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      Primer and platform effects on 16S rRNA tag sequencing.

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          Abstract

          Sequencing of 16S rRNA gene tags is a popular method for profiling and comparing microbial communities. The protocols and methods used, however, vary considerably with regard to amplification primers, sequencing primers, sequencing technologies; as well as quality filtering and clustering. How results are affected by these choices, and whether data produced with different protocols can be meaningfully compared, is often unknown. Here we compare results obtained using three different amplification primer sets (targeting V4, V6-V8, and V7-V8) and two sequencing technologies (454 pyrosequencing and Illumina MiSeq) using DNA from a mock community containing a known number of species as well as complex environmental samples whose PCR-independent profiles were estimated using shotgun sequencing. We find that paired-end MiSeq reads produce higher quality data and enabled the use of more aggressive quality control parameters over 454, resulting in a higher retention rate of high quality reads for downstream data analysis. While primer choice considerably influences quantitative abundance estimations, sequencing platform has relatively minor effects when matched primers are used. Beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.

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          Most cited references65

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          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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              QIIME allows analysis of high-throughput community sequencing data.

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                Author and article information

                Journal
                Front Microbiol
                Frontiers in microbiology
                Frontiers Media SA
                1664-302X
                1664-302X
                2015
                : 6
                Affiliations
                [1 ] Department of Energy Joint Genome Institute Walnut Creek, CA, USA ; National Research Council Canada Montreal, QC, Canada.
                [2 ] Department of Energy Joint Genome Institute Walnut Creek, CA, USA.
                [3 ] Illumina, Inc. San Francisco, CA, USA.
                [4 ] Department of Biology and Howard Hughes Medical Institute, Curriculum in Genetics and Molecular Biology, Department of Microbiology and Immunology, Carolina Center for Genome Sciences, University of North Carolina Chapel Hill, NC, USA.
                Article
                10.3389/fmicb.2015.00771
                4523815
                26300854
                631cf823-76f8-4da7-a3b9-335f44165130
                History

                16S rRNA gene sequencing,amplification,community assembly,high throughput sequencing,microbial diversity,microbial population and community ecology,sequencing error

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