Evidence of new species for malaria vector Anopheles nuneztovari sensu lato in the Brazilian Amazon region

• Autor(a) principal: Scarpassa, Vera Margarete
• Data de Publicação: 2016
• Outros Autores: Cunha-Machado, Antônio Saulo, Saraiva, José Ferreira
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional do INPA
• Texto Completo: https://repositorio.inpa.gov.br/handle/1/15823
• topic: Amazona; Anopheles Nuneztovari; Bayes Theorem; Correspondence Analysis; Disease Carrier; Genbank; Genetic Distance; Genetic Variability; Haplotype; Human; Human Tissue; Major Clinical Study; Maximum Likelihood Method; Microsatellite Marker; Monophyly; New Species; Plasmodium; Genetics, Population; Population Structure; Zoology; Animals; Anopheles; Brasil; Classification; Dna Sequence; Genetics; Insect Vector; Malaria; Metabolism; Parasitology; Phylogeny; Cytochrome C Oxidase; Insect Proteins; Microsatellite Dna; Animal; Anopheles; Bayes Theorem; Brasil; Electron Transport Complex Iv; Haplotypes; Insect Proteins; Insect Vectors; Malaria; Microsatellite Repeats; Phylogeny; Sequence Analysis, Dna

Background: Anopheles nuneztovari sensu lato comprises cryptic species in northern South America, and the Brazilian populations encompass distinct genetic lineages within the Brazilian Amazon region. This study investigated, based on two molecular markers, whether these lineages might actually deserve species status. Methods: Specimens were collected in five localities of the Brazilian Amazon, including Manaus, Careiro Castanho and Autazes, in the State of Amazonas; Tucuruí, in the State of Pará; and Abacate da Pedreira, in the State of Amapá, and analysed for the COI gene (Barcode region) and 12 microsatellite loci. Phylogenetic analyses were performed using the maximum likelihood (ML) approach. Intra and inter samples genetic diversity were estimated using population genetics analyses, and the genetic groups were identified by means of the ML, Bayesian and factorial correspondence analyses and the Bayesian analysis of population structure. Results: The Barcode region dataset (N = 103) generated 27 haplotypes. The haplotype network suggested three lineages. The ML tree retrieved five monophyletic groups. Group I clustered all specimens from Manaus and Careiro Castanho, the majority of Autazes and a few from Abacate da Pedreira. Group II clustered most of the specimens from Abacate da Pedreira and a few from Autazes and Tucuruí. Group III clustered only specimens from Tucuruí (lineage III), strongly supported (97 %). Groups IV and V clustered specimens of A. nuneztovari s.s. and A. dunhami, strongly (98 %) and weakly (70 %) supported, respectively. In the second phylogenetic analysis, the sequences from GenBank, identified as A. goeldii, clustered to groups I and II, but not to group III. Genetic distances (Kimura-2 parameters) among the groups ranged from 1.60 % (between I and II) to 2.32 % (between I and III). Microsatellite data revealed very high intra-population genetic variability. Genetic distances showed the highest and significant values (P = 0.005) between Tucuruí and all the other samples, and between Abacate da Pedreira and all the other samples. Genetic distances, Bayesian (Structure and BAPS) analyses and FCA suggested three distinct biological groups, supporting the barcode region results. Conclusions: The two markers revealed three genetic lineages for A. nuneztovari s.l. in the Brazilian Amazon region. Lineages I and II may represent genetically distinct groups or species within A. goeldii. Lineage III may represent a new species, distinct from the A. goeldii group, and may be the most ancestral in the Brazilian Amazon. They may have differences in Plasmodium susceptibility and should therefore be investigated further. © 2016 Scarpassa et al.