Assembling metagenomes, one community at a time

BMC Genomics

Research Article

Oleg Reva¹  Don Arthur Cowan²  Marc Warwick van Goethem²  Jean-Baptiste Ramond²  Thulani Peter Makhalanyane²  Andries Johannes van der Walt³ 

[1] Centre for Bioinformatics and Computational Biology, Department of Biochemistry, University of Pretoria, Pretoria, South Africa;Centre for Microbial Ecology and Genomics (CMEG), Department of Genetics, University of Pretoria, Natural Sciences Building 2, Lynnwood Road, 0028, Pretoria, South Africa;Centre for Microbial Ecology and Genomics (CMEG), Department of Genetics, University of Pretoria, Natural Sciences Building 2, Lynnwood Road, 0028, Pretoria, South Africa;Centre for Bioinformatics and Computational Biology, Department of Biochemistry, University of Pretoria, Pretoria, South Africa;

关键词: Metagenome assembly;    Microbial ecology;    Ilumina HiSeq;    Assembler;    Bioinformatics;   

DOI  :  10.1186/s12864-017-3918-9

 received in 2017-04-04, accepted in 2017-07-02,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundMetagenomics allows unprecedented access to uncultured environmental microorganisms. The analysis of metagenomic sequences facilitates gene prediction and annotation, and enables the assembly of draft genomes, including uncultured members of a community. However, while several platforms have been developed for this critical step, there is currently no clear framework for the assembly of metagenomic sequence data.ResultsTo assist with selection of an appropriate metagenome assembler we evaluated the capabilities of nine prominent assembly tools on nine publicly-available environmental metagenomes, as well as three simulated datasets. Overall, we found that SPAdes provided the largest contigs and highest N50 values across 6 of the 9 environmental datasets, followed by MEGAHIT and metaSPAdes. MEGAHIT emerged as a computationally inexpensive alternative to SPAdes, assembling the most complex dataset using less than 500 GB of RAM and within 10 hours.ConclusionsWe found that assembler choice ultimately depends on the scientific question, the available resources and the bioinformatic competence of the researcher. We provide a concise workflow for the selection of the best assembly tool.

【 授权许可】

CC BY   
© The Author(s). 2017