Data from: Deep mitochondrial divergence in Baja California populations of an aquilopelagic elasmobranch: the golden cownose ray

Assessing the realized effect of dispersal in the genetic makeup of a species has significant evolutionary, ecological, and economical consequences. Here, we investigate the genetic diversity and population differentiation in the aquilopelagic golden cownose ray Rhinoptera steindachneri from the Gulf of California (GC) and the Pacific coast of Baja California (PCBC) using the mitochondrial NADH2 gene. Low levels of genetic diversity were found with only 4 polymerase chain reaction-restriction fragment length polymorphism haplotypes among 76 specimens. Pacific coast organisms were fixed for a unique haplotype not shared with rays from the gulf; 92% of GC rays possessed a single NADH2 haplotype not found in the Pacific. This produced significant differentiation between the GC and the PCBC (ΦCT = 0.972, P < 0.001). A pronounced phylogeographic pattern was found in which GC haplotypes were reciprocally monophyletic relative to a very divergent Pacific lineage (d = 10%). Our results indicate that despite high dispersal potential, GC and PCBC golden cownose ray populations are characterized by highly divergent mitochondrial lineages. Although more evidence is needed to corroborate the genetic isolation and systematic status of PCBC and GC golden cownose rays, our results suggest a possible cryptic species in the region.

Identifier
DOI https://doi.org/10.5061/dryad.8437
PID https://nbn-resolving.org/urn:nbn:nl:ui:13-6v-u4r1
Metadata Access https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:80804
Provenance
Creator Sandoval-Castillo, Jonathan; Rocha-Olivares, Axayácatl
Publisher Data Archiving and Networked Services (DANS)
Publication Year 2011
Rights info:eu-repo/semantics/openAccess; License: http://creativecommons.org/publicdomain/zero/1.0; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Representation
Resource Type Dataset
Discipline Life Sciences; Medicine