Microbial diversity in sediment or soil environments is very high, but the exact number of the taxa richness remains elusive . The estimated bacterial species ranged from nearly 103  to over 106  in a gram of sediment sample. Nevertheless, the figure has never been verified because of the low throughput of the traditional 16 S rRNA clone library method. Determining 16 S rRNA short variable tags using the pyrosequencing provided an unprecedented sequencing depth with tens to hundreds of thousands of tags per sample [4, 5], and the method regenerated people's interest in measuring and comparing the microbial taxa richness in various samples [6–8]. Nevertheless, two major types of problems about the 16 S rRNA pyrosequencing process were shortly revealed.
One was that, in any determined samples, the rarefaction curve, particularly for the unique operational taxonomy units (OTU) (100% similarity), never approached asymptotic. The highest number of sequences for a single sample (442,058) was performed on a deep marine biosphere, but the rarefaction curve of the 0.03 distance OTU (97% similarity) was still increasing steeply . The ever-increasing number of different tags either reflects a real microbial taxa richness being detectable only with a higher sequencing effort, or they are artifacts produced by PCR or sequencing processes. Recently, Quince et al. (2009) found that the base calling error of the pyrosequencing method significantly increased the number of novel unique sequences. Consequently, the escalating number of the unique tag, particularly the singletons (tags occur only once) , might be produced mainly from experimental artifacts of pyrosequencing, rather than from the true diversity; and the pyrosequencing method was suggested to overestimate the taxa richness accordingly [10, 11].
The other type of problems was that the microbial diversity might be skewed by experimental procedures, particularly by PCR. Studies suggested that the PCR primer and amplicon length affected the estimation of species richness and evenness [12, 13], and the primers missed half of rRNA microbial diversity . In addition to primers, the effect of some other PCR conditions, like PCR cycle number, annealing temperature et al., have been evaluated with the traditional 16 S rRNA clone library or fingerprinting methods [9, 14–16], but their effects have never been assessed with any next generation sequencing approach yet.
Very recently, we developed a barcoded Illumina paired end sequencing (BIPES) method to determine the 16 S rRNA V6 tags by pair end sequencing strategy on another next generation sequencing platform, the Illumina systems . In the present study, we report our evaluation of three PCR conditions, namely template dilution, PCR cycle number and polymerase, on the V6 microbial diversity analysis.