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  • 标题:Improvement of eukaryotic protein predictions from soil metagenomes
  • 本地全文:下载
  • 作者:Carole Belliardo ; Georgios D.Koutsovoulos ; Corinne Rancurel
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2022
  • 卷号:9
  • 期号:1
  • 页码:1-14
  • DOI:10.1038/s41597-022-01420-4
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:During the last decades, metagenomics has highlighted the diversity of microorganisms from environmental or host-associated samples . Most metagenomics public repositories use annotation pipelines tailored for prokaryotes regardless of the taxonomic origin of contigs . Consequently, eukaryotic contigs with intrinsically diferent gene features, are not optimally annotated . Using a bioinformatics pipeline, we have fltered 7.9 billion contigs from 6,872 soil metagenomes in the JGI’s IMG/M database to identify eukaryotic contigs . We have re-annotated genes using eukaryote-tailored methods, yielding 8 million eukaryotic proteins and over 300,000 orphan proteins lacking homology in public databases . Comparing the gene predictions we made with initial JGI ones on the same contigs, we confrmed our pipeline improves eukaryotic proteins completeness and contiguity in soil metagenomes . The improved quality of eukaryotic proteins combined with a more comprehensive assignment method yielded more reliable taxonomic annotation . This dataset of eukaryotic soil proteins with improved completeness, quality and taxonomic annotation reliability is of interest for any scientist aiming at studying the composition, biological functions and gene fux in soil communities involving eukaryotes .
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