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Recovery of 447 Eukaryotic bins reveals major challenges for Eukaryote genome reconstruction from metagenomes

基因组 生物 真核细胞染色体精细结构 真核生物 进化生物学 计算生物学 遗传学 基因
作者
Joao Saraiva,Alexander Bartholomäus,Rodolfo Toscan,Petr Baldrian,Ulisses da Rocha
出处
期刊:Authorea - Authorea
标识
DOI:10.22541/au.164943444.40171655/v1
摘要

An estimated 8.7 million eukaryotic species exist on our planet. However, recent tools for taxonomic classification of eukaryotes only dispose of 734 reference genomes. As most Eukaryotic genomes are yet to be sequenced, the mechanisms underlying their contribution to different ecosystem processes remain untapped. Although approaches to recover Prokaryotic genomes have become common in genome biology, few studies have tackled the recovery of Eukaryotic genomes from metagenomes. This study assessed the reconstruction of Eukaryotic genomes using 215 metagenomes from diverse environments using the EukRep pipeline. We obtained 447 eukaryotic bins from 15 classes (e.g., Saccharomycetes, Sordariomycetes, and Mamiellophyceae) and 16 orders (e.g., Mamiellales, Saccharomycetales, and Hypocreales). More than 73% of the obtained eukaryotic bins were recovered from samples whose biomes were classified as host-associated, aquatic and anthropogenic terrestrial. However, only 93 bins showed taxonomic classification to (9 unique) genera and 17 bins to (6 unique) species. A total of 193 bins contained completeness and contamination measures. Average completeness and contamination were 44.64% (σ=27.41%) and 3.97% (σ=6.53%), respectively. Micromonas commoda was the most frequent taxa found while Saccharomyces cerevisiae presented the highest completeness, possibly resulting from a more significant number of reference genomes. However, mapping eukaryotic bins to the chromosomes of the reference genomes suggests that completeness measures should consider both single-copy genes and chromosome coverage. Recovering eukaryotic genomes will benefit significantly from long-read sequencing, intron removal after assembly, and improved reference genomes databases.

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