Computational framework for high-quality production and large-scale evolutionary analysis of metagenome assembled genomes

Murovec, Boštjan (author), Deutsch, Leon (author), Stres, Blaž (author)

Microbial species play important roles in different environments and the production of high-quality genomes from metagenome data sets represents a major obstacle to understanding their ecological and evolutionary dynamics. Metagenome-Assembled Genomes Orchestra (MAGO) is a computational framework that integrates and simplifies metagenome assembly, binning, bin improvement, bin quality (completeness and contamination), bin annotation, and evolutionary placement of bins via detailed maximum-likelihood phylogeny based on multiple marker genes using different amino acid substitution models, next to average nucleotide identity analysis of genomes for delineation of species boundaries and operational taxonomic units. MAGO offers streamlined execution of the entire metagenomics pipeline, error checking, computational resource distribution and compatibility of data formats, governed by usertailored pipeline processing. MAGO is an open-source-software package released in three different ways, as a singularity image and a Docker container for HPC purposes as well as for running MAGO on a commodity hardware, and a virtual machine for gaining a full access to MAGO underlying structure and source code. MAGO is open to suggestions for extensions and is amenable for use in both research and teaching of genomics and molecular evolution of genomes assembled from small single-cell projects or large-scale and complex environmental metagenomes.

• Language: English
• Keywords: metagenomics, evolutionary analyses, microbial draft genomes, species boundaries, FastANI, genome assembly and binning
• Work type: Article
• Typology: 1.03 - Short Scientific Article
• Organization: FE - Faculty of Electrical Engineering; BF - Biotechnical Faculty; MF - Faculty of Medicine; FGG - Faculty of Civil and Geodetic Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2020
• Number of pages: Str. 593-598
• Numbering: Vol. 37, iss. 2
• PID: 20.500.12556/RUL-124366
• UDC: 579:575
• ISSN on article: 0737-4038
• DOI: 10.1093/molbev/msz237
• COBISS.SI-ID: 4315528
• Publication date in RUL: 18.01.2021

Record is a part of a journal

• Title: Molecular biology and evolution
• Publisher: Society for Molecular Biology and Evolution, Oxford University Press
• ISSN: 0737-4038
• COBISS.SI-ID: 236111

Licences

• License: CC BY-NC 4.0, Creative Commons Attribution-NonCommercial 4.0 International
• Link: http://creativecommons.org/licenses/by-nc/4.0/
• Description: A creative commons license that bans commercial use, but the users don’t have to license their derivative works on the same terms.
• Licensing start date: 01.02.2020

Secondary language

• Language: Slovenian
• Keywords: mikrobiologija, genetika, bioinformatika, MAGO