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Testing the Effectiveness of DNA Barcoding for Biodiversity Assessment of Moths from Nigeria
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Comprehensive biodiversity assessment of moths in Nigeria rely greatly on accurate species identification. While most of the Nigerian moths are identified effortlessly using their morphological traits, some taxa are morphologically indistinguishable, which makes it difficult for taxon diagnosis. We investigated the efficiency of the DNA barcode, a fragment of the mitochondrial Cytochrome C oxidase subunit I, as a tool for the identification of Nigerian moths. We barcoded 152 individuals comprising 18 morphospecies collected from one of the remaining and threatened rainforest blocks of Nigeria – the Cross River National Park. Phenetic neighbor-joining tree and phylogenetic Maximum Likelihood approach were employed for the molecular-based species identification. Results showed that DNA barcodes enabled species-level identification of most of the individuals collected from the Park. Additionally, DNA barcoding unraveled the presence of at least six potential new and yet undescribed species—Amnemopsyche sp., Arctia sp., Deinypena sp., Hodebertia sp., Otroeda sp., and Palpita sp. The phylogenetic Maximum Likelihood using the combined dataset of all the newly assembled sequences from Nigeria showed that all species formed unique clades. The phylogenetic analyses provided evidence of population divergence in Euchromia lethe, Nyctemera leuconoe, and Deinypena lacista. This study thus illustrates the efficacy of DNA barcoding for species identification and discovery of potential new species, which demonstrates its relevance in biodiversity documentation of Nigerian moths. Future work should, therefore, extend to the creation of an exhaustive DNA barcode reference library comprising all species of moths from Nigeria to have a comprehensive insight on the diversity of moths in the country. Finally, we propose integrated taxonomic methods that would combine morphological, ecological, and molecular data in the identification and diversity studies of moths in Nigeria.
Title: Testing the Effectiveness of DNA Barcoding for Biodiversity Assessment of Moths from Nigeria
Description:
Comprehensive biodiversity assessment of moths in Nigeria rely greatly on accurate species identification.
While most of the Nigerian moths are identified effortlessly using their morphological traits, some taxa are morphologically indistinguishable, which makes it difficult for taxon diagnosis.
We investigated the efficiency of the DNA barcode, a fragment of the mitochondrial Cytochrome C oxidase subunit I, as a tool for the identification of Nigerian moths.
We barcoded 152 individuals comprising 18 morphospecies collected from one of the remaining and threatened rainforest blocks of Nigeria – the Cross River National Park.
Phenetic neighbor-joining tree and phylogenetic Maximum Likelihood approach were employed for the molecular-based species identification.
Results showed that DNA barcodes enabled species-level identification of most of the individuals collected from the Park.
Additionally, DNA barcoding unraveled the presence of at least six potential new and yet undescribed species—Amnemopsyche sp.
, Arctia sp.
, Deinypena sp.
, Hodebertia sp.
, Otroeda sp.
, and Palpita sp.
The phylogenetic Maximum Likelihood using the combined dataset of all the newly assembled sequences from Nigeria showed that all species formed unique clades.
The phylogenetic analyses provided evidence of population divergence in Euchromia lethe, Nyctemera leuconoe, and Deinypena lacista.
This study thus illustrates the efficacy of DNA barcoding for species identification and discovery of potential new species, which demonstrates its relevance in biodiversity documentation of Nigerian moths.
Future work should, therefore, extend to the creation of an exhaustive DNA barcode reference library comprising all species of moths from Nigeria to have a comprehensive insight on the diversity of moths in the country.
Finally, we propose integrated taxonomic methods that would combine morphological, ecological, and molecular data in the identification and diversity studies of moths in Nigeria.
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