Abstract

Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB), which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN) of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other pathogenic fungi, which demonstrate the effectiveness of the proposed method. The results presented in this paper not only can provide guidelines for future experimental verification, but also shed light on the pathogenesis of the destructive fungus F. graminearum.

Highlights

  • The filamentous ascomycete Fusarium graminearum is the major pathogenic agent of Fusarium head blight(FHB) [1], which can cause diseases for wheat, barley and other crops, and is becoming a serious disease in many countries over the world

  • The microarray data obtained with F. graminearum Affymetrix GeneChip were downloaded from Plant Expression Database (PLEXdb, http://www.plexdb.org/index.php), which is a unified public resource for gene expression data of plants and plant pathogens

  • Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB) which is a destructive disease on wheat and barley

Read more

Summary

Introduction

The filamentous ascomycete Fusarium graminearum (teleomorph Gibberella zeae) is the major pathogenic agent of Fusarium head blight(FHB) [1], which can cause diseases for wheat, barley and other crops, and is becoming a serious disease in many countries over the world. FHB causes diseases to crops within a few weeks [2], and results in huge economic loss and causes health problems to human and animals by contaminating grains [3]. By the writing of this paper, there are 49 pathogenic genes of F. graminearum that were verified by biological experiments and stored in PHI-base database (http://www.phi-base.org/ query.php). The pathogenic gene list is far from complete and it will be a painful process to identify pathogenic genes in lab considering the genome size of F. graminearum and time-consuming experiments. Computational methods can provide alternative ways for this problem, especially after the genome sequence of F. graminearum is released by Broad Institute (http://www.broadinstitute.org). It is found that there are no specific genes that uniquely occur in pathogenic fungi but not in non-pathogenic fungi, which makes it difficult to identify pathogenic genes of F. graminearum

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call