Strengths and Biases of High-Throughput Sequencing Data in the Characterization of Freshwater Ciliate Microbiomes

Molecular surveys of eukaryotic microbial communities employing high-throughput sequencing (HTS) techniques are rapidly supplanting traditional morphological approaches due to their larger data output and reduced bench work time. Here, we directly compare morphological and Illumina data obtained from the same samples, in an effort to characterize ciliate faunas from sediments in freshwater environments. We show how in silico processing affects the final outcome of our HTS analysis, providing evidence that quality filtering protocols strongly impact the number of predicted taxa, but not downstream conclusions such as biogeography patterns. We determine the abundance distribution of ciliates, showing that a small fraction of abundant taxa dominates read counts. At the same time, we advance reasons to believe that biases affecting HTS abundances may be significant enough to blur part of the underlying biological picture. We confirmed that the HTS approach detects many more taxa than morphological inspections, and highlight how the difference varies among taxonomic groups. Finally, we hypothesize that the two datasets actually correspond to different conceptions of “diversity,” and consequently that neither is entirely superior to the other when investigating environmental protists.