The human DARC (Duffy antigen receptor for chemokines) gene encodes a membrane-bound chemokine receptor crucial for the infection of red blood cells by Plasmodium vivax, a major causative agent of malaria. Of the three major allelic classes segregating in human populations, the FY*O allele has been shown to protect against P. vivax infection and is at near fixation in sub-Saharan Africa, while FY*B and FY*A are common in Europe and Asia, respectively. Due to the combination of strong geographic differentiation and association with malaria resistance, DARC is considered a canonical example of positive selection in humans. Despite this, details of the timing and mode of selection at DARC remain poorly understood. Here, we use sequencing data from over 1,000 individuals in twenty-one human populations, as well as ancient human genomes, to perform a fine-scale investigation of the evolutionary history of DARC. We estimate the time to most recent common ancestor (TMRCA) of the most common FY*O haplotype to be 42 kya (95% CI: 34–49 kya). We infer the FY*O null mutation swept to fixation in Africa from standing variation with very low initial frequency (0. 1%) and a selection coefficient of 0. 043 (95% CI: 0. 011–0. 18), which is among the strongest estimated in the human genome. We estimate the TMRCA of the FY*A mutation in non-Africans to be 57 kya (95% CI: 48–65 kya) and infer that, prior to the sweep of FY*O, all three alleles were segregating in Africa, as highly diverged populations from Asia and ≠Khomani San hunter-gatherers share the same FY*A haplotypes. We test multiple models of admixture that may account for this observation and reject recent Asian or European admixture as the cause.
Infectious diseases have played a crucial part in shaping current and past human demography and genetics. Among all infectious diseases affecting humans, malaria has long been recognized as one of the strongest selective pressures in recent human history [1,2]. The Duffy antigen, also known as DARC (Duffy antigen receptor for chemokines) and more recently as ACKR1 (atypical chemokine receptor 1), is a transmembrane receptor used by Plasmodium vivax, a malaria-causing protozoan, to infect red blood cells. P. vivax causes a chronic form of malaria and is the most widespread type of malaria outside of Africa [3,4]. The DARC gene has three major allelic types that are the product of two common polymorphisms, forming the basis of the Duffy blood group system [5,6]. The two variant forms, FY*B and FY*A, are the allelic types commonly observed in non-African populations. FY*B is the ancestral form of the receptor, and is widespread in Europe and parts of Asia. FY*A is defined by a derived non-synonymous mutation (D42G, rs12075) in the P. vivax binding region of the DARC protein. It is the most prevalent of the three alleles in modern human populations, with highest frequency in Asia (predicted frequency >80%) and at 30–50% frequency in Europe [4]. FY*A is also present in southern Africa, despite absence from western and central Africa [4,7–9]. FY*O (also known as Duffy null) is defined by a mutation (T-42C, rs2814778) in the GATA-1 transcription factor binding site in the DARC gene promoter region, and occurs mostly on a FY*B background. The derived FY*O mutation exhibits extreme geographic differentiation, being near fixation in equatorial Africa, but nearly absent from Asia and Europe [4]. Of the three allelic types, FY*A and FY*B are functional proteins, while FY*O does not express the protein on erythrocyte surfaces due to a mutation in the promoter region, which causes erythroid-specific suppression of gene expression [6,10]. The lack of expression of DARC in erythrocytes has been shown to halt P. vivax infection [6,10]. Moreover, recent evidence shows that heterozygous individuals have reduced DARC gene expression and evidence of partial protection against P. vivax [11,12]. It has been proposed that due to the near-fixation of FY*O, P. vivax infection in humans is largely absent from equatorial Africa. An important recent discovery suggests low levels of P. vivax infection in FY*O homozygotes [13–17], which indicates that P. vivax might be evolving escape variants able to overcome the protective effect of FY*O. Phenotypic effects of the FY*A mutation are less clear than FY*O; however, there is evidence of natural selection and reduced P. vivax infection in individuals with this genotype ([18,19], with conflicting reports in the Brazilian Amazon however [12,20,21]). There is long running interest in characterizing the evolutionary forces that have shaped the Duffy locus. The combination of strong geographic differentiation and a plausible phenotypic association (resistance to malaria) has led to the Duffy antigen being cited as a canonical example of positive selection in the human genome (eg. [22–26]); however, details of its genetic structure remain understudied. Though touted as under positive selection, the few early population genetic studies of this locus found complex signatures of natural selection [27,28] and it is rarely identified in whole genome selection scans [29–37]. Some genomic loci display signatures of selection readily captured by standard methods, yet other well-known loci, like FY*O, are overlooked potentially due to intricacies not captured by simple models of hard selective sweeps. Detailed analyses of the haplotype structure can help us better understand complicated scenarios shaping genetic variation in loci under selection. What makes the evolution of FY*O such a complex and uncommon scenario? Plasmodium species and mammals have coexisted for millions of years, with frequent cases of host-shifts and host range expansions along their evolution [38,39]. Great apes are commonly infected with malaria-related parasites [40,41] and recent evidence suggests that human P. vivax originated in African great apes [40], contrasting with previous results that supported an Asian origin for P. vivax [42,43]. In addition to the complex evolutionary relationship among Plasmodium species and mammals, the specific mechanisms of invasion of erythrocytes employed by different species are highly diverse and present commonalities among species. Plasmodium falciparum, the parasite with the highest prevalence currently in Sub-Saharan Africa presents a highly redundant set of targets that enable erythrocyte invasion, but does not include DARC [44]. On the other hand, DARC erythroid expression influences infection in a variety of other species of Plasmodium. For example, it is required for infection by Plasmodium knowlesi, a malaria parasite that infects macaques, and SNPs upstream of the DARC gene homologue in baboons influence DARC expression and correlate with infection rates of a malaria-like parasite [45,46]. Despite the general understanding of the relevance of DARC in the evolution of the interaction between Plasmodium and primates, a thorough analysis of the complex evolutionary history of this locus using recently available large-scale genomic datasets of diverse human populations is still lacking. Here, we analyze the fine scale population structure of DARC using next-generation sequencing data from twenty-one human populations (eleven African populations), as well as ancient human genomes. We estimate the time to most recent common ancestor of the FY*A and FY*O mutations and estimate the strength of selection on FY*O. We propose a model for the spread of FY*O through Africa that builds on previous findings and provides a more complete picture for the evolution of FY*O. We further explore the relationship between the common FY*A haplotype in Asia and the FY*A haplotype found in southern Africa.
We were interested in estimating the age of the FY*A and FY*O alleles and the start time of selection for FY*O, based on the average number of pairwise differences between haplotypes. For FY*O, we initially estimate the time to most recent common ancestor (TMRCA) over all FY*O haplotypes to be 230,779 years (95% CI: 169,790–291,039 years), which would imply very old selection under the assumption of a de novo sweep model. We note however that both the presence of two deeply diverged haplotypes with low levels of within-group diversity, as well as observed recombination between FY*O and the FY*A/FY*B alleles may artificially increase the estimated TMRCA. We therefore devised a strategy to remove the effects of recombination and estimate the TMRCA separately on each of the two major haplotypes, in order to obtain an approximate estimate for the start time of selection under the standing variation model. We estimate the major FY*O haplotype class to be 42,183 years old (95% CI: 34,100–49,030) and the minor haplotype class to be 56,052 years old (95% CI: 38,927–75,073) (S8–S10 Tables). For the FY*A allele, the allele age was estimated as 57,184 years old (95% CI: 47,785–64,732). Variation between population-specific TMRCA estimates was low. Additionally, we find that Ust’-Ishim, a 45,000 years old individual from Siberia [51] is heterozygous for FY*A. Under the assumption of no recurrent mutations, this would set a minimum age of 45,000 years for the FY*A mutation. These results corroborate our hypothesis that FY*O was an ancient sweep, likely tens of thousands of years older than most other mutations associated with malaria resistance [57]. These TMRCA estimates were used as a guide to seed our simulations for the following analysis; however, selection scenarios were not limited to these times. FY*O’s two divergent haplotypes indicate it may have reached fixation in Africa via selection on standing variation. To investigate this, we utilized an Approximate Bayesian Computation (ABC) approach to estimate the magnitude of FY*O’s allele frequency at selection onset, followed by the selection coefficient (s) of FY*O. To infer the magnitude of FY*O’s allele frequency at selection onset, we compared the posterior probability of five models of initial frequency at selection onset (de novo mutation (1/2N), 0. 1%, 1%, 10%, 25%), utilizing a Bayesian model selection approach in ABC, based on Peter et al. (2012) [58–61]. It is important to remark that we use additional summary statistics in our ABC implementation, including commonly used scans of selection. We realized that the original method proposed by Peter et al. (2012) [58] did not include any of these statistics but, as we show in this work, those prove to be highly informative of the process. Briefly, for each model we ran 100,000 simulations based on the African demographic model inferred in [62] and centered on an allele with selection coefficient drawn from the distribution 10U (−3, −0. 5). We assumed an additive selective model, as empirical studies predict heterozygotes have intermediate protection against P. vivax infection [11,12] and a selection start time similar to the estimated TMRCA of FY*O’s major haplotype (40 kya). We investigate our power to distinguish between the different models utilizing cross validation. We show that we have high power to distinguish between de novo and higher initial frequencies, though there is some overlap between adjacent models (S1 Appendix). Utilizing a multinomial logistic regression method, we observed strong support for the 0. 1% initial frequency model and low support all other models (posterior probabilities: de novo 0. 0002; 0. 1% 0. 9167; 1% 0. 0827; 10% 0. 0000; 25% 0. 0004) (S1 Appendix). We found these results to be robust to a range of recombination rates, selection start times and demographic models (Table 4 in S1 Appendix). We conclude selection on FY*O occurred on standing variation with a very low (0. 1%) allele frequency at selection onset. We next sought to infer the strength of the selective pressure for FY*O. We estimated FY*O’s selection coefficient via ABC and local linear regression, assuming an allele frequency at selection onset of 0. 1%. We find we have reasonable power to accurately infer s from these simulations; estimated and true selection coefficients have an r2 value of 0. 85 with a slight bias of regression to the mean (Fig 3 in S1 Appendix). We estimate the selection coefficient to be 0. 043 (95% CI: 0. 011–0. 18) (Fig 3). To validate our model choice, we sampled selection coefficients from this posterior distribution and ran simulations with the initial frequency drawn from either 10U (−5, −0. 5) or U (0,1). With the log-based prior distribution, we re-estimate the initial frequency at 0. 15% (95% CI: 0. 018–0. 77%; Fig 4 in S1 Appendix), closely fitting our inference. With the uniform prior distribution, we have much lower power to estimate initial allele frequency and we re-estimate the initial frequency at 6. 86% (95% CI: -20. 3–51. 6%) (Fig 5 in S1 Appendix). This is not surprising as it has previously been shown that it is very difficult to estimate initial frequency with a uniform prior [58]. We also sought to understand the history of these alleles in southern Africa as, unlike equatorial Africa, malaria is not currently endemic in southwestern Africa and past climate was potentially unsuitable for malaria. Thus, we expect there was a lower or no selection pressure for FY*O or FY*A in this region. We analyzed sequences from the Bantu-speaking Zulu and indigenous ≠Khomani San. We find all three allelic classes are present in both populations (Zulu: FY*A 6%, FY*B 16%, FY*O 79%; ≠Khomani San: FY*A: 35%, FY*B 44%, FY*O 21%). The KhoeSan peoples are a highly diverse set of southern African populations that diverged from all other populations approximately 100 kya [63], and the ≠Khomani San represent one of the populations in this group. The Zulu population is a Bantu-speaking group from South Africa; southern Bantu-speakers derive 4–30% KhoeSan ancestry [64] from recent gene flow during the past 1,000 years. We first ask if the FY*O allele in the KhoeSan group represents recent gene flow from Bantu-speakers or whether FY*O has been segregating in southern Africa for thousands of years. We investigated global and local ancestry differences between FY*O carriers and non-carriers. We find a significant difference in genome-wide western African ancestry in ≠Khomani San FY*O carriers vs. non-carriers (17% average in FY*O carriers vs. 5. 4% average in non-FY*O carriers, p = 0. 014 based on a Wilcoxon Rank-Sum test). We also find a significant enrichment of local Bantu-derived ancestry around the FY*O mutation in the ≠Khomani San FY*O carriers (p = 2. 78*10−12 based on Fisher’s exact test; S4 and S5 Figs). Each of these factors indicate that FY*O was recently derived from gene flow into the ≠Khomani San population from either Bantu-speaking or eastern African groups. We then explored the relationship of FY*O in KhoeSan and Zulu samples to Bantu-speaking populations from equatorial Africa. A haplotype network of the ≠Khomani San FY*O carriers indicated that each 20kb haplotype was identical to a haplotype from populations further north (S6 Fig). We tested the Zulu FY*O samples as well, and found that they have identical, though more diverse, haplotypes than other Bantu-speaking populations (Fig 2). However, the increase in diversity may be due to calling biases and recombination between different allelic classes in the Zulus (see discussion). We then sought to understand the prehistory of FY*A in southern Africa. The FY*A allele is common in San populations, despite its absence from equatorial Africa (Fig 1). We compared the FY*A haplotypes found in the ≠Khomani San and Zulu populations with FY*A haplotypes present in Asia and Europe to distinguish between three hypotheses. The FY*A mutation in southern Africa either was 1) segregating in the ancestral human population, 2) due to recent admixture from migrations ‘back to Africa’, or 3) arose convergently in a separate mutation event distinct from the European / Asian mutation. We find that Zulu FY*A haplotypes are highly diverse; some are identical to non-African FY*A haplotypes, while others are unique or ancestral (Fig 2). Global ancestry results show no statistically significant difference between Bantu or KhoeSan ancestry in FY*A ≠Khomani San carriers and non-carriers based on a Wilcoxon Rank-Sum test (San: p = 0. 85, Bantu: p = 0. 101). Our local ancestry results indicate that FY*A carriers are significantly enriched for San ancestry around FY*A compared with non-carriers based on Fisher’s exact test (p = 0. 011). Our results support hypothesis (1), i. e. high ≠Khomani San FY*A haplotype diversity indicates FY*A has an ancient presence in southern Africa. Furthermore, as Bantu-speaking populations from equatorial Africa currently are exclusively FY*O, it is unlikely they transferred FY*A to KhoeSan after the Bantu expansion. Rather, the FY*A haplotypes in the Zulu are largely derived from admixture with the indigenous KhoeSan populations, or potentially very recent gene flow from European/Asian immigrants to South Africa.
We estimate the TMRCA of all FY*O haplotypes to be 230,779 years (95% CI: 169,790–291,039 years) and the TMRCA of the most common haplotype class to be 42,183 years (95% CI: 34,100–49,030 years). We note that two of the assumptions of our estimation method (no recombination and star-like phylogeny) are partially violated in our data. However, we developed a strategy to mitigate the effect of recombination (see Methods) and only the TMRCA estimation with all FY*O haplotypes differs greatly from a star-like phylogeny (due to the deep divergence in the two main haplotypes). Estimates of TMRCA are also prone to large confidence intervals due to the stochasticity of the allele frequency trajectory, but all estimates indicate the FY*O mutation is older than most known malaria resistance alleles [57]. Previous estimates of the time of fixation of the FY*O mutation, based on lower density data, range from 9–63 kya (adjusted to our mutation rate and generation times) [28,73]. Other TMRCA estimates ranging from 9 to 14 kya were calculated on microsatellites linked to FY*O [73], which seem to have underestimated the age of the mutation. Perhaps the most comprehensive work on this problem until now was by Hamblin and DiRienzo [28], who estimated the time to fixation of FY*O to be 63 kya (95% CI: 13,745–205,541 years; converted to our mutation rate). This is older than our estimates, but has overlapping confidence intervals. More recently, Hodgson et al. [74] estimated the time necessary for FY*O’s frequency to increase from 0. 01–0. 99 to be 41,150 years, based on an inferred selection coefficient in Madagascar. We inferred FY*A to be an ancient mutation, likely segregating throughout Africa before FY*O swept to fixation. We estimate FY*A to be 57,187 years old (95% CI: 47,785–64,732 years), 15,000 years older than the most common FY*O haplotype and overlapping estimates of the out-of-Africa expansion time [62,75–77]. We note that the San FY*A haplotypes were not used in this TMRCA calculation as there were few homozygous sequenced FY*A San samples and we confined our estimates to homozygotes to reduce issues due to phasing errors. As we are only looking at the out-of-Africa diversity of FY*A, it is likely this TMRCA is more indicative of FY*A’s expansion during and after the out-of-Africa event. Ancient DNA from a Paleolithic hunter-gatherer provides evidence that FY*A was already present in Eurasia by at least 45,000 years ago, thereby setting a lower bound for the age of the mutation. Its intermediate frequency in ≠Khomani San and Zulu populations, and similar haplotypic structure is consistent with FY*A existence in Africa at an appreciable frequency before the out-of-Africa expansion had occurred. The deep divergence of the ≠Khomani San from all other tested populations carrying FY*A strongly supports this ancient origin. Our results are scaled with the mutation rate of 1. 2 * 10−8 mutations / basepair / generation and a 25 year generation time. This mutation rate is supported by many previous whole-genome studies ([51,78–81]; range: 1 − 1. 2 * 10−8 mutations / basepair / generation), but we are aware of recent studies suggesting a higher mutation rate that are either based on exome data ([82–84]; range: 1. 3 − 2. 2 * 10−8 mutations / basepair / generation) or whole-genome data ([85,86]; range: 1. 61 − 1. 66 * 10−8 mutations / basepair / generation). To take into account this uncertainty, we performed additional analyses using a mutation rate of 1. 6 * 10−8 mutations / basepair / generation. With this higher rate, we estimate more recent coalescent times of the FY*O and FY*A mutations; specifically we would estimate the FY*O TMRCA to be 32 kya (vs. 42 kya) and the FY*A TMRCA to be about 43 kya (vs. 57 kya). It is important to consider that most quantities in population genetics are scaled by the mutation rate and effective population size. Therefore, any changes in the mutation rate result in changes not only in our TMRCA estimates, but also in the timescale of the split between African and non-African populations. For example, a recent study of the divergence between African and non-Africans, estimates a median of divergence between 52–69 kya and a final split around 43 kya, using a mutation rate of 1. 2 * 10−8 mutations / basepair / generation [76]. If we use a higher mutation rate of 1. 6 * 10−8 mutations / basepair / generation the median divergence would be 39–52 kya with a final split around 33 kya. Thus, regardless of the mutation rate (and the corresponding demographic scenario), we estimate the FY*O mutation to have occurred soon after the estimated final split. FY*O’s two divergent, common haplotypes in Africa indicate it may have reached fixation due to selection on standing variation. We infer that the FY*O mutation underwent a selective sweep on standing variation with a selection coefficient comparable to some of the most strongly selected loci in the human genome [57]. Utilizing a Bayesian model selection approach implemented in an ABC framework, we find that FY*O likely rose to fixation via selection on standing variation; though the frequency of FY*O at selection onset was very low (0. 1%). We estimate FY*O’s selection coefficient to be 0. 043 (95% CI: 0. 011–0. 18), consistent with previous estimates (>0. 002 in the Hausa [28], 0. 066 in Madagascar [74]). The similarity of these results indicates FY*O may have a similar selective effect in diverse environments. This selection coefficient is similar to other loci inferred to have undergone strong selection in the human genome, including other malaria resistance alleles [57]. The selection coefficients of these other malaria resistance alleles were inferred via a variety of different methods, mostly utilizing simulations and a rejection framework. Our understanding of human demographic history has improved over the past few years with the increase of genomic data. Previous estimates did not consider realistic demographic models, while we utilized the African demographic model inferred in Gravel et al. [62]. Assuming the standard neutral model when the true demography is more complex may result in overestimating the selection coefficient for some of the regions mentioned in Hedrick et al. 2011 [57] (due to recent population expansions). At first glance it would be reasonable to consider such a low initial frequency equivalent to a scenario of selection on a de novo mutation. In order to distinguish between the two possibilities we use the diffusion approximation by Kimura [87,88] to estimate the probability of fixation (equation 8 in [88]) and demonstrate that it is much more likely to reach fixation with an initial frequency of 0. 1% than a scenario of a new mutation arising in the population. We find that an allele with selection coefficient 0. 043 and initial frequency 0. 001 has a 99. 4% probability of fixing, while a de novo mutation with the same s has only an 8. 2% probability of fixing. It is important to note that in our calculation the initial frequency (p) in the equation for the de novo mutation scenario is calculated using the effective population size, as opposed to the census population size. However, if we reasonably assume N ≥ Ne, p is likely at least 0. 1% in the population. This translates in our estimates for the probability of fixation of a de novo mutation being far more optimistic than expected if the ancestral African census population size was much larger than the effective size. This low initial frequency until 40 kya is consistent with FY*O’s absence from non-African present and ancient genomes. It is important to note that selection on standing variation and a soft sweep are not necessarily synonymous. Selection on standing variation (the model we are testing) asks about the frequency of the allele at selection onset. However, it is agnostic to the number of haplotypes that are actually picked up at selection onset. A soft sweep states that multiple haplotypes are picked up at selection onset. Via our msms simulations, we are unable to say, for each individual simulation, whether just one haplotype was picked up or if multiple haplotypes were picked up (either due to additional mutations or recombination). However, we note that of our accepted simulations, summary statistics of the 0. 1% model are much more diverse and much more similar to our data, than the de novo model. We speculate that this may be due to multiple haplotypes that are being picked up in the 0. 1% model. FY*O and FY*A are thought to be under positive selection due to P. vivax, a malaria-causing protozoan that infects red blood cells through the Duffy receptor. Individuals with the FY*O allele do not express the Duffy receptor in red blood cells resulting in immunity to P. vivax [6,10] and individuals with the FY*A allele may have lower infectivity rates [11,12,18–21]. Unlike P. falciparum, the most common and deadly malaria protozoan in Africa that uses multiple entry receptors, P. vivax’s one mode of entry allows the possibility of resistance with only one SNP. Was P. vivax the selective pressure for either the FY*O or FY*A mutations? P. vivax is currently prevalent in equatorial regions outside of Africa; however it is unknown if P. vivax has ever been endemic to Africa. There is an ongoing debate as to if P. vivax originated in Asia or Africa. Previously, it was thought P. vivax originated in Asia, as Asian and Melanesian P. vivax has the highest genetic diversity [42,89] and the most closely related parasite to P. vivax is P. cynomolgi, a macaque parasite [40,42]. However, recent evidence shows global human-specific P. vivax forms a monophyletic cluster from P. vivax-like parasites infecting African great apes, suggesting an African origin [40]. Human-specific P. vivax sequences form a star-like phylogeny likely due to a relatively recent demographic expansion. Our TMRCA estimates of human-specific P. vivax sequences are 70–250 kya (S12 Table), consistent with previous estimates (50–500 kya, [42,43,89]). As the TMRCA of human-specific P. vivax is estimated to be before or overlapping the TMRCA of FY*O, this is consistent with the hypothesis of P. vivax being the selective agent responsible for the rise of FY*O in Africa. However, there are two possible scenarios that could explain the TMRCA estimates for P. vivax. A first scenario is that the estimated TMRCA of human P. vivax indicates the start of the association between host and parasite, thus marking the start of selective pressure on the host. A second scenario is that these estimates overlap the human out-of-Africa expansion times. It is possible that human-specific P. vivax expanded out of Africa with humans, resulting in the estimated TMRCA for P. vivax. The human P. vivax currently in Africa could be from recent migration [43,89]. Additionally, it is yet unclear if such a high selection coefficient is consistent with the fact that the general severity of P. vivax is currently much lower than that observed for P. falciparum, causing more morbidity than mortality. The combination of these observations lead us to suggest that further work is necessary to better understand the evolutionary history of P. vivax to reconcile the demographic scenarios that could have given rise to such a complex pattern. All together, our results suggest that the evolutionary history of the FY*O mutation, a single SNP under strong selection in human populations, has been a complex one. Multiple haplotypes present in highly divergent African populations are consistent with selection on standing variation, shaping the evolution of this locus that was present in very low frequency in ancestral populations. Although more work needs to be done to understand how P. vivax may have shaped the evolution of this locus, our results provide a framework to evaluate the evolution of the parasite and formulate specific hypotheses for its evolutionary history in association with its human host.
Infectious diseases have undoubtedly played an important role in ancient and modern human history. Yet, there are relatively few regions of the genome involved in resistance to pathogens that show a strong selection signal in current genome-wide searches for this kind of signal. We revisit the evolutionary history of a gene associated with resistance to the most common malaria-causing parasite, Plasmodium vivax, and show that it is one of regions of the human genome that has been under strongest selective pressure in our evolutionary history (selection coefficient: 4. 3%). Our results are consistent with a complex evolutionary history of the locus involving selection on a mutation that was at a very low frequency in the ancestral African population (standing variation) and subsequent differentiation between European, Asian and African populations.
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Population genetic analysis of the DARC locus (Duffy) reveals adaptation from standing variation associated with malaria resistance in humans