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Hidden diversity in the genus Tethya: comparing molecular and morphological techniques for species identification.

Megan R ShafferSimon K DavyJames J Bell
Published in: Heredity (2018)
Correctly determining species' identity is critical for estimating biodiversity and effectively managing marine populations, but is difficult for species that have few morphological traits or are highly plastic. Sponges are considered a taxonomically difficult group because they lack multiple consistent diagnostic features, which coupled with their common phenotypic plasticity, makes the presence of species complexes likely, but difficult to detect. Here, we investigated the evolutionary relationship of Tethya spp. in central New Zealand using both molecular and morphological techniques to highlight the potential for cryptic speciation in sponges. Phylogenetic reconstructions based on two mitochondrial markers (rnl, COI-ext) and one nuclear marker (18S) revealed three genetic clades, with one clade representing Tethya bergquistae and two clades belonging to what was a priori thought to be a single species, Tethya burtoni. Eleven microsatellite markers were also used to further resolve the T. burtoni group, revealing a division consistent with the 18S and rnl data. Morphological analysis based on spicule characteristics allowed T. bergquistae to be distinguished from T. burtoni, but revealed no apparent differences between the T. burtoni clades. Here, we highlight hidden genetic diversity within T. burtoni, likely representing a group consisting of incipient species that have undergone speciation but have yet to express clear morphological differences. Our study supports the notion that cryptic speciation in sponges may go undetected and diversity underestimated when using only morphology-based taxonomy, which has broad scale implications for conservation and management of marine systems.
Keyphrases
  • genetic diversity
  • genome wide
  • oxidative stress
  • gene expression
  • computed tomography
  • risk assessment
  • single molecule
  • copy number
  • electronic health record
  • deep learning
  • diffusion weighted imaging