A comparative hidden Markov model analysis pipeline identifies proteins characteristic of cereal-infecting fungi.

ABSTRACT:

Background

Fungal pathogens cause devastating losses in economically important cereal crops by utilising pathogen proteins to infect host plants. Secreted pathogen proteins are referred to as effectors and have thus far been identified by selecting small, cysteine-rich peptides from the secretome despite increasing evidence that not all effectors share these attributes.

Results

We take advantage of the availability of sequenced fungal genomes and present an unbiased method for finding putative pathogen proteins and secreted effectors in a query genome via comparative hidden Markov model analyses followed by unsupervised protein clustering. Our method returns experimentally validated fungal effectors in Stagonospora nodorum and Fusarium oxysporum as well as the N-terminal Y/F

SUBMITTER: Sperschneider J 

PROVIDER: S-EPMC3914424 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature