Allometric scaling of interspecific RNA transcript abundance to extend the use of metatranscriptomics in characterizing complex communities.

Metatranscriptomics allows profiling of community mRNA and rRNA transcript abundance under certain environmental conditions. However, variations in the proportion of RNA transcripts across different community size structures remain less explained, thus limiting the possible applications of metatranscriptomics in community studies. Here, we extended the assumptions of the growth-rate hypothesis (GRH) and the metabolic theory of ecology (MTE) to validate the allometric scaling of interspecific RNA transcript (mRNA and rRNA) abundance through metatranscriptomic analysis of mock communities consisting of model organisms. The results suggest that body size imposes significant constraints on RNA transcript abundance. Interestingly, the relationship between the total mitochondrial transcript abundance (mRNA and rRNA slopes were -0.30 and -0.28, respectively) and body size aligned with the MTE assumptions with slopes close to -», while the nuclear transcripts displayed much steeper slopes (mRNA and rRNA slopes were -0.33 and -0.40, respectively). The assumed temperature dependence was not observed in this study. At the gene level, the allometric slopes range from 0 to -1. Overall, the above results showed that larger individuals have lesser RNA transcript abundance per tissue mass than smaller ones regardless of temperature. Analyses of field-collected microcrustacean zooplankton samples demonstrated that the correction of size effect, using the allometric exponents derived from the model organism mock community, explains better the patterns of interspecific RNA transcripts abundance within the metatranscriptome. Integrating allometry with metatranscriptomics can extend the use of RNA transcript reads in estimating ecological processes within complex communities.

Using metatranscriptomics to estimate the diversity and composition of zooplankton communities.

DNA metabarcoding is a rapid, high-resolution tool used for biomonitoring complex zooplankton communities. However, diversity estimates derived with this approach can be biased by the co-detection of sequences from environmental DNA (eDNA), nuclear-encoded mitochondrial (NUMT) pseudogene contamination, and taxon-specific PCR primer affinity differences. To avoid these methodological uncertainties, we tested the use of metatranscriptomics as an alternative approach for characterizing zooplankton communities. Specifically, we compared metatranscriptomics with PCR-based methods using genomic (gDNA) and complementary DNA (cDNA) amplicons, and morphology-based data for estimating species diversity and composition for both mock communities and field-collected samples. Mock community analyses showed that the use of gDNA mitochondrial cytochrome c oxidase I (mtCO1) amplicons inflates species richness due to the co-detection of extra-organismal eDNA. Significantly more amplicon sequence variants, nucleotide diversity, and indels were observed with gDNA amplicons than with cDNA, indicating the presence of putative NUMT pseudogenes. Moreover, PCR-based methods failed to detect the most abundant species in mock communities due to priming site mismatch. Overall, metatranscriptomics provided estimates of species richness and composition that closely resembled those derived from morphological data. The use of metatranscriptomics was further tested using field-collected samples, with the results showing consistent species diversity estimates among biological and technical replicates. Additionally, temporal zooplankton species composition changes could be monitored using different mitochondrial markers. These findings demonstrate the advantages of metatranscriptomics as an effective tool for monitoring diversity in zooplankton research.