Effects of intragenomic polymorphism in the SSU rRNA gene on estimating marine microeukaryotic diversity: A test for ciliates using single‐cell high‐throughput DNA sequencing

Abstract

Diversity assessments using the small subunit (SSU) rRNA gene allow for rapid assessments of microeukaryotic communities. Yet, for microeukaryotes, only limited information is available on the extent to which sequence variations within individual genomes exist at this locus. We investigated 14 marine species belonging to four major ciliate groups by single‐cell high‐throughput DNA sequencing to estimate the extent of intragenomic polymorphism in the V4 region of the SSU rRNA gene. Based on these results, we evaluated the potential effect of polymorphism on metabarcoding studies. The intragenomic variability was generally below 3% among about 1000 unique sequences obtained from each studied cell, except of Protocruzia sp., whose intragenomic variability was as high as 15.6% among about 2000 unique sequences. Intragenomic variations significantly correlated with the number of macronuclei, but not with the biovolume of cell or macronuclei, indicating the occurrence of nonuniform evolution within the macronuclei. The removal of rare unique sequences greatly decreased the number of variations. For diversity studies, we therefore propose to conservatively discard rare amplicons. Considering the intragenomic variation within the V4 region, a sequence similarity cutoff of 3% to delimit marine ciliate operational taxonomic units could be substantiated, as at least this threshold could exclude most effect of intragenomic polymorphisms, although it may be too strict for some particular groups.

Genetic Diversity in Marine Planktonic Ciliates (Alveolata, Ciliophora) Suggests Distinct Geographical Patterns – Data From Chinese and European Coastal Waters

“…In the present study, the number of supposed 'minor' amplicon variants surpasses by far the findings obtained from sequencing up to three conspecific specimens and subsequent cloning steps in most major ciliate groups (Gong et al, 2013;Wang et al, 2017Wang et al, , 2019. We agree with these and previous studies that most genetic diversity originates from the high number of low-divergent sequence variants present in individuals of single ciliate species (Forster et al, 2019;Zhao et al, 2019). OTU clustering by Swarm in combination with second-level clustering turned out to represent an elegant solution to this problem, since the approach allows for inferring species-specific thresholds (Forster et al, 2019;Wang et al, 2019;Zhao et al, 2019).…”

“…We agree with these and previous studies that most genetic diversity originates from the high number of low-divergent sequence variants present in individuals of single ciliate species (Forster et al, 2019;Zhao et al, 2019). OTU clustering by Swarm in combination with second-level clustering turned out to represent an elegant solution to this problem, since the approach allows for inferring species-specific thresholds (Forster et al, 2019;Wang et al, 2019;Zhao et al, 2019).…”

“…Evaluating the properties of the internal network structure distinctively increases the resolution of diversity down to single nucleotide differences and, therefore allows unprecedented insights into genetic diversity and geographical distribution patterns. Investigations of intraspecific genetic diversity are especially important within ciliates, which exhibit high copy numbers and sequence variation even within individual specimens (Gong et al, 2013;Wang et al, 2017;Zhao et al, 2019). An additional second-level clustering of Swarm OTUs enables an efficient differentiation of genetically divergent sequences into species-specific network sequence clusters.…”

“…This strategy thus allows for a closer approximation between morphospecies and OTUs, i.e., a better estimation of the real species diversity from metabarcoding datasets (Forster et al, 2019). Owing to differences in evolutionary rates, however, a refinement of the similarity cut-off values for particular lineages is required (Wang et al, 2019;Zhao et al, 2019).…”

Dataset complexity impacts both MOTU delimitation and biodiversity estimates in eukaryotic 18S rRNA metabarcoding studies

“…While some of these artefacts can be detected and bioinformatically eliminated via the incorporation of rigorous control samples (e.g., DNA extraction blanks, PCR negative controls, and mock community standards, (Alberdi et al, 2018;Deiner et al, 2017;Hornung et al, 2019)) and data cleaning software (e.g., Decontam, microDecon, (Davis et al, 2018;McKnight et al, 2019)), other "artefacts" appear to result from the biological nuances of the chosen metabarcoding locus (i.e., differential patterns of gene evolution across taxa). For example, intragenomic variation persists within nuclear rRNA loci, even though rRNA tandem repeat arrays are subjected to concerted evolution within eukaryotic genomes (Bik et al, 2013;Kumar et al, 2017;Pawłowska et al, 2020;Zhao et al, 2019). As a result, an individual eukaryote will typically be represented by a "Head-Tail" pattern in 18S rRNA metabarcoding datasets, exhibiting a dominant "Head" sequence with high relative abundance that represents the species-specific DNA barcode, as well as a "Tail" of rarer low-abundance sequences that exhibit high pairwise similarity to the diagnostic reference barcode (Porazinska, Giblin-Davis, Esquivel, et al, 2010;.…”