Genome-resolved metagenomics using environmental and clinical samples

Author:

Kayani Masood ur Rehman1ORCID,Huang Wanqiu2,Feng Ru1,Chen Lei1

Affiliation:

1. Center for Microbiota and Immunological Diseases, Shanghai General Hospital, Shanghai Institute of Immunology, Shanghai Jiao Tong University, School of Medicine, Shanghai 2,000,025, China

2. Shanghai Institute of Immunology, Shanghai Jiao Tong University, School of Medicine, Shanghai 200,000, China

Abstract

Abstract Recent advances in high-throughput sequencing technologies and computational methods have added a new dimension to metagenomic data analysis i.e. genome-resolved metagenomics. In general terms, it refers to the recovery of draft or high-quality microbial genomes and their taxonomic classification and functional annotation. In recent years, several studies have utilized the genome-resolved metagenome analysis approach and identified previously unknown microbial species from human and environmental metagenomes. In this review, we describe genome-resolved metagenome analysis as a series of four necessary steps: (i) preprocessing of the sequencing reads, (ii) de novo metagenome assembly, (iii) genome binning and (iv) taxonomic and functional analysis of the recovered genomes. For each of these four steps, we discuss the most commonly used tools and the currently available pipelines to guide the scientific community in the recovery and subsequent analyses of genomes from any metagenome sample. Furthermore, we also discuss the tools required for validation of assembly quality as well as for improving quality of the recovered genomes. We also highlight the currently available pipelines that can be used to automate the whole analysis without having advanced bioinformatics knowledge. Finally, we will highlight the most widely adapted and actively maintained tools and pipelines that can be helpful to the scientific community in decision making before they commence the analysis.

Funder

Shanghai Jiao Tong University, School of Medicine New PI Startup Fund

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

Reference227 articles.

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