Genome compartmentalization predates species divergence in the plant pathogen genus Zymoseptoria.

Background: Antagonistic co-evolution can drive rapid adaptation in pathogens and shape genome architecture. Comparative genome analyses of several fungal pathogens revealed highly variable genomes, for many species characterized by specific repeat-rich genome compartments with exceptionally high sequence variability. Dynamic genome structure may enable fast adaptation to host genetics.

Intraspecific comparative genomics of isolates of the Norway spruce pathogen (Heterobasidion parviporum) and identification of its potential virulence factors.

Background: Heterobasidion parviporum is an economically most important fungal forest pathogen in northern Europe, causing root and butt rot disease of Norway spruce (Picea abies (L.) Karst.).

Show me the way: rust effector targets in heterologous plant systems.

For years, the study of rust fungal effectors has been impeded by the lack of molecular genetic tools in rust pathosystems. The recent use of heterologous plants to perform effector screens (effectoromics)-including effector localisation (cellular targets) and protein interactors (molecular targets) in plant cells-has changed the game. These screens revealed that many candidate effectors from various rust fungi target specific plant cell compartments, including chloroplasts, and associate with specific plant protein complexes.

The Rust Fungus Melampsora larici-populina Expresses a Conserved Genetic Program and Distinct Sets of Secreted Protein Genes During Infection of Its Two Host Plants, Larch and Poplar.

Mechanisms required for broad-spectrum or specific host colonization of plant parasites are poorly understood. As a perfect illustration, heteroecious rust fungi require two alternate host plants to complete their life cycles. Melampsora larici-populina infects two taxonomically unrelated plants, larch, on which sexual reproduction is achieved, and poplar, on which clonal multiplication occurs, leading to severe epidemics in plantations.

Computational Methods for Predicting Effectors in Rust Pathogens.

Lower costs and improved sequencing technologies have led to a large number of high-quality rust pathogen genomes and deeper characterization of gene expression profiles during early and late infection stages. However, the set of secreted proteins expressed during infection is too large for experimental investigations and contains not only effectors but also proteins that play a role in niche colonization or in fighting off competing microbes. Therefore, accurate computational prediction is essential for identifying high-priority rust effector candidates from secretomes.