The sequencing chips and kits of the Ion Torrent Personal Genome Machine (PGM), which employs semiconductor technology to measure pH changes in polymerization events, have recently been upgraded. The quality of PGM sequences has not been reassessed, and results have not been compared in the context of a gene-targeted microbial ecology study. To address this, we compared sequence profiles across available PGM chips and chemistries and with 454 pyrosequencing data by determining error types and rates and diazotrophic community structures. The PGM was then used to assess differences in nifH-harboring bacterial community structure among four corn-based cropping systems. Using our suggested filters from mock community analyses, the overall error rates were 0.62, 0.36, and 0.39% per base for chips 318 and 314 with the 400-bp kit and chip 318 with the Hi-Q chemistry, respectively. Compared with the 400-bp kit, the Hi-Q kit reduced indel rates by 28 to 59% and produced one to seven times more reads acceptable for downstream analyses. The PGM produced higher frameshift rates than pyrosequencing that were corrected by the RDP FrameBot tool. Significant differences among platforms were identified, although the diversity indices and overall site-based conclusions remained similar. For the cropping system analyses, a total of 6,182 unique NifH operational taxonomic units at 5% amino acid dissimilarity were obtained. The current crop type, as well as the crop rotation history, significantly influenced the composition of the soil diazotrophic community detected.
ASJC Scopus subject areas
- Food Science
- Applied Microbiology and Biotechnology