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Mitochondrial genome from an abyssal sponge

Added on 2017-10-03 17:54:48 by Boury-Esnault, Nicole
Taboada, S.; Kenny, N.J.; Riesgo, A.; Wiklund, H.: Paterson, G.L.J.; Dahlgren, T.G.; Glover, A. G. (2017). Mitochondrial genome and polymorphic microsatellite markers from the abyssal sponge Plenaster craigi Lim & Wiklund, 2017: tools for understanding the impact of deep-sea mining. Marine Biodiversity, 1-10. DOI 10.1007/s12526-017-0786-0
The abyssal demosponge Plenaster craigi is endemic to the Clarion - Clipperton Zone (CCZ) in the NE Pacific, a region with abundant seafloor polymetallic nodules and of potential interest for mining. Plenaster craigi encrusts on these nodules and is an abundant component of the ecosystem. To assess the impact of mining operations, it is crucial to understand the genetics of this species, because its genetic diversity and connectivity across the area may be representative of other nodule-encrusting invertebrate epifauna. Here we describe and characterize 14 polymorphic microsatellite markers from this keystone species using Illumina MiSeq, tested for 75 individuals from three different areas across the CCZ, including an Area of Particular Environmental Interest (APEI-6) and two areas within the adjacent UK1 mining exploration area. The number of alleles per locus ranged from 3 to 30 (13.33 average alleles for all loci across areas). Observed and expected heterozygosity ranged from 0.909–0.048 and from 0.954–0.255, respectively. Several loci displayed significant deviation from the Hardy- Weinberg equilibrium, which appears to be common in other sponge studies. The microsatellite loci described here will be used to assess the genetic structure and connectivity on populations of the sponge across the CCZ, which will be invaluable for monitoring the impact of mining operations on its habitat. Also, we provide the annotated mitochondrial genome of P. craigi, compare its arrangement with other closely related species, and discuss the phylogenetic framework for the sponge after Maximum Likelihood and Bayesian Inference analyses using nucleotide and amino acid sequences data sets separately.


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