Finding associations in dense genetic maps: a genetic algorithm approach

Large-scale association studies hold promise for discovering the genetic basis of common human disease. These studies will consist of a large number of individuals, as well as large number of genetic markers, such as single nucleotide polymorphisms (SNPs). The potential size of the data and the resulting model space require the development of efficient methodology to unravel associations between phenotypes and SNPs in dense genetic maps. Our approach uses a genetic algorithm (GA) to construct logic trees consisting of Boolean expressions involving strings or blocks of SNPs. These blocks or nodes of the logic trees consist of SNPs in high linkage disequilibrium (LD), that is, SNPs that are highly correlated with each other due to evolutionary processes. At each generation of our GA, a population of logic tree models is modified using selection, cross-over and mutation moves. Logic trees are selected for the next generation using a fitness function based on the marginal likelihood in a Bayesian regression frame-work. Mutation and cross-over moves use LD measures to pro pose changes to the trees, and facilitate the movement through the model space. We demonstrate our method and the flexibility of logic tree structure with variable nodal lengths on simulated data from a coalescent model, as well as data from a candidate gene study of quantitative genetic variation.     

Quantification of a genetic message in selection

The genetic communication system includes the following components: the parent, which represents the information source and which emits messages; the gametes, which are the messenger carriers; and the offspring, which results from the decoding of two of these messages and can, in turn, become an information source.In a diploid species, a pair of heterozygous homologous loci may emit two equally probable messages, the quantity of genetic information (Q) produced being equivalent to: Q=log₂ 2=1 bit. For n independent pairs of heterozygous homologous loci, Q=n.log₂ 2=n bits. The evolution of Q is examined whenever the parent is used in inbreeding or crossbreeding. In the case of inbreeding, the initial Q is depleted as the loci become homozygous; for hybridization the evolution of Q is unpredictable.In the case of pairs of linked heterozygous homologous loci, Q is represented by an equation similar to that used to describe entropy. The value of entropy is lower when linkage between loci is tighter, the freedom of choice in selection is reduced.     

Reinforcement of genetic coherence in a two-locus model

Background  

In order to maintain populations as units of reproduction and thus enable anagenetic evolution, genetic factors must exist which prevent continuing reproductive separation or enhance reproductive contact. This evolutionary principle is called genetic coherence and it marks the often ignored counterpart of cladistic evolution. Possibilities of the evolution of genetic coherence are studied with the help of a two-locus model with two alleles at each locus. The locus at which viability selection takes place is also the one that controls the fusion of gametes. The second locus acts on the first by modifying the control of the fusion probabilities. It thus acts as a mating modifier whereas the first locus plays the role of the object of selection and mating. Genetic coherence is enhanced by modifications which confer higher probabilities of fusion to heterotypic gametic combinations (resulting in heterozygous zygotes) at the object locus.     

Genome-wide prediction of genetic interactions in a metazoan

Genetic interactions provide information about genes and processes with overlapping functions in biological systems. For Saccharomyces cerevisiae, computational integration of multiple types of functional genomic data is used to generate genome-wide predictions of genetic interactions. However, this methodology cannot be applied to the vastly more complex genome of metazoans, and only recently has the first metazoan genome-wide prediction of genetic interactions been reported. The prediction for Caenorhabditis elegans was generated by computationally integrating functional genomic data from S. cerevisiae, C. elegans and Drosophila melanogaster. This achievement is an important step toward system-level understanding of biological systems and human diseases.     

Neutral additive genetic variance in a metapopulation

For neutral, additive quantitative characters, the amount of additive genetic variance within and among populations is predictable from Wright's FST, the effective population size and the mutational variance. The structure of quantitative genetic variance in a subdivided metapopulation can be predicted from results from coalescent theory, thereby allowing single-locus results to predict quantitative genetic processes. The expected total amount of additive genetic variance in a metapopulation of diploid individual is given by 2Ne sigma m2 (1 + FST), where FST is Wright's among-population fixation index, Ne is the eigenvalue effective size of the metapopulation, and sigma m2 is the mutational variance. The expected additive genetic variance within populations is given by 2Ne sigma e2(1-FST), and the variance among demes is given by 4FSTNe sigma m2. These results are general with respect to the types of population structure involved. Furthermore, the dimensionless measure of the quantitative genetic variance among populations, QST, is shown to be generally equal to FST for the neutral additive model. Thus, for all population structures, a value of QST greater than FST for neutral loci is evidence for spatially divergent evolution by natural selection.     

Study of the genetic code adaptability by means of a genetic algorithm

We used simulated evolution to study the adaptability level of the canonical genetic code. An adapted genetic algorithm (GA) searches for optimal hypothetical codes. Adaptability is measured as the average variation of the hydrophobicity that the encoded amino acids undergo when errors or mutations are present in the codons of the hypothetical codes. Different types of mutations and point mutation rates that depend on codon base number are considered in this study. Previous works have used statistical approaches based on randomly generated alternative codes or have used local search techniques to determine an optimum value. In this work, we emphasize what can be concluded from the use of simulated evolution considering the results of previous works. The GA provides more information about the difficulty of the evolution of codes, without contradicting previous studies using statistical or engineering approaches. The GA also shows that, within the coevolution theory, the third base clearly improves the adaptability of the current genetic code.     

Temporal genetic patterns of diversity and structure evidence chaotic genetic patchiness in a spiny lobster

Population structure of many marine organisms is spatially patchy and varies within and between years, a phenomenon defined as chaotic genetic patchiness. This results from the combination of planktonic larval dispersal and environmental stochasticity. Additionally, in species with bi‐partite life, postsettlement selection can magnify these genetic differences. The high fecundity (up to 500,000 eggs annually) and protracted larval duration (12–24 months) and dispersal of the southern rock lobster, Jasus edwardsii, make it a good test species for chaotic genetic patchiness and selection during early benthic life. Here, we used double digest restriction site‐associated DNA sequencing (ddRADseq) to investigate chaotic genetic patchiness and postsettlement selection in this species. We assessed differences in genetic structure and diversity of recently settled pueruli across four settlement years and between two sites in southeast Australia separated by approximately 1,000 km. Postsettlement selection was investigated by identifying loci under putative positive selection between recently settled pueruli and postpueruli and quantifying differences in the magnitude and strength of the selection at each year and site. Genetic differences within and among sites through time in neutral SNP markers indicated chaotic genetic patchiness. Recently settled puerulus at the southernmost site exhibited lower genetic diversity during years of low puerulus catches, further supporting this hypothesis. Finally, analyses of outlier SNPs detected fluctuations in the magnitude and strength of the markers putatively under positive selection over space and time. One locus under putative positive selection was consistent at both locations during the same years, suggesting the existence of weak postsettlement selection.     

Contrasting patterns of genetic diversity at three different genetic markers in a marine mammal metapopulation

Many studies use genetic markers to explore population structure and variability within species. However, only a minority use more than one type of marker and, despite increasing evidence of a link between heterozygosity and individual fitness, few ask whether diversity correlates with population trajectory. To address these issues, we analysed data from the Steller's sea lion, Eumetiopias jubatus , where three stocks are distributed over a vast geographical range and where both genetic samples and detailed demographic data have been collected from many diverse breeding colonies. To previously published mitochondrial DNA (mtDNA) and microsatellite data sets, we have added new data for amplified fragment length polymorphism (AFLP) markers, comprising 238 loci scored in 285 sea lions sampled from 23 natal rookeries. Genotypic diversity was low relative to most vertebrates, with only 37 loci (15.5%) being polymorphic. Moreover, contrasting geographical patterns of genetic diversity were found at the three markers, with Nei's gene diversity tending to be higher for AFLPs and microsatellites in rookeries of the western and Asian stocks, while the highest mtDNA values were found in the eastern stock. Overall, and despite strongly contrasting demographic histories, after applying phylogenetic correction we found little correlation between genetic diversity and either colony size or demography. In contrast, we were able to show a highly significant positive relationship between AFLP diversity and current population size across a range of pinniped species, even though equivalent analyses did not reveal significant trends for either microsatellites or mtDNA.     

Spatial genetic structure of a small rodent in a heterogeneous landscape

Gene flow in natural populations may be strongly influenced by landscape features. The integration of landscape characteristics in population genetic studies may thus improve our understanding of population functioning. In this study, we investigated the population genetic structure and gene flow pattern for the common vole, Microtus arvalis, in a heterogeneous landscape characterised by strong spatial and temporal variation. The studied area is an intensive agricultural zone of approximately 500 km² crossed by a motorway. We used individual-based Bayesian methods to define the number of population units and their spatial borders without prior delimitation of such units. Unexpectedly, we determined a single genetic unit that covered the entire area studied. In particular, the motorway considered as a likely barrier to dispersal was not associated with any spatial genetic discontinuity. Using computer simulations, we demonstrated that recent anthropogenic barriers to effective dispersal are difficult to detect through analysis of genetic variation for species with large effective population sizes. We observed a slight, but significant, pattern of isolation by distance over the whole study site. Spatial autocorrelation analyses detected genetic structuring on a local scale, most probably due to the social organisation of the study species. Overall, our analysis suggests intense small-scale dispersal associated with a large effective population size. High dispersal rates may be imposed by the strong spatio-temporal heterogeneity of habitat quality, which characterises intensive agroecosystems.     

Parasite-driven genetic change in a natural population of Daphnia

A substantial body of theory indicates that parasites may mould the population genetic structure of their hosts, but few empirical studies have directly linked parasitism to genetic dynamics. We used molecular markers (allozymes) to investigate genotype frequency changes in a natural population of the crustacean Daphnia magna in relation to an epidemic of the bacterial pathogen Pasteuria ramosa. The population experienced a severe epidemic during the study period in which parasite prevalence reached 100% of the adult portion of the population. The parasite epidemic was associated with genetic change in the host population. Clonal diversity was observed to decrease as parasite prevalence increased in the population, and tests for differences in the clonal composition of the population before, during, and after the epidemic indicated that significant change had occurred. A laboratory infection experiment showed that the genotypes which were more common following the peak of the parasite epidemic were also the most resistant to parasite infection. Thus, this study provides an illustration of parasite-mediated selection in the wild.     

Convergence of genetic distances in a migration matrix model

A recurring problem with the use of migration matrix models of genetic differentiation has to do with their convergence properties. In practice, predictions can be drawn from these models only at equilibrium; but in the case of the standard predictors (most of which are modifications of Wright's FST), it can take an unrealistically large number of generations to approach equilibrium. An alternative set of predictors, the set of all pairwise genetic distances among the populations that define the rows and columns of the migration matrix, is investigated here. These distances are shown analytically to converge much more rapidly than the more commonly used predictors. In an application of the model to migration data on a human population from Papua New Guinea, it takes only about three to four generations for the pairwise distances to converge, in contrast to more than 100 generations for one of the standard predictors. In this case, moreover, the distances predicted by the model at equilibrium are similar to those calculated from the available genetic data.     

Context-dependent genetic benefits of polyandry in a marine hermaphrodite

Numerous studies emphasize the potential indirect (genetic) benefits of polyandry in animals with resource-free mating systems. In this paper, we examine the potential for these benefits to fuel sexual selection and polyandry in the hermaphroditic ascidian Pyura stolonifera. Individuals were designated either sire (sperm producers) or dam (egg producers) at random and crossed in a North Carolina II breeding design to produce both paternal and maternal half siblings for our quantitative genetic analysis. We then partitioned the phenotypic variance in fertilization and hatching rates into additive and non-additive variance components. We found significant additive variance attributable to sire and dam effects at fertilization and hatching, suggesting the potential for selection to favour individuals carrying intrinsically 'good genes' for these traits. In separate analyses involving monandrous and polyandrous clutches, we found that both traits were elevated under polyandry, but the difference in hatching rates was due entirely to the difference in fertilization rates between treatments. When the hatching rates were standardized to account for variance at fertilization, there was no overall net benefit of polyandry for this trait. Despite this, we found that hatching success declined with increasing embryo densities, and that the slope of this decline was significantly greater in monandrous than polyandrous clutches. Hence, selection on embryo viability may still favour polyandry under restricted environmental conditions. Nevertheless, our results caution against interpreting elevated hatching success as an indirect genetic benefit of polyandry when variance in fertilization is not controlled.     

Cost-efficient selection of a marker panel in genetic studies

Genetic techniques are frequently used to sample and monitor wildlife populations. The goal of these studies is to maximize the ability to distinguish individuals for various genetic inference applications, a process which is often complicated by genotyping error. However, wildlife studies usually have fixed budgets, which limit the number of genetic markers available for inclusion in a study marker panel. Prior to our study, a formal algorithm for selecting a marker panel that included genotyping error, laboratory costs, and ability to distinguish individuals did not exist. We developed a constrained nonlinear programming optimization algorithm to determine the optimal number of markers for a marker panel, initially applied to a pilot study designed to estimate black bear abundance in central Georgia. We extend the algorithm to other genetic applications (e.g., parentage or population assignment) and incorporate possible null alleles. Our algorithm can be used in wildlife pilot studies to assess the feasibility of genetic sampling for multiple genetic inference applications. © 2011 The Wildlife Society.     

Self-organised criticality in a genetic model of species-species interaction

Summary Genetics incorporated into a two trophic level species-species interaction model allows the populations of species to evolve. The system enters a regime where the extinction of species follows an erratic pattern in time and appears chaotic to the eye. Quantitative measurements suggest that the dynamics of the model exhibits self organised criticality. Fourier Transform analysis of the time series and autocorrelation function for the population data, as well as the distribution of lineage sizes and longevity of lineages, all show power law behavior. The lineages are the analogue of avalanches in other models of self organised criticality     

The genetic architecture of behavioral traits in a spider

The existence of consistent individual differences in behavior has been shown in a number of species, and several studies have found observable sex differences in these behaviors, yet their evolutionary implications remain unclear. Understanding the evolutionary dynamics of behavioral traits requires knowledge of their genetic architectures and whether this architecture differs between the sexes. We conducted a quantitative genetic study in a sexually size‐dimorphic spider, Larinioides sclopetarius, which exhibits sex differences in adult lifestyles. We observed pedigreed spiders for aggression, activity, exploration, and boldness and used animal models to disentangle genetic and environmental influences on these behaviors. We detected trends toward (i) higher additive genetic variances in aggression, activity, and exploration in males than females, and (ii) difference in variances due to common environment/maternal effects, permanent environment and residual variance in aggression and activity with the first two variances being higher in males for both behaviors. We found no sex differences in the amount of genetic and environmental variance in boldness. The mean heritability estimates of aggression, activity, exploration, and boldness range from 0.039 to 0.222 with no sizeable differences between females and males. We note that the credible intervals of the estimates are large, implying a high degree of uncertainty, which disallow a robust conclusion of sex differences in the quantitative genetic estimates. However, the observed estimates suggest that sex differences in the quantitative genetic architecture of the behaviors cannot be ruled out. Notably, the present study suggests that genetic underpinnings of behaviors may differ between sexes and it thus underscores the importance of taking sex differences into account in quantitative genetic studies.