A numerical solution to the equilibria of the two-locus two-allele selection model.

Examination of the equilibria of the standard two-locus two-allele selection model leads to the construction of a polynomial with coefficients derived from selective values in the genotypic fitness matrix. This polynomial can be partially factored algebraically and numerical techniques are available to extract the roots of the remainder. Each root provides a possible value of the disequilibrium coefficient and the gametic frequencies at equilibrium, and these can be readily checked for stability.     

On the number of stable equilibria and the simultaneous stability of fixation and polymorphism in two-locus models

It is shown that in simple symmetric two-locus, two-allele constant fitness models the bound of four simultaneously stable equilibria previously accepted for general two-locus, two-allele models is exceeded. Situations with five and six stable equilibria are exhibited. These involve four chromosomal fixations and either one or two polymorphic stable equilibria.     

Two-stage two-locus models in genome-wide association

Studies in model organisms suggest that epistasis may play an important role in the etiology of complex diseases and traits in humans. With the era of large-scale genome-wide association studies fast approaching, it is important to quantify whether it will be possible to detect interacting loci using realistic sample sizes in humans and to what extent undetected epistasis will adversely affect power to detect association when single-locus approaches are employed. We therefore investigated the power to detect association for an extensive range of two-locus quantitative trait models that incorporated varying degrees of epistasis. We compared the power to detect association using a single-locus model that ignored interaction effects, a full two-locus model that allowed for interactions, and, most important, two two-stage strategies whereby a subset of loci initially identified using single-locus tests were analyzed using the full two-locus model. Despite the penalty introduced by multiple testing, fitting the full two-locus model performed better than single-locus tests for many of the situations considered, particularly when compared with attempts to detect both individual loci. Using a two-stage strategy reduced the computational burden associated with performing an exhaustive two-locus search across the genome but was not as powerful as the exhaustive search when loci interacted. Two-stage approaches also increased the risk of missing interacting loci that contributed little effect at the margins. Based on our extensive simulations, our results suggest that an exhaustive search involving all pairwise combinations of markers across the genome might provide a useful complement to single-locus scans in identifying interacting loci that contribute to moderate proportions of the phenotypic variance.     

A complete classification of epistatic two-locus models

Background

The study of epistasis is of great importance in statistical genetics in fields such as linkage and association analysis and QTL mapping. In an effort to classify the types of epistasis in the case of two biallelic loci Li and Reich listed and described all models in the simplest case of 0/1 penetrance values. However, they left open the problem of finding a classification of two-locus models with continuous penetrance values.

Results

We provide a complete classification of biallelic two-locus models. In addition to solving the classification problem for dichotomous trait disease models, our results apply to any instance where real numbers are assigned to genotypes, and provide a complete framework for studying epistasis in QTL data. Our approach is geometric and we show that there are 387 distinct types of two-locus models, which can be reduced to 69 when symmetry between loci and alleles is accounted for. The model types are defined by 86 circuits, which are linear combinations of genotype values, each of which measures a fundamental unit of interaction.

Conclusion

The circuits provide information on epistasis beyond that contained in the additive × additive, additive × dominance, and dominance × dominance interaction terms. We discuss the connection between our classification and standard epistatic models and demonstrate its utility by analyzing a previously published dataset.     

Neutral two-locus multiple allele models with recombination

General formulae for the homozygosity and variance of linkage disequilibrium are derived for neutral, stationary, two-locus multiple allele models where there is a symmetric type of mutation at each locus. Particular cases examined are K allele models, the infinite alleles model, and the stepwise mutation model. The two-locus infinite allele model is examined at the molecular level and a joint probability generating function is found for the number of heterozygous sites at each locus in two randomly chosen gametes.     

Uniqueness of polymorphic equilibria under soft selection

Any two allele polymorphic equilibrium of a subdivided haploid population subject to soft selection is stable. This provides that for a two allele system in a subdivided haploid population there is a globally attracting equilibrium which is polymorphic if a polymorphic equilibrium exists, otherwise monomorphic. These results extend to diploid populations if within each habitat the heterozygote viability is greater than or equal to the geometric mean of the homozygote viabilities.     

A complete enumeration and classification of two-locus disease models

There are 512 two-locus, two-allele, two-phenotype, fully penetrant disease models. Using the permutation between two alleles, between two loci, and between being affected and unaffected, one model can be considered to be equivalent to another model under the corresponding permutation. These permutations greatly reduce the number of two-locus models in the analysis of complex diseases. This paper determines the number of nonredundant two-locus models (which can be 102, 100, 96, 51, 50, or 58, depending on which permutations are used, and depending on whether zero-locus and single-locus models are excluded). Whenever possible, these nonredundant two-locus models are classified by their property. Besides the familiar features of multiplicative models (logical AND), heterogeneity models (logical OR), and threshold models, new classifications are added or expanded: modifying-effect models, logical XOR models, interference and negative interference models (neither dominant nor recessive), conditionally dominant/recessive models, missing lethal genotype models, and highly symmetric models. The following aspects of two-locus models are studied: the marginal penetrance tables at both loci, the expected joint identity-by-descent (IBD) probabilities, and the correlation between marginal IBD probabilities at the two loci. These studies are useful for linkage analyses using single-locus models while the underlying disease model is two-locus, and for correlation analyses using the linkage signals at different locations obtained by a single-locus model.     

A simple method for testing two-locus models of inheritance

A graphic method for testing simple two-locus models of inheritance is developed. The model assumes two alleles at each locus where both loci exhibit dominant, both exhibit recessive, or one locus exhibits dominant and one locus exhibits recessive inheritance. Examples of applying the graphs using published data on three diseases are given.     

Multiple stable equilibria in a predator-prey system

Necessary and sufficient conditions are given for three equilibria to occur in a predatorprey model and conditions are given for two of these to be stable. The existence of two stable equilibria requires predator intraspecific competition for either space or food, and the lower the prey growth rate the stronger this predator self-regulation must be. A prey growth rate that is skewed to the right, the ability of a few predators to survive at low prey densities, and predators with high searching effectiveness, long handling times, and large maximum per capita rate of increase all make two stable equilibria more likely.     

Simulation studies of segregation analysis: application to two-locus models

We tested the power of a segregation analysis method (first proposed by Elandt-Johnson) to distinguish between single-locus and two-locus models, with and without environmentally caused reduced penetrance. We also looked at the effect of ascertainment probability on the analysis and at the proband-conditioned ascertainment correction proposed by Cannings and Thompson. We found that: (1) the segregation analysis has sufficient power to distinguish between the fully-penetrant double-recessive (RR) model and the fully-penetrant single-locus dominant and recessive models; (2) the method can also distinguish fairly well between the dominant-recessive (DR) and RR models, even when one does not take into account the population prevalence; (3) the method has much less power to distinguish between the fully-penetrant RR model and the single-locus models with reduced penetrance; (4) when environmental penetrance is taken account of in the analysis, the power of the method to distinguish between the one- and two-locus models improved substantially; (5) the estimates of ascertainment probability, pi, were robust, regardless of the model under which the data were generated; and (6) the Cannings-Thompson approach to ascertainment correction worked well only when the pi used to generate the data was less than .1.     

One- and two-locus models of the origin of worker behavior in hymenoptera

Hamilton, 1964, Hamilton, 1972 suggested that, if females are singly inseminated, the asymmetries in intra-familial relationships inherent in haplo-diploidy should predispose the Hymenoptera to evolve female sex-limited worker behavior, if either a worker raises sibs as reproductives but raises a bias of sisters (pathway 1), or she raises a combination of sibs and sons as reproductives but substitutes sons for brothers preferentially (pathway 2). To investigate these hypotheses when mating is random, we present mathematical and numerical analyses of the one-locus two-allele model of Charnov (1978a) which we generalize. Furthermore, we extend the Charnov model to a more realistic two-locus situation where we postulate that the ability of a worker to raise a bias of sisters or to substitute sons for brothers preferentially is controlled by a locus separate from the locus controlling worker behavior, rather than being a pleiotropic effect of that locus. Considerations of the relative stringencies of the conditions for substitution of the allele for worker behavior and the constraints on linkage suggest that pathway 2 is more likely than pathway 1 for the origin of worker behavior. For pathway 1, we compare the Charnov model with its diplo-diploid analogue. This comparison reveals that, depending on the penetrance of the allele for worker behavior in the heterozygous state, both models permit the evolution of worker behavior even when workers raise the ratio of sisters to brothers laid by the queens, and that an advantage to haplo-diploidy becomes apparent only when workers raise a bias of sisters. For pathway 1, we also consider a generalization of the Craig model (Craig, 1979) which is quite similar to the Charnov model.