Inferring malaria parasite population structure from serological networks

Age-specific patterns of DBLα var diversity can explain why residents of high malaria transmission areas remain susceptible to Plasmodium falciparum blood stage infection throughout life

Immunity to Plasmodium falciparum is non-sterilising, thus individuals residing in malaria-endemic areas are at risk of infection throughout their lifetime. Here we seek to find a genomic epidemiological explanation for why residents of all ages harbour blood stage infections despite lifelong exposure to P. falciparum in areas of high transmission. We do this by exploring, for the first known time, the age-specific patterns of diversity of variant antigen encoding (var) genes in the reservoir of infection. Microscopic and submicroscopic P. falciparum infections were analysed at the end of the wet and dry seasons in 2012-2013 for a cohort of 1541 residents aged from 1 to 91 years in an area characterised by high seasonal malaria transmission in Ghana. By sequencing the near ubiquitous Duffy-binding-like alpha domain (DBLα) that encodes immunogenic domains, we defined var gene diversity in an estimated 1096 genomes detected in sequential wet and dry season sampling of this cohort. Unprecedented var (DBLα) diversity was observed in all ages with 42,399 unique var types detected. There was a high degree of maintenance of types between seasons (>40% seen more than once), with many of the same types, especially upsA, appearing multiple times in isolates from different individuals. Children and adolescents were found to be significant reservoirs of var DBLα diversity compared with adults. Var repertoires within individuals were highly variable, with children having more related var repertoires compared to adolescents and adults. Individuals of all ages harboured multiple genomes with var repertoires unrelated to those infecting other hosts. High turnover of parasites with diverse isolate var repertoires was also observed in all ages. These age-specific patterns are best explained by variant-specific immune selection. The observed level of var diversity for the population was then used to simulate the development of variant-specific immunity to the diverse var types under conservative assumptions. Simulations showed that the extent of observed var diversity with limited repertoire relatedness was sufficient to explain why adolescents and adults in this community remain susceptible to blood stage infection, even with multiple genomes.

Bayesian estimation of community size and overlap from random subsamples

Counting the number of species, items, or genes that are shared between two groups, sets, or communities is a simple calculation when sampling is complete. However, when only partial samples are available, quantifying the overlap between two communities becomes an estimation problem. Furthermore, to calculate normalized measures of β-diversity, such as the Jaccard and Sorenson-Dice indices, one must also estimate the total sizes of the communities being compared. Previous efforts to address these problems have assumed knowledge of total community sizes and then used Bayesian methods to produce unbiased estimates with quantified uncertainty. Here, we address communities of unknown size and show that this produces systematically better estimates—both in terms of central estimates and quantification of uncertainty in those estimates. We further show how to use species, item, or gene count data to refine estimates of community size in a Bayesian joint model of community size and overlap.

Evolutionary analyses of the major variant surface antigen-encoding genes reveal population structure of Plasmodium falciparum within and between continents

Malaria remains a major public health problem in many countries. Unlike influenza and HIV, where diversity in immunodominant surface antigens is understood geographically to inform disease surveillance, relatively little is known about the global population structure of PfEMP1, the major variant surface antigen of the malaria parasite Plasmodium falciparum. The complexity of the var multigene family that encodes PfEMP1 and that diversifies by recombination, has so far precluded its use in malaria surveillance. Recent studies have demonstrated that cost-effective deep sequencing of the region of var genes encoding the PfEMP1 DBLα domain and subsequent classification of within host sequences at 96% identity to define unique DBLα types, can reveal structure and strain dynamics within countries. However, to date there has not been a comprehensive comparison of these DBLα types between countries. By leveraging a bioinformatic approach (jumping hidden Markov model) designed specifically for the analysis of recombination within var genes and applying it to a dataset of DBLα types from 10 countries, we are able to describe population structure of DBLα types at the global scale. The sensitivity of the approach allows for the comparison of the global dataset to ape samples of Plasmodium Laverania species. Our analyses show that the evolution of the parasite population emerging out of Africa underlies current patterns of DBLα type diversity. Most importantly, we can distinguish geographic population structure within Africa between Gabon and Ghana in West Africa and Uganda in East Africa. Our evolutionary findings have translational implications in the context of globalization. Firstly, DBLα type diversity can provide a simple diagnostic framework for geographic surveillance of the rapidly evolving transmission dynamics of P. falciparum. It can also inform efforts to understand the presence or absence of global, regional and local population immunity to major surface antigen variants. Additionally, we identify a number of highly conserved DBLα types that are present globally that may be of biological significance and warrant further characterization.

Bayes-optimal estimation of overlap between populations of fixed size

Measuring the overlap between two populations is, in principle, straightforward. Upon fully sampling both populations, the number of shared objects—species, taxonomical units, or gene variants, depending on the context—can be directly counted. In practice, however, only a fraction of each population’s objects are likely to be sampled due to stochastic data collection or sequencing techniques. Although methods exists for quantifying population overlap under subsampled conditions, their bias is well documented and the uncertainty of their estimates cannot be quantified. Here we derive and validate a method to rigorously estimate the population overlap from incomplete samples when the total number of objects, species, or genes in each population is known, a special case of the more general β-diversity problem that is particularly relevant in the ecology and genomic epidemiology of malaria. By solving a Bayesian inference problem, this method takes into account the rates of subsampling and produces unbiased and Bayes-optimal estimates of overlap. In addition, it provides a natural framework for computing the uncertainty of its estimates, and can be used prospectively in study planning by quantifying the tradeoff between sampling effort and uncertainty.

Understanding when two populations are composed of similar species is important for ecologists, epidemiologists, and population geneticists, and in principle it is easy: just sample the two populations, compare the sets of species identified in each, and count how many appear in both populations. In practice, however, this is difficult because sampling methods typically produce only a random subset of the total population, leaving current population overlap estimates biased. Knowing only the number of shared members between two of these partial population samples, this paper shows how we can nevertheless estimate the true overlap between the full populations, when those full populations’ sizes are known. Using Bayesian statistics, we can also compute credible intervals to produce error bars. We show that using this unbiased approach has a dramatic impact on the conclusions one might draw from previously published studies in the malaria literature, which used simple but biased methods. Because the method in this paper quantifies the tradeoff between sampling effort and uncertainty, we also show how to compute the number of samples required to ensure high-confidence results, which may be useful for planning future studies or budgeting lab reagents and time.

Signatures of competition and strain structure within the major blood-stage antigen of Plasmodium falciparum in a local community in Ghana

The concept of niche partitioning has received considerable theoretical attention at the interface of ecology and evolution of infectious diseases. Strain theory postulates that pathogen populations can be structured into distinct nonoverlapping strains by frequency-dependent selection in response to intraspecific competition for host immune space. The malaria parasite Plasmodium falciparum presents an opportunity to investigate this phenomenon in nature, under conditions of high recombination rate and extensive antigenic diversity. The parasite's major blood-stage antigen, Pf EMP1, is encoded by the hyperdiverse var genes. With a dataset that includes thousands of var DBLα sequence types sampled from asymptomatic cases within an area of high endemicity in Ghana, we address how var diversity is distributed within isolates and compare this to the distribution of microsatellite allelic diversity within isolates to test whether antigenic and neutral regions of the genome are structured differently. With respect to var DBLα sequence types, we find that on average isolates exhibit significantly lower overlap than expected randomly, but that there also exists frequent pairs of isolates that are highly related. Furthermore, the linkage network of var DBLα sequence types reveals a pattern of nonrandom modularity unique to these antigenic genes, and we find that modules of highly linked DBLα types are not explainable by neutral forces related to var recombination constraints, microsatellite diversity, sampling location, host age, or multiplicity of infection. These findings of reduced overlap and modularity among the var antigenic genes are consistent with a role for immune selection as proposed by strain theory. Identifying the evolutionary and ecological dynamics that are responsible for the nonrandom structure in P. falciparum antigenic diversity is important for designing effective intervention in endemic areas.

Population genomics of virulence genes of Plasmodium falciparum in clinical isolates from Uganda

Plasmodium falciparum causes a spectrum of malarial disease from asymptomatic to uncomplicated through to severe. Investigations of parasite virulence have associated the expression of distinct variants of the major surface antigen of the blood stages known as Pf EMP1 encoded by up to 60 var genes per genome. Looking at the population genomics of var genes in cases of uncomplicated malaria, we set out to determine if there was any evidence of a selective sweep of specific var genes or clonal epidemic structure related to the incidence of uncomplicated disease in children. By sequencing the conserved DBLα domain of var genes from six sentinel sites in Uganda we found that the parasites causing uncomplicated P. falciparum disease in children were highly diverse and that every child had a unique var DBLα repertoire. Despite extensive var DBLα diversity and minimal overlap between repertoires, specific DBLα types and groups were conserved at the population level across Uganda. This pattern was the same regardless of the geographic distance or malaria transmission intensity. These data lead us to propose that any parasite can cause uncomplicated malarial disease and that these diverse parasite repertoires are composed of both upsA and non-upsA var gene groups.

Evidence of strain structure in Plasmodium falciparum var gene repertoires in children from Gabon, West Africa

Existing theory on competition for hosts between pathogen strains has proposed that immune selection can lead to the maintenance of strain structure consisting of discrete, weakly overlapping antigenic repertoires. This prediction of strain theory has conceptual overlap with fundamental ideas in ecology on niche partitioning and limiting similarity between coexisting species in an ecosystem, which oppose the hypothesis of neutral coexistence. For Plasmodium falciparum, strain theory has been specifically proposed in relation to the major surface antigen of the blood stage, known as PfEMP1 and encoded by the multicopy multigene family known as the var genes. Deep sampling of the DBLα domain of var genes in the local population of Bakoumba, West Africa, was completed to define whether patterns of repertoire overlap support a role of immune selection under the opposing force of high outcrossing, a characteristic of areas of intense malaria transmission. Using a 454 high-throughput sequencing protocol, we report extremely high diversity of the DBLα domain and a large parasite population with DBLα repertoires structured into nonrandom patterns of overlap. Such population structure, significant for the high diversity of var genes that compose it at a local level, supports the existence of "strains" characterized by distinct var gene repertoires. Nonneutral, frequency-dependent competition would be at play and could underlie these patterns. With a computational experiment that simulates an intervention similar to mass drug administration, we argue that the observed repertoire structure matters for the antigenic var diversity of the parasite population remaining after intervention.

Pathogen evolution and the immunological niche

Host immunity is a major driver of pathogen evolution and thus a major determinant of pathogen diversity. Explanations for pathogen diversity traditionally assume simple interactions between pathogens and the immune system, a view encapsulated by the susceptible-infected-recovered (SIR) model. However, there is growing evidence that the complexity of many host-pathogen interactions is dynamically important. This revised perspective requires broadening the definition of a pathogen's immunological phenotype, or what can be thought of as its immunological niche. After reviewing evidence that interactions between pathogens and host immunity drive much of pathogen evolution, I introduce the concept of a pathogen's immunological phenotype. Models that depart from the SIR paradigm demonstrate the utility of this perspective and show that it is particularly useful in understanding vaccine-induced evolution. This paper highlights questions in immunology, evolution, and ecology that must be answered to advance theories of pathogen diversity.

Modeling malaria infection and immunity against variant surface antigens in Príncipe Island, West Africa

After remarkable success of vector control campaigns worldwide, concerns about loss of immunity against Plasmodium falciparum due to lack of exposure to the parasite are relevant since an increase of severe cases in less immune individuals is expected. We present a mathematical model to investigate the impact of reducing exposure to the parasite on the immune repertoire against P. falciparum erythrocyte membrane protein 1 (PfEMP1) variants. The model was parameterized with data from Príncipe Island, West Africa, and applied to simulate two alternative transmission scenarios: one where control measures are continued to eventually drive the system to elimination; and another where the effort is interrupted after 6 years of its initiation and the system returns to the initial transmission potential. Population dynamics of parasite prevalence predict that in a few years infection levels return to the pre-control values, while the re-acquisition of the immune repertoire against PfEMP1 is slower, creating a window for increased severity. The model illustrates the consequences of loss of immune repertoire against PfEMP1 in a given setting and can be applied to other regions where similar data may be available.

Genetic structure of Plasmodium falciparum populations across the Honduras-Nicaragua border

Background

The Caribbean coast of Central America remains an area of malaria transmission caused by Plasmodium falciparum despite the fact that morbidity has been reduced in recent years. Parasite populations in that region show interesting characteristics such as chloroquine susceptibility and low mortality rates. Genetic structure and diversity of P. falciparum populations in the Honduras-Nicaragua border were analysed in this study.

Methods

Seven neutral microsatellite loci were analysed in 110 P. falciparum isolates from endemic areas of Honduras (n = 77) and Nicaragua (n = 33), mostly from the border region called the Moskitia. Several analyses concerning the genetic diversity, linkage disequilibrium, population structure, molecular variance, and haplotype clustering were conducted.

Results

There was a low level of genetic diversity in P. falciparum populations from Honduras and Nicaragua. Expected heterozigosity (H_e) results were similarly low for both populations. A moderate differentiation was revealed by the F_ST index between both populations, and two putative clusters were defined through a structure analysis. The main cluster grouped most of samples from Honduras and Nicaragua, while the second cluster was smaller and included all the samples from the Siuna community in Nicaragua. This result could partially explain the stronger linkage disequilibrium (LD) in the parasite population from that country. These findings are congruent with the decreasing rates of malaria endemicity in Central America.

The antigenic switching network of Plasmodium falciparum and its implications for the immuno-epidemiology of malaria

Antigenic variation in the human malaria parasite Plasmodium falciparum involves sequential and mutually exclusive expression of members of the var multi-gene family and appears to follow a non-random pattern. In this study, using a detailed in vitro gene transcription analysis of the culture-adapted HB3 strain of P. falciparum, we show that antigenic switching is governed by a global activation hierarchy favouring short and highly diverse genes in central chromosomal location. Longer and more conserved genes, which have previously been associated with severe infection in immunologically naive hosts, are rarely activated, however, implying an in vivo fitness advantage possibly through adhesion-dependent survival rates. We further show that a gene’s activation rate is positively associated sequence diversity, which could offer important new insights into the evolution and maintenance of antigenic diversity in P. falciparum malaria.

DOI:http://dx.doi.org/10.7554/eLife.01074.001

Our ability to acquire immunity to a disease depends on our immune system learning to recognise foreign molecules—called antigens—that are specific to the disease-causing virus, bacterium or parasite. However, some pathogens, such as the malaria-causing parasite Plasmodium falciparum, get around this defence through a process called antigenic variation. This involves the parasite switching between different antigens over the course of an infection, preventing the host immune system from learning to recognise them and leading to infections that last many weeks or even months.

The main antigen in P. falciparum is a protein called PfEMP1, which is encoded by a family of genes called var (‘variable’). Var genes have evolved to be highly diverse, and different parasites have different repertoires of around 50–60 var genes. This ensures that there are a huge number of distinct variants of the PfEMP1 antigen available within the population, allowing the malaria parasite to maintain long-lasting infections and also to infect the same individuals again and again.

Previous work has shown that the expression of var genes is not random, but it is not clear what determines which genes are expressed at any given time. Now, Noble et al. have performed a detailed investigation of antigenic switching in P. falciparum. Using clonal parasites, they closely monitored the expression of the entire var gene repertoire during many generations of parasite culture. They observed that although different cultures initially expressed distinct var genes, most of them ended up expressing two particular genes—var27 and var29—at high levels, indicating a hard-wired gene ‘activation hierarchy’.

Noble et al. found that whenever the parasites switched antigens, var genes that were centrally located on chromosomes—such as var27 and var29—were more likely to be activated than those at the ends of chromosomes. Moreover, var genes that were highly diverse were more likely to be activated than more conserved genes: this is the first evidence linking var gene evolution with gene activation probabilities. Together, these factors gave rise to the proposed activation hierarchy, which favours genes optimised for immune evasion and aids their continued evolution and diversification. Further work is now needed to identify the molecular mechanisms that control antigenic switching and to determine whether these could represent new therapeutic targets for malaria.

DOI:http://dx.doi.org/10.7554/eLife.01074.002

Population structuring of multi-copy, antigen-encoding genes in Plasmodium falciparum

The coexistence of multiple independently circulating strains in pathogen populations that undergo sexual recombination is a central question of epidemiology with profound implications for control. An agent-based model is developed that extends earlier ‘strain theory’ by addressing the var gene family of Plasmodium falciparum. The model explicitly considers the extensive diversity of multi-copy genes that undergo antigenic variation via sequential, mutually exclusive expression. It tracks the dynamics of all unique var repertoires in a population of hosts, and shows that even under high levels of sexual recombination, strain competition mediated through cross-immunity structures the parasite population into a subset of coexisting dominant repertoires of var genes whose degree of antigenic overlap depends on transmission intensity. Empirical comparison of patterns of genetic variation at antigenic and neutral sites supports this role for immune selection in structuring parasite diversity.

DOI:http://dx.doi.org/10.7554/eLife.00093.001

Malaria is an infectious disease that is estimated to kill more than half a million people every year, mostly young children in Africa. It is spread by mosquitos that are infected with Plasmodium parasites that attack red blood cells in the human body. Plasmodium falciparum, the species that is responsible for most of these deaths, causes malaria by entering red blood cells and releasing antigens that travel to the surface of the cells, where they change the adhesion properties. This causes the infected red blood cells to accumulate in small blood vessels, surface capillaries or the brain, which can have severe consequences for the person infected.

P. falciparum is particularly dangerous because of its ability to vary the antigens displayed on the cell surface: this process, known as antigenic variation, helps to maintain infections for extended periods of time by allowing the antigens to stay one step ahead of the immune system (a process known as immune escape). The origins of antigenic variation lie in the fact that each P. falciparum genome has a repertoire of between 50 and 60 var genes that code for the variability of a major antigen that is responsible for immune escape in malaria. Molecular sequencing has shown that local parasite populations contain thousands of different types of var genes: hence, meiotic recombination in the mosquito can create a vast number of combinations of var repertoires.

Artzy-Randrup et al. have developed a computational model of this highly diverse and complex system to address the following question: is a local pathogen population composed of largely random and ephemeral repertoires of these genes, or is it structured into independently circulating strains? Their model goes beyond previous models by including interactions within the local host population that arise as a result of indirect competition between different strains of the pathogen for available hosts: this competition is influenced by the history of infection and, therefore, by the patterns of immunity within the host population. Previous models included within-host processes but not these higher, local population-level interactions.

The model simulates the dynamics of all the unique combinations of var genes in a population of hosts, and shows that even with high rates of reproduction, the parasite population self-organizes into a limited number of coexisting strains: the distinct var repertoires of these strains only weakly overlap, suggesting that the immune response of the host population has been partitioned into distinct niches. By investigating genetic variation at both antigenic sites and regions of the genome that do not code for antigens, Artzy-Randrup et al. suggest that immune selection—the selection imposed on var repertoires by the build up of specific immunity at the population level—plays a central role in structuring parasite diversity.

The new model should lead to a better understanding of the epidemiology of Plasmodium and other pathogens that work in similar ways, including Trypanosoma brucei (sleeping sickness), Borellia burgdorferi (Lyme disease) and Giardia lamblia (gastroenteritis), and help with global efforts to eliminate malaria and other diseases.

DOI:http://dx.doi.org/10.7554/eLife.00093.002

A modeller's perspective on infection dynamics within and between hosts

The goal of this case-series was to increase our understanding of some complex within and between-host infection dynamics through the creation of mathematical and computational models that are able to capture the existing host and/or parasite heterogeneity. This goal was reached through a series of research projects (regarding experimental autoimmune encephalomyelitis (EAE) in mice, Mycobacterium avium subspecies paratuberculosis infection in cattle, Eimeria acervulina infection in chicken and human malaria) that gradually build up in complexity of both the system modelled and the modelling techniques used. In this case-series, the vast majority of model components have a direct link with reality. The results have shown some detailed examples of the valuable contribution that models have in understanding infection processes. The most satisfying achievements have come from those models that were able to, in hindsight, make complicated experimental results seem obvious and logical, and where the process of building the model was as insightful as the final results. The models created in these projects help to explain a wide range of sometimes contradictory experimental results and are used to predict the effect of control measures. In addition, they generate ideas for the development of new methods of control.

Niche and neutral effects of acquired immunity permit coexistence of pneumococcal serotypes

Over 90 capsular serotypes of Streptococcus pneumoniae, a common nasopharyngeal colonizer and major cause of pneumonia, bacteremia, and meningitis, are known. It is unclear why some serotypes can persist at all: They are more easily cleared from carriage and compete poorly in vivo. Serotype-specific immune responses, which could promote diversity in principle, are weak enough to allow repeated colonizations by the same type. We show that weak serotype-specific immunity and an acquired response not specific to the capsule can together reproduce observed diversity. Serotype-specific immunity stabilizes competition, and acquired immunity to noncapsular antigens reduces fitness differences. Our model can be used to explain the effects of pneumococcal vaccination and indicates general factors that regulate the diversity of pathogens.

How selection forces dictate the variant surface antigens used by malaria parasites

Red blood cells infected by the malaria parasite Plasmodium falciparum express variant surface antigens (VSAs) that evade host immunity and allow the parasites to persist in the human population. There exist many different VSAs and the differential expression of these VSAs is associated with the virulence (damage to the host) of the parasites. The aim of this study is to unravel the differences in the effect key selection forces have on parasites expressing different VSAs such that we can better understand how VSAs enable the parasites to adapt to changes in their environment (like control measures) and how this may impact the virulence of the circulating parasites. To this end, we have built an individual-based model that captures the main selective forces on malaria parasites, namely parasite competition, host immunity, host death and mosquito abundance at both the within- and between-host levels. VSAs are defined by the net growth rates they infer to the parasites and the model keeps track of the expression of, and antibody build-up against, each VSA in all hosts. Our results show an ordered acquisition of VSA-specific antibodies with host age, which causes a dichotomy between the more virulent VSAs that reach high parasitaemias but are restricted to young relatively non-immune hosts, and less virulent VSAs that do not reach such high parasitaemias but can infect a wider range of hosts. The outcome of a change in the parasite's environment in terms of parasite virulence depends on the exact balance between the selection forces, which sets the limiting factor for parasite survival. Parasites will evolve towards expressing more virulent VSAs when the limiting factor for parasite survival is the within-host parasite growth and the parasites are able to minimize this limitation by expressing more virulent VSAs.

The selection landscape of malaria parasites

Malaria parasites have to survive and transmit within a highly selective and ever-changing host environment. Because immunity to malaria is nonsterilizing and builds up slowly through repeated infections, commonly the parasite invades a host that is immunologically and physiologically different from its previous host. During the course of infection, the parasite must also keep pace with changes in host immune responses and red-blood-cell physiology. Here, we describe the "selection landscape" of the most virulent of the human malaria parasites, Plasmodium falciparum, and the adaptive mechanisms it uses to navigate through that landscape. Taking a cost-benefit view of parasite fitness, we consider the evolutionary outcomes of the most important forces of selection operating on the parasite, namely immunity, host death, drugs, mosquito availability, and coinfection. Given the huge potential for malaria parasite evolution in the context of the recently renewed effort to eradicate malaria, a deeper understanding of P. falciparum adaptation is essential.

Detecting signatures of balancing selection to identify targets of anti-parasite immunity

Parasite antigen genes might evolve under frequency-dependent immune selection. The distinctive patterns of polymorphism that result can be detected using population genetic methods that test for signatures of balancing selection, allowing genes encoding important targets of immunity to be identified. Analyses can be complicated by population structures, histories and features of a parasite's genome. However, new sequencing technologies facilitate scans of polymorphism throughout parasite genomes to identify the most exceptional gene specific signatures. We focus on malaria parasites to illustrate challenges and opportunities for detecting targets of frequency-dependent immune selection to discover new potential vaccine candidates.

Immune selection and within-host competition can structure the repertoire of variant surface antigens in Plasmodium falciparum--a mathematical model

Background

The evolutionary mechanisms structuring the expression pattern of variant surface antigen (VSA) families that allow pathogens to evade immune responses and establish chronic and repeated infections pose major challenges to theoretical research. In Plasmodium falciparum, the best-studied VSA family is erythrocyte membrane protein 1 (PfEMP1). Each parasite genome encodes about 60 PfEMP1 variants, which are important virulence factors and major targets of host antibody responses. Transcriptional switching is the basis of clonal PfEMP1 variation and immune evasion. A relatively conserved subset of PfEMP1 variants tends to dominate in non-immune patients and in patients with severe malaria, while more diverse subsets relate to uncomplicated infection and higher levels of pre-existing protective immunity.

Methodology/Principal Findings

Here, we use the available molecular and serological evidence regarding VSAs, in particular PfEMP1, to formulate a mathematical model of the evolutionary mechanisms shaping VSA organization and expression patterns. The model integrates the transmission dynamics between hosts and the competitive interactions within hosts, based on the hypothesis that the VSAs can be organized into so-called dominance blocks, which characterize their competitive potential. The model reproduces immunological trends observed in field data, and predicts an evolutionary stable balance between inter-clonally conserved dominance blocks that are highly competitive within-host and diverse blocks that are favoured by immune selection at the population level.

Conclusions/Significance

The application of a monotonic dominance profile to VSAs encoded by a gene family generates two opposing selective forces and, consequently, two distinct clusters of genes emerge in adaptation to naïve and partially immune hosts, respectively.