Biases in genome reconstruction from metagenomic data

Author:

Nelson William C.1ORCID,Tully Benjamin J.23ORCID,Mobberley Jennifer M.4ORCID

Affiliation:

1. Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA

2. Department of Biological Sciences, Marine Environmental Biology Section, University of Southern California, Los Angeles, CA, USA

3. Center for Dark Energy Biosphere Investigations, University of Southern California, Los Angeles, CA, USA

4. Chemical and Biological Signature Science Group, Pacific Northwest National Laboratory, Richland, WA, USA

Abstract

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.

Funder

U.S. Department of Energy

Office of Biological and Environmental Research

BER’s Genomic Science Program

Pacific Northwest National Laboratory

Battelle Memorial Institute

DOE Joint Genome Institute

Community Science Project 701

Center for Dark Energy Biosphere Investigations

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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