Kin selection and ethnic group selection

Ethnicity looks something like kinship on a larger scale. The same math can be used to measure genetic similarity within ethnic/racial groups and relatedness within families. For example, members of the same continental race are about as related (r = 0.18–0.26) as half-siblings (r = 0.25). However (contrary to some claims) the theory of kin selection does not apply straightforwardly to ethnicity, because inclusive fitness calculations based on Hamilton's rule break down when there are complicated social interactions within groups, and/or groups are large and long-lasting. A more promising approach is a theory of ethnic group selection, a special case of cultural group selection. An elementary model shows that the genetic assimilation of a socially enforced cultural regime can promote group solidarity and lead to the regulation of recruitment to groups, and to altruism between groups, based on genetic similarity – in short, to ethnic nepotism. Several lines of evidence, from historical population genetics and political psychology, are relevant here.     

Multilevel selection: the evolution of cooperation in non-kin groups

Hamiltons (1964a, 1964b) landmark papers are rightly recognized as the formal basis for our understanding of the evolution of altruistic traits. However, Hamiltons equation as he originally expressed it is simplistic. A genetically oriented approach to studying multilevel selection can provide insights into how the terminology and assumptions used by Hamilton can be generalized. Using contextual analysis I demonstrated that Hamiltons rule actually embodies three distinct processes, group selection, individual selection, and transmission genetics or heritability. Whether an altruistic trait will evolve depends the balance of all of these factors. The genetical approach, and particularly, contextual analysis provides a means of separating these factors and examining them one at a time. Perhaps the greatest issue with Hamiltons equation is the interpretation of r. Hamilton (1964a) interpreted this as relatedness. In this paper I show that what Hamilton called relatedness is more generally interpreted as the proportion for variance among groups, and that many processes in addition to relatedness can increase the variance among groups. I also show that the evolution of an altruistic trait is driven by the ratio of the heritability at the group level to the heritability at the individual level. Under some circumstances this ratio can be greater than 1. In this situation altruism can evolve even if selection favoring selfish behavior is stronger than selection favoring altruism.     

Kin selection may inhibit the evolution of reciprocation

Kin selection and reciprocal cooperation provide two candidate explanations for the evolution of cooperation. Models of the evolution of cooperation have typically focussed on one or the other mechanism, despite claims that kin selection could pave the way for the evolution of reciprocal cooperation. We describe a computer simulation model that explicitly supports both kin selection and reciprocal cooperation. The model simulates a viscous population of discrete individuals with social interaction taking the form of the Prisoner's Dilemma and selection acting on performance in these interactions. We recount how the analytical and empirical study of this model led to the conclusion that kin selection may actually inhibit the evolution of effective strategies for establishing reciprocal cooperation.     

Kin selection and coefficients of relatedness in family-structured populations with inbreeding

We consider family specific fitnesses that depend on mixed strategies of two basic phenotypes or behaviours. Pairwise interactions are assumed, but they are restricted to occur between sibs. To study the change in frequency of a rare mutant allele, we consider two different forms of weak selection, one applied through small differences in genotypic values determining individual mixed strategies, the other through small differences in viabilities according to the behaviours chosen by interacting sibs. Under these two specific forms of weak selection, we deduce conditions for initial increase in frequency of a rare mutant allele for autosomal genes in the partial selfing model as well as autosomal and sex-linked genes in the partial sib-mating model with selection before mating or selection after mating. With small differences in mixed strategies, we show that conditions for protection of a mutant allele are tantamount to conditions for initial increase in frequency obtained in additive kin selection models. With particular reference to altruism versus selfishness, we provide explicit ranges of values for the selfing or sib-mating rate based on a fixed cost-benefit ratio and the dominance scheme that allow the spreading of a rare mutant allele into the population. This study confirms that more inbreeding does not necessarily promote the evolution of altruism. Under the hypothesis of small differences in viabilities, the situation is much more intricate unless an additive model is assumed. In general however, conditions for initial increase in frequency of a mutant allele can be obtained in terms of fitness effects that depend on the genotypes of interacting individuals or their mates and generalized conditional coefficients of relatedness according to the inbreeding condition of the interacting individuals.     

On the effect of population heterogeneity on dynamics of epidemic diseases

The paper investigates a class of SIS models of the evolution of an infectious disease in a heterogeneous population. The heterogeneity reflects individual differences in the susceptibility or in the contact rates and leads to a distributed parameter system, requiring therefore, distributed initial data, which are often not available. It is shown that there exists a corresponding homogeneous (ODE) population model that gives the same aggregated results as the distributed one, at least in the expansion phase of the disease. However, this ODE model involves a nonlinear “prevalence-to-incidence” function which is not constructively defined. Based on several established properties of this function, a simple class of approximating function is proposed, depending on three free parameters that could be estimated from scarce data.How the behaviour of a population depends on the level of heterogeneity (all other parameters kept equal) – this is the second issue studied in the paper. It turns out that both for the short run and for the long run behaviour there exist threshold values, such that more heterogeneity is advantageous for the population if and only if the initial (weighted) prevalence is above the threshold.This research was partly supported by the Austrian Science Foundation under contract N0. 15618-OEK.     

Multilocus models in the infinite island model of population structure

Different methods have been developed to consider the effects of statistical associations among genes that arise in population genetics models: kin selection models deal with associations among genes present in different interacting individuals, while multilocus models deal with associations among genes at different loci. It was pointed out recently that these two types of models are very similar in essence. In this paper, we present a method to construct multilocus models in the infinite island model of population structure (where deme size may be arbitrarily small). This method allows one to compute recursions on allele frequencies, and different types of genetic associations (including associations between different individuals from the same deme), and incorporates selection. Recursions can be simplified using quasi-equilibrium approximations; however, we show that quasi-equilibrium calculations for associations that are different from zero under neutrality must include a term that has not been previously considered. The method is illustrated using simple examples.     

Kin selection and evolution of infectious disease resistance

Discoveries of mutations conferring resistance to infectious diseases have led to increased interest in the evolutionary dynamics of disease resistance. Several recent papers have estimated the historical strength of selection for mutations conferring disease resistance. These studies are based on simple population genetic models that do not take account of factors such as spatial and family structure. Such factors may have a substantial impact on the strength of natural selection through inclusive fitness effects. That is, people have a strong tendency to live with relatives and therefore have a high probability of transmitting infectious diseases to them. Thus, an allele that protects an individual against disease infection also protects that individual's family members. Because some of these family members are likely to also be carrying the allele, selection for that allele is magnified by family structure. In this paper, I use mathematical modeling techniques to explore the impact of such kin selection on the strength of selection for infectious disease resistance alleles. I show that if the resistance allele has the same proportional effect on both within- and between-family transmission, then the impact of kin selection is relatively minor. Selection coefficients are increased by 5-35%, with a greater benefit for weaker alleles. The reason is that an individual with a strong resistance allele does not need much protection from infection by family members and thus does not benefit much from their alleles. The effect of kin selection can be dramatic, however, if the resistance allele has a larger effect on between-family transmission than within-family transmission (which can occur if between-family infection rates are much smaller than within-family rates), increasing selection coefficients by as much as two- to threefold. These results show conditions when it is important to consider family structure in estimates of the strength of selection for infectious disease resistance alleles.     

AdmixKJump: identifying population structure in recently diverged groups

Motivation

Correctly modeling population structure is important for understanding recent evolution and for association studies in humans. While pre-existing knowledge of population history can be used to specify expected levels of subdivision, objective metrics to detect population structure are important and may even be preferable for identifying groups in some situations. One such metric for genomic scale data is implemented in the cross-validation procedure of the program ADMIXTURE, but it has not been evaluated on recently diverged and potentially cryptic levels of population structure. Here, I develop a new method, AdmixKJump, and test both metrics under this scenario.

Findings

I show that AdmixKJump is more sensitive to recent population divisions compared to the cross-validation metric using both realistic simulations, as well as 1000 Genomes Project European genomic data. With two populations of 50 individuals each, AdmixKJump is able to detect two populations with 100% accuracy that split at least 10KYA, whereas cross-validation obtains this 100% level at 14KYA. I also show that AdmixKJump is more accurate with fewer samples per population. Furthermore, in contrast to the cross-validation approach, AdmixKJump is able to detect the population split between the Finnish and Tuscan populations of the 1000 Genomes Project.

Conclusion

AdmixKJump has more power to detect the number of populations in a cohort of samples with smaller sample sizes and shorter divergence times.

Availability

A java implementation can be found at https://sites.google.com/site/igsevolgenomicslab/home/downloads     

Why kin and group selection models may not be enough to explain human other-regarding behaviour

Models of kin or group selection usually feature only one possible fitness transfer. The phenotypes are either to make this transfer or not to make it and for any given fitness transfer, Hamilton's rule predicts which of the two phenotypes will spread. In this article we allow for the possibility that different individuals or different generations face similar, but not necessarily identical possibilities for fitness transfers. In this setting, phenotypes are preference relations, which concisely specify behaviour for a range of possible fitness transfers (rather than being a specification for only one particular situation an animal or human can be in). For this more general set-up, we find that only preference relations that are linear in fitnesses can be explained using models of kin selection and that the same applies to a large class of group selection models. This provides a new implication of hierarchical selection models that could in principle falsify them, even if relatedness--or a parameter for assortativeness--is unknown. The empirical evidence for humans suggests that hierarchical selection models alone are not enough to explain their other-regarding or altruistic behaviour.     

Kin selection may contribute to lek evolution and trait introgression across an avian hybrid zone

Understanding the mechanism(s) that favour cooperation among individuals competing for the same resources provides direct insights into the evolution of grouping behaviour. In a hybrid zone between golden-/yellow-collared (Manacus vitellinus) and white-collared (Manacus candei) manakins, males form aggregations composed of white and yellow males solely to attract females ('mixed leks'). Previous work shows that yellow males in these mixed leks experience a clear mating advantage over white males, resulting in the preferential introgression of yellow plumage allele(s) into the white species. However, the yellow male mating advantage only occurs in mixed leks with high frequencies of yellow males, and only a few of these males probably mate. Hence, it remains unclear why unsuccessful males join leks. Here, we used microsatellite markers to estimate pairwise relatedness among males within and between leks to test whether indirect genetic benefits of helping kin ('kin selection') can promote grouping. We found that yellow males are significantly more related to each other within than between leks, while relatedness among white males did not differ within and between leks. This suggests that yellow males may indirectly enhance their own reproductive success by preferentially lekking with relatives because yellow plumage is under positive frequency-dependent selection (positive FDS). Our results are consistent with the hypothesis that kin selection may promote grouping and facilitate positive FDS for yellow males, mediating the movement of yellow plumage across this hybrid zone.     

Diffusion approximations for one-locus multi-allele kin selection,mutation and random drift in group-structured populations: a unifying approach to selection models in population genetics

Diffusion approximations are ascertained from a two-time-scale argument in the case of a group-structured diploid population with scaled viability parameters depending on the individual genotype and the group type at a single multi-allelic locus under recurrent mutation, and applied to the case of random pairwise interactions within groups. The main step consists in proving global and uniform convergence of the distribution of the group types in an infinite population in the absence of selection and mutation, using a coalescent approach. An inclusive fitness formulation with coefficient of relatedness between a focal individual J affecting the reproductive success of an individual I, defined as the expected fraction of genes in I that are identical by descent to one or more genes in J in a neutral infinite population, given that J is allozygous or autozygous, yields the correct selection drift functions. These are analogous to the selection drift functions obtained with pure viability selection in a population with inbreeding. They give the changes of the allele frequencies in an infinite population without mutation that correspond to the replicator equation with fitness matrix expressed as a linear combination of a symmetric matrix for allozygous individuals and a rank-one matrix for autozygous individuals. In the case of no inbreeding, the mean inclusive fitness is a strict Lyapunov function with respect to this deterministic dynamics. Connections are made between dispersal with exact replacement (proportional dispersal), uniform dispersal, and local extinction and recolonization. The timing of dispersal (before or after selection, before or after mating) is shown to have an effect on group competition and the effective population size. In memory of Sam Karlin.     

Background selection and population differentiation

A general analytical formula is derived, which predicts the effects of background selection on population differentiation at a neutral locus as a result of its linkage with selected loci of deleterious mutations. The theory is based on the assumptions of random mating, multiplicative fitness, and weak selection in hermaphrodite plants in the island model of population structure. The analytical results show that Fst at the neutral locus increases as a result of the effects of background selection, regardless of the dependence or independence among linked background selective loci. The increment in Fst is closely related to the magnitude of linkage disequilibria between the neutral locus and selected loci, and can be estimated by the ratio of Fst with background selection to Fst without background selection minus one. The steady-state linkage disequilibrium between a neutral locus and a selected locus in subpopulations, primarily attained by gene flow, decreases with the recombination rate, and can be enhanced when there are dependence among linked selected loci. Monte Carlo computer simulations with two- and three-locus models show that the analytical formulae perform well under general conditions. Application of the present theory may aid in analyzing the genome-wide mapping of the effect of background selection in terms of Fst.     

SSR and morphological trait based population structure analysis of 130 diverse flax (Linum usitatissimum L.) accessions

A total of 130 flax accessions of diverse morphotypes and worldwide origin were assessed for genetic diversity and population structure using 11 morphological traits and microsatellite markers (15 gSSRs and 7 EST–SSRs). Analysis performed after classifying these accessions on the basis of plant height, branching pattern, seed size, Indian/foreign origin into six categories called sub-populations viz. fibre type exotic, fibre type indigenous, intermediate type exotic, intermediate type indigenous, linseed type exotic and linseed type indigenous. The study assessed different diversity indices, AMOVA, population structure and included a principal coordinate analysis based on different marker systems. The highest diversity was exhibited by gSSR markers (SI = 0.46; He = 0.31; P = 85.11). AMOVA based on all markers explained significant difference among fibre type, intermediate type and linseed type populations of flax. In terms of variation explained by different markers, EST-SSR markers (12%) better differentiated flax populations compared to morphological (9%) and gSSR (6%) markers at P = 0.01. The maximum Nei's unbiased genetic distance (D = 0.11) was observed between fibre type and linseed type exotic sub-populations based on EST-SSR markers. The combined structure analysis by using all markers grouped Indian fibre type accessions (63.4%) in a separate cluster along with the Indian intermediate type (48.7%), whereas Indian accessions (82.16%) of linseed type constituted an independent cluster. These findings were supported by the results of the principal coordinate analysis. Morphological markers employed in the study found complementary with microsatellite based markers in deciphering genetic diversity and population structure of the flax germplasm.     

Friends and strangers: a test of the Charnov-Finerty Hypothesis

Summary We tested the hypothesis that populations composed of unrelated animals should perform worse than those composed of related animals by setting up two moderatedly dense field populations in adjacent enclosures: one was composed of related females and one of unrelated females; both had unrelated males. The survival and reproductive success of a number of litters located by spooling were determined. Final population size, pregnancy success, number of young recruited per pregnancy, and survival were similar in both populations. Thus, differences in relatedness produced no differences in demography. We conclude that the Charnov-Finerty Hypothesis in unlikely to be an explanation for microtine population fluctuations.     

TESS3: fast inference of spatial population structure and genome scans for selection

Geography and landscape are important determinants of genetic variation in natural populations, and several ancestry estimation methods have been proposed to investigate population structure using genetic and geographic data simultaneously. Those approaches are often based on computer‐intensive stochastic simulations and do not scale with the dimensions of the data sets generated by high‐throughput sequencing technologies. There is a growing demand for faster algorithms able to analyse genomewide patterns of population genetic variation in their geographic context. In this study, we present TESS3 , a major update of the spatial ancestry estimation program TESS . By combining matrix factorization and spatial statistical methods, TESS3 provides estimates of ancestry coefficients with accuracy comparable to TESS and with run‐times much faster than the Bayesian version. In addition, the TESS3 program can be used to perform genome scans for selection, and separate adaptive from nonadaptive genetic variation using ancestral allele frequency differentiation tests. The main features of TESS3 are illustrated using simulated data and analysing genomic data from European lines of the plant species Arabidopsis thaliana.     

A model for pathogen population structure with cross-protection depending on the extent of overlap in antigenic variant repertoires

The persistence of discrete antigenic types among pathogens with multiple immunogenic loci can be explained by the action of immune-mediated competition. It has previously been shown that pathogen populations will self-organize into non-overlapping subsets of antigenic variants if cross-protection between pathogen types sharing any variants is high. Here, we examine the critical question of whether such strain structure will emerge if the degree of immune-mediated competition is dependent on the number of variants shared between pathogen types, rather than in an all-or-nothing manner. Our analysis uncovers a progression from no strain structure through to discrete stable strain structure through intermediate partially structured states. This suggests that the number of loci or epitope regions required to detect linkage disequilibrium (as a manifestation of stable discrete strain structure) in pathogen populations correlates inversely with the strength of immune selection.     

Kin structure and queen execution in the Argentine ant Linepithema humile

Every spring, workers of the Argentine Ant Linepithema humile kill a large proportion of queens within their nests. Although this behaviour inflicts a high energetic cost on the colonies, its biological significance has remained elusive so far. An earlier study showed that the probability of a queen being executed is not related to her weight, fecundity, or age. Here we test the hypothesis that workers collectively eliminate queens to which they are less related, thereby increasing their inclusive fitness. We found no evidence for this hypothesis. Workers of a nest were on average not significantly less related to executed queens than to surviving ones. Moreover, a population genetic analysis revealed that workers were not genetically differentiated between nests. This means that workers of a given nest are equally related to any queen in the population and that there can be no increase in average worker–queen relatedness by selective elimination of queens. Finally, our genetic analyses also showed that, in contrast to workers, queens were significantly genetically differentiated between nests and that there was significant isolation by distance for queens.     

西非防控埃博拉病毒病暴发和流行的分析

埃博拉出血热自1976年首次暴发以来,其高致死率引起了人们的高度重视。2014年的埃博拉病毒病疫情已造成6800多人死亡。其暴发流行既有病原学和流行病学因素,也与西非当地的政治、经济、文化、卫生现状及应对措施密切相关。因此,综合分析造成流行的因素,有利于尽快控制疫情的迅速蔓延。目前包括中国政府在内的国际社会给予了积极帮助,国际社会与西非本国防控力量的有效结合将在更短的时间内控制疫情,并为我国做好埃博拉病毒病疫情的相关防控提供新的思考。     

Spatial population genetic structure in Trillium grandiflorum: the roles of dispersal, mating, history, and selection

The roles of the various potential ecological and evolutionary causes of spatial population genetic structure (SPGS) cannot in general be inferred from the extant structure alone. However, a stage-specific analysis can provide clues as to the causes of SPGS. We conducted a stage-specific SPGS analysis of a mapped population of about 2000 Trillium grandiflorum (Liliaceae), a long-lived perennial herb. We compared SPGS for juvenile (J), nonreproductive (NR), and reproductive (R) stages. Fisher's exact test showed that genotypes had Hardy-Weinberg frequencies at all loci and stage classes. Allele frequencies did not differ between stages. Bootstrapped 99% confidence intervals (99%CI) indicate that F-statistic values are indistinguishable from zero, (except for a slightly negative FIT for the R stage). Spatial autocorrelation was used to calculate f the average kinship coefficient between individuals within distance intervals. Null hypothesis 99%CIs for f were constructed by repeatedly randomizing genotypic locations. Significant positive fine-scale genetic structure was detected in the R and NR stages, but not in the J stage. This structure was most pronounced in the R stage, and declined by about half in each remaining stage: near-neighbor f = 0.122, 0.065, 0.027, for R, NR, and J, respectively. For R and NR, the near-neighbor f lies outside the null hypothesis 99%CI, indicating kinship at approximately the level of half-sibs and first cousins, respectively. We also simulated the expected SPGS of juveniles post dispersal, based on measured R-stage SPGS, the mating system, and measured pollen and seed dispersal properties. This provides a null hypothesis expectation (as a 99%CI) for the J-stage correlogram, against which to test the likelihood that post-dispersal events have influenced J-stage SPGS. The actual J correlogram lies within the null hypothesis 99%CI for the shortest distance interval and nearly all other distance intervals indicating that the observed low recruitment, random mating and seed dispersal patterns are sufficient to account for the disappearance of SPSG between the R and the J stages. The observed increase in SPGS between J and R stages has two potential explanations: history and local selection. The observed low total allelic diversity is consistent with a past bottleneck: a possible historical explanation. Only a longitudinal stage-specific study of SPGS structure can distinguish between historical events and local selection as causes of increased structure with increasing life history stage.