Exploring Pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology

PLoS One. 2012;7(11):e49202. doi: 10.1371/journal.pone.0049202. Epub 2012 Nov 21.

Abstract

High throughput sequencing technologies are revolutionizing genetic research. With this "rise of the machines", genomic sequences can be obtained even for unknown genomes within a short time and for reasonable costs. This has enabled evolutionary biologists studying genetically unexplored species to identify molecular markers or genomic regions of interest (e.g. micro- and minisatellites, mitochondrial and nuclear genes) by sequencing only a fraction of the genome. However, when using such datasets from non-model species, it is possible that DNA from non-target contaminant species such as bacteria, viruses, fungi, or other eukaryotic organisms may complicate the interpretation of the results. In this study we analysed 14 genomic pyrosequencing libraries of aquatic non-model taxa from four major evolutionary lineages. We quantified the amount of suitable micro- and minisatellites, mitochondrial genomes, known nuclear genes and transposable elements and searched for contamination from various sources using bioinformatic approaches. Our results show that in all sequence libraries with estimated coverage of about 0.02-25%, many appropriate micro- and minisatellites, mitochondrial gene sequences and nuclear genes from different KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways could be identified and characterized. These can serve as markers for phylogenetic and population genetic analyses. A central finding of our study is that several genomic libraries suffered from different biases owing to non-target DNA or mobile elements. In particular, viruses, bacteria or eukaryote endosymbionts contributed significantly (up to 10%) to some of the libraries analysed. If not identified as such, genetic markers developed from high-throughput sequencing data for non-model organisms may bias evolutionary studies or fail completely in experimental tests. In conclusion, our study demonstrates the enormous potential of low-coverage genome survey sequences and suggests bioinformatic analysis workflows. The results also advise a more sophisticated filtering for problematic sequences and non-target genome sequences prior to developing markers.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Bacteria / genetics
  • Cell Nucleus / genetics
  • Contig Mapping
  • DNA / genetics
  • DNA, Mitochondrial / genetics
  • Data Collection*
  • Databases, Genetic
  • Evolution, Molecular*
  • Gene Library
  • Genes, Mitochondrial / genetics
  • Genetic Markers
  • Genome / genetics*
  • Genome Size / genetics
  • Genome, Mitochondrial / genetics
  • Microsatellite Repeats / genetics
  • RNA, Ribosomal / genetics
  • Sequence Analysis, DNA
  • Viral Proteins / genetics

Substances

  • DNA, Mitochondrial
  • Genetic Markers
  • RNA, Ribosomal
  • Viral Proteins
  • DNA

Grant support

FL and CM were supported by German Research Foundation (DFG) grants LE 2323/2 and MA 3684/3 within the DFG priority programme (SPP) 1158. FL was furthermore supported by a European Science Foundation “Frontiers of Speciation Research“ exchange grant to Cambridge, UK. CJS was supported by an Antarctic Science Bursary grant. CDS and NTR were supported by DFG grants 1460/3, 1460/8, by Jürgen Heinze, and by a student scholarship of The Crustacean Society to NTR. KL and JJ were supported by Consortium Grant (NE/DO1249X/1) and the British Antarctic Survey Polar Science for Planet Earth Programme both funded by The Natural Environment Research Council. JD was supported by DFG grant RA 1688/2. SS was supported by a scheme to support specific activities of doctoral students of the rectorate of the Ruhr University Bochum. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.