Hybrid-denovo: a de novo OTU-picking pipeline integrating single-end and paired-end 16S sequence tags

Gigascience. 2018 Mar 1;7(3):1-7. doi: 10.1093/gigascience/gix129.

Abstract

Background: Illumina paired-end sequencing has been increasingly popular for 16S rRNA gene-based microbiota profiling. It provides higher phylogenetic resolution than single-end reads due to a longer read length. However, the reverse read (R2) often has significant low base quality, and a large proportion of R2s will be discarded after quality control, resulting in a mixture of paired-end and single-end reads. A typical 16S analysis pipeline usually processes either paired-end or single-end reads but not a mixture. Thus, the quantification accuracy and statistical power will be reduced due to the loss of a large amount of reads. As a result, rare taxa may not be detectable with the paired-end approach, or low taxonomic resolution will result in a single-end approach.

Results: To have both the higher phylogenetic resolution provided by paired-end reads and the higher sequence coverage by single-end reads, we propose a novel OTU-picking pipeline, hybrid-denovo, that can process a hybrid of single-end and paired-end reads. Using high-quality paired-end reads as a gold standard, we show that hybrid-denovo achieved the highest correlation with the gold standard and performed better than the approaches based on paired-end or single-end reads in terms of quantifying the microbial diversity and taxonomic abundances. By applying our method to a rheumatoid arthritis (RA) data set, we demonstrated that hybrid-denovo captured more microbial diversity and identified more RA-associated taxa than a paired-end or single-end approach.

Conclusions: Hybrid-denovo utilizes both paired-end and single-end 16S sequencing reads and is recommended for 16S rRNA gene targeted paired-end sequencing data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology
  • High-Throughput Nucleotide Sequencing
  • Microbiota / genetics*
  • Phylogeny*
  • RNA, Ribosomal, 16S / genetics*
  • Sequence Analysis, DNA / methods*

Substances

  • RNA, Ribosomal, 16S