Massive partial sequencing of 16S rRNA genes has become the predominant tool used for studying microbial ecology. However, determining which hypervariable regions and primer sets should be used for screening microbial communities requires extensive investigation if controversial results are to be avoided. Here, the performances of different variable regions of the 16S rRNA gene on bacterial diversity studies were evaluated in silico with respect to the SILVA non-redundant reference database (SILVA SSU Ref 123NR), and subsequently verified using samples from Lake Taihu in China, a eutrophic lake. We found that the bacterial community composition results were strongly impacted by the different V regions. The results show that V1-V2 and V1-V3 regions were the most reliable regions in the full-length 16S rRNA sequences, while most V3 to V6 regions (including V3, V4, V3-V4, V5, V4-V5, V6, V3-V6, V4-V6, and V5-V6) were more closely aligned with the SILVA SSU Ref 123NR database. Overall, V4 was the most prominent V region for achieving good domain specificity, higher coverage and a broader spectrum in the Bacteria domain, as confirmed by the validation experiments. S-D-Bact-0564-a-S-15/S-D-Bact-0785-b-A-18 is, therefore, a promising primer set for surveying bacterial diversity in eutrophic lakes.
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http://dx.doi.org/10.1016/j.scitotenv.2017.09.228 | DOI Listing |
Int J Syst Evol Microbiol
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Department of Biology, Slippery Rock University, Slippery Rock, Pennsylvania, 16057, USA.
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Department of Microbiology and Cell Biology, Montana State University, Bozeman, Montana, USA.
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Laboratory of Microbiology and Immunology, School of Basic Medical Science, Inner Mongolia Medical University, Hohhot, China.
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