We used polymorphic microsatellite markers to look for recombination during parthenogenetic oogenesis between the X chromosomes of aphids of the tribe Macrosiphini. We examined the X chromosome because it comprises ∼25% of the genome and previous cytological observations of chromosome pairing and nucleolar organizer (NOR) heteromorphism suggest recombination, although the same is not true for autosomes. A total of 564 parthenogenetic females of Myzus clones with three distinct reproductive modes (cyclical parthenogenesis, obligate parthenogenesis and obligate parthenogenesis with male production) were genotyped at three informative X-linked loci. Also, parthenogenetically produced males from clones encompassing the full range of male-producing reproductive strategies were genotyped. These included 391 Myzus persicae males that were genotyped at three X-linked loci and 538 males from Sitobion clones that were genotyped at five informative X-linked loci. Our results show no departure from clonality in parthenogenetic generations of aphids of the tribe Macrosiphini: no recombinant genotypes were observed in parthenogenetically produced males or females.

The nature of forces maintaining variation for quantitative traits can only be assessed at the level of individual genes affecting variation in the traits. Identification of single-nucleotide polymorphisms (SNPs) associated with variation in Drosophila sensory bristle number at the Delta (Dl) locus provides us with the opportunity to test a model for the maintenance of variation in bristle number by genotype by environment interaction (GEI). Under this model, genetic variation is maintained at a locus under stabilizing selection if phenotypic values of heterozygotes are more stable than homozygotes across a range of environments, and the mean allelic effect is much smaller than the standard deviation of allelic effects across environments. Homozygotes and heterozygotes for two SNPs at Dl, one affecting sternopleural and the other abdominal bristle number, were reared in five different environments. There was significant GEI for both bristle traits. Neither condition of the model was satisfied for Dl SNPs exhibiting GEI for sternopleural bristle number. Heterozygotes for the abdominal bristle number SNPs were indeed the most stable genotype for two of the three environment pairs exhibiting GEI, but the mean genotypic effect was greater than the standard deviation of effects across environments. Therefore, this mechanism of GEI seems unlikely to be responsible for maintaining the common bristle number polymorphisms at Dl.

Rutidosis leptorrynchoides is a perennial forb endemic to grasslands and grassy woodlands in southeastern Australia. Studies of seed dispersal, spatial genetic structure and clonality were carried out in four populations around the Canberra region that varied in levels of correlated paternity to examine: (1) whether R. leptorrhynchoides populations exhibit fine-scale spatial genetic structure and whether this varies between populations as a function of correlated paternity; (2) whether there is a correlation between seed dispersal distance and genetic relatedness within populations; and (3) whether clonal reproduction occurs in this species and to what degree this could account for the observed spatial genetic structure. The results show that there is variation in the magnitude and extent of spatial genetic structure between R. leptorrhynchoides populations. The three larger populations, with low to moderate full-sib proportions, showed significant patterns of coancestry between plants over scales of up to one metre, whereas the smallest population, with a high full-sib proportion, had erratically high but non-significant coancestry values. The observed patterns of genetic clumping could be explained by a combination of limited seed dispersal and correlated mating owing to limited mate availability resulting from the species' sporophytic self-incompatibility system. Clonality does not appear to be an important factor contributing to genetic structure in this species.

Markov chain Monte Carlo procedures allow the reconstruction of full-sibships using data from genetic marker loci only. In this study, these techniques are extended to allow the reconstruction of nested full- within half-sib families, and to present an efficient method for calculating the likelihood of the observed marker data in a nested family. Simulation is used to examine the properties of the reconstructed sibships, and of estimates of heritability and common environmental variance of quantitative traits obtained from those populations. Accuracy of reconstruction increases with increasing marker information and with increasing size of the nested full-sibships, but decreases with increasing population size. Estimates of variance component are biased, with the direction and magnitude of bias being dependent upon the underlying errors made during pedigree reconstruction.

The logistic or S-shaped curve of growth is one of the few universal laws in biology. It is certain that there exist specific genes affecting growth curves, but, due to a lack of statistical models, it is unclear how these genes cause phenotypic differentiation in growth and developmental trajectories. In this paper we present a statistical model for detecting major genes responsible for growth trajectories. This model is incorporated with pervasive logistic growth curves under the maximum likelihood framework and, thus, is expected to improve over previous models in both parameter estimation and inference. The power of this model is demonstrated by an example using forest tree data, in which evidence of major genes affecting stem growth processes is successfully detected. The implications for this model and its extensions are discussed.

Amplified fragment length polymorphisms (AFLPs) are a widely used marker system: the technique is very cost-effective, easy and rapid, and reproducibly generates hundreds of markers. Unfortunately, AFLP alleles are typically scored as the presence or absence of a band and, thus, heterozygous and dominant homozygous genotypes cannot be distinguished. This results in a significant loss of information, especially as regards mapping of quantitative trait loci (QTLs). We present a Monte Carlo Markov Chain method that allows us to compute the identity by descent probabilities (IBD) in a general pedigree whose individuals have been typed for dominant markers. The method allows us to include the information provided by the fluorescent band intensities of the markers, the rationale being that homozygous individuals have on average higher band intensities than heterozygous individuals, as well as information from linked markers in each individual and its relatives. Once IBD probabilities are obtained, they can be combined into the QTL mapping strategy of choice. We illustrate the method with two simulated populations: an outbred population consisting of full sib families, and an F2 cross between inbred lines. Two marker spacings were considered, 5 or 20 cM, in the outbred population. There was almost no difference, for the practical purpose of QTL estimation, between AFLPs and biallelic codominant markers when the band density is taken into account, especially at the 5 cM spacing. The performance of AFLPs every 5 cM was also comparable to that of highly polymorphic markers (microsatellites) spaced every 20 cM. In economic terms, QTL mapping with a dense map of AFLPs is clearly better than microsatellite QTL mapping and little is lost in terms of accuracy of position. Nevertheless, at low marker densities, AFLPs or other biallelic markers result in very inaccurate estimates of QTL position.

Empirical confidence intervals (CIs) for the estimated quantitative trait locus (QTL) location from selective and non-selective non-parametric bootstrap resampling methods were compared for a genome scan involving an Angus×Brahman reciprocal fullsib backcross population. Genetic maps, based on 357 microsatellite markers, were constructed for 29 chromosomes using CRI-MAP V2.4. Twelve growth, carcass composition and beef quality traits (n = 527–602) were analysed to detect QTLs utilizing (composite) interval mapping approaches. CIs were investigated for 28 likelihood ratio test statistic (LRT) profiles for the one QTL per chromosome model. The CIs from the non-selective bootstrap method were largest (87·7 cM average or 79·2% coverage of test chromosomes). The Selective II procedure produced the smallest CI size (42·3 cM average). However, CI sizes from the Selective II procedure were more variable than those produced by the two LOD drop method. CI ranges from the Selective II procedure were also asymmetrical (relative to the most likely QTL position) due to the bias caused by the tendency for the estimated QTL position to be at a marker position in the bootstrap samples and due to monotonicity and asymmetry of the LRT curve in the original sample.