Abstract:
BACKGROUND:More accurate and complete reference genomes have improved understanding of gene function, biology, and evolutionary mechanisms. Hybrid genome assembly approaches leverage benefits of both long, relatively error-prone reads from third-generation sequencing technologies and short, accurate reads from second-generation sequencing technologies, to produce more accurate and contiguous de novo genome assemblies in comparison to using either technology independently. In this study, we present a novel hybrid assembly pipeline that allowed for both mitogenome de novo assembly and telomere length de novo assembly of all 7 chromosomes of the model entomopathogenic fungus, Metarhizium brunneum. RESULTS:The improved assembly allowed for better ab initio gene prediction and a more BUSCO complete proteome set has been generated in comparison to the eight current NCBI reference Metarhizium spp. genomes. Remarkably, we note that including the mitogenome in ab initio gene prediction training improved overall gene prediction. The assembly was further validated by comparing contig assembly agreement across various assemblers, assessing the assembly performance of each tool. Genomic synteny and orthologous protein clusters were compared between Metarhizium brunneum and three other Hypocreales species with complete genomes, identifying core proteins, and listing orthologous protein clusters shared uniquely between the two entomopathogenic fungal species, so as to further facilitate the understanding of molecular mechanisms underpinning fungal-insect pathogenesis. CONCLUSIONS:The novel assembly pipeline may be used for other haploid fungal species, facilitating the need to produce high-quality reference fungal genomes, leading to better understanding of fungal genomic evolution, chromosome structuring and gene regulation.
journal_name
BMC Genomicsjournal_title
BMC genomicsauthors
Saud Z,Kortsinoglou AM,Kouvelis VN,Butt TMdoi
10.1186/s12864-021-07390-ysubject
Has Abstractpub_date
2021-01-28 00:00:00pages
87issue
1issn
1471-2164pii
10.1186/s12864-021-07390-yjournal_volume
22pub_type
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