A unique chromatin profile defines adaptive genomic regions in a fungal plant pathogen
Abstract
Genomes store information at scales beyond the linear nucleotide sequence, which impacts genome function at the level of an individual, while influences on populations and long-term genome function remains unclear. Here, we addressed how physical and chemical DNA characteristics influence genome evolution in the plant pathogenic fungus Verticillium dahliae. We identified incomplete DNA methylation of repetitive elements, associated with specific genomic compartments originally defined as Lineage-Specific (LS) regions that contain genes involved in host adaptation. Further chromatin characterization revealed associations with features such as H3 Lys-27 methylated histones (H3K27me3) and accessible DNA. Machine learning trained on chromatin data identified twice as much LS DNA as previously recognized, which was validated through orthogonal analysis, and we propose to refer to this DNA as adaptive genomic regions. Our results provide evidence that specific chromatin profiles define adaptive genomic regions, and highlight how different epigenetic factors contribute to the organization of these regions.
Data availability
The sequencing data for this project are accessible from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under BioProject PRJNA592220.
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A unique chromatin profile defines adaptive genomic regions in a fungal plant pathogenNCBI Sequence Read Archive, BioProject PRJNA592220.
Article and author information
Author details
Funding
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Michael F Seidl
- Bart PHJ Thomma
European Molecular Biology Organization (Postdoctoral fellowship EMBO, ALTF 969-2013)
- David E Cook
Human Frontier Science Program (Postdoctoral Fellowship HFSP, LT000627/2014-L)
- David E Cook
Deutsche Forschungsgemeinschaft
- Bart PHJ Thomma
Conacyt
- David E Torres
United States Department of Agriculture
- David E Cook
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Cook et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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