A High-Throughput DNA Sequence Aligner for Microbial Ecology Studies

By Patrick D. Schloss. PLoS ONE, 2009

334 citations recorded by the source corpus.

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.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/69898e67ce21e28484e22c0089dd7c144d350c9a

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Citations in the corpus

SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes (2012, background): “That is, all identical bases sharing a column in the reference MSA are coalesced into one node.”
Intestinal domination and the risk of bacteremia in patients undergoing allogeneic hematopoietic stem cell transplantation. (2012, methodology): “Sequence data were screened and filtered for quality [17], then aligned to the full-length 16S rRNA gene, using as template the SILVA reference alignment [18].”
Assessing and Improving Methods Used in Operational Taxonomic Unit-Based Approaches for 16S rRNA Gene Sequence Analysis (2011, background): “Furthermore, NAST-based aligners have been parallelized and are capable of aligning 18 full-length sequences per second (19).”
Reducing the Effects of PCR Amplification and Sequencing Artifacts on 16S rRNA-Based Studies (2011, methodology): “Identification of chimeras and sequencing errors All reference and de novo sequences were aligned to a 50,000column wide SILVA-based reference alignment using mothur’s NAST-based aligner [39,40].”
The Effects of Alignment Quality, Distance Calculation Method, Sequence Filtering, and Region on the Analysis of 16S rRNA Gene-Based Studies (2010, methodology): “Visual inspection of the greengenes alignment suggests that in many instances the variable region alignments are somewhat random [11].”
25 years of serving the community with ribosomal RNA gene reference databases and tools. (2017, result): “Schloss and the results show that SILVA outcompetes both Greengenes and RDP (Schloss, 2009).”
Metagenomic biomarker discovery and explanation (2011, methodology): “All sequences were aligned using a NAST-based sequence aligner to a custom reference based on the SILVA alignment [106,107].”
The effects of intestinal tract bacterial diversity on mortality following allogeneic hematopoietic stem cell transplantation. (2014, methodology): “Sequence data were screened and filtered for quality(5) and then aligned to the full-length 16S rRNA gene, using as a template the SILVA reference alignment.(6) Sequences were grouped into operational taxonomic units of 97% similarity.”