Dataset Information

Century-Old DNA Barcodes Reveal Phylogenetic Placement of the Extinct Jamaican Sunset Moth, Urania sloanus Cramer (Lepidoptera: Uraniidae).

ABSTRACT: Analysis of the DNA barcode region of the cytochrome c oxidase 1 gene from a specimen of the extinct Jamaican sunset moth, Urania sloanus, places this species as a sister to the Central American U. fulgens. We found that all Urania F. species were closely related (<2.8% maximum divergence at COI), with the Cuban endemic U. boisduvalii appearing as sister to the rest. The low divergence in DNA barcodes and genitalic structures indicate that the Cuban U. poeyi and eastern Brazilian U. brasiliensis are geographic segregates of U. fulgens and U. leilus respectively, so the former two taxa are accordingly recognized as subspecies.

SUBMITTER: Nazari V

PROVIDER: S-EPMC5072700 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Century-Old DNA Barcodes Reveal Phylogenetic Placement of the Extinct Jamaican Sunset Moth, Urania sloanus Cramer (Lepidoptera: Uraniidae).

Nazari Vazrick V Schmidt B Christian BC Prosser Sean S Hebert Paul D N PD

PloS one 20161020 10

Analysis of the DNA barcode region of the cytochrome c oxidase 1 gene from a specimen of the extinct Jamaican sunset moth, Urania sloanus, places this species as a sister to the Central American U. fulgens. We found that all Urania F. species were closely related (<2.8% maximum divergence at COI), with the Cuban endemic U. boisduvalii appearing as sister to the rest. The low divergence in DNA barcodes and genitalic structures indicate that the Cuban U. poeyi and eastern Brazilian U. brasiliensis ...[more]

PMID: 27764148

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Project description:Identification of pyraloid species is often hampered by highly similar external morphology requiring microscopic dissection of genitalia. This becomes especially obvious when mass samples from ecological studies or insect monitoring have to be analysed. DNA barcode sequences could accelerate identification, but are not available for most pyraloid species from New Zealand. Hence, we are presenting a first DNA-barcode library for this group, providing 440 COI barcodes (cytochrome C oxidase I sequences) for 73 morphologically-identified species, which is 29% of Pyraloidea known from New Zealand. Results are analysed using the Barcode Index Number system (BIN) of BOLD and the Automatic Barcode Gap Discovery method (ABGD). Using BIN, the 440 barcodes reveal 82 clusters. A perfect match between BIN assignment and morphological identification was found for 63 species (86.3%). Four species (5.5%) share BINs, each with two species in one BIN, of which Glaucocharis epiphaea and Glaucocharis harmonica even share the same barcode. In contrast, six species (8.2%) split into two or more BINs, with the highest number of five BINs for Orocrambus ramosellus. The interspecific variation of all collected specimens of New Zealand Pyraloidea averages 12.54%. There are deep intraspecific divergences (> 2%) in seven species, for instance Orocrambus vulgaris with up to 6.6% and Scoparia ustimacula with 5.5%. Using ABGD, the 440 barcodes reveal 71 or 88 operational taxonomic units (OTUs), depending on the preferred partition. A perfect match between OTU and morphological identification was found for 56 species (76.7%) or 62 species (84.9%). ABGD delivers four or seven species sharing OTUs and four or ten species split into more than one OTU. Morphological re-examination, as well as the analysis of a concatenated dataset of COI and the nuclear markers EF1α and GADPH for species split into more than one BIN or OTU, do not support a higher number of species. Likewise, there is no evidence for Wolbachia infection as a trigger for these sequence variations.

Dataset Information

Century-Old DNA Barcodes Reveal Phylogenetic Placement of the Extinct Jamaican Sunset Moth, Urania sloanus Cramer (Lepidoptera: Uraniidae).

Publications

Century-Old DNA Barcodes Reveal Phylogenetic Placement of the Extinct Jamaican Sunset Moth, Urania sloanus Cramer (Lepidoptera: Uraniidae).

Similar Datasets

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