Comparative analysis of zooplankton diversities and compositions estimated from complement DNA and genomic DNA amplicons, metatranscriptomics, and morphological identifications

Abstract

Community-based diversity analyses, such as metabarcoding, are increasingly popular in the field of metazoan zooplankton community ecology. However, some of the methodological uncertainties remain, such as the potential inflation of diversity estimates resulting from contamination by pseudogene sequences. Furthermore, primer affinity to specific taxonomic groups might skew community composition and structure during PCR. In this study, we estimated OTU (operational taxonomic unit) richness, Shannon’s H’, and the phylum-level community composition of samples from a coastal zooplankton community using four approaches: complement DNA (cDNA) and genomic DNA (gDNA) mitochondrial COI (Cytochrome oxidase subunit I) gene amplicon, metatranscriptome sequencing, and morphological identification. Results of mismatch distribution demonstrated that 90% is good threshold percentage to differentiate intra- and inter-species. Moderate level of correlations appeared upon comparing the species/OTU richness estimated from the different methods. Results strongly indicated that diversity inflation occurred in the samples amplified from gDNA because of mitochondrial pseudogene contamination (overall, gDNA produced two times more richness compared with cDNA amplicons). The unique community compositions observed in the PCR-based methods indicated that taxonomic amplification bias had occurred during the PCR. Therefore, it is recommended that PCR-free approaches be used whenever resolving community structure represents an essential aspect of the analysis.

Development of transcriptomics‐based growth rate indices in two model eukaryotes and relevance to metatranscriptomics datasets

“…However, not all species have the homolog genes of the nuclear gene proposed in this study, such as the homologue of ETHE1, which is yet to be discovered in S. cerevisiae. Lenz et al, 2021;Lopez et al, 2021;Machida et al, 2021).…”

MIDORI2: A collection of quality controlled, preformatted, and regularly updated reference databases for taxonomic assignment of eukaryotic mitochondrial sequences

“…Conserved primers are available for PCR‐based surveys of selected metazoans, all metazoans, or all eukaryotes [e.g., Cytochrome c oxidase subunit 1 ( CO1 ) (Elbrecht et al, 2019; Leray et al, 2013); Small rRNA ( srRNA ) (Machida et al, 2012); Large rRNA ( lrRNA ) (Kelly et al, 2016)]. Studies have also successfully used PCR‐free mitochondrial metagenomics (mitogenomics) and metatranscriptomics to infer composition and relative biomass of complex mixed‐species samples (Bista et al, 2018; Lopez et al, 2022; Machida et al, 2021).…”

“…Of course, molecular approaches for censusing species have their own biases and limitations (Aylagas et al, 2016;Kelly et al, 2019). Nevertheless, studies so far show that analyses of environmental DNA provide higher species detectability in a variety of environments (Bush et al, 2020;Machida et al, 2021;Nguyen et al, 2020;Thomsen & Sigsgaard, 2019), and new applications continue to be developed (e.g., Clare et al, 2022;Lynggaard et al, 2022).…”

“…Studies have also successfully used PCR-free mitochondrial metagenomics (mitogenomics) and metatranscriptomics to infer composition and relative biomass of complex mixed-species samples (Bista et al, 2018;Lopez et al, 2022;Machida et al, 2021).…”

Using metatranscriptomics to estimate the diversity and composition of zooplankton communities

“…Given these methodological uncertainties, a molecular approach bypassing PCR and using RNA instead of gDNA as a template is an ideal alternative method for monitoring zooplankton communities (Machida et al, 2021 ; Semmouri et al, 2019 ). RNA‐based methods that capture messenger RNA (mRNA), such as metatranscriptomics, may be less prone to biases when characterizing zooplankton communities.…”