Consistency analysis of MiSeq sequencing data of 16S rRNA genes from different biotech companies

Abstract:

[Background] High-throughput sequencing technology has been widely used in the research field of environmental microbiology. Due to sequencing platform based on different principles, and personalized service biotech companies provided, huge amounts of various sequencing data are emerged. Although personalized service is good to meet customers’ different requirements, there is a widespread concern if the sequencing data from different sequencing platforms or different companies could be equally treated. [Objective] The aim of this study is to explore the impacts of different sequencing conditions and sequencing depths on the final sequencing data of the same sample using MiSeq sequencing platform, and further to find out the reasons for the differences, and the subsequent effects of these differences on the experimental data. [Methods] Sediment samples were collected from Songmenshan Region, Nanjishan, Raohe River and Baishazhou of the Poyang Lake. High-throughput sequencing of 16S rRNA gene V3?V4 region was performed in two biotech companies with different sequencing depths, and two sets of data were compared. [Results] Two sets of data showed highly similarity in microbial community structure, but the abundance difference between the rare species resulted in a different pattern in the PCoA and cluster analysis. Co-occurrence network revealed that the data with higher sequencing depth could reflect more complex interactions between and within microbial taxa. Some rare species such as Deferribacteres and Lentisphaerae were found to be important for the community eco-function. A total of 14 categories of differentiated metabolism were found between two datasets by METAGEN assist functional forecast method, including Atrazine metabolism, Chitin degradation, Sulfate reducer, Nitrogen fixation and so on. [Conclusion] The impacts of different sequencing environments on experimental data can be reduced or even eliminated by data quality control processes, but different sequencing depths have a significant impact on the sequencing data. Increasing the sequencing depth can significantly improve the richness of rare species, and thus supply a comprehensive knowledge of microbial community function.