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Background Nyssorhynchus darlingi (also known as Anopheles darlingi) is the primary malaria vector in the Amazon River Basin. In Brazil, analysis of single nucleotide polymorphisms (SNPs) previously detected three major population clusters, and a common garden experiment in a laboratory setting revealed significant population variation in life history traits. Increasing temperatures and local level variation can affect life history traits, i.e. adult longevity, that alter vectorial capacity with implications for malaria transmission in Ny. darlingi. Methods We investigated the population structure of Ny. darlingi from 7 localities across Brazil utilizing SNPs and compared them to a comprehensive Ny. darlingi catalog. To test the effects of local level variation on life history traits, we reared F1 progeny from the 7 localities at three constant temperatures (20, 24 and 28 °C), measuring key life history traits (larval development, food-starved adult lifespan, adult size and daily survival). Results Using nextRAD genotyping-by-sequencing, 93 of the field-collected Ny. darlingi were genotyped at 33,759 loci. Results revealed three populations (K = 3), congruent with major biomes (Amazonia, Cerrado and Mata Atlântica), with greater FST values between biomes than within. In the life history experiments, increasing temperature reduced larval development time, adult lifespan, and wing length in all localities. The variation of family responses for all traits within four localities of the Amazonia biome was significant (ANOVA, P Conclusions SNP analysis of several Brazilian localities provided results in support of a previous study wherein populations of Ny. darlingi were clustered by three major Brazilian biomes. Our laboratory results of temperature effects demonstrated that population variation in life history traits of Ny. darlingi exists at the local level, supporting previous research demonstrating the high plasticity of this species. Understanding this plasticity and inherent variation between families of Ny. darlingi at the local level should be considered when deploying intervention strategies and may improve the likelihood of successful malaria elimination in South America.

The relationship between deforestation and malaria in Amazonian Brazil is complex, and a deeper understanding of this relationship is required to inform effective control measures in this region. Here, we are particularly interested in characterizing the impact of land use and land cover change on the genetics of the major regional vector of malaria, Nyssorhynchus darlingi (Root). We used nextera-tagmented, Reductively Amplified DNA (nextRAD) genotyping-by-sequencing to genotype 164 Ny. darlingi collected from 16 collection sites with divergent forest cover levels in seven municipalities in four municipality groups that span the state of Amazonas in northwestern Amazonian Brazil: Sao Gabriel da Cachoeira, Presidente Figueiredo, four municipalities in the area around Cruzeiro do Sul, and Labrea. Using a dataset of 5,561 Single Nucleotide Polymorphisms (SNPs), we investigated the genetic structure of these Ny. darlingi populations with a combination of model- and non-model-based analyses. We identified weak to moderate genetic differentiation among the four municipality groups. There was no evidence for microgeographic genetic structure of Ny. darlingi among forest cover levels within the municipality groups, indicating that there may be gene flow across areas of these municipalities with different degrees of deforestation. Additionally, we conducted an environmental association analysis using two outlier detection methods to determine whether individual SNPs were associated with forest cover level without affecting overall population genetic structure. We identified 14 outlier SNPs, and investigated functions associated with their proximal genes, which could be further characterized in future studies.

Background In Loreto Department, Peru, a successful 2005–2010 malaria control programme (known as PAMAFRO) included massive distribution of long-lasting insecticidal nets (LLINs). Additional local distribution of LLINs occurred in individual villages, but not between 2012 and 2015. A 2011–2012 study of the primary regional malaria vector Anopheles darlingi detected a trend of increased exophagy compared with pre-PAMAFRO behaviour. For the present study, An. darlingi were collected in three villages in Loreto in 2013–2015 to test two hypotheses: (1) that between LLIN distributions, An. darlingi reverted to pre-intervention biting behaviour; and, (2) that there are separate sub-populations of An. darlingi in Loreto with distinct biting behaviour. Results In 2013–2015 An. darlingi were collected by human landing catch during the rainy and dry seasons in the villages of Lupuna and Cahuide. The abundance of An. darlingi varied substantially across years, villages and time periods, and there was a twofold decrease in the ratio of exophagic:endophagic An. darlingi over the study period. Unexpectedly, there was evidence of a rainy season population decline in An. darlingi. Plasmodium-infected An. darlingi were detected indoors and outdoors throughout the night, and the monthly An. darlingi human biting rate was correlated with the number of malaria cases. Using nextRAD genotyping-by-sequencing, 162 exophagic and endophagic An. darlingi collected at different times during the night were genotyped at 1021 loci. Based on model-based and non-model-based analyses, all genotyped An. darlingi belonged to a homogeneous population, with no evidence for genetic differentiation by biting location or time. Conclusions This study identified a decreasing proportion of exophagic An. darlingi in two villages in the years between LLIN distributions. As there was no evidence for genetic differentiation between endophagic and exophagic An. darlingi, this shift in biting behaviour may be the result of behavioural plasticity in An. darlingi, which shifted towards increased exophagy due to repellence by insecticides used to impregnate LLINs and subsequently reverted to increased endophagy as the nets aged. This study highlights the need to target vector control interventions to the biting behaviour of local vectors, which, like malaria risk, shows high temporal and spatial heterogeneity. Electronic supplementary material The online version of this article (10.1186/s12936-018-2234-4) contains supplementary material, which is available to authorized users.

Population structure inference using the software STRUCTURE has become an integral part of population genetic studies covering a broad spectrum of taxa including humans. The ever-expanding size of genetic data sets poses computational challenges for this analysis. Although at least one tool currently implements parallel computing to reduce computational overload of this analysis, it does not fully automate the use of replicate STRUCTURE analysis runs required for downstream inference of optimal K. There is pressing need for a tool that can deploy population structure analysis on high performance computing clusters. We present an updated version of the popular Python program StrAuto, to streamline population structure analysis using parallel computing. StrAuto implements a pipeline that combines STRUCTURE analysis with the Evanno Δ K analysis and visualization of results using STRUCTURE HARVESTER. Using benchmarking tests, we demonstrate that StrAuto significantly reduces the computational time needed to perform iterative STRUCTURE analysis by distributing runs over two or more processors. StrAuto is the first tool to integrate STRUCTURE analysis with post-processing using a pipeline approach in addition to implementing parallel computation – a set up ideal for deployment on computing clusters. StrAuto is distributed under the GNU GPL (General Public License) and available to download from http://strauto.popgen.org .

Made available in DSpace on 2018-12-11T17:31:27Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-02-13 Background: In recent decades, throughout the Amazon Basin, landscape modification contributing to profound ecological change has proceeded at an unprecedented rate. Deforestation that accompanies human activities can significantly change aspects of anopheline biology, though this may be site-specific. Such local changes in anopheline biology could have a great impact on malaria transmission. The aim of this study was to investigate population genetics of the main malaria vector in Brazil, Anopheles darlingi, from a microgeographical perspective. Methods: Microsatellites and ddRADseq-derived single nucleotide polymorphisms (SNPs) were used to assess levels of population genetic structuring among mosquito populations from two ecologically distinctive agricultural settlements (~60 km apart) and a population from a distant (~700 km) urban setting in the western Amazon region of Brazil. Results: Significant microgeographical population differentiation was observed among Anopheles darlingi populations via both model- and non-model-based analysis only with the SNP dataset. Microsatellites detected moderate differentiation at the greatest distances, but were unable to differentiate populations from the two agricultural settlements. Both markers showed low polymorphism levels in the most human impacted sites. Conclusions: At a microgeographical scale, signatures of genetic heterogeneity and population divergence were evident in Anopheles darlingi, possibly related to local environmental anthropic modification. This divergence was observed only when using high coverage SNP markers. Biotechnology Institute (IBTEC) and Biosciences Institute at Botucatu (IBB) Sao Paulo State University (UNESP) Department of Biomedical Sciences School of Public Health University at Albany State University of New York New York State Department of Health Wadsworth Center Division of Infectious Diseases Department of Medicine University of California San Diego Instituto de Medicina Tropical Alexander von Humboldt, Departamento de Ciencias Celulares y Moleculares Laboratorio de Investigación y Desarrollo Universidad Peruana Cayetano Heredia Biology Department St. Mary's College of Maryland Biotechnology Institute (IBTEC) and Biosciences Institute at Botucatu (IBB) Sao Paulo State University (UNESP)

Identifying regions of the genome contributing to phenotypic evolution often involves genetic mapping of quantitative traits. The focus then turns to identifying regions of ‘major’ effect, overlooking the observation that traits of ecological or evolutionary relevance usually involve many genes whose individual effects are small but whose cumulative effect is large. Herein, we use the power of fully interfertile natural populations of a single species of mosquito to develop three quantitative trait loci (QTL) maps: one between two post-glacially diverged populations and two between a more ancient and a post-glacial population. All demonstrate that photoperiodic response is genetically a highly complex trait. Furthermore, we show that marker regressions identify apparently ‘non-significant’ regions of the genome not identified by composite interval mapping, that the perception of the genetic basis of adaptive evolution is crucially dependent upon genetic background and that the genetic basis for adaptive evolution of photoperiodic response is highly variable within contemporary populations as well as between anciently diverged populations.

The genetic relationship between the daily circadian clock and the seasonal photoperiodic timer remains a subject of intense controversy. In Wyeomyia smithii, the critical photoperiod (an overt expression of the photoperiodic timer) evolves independently of the rhythmic response to the Nanda–Hamner protocol (an overt expression of the daily circadian clock) over a wide geographical range in North America. Herein, we focus on these two processes within a single local population in which there is a negative genetic correlation between them. We show that antagonistic selection against this genetic correlation rapidly breaks it down and, in fact, reverses its sign, showing that the genetic correlation is due primarily to linkage and not to pleiotropy. This rapid reversal of the genetic correlation within a small, single population means that it is difficult to argue that circadian rhythmicity forms the necessary, causal basis for the adaptive divergence of photoperiodic time measurement within populations or for the evolution of photoperiodic time measurement among populations over a broad geographical gradient of seasonal selection.

The distinction between model and nonmodel organisms is becoming increasingly blurred. High-throughput, second-generation sequencing approaches are being applied to organisms based on their interesting ecological, physiological, developmental, or evolutionary properties and not on the depth of genetic information available for them. Here, we illustrate this point using a low-cost, efficient technique to determine the fine-scale phylogenetic relationships among recently diverged populations in a species. This application of restriction site-associated DNA tags (RAD tags) reveals previously unresolved genetic structure and direction of evolution in the pitcher plant mosquito, Wyeomyia smithii , from a southern Appalachian Mountain refugium following recession of the Laurentide Ice Sheet at 22,000–19,000 B.P. The RAD tag method can be used to identify detailed patterns of phylogeography in any organism regardless of existing genomic data, and, more broadly, to identify incipient speciation and genome-wide variation in natural populations in general.

The major drivers of the extensive biodiversity of the Neotropics are proposed to be geological and tectonic events together with Pliocene and Pleistocene environmental and climatic change. Geographical barriers represented by the rivers Amazonas/Solimões, the Andes and the coastal mountain ranges in eastern Brazil have been hypothesized to lead to diversification within the primary malaria vector, Anopheles (Nyssorhynchus) darlingi Root, which primarily inhabits rainforest. To test this biogeographical hypothesis, we analyzed 786 single nucleotide polymorphisms (SNPs) in 12 populations of An. darlingi from across the complex Brazilian landscape. Both model-based (STRUCTURE) and non-model-based (Principal Components and Discriminant Analysis) analysis of population structure detected three major genetic clusters that correspond with newly described Neotropical biogeographical regions: 1) Atlantic Forest province (= southeast population); 2) Parana Forest province (= West Atlantic forest population, with one Chacoan population - SP); and 3) Brazilian dominion population (= Amazonian population with one Chacoan population - TO). Significant levels of pairwise genetic divergences were found among the three clusters, allele sharing among clusters was negligible, and geographical distance did not contribute to differentiation. We infer that the Atlantic forest coastal mountain range limited dispersal between the Atlantic Forest province and the Parana Forest province populations, and that the large, diagonal open vegetation region of the Chacoan dominion dramatically reduced dispersal between the Parana and Brazilian dominion populations. We hypothesize that the three genetic clusters may represent three putative species.