Fine-Scale Recombination Maps of Fungal Plant Pathogens Reveal Dynamic Recombination Landscapes and Intragenic Hotspots

• Published in: Genetics (Austin) 2018-03, Vol.208 (3), p.1209-1229
• Main Authors: Stukenbrock, Eva H, Dutheil, Julien Y
• Format: Article
• Language: English
• Subjects: Ascomycota; Ascomycota - genetics; Base Composition; Biodiversity; Biological evolution; Centromere; Centromere - genetics; Centromeres; Chromosome Mapping; Chromosomes; Chromosomes, Fungal; Crossing Over, Genetic; Evolution; Evolution, Molecular; Fungi; Gene loci; Gene mapping; Genetic recombination; Genetics; Genome, Fungal; Genomics; Genomics - methods; Investigations; Landscape preservation; Life Sciences; Linkage Disequilibrium; Meiosis; Pathogenicity; Pathogens; Plant Diseases; Plant Diseases - microbiology; Polymorphism, Single Nucleotide; Population (statistical); Population studies; Populations and Evolution; Recombination; Recombination hot spots; Recombination, Genetic; Sibling species; Simulation analysis; Statistical methods; Vegetal Biology; Wheat; Yeast; Zymoseptoria ardabiliae; Zymoseptoria tritici
• ISSN: 1943-2631; 0016-6731; 1943-2631
• DOI: 10.1534/genetics.117.300502

Meiotic recombination is an important driver of evolution. Variability in the intensity of recombination across chromosomes can affect sequence composition, nucleotide variation, and rates of adaptation. In many organisms, recombination events are concentrated within short segments termed recombination hotspots. The variation in recombination rate and positions of recombination hotspot can be studied using population genomics data and statistical methods. In this study, we conducted population genomics analyses to address the evolution of recombination in two closely related fungal plant pathogens: the prominent wheat pathogen and a sister species infecting wild grasses We specifically addressed whether recombination landscapes, including hotspot positions, are conserved in the two recently diverged species and if recombination contributes to rapid evolution of pathogenicity traits. We conducted a detailed simulation analysis to assess the performance of methods of recombination rate estimation based on patterns of linkage disequilibrium, in particular in the context of high nucleotide diversity. Our analyses reveal overall high recombination rates, a lack of suppressed recombination in centromeres, and significantly lower recombination rates on chromosomes that are known to be accessory. The comparison of the recombination landscapes of the two species reveals a strong correlation of recombination rate at the megabase scale, but little correlation at smaller scales. The recombination landscapes in both pathogen species are dominated by frequent recombination hotspots across the genome including coding regions, suggesting a strong impact of recombination on gene evolution. A significant but small fraction of these hotspots colocalize between the two species, suggesting that hotspot dynamics contribute to the overall pattern of fast evolving recombination in these species.