THE EVOLUTION OF GENETIC CORRELATIONS: AN ANALYSIS OF PATTERNS

The genetic correlation is a central parameter of quantitative genetics, providing a measure of the rate at which traits respond to indirect selection (i.e., selection that does not act upon the traits under study, but some other trait with which they have genes in common). In this paper, I review the pattern of variation among four combinations of traits: life history × life history (L × L), morphological × morphological (M × M), life history × morphological (L × M), and behavioral × behavioral (B × B). A few other combinations were investigated, but insufficient data were obtained for separate analysis. A total of 1798 correlations, distributed over 51 different animal and plant species, were analyzed. The analysis was conducted at two levels: first by dividing the data set solely by trait combination, and second by blocking the data by trait combination and species. Because selection will tend to fix alleles that show positive correlations with fitness traits faster than those that are negative and because the latter are expected to arise more frequently by mutation, correlations between life-history traits are predicted to be more often negative than those between morphological traits. This prediction was supported, with the ranking in decreasing proportion of negative correlations being: L × L > L × M > B × B > M × M. The mean magnitude of the genetic correlation shows little variation among morphological and life-history combinations, and the distribution of values is remarkably flat. However, the estimated standard errors and the coefficient of variation (SE/r_G) are large, making it difficult to separate biological factors influencing the pattern of dispersion from experimental error. Analysis of the phenotypic and genetic correlations suggest that for the combinations M × M and L × M, but not L × L or B × B, the phenotypic correlation is an adequate estimate of the genetic correlation.     

pathmatrix: a geographical information system tool to compute effective distances among samples

pathmatrix is a tool used to compute matrices of effective geographical distances among samples using a least‐cost path algorithm. This program is dedicated to the study of the role of the environment on the spatial genetic structure of populations. Punctual locations (e.g. individuals) or zones encompassing sample data points (e.g. demes) are used in conjunction with a species‐specific friction map representing the cost of movement through the landscape. Matrices of effective distances can then be exported to population genetic software to test, for example, for isolation by distance. pathmatrix is an extension to the geographical information system (GIS) software arcview 3.x.     

Polymorphism of the SLB serologically defined (non-MHC) alloantigenic system in pigs

Six new antigenic specificities (designated SLB-2 to SLB-7) detectable with polyclonal reagents in the complement-dependent lymphocytotoxic test were determined in the SLB alloantigenic system of pigs. The SLB specificities (including the previously described SLB-1) are controlled by 13 alleles. An analysis of a further 121 double backcross matings (with 817 offspring) confirmed that the products of SLB alleles segregated independently of the SLA haplotypes (swine MHC). In addition, in 112 families of the same mating type (with 746 progeny) the map distance of the SLB locus and the highly polymorphic L blood group locus was found to be 7.82 centimorgans in the heterogametic sex and 12.57 centimorgans in the homogametic sex.     

Intraspecific genetic variation and competition interact to influence niche expansion

Theory and empirical evidence show that intraspecific competition can drive selection favouring the use of novel resources (i.e. niche expansion). The evolutionary response to such selection depends on genetic variation for resource use. However, while genetic variation might facilitate niche expansion, genetically diverse groups may also experience weaker competition, reducing density-dependent selection on resource use. Therefore, genetic variation for fitness on different resources could directly facilitate, or indirectly retard, niche expansion. To test these alternatives, we factorially manipulated both the degree of genetic variation and population density in flour beetles (Tribolium castaneum) exposed to both novel and familiar food resources. Using stable carbon isotope analysis, we measured temporal change and individual variation in beetle diet across eight generations. Intraspecific competition and genetic variation acted on different components of niche evolution: competition facilitated niche expansion, while genetic variation increased individual variation in niche use. In addition, genetic variation and competition together facilitated niche expansion, but all these impacts were temporally variable. Thus, we show that the interaction between genetic variation and competition can also determine niche evolution at different time scales.     

Preparation of fatty acid methyl esters for gas-liquid chromatography

A convenient method using commercial aqueous concentrated HCl (conc. HCl; 35%, w/w) as an acid catalyst was developed for preparation of fatty acid methyl esters (FAMEs) from sterol esters, triacylglycerols, phospholipids, and FFAs for gas-liquid chromatography (GC). An 8% (w/v) solution of HCl in methanol/water (85:15, v/v) was prepared by diluting 9.7 ml of conc. HCl with 41.5 ml of methanol. Toluene (0.2 ml), methanol (1.5 ml), and the 8% HCl solution (0.3 ml) were added sequentially to the lipid sample. The final HCl concentration was 1.2% (w/v). This solution (2 ml) was incubated at 45°C overnight or heated at 100°C for 1–1.5 h. The amount of FFA formed in the presence of water derived from conc. HCl was estimated to be <1.4%. The yields of FAMEs were >96% for the above lipid classes and were the same as or better than those obtained by saponification/methylation or by acid-catalyzed methanolysis/methylation using commercial anhydrous HCl/methanol. The method developed here could be successfully applied to fatty acid analysis of various lipid samples, including fish oils, vegetable oils, and blood lipids by GC.     

The benefits of interpopulation hybridization diminish with increasing divergence of small populations

Interpopulation hybridization can increase the viability of small populations suffering from inbreeding and genetic drift, but it can also result in outbreeding depression. The outcome of hybridization can depend on various factors, including the level of genetic divergence between the populations, and the number of source populations. Furthermore, the effects of hybridization can change between generations following the hybridization. We studied the effects of population divergence (low vs. high level of divergence) and the number of source populations (two vs. four source populations) on the viability of hybrid populations using experimental Drosophila littoralis populations. Population viability was measured for seven generations after hybridization as proportion of populations facing extinction and as per capita offspring production. Hybrid populations established at the low level of population divergence were more viable than the inbred source populations and had higher offspring production than the large control population. The positive effects of hybridization lasted for the seven generations. In contrast, at the high level of divergence, the viability of the hybrid populations was not significantly different from the inbred source populations, and offspring production in the hybrid populations was lower than in the large control population. The number of source populations did not have a significant effect at either low or high level of population divergence. The study shows that the benefits of interpopulation hybridization may decrease with increasing divergence of the populations, even when the populations share identical environmental conditions. We discuss the possible genetic mechanisms explaining the results and address the implications for conservation of populations.     

Influence of genetic architecture on contemporary local evolution in the soapberry bug,Jadera haematoloma: artificial selection on beak length

Little is known about the influence of genetic architecture on local adaptation. We investigated the genetic architecture of the rapid contemporary evolution of mouthparts, the flight polymorphism and life history traits in the soapberry bug Jadera haematoloma (Hemiptera) using laboratory selection. The mouthparts of these seed‐feeding bugs have adapted in 40–50 years by decreasing in length following novel natural selection induced by a host switch to the seeds of an introduced tree with smaller fruits than those of the native host vine. Laboratory selection on beak length in both an ancestral population feeding on the native host and a derived population feeding on the introduced host reveals genetic variance allowing a rapid response (heritabilities of 0.51–0.87) to selection for either longer or shorter beaks. This selection resulted in reverse evolution by restoring long beaks in the derived population and forward evolution by re‐creating short beaks in the ancestral bugs. There were strong genetic correlations (0.68–0.84) in both populations between beak lengths and the frequency of flight morphs, with short beaks associated with short wings. The results reveal a genetically interrelated set of adaptive multivariate traits including both beak length and flight morph. This suite of traits reflects host plant patchiness and seeding phenology. Weaker evidence suggests that egg mass and early egg production may be elements of the same suite. Reversible or forward evolution thus may occur in a broad set of genetically correlated multivariate traits undergoing rapid contemporary adaptation to altered local environments.     

Character compatibility of molecular markers to distinguish asexual and sexual reproduction

Particularly in polyploids, the potential of the high variability of dominant markers such as random amplified polymorphic DNA fragments (RAPDs) and amplified fragment length polymorphisms (AFLPs) in population genetic studies and analysis of breeding systems is reduced due to their dominant nature. In contrast, the criterion of character compatibility is hindered neither by dominance nor by polyploidy as allelic interpretation is not necessary. Character compatibility, which can be used to detect events of genetic exchange (or recombination), is particularly informative if these events are expected to be rare such as in taxa with extensive vegetative reproduction or apomixis. Binary unordered characters such as presence and absence of anonymous DNA markers are incompatible if all four pairwise combinations of character states are present among the individuals studied. Because incompatible character state distributions defy any progenitor–derivative relationship among individuals, they provide strong evidence for genetic exchange. Both the absolute number of incompatible character combinations and the probability of compatibility can be used as a measure of incompatibility. Although these measures may not directly relate to the frequency of genetic exchange, they provide a useful tool to heuristically explore data sets. The most commonly used input for multivariate analyses and analysis of molecular variance in population genetic studies of (dis)similarity of marker distributions are amalgamates of mutation and recombination. Character compatibility can be used to complement these traditional methods of analysis. Advantages and disadvantages of character incompatibility relative to multilocus analysis of modes of reproduction and population genetics are demonstrated with data from RAPDs, isozymes, and restriction fragment length polymorphisms (RFLPs) of the nuclear ribosomal and chloroplast genome.