Towards standardized molecular monitoring of HABs: A consensus guide to qPCR - Uwe John; Dave Clarke; Holly Bowers; Shauna Murray; Antonella Penna; Amna Ashfaq; Karl Blyth Andree; Mathiroopini Andipalagan; Elisa Berdalet; Silvia Casabianca; Catarina Churro; Anette Engesmo; et al. (Harmful Algae, 2026)

Ingestion of Alexandrium pacificum Cysts by a Deposit Feeder: An Option for Ecosystem‐Based Approach Benefiting Aquaculture and Coastal Communities? - Leonardo N. Zamora; Kirsty F. Smith; Jacqui Stuart; D. Tim Harwood; Shenae L. Wales; Emillie M. F. Passfield; Lincoln Mackenzie (New Zealand Journal of Marine and Freshwater Research, 2026)
Harmful algal blooms caused by the paralytic shellfish toxin‐producing species Alexandrium pacificum have increased in recent years in one of the most important aquaculture regions of New Zealand, the Marlborough Sounds. Reoccurring blooms have created large cysts beds in the sediments throughout the sounds. In this region, large populations of the sea cucumber Australostichopus mollis can also be found. These deposit feeders potentially ingest the resting cysts of A. pacificum when feeding. To investigate this, we used molecular techniques to evaluate and quantify cyst ingestion, and chemical analysis to determine toxin accumulation in A. mollis . Results indicate that sea cucumbers can act as bioindicators of cyst distribution through their selective feeding behaviours, with high concentrations of A. pacificum DNA in foregut samples. Sea cucumbers could also serve as a biocontrol tool, as A. pacificum DNA concentrations decreased along the digestive tract, from the foregut to the hindgut, indicating a reduction in cyst number during the digestion process. Furthermore, no toxin accumulation was detected in the sea cucumber tissue. These encouraging results open the possibility for further research to evaluate the efficiency of integrated biocontrol management and the emergence of a multi‐impact aquaculture sector around this iconic New Zealand echinoderm.

Tropics to the Poles: A Snapshot of Coastal Eukaryotic Marine Microalgal Diversity Across Five Ecoregions - Jacqui Stuart; Ken G. Ryan; John K. Pearman; Natalie Robinson; Svenja Halfter; Jacob Thomson‐Laing; Laura Biessy; Kirsty F. Smith (Molecular Ecology, 2025)
Eukaryotic microalgae are key organisms in marine environments, contributing to essential nutrient and biogeochemical cycles. Climate change is already causing shifts in the composition and diversity of microalgal assemblages, with coastal ecosystems experiencing increased pressure. Molecular techniques, such as environmental DNA (eDNA) metabarcoding, have allowed eukaryotic microalgal communities (EMCs) to be characterised more rapidly than traditional methods, addressing some data gaps. Many geographic regions still lack comprehensive baseline assessments of entire EMCs, often focusing on specific taxonomic or functional groups. In this study, we used eDNA metabarcoding of the 18S V9 gene region to characterise EMCs across a latitudinal gradient spanning five ecoregions from the South Pacific to the Ross Sea. Temperate sites had the highest alpha diversity and the most distinct EMCs across all ecoregions. Community composition showed clear latitudinal gradients, with a shift from dinoflagellate‐dominant EMCs at lower latitudes to diatom‐dominant EMCs at higher latitudes. The formation of EMCs was influenced by similar habitats/conditions (homogeneous selection) and proximity (homogenising dispersal) within ecoregions, while variable conditions (variable selection) and limited interconnectivity (dispersal limitation) were more prevalent between ecoregions. This snapshot of coastal EMC diversity across five ecoregions highlights distinct latitudinal patterns in community composition, with temperate regions showing higher diversity compared to polar areas. These findings provide a useful baseline for future monitoring and can help guide assessments of potential changes in microalgal communities due to climate change.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.