Abstract
The advent of next generation sequencing has coincided with a growth in interest in using these approaches to better understand the role of the structure and function of the microbial communities in human, animal, and environmental health. Yet, use of next generation sequencing to perform 16S rRNA gene sequence surveys has resulted in considerable controversy surrounding the effects of sequencing errors on downstream analyses. We analyzed 2.7×106 reads distributed among 90 identical mock community samples, which were collections of genomic DNA from 21 different species with known 16S rRNA gene sequences; we observed an average error rate of 0.0060. To improve this error rate, we evaluated numerous methods of identifying bad sequence reads, identifying regions within reads of poor quality, and correcting base calls and were able to reduce the overall error rate to 0.0002. Implementation of the PyroNoise algorithm provided the best combination of error rate, sequence length, and number of sequences. Perhaps more problematic than sequencing errors was the presence of chimeras generated during PCR. Because we knew the true sequences within the mock community and the chimeras they could form, we identified 8% of the raw sequence reads as chimeric. After quality filtering the raw sequences and using the Uchime chimera detection program, the overall chimera rate decreased to 1%. The chimeras that could not be detected were largely responsible for the identification of spurious operational taxonomic units (OTUs) and genus-level phylotypes. The number of spurious OTUs and phylotypes increased with sequencing effort indicating that comparison of communities should be made using an equal number of sequences. Finally, we applied our improved quality-filtering pipeline to several benchmarking studies and observed that even with our stringent data curation pipeline, biases in the data generation pipeline and batch effects were observed that could potentially confound the interpretation of microbial community data.
Highlights
The advent of 16S rRNA gene sequencing has revolutionized how microbial ecologists understand the bacterial and archaeal world around them [1]
The distribution of quality scores for substitutions was bimodal suggesting that the lower quality substitutions were sequencing errors and the higher quality substitutions were due to PCR artifacts or chimeras whose parent sequences were from different operons in the same genome and were not detected by our approach because they were less than 3 bp different from each other (Fig. 2C)
Using the sequencing runs originating from Baylor College of Medicine (BCM), Broad Institute (BI), and JCVI, we found that 5.5% of the raw sequence reads were chimeric
Summary
The advent of 16S rRNA gene sequencing has revolutionized how microbial ecologists understand the bacterial and archaeal world around them [1]. A limitation of this approach is that it is not possible to obtain a full-length sequence of the 16S rRNA gene To overcome this limitation, PCR primers have been designed to target one or more of the 9 variable regions within the gene; there is no region that has received universal acceptance by the field. The creation of DNA barcodes, short DNA sequences are included upstream of the PCR primer, has enabled investigators to multiplex numerous samples has enabled investigators to allocate vast sequencing resources to numerous samples [3]. These improvements allow for more robust experimental designs; whereas biological or technical replicates were rarely obtained using Sanger technology, it has since become expected [4]
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