A large portion of nuclear DNA is composed of transposable element (TE) sequences, whose transposition is controlled by diverse host defense strategies in order to maintain genomic integrity. One such strategy is the fungal-specific Repeat-Induced Point mutation (RIP) that hyper-mutates repetitive DNA sequences. While RIP is found across Fungi, it has been shown to vary in efficiency. The filamentous ascomycete Neurospora crassa has been a pioneer in the study of RIP, but data on TEs and RIP from other species in the genus is limited. In this study, we investigated 18 nearly gapless genome assemblies of ten Neurospora species, which diverged from a common ancestor about 7 MYA, to determine and compare genome-wide TE distribution and their associated RIP patterns. Four of these assemblies, generated by PacBio technology, represent new genomic datasets. We showed that the TE contents between 8.7-18.9% covary with genome sizes that range between 37.8-43.9 Mb. Degraded copies of Long Terminal Repeat (LTR) retrotransposons were abundant among the identified TEs, and these are distributed across the genome at varying frequencies. In all investigated Neurospora genomes, TE sequences had signs of numerous C-to-T substitutions, suggesting that RIP occurred in all species, and accordingly, RIP signatures correlated with TE-dense regions in all genomes. In conclusion, essentially gapless genome assemblies allowed us to identify TEs in Neurospora genomes, and reveal that TEs contribute to genome size variation in this group. Our study suggests that TEs and RIP are highly correlated in each examined Neurospora species, and hence, the pattern of interaction is conserved over the investigated evolutionary timescale. Finally, with our results, we verify that RIP signatures can be used to facilitate the identification of TE-rich region in the genome. The comprehensive genomic dataset of Neurospora is a rich resource for further in-depth analyses of fungal genomes by the community.

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Creative Commons Attribution-Share Alike 4.0 License
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