Assessment of Three Mitochondrial Genes (16S, Cytb, CO1) for Identifying Species in the Praomyini Tribe (Rodentia: Muridae)

• Published in: PloS one Vol. 7; no. 5; p. e36586
• Main Authors: Nicolas, Violaine, Schaeffer, Brigitte, Missoup, Alain Didier, Kennis, Jan, Colyn, Marc, Denys, Christiane, Tatard, Caroline, Cruaud, Corinne, Laredo, Catherine
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 04.05.2012; Public Library of Science (PLoS)
• Subjects: Acomys; Animals; Biodiversity; Biodiversity and Ecology; Biology; Chiroptera; Classification; Crop damage; Crops; Cytochrome; Cytochromes b - genetics; Deoxyribonucleic acid; Divergence; DNA; DNA Barcoding, Taxonomic - methods; Electron Transport Complex IV - genetics; Environmental Sciences; Epidemiology; Epomophorus gambianus; Evolution; Forests; Genes; Genes, Mitochondrial - genetics; Genomes; Identification; Identification methods; Interspecific; Lemniscomys striatus; Mammalia; Markers; Micropteropus pusillus; Mitochondria; Mitochondrial DNA; Muridae; Muridae - classification; Muridae - genetics; Nematodes; Neotoma; New species; Nuclear electric power generation; Nucleotides; Phylogenetics; Pteropodidae; Rodentia; Rodents; Sequence Analysis, DNA; Sibling species; Statistical methods; Statistics; Studies; Taxonomy; Trees; France
• DOI: 10.1371/journal.pone.0036586
• ISSN: 1932-6203

The Praomyini tribe is one of the most diverse and abundant groups of Old World rodents. Several species are known to be involved in crop damage and in the epidemiology of several human and cattle diseases. Due to the existence of sibling species their identification is often problematic. Thus an easy, fast and accurate species identification tool is needed for non-systematicians to correctly identify Praomyini species. In this study we compare the usefulness of three genes (16S, Cytb, CO1) for identifying species of this tribe. A total of 426 specimens representing 40 species (sampled across their geographical range) were sequenced for the three genes. Nearly all of the species included in our study are monophyletic in the neighbour joining trees. The degree of intra-specific variability tends to be lower than the divergence between species, but no barcoding gap is detected. The success rate of the statistical methods of species identification is excellent (up to 99% or 100% for statistical supervised classification methods as the k-Nearest Neighbour or Random Forest). The 16S gene is 2.5 less variable than the Cytb and CO1 genes. As a result its discriminatory power is smaller. To sum up, our results suggest that using DNA markers for identifying species in the Praomyini tribe is a largely valid approach, and that the CO1 and Cytb genes are better DNA markers than the 16S gene. Our results confirm the usefulness of statistical methods such as the Random Forest and the 1-NN methods to assign a sequence to a species, even when the number of species is relatively large. Based on our NJ trees and the distribution of all intraspecific and interspecific pairwise nucleotide distances, we highlight the presence of several potentially new species within the Praomyini tribe that should be subject to corroboration assessments.