Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency
1 Biodiversity Research Center, Academia Sinica, Taipei, 115, Taiwan
2 Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan
3 Research Center for Information Technology Innovation, Academia Sinica, Taipei, 115, Taiwan
4 Department of Computer Science and Information Engineering, National Taiwan University, Taipei, 106, Taiwan
BMC Bioinformatics 2010, 11:565 doi:10.1186/1471-2105-11-565Published: 18 November 2010
Investigation of metagenomes provides greater insight into uncultured microbial communities. The improvement in sequencing technology, which yields a large amount of sequence data, has led to major breakthroughs in the field. However, at present, taxonomic binning tools for metagenomes discard 30-40% of Sanger sequencing data due to the stringency of BLAST cut-offs. In an attempt to provide a comprehensive overview of metagenomic data, we re-analyzed the discarded metagenomes by using less stringent cut-offs. Additionally, we introduced a new criterion, namely, the evolutionary conservation of adjacency between neighboring genes. To evaluate the feasibility of our approach, we re-analyzed discarded contigs and singletons from several environments with different levels of complexity. We also compared the consistency between our taxonomic binning and those reported in the original studies.
Among the discarded data, we found that 23.7 ± 3.9% of singletons and 14.1 ± 1.0% of contigs were assigned to taxa. The recovery rates for singletons were higher than those for contigs. The Pearson correlation coefficient revealed a high degree of similarity (0.94 ± 0.03 at the phylum rank and 0.80 ± 0.11 at the family rank) between the proposed taxonomic binning approach and those reported in original studies. In addition, an evaluation using simulated data demonstrated the reliability of the proposed approach.
Our findings suggest that taking account of conserved neighboring gene adjacency improves taxonomic assignment when analyzing metagenomes using Sanger sequencing. In other words, utilizing the conserved gene order as a criterion will reduce the amount of data discarded when analyzing metagenomes.