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Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences.

ABSTRACT: Microbial community profiling using 16S rRNA gene sequences requires accurate taxonomy assignments. 'Universal' primers target conserved sequences and amplify sequences from many taxa, but they provide variable coverage of different environments, and regions of the rRNA gene differ in taxonomic informativeness--especially when high-throughput short-read sequencing technologies (for example, 454 and Illumina) are used. We introduce a new evaluation procedure that provides an improved measure of expected taxonomic precision when classifying environmental sequence reads from a given primer. Applying this measure to thousands of combinations of primers and read lengths, simulating single-ended and paired-end sequencing, reveals that these choices greatly affect taxonomic informativeness. The most informative sequence region may differ by environment, partly due to variable coverage of different environments in reference databases. Using our Rtax method of classifying paired-end reads, we found that paired-end sequencing provides substantial benefit in some environments including human gut, but not in others. Optimal primer choice for short reads totaling 96 nt provides 82-100% of the confident genus classifications available from longer reads.

SUBMITTER: Soergel DA

PROVIDER: S-EPMC3379642 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences.

Soergel David A W DA Dey Neelendu N Knight Rob R Brenner Steven E SE

The ISME journal 20120112 7

Microbial community profiling using 16S rRNA gene sequences requires accurate taxonomy assignments. 'Universal' primers target conserved sequences and amplify sequences from many taxa, but they provide variable coverage of different environments, and regions of the rRNA gene differ in taxonomic informativeness--especially when high-throughput short-read sequencing technologies (for example, 454 and Illumina) are used. We introduce a new evaluation procedure that provides an improved measure of e ...[more]

PMID: 22237546

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Project description:Based on comparative phylogenetic analysis of 16S rRNA gene sequences deposited in an RDP database, we constructed a local database of thaumarchaeotal 16S rRNA gene sequences and developed a novel PCR primer specific for the archaeal phylum Thaumarchaeota. Among 9,727 quality-filtered (chimeral-checked, size >1.2 kb) archaeal sequences downloaded from the RDP database, 1,549 thaumarchaeotal sequences were identified and included in our local database. In our study, Thaumarchaeota included archaeal groups MG-I, SAGMCG-I, SCG, FSCG, RC, and HWCG-III, forming a monophyletic group in the phylogenetic tree. Cluster analysis revealed 114 phylotypes for Thaumarchaeota. The majority of the phylotypes (66.7%) belonged to the MG-I and SCG, which together contained most (93.9%) of the thaumarchaeotal sequences in our local database. A phylum-directed primer was designed from a consensus sequence of the phylotype sequences, and the primer's specificity was evaluated for coverage and tolerance both in silico and empirically. The phylum-directed primer, designated THAUM-494, showed >90% coverage for Thaumarchaeota and <1% tolerance to non-target taxa, indicating high specificity. To validate this result experimentally, PCRs were performed with THAUM-494 in combination with a universal archaeal primer (ARC917R or 1017FAR) and DNAs from five environmental samples to construct clone libraries. THAUM-494 showed a satisfactory specificity in empirical studies, as expected from the in silico results. Phylogenetic analysis of 859 cloned sequences obtained from 10 clone libraries revealed that >95% of the amplified sequences belonged to Thaumarchaeota. The most frequently sampled thaumarchaeotal subgroups in our samples were SCG, MG-I, and SAGMCG-I. To our knowledge, THAUM-494 is the first phylum-level primer for Thaumarchaeota. Furthermore, the high coverage and low tolerance of THAUM-494 will make it a potentially valuable tool in understanding the phylogenetic diversity and ecological niche of Thaumarchaeota.

Project description:Background. 16S rRNA gene sequences are routinely assigned to operational taxonomic units (OTUs) that are then used to analyze complex microbial communities. A number of methods have been employed to carry out the assignment of 16S rRNA gene sequences to OTUs leading to confusion over which method is optimal. A recent study suggested that a clustering method should be selected based on its ability to generate stable OTU assignments that do not change as additional sequences are added to the dataset. In contrast, we contend that the quality of the OTU assignments, the ability of the method to properly represent the distances between the sequences, is more important. Methods. Our analysis implemented six de novo clustering algorithms including the single linkage, complete linkage, average linkage, abundance-based greedy clustering, distance-based greedy clustering, and Swarm and the open and closed-reference methods. Using two previously published datasets we used the Matthew's Correlation Coefficient (MCC) to assess the stability and quality of OTU assignments. Results. The stability of OTU assignments did not reflect the quality of the assignments. Depending on the dataset being analyzed, the average linkage and the distance and abundance-based greedy clustering methods generated OTUs that were more likely to represent the actual distances between sequences than the open and closed-reference methods. We also demonstrated that for the greedy algorithms VSEARCH produced assignments that were comparable to those produced by USEARCH making VSEARCH a viable free and open source alternative to USEARCH. Further interrogation of the reference-based methods indicated that when USEARCH or VSEARCH were used to identify the closest reference, the OTU assignments were sensitive to the order of the reference sequences because the reference sequences can be identical over the region being considered. More troubling was the observation that while both USEARCH and VSEARCH have a high level of sensitivity to detect reference sequences, the specificity of those matches was poor relative to the true best match. Discussion. Our analysis calls into question the quality and stability of OTU assignments generated by the open and closed-reference methods as implemented in current version of QIIME. This study demonstrates that de novo methods are the optimal method of assigning sequences into OTUs and that the quality of these assignments needs to be assessed for multiple methods to identify the optimal clustering method for a particular dataset.

Dataset Information

Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences.

Publications

Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences.

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