Date Published: June 6, 2013
Publisher: Public Library of Science
Author(s): Sook-Young Park, Jaeyoung Choi, Se-Eun Lim, Gir-Won Lee, Jongsun Park, Yang Kim, Sunghyung Kong, Se Ryun Kim, Hee-Sool Rho, Junhyun Jeon, Myung-Hwan Chi, Soonok Kim, Chang Hyun Khang, Seogchan Kang, Yong-Hwan Lee, Leah E. Cowen.
Because most efforts to understand the molecular mechanisms underpinning fungal pathogenicity have focused on studying the function and role of individual genes, relatively little is known about how transcriptional machineries globally regulate and coordinate the expression of a large group of genes involved in pathogenesis. Using quantitative real-time PCR, we analyzed the expression patterns of 206 transcription factor (TF) genes in the rice blast fungus Magnaporthe oryzae under 32 conditions, including multiple infection-related developmental stages and various abiotic stresses. The resulting data, which are publicly available via an online platform, provided new insights into how these TFs are regulated and potentially work together to control cellular responses to a diverse array of stimuli. High degrees of differential TF expression were observed under the conditions tested. More than 50% of the 206 TF genes were up-regulated during conidiation and/or in conidia. Mutations in ten conidiation-specific TF genes caused defects in conidiation. Expression patterns in planta were similar to those under oxidative stress conditions. Mutants of in planta inducible genes not only exhibited sensitive to oxidative stress but also failed to infect rice. These experimental validations clearly demonstrated the value of TF expression patterns in predicting the function of individual TF genes. The regulatory network of TF genes revealed by this study provides a solid foundation for elucidating how M. oryzae regulates its pathogenesis, development, and stress responses.
Fungal pathogenesis requires well-orchestrated regulation of multiple cellular and developmental processes in response to diverse stimuli from the host and the environment. Transcription factors (TFs) function as key regulators of such processes. Identification of TF genes, which typically represent 3–6% of the predicted genes in eukaryotic genomes, has been greatly facilitated by genome sequencing . High-throughput methods for gene expression analysis have enabled studies on how TF genes are globally regulated under diverse conditions –. A combination of these approaches has uncovered putative roles and potential interactions of TFs in animals and plants , . Although DNA microarrays have been successfully used to study global gene expression patterns, this approach may not be sensitive enough to accurately analyze low-abundance transcripts, including those from many TF genes . Quantitative RT-PCR (qRT-PCR) has been shown to be five times more sensitive than microarrays , serving as an effective means for accurate quantification of TF transcripts.
Advances in tools for analyzing global gene expression profiles have facilitated the identification of genes potentially associated with specific processes and the characterization of regulatory networks controlling their expression. To test whether expression patterns of TF genes under diverse conditions help predict the functional roles of individual genes and potential regulatory interactions among them, we analyzed expression of 206 M. oryzae TF genes under 32 conditions using qRT-PCR. Expression profiles and functional validation of several genes selected based on their expression patterns clearly demonstrate the value of TF gene expression patterns in predicting their function. This comprehensive expression data of TF genes, publicly available through FTFD, will serve as a new community resource in analyzing the functions of and potential interactions among individual TF genes.