bioRxivEvolutionary BiologyPreprint
Genome expansion and lineage-specific genetic innovations in the world’s largest organisms (Armillaria)
György SiposiD, Arun N. Prasanna, Mathias C. Walther, Eoin O’Connor, Balázs BálintiD, Krisztina Krizsán, Brigitta Kiss, Jaqueline Hess, Torda VargaiD, Jason Slot, Robert Riley, Bettina Bóka, Daniel RiglingiD, Kerrie BarryiD, Juna LeeiD, Sirma Mihaltcheva, Kurt Labutti, Anna LipzeniD, Rose Waldron, Nicola M. Moloney, Christoph Sperisen, László Kredics, Csaba Vágvölgyi, Andrea Patrigniani, David Fitzpatrick, , László G Nagy
Abstract
Armillaria species are both devastating forest pathogens and some of the largest terrestrial organisms on Earth. They forage for hosts and achieve immense colony sizes using rhizomorphs, root-like multicellular structures of clonal dispersal. Here, we sequenced and analyzed genomes of four Armillaria species and performed RNA-Seq and quantitative proteomic analysis on seven invasive and reproductive developmental stages of A. ostoyae. Comparison with 22 related fungi revealed a significant genome expansion in Armillaria, affecting several pathogenicity-related genes, lignocellulose degrading enzymes and lineage-specific genes likely involved in rhizomorph development. Rhizomorphs express an evolutionarily young transcriptome that shares features with the transcriptomes of fruiting bodies and vegetative mycelia. Several genes show concomitant upregulation in rhizomorphs and fruiting bodies and shared cis-regulatory signatures in their promoters, providing genetic and regulatory insights into complex multicellularity in fungi. Our results suggest that the evolution of the unique dispersal and pathogenicity mechanisms of Armillaria might have drawn upon ancestral genetic toolkits for wood-decay, morphogenesis and complex multicellularity.
- organism: fungi (other)
- assay: whole-genome sequencing
- assay: bulk RNA-seq
- assay: proteomics
- research focus: chromatin & epigenetic regulation
- research focus: development & morphogenesis
- research focus: gene regulatory network inference
- approach: comparative / phylogenetic analysis
- approach: statistical model
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