Department Aquatic Ecology

Gene duplications and novel genes have been shown to play a major role in helminth adaptation to a parasitic lifestyle because they provide the novelty necessary for adaptation to a changing environment, such as living in multiple hosts. Here we present the de novo sequenced and annotated genome of the parasitic trematode Atriophallophorus winterbourni and its comparative genomic analysis to other major parasitic trematodes. First, we reconstructed the species phylogeny, and dated the split of A. winterbourni from the Opisthorchiata suborder to approximately 237.4 MYA (± 120.4 MY). We then addressed the question of which expanded gene families and gained genes are potentially involved in adaptation to parasitism. To do this, we used Hierarchical Orthologous Groups to reconstruct three ancestral genomes on the phylogeny leading to A. winterbourni and performed a GO enrichment analysis of the gene composition of each ancestral genome, allowing us to characterize the subsequent genomic changes. Out of the 11,499 genes in the A. winterbourni genome, as much as 24% have arisen through duplication events since the speciation of A. winterbourni from the Opisthorchiata, and as much as 31.9% appear to be novel, i.e. newly acquired. We found 13 gene families in A. winterbourni to have had more than 10 genes arising through these recent duplications; all of which have functions potentially relating to host behavioural manipulation, host tissue penetration, and hiding from host immunity through antigen presentation. We identified several families with genes evolving under positive selection. Our results provide a valuable resource for future studies on the genomic basis of adaptation to parasitism and point to specific candidate genes putatively involved in antagonistic host-parasite adaptation.

The current biodiversity crisis calls for appropriate methods for assessing biodiversity. In this respect, environmental DNA (eDNA) holds great promise, especially for aquatic ecosystems. While initial eDNA studies assessed biodiversity at single sites, technology now allows analyzing samples from many points simultaneously. However, the selection of these sites has been mostly motivated on an ad‐hoc basis. To this end, hydrology‐based models might offer a unique guidance on where to sample eDNA to most effectively reconstruct spatial patterns of biodiversity. Here, we performed computer simulations to identify best‐practice criteria for the choice of positioning of eDNA sampling sites in river networks. To do so, we combined a hydrology‐based eDNA transport model with a virtual river network reproducing the scaling features of real rivers. In particular, we conducted simulations investigating scenarios of different number and location of eDNA sampling sites in a riverine network, different spatial taxon distributions, and different eDNA measurement errors. We found that, due to hydrological controls, non‐uniform patterns of eDNA concentration arise even if the taxon distribution is uniform and decay is neglected. Best practices for sampling site selection depend on the taxon's spatial distribution: when taxa are concentrated in some hotspots and only few sampling sites can be placed, it is better to preferentially locate them in the downstream part of the catchment; when taxa are more evenly distributed, and/or many sites can be placed, these should be preferentially located upstream. We also found that uncertainties in eDNA concentration estimates do not necessarily hamper model predictions. Knowledge of eDNA decay rates improves model predictions, highlighting the need for empirical estimates of these rates under relevant environmental conditions. Our simulations help define strategies for designing eDNA sampling campaigns in river networks and can guide the sampling effort of field ecologists and environmental authorities.

Danube Delta shallow lakes experience cyanobacteria blooms that can negatively affect the aquatic ecosystem. Although there are several studies on Danube Delta cyanobacteria, little is known about their spatial–temporal patterns and the potential predictive role they can offer. We therefore analyzed the distribution of cyanobacteria in 19 lakes belonging to three lake complexes and tested whether their seasonal dynamics are in line with the predictions of the PEG model. Furthermore, we investigated to which extent cyanobacteria diversity and abundance were related to lake hydrogeomorphological characteristics such as surface, water level, connectivity, water retention, flood risk, and transparency. Although lakes had different seasonal cyanobacterial assemblages, the biovolume and genus richness had a geographical pattern, decreasing from south-east (lakes forming the fluvial delta) towards north-west (lakes forming the maritime delta). Cyanobacteria biovolume reflected largely the PEG model peaking in summer (the fluvial delta) and autumn (the maritime delta). Genus richness followed the same pattern. Cyanobacteria distribution was predicted by various abiotic (e.g., risk of flooding, connectivity) and biotic factors (e.g., submersed macrophytes, phytoplankton diversity, peat deposits). Our study contributes to the understanding of cyanobacteria diversity and distribution in shallow interconnected lakes by revealing the complexity of predictors for geographical and seasonal patterns.