TY - JOUR
T1 - A review of computational tools for generating metagenome-assembled genomes from metagenomic sequencing data
AU - YANG, Chao
AU - CHOWDHURY, Debajyoti
AU - ZHANG, Zhenmiao
AU - CHEUNG, William Kwok Wai
AU - LYU, Aiping
AU - BIAN, Zhaoxiang
AU - ZHANG, Lu
N1 - supported by a Research Grant Council Early Career Scheme (HKBU 22201419), an IRCMS HKBU (No. IRCMS/19-20/D02), an HKBU Start-up Grant Tier 2 (RC-SGT2/19-20/SCI/007), two grants from the Guangdong Basic and Applied Basic Research Foundation (No. 2019A1515011046 and No. 2021A1515012226).
Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
PY - 2021/11/29
Y1 - 2021/11/29
N2 - Metagenomic sequencing provides a culture-independent avenue to investigate the complex microbial communities by constructing metagenome-assembled genomes (MAGs). A MAG represents a microbial genome by a group of sequences from genome assembly with similar characteristics. It enables us to identify novel species and understand their potential functions in a dynamic ecosystem. Many computational tools have been developed to construct and annotate MAGs from metagenomic sequencing, however, there is a prominent gap to comprehensively introduce their background and practical performance. In this paper, we have thoroughly investigated the computational tools designed for both upstream and downstream analyses, including metagenome assembly, metagenome binning, gene prediction, functional annotation, taxonomic classification, and profiling. We have categorized the commonly used tools into unique groups based on their functional background and introduced the underlying core algorithms and associated information to demonstrate a comparative outlook. Furthermore, we have emphasized the computational requisition and offered guidance to the users to select the most efficient tools. Finally, we have indicated current limitations, potential solutions, and future perspectives for further improving the tools of MAG construction and annotation. We believe that our work provides a consolidated resource for the current stage of MAG studies and shed light on the future development of more effective MAG analysis tools on metagenomic sequencing.
AB - Metagenomic sequencing provides a culture-independent avenue to investigate the complex microbial communities by constructing metagenome-assembled genomes (MAGs). A MAG represents a microbial genome by a group of sequences from genome assembly with similar characteristics. It enables us to identify novel species and understand their potential functions in a dynamic ecosystem. Many computational tools have been developed to construct and annotate MAGs from metagenomic sequencing, however, there is a prominent gap to comprehensively introduce their background and practical performance. In this paper, we have thoroughly investigated the computational tools designed for both upstream and downstream analyses, including metagenome assembly, metagenome binning, gene prediction, functional annotation, taxonomic classification, and profiling. We have categorized the commonly used tools into unique groups based on their functional background and introduced the underlying core algorithms and associated information to demonstrate a comparative outlook. Furthermore, we have emphasized the computational requisition and offered guidance to the users to select the most efficient tools. Finally, we have indicated current limitations, potential solutions, and future perspectives for further improving the tools of MAG construction and annotation. We believe that our work provides a consolidated resource for the current stage of MAG studies and shed light on the future development of more effective MAG analysis tools on metagenomic sequencing.
KW - Metagenomic sequencing
KW - Metagenome-assembled genomes
KW - Genome assembly
KW - Metagenome binning
KW - Gene prediction
KW - Gene functional annotation
KW - Taxonomic classification
KW - Microbial abundance profiling
U2 - 10.1016/j.csbj.2021.11.028
DO - 10.1016/j.csbj.2021.11.028
M3 - Review article
SN - 2001-0370
VL - 19
SP - 6301
EP - 6314
JO - Computational and Structural Biotechnology Journal
JF - Computational and Structural Biotechnology Journal
ER -