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bioRxiv · 10.1101/320986

Evaluating the information content of shallow shotgun metagenomics

Abstract

Although microbial communities are associated with many aspects of human, environmental, plant, and animal health, there exists no cost-effective method for precisely characterizing species and genes present in such communities. While deep whole-genome shotgun (WGS) sequencing provides the highest-level of taxonomic and functional resolution, it is often prohibitively expensive for large-scale studies. The prevailing alternative, high-throughput 16S rRNA gene amplicon sequencing (16S), often does not resolve taxonomy past the genus level and provides only moderately accurate predictions of the functional profile; thus, there is currently no widely accepted approach to affordable, high-resolution, taxonomic and functional microbiome analysis. To address this technology gap, we evaluated the information content of shallow shotgun sequencing with as low as 0.5 million sequences per sample as an alternative to 16S sequencing for large human microbiome studies. We describe a library preparation protocol enabling shallow shotgun sequencing at approximately the same per-sample cost as 16S. We analyzed multiple real and simulated biological data sets, including two novel human stool samples with ultra-deep sequencing of 2.5 billion sequences per sample, and found that shallow shotgun recovers accurate species-level taxonomic and functional profiles of the human microbiome. We recognize and discuss some of the inherent limitations of shallow shotgun sequencing, and note that 16S sequencing remains a valuable and important method for taxonomic profiling of novel environments. Although deep WGS remains the gold standard for high-resolution microbiome analysis, we recommend that researchers consider shallow shotgun sequencing as a useful alternative to 16S for large-scale human microbiome research studies.

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BibTeXRIS

Hillmann, B., Al-Ghalith, G. A., Shields-Cutler, R., Zhu, Q., Gohl, D., Beckman, K. B., Knight, R., Knights, D.. 2018-05-12. Evaluating the information content of shallow shotgun metagenomics. https://doi.org/10.1101/320986

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