Abstract:The mosquito species Anopheles cruzii and Anopheles homunculus are co-occurring vectors for etiological agents of malaria in southeastern Brazil, a region known to be a major epidemic spot for malaria outside Amazon region. We sought to better understand the biology of these species in order to contribute to future control efforts by (1) improving species identification, which is complicated by the fact that the females are very similar, (2) investigating genetic composition and morphological differences betwe… Show more
“…The ability of wing traits to capture a genetic pattern so strikingly similar to that inferred from hundreds of molecular loci spread across the 16 honey bee chromosomes [35,52] could be explained by a high heritability and a polygenic nature of wing shape. While the genetic basis of forewing venation is virtually unknown in most insects, including honey bees, it is likely that wing shape has a strong genetic control, as suggested by this and other studies which have also reported concordance between wing morphology and molecular markers, such as mtDNA and microsatellites [78][79][80][81][82][83].…”
Wing geometric morphometrics has been applied to honey bees (Apis mellifera) in identification of evolutionary lineages or subspecies and, to a lesser extent, in assessing genetic structure within subspecies. Due to bias in the production of sterile females (workers) in a colony, most studies have used workers leaving the males (drones) as a neglected group. However, considering their importance as reproductive individuals, the use of drones should be incorporated in these analyses in order to better understand diversity patterns and underlying evolutionary processes. Here, we assessed the usefulness of drone wings, as well as the power of wing geometric morphometrics, in capturing the signature of complex evolutionary processes by examining wing shape data, integrated with geographical information, from 711 colonies sampled across the entire distributional range of Apis mellifera iberiensis in Iberia. We compared the genetic patterns reconstructed from spatially-explicit shape variation extracted from wings of both sexes with that previously reported using 383 genome-wide SNPs (single nucleotide polymorphisms). Our results indicate that the spatial structure retrieved from wings of drones and workers was similar (r = 0.93) and congruent with that inferred from SNPs (r = 0.90 for drones; r = 0.87 for workers), corroborating the clinal pattern that has been described for A. m. iberiensis using other genetic markers. In addition to showing that drone wings carry valuable genetic information, this study highlights the capability of wing geometric morphometrics in capturing complex genetic patterns, offering a reliable and low-cost alternative for preliminary estimation of population structure.
“…The ability of wing traits to capture a genetic pattern so strikingly similar to that inferred from hundreds of molecular loci spread across the 16 honey bee chromosomes [35,52] could be explained by a high heritability and a polygenic nature of wing shape. While the genetic basis of forewing venation is virtually unknown in most insects, including honey bees, it is likely that wing shape has a strong genetic control, as suggested by this and other studies which have also reported concordance between wing morphology and molecular markers, such as mtDNA and microsatellites [78][79][80][81][82][83].…”
Wing geometric morphometrics has been applied to honey bees (Apis mellifera) in identification of evolutionary lineages or subspecies and, to a lesser extent, in assessing genetic structure within subspecies. Due to bias in the production of sterile females (workers) in a colony, most studies have used workers leaving the males (drones) as a neglected group. However, considering their importance as reproductive individuals, the use of drones should be incorporated in these analyses in order to better understand diversity patterns and underlying evolutionary processes. Here, we assessed the usefulness of drone wings, as well as the power of wing geometric morphometrics, in capturing the signature of complex evolutionary processes by examining wing shape data, integrated with geographical information, from 711 colonies sampled across the entire distributional range of Apis mellifera iberiensis in Iberia. We compared the genetic patterns reconstructed from spatially-explicit shape variation extracted from wings of both sexes with that previously reported using 383 genome-wide SNPs (single nucleotide polymorphisms). Our results indicate that the spatial structure retrieved from wings of drones and workers was similar (r = 0.93) and congruent with that inferred from SNPs (r = 0.90 for drones; r = 0.87 for workers), corroborating the clinal pattern that has been described for A. m. iberiensis using other genetic markers. In addition to showing that drone wings carry valuable genetic information, this study highlights the capability of wing geometric morphometrics in capturing complex genetic patterns, offering a reliable and low-cost alternative for preliminary estimation of population structure.
“…darlingi from Central America and Colombia. Comparisons of haplotype divergence among Kerteszia species by Lorenz et al (2015) detected a magnitude of difference between An. cruzii and An.…”
A reference 535 bp barcode sequence from a fragment of the mitochondrial gene cytochrome oxidase I (COI), acquired from specimens of An. neivai Howard, Dyar & Knab, 1913 from its type locality in Panama, was used as a tool for distinguishing this species from others in the subgenus Kerteszia. Comparisons with corresponding regions of COI between An. neivai and other species in the subgenus (An. bellator Dyar & Knab 1906, An. homunculus Komp 1937, An cruzii Dyar & Knab, 1908 and An. laneanus Corrêa & Cerqueira, 1944) produced K2P genetic distances of 8.3–12.6%, values well above those associated with intraspecific variation. In contrast, genetic distances among 55 specimens from five municipalities in the Colombian Pacific coastal state of Chocó were all within the range of 0–2.5%, with an optimized barcode threshold of 1.3%, the limit for unambiguous differentiation of An. neivai. Among specimens from the Chocó region, 18 haplotypes were detected, two of which were widely distributed over the municipalities sampled. The barcode sequence permits discrimination of An. neivai from sympatric species and indicates genetic variability within the species; aspects key to malaria surveillance and control as well as defining geographic distribution and dispersion patterns.
“…Recently, a handful of studies have tried to understand the evolutionary relationship among different species from Kerteszia subgenus (including An. bellator , Anopheles cruzii and Anopheles homunculus ), 6 , 7 rather than investigating the genetic diversity between An. bellator populations.…”
Anopheles bellator
is a primary malaria vector in the Atlantic Forest. Partial sequences of
timeless
and
Clock
genes were used to assess the genetic differentiation of five Brazilian populations, which showed strong population structure (e.g. high
F
ST
values and fixed differences) in all pairwise comparisons between Bahia sample and the others from Paraná, São Paulo and Rio de Janeiro states. Also, the resulting phylogenetic trees clearly grouped the sequences from Bahia in a different cluster with high bootstrap values. Among southern and southeastern populations low levels of genetic differentiation were found suggesting a general stability of the genetic structure.
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