Global change is disproportionately affecting cold environments (polar and high elevation regions), with potentially negative impacts on microbial diversity and functional processes. In most cold environments the combination of low temperatures, and physical stressors, such as katabatic wind episodes and limited water availability result in biotic systems, which are in trophic terms very simple and primarily driven by microbial communities. Metagenomic approaches have provided key insights on microbial communities in these systems and how they may adapt to stressors and contribute towards mediating crucial biogeochemical cycles. Here we review, the current knowledge regarding edaphic-based microbial diversity and functional processes in Antarctica, and the Artic. Such insights are crucial and help to establish a baseline for understanding the impact of climate change on Polar Regions.

Background

Metagenomics 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.

Results

To 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.

Conclusions

We 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.