The historical population genetic processes associated with the divergence of members of the Drosophila virilis species group were examined using DNA sequence variation from two loci. New data on DNA sequence variation from the oskar locus, taken from within and among all five closely related taxa in the virilis phylad of the D. virilis species group, were examined and compared with similar data previously collected from the period locus. Overall, the oskar and period data sets reveal similar patterns of variation. Both loci support the conclusion that the two subspecies of D. americana have had a large historical population size and are exchanging genes in nature. From these data there is little reason to consider them as distinct taxa. In the case of D. novamexicana, from which six lines were sequenced at each locus, there is an intriguing difference in the pattern seen at the two loci. Both loci reveal two distinct groups that are considerably divergent from each other, with very little evidence of gene flow between them. However, the grouping of lines into distinct subgroups based on oskar is different from the grouping based on period. The simplest explanation seems to be that D. novamexicana includes two distinct species, and that the sample of six lines happens to include cases of recent gene exchange. Alternatively, both oskar and period could be linked to sites of strong balancing selection and limited recombination.

Resistance to toxicants is a convenient model for investigating whether adaptive changes are associated with pleiotropic fitness costs. Despite the voluminous literature devoted to this subject, intraspecific comparisons among toxicant resistance genes are rare. We report here results on the pleiotropic effect on adult survival of Culex pipiens mutants involved in the same adaptation: the resistance to organophosphorus insecticides. This field study was performed in southern France where four resistance genes sequentially appeared and increased in frequency in response to intense insecticide control. By repeated sampling of overwintering females through winter, we analysed the impact of each of three resistance genes on adult survival. We showed that (i) the most recent gene seems to be of no disadvantage during winter, (ii) the oldest affects survival in some environmental conditions, and (iii) the third induces a constant, severe and dominant survival cost. Such variability is discussed in relation to the physiological changes involved in resistance.

Individual records from the coding of molecular polymorphism (molecular profiles) are particularly useful for the identification of clones or cultivars, in pedigree analysis, in the estimation of genetic distances and relatedness, and as a tool in genome mapping and population genetics. A parametric statistical analysis of molecular profile components can be infeasible because of the huge number of observed markers, the presence of missing values and the high number of parameters required to evaluate the importance of interactions among markers. Moreover, new powerful molecular techniques make possible the analysis of numerous markers at one time; therefore parametric statistical methods could result in troublesome models with more parameters than data. The field of computer-based techniques offers new strategies to cope with the complexity of molecular profiles. We suggest the use of a Genetic Classifier System to evaluate the importance of profile components. The procedure is based on a Genetic Algorithm approach, a numerical technique that simulates some features of the natural selection process to solve problems. A set of isozyme data from a Norway spruce population is analysed in order to assess their ability to predict the individual plant response to the presence of abiotic stresses. The results, obtained by three different computer simulations, show that this computer-based approach is particularly effective for ranking profile components according to their relevance. Genetic Classifier Systems could also be used as a preliminary step to reduce the complexity of molecular data sets.

Allozyme-associated heterosis has been repeatedly observed in marine bivalves, but its genetic origin remains debatable. A simple explanation is direct overdominance at the enzyme loci scored. An alternative is associative overdominance due to partial inbreeding, affecting the whole genome. The two hypotheses yield different predictions concerning (i) locus-specific effects, (ii) the relationship between heterozygosity and the variance in fitness, and (iii) the expected form of the relationship between the multilocus genotype and mean fitness. The relationship between heterozygosity and growth, a component of fitness, is here analysed in Spisula ovalis (1669 individuals, 9 loci), using statistical models designed to test these predictions. In contrast to most other bivalves, S. ovalis shells display clear annual growth lines allowing accurate quantification of individual age and growth. Our results show (i) that there is no evidence for locus-specific effects, (ii) that the variance in growth decreases significantly when heterozygosity increases, and (iii) that growth is better predicted by a genetic variable optimized for inbreeding than by a variable optimized for overdominance. In addition, the heterozygosity–growth relationship displays a significant variation among annual cohorts, being more pronounced in young cohorts. Although the need to pool alleles and the occurrence of null alleles may limit the efficiency of some of the models used (especially for result (iii)), our results suggest that the heterozygosity–growth relationship is due to inbreeding effects.

Mouse populations differing in metabolic rate have been developed through selection for high (MH) and low (ML) heat loss (HLOSS), along with randomly selected controls (MC). Objectives of this study were to (a) compare MH, ML and MC lines for HLOSS and correlated traits of feed intake, body composition and organ weights; (b) compare three widely used inbred mouse lines with MH, ML and MC for the same traits; and (c) investigate potential genotype by diet interaction resulting from feeding diets differing in fat percentage. Heat loss (kcal/day) of MH and ML mice differed by 37% of the mean and remained significant (33%) when HLOSS was expressed on a fat-free mass basis. MH mice consumed more energy than ML with a greater difference in mice fed high-fat compared with standard diets (27% vs 13·9%). Despite greater energy consumption, MH mice were leaner than ML with a difference in total body fat percentage of 40%. The greatest difference in HLOSS between selection and inbred lines was between MH and C57BL/6J (BL), which differed by 26·3%. MH and BL mice also differed in energy intake (15·5%). Body composition of BL mice was similar to MH when fed a standard diet, but similar to ML when fed a high-fat diet. Crosses between MH and ML or between MH and BL would be useful to investigate the genetic regulation of, and identify quantitative trait loci influencing HLOSS, energy intake and body composition. Feeding of a high-fat diet may allow diet-specific loci influencing body composition to be identified in MH and BL lines.

Linkage analysis and map construction using molecular markers is far more complicated in full-sib families of outbreeding plant species than in progenies derived from homozygous parents. Markers may vary in the number of segregating alleles. One or both parents may be heterozygous, markers may be dominant or codominant and usually the linkage phases of marker pairs are unknown. Because of these differences, marker pairs provide different amounts of information for the estimation of recombination frequencies and the linkage phases of the markers in the two parents, and usually these have to be estimated simultaneously. In this paper we present a complete overview of all possible configurations of marker pairs segregating in full-sib families. Maximum likelihood estimators for the recombination frequency and LOD score formulas are presented for all cases. Statistical properties of the estimators are studied analytically and by simulation. Specific problems of dominant markers, in particular with respect to the probability of detecting linkage, the probability of obtaining zero estimates, and the ability to distinguish linkage phase combinations, and consequences for mapping studies in outbred progenies are discussed.

The variance effective size (Ne) was formulated for populations of monoecious plant species that are partly asexually propagating with discrete or overlapping generations. It was shown that partly asexually reproducing populations have larger or smaller effective sizes (ratios to the census size N) than fully sexually reproducing populations, according to whether the term Vc/c¯ is smaller or larger than the term (Vk/k¯ +1−β)/2, where c¯ and Vc are the mean and variance of the number of progeny asexually produced per plant per year, respectively, k¯ and Vk are the mean and variance of the number of gametes contributed per plant per year, respectively, and β is the selfing rate of each plant. Asexual reproduction has no effect on Ne when the two terms are equal, as is true when the numbers of both sexually and asexually produced progeny per plant per year are Poisson-distributed (Vc/c¯=1 and Vk/k¯=1+β). Populations with a larger generation length (L) tend to have a smaller effective size: for a population model of age-independent survival and fecundity with an annual rate δ of asexual reproduction, Ne declines asymptotically to N(2−β)/{3−β +Vk/k¯ +(2Vc/c¯ −Vk/k¯ −1+β).δ} as L gets large, which simplifies to N(2−β)/4 under a Poisson-distributed reproductive contribution. The trade-off relation of Ne and L, however, does not always hold: for stage-structured populations, increase in the survival rate of juveniles may act to increase both Ne and L.

Selective genotyping, i.e. increasing the size of the population phenotyped and genotyping only individuals from the high and low tails of the population, can considerably improve the efficiency of experiments aimed at detecting and locating quantitative trait loci (QTLs) affecting a single trait. In this paper we study how selective genotyping can increase the efficiency of multitrait QTL experiments. By selecting on an index combining the variables of interest and having the maximum correlation with each variable, the efficiency of QTL detection is increased for each trait. The efficiency of selective genotyping relative to random selection strongly depends on the correlation between the index and each variable. The optimum selection rate that minimizes costs for a given experimental power depends also on this correlation and on the genotyping costs relative to phenotyping costs. When the population segregating for the quantitative traits and the markers is not as simple as a backcross or an F2 population, but is composed of several connected or unconnected families, selective genotyping can be used to improve the efficiency of the QTL study. In this case, the extreme individuals should be selected within each family. A method is provided to choose the selection rates within each family in order to optimize the global power of the experiment when the family sizes are unequal.