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Riverscape genomics of cichlid fishes in the lower Congo: Uncovering mechanisms of diversification in an extreme hydrological regime.

Naoko P KurataMichael J HickersonSandra L HoffbergNed GardinerMelanie L J StiassnyS Elizabeth Alter
Published in: Molecular ecology (2022)
Freshwater fishes are notably diverse, given that freshwater habitat represents a tiny fraction of the earth's surface, but the mechanisms generating this diversity remain poorly understood. Rivers provide excellent models to understand how freshwater diversity is generated and maintained across heterogeneous habitats. In particular, the lower Congo River (LCR) consists of a dynamic hydroscape exhibiting extraordinary aquatic biodiversity, endemicity, morphological and ecological specialization. Previous studies have suggested that the numerous high-energy rapids throughout the LCR form physical barriers to gene flow, thus facilitating diversification and speciation, generating ichthyofaunal diversity. However, this hypothesis has not been fully explored using genome-wide SNPs for fish species distributed across the LCR. Here, we examined four lamprologine cichlids endemic to the LCR that are distributed along the river without range overlap. Using genome-wide SNP data, we tested the hypotheses that high-energy rapids serve as physical barriers to gene flow that generate genetic divergence at interspecific and intraspecific levels, and that gene flow occurs primarily in a downstream direction. Our results are consistent with the prediction that powerful rapids sometimes act as a barrier to gene flow but also suggest that, at certain temporal and spatial scales, they may provide multidirectional dispersal opportunities for riverine rheophilic cichlid fishes. These results highlight the complexity of diversification processes in rivers and the importance of assessing such processes across different riverscapes.
Keyphrases
  • genome wide
  • dna methylation
  • copy number
  • climate change
  • physical activity
  • mental health
  • electronic health record
  • big data
  • genome wide identification
  • deep learning
  • single cell
  • artificial intelligence