A single-cell genomics pipeline for environmental microbial eukaryotes

Single-cell sequencing of environmental microorganisms is an essential component of the microbial ecology toolkit. However, large-scale targeted single-cell sequencing for the whole-genome recovery of uncultivated eukaryotes is lagging. The key challenges are low abundance in environmental communiti...

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Veröffentlicht in:iScience 2021-04, Vol.24 (4), p.102290, Article 102290
Hauptverfasser: Ciobanu, Doina, Clum, Alicia, Ahrendt, Steven, Andreopoulos, William B., Salamov, Asaf, Chan, Sandy, Quandt, C. Alisha, Foster, Brian, Meier-Kolthoff, Jan P., Tang, Yung Tsu, Schwientek, Patrick, Benny, Gerald L., Smith, Matthew E., Bauer, Diane, Deshpande, Shweta, Barry, Kerrie, Copeland, Alex, Singer, Steven W., Woyke, Tanja, Grigoriev, Igor V., James, Timothy Y., Cheng, Jan-Fang
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Sprache:eng
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Zusammenfassung:Single-cell sequencing of environmental microorganisms is an essential component of the microbial ecology toolkit. However, large-scale targeted single-cell sequencing for the whole-genome recovery of uncultivated eukaryotes is lagging. The key challenges are low abundance in environmental communities, large complex genomes, and cell walls that are difficult to break. We describe a pipeline composed of state-of-the art single-cell genomics tools and protocols optimized for poorly studied and uncultivated eukaryotic microorganisms that are found at low abundance. This pipeline consists of seven distinct steps, beginning with sample collection and ending with genome annotation, each equipped with quality review steps to ensure high genome quality at low cost. We tested and evaluated each step on environmental samples and cultures of early-diverging lineages of fungi and Chromista/SAR. We show that genomes produced using this pipeline are almost as good as complete reference genomes for functional and comparative genomics for environmental microbial eukaryotes. [Display omitted] •We optimized single-cell methodology using a broad sample range, for EME•We combined bioinformatic and bench protocols into a concise workflow•We benchmarked the pipeline and used it on environmental samples•We selected a set of QC criteria for best genome quality prediction Genomics ; Geomicrobiology ; Microbiology
ISSN:2589-0042
2589-0042
DOI:10.1016/j.isci.2021.102290