bioRxivGenomicsPreprint
Gene erosion and genome expansion in a group of highly host-specialized fungal phytopathogens
Lamprinos FrantzeskakisiD, Márk Z. NémethiD, Mirna BarsoumiD, Stefan KuschiD, Levente KissiD, Susumu TakamatsuiD, Ralph PanstrugaiD
Abstract
Due to their comparatively small genome size and short generation time, fungi are exquisite model systems to study eukaryotic genome evolution. Powdery mildew (PM) fungi present an exceptional case where their strict host dependency (a lifestyle termed obligate biotrophy) is associated with some of the largest fungal genomes sequenced so far (>100 Mbp). This size expansion is largely due to the pervasiveness of transposable elements (TEs), which can cover more than 70% of these genomes, and is associated with the loss of multiple conserved ascomycete genes (CAGs) required for a free-living lifestyle. To date, little is known about the mechanisms that drove this expansion, and information on ancestral PM genomes is lacking. We report the genome analysis of the early-diverged PM species Parauncinula polyspora that in contrast to most other PMs reproduces exclusively sexually. The P. polyspora genome is surprisingly small (<30 Mb) and sparsely equipped with TEs (<10%), despite the conserved absence of a common defense mechanism (RIP) involved in constraining repetitive elements. The genome still harbors the majority of the CAGs that are absent in the genomes of the recently evolved PMs. We speculate that TE spread might have been limited by its unique reproduction strategy and host features and further hypothesize that the loss of CAGs may promote the evolutionary isolation and host niche specialization of PM fungi. Limitations associated with this evolutionary trajectory might have been in part counteracted by the evolution of plastic, TE-rich genomes and/or the expansion of gene families encoding secreted virulence proteins.
- organism: fungi (other)
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- research focus: variant calling
- approach: statistical model
- Citations
- 2
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