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ABSTRACT To analyze the genetic relatedness and phylogeographic structure of _Anopheles darlingi_ from 19 localities throughout Central and South America, we used a minimum spanning network,

diversity measures, differentiation, neutrality tests, and mismatch distribution with mitochondrial cytochrome oxidase subunit I (_COI_) sequences. All the Central American haplotypes were

separated by seven mutational steps from the South American haplotypes and the _F_ST distance-based neighbor-joining tree showed a primary division between Central and South America,

evidence for a putative gene pool division. More ancestral and diverse haplotypes were found in Amazonian and southern Brazil populations, suggesting that Central American populations may

have originated in South America. The patterns of the mtDNA haplotype diversity and five of six tests for equilibrium implicate demographic expansion in the South American populations as the

historical structure, but mismatch distribution depicts populations at mutation drift equilibrium (MDE). In South America, the departure from equilibrium was consistent with an expansion

that occurred during the Pleistocene. SIMILAR CONTENT BEING VIEWED BY OTHERS INTEGRATED TAXONOMY TO ADVANCE SPECIES DELIMITATION OF THE _ANOPHELES MACULIPENNIS_ COMPLEX Article Open access

28 December 2024 THE ORIGIN OF ISLAND POPULATIONS OF THE AFRICAN MALARIA MOSQUITO, _ANOPHELES COLUZZII_ Article Open access 26 May 2021 POPULATION GENOMIC EVIDENCE OF A PUTATIVE ‘FAR-WEST’

AFRICAN CRYPTIC TAXON IN THE _ANOPHELES GAMBIAE_ COMPLEX Article Open access 10 September 2024 INTRODUCTION Globally, there are approximately 273 million annual malaria cases, and greater

than 2.1 billion people are at risk of malaria (WHO/TDR, 2004). There are an estimated 960 000 cases of malaria reported in the Americas, and approximately 41% occur in Brazil (99% in the

Amazon region) (PAHO, 2002). One of the factors determining the degree of malaria endemicity in a susceptible geographic region is the species of mosquito vector present. Vector species and

population differences within species influence biting times, feeding and resting sites, and anthropophily (Lounibos and Conn, 2000), and these behaviors determine human mosquito contact.

The factors that affect the vector's capacity to transmit the plasmodium parasite vary with species and population, and include mosquito abundance, infection rate, anthropophily, and

longevity (Foster and Walker, 2002). In the Neotropics, relative abundances of important malaria vectors have changed temporally, such as _Anopheles albitarsis_ in southeastern Brazil

(Forattini et al, 1993), _Anopheles marajoara_ in northern Amazonian Brazil (Conn et al, 2002; Lehr, 2003) and _A. darlingi_ in western Amazonian Brazil (Soares Gil et al, 2003) and in the

city of Belém (Póvoa et al, 2003). _Anopheles albitarsis_ has emerged in southeastern Brazil possibly due to the development of irrigated land (Forattini et al, 1993). _Anopheles

darlingi_'s recent resurgence, in places such as Iquitos, Peru has been linked to increased malaria cases (Aramburu Guarda et al, 1999; Schoeler et al, 2003). The resurgence of _A.

darlingi_ is proposed to be a result of human migration and land use changes, which often result in invasion of its primary breeding sites along warm lowland rivers and subsequent increased

abundance (Charlwood, 1996; Conn et al, 1999). Such anthropogenic changes highlight important aspects of targeted malaria control: the possibility of altering locally important vectors, and

complicated interactions with human populations (Conn et al, 2002; Póvoa et al, 2003). _Anopheles darlingi_ is the most important malaria vector in the Amazon Basin (Deane, 1947, 1988). In

addition to high rates of infection, _A. darlingi_ is also a good malaria vector owing to its anthropophilic (Charlwood and Alecrim, 1989) and endophagic (feeds indoors) behavior

(Lourenço-de-Oliveira et al, 1989); although recently it is thought to have evolved to be more exophilic (rests outdoors) as a result of prolonged residual insecticide use in many regions

(Charlwood, 1996; Soares Gil et al, 2003). _Anopheles darlingi_ has an extensive distribution from southern Mexico to southern Brazil (Forattini, 1962). Although there are no documented

barriers to gene flow for _A. darlingi_, rDNA data that detected a fixed insertion/deletion in samples from Belize, but not in those from South America (Manguin et al, 1999), are suggestive.

_Anopheles albimanus_ and _A. pseudopunctipennis_, with distributions similar to _A. darlingi_, are differentiated between Central and South America (De Merida et al, 1995, 1999; Manguin et

al, 1995), possibly due to vicariance (Krzywinski and Besansky, 2003) or barriers to gene flow in Costa Rica and Panama (Molina-Cruz et al, 2004). Even though _A. darlingi_ is considered a

single species (reviewed in Manguin et al, 1999; Lounibos and Conn, 2000), it does exhibit heterogeneity in body size (Charlwood, 1996) and in some genetic markers such as polytene

chromosomes (Kreutzer et al, 1972), mtDNA (Freitas-Sibajev et al, 1995; Conn et al, 1999) and rDNA ITS2 sequences (Malafronte et al, 1999). The observed heterogeneity can affect important

behavioral determinants of vector efficiency, such as endophily (rests indoors) and possibly dispersal ability (range expansion) (Lounibos and Conn, 2000; Fairley et al, 2002). Within

species differentiation can also affect the efficacy of control techniques; for example, variation in biting times can affect usefulness of personal protection measures (Zimmerman and

Voorham, 1997). Owing to their relationship to human populations, many anopheline mosquito species are likely to violate mutation drift equilibrium (MDE) assumptions (Donnelly et al, 2001).

One result of this is inaccurate estimates of gene flow, which can confound potential choices of target populations for the introduction of refractory genes. Avise (2000) suggests that

closely related species in the same geographic region should have similar demographic histories due to their phylogenetic relatedness. In the northeastern Amazon, Lehr (2003) demonstrated

that _A. marajoara_, a close relative of _A. darlingi_ (Sallum et al, 2000), has undergone a recent population expansion, and is therefore not at MDE. In the present study, we analyze the

population structure of _A. darlingi_ from 19 localities throughout Central and South America, including Brazil, Peru, Belize, Colombia, French Guiana, and Guatemala. Using sequences of the

mitochondrial cytochrome oxidase subunit I (_COI_) gene, we test the hypothesis that _A. darlingi_ will have a similar demographic history to _A. marajoara_ in the northeastern Amazon

(Avise, 2000) and determine whether there is a division in the gene pool between Central and South America, as proposed by Krzywinski and Besansky (2003). MATERIALS AND METHODS MOSQUITO

COLLECTIONS Adult _A. darlingi_ were collected outdoors between 19:00 and 21:00 h by human landing catches and identified morphologically using the key of Deane et al (1946). The human

landing catch protocol was reviewed and approved by the Institutional Review Board of the New York State Department of Health and by the Biosafety Committee of the Instituto Evandro Chages,

Belém, Brazil. Table 1 depicts the 19 localities, longitude and latitude of each site, and number of mosquitoes sequenced. All mosquitoes were maintained in 95% ethanol at −80°C until use.

DNA from each specimen used herein has been retained as a frozen voucher at −80°C in the Conn Laboratory. DNA EXTRACTION AND SEQUENCING DNA was isolated from the head, thorax, or legs using

the DNeasy tissue kit, following standard DNeasy Tissue Handbook protocol for isolation of total DNA from animal tissues (Qiagen, CA, USA). A 1300 bp fragment of the _COI_ gene was amplified

using the forward primer UEA3 and the reverse primer UEA10 (Lunt et al, 1996). Each individual PCR reaction was performed using a Ready-To-Go-PCR bead (Amersham Pharmacia/Biotech, NJ, USA)

and run on a PTC-200 thermal cycler (BioRad, Inc.). The PCR products were cleaned with CentriSpin 40 columns (Princeton Separations, NJ, USA), and sent to the Wadsworth Center Molecular

Genetics Core for sequencing. The forward and reverse sequences were aligned using Sequencher 3.0 (Gene Codes Corp, MI, USA), grouped together by site and trimmed in PAUP, version 4.0

(Swofford, 2003), creating a 978 bp fragment of the _COI_ gene. Unique haplotypes were determined using MacClade, version 3.0 (Maddison and Maddison, 1997); identical sequences were

considered to be a single haplotype. PHYLOGENETIC RELATEDNESS The number of mutational steps necessary to link any two haplotypes with 95% confidence level was determined in ParsProb 1.1

(Posada et al, 2000). A minimum spanning network of the _A. darlingi_ haplotypes was created using TCS 1.12 (Clement et al, 2000). Phylogenetic relationships among the haplotypes were

estimated with PAUP using maximum likelihood and maximum parsimony (Swofford, 2003), and with Mr Bayes using a Bayesian approach (Rannala and Yang, 1996; Mau and Newton, 1997; Mau et al,

1999). _Anopheles albimanus_ was used as an outgroup (Sallum et al, 2000). Pairwise population estimates of _F_ST were computed using Arlequin 2.01 (Schneider et al, 2000), and the _F_ST

values were used as distance measures to create a neighbor-joining (NJ) tree using Mega V2.1 (Kumar et al, 2001). HISTORICAL DEMOGRAPHY The haplotype and nucleotide diversities were computed

in Arlequin 2.01 (Schneider et al, 2000). Nei's _G_ST was calculated to estimate the population differentiation based on differences in allele frequencies; Nei's _N_M was used to

estimate gene flow based on _G_ST (Nei, 1973). The tests of Tajima (1989) and Fu and Li (1993) were used to test the hypothesis that all mutations are selectively neutral (Kimura, 1983).

Tajima's _D_T (1989) is based on the differences between the number of segregating sites and the average number of nucleotide differences. The _D_ and _F_ tests, proposed by Fu and Li

(1993), are based on molecular polymorphism data. Fu's _F_S test (1997) and Strobeck's _S_ statistic (1987) assess the haplotype structure based on the haplotype frequency

distribution, and were used as additional tests of neutrality. These analyses were calculated using DnaSP, version 3 (Rozas and Rozas, 1999). The mismatch distribution (a frequency

distribution of the observed number of pairwise sequence differences) was performed to distinguish between a smooth unimodal distribution and a multimodal, or ragged, distribution (Slatkin

and Hudson, 1991; Rogers and Harpending, 1992; Rogers, 1995). The raggedness (_r_) statistic was calculated to quantify the smoothness of the mismatch distribution (Harpending et al, 1993).

The Mantel analysis was used to test the null hypothesis of the independence of the geographic and genetic distance by a pairwise matrix of geographical and genetic distances (estimated by

_F_ST). The mismatch distribution and Mantel test (Mantel, 1967) were calculated in Arlequin 2.01 (Schneider et al, 2000), and the raggedness test in DnaSP, version 3 (Rozas and Rozas,

1999). Significance of the Mantel test was determined by a permutation test of _n_=1000. RESULTS GENETIC VARIATION Of the 36 unique haplotypes detected, seven were shared (A, B, C, J, T, W,

and X); the remainder were unique to a single geographic location (Figure 1). All the sequences were A–T rich (combined frequency of 72.05%), which is expected within Insecta. Sixty-nine

transitions and seven transversions were identified, and there were four nonsynonymous mutations. A mutation at position 45 resulted in a methionine present in haplotype V (_A. darlingi_ in

ARA) in place of a valine in all other haplotypes. Another southern Amazonian mutation resulted in an isoleucine in place of a valine in haplotype W (_A. darlingi_ in ARA, BEL, and CAP). A

nonsilent mutation at position 193 produced a threonine in haplotype N (_A. darlingi_ in NEC) where an alanine is present in all other haplotypes; and a mutation in haplotype Q (_A.

darlingi_ in IQ) resulted in an alanine in place of a threonine. There were no nonfunctional genes (ie, pseudogenes) as shown by the absence of stop codons, the prevalence of synonymous

substitutions, low pairwise divergence and clear electrophorograms. The two most common haplotypes were T (_n_=17) in Belize and Guatemala, and B (_n_=15) in northeastern Amazonian Brazil

(Table 2). Localities south of the Amazon region in Brazil have the highest haplotype diversities (ITB, MOJ, PEX, and DOU), and localities just northeast and southeast of the Amazon have the

most shared haplotypes within the populations (TAR, LI, ANT, TRP; TAI, BEL, ARA, PEB, and CAP) (Figure 1; Table 2). Populations in close geographic proximity have the greatest quantity of

shared haplotypes, and populations that are farther apart do not share haplotypes. Interestingly, localities directly northeast (TAR, LI, ANT, and TRP) and southeast of the Amazon (TAI, BEL,

ARA, PEB, MOJ, and CAP) do not share haplotypes, and localities northeast of the Amazon (TAR, LI, ANT, and TRP) only have two unique haplotypes (Table 2). Haplotypes in Peru and Colombia

are not shared among any other population, which could be due to their geographic separation from other localities sampled and (or) potential geographic or climatic barriers. In general,

these data would seem to support the isolation by distance model (Wright, 1951). Belize and Guatemala had low diversity with only four haplotypes identified from 21 mosquitoes analyzed.

Haplotype X is shared among the greatest number of populations in Brazil, followed by B and C (Table 2). Sequences for _A. darlingi_ and _A. albimanus_ used in this study have been deposited

in GenBank, accession numbers DQ298209 to DQ298244. PHYLOGEOGRAPHIC RELATEDNESS The minimum spanning network illustrates the mutational relationship of the _A. darlingi_ haplotypes (Figure

2). All haplotypes differed by less than 13 mutational steps, so they could be connected parsimoniously. The Central American haplotypes are separated by seven mutational steps from the

Colombian haplotypes (M and N), which are separated by an additional seven mutational steps from a Brazilian haplotype, DA. Many southern Amazonian Brazil haplotypes (X, C, W, V, Y, K, I)

differed by only one or two mutational steps, suggestive of a demographic expansion (Slatkin and Hudson, 1991; Fu, 1997). Haplotype X was the most common interior haplotype, so is most

likely the oldest haplotype (Castelloe and Templeton, 1994). The majority of haplotypes were tip alleles, and are considered as more recently derived and geographically restricted (Crandall

and Templeton, 1993; Castelloe and Templeton, 1994). The phylogenetic relationship among the haplotypes using the maximum-likelihood, maximum-parsimony, and Bayesian analyses were all very

poorly resolved and not informative because the sequence variation contains insufficient phylogenetic signal (data not shown). The _F_ST pairwise estimates of differentiation ranged from 0

to 1, and were used to create the NJ tree. Two primary clusters were found: (I) South America, and, (II) Central America plus NW Colombia (Figure 3). There appears to be a secondary division

within cluster I between the southern Amazon and southern South America (IA) and the Northern Amazon (IB). The pairwise comparisons of _F_ST within clusters I and II were 52.5 and 55%

significant, respectively, and the _F_ST comparisons between clusters were 100% significant (_F_ST values shown in Table 3) (Donnelly et al, 2004). Additional support for the primary

division is found from samples of the conserved nuclear _white_ gene that were cloned and sequenced for over 200 samples of _A. darlingi_ from most of the same localities as in the current

study (Mirabello and Conn, unpublished). HISTORICAL DEMOGRAPHY Nucleotide and haplotype diversities were used as measures of genetic diversity of _A. darlingi_. Haplotypes B and T had the

greatest haplotype frequency (Table 2). ITB, CAP, and PEX had the highest haplotype diversities. ANT, TAI, and CAY had no detectable diversity measures because only a single haplotype was

detected in each. Both of the diversity measures were high in ITB, DOU, and IQ. The NJ cluster with the greatest haplotype diversity was IA, and IB had the highest nucleotide diversity (also

having the greatest average number of nucleotide differences). Cluster II had low haplotype and nucleotide diversity measures. Nei's _G_ST and _N_M (1973) were used to examine the

pairwise genetic differentiation and gene flow, respectively, between the population clusters (IA, IB, and II) (Table 4). The highest level of genetic differentiation (_G_ST=0.3109) was

detected between Central America (II) and northern Amazon (IB) (Table 4). The estimates of gene flow (_N_M) were moderate among South America populations and between Amazonian and southern

South America and Central America. Only the gene flow estimate between Central America plus NW Colombia (II) and northern Amazon (IB) was below 1. Population comparisons with _N_M values

less than 1 are considered to have no gene flow (Nei, 1973, 1975). Tajima's (1989) _D_T and Fu and Li's (1993) _F_ and _D_ neutrality tests found that cluster I and IA have

significant negative _D_ and _F_ values, and nonsignificant negative _D_T values (Table 5). The results allow rejection of the neutral model in these regions, as a result of two possible

factors: (1) a relatively recent population expansion, which can raise the number of low-frequency variants, and (2) natural selection. The neutral model is also rejected in cluster IB,

where the _D_T, _D_, and _F_ values were all significantly positive (cluster II also had positive values, but nonsignificant), which suggests possible balancing selection or population

subdivision (Table 5). Fu's _F_S test (1997) and Strobeck's _S_ statistic (1987) determined that both cluster I and IA have significantly negative _F_S values and positive _S_ of

0.995 and 1.000, respectively, indicating possible population expansion. Fu (1997) states that _F_S is the most powerful test for detecting population expansion and genetic hitchhiking,

followed by Tajima's _D_T, and Fu and Li's _D_ and _F_ tests (Fu and Li, 1993). Cluster IB has significantly positive _F_S and a low _S_ statistic of 0.0001, indicating possible

background selection. Cluster II also had a positive _F_S and low _S_-value, but they were not statistically significant. Through a graphical illustration of the mismatch distribution it is

possible to determine if there is a smooth unimodal distribution following the Poisson distribution characteristic of a recent bottleneck or population expansion, or a multimodal

distribution indicating a population at MDE. In contrast to the previous demographic history analyses for _A. darlingi_, the mismatch distribution did not demonstrate the expected unimodal

distribution for all the localities together or for either primary or secondary clusters. The observed mismatch distribution for cluster I differed significantly from the simulated

distribution of a demographic expansion model (Figure 4). The distribution for all the localities throughout Central and South America showed a multimodal distribution typical of populations

at MDE. The raggedness statistic for clusters I and IB are both very small (0.0174 and 0.0105, respectively), suggesting a population expansion. Cluster IB has a large _r_-value (0.7395),

indicating a population at equilibrium. Time since the population expansion can be estimated from _t_=_τ_/2_μ_, where _μ_ is the mutation rate per site per generation (Slatkin and Hudson,

1991). The Drosophila mutation rate of 10−8/site/year (Powell et al, 1986) and 10 generations/year (Walton et al, 2000) were used in the calculation. The estimate of _τ_, from the raggedness

calculation, is 4.951 for cluster I, and 3.176 for cluster IA. Therefore, the time to expansion for _A. darlingi_ in South America is approximately 253 119 years ago (95% CI, 85 554–402 

419), and in Amazonian and southern South America is approximately 162 372 years ago (95% CI, 54 882–258 144). Both expansion times are during the late Pleistocene. The Mantel analysis to

test the null hypothesis of the independence of the geographic and genetic distance between each population was conducted to test for isolation by distance. The correlation was not

significant (_R_2=0.011, _P_=0.489). DISCUSSION In a review of evolutionary studies Donnelly et al (2002) claim that the genetic population structure of primary malaria vectors is shallow

with a weak effect of distance on differentiation, and this has been supported by studies of the major African vectors _A. gambiae_ (Lehmann et al, 1996) and _A. arabiensis_ (Donnelly and

Townson, 2000). Our analyses detected considerable population structure, and isolation by distance was detected by Conn et al (1999) for _A. darlingi_ in South America. A similar pattern was

also found in neotropical vectors _A. aquasalis_ (Fairley et al, 2002) and _A. albimanus_ (De Merida et al, 1999), although in a more recent study in the latter species the effect of

distance on differentiation was weak (Molina-Cruz et al, 2004). In our study of _A_. _darlingi_, the inference of range expansion was well supported but isolation by distance was not.

Isolation by distance and the low nucleotide diversity observed in Central American populations of _A. albimanus_ and low nucleotide diversity in _A. darlingi_ could be due to small

effective migration rates and effective population size, and/or genetic drift (De Merida et al, 1999; Molina-Cruz et al, 2004). The nucleotide diversity estimates for _A. gambiae_ are also

low, which is consistent with a large panmictic population (Besansky et al, 1997; Lehmann et al, 1998). These differences may be due to lack of isolation by distance in the African

_Anopheles_, as compared to the Neotropical _Anopheles_, and their high dispersal ability, large effective population size, and/or recent range expansion (corresponding to the human

population expansion during the arrival of agriculture in West Africa) (Lounibos and Conn, 2000; Donnelly et al, 2001, 2002). The _N_M estimates between Central America and the northern

Amazon indicated little or no recurrent gene flow (_N_M<1). Contemporary gene flow estimates are important in malaria vectors because they are used to predict the spread of genes,

essential information for effective introduction of transgenes for _Plasmodium_ resistance (Cohuet et al, 2005; Tripet et al, 2005). No gene flow combined with high genetic differentiation

may be the result of vicariance or obstruction by natural barriers (ie, topography or habitat that a migrating individual cannot cross) existing between Central America and northern Amazon.

_Anopheles albimanus_ data suggest that a single barrier exists within Central America, which may be the mountain range that crosses Costa Rica and Western Panama (Molina-Cruz et al, 2004).

The phylogeographic break between Central American plus NW Colombia and South American _A. darlingi_ is consistent with studies of other Neotropical taxa, such as Neotropical butterflies

(Brower 1994), toads (Slade and Moritz, 1998), bats (Hoffmann and Baker, 2003) and trees (Dick et al, 2003). However, Manguin et al (1999) observed substantial gene flow among populations of

_A. darlingi_ throughout its geographic range using four nonmitochondrial markers (isozyme, RAPD-PCR, ITS2, and morphology). These conflicting results may be due to the differences in

mitochondrial and nuclear DNA inheritance and evolutionary histories which can affect estimates of gene flow (Presa et al, 2002). Mitochondrial DNA evolves relatively rapidly, it is

maternally inherited, and has an extremely low level of recombination as compared to the nuclear genome (Avise, 2000). Manguin et al (1999) found that _A. darlingi_ from Belize differed from

all the South American populations by a three-base deletion in the rDNA ITS2 marker. There is no evidence of clinal variation, and the range of _A. darlingi_ in Central America is narrow

(Manguin et al, 1999). Therefore, Manguin et al (1999) suggested the differentiation is either due to a recent introduction event that may have been caused by humans, or an extrinsic factor.

One interpretation of our data is a possible introduction event from Colombian _A. darlingi_ populations into Central America. More ancestral and diverse haplotypes were observed in

Amazonian and southern Brazil populations, so they are likely older, and Colombian haplotypes are, of the South American samples examined in this study, most closely related to the Central

American haplotypes. In general, older populations have a higher diversity than younger populations (Kambhampati and Rai, 1991; Molina-Cruz et al, 2004). In our study, the older populations

with the highest diversity are ITB, CAP and PEX, and cluster IA (Amazonian and southern South America). According to Avise (2000), high haplotype diversity relative to the nucleotide

diversity suggests a population bottleneck followed by a rapid population expansion and buildup of mutations; nearly all the populations (except TAI and PEB) of _A. darlingi_ in cluster IA,

and all the localities together fit this criterion. We hypothesized that the Amazonian populations of _A. darlingi_ had undergone a population expansion similar to _A. marajoara_ in northern

Brazil (Lehr, 2003), based on regional patterns determined for many organisms reviewed in Avise (2000). The large proportion of shared haplotypes and lack of unique haplotypes in the Amazon

region in Brazil, and most of the demographic history analyses support an expansion in Amazonian and southern South America populations of _A. darlingi_. However, mismatch analysis shows a

multimodal pattern characteristic of populations at MDE. Harpending (1994) states that a population expansion that is too recent, for example at the end of the Pleistocene epoch, would not

result in a smooth unimodal mismatch distribution. MDE is thought to be achieved when the effective population (_N_e) size has stayed constant for 2_N_e–4_N_e generations (Nei and Li, 1976).

_A. darlingi_ population size probably fluctuates due to its dependence on specific climatic and environmental conditions, which have changed dramatically over the last millennia (Prance,

1982; Absy et al, 1991; Cavalli-Sforza et al, 1994; Nicholson, 1995; Donnelly et al, 2001). The estimated expansion time for _A. marajoara_ was much more recent (36 400 years ago in the

eastern Amazon; Lehr, 2003) as compared to _A. darlingi_ (estimated time to expansion is >100 000 years). This difference may reflect the cycles of Amazonian savannah contraction and

re-expansion, and thus habitat availability owing to the differences in habitat preference between _A. marajoara_ (breeding sites associated with savannah and agricultural habitat; Conn et

al, 2002; Lehr, 2003) and _A. darlingi_ (primary breeding sites along warm lowland rivers; Rozendaal, 1990; Roberts et al, 2002). If _A. darlingi_, like other primary vectors (eg, _A.

gambiae_) has only recently become a human pest, it would be expected to show a recent population expansion. However, the historical human population expansion in the Amazon region is

predicted to have occurred between 10 000 (Roosevelt et al, 1991) and 2500 years BP (Willis et al, 2004), and a rapid decline in indigenous human population size occurred after colonial

contact in the 18th–19th centuries (Willis et al, 2004). Brazilian government settlement policies, still in effect today, have caused nonindigenous human populations in many areas of the

Amazon in Brazil to expand significantly during the 20th century (Cruz Marques, 1987; Alecrim, 1992; Schmink and Wood, 1992). Our estimates support a very different history for _A. darlingi_

in South America compared with _A. gambiae_ in subSaharan Africa, despite both being primary vectors. _Anopheles darlingi_ being a more opportunistic feeder (Charlwood, 1996) is not nearly

as dependent on human blood meals compared with _A. gambiae_ (White, 1974; Coluzzi et al, 1979; Besansky et al, 2004). Therefore its populations are more likely to fluctuate based on

climatic conditions (that would influence breeding site availability) compared with _A. gambiae_'s noteworthy dependence on human population densities (Coluzzi, 1982; Donnelly et al,

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CAS  Google Scholar  Download references ACKNOWLEDGEMENTS We are particularly grateful to Drs Robert H Gilman, Ranulfo González, John P Grieco, Sylvie Manguin, Marinete M Póvoa, Norma

Padilla, and Richard C Wilkerson for providing samples. We thank members of the Conn laboratory for technical help and advice. We appreciate the comments of two anonymous reviewers who

improved this manuscript. This study was funded by National Institutes of Health grants AI R2940116 and AI R0154139 to JEC. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of

Biomedical Sciences, Division of Immunology and Infectious Disease, University at Albany, State University of New York, 1400 Washington Avenue, Albany, 12222, NY, USA L Mirabello & J E

Conn * New York State Department of Health, Wadsworth Center, Griffin Laboratory, 5668 State Farm Road, Slingerlands, 12159, NY, USA J E Conn Authors * L Mirabello View author publications

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Correspondence to J E Conn. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Mirabello, L., Conn, J. Molecular population genetics of the malaria vector

_Anopheles darlingi_ in Central and South America. _Heredity_ 96, 311–321 (2006). https://doi.org/10.1038/sj.hdy.6800805 Download citation * Received: 24 March 2005 * Accepted: 15 November

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KEYWORDS * _Anopheles darlingi_ * malaria vector * population genetics * mtDNA * range expansion