Non-biological synthetic spike-in controls and the AMPtk software pipeline improve fungal high throughput amplicon sequencing data

High throughput amplicon sequencing (HTAS) of conserved regions of DNA has emerged as a powerful technique to characterize environmental communities. Depending on the taxa of interest, several molecular markers have been developed to use as templates for HTAS; small subunit (16S) rRNA, large subunit (LSU) rRNA, internal transcribed spacer (ITS) rRNA, or mitochondrial cytochrome oxidase 1 (mtCO1). A major challenge in analyzing HTAS experimental data is differentiating sequencing errors versus those of real biological sequence variation. One strategy that has been employed is the inclusion of spike-in mock communities as a tool to measure the accuracy of the sequencing platform and subsequent data processing. HTAS for identification of fungi via the ITS region requires a pipeline that can accurately deal with amplicons of variable length, variable GC content, and large homopolymer stretches. To assess the ability of sequencing platforms and data processing pipelines using fungal ITS amplicons, we created two fungal ITS spike-in control mock communities composed of single copy plasmid DNA; the biological mock community (BioMock) consists of cloned ITS sequences whereas the synthetic mock community (SynMock) consists of non-biological ITS-like sequences. Using these spike-in controls we show that pre-clustering steps for variable length amplicons are critically important. Additionally, a major source of bias is attributed to the primary DNA sequence of individuals as well as the initial PCR reaction, indicating that read abundances are not representative of fungal communities. These data indicate that using non-biological ITS-like sequences as a spike-in control allows for accurate estimation of data processing and identification of index-bleed (index-hopping or barcode crossover) between samples. Finally, we developed AMPtk (amplicon toolkit), a versatile software solution equipped to deal with variable length amplicons as well as a built-in method to quality filter HTAS data based on spike-in controls. While we describe herein a non-biological (synthetic) mock community for ITS sequences, the concept can be widely applied to any HTAS dataset.

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