & Plotkin, J.B. Using protein complexes to predict phenotypic effects of gene mutation. Genome Biol. 8, R252 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  7. 7

    Lee, I. et al. A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans. Nat. Genet. 40, 181–188 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. 8

    Zhong, W. & Sternberg, P.W. Genome-wide prediction of C. elegans genetic interactions. Science 311, 1481–1484 (2006).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  9. 9

    Lee, I. et al. Predicting genetic modifier loci using functional gene networks. Genome Res. 20, 1143–1153 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  10. 10

    Franke, L. et al. Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes. Am. J. Hum. Genet. 78, 1011–1025 (2006).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. 11

    Huttenhower, C. et al. Exploring the human genome with functional maps. Genome Res. 19, 1093–1106 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12

    Lage, K. et al. A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat. Biotechnol. 25, 309–316 (2007).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. 13

    Linghu, B., Snitkin, E.S., Hu, Z., Xia, Y. & Delisi, C. Genome-wide prioritization of disease genes and identification of disease-disease associations from an integrated human functional linkage network. Genome Biol. 10, R91 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  14. 14

    Szklarczyk, D. et al. The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res. 39, D561–D568 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  15. 15

    Mostafavi, S., Ray, D., Warde-Farley, D., Grouios, C. & Morris, Q. GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function. Genome Biol. 9 (Suppl 1): S4 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  16. 16

    Lee, I., Ambaru, B., Thakkar, P., Marcotte, E.M. & Rhee, S.Y. Rational association of genes with traits using a genome-scale gene network for Arabidopsis thaliana. Nat. Biotechnol. 28, 149–156 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  17. 17

    Cui, J. et al. AtPID: Arabidopsis thaliana protein interactome database—an integrative platform for plant systems biology. Nucleic Acids Res. 36, D999–D1008 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  18. 18

    Geisler-Lee, J. et al. A predicted interactome for Arabidopsis. Plant Physiol. 145, 317–329 (2007).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  19. 19

    Gutierrez, R.A. et al. Qualitative network models and genome-wide expression data define carbon/nitrogen-responsive molecular machines in Arabidopsis. Genome Biol. 8, R7 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  20. 20

    Ma, S., Gong, Q. & Bohnert, H.J. An Arabidopsis gene network based on the graphical Gaussian model. Genome Res. 17, 1614–1625 (2007).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  21. 21

    Fawcett, T. ROC Graphs: Notes and Practical Considerations for Data Mining Researchers (Hewlett-Packard Company, 2003).

  22. 22

    Storey, J.D. & Tibshirani, R. Statistical significance for genomewide studies. Proc. Natl. Acad. Sci. USA 100, 9440–9445 (2003).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  23. 23

    Berardini, T.Z. et al. Functional annotation of the Arabidopsis genome using controlled vocabularies. Plant Physiol. 135, 745–755 (2004).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  24. 24

    Avraham, S. et al. The Plant Ontology Database: a community resource for plant structure and developmental stages controlled vocabulary and annotations. Nucleic Acids Res. 36, D449–D454 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  25. 25

    Hunter, S. et al. InterPro: the integrative protein signature database. Nucleic Acids Res. 37, D211–D215 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  26. 26

    Rhee, S.Y. et al. The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized, curated gateway to Arabidopsis biology, research materials and community. Nucleic Acids Res. 31, 224–228 (2003).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  27. 27

    Remm, M., Storm, C.E. & Sonnhammer, E.L. Automatic clustering of orthologs and in-paralogs from pairwise species comparisons. J. Mol. Biol. 314, 1041–1052 (2001).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  28. 28

    Blanc, G., Hokamp, K. & Wolfe, K.H. A recent polyploidy superimposed on older large-scale duplications in the Arabidopsis genome. Genome Res. 13, 137–144 (2003).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  29. 29

    Lopes, C.T. et al. Cytoscape Web: an interactive web-based network browser. Bioinformatics 26, 2347–2348 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  30. 30

    Cline, M.S. et al. Integration of biological networks and gene expression data using Cytoscape. Nat. Protoc. 2, 2366–2382 (2007).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  31. 31

    Bard, J.B. & Rhee, S.Y. Ontologies in biology: design, applications and future challenges. Nat. Rev. Genet. 5, 213–222 (2004).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  32. 32

    Ashburner, M. et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25–29 (2000).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. 33

    Danyluk, J., Carpentier, E. & Sarhan, F. Identification and characterization of a low temperature regulated gene encoding an actin-binding protein from wheat. FEBS Lett. 389, 324–327 (1996).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. 34

    Scholl, R. & Anderson, M. Arabidopsis Biological Resource Center. Plant Mol. Bio. Rep. 12, 242–244 (1994).

    Article  Google Scholar 

  35. 35

    Wang, P.I. & Marcotte, E.M. It's the machine that matters: predicting gene function and phenotype from protein networks. J. Proteomics 73, 2277–2289 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported by the National Research Foundation of Korea grant funded by the Korean government (no. 20100017649); Pohang Iron and Steel Company (POSCO) TJ Park Science Fellowship (to I.L.); grants from the National Science Foundation, National Institutes of Health, Welch (F1515) and Packard Foundations (to E.M.M.); the Carnegie Institution for Science; and a grant from the National Science Foundation (to S.Y.R.).

AUTHOR CONTRIBUTIONS

I.L., E.M.M., S.Y.R. and S.H. conceived the protocol. S.H. constructed the current version of the AraNet web application and wrote the protocol. I.L., E.M.M. and S.Y.R. edited the protocol.

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I.L., E.M.M., S.Y.R. and S.H. conceived the protocol. S.H. constructed the current version of the AraNet web application and wrote the protocol. I.L., E.M.M. and S.Y.R. edited the protocol.

Corresponding authors

Correspondence to Seung Y Rhee or Edward M Marcotte or Insuk Lee.

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The authors declare no competing financial interests.

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Hwang, S., Rhee, S., Marcotte, E. et al. Systematic prediction of gene function in Arabidopsis thaliana using a probabilistic functional gene network. Nat Protoc 6, 1429–1442 (2011). https://doi.org/10.1038/nprot.2011.372

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