Mystery of the parasites inhabiting pelagic zones: the case of monogeneans in Lake Tanganyika

Abstract

Pelagic zones are characterised by consistent large-scale patterns of circulation. Lake Tanganyika is the deepest of the African Great Lakes and harbours one of the most diverse fish assemblages. A high species richness in the littoral zone contrast with a lower diversity in the open waters. Therefore, Lake Tanganyika, as an enclosed ecosystem, provides a plying field to study evolutionary and ecological processes in open water areas worldwide. Research on parasite diversity and dynamics on ecosystem level is underrepresented in the Global South. Our teamwork is based on a multilateral North-South collaboration with the shared goal to uncover diversity and pelagic ecosystem dynamics in this biodiversity hotspot. To explore evolutionary and ecological patterns of parasitic flatworms in this barrier-free habitat, we examined spatiotemporal dynamics of the monogenean fauna infecting two endemic species of pelagic clupeid hosts in the lake. We combined data on spatiotemporal dynamics (1730 screened fishes, 3710 parasites) of two parasite species (Kapentagyrus spp., Monogenea) with morphological variation of their clupeid hosts to investigate general patterns of host-parasite interactions in the lake’s pelagic zone of this ancient lake. Starting from pooled population samples, altogether containing more than 800 parasite specimens, we provide the first population-genomic study on any parasite in the African Great Lakes, using the relatively new DNA PoolSeq technique. Combining ecological and genomic data, we show that the distribution of parasitic flatworms is geographically restricted by host life strategies even in this ecosystem which lacks obvious physical barriers. Contrasting levels of variation across mitochondrial protein coding regions within and across monogenean species are likely linked to the age of diversification. Furthermore, we highlight PoolSeq as suitable method for (mito–)genomics of minute taxa that are hard to access in the field through a comparison of population-genetic parameters based on individual specimens vs. pooled samples.