We introduce a rational approach for associating genes with plant traits by combined use of a genome-scale functional network and targeted reverse genetic screening. We present a probabilistic network (AraNet) of functional associations among 19,647 (73%) genes of the reference flowering plant Arabidopsis thaliana. AraNet associations are predictive for diverse biological pathways, and outperform predictions derived only from literature-based protein interactions, achieving 21% precision for 55% of genes. AraNet prioritizes genes for limited-scale functional screening, resulting in a hit-rate tenfold greater than screens of random insertional mutants, when applied to early seedling development as a test case. By interrogating network neighborhoods, we identify AT1G80710 (now DROUGHT SENSITIVE 1; DRS1) and AT3G05090 (now LATERAL ROOT STIMULATOR 1; LRS1) as regulators of drought sensitivity and lateral root development, respectively. AraNet (http://www.functionalnet.org/aranet/) provides a resource for plant gene function identification and genetic dissection of plant traits.
Bibliographical noteFunding Information:
We are grateful to M. Ahn, A. Noorani and V. Bakshi for technical assistance, J. Shin for assistance on AraNet web design, T. Nakagawa (Shimane University, Japan) for providing pGWB2, K. Barton for providing lab space and D. Meinke, M. Running, W. Briggs, Z. Wang and K. Dreher for helpful discussions. This work was supported by Carnegie Institution for Science (B.A., S.Y.R.), a grant from the National Science Foundation (MCB0520140) to S.Y.R. and by the National Research Foundation of Korea (NRF) grant funded by the Korean government (no. 20090063342, 2009-0070968) and Yonsei University (no. 200870284, 200810018) to I.L. and from the National Science Foundation, National Institutes of Health, and Welch (F1515) and Packard Foundations to E.M.M.
All Science Journal Classification (ASJC) codes
- Applied Microbiology and Biotechnology
- Molecular Medicine
- Biomedical Engineering