Metagenomics versus total RNA sequencing: most accurate data-processing tools, microbial identification accuracy and perspectives for ecological assessments.

Metagenomics and total RNA sequencing (total RNA-Seq) have the potential to improve the taxonomic identification of diverse microbial communities, which could allow for the incorporation of microbes into routine ecological assessments. However, these target-PCR-free techniques require more testing and optimization. In this study, we processed metagenomics and total RNA-Seq data from a commercially available microbial mock community using 672 data-processing workflows, identified the most accurate data-processing tools, and compared their microbial identification accuracy at equal and increasing sequencing depths. The accuracy of data-processing tools substantially varied among replicates. Total RNA-Seq was more accurate than metagenomics at equal sequencing depths and even at sequencing depths almost one order of magnitude lower than those of metagenomics. We show that while data-processing tools require further exploration, total RNA-Seq might be a favorable alternative to metagenomics for target-PCR-free taxonomic identifications of microbial communities and might enable a substantial reduction in sequencing costs while maintaining accuracy. This could be particularly an advantage for routine ecological assessments, which require cost-effective yet accurate methods, and might allow for the incorporation of microbes into ecological assessments.

Freshwater connectivity transforms spatially integrated signals of biodiversity.

Aquatic ecosystems offer a continuum of water flow from headwater streams to inland lakes and coastal marine systems. This spatial connectivity influences the structure, function and dynamics of aquatic communities, which are among the most threatened and degraded on the Earth. Here, we determine the spatial resolution of environmental DNA (eDNA) in dendritic freshwater networks, which we use as a model for connected metacommunities. Our intensive sampling campaign comprised over 420 eDNA samples across 21 connected lakes, allowing us to analyse detections at a variety of scales, from different habitats within a lake to entire lake networks. We found strong signals of within-lake variation in eDNA distribution reflective of typical habitat use by both fish and zooplankton. Most importantly, we also found that connecting channels between lakes resulted in an accumulation of downstream eDNA detections in lakes with a higher number of inflows, and as networks increased in length. Environmental DNA achieves biodiversity surveys in these habitats in a high-throughput, spatially integrated way. These findings have profound implications for the interpretation of eDNA detections in aquatic ecosystems in global-scale biodiversity monitoring observations.

Molecular organization of the 5S rDNA gene type II in elasmobranchs.

The 5S rDNA gene is a non-coding RNA that can be found in 2 copies (type I and type II) in bony and cartilaginous fish. Previous studies have pointed out that type II gene is a paralog derived from type I. We analyzed the molecular organization of 5S rDNA type II in elasmobranchs. Although the structure of the 5S rDNA is supposed to be highly conserved, our results show that the secondary structure in this group possesses some variability and is different than the consensus secondary structure. One of these differences in Selachii is an internal loop at nucleotides 7 and 112. These mutations observed in the transcribed region suggest an independent origin of the gene among Batoids and Selachii. All promoters were highly conserved with the exception of BoxA, possibly due to its affinity to polymerase III. This latter enzyme recognizes a dT4 sequence as stop signal, however in Rajiformes this signal was doubled in length to dT8. This could be an adaptation toward a higher efficiency in the termination process. Our results suggest that there is no TATA box in elasmobranchs in the NTS region. We also provide some evidence suggesting that the complexity of the microsatellites present in the NTS region play an important role in the 5S rRNA gene since it is significantly correlated with the length of the NTS.

Assessment of current taxonomic assignment strategies for metabarcoding eukaryotes.

The effective use of metabarcoding in biodiversity science has brought important analytical challenges due to the need to generate accurate taxonomic assignments. The assignment of sequences to genus or species level is critical for biodiversity surveys and biomonitoring, but it is particularly challenging as researchers must select the approach that best recovers information on species composition. This study evaluates the performance and accuracy of seven methods in recovering the species composition of mock communities by using COI barcode fragments. The mock communities varied in species number and specimen abundance, while upstream molecular and bioinformatic variables were held constant, and using a set of COI fragments. We evaluated the impact of parameter optimization on the quality of the predictions. Our results indicate that BLAST top hit competes well with more complex approaches if optimized for the mock community under study. For example, the two machine learning methods that were benchmarked proved more sensitive to reference database heterogeneity and completeness than methods based on sequence similarity. The accuracy of assignments was impacted by both species and specimen counts (query compositional heterogeneity) which ultimately influence the selection of appropriate software. We urge researchers to: (i) use realistic mock communities to allow optimization of parameters, regardless of the taxonomic assignment method employed; (ii) carefully choose and curate the reference databases including completeness; and (iii) use QIIME, BLAST or LCA methods, in conjunction with parameter tuning to better assign taxonomy to diverse communities, especially when information on species diversity is lacking for the area under study.