MHC allele frequency distributions under parasite-driven selection: A simulation model

<p>Abstract</p> <p>Background</p> <p>The extreme polymorphism that is observed in major histocompatibility complex (MHC) genes, which code for proteins involved in recognition of non-self oligopeptides, is thought to result from a pressure exerted by parasites because parasite antigens are more likely to be recognized by MHC heterozygotes (heterozygote advantage) and/or by rare MHC alleles (negative frequency-dependent selection). The Ewens-Watterson test (EW) is often used to detect selection acting on MHC genes over the recent history of a population. EW is based on the expectation that allele frequencies under balancing selection should be more even than under neutrality. We used computer simulations to investigate whether this expectation holds for selection exerted by parasites on host MHC genes under conditions of heterozygote advantage and negative frequency-dependent selection acting either simultaneously or separately.</p> <p>Results</p> <p>In agreement with simple models of symmetrical overdominance, we found that heterozygote advantage acting alone in populations does, indeed, result in more even allele frequency distributions than expected under neutrality, and this is easily detectable by EW. However, under negative frequency-dependent selection, or under the joint action of negative frequency-dependent selection and heterozygote advantage, distributions of allele frequencies were less predictable: the majority of distributions were indistinguishable from neutral expectations, while the remaining runs resulted in either more even or more skewed distributions than under neutrality.</p> <p>Conclusions</p> <p>Our results indicate that, as long as negative frequency-dependent selection is an important force maintaining MHC variation, the EW test has limited utility in detecting selection acting on these genes.</p

Food resource uncertainty shapes the fitness consequences of early spring onset in capital and income breeding migratory birds

Due to climate change, the timing of spring arrival and nesting onset in many migratory bird species have advanced. Earlier spring onsets prolong the available breeding period but can also deteriorate local conditions, leading to increased temporal variation in resource availability. This interaction between phenological shifts in nesting onset and short-term temporal variation in food gain has unknown consequences for fitness of migratory bird species. We model two contrasting breeding strategies to investigate the fitness consequences of stochastically fluctuating food gain and storing of energetic reserves for reproduction. The model was inspired by the biology of common eiders (Somateria mollissima), which store extensive reserves prior to egg laying and incubation (capital breeding strategy), and king eiders (S. spectabilis), which continue to forage during nesting (income breeding strategy). For capital breeders, foraging prior to breeding increases energy reserves and clutch size, but for both strategies, postponing nesting reduces the chances of recruitment. We found that in scenarios with early spring onset, the average number of recruits produced by capital breeders was higher under conditions of stochastic rather than deterministic food gain. This is because under highly variable daily food gain, individuals successful in obtaining food can produce large clutches early in the season. However, income breeders do not build up reserve buffers; consequently, their fitness is always reduced, when food availability fluctuates. For both modeled strategies, resource uncertainty had only a minor effect on the timing of nesting onset. Our work shows that the fitness consequences of global changes in breeding season onset depend on the level of uncertainty in food intake and the degree to which reserves are used to fuel the reproductive effort. We predict that among migratory bird species producing one clutch per year, capital breeders are more resilient to climate-induced changes in spring phenology than income breeders.publishedVersio

Probing of mortality rate by staying alive: The growth-reproduction trade-off in a spatially heterogeneous environment

1. In many annual plants, mollusks, crustaceans and ectothermic vertebrates, growth accompanies reproduction. The growth curves of these organisms often exhibit a complex shape, with episodic cessations or accelerations of growth occurring long after maturation. The mixed allocation to growth and reproduction has poorly understood adaptive consequences, and the life‐history theory does not explain if complex growth in short‐lived organisms can be adaptive. 2. We model the trade‐off between growth and reproduction in a short‐lived organism evolving in a metapopulation. Individuals occupy risky or safe sites throughout their lives, but are uncertain regarding the risk of death. Modelled organisms are allowed to grow and produce offspring at specified time points (moults), although we also consider scenarios that approximate continuous growth and reproduction. 3. Certain combinations of risky to safe sites select for strategies with mixed allocation to growth and reproduction that bet‐hedge offspring production in safe and risky sites. Our model shows that spatially heterogeneous environments select for mixed allocation only if safe sites do not become the prevailing source of recruits, for example, when risky sites are frequent. In certain conditions, growth curves are multi‐phasic, with allocation to growth that stops, remains constant or accelerates during adult life. The resulting complex growth curves are more likely to evolve in short‐lived organisms that moult several times per adult life. 4. Our work shows that spatial heterogeneity can select for growth that accompanies reproduction and provides insights into the adaptive significance of complex growth curves. Short‐lived crustaceans are particularly predisposed to exhibit complex growth patterns as an adaptive response to spatially heterogeneous environments. Our results suggest that standard statistical growth models assuming adult growth rate to only decelerate over life are not well suited to approximate growth curves of short‐lived crustaceans

Data files (Matlab worksapces) packed in a ZIP archive - scenarios with pathogens, mutation rate 5*10^-3

Scenarios in which pathogens interact with hosts Data set is packed in a ZIP archive. Names of catalogue in the archive indicate scenario parameters: host population size N and simulated mechanism of partner choice (RM - random mating, h0 - soft assortative mating, h1 - hard assortative mating; see Materials and Methods for details). Each scenario catalogue contains 100 files (Matlab workspaces) with saved variables of each of 100 independent replications. Saved variables: HED_scen – partner choice scenario (random mating HED_scen=NaN, soft assortative mating h0 HED_scen=0, hard assortative mating h1 HED_scen=1) N – host population size off_val_occ – offspring reproductive value at birth in subsequent mating attempts h_mut_rat – host mutation rate bits_num – number of bits in MHC molecule match – number of matching bits necessary for antigen presentation num_pat_spec – number of pathogen species p_mut_rat – pathogen mutation rate pat_gen – number of pathogen generations per one host generation pept_num – number of antigens produced by a pathogen host_n_all – allelic richness across generations host_time – host generation number mat_occ_distr – number of mating pairs in subsequent mating attempts (first row indicate first mating attempt) saved every host generation Compl_all_hist – frequency distribution of MHC alleles saved in last 1400 host generations (host generations 1600-3000). Matrix of allele frequency distribution is saved as Matlab sparse matrix, (type full(Compl_all_hist) to transform Compl_all_hist into trajectories of allele frequency) in_pres_al – decimal labels of MHC alleles in allele frequency history matrix Compl_all_hist mean_pres_pat – mean proportion of presented pathogens SD_pres_pat – standard deviation for the proportion of presented pathogen

Population size and MHC polymorphism.

<p>Impact of population size on the maintenance of MHC polymorphism (upper panels) and heterozygosity (lower panels) under three simulated scenarios–heterozygote advantage (HA), Red Queen (RQ) dynamics, and both (HA+RQ) (see legend)–with three pathogen mutation rates (given above the panels). Data points indicate the mean number of MHC alleles (A-C) and mean heterozygosity (D-F) and are calculated across the last 6000 generations of 10 replicate simulations. Error bars indicate bootstrapped 95% confidence intervals.</p

Presentation ability and probability of recruitment of a new mutant MHC allele.

<p>(A-C) Data points indicate the probability that a mutant allele will stay in the population for at least 10 host generations (cut-off points longer or shorter than 10 generations (e.g., 2 or 20) showed similar patterns). (D-F) Data points indicate the relative pathogen-recognition ability of a mutant MHC allele relative to the immunocompetence of resident alleles. The average immunocompetence of resident alleles was measured as the number of pathogens recognized in a given generation, weighted by the frequency of each resident allele. Note that a presentation spectrum equal to 1 indicates the threshold at which a mutant allele is able to present, on average, the same proportion of pathogens as resident alleles are. (A-F) Characteristics were calculated across the last 6000 generations of 10 replicates. Scenario labels: HA–heterozygote advantage, RQ–Red Queen, HA+RQ–both. Pathogen mutation rates are given above the panels.</p

Data from: Sexual selection and the evolution of the Major Histocompatibility Complex

The genes of the major histocompatibility complex (MHC) are a key component of the adaptive immune system and among the most variable loci in the vertebrate genome. Pathogen-mediated natural selection and MHC-based disassortative mating are both thought to structure MHC polymorphism, but their effects have proven difficult to discriminate in natural systems. Using the first model of MHC dynamics incorporating both survival and reproduction, we demonstrate that natural and sexual selection produce distinctive signatures of MHC allelic diversity with critical implications for understanding host–pathogen dynamics. While natural selection produces the Red Queen dynamics characteristic of host–parasite interactions, disassortative mating stabilizes allele frequencies, damping major fluctuations in dominant alleles and protecting functional variants against drift. This subtle difference generates a complex interaction between MHC allelic diversity and population size. In small populations, the stabilizing effects of sexual selection moderate the effects of drift, whereas pathogen-mediated selection accelerates the loss of functionally important genetic diversity. Natural selection enhances MHC allelic variation in larger populations, with the highest levels of diversity generated by the combined action of pathogen-mediated selection and disassortative mating. MHC-based sexual selection may help to explain how functionally important genetic variation can be maintained in populations of conservation concern