Evaluating the Assembly Strategy of a Fungal Genome from Metagenomic Data: Solorina crocea (Peltigerales, Ascomycota) as a Case Study.

Abstract

The advent of next-generation sequencing technologies has given rise to considerably diverse techniques. However, integrating data from these technologies to generate high-quality genomes remains challenging, particularly when starting from metagenomic data. To provide further insight into this process, the genome of the lichenized fungus Solorina crocea was sequenced using DNA extracted from the thallus, which contains the genome of the mycobiont, along with those of the photobionts (a green alga and a cyanobacterium), and other associated microorganisms. Three different strategies were assessed for the assembly of a de novo genome, employing data obtained from Illumina and PacBio HiFi technologies: (1) hybrid assembly based on metagenomic data; (2) assembly based on metagenomic long reads and scaffolded with filtered mycobiont long and short reads; (3) hybrid assembly based on filtered mycobiont short and long reads. Assemblies were compared according to contiguity and completeness criteria. Strategy 2 achieved the most continuous and complete genome, with a size of 55.5 Mb, an N50 of 148.5 kb, and 519 scaffolds. Genome annotation and functional prediction were performed, including identification of secondary metabolite biosynthetic gene clusters. Genome annotation predicted 6151 genes, revealing a high number of genes associated with transport, carbohydrate metabolism, and stress response.