EukRep

EukRep classifies eukaryotic sequences in metagenomic datasets using a k-mer-based strategy to separate eukaryotic from prokaryotic fragments and enable genome recovery and metabolic analysis.


Key Features:

  • K-mer-based classification: Implements a k-mer–based strategy to classify sequence fragments as eukaryotic or prokaryotic.
  • Eukaryotic sequence identification: Distinguishes eukaryotic and prokaryotic fragments within mixed metagenomic data to facilitate extraction of eukaryotic sequences.
  • Genome recovery and completeness evaluation: Supports reconstruction of near-complete eukaryotic genomes, demonstrated by recovery of three fungi (Eurotiomycetes) and an arthropod.
  • Metabolic potential prediction: Enables downstream prediction of metabolic functions and detection of community metabolic shifts, as observed after organic carbon addition with increased secreted proteases, lipases, cellulose-targeting CAZymes, and methanol oxidation.
  • Application to environmental samples: Applied to complex environmental datasets to reconstruct and evaluate high-quality genomes from fungi, protists, and rotifers for cultivation-independent community analyses.

Scientific Applications:

  • Ecosystem and microbial community studies: Integrates eukaryotic sequences into metagenomic analyses to improve interpretation of microbial community dynamics and functions.
  • Genome-resolved environmental genomics: Enables cultivation-independent reconstruction of near-complete eukaryotic genomes from environmental samples such as geyser-associated microbial communities.
  • Metabolic response analysis: Detects metabolic shifts in eukaryotic populations under environmental perturbations, exemplified by changes after organic carbon addition (secreted proteases, lipases, CAZymes, methanol oxidation).
  • Taxonomic recovery across eukaryotes: Facilitates recovery and evaluation of genomes from diverse eukaryotes including fungi, protists, rotifers, and arthropods.

Methodology:

Classifies sequence fragments using a k-mer-based strategy to separate eukaryotic from prokaryotic sequences.

Topics

Details

License:
MIT
Tool Type:
command-line tool
Programming Languages:
Python
Added:
7/30/2025
Last Updated:
7/30/2025

Operations

Data Inputs & Outputs

Publications

West PT, Probst AJ, Grigoriev IV, Thomas BC, Banfield JF. Genome-reconstruction for eukaryotes from complex natural microbial communities. Genome Research. 2018;28(4):569-580. doi:10.1101/gr.228429.117. PMID:29496730. PMCID:PMC5880246.

Funding: - National Science Foundation: DGE 1106400 - Sloan Foundation: G-2016-20166041 - Office of Science of the US Department of Energy: DE-AC02-05CH11231 - German Science Foundation: DFG PR 1603/1-1