4.7 Article

iGDP: An integrated genome decontamination pipeline for wild ciliated microeukaryotes

期刊

MOLECULAR ECOLOGY RESOURCES
卷 23, 期 5, 页码 1182-1193

出版社

WILEY
DOI: 10.1111/1755-0998.13782

关键词

bioinformatics; contamination; genomics; protist; sequence filtering

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Researchers developed an integrated Genome Decontamination Pipeline (iGDP) to filter contaminated ciliate genome assemblies from wild specimens, resulting in high-quality ciliate genomes. iGDP showed good performance in filtering contaminants and can be applied to other microeukaryotes.
Ciliates are a large group of ubiquitous and highly diverse single-celled eukaryotes that play an essential role in the functioning of microbial food webs. However, their genomic diversity is far from clear due to the need to develop cultivation methods for most species, so most research is based on wild organisms that almost invariably contain contaminants. Here we establish an integrated Genome Decontamination Pipeline (iGDP) that combines homology search, telomere reads-assisted and clustering approaches to filter contaminated ciliate genome assemblies from wild specimens. We benchmarked the performance of iGDP using genomic data from a contaminated ciliate culture and the results showed that iGDP could recall 91.9% of the target sequences with 96.9% precision. We also used a synthetic dataset to offer guidelines for the application of iGDP in the removal of various groups of contaminants. Compared with several popular metagenome binning tools, iGDP could show better performance. To further validate the effectiveness of iGDP on real-world data, we applied it to decontaminate genome assemblies of three wild ciliate specimens and obtained their genomes with high quality comparable to that of previously well-studied model ciliate genomes. It is anticipated that the newly generated genomes and the established iGDP method will be valuable community resources for detailed studies on ciliate biodiversity, phylogeny, ecology and evolution. The pipeline () can be implemented automatically to reduce manual filtering and classification and may be further developed to apply to other microeukaryotes.

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