ena-STUDY-UNIVERSITY OF BRITISH COLUMBIA, DEPT BOTANY-27-01-2016-02:13:48:974-47
Strengths and biases of morphological and NGS data on eukaryotic microbiome characterizations
Molecular surveys of eukaryotic microbial communities, employing next-generation sequencing (NGS) techniques, are rapidly supplanting traditional morphological approaches due to their larger data output and reduced bench working time. Although several biases are known to hamper these analyses, it is not yet entirely clear how to quantify them. Here we directly compare morphological and NGS data obtained from the same samples, in an effort to characterize ciliate communities from freshwater sediments in different environments. We show how in silico processing affects the final outcome, suggesting that stringent filtering provides more consistent results. We determine the abundance distribution of ciliate communities, showing that a small fraction of extremely abundant taxa dominate read counts. At the same time, we advance reasons to believe that errors affecting NGS abundances may be significant enough to blur some biological realities. We confirmed that the NGS approach detects far more taxa than morphological inspections, but that the difference varies among taxonomic groups. Finally, we hypothesize that the two datasets actually correspond to different interpretations of “diversity”, and consequently that neither is entirely superior to the other when investigating environmental protists.
Molecular surveys of eukaryotic microbial communities, employing next-generation sequencing (NGS) techniques, are rapidly supplanting traditional morphological approaches due to their larger data output and reduced bench working time. Although several biases are known to hamper these analyses, it is not yet entirely clear how to quantify them. Here we directly compare morphological and NGS data obtained from the same samples, in an effort to characterize ciliate communities from freshwater sediments in different environments. We show how in silico processing affects the final outcome, suggesting that stringent filtering provides more consistent results. We determine the abundance distribution of ciliate communities, showing that a small fraction of extremely abundant taxa dominate read counts. At the same time, we advance reasons to believe that errors affecting NGS abundances may be significant enough to blur some biological realities. We confirmed that the NGS approach detects far more taxa than morphological inspections, but that the difference varies among taxonomic groups. Finally, we hypothesize that the two datasets actually correspond to different interpretations of “diversity”, and consequently that neither is entirely superior to the other when investigating environmental protists.