EffectorO: Motif-Independent Prediction of Effectors in Oomycete Genomes Using Machine Learning and Lineage Specificity.
Mol Plant Microbe Interact
; 36(7): 397-410, 2023 Jul.
Article
em En
| MEDLINE
| ID: mdl-36853198
ABSTRACT
Oomycete plant pathogens cause a wide variety of diseases, including late blight of potato, sudden oak death, and downy mildews of plants. These pathogens are major contributors to loss in numerous food crops. Oomycetes secrete effector proteins to manipulate their hosts to the advantage of the pathogen. Plants have evolved to recognize effectors, resulting in an evolutionary cycle of defense and counter-defense in plant-microbe interactions. This selective pressure results in highly diverse effector sequences that can be difficult to computationally identify using only sequence similarity. We developed a novel effector prediction tool, EffectorO, that uses two complementary approaches to predict effectors in oomycete pathogen genomes i) a machine learning-based pipeline that predicts effector probability based on the biochemical properties of the N-terminal amino-acid sequence of a protein and ii) a pipeline based on lineage specificity to find proteins that are unique to one species or genus, a sign of evolutionary divergence due to adaptation to the host. We tested EffectorO on Bremia lactucae, which causes lettuce downy mildew, and Phytophthora infestans, which causes late blight of potato and tomato, and predicted many novel effector candidates while recovering the majority of known effector candidates. EffectorO will be useful for discovering novel families of oomycete effectors without relying on sequence similarity to known effectors. [Formula see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Oomicetos
/
Peronospora
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Phytophthora infestans
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Mol Plant Microbe Interact
Assunto da revista:
BIOLOGIA MOLECULAR
/
BOTANICA
/
MICROBIOLOGIA
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Estados Unidos