Jorg

Jorg circularizes microbial genomes assembled from metagenomic datasets to confirm genome completeness and enable genomic-context and metabolic-inference studies.


Key Features:

  • Circular Genome Assembly: Facilitates circularization of microbial genomes to confirm completeness and integrity, provide scaffolds for future assemblies, recover complete gene content, minimize contamination, study synteny, and link protein-coding genes with ribosomal RNA genes.
  • Iterative Methodology: Employs an iterative approach combining assembly, binning, and read mapping to improve circularization accuracy and to identify potential misassemblies arising from k-mer-based assemblies.
  • Focus on Candidate Phyla Radiation (CPR) and other small genomes: Applied to small genomes with single ribosomal RNA operons, including successful circularization of 34 CPR genomes and additional genomes from Margulisbacteria, Chloroflexi, and megaphages.
  • Exposure of Novel Insights: Enables detection of genomic features such as non-operonic ribosomal genes in most CPR species and diverged forms of RNase P RNA.

Scientific Applications:

  • Reference Collection Building: Produces circularized genomes that can be used to build reference collections serving as scaffolds for future genomic assemblies.
  • Genomic Context Studies: Enables analysis of synteny and gene organization within complete circular genomes.
  • Metabolic Inference Linkage: Allows linking of protein-coding genes to ribosomal RNA genes to support metabolic inference based on 16S rRNA gene sequencing.

Methodology:

Uses a semi-automated, iterative process of assembly, binning, and read mapping that identifies potential k-mer-derived misassemblies and is effective for small genomes with a single ribosomal RNA operon.

Topics

Details

License:
GPL-3.0
Tool Type:
command-line tool
Programming Languages:
Shell
Added:
10/4/2021
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

De-novo assembly

Publications

Lui LM, Nielsen TN, Arkin AP. A method for achieving complete microbial genomes and improving bins from metagenomics data. PLOS Computational Biology. 2021;17(5):e1008972. doi:10.1371/journal.pcbi.1008972. PMID:33961626. PMCID:PMC8172020.

PMID: 33961626
PMCID: PMC8172020
Funding: - Joint Genome Institute: DE-AC02-05CH11231 - National Energy Research Scientific Computing Center: DE-AC02-05CH11231 - U.S. Department of Energy Office of Science User Facilities: DE-AC02-05CH11231