Biases in genome reconstruction from metagenomic data

Nelson, William C.; Tully, Benjamin J.; Mobberley, Jennifer M.

doi:10.7717/peerj.10119

Biases in genome reconstruction from metagenomic data

Journal Article · Fri Oct 30 00:00:00 EDT 2020 · PeerJ

DOI:https://doi.org/10.7717/peerj.10119· OSTI ID:1693794

^[1]; ^[2]; ^[3]

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
Department of Biological Sciences, Marine Environmental Biology Section, University of Southern California, Los Angeles, CA, USA, Center for Dark Energy Biosphere Investigations, University of Southern California, Los Angeles, CA, USA
Chemical and Biological Signature Science Group, Pacific Northwest National Laboratory, Richland, WA, USA

Background

Advances in sequencing, assembly, and assortment of contigs into species-specific bins has enabled the reconstruction of genomes from metagenomic data (MAGs). Though a powerful technique, it is difficult to determine whether assembly and binning techniques are accurate when applied to environmental metagenomes due to a lack of complete reference genome sequences against which to check the resulting MAGs.

Methods

We compared MAGs derived from an enrichment culture containing ~20 organisms to complete genome sequences of 10 organisms isolated from the enrichment culture. Factors commonly considered in binning software—nucleotide composition and sequence repetitiveness—were calculated for both the correctly binned and not-binned regions. This direct comparison revealed biases in sequence characteristics and gene content in the not-binned regions. Additionally, the composition of three public data sets representing MAGs reconstructed from the Tara Oceans metagenomic data was compared to a set of representative genomes available through NCBI RefSeq to verify that the biases identified were observable in more complex data sets and using three contemporary binning software packages.

Results

Repeat sequences were frequently not binned in the genome reconstruction processes, as were sequence regions with variant nucleotide composition. Genes encoded on the not-binned regions were strongly biased towards ribosomal RNAs, transfer RNAs, mobile element functions and genes of unknown function. Our results support genome reconstruction as a robust process and suggest that reconstructions determined to be >90% complete are likely to effectively represent organismal function; however, population-level genotypic heterogeneity in natural populations, such as uneven distribution of plasmids, can lead to incorrect inferences.

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Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: Center for Dark Energy Biosphere Investigations; USDOE

Grant/Contract Number:: AC02-05CH11231; AC05-76RL01830

OSTI ID:: 1693794

Alternate ID(s):: OSTI ID: 1706676

Report Number(s):: PNNL-SA--151193; e10119

Journal Information:: PeerJ, Journal Name: PeerJ Vol. 8; ISSN 2167-8359

Publisher:: PeerJ Inc.Copyright Statement

Country of Publication:: United States

Language:: English

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