Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning.

Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic activities in marine environments. Traditionally, marine biomonitoring involves the sorting and morphological identification of benthic macro-invertebrates, which is time-consuming and taxonomic-expertise demanding. High-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) represents a promising alternative for benthic monitoring.

Taxonomy-free molecular diatom index for high-throughput eDNA biomonitoring.

Current biodiversity assessment and biomonitoring are largely based on the morphological identification of selected bioindicator taxa. Recently, several attempts have been made to use eDNA metabarcoding as an alternative tool. However, until now, most applied metabarcoding studies have been based on the taxonomic assignment of sequences that provides reference to morphospecies ecology.

High-throughput sequencing and morphology perform equally well for benthic monitoring of marine ecosystems.

Environmental diversity surveys are crucial for the bioassessment of anthropogenic impacts on marine ecosystems. Traditional benthic monitoring relying on morphotaxonomic inventories of macrofaunal communities is expensive, time-consuming and expertise-demanding. High-throughput sequencing of environmental DNA barcodes (metabarcoding) offers an alternative to describe biological communities.

Environmental Monitoring: Inferring the Diatom Index from Next-Generation Sequencing Data.

Diatoms are widely used as bioindicators for the assessment of water quality in rivers and streams. Classically, the diatom biotic indices are based on the relative abundance of morphologically identified species weighted by their autoecological value. Obtaining such indices is time-consuming, costly, and requires excellent taxonomic expertise, which is not always available.

Accurate multiplexing and filtering for high-throughput amplicon-sequencing.

Tagging amplicons with tag sequences appended to PCR primers allow the multiplexing of numerous samples for high-throughput sequencing (HTS). This approach is routinely used in HTS-based diversity analyses, especially in microbial ecology and biomedical diagnostics. However, amplicon library preparation is subject to pervasive sample sequence cross-contaminations as a result of tag switching events referred to as mistagging.

Environmental monitoring through protist next-generation sequencing metabarcoding: assessing the impact of fish farming on benthic foraminifera communities.

The measurement of species diversity represents a powerful tool for assessing the impacts of human activities on marine ecosystems. Traditionally, the impact of fish farming on the coastal environment is evaluated by monitoring the dynamics of macrobenthic infaunal populations. However, taxonomic sorting and morphology-based identification of the macrobenthos demand highly trained specialists and are extremely time-consuming and costly, making it unsuitable for large-scale biomonitoring efforts involving numerous samples.

Ancient DNA complements microfossil record in deep-sea subsurface sediments.

Deep-sea subsurface sediments are the most important archives of marine biodiversity. Until now, these archives were studied mainly using the microfossil record, disregarding large amounts of DNA accumulated on the deep-sea floor. Accessing ancient DNA (aDNA) molecules preserved down-core would offer unique insights into the history of marine biodiversity, including both fossilized and non-fossilized taxa.

Ultra-deep sequencing of foraminiferal microbarcodes unveils hidden richness of early monothalamous lineages in deep-sea sediments.

Deep-sea floors represent one of the largest and most complex ecosystems on Earth but remain essentially unexplored. The vastness and remoteness of this ecosystem make deep-sea sampling difficult, hampering traditional taxonomic observations and diversity assessment. This problem is particularly true in the case of the deep-sea meiofauna, which largely comprises small-sized, fragile, and difficult-to-identify metazoans and protists.