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Metabarcoding is a powerful tool for exploring microbial diversity in the environment, but its accurate interpretation is impeded by diverse technical (e.g. PCR and sequencing errors) and biological biases (e.g. intra-individual polymorphism) that remain poorly understood. To help interpret environmental metabarcoding datasets, we investigated the intracellular diversity of the V4 and V9 regions of the 18S rRNA gene from Acantharia and Nassellaria (radiolarians) using 454 pyrosequencing. Individual cells of radiolarians were isolated, and PCRs were performed with generalist primers to amplify the V4 and V9 regions. Different denoising procedures were employed to filter the pyrosequenced raw amplicons (Acacia, AmpliconNoise, Linkage method). For each of the six isolated cells, an average of 541 V4 and 562 V9 amplicons assigned to radiolarians were obtained, from which one numerically dominant sequence and several minor variants were found. At the 97% identity, a diversity metrics commonly used in environmental surveys, up to 5 distinct OTUs were detected in a single cell. However, most amplicons grouped within a single OTU whereas other OTUs contained very few amplicons. Different analytical methods provided evidence that most minor variants forming different OTUs correspond to PCR and sequencing artifacts. Duplicate PCR and sequencing from the same DNA extract of a single cell had only 9 to 16% of unique amplicons in common, and alignment visualization of V4 and V9 amplicons showed that most minor variants contained substitutions in highly-conserved regions. We conclude that intracellular variability of the 18S rRNA in radiolarians is very limited despite its multi-copy nature and the existence of multiple nuclei in these protists. Our study recommends some technical guidelines to conservatively discard artificial amplicons from metabarcoding datasets, and thus properly assess the diversity and richness of protists in the environment.

Intracellular Diversity of the V4 and V9 Regions of the 18S rRNA in Marine Protists (Radiolarians) Assessed by High-Throughput Sequencing