A high-throughput DNA sequence aligner for microbial ecology studies - PubMed (original) (raw)

A high-throughput DNA sequence aligner for microbial ecology studies

Patrick D Schloss. PLoS One. 2009.

Abstract

As the scope of microbial surveys expands with the parallel growth in sequencing capacity, a significant bottleneck in data analysis is the ability to generate a biologically meaningful multiple sequence alignment. The most commonly used aligners have varying alignment quality and speed, tend to depend on a specific reference alignment, or lack a complete description of the underlying algorithm. The purpose of this study was to create and validate an aligner with the goal of quickly generating a high quality alignment and having the flexibility to use any reference alignment. Using the simple nearest alignment space termination algorithm, the resulting aligner operates in linear time, requires a small memory footprint, and generates a high quality alignment. In addition, the alignments generated for variable regions were of as high a quality as the alignment of full-length sequences. As implemented, the method was able to align 18 full-length 16S rRNA gene sequences and 58 V2 region sequences per second to the 50,000-column SILVA reference alignment. Most importantly, the resulting alignments were of a quality equal to SILVA-generated alignments. The aligner described in this study will enable scientists to rapidly generate robust multiple sequences alignments that are implicitly based upon the predicted secondary structure of the 16S rRNA molecule. Furthermore, because the implementation is not connected to a specific database it is easy to generalize the method to reference alignments for any DNA sequence.

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Conflict of interest statement

Competing Interests: The author has declared that no competing interests exist.

Figures

Figure 1

Figure 1. Flowchart describing the alignment algorithm.

The published and current greengenes aligner algorithm is shown in black and the modifications that were tested in this study are shown in blue.

Figure 2

Figure 2. Comparison of alignments generated by the RDP, greengenes, and SILVA databases.

Alignments were taken between positions 60 and 113 of the E. coli 16S rRNA gene sequence for E. coli and four Enteroccocus spp. The alignment generated for these sequences within this region using 8-mers and the Needleman-Wunsch algorithm was identical to that found in the SILVA alignment. The lower-case bases in the RDP alignment indicate unaligned positions. For the greengenes and SILVA alignments, yellow-highlighting represents bases that are predicted to form traditional Watson-Crick base-pairs in the secondary structure, gray-highlighting represents weak base-pairs, black-highlighting represents bases that will not form base-pairs, and a lack of highlighting represents bases that are predicted to be in loop structures.

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