The past decade has yielded new tools for pig geneticists and breeders thanks to the considerable developments resulting from efforts to map the pig genome. The pig genetic linkage map now has nearly 5000 loci including several hundred genes, microsatellites and amplified fragment length polymorphisms (AFLP) markers. Using tools that include somatic cell hybrid panels and radiation hybrid panels, the physical genetic map is also growing rapidly and has over 4000 genes and markers. Scientists using both exotic and commercial breeds for quantitative trait loci (QTL) scans and candidate gene analyses have identified a number of important chromosomal regions and individual genes associated with growth rate, leanness, feed intake, meat quality, litter size and disease resistance. Using marker-assisted selection (MAS) the commercial pig industry is actively incorporating these gene markers and traditional performance information to improve traits of economic importance in pig production. Researchers now have novel tools including pig gene arrays and advanced bioinformatics that are being exploited to find new candidate genes and to advance the understanding of gene function in the pig. Sequencing of the pig genome has been initiated and further sequencing is now being considered. Advances in pig genomics and directions for future research and the implications to both the pig industry and human health are reviewed.

Many quantitative traits are measured as percentages. As a result, the assumption of a normal distribution for the residual errors of such percentage data is often violated. However, most quantitative trait locus (QTL) mapping procedures assume normality of the residuals. Therefore, proper data transformation is often recommended before statistical analysis is conducted. We propose the probit transformation to convert percentage data into variables with a normal distribution. The advantage of the probit transformation is that it can handle measurement errors with heterogeneous variance and correlation structure in a statistically sound manner. We compared the results of this data transformation with other transformations and found that this method can substantially increase the statistical power of QTL detection. We develop the QTL mapping procedure based on the maximum likelihood methodology implemented via the expectation-maximization algorithm. The efficacy of the new method is demonstrated using Monte Carlo simulation.

The Notch pathway comprises a signal transduction cascade required for the proper formation of multiple tissues during metazoan development. Originally described in Drosophila for its role in nervous system formation, the pathway has attracted much wider interest owing to its fundamental roles in a range of developmental and disease-related processes. Despite extensive analysis, Notch signaling is not completely understood and it appears that additional components of the pathway remain to be identified and characterized. Here, we describe a novel genetic strategy to screen for additional Notch pathway genes. The strategy combines partial loss of function for pathway activity with Enhancer-promoter (EP)-induced overexpression of random loci across the dorsoventral wing margin. Mastermind (Mam) is a nuclear component of the Notch signaling cascade. Using a GAL4-UAS-driven dominant-negative form of Mam, we created a genotype that exhibits a completely penetrant dominant wing-nicking phenotype. This phenotype was assayed for enhancement or suppression after outcrossing to several thousand EP lines. The screen identified known components or modifiers of Notch pathway function, as well as several potential new components. Our results suggest that a genetic screen that combines partial loss of function with random gene overexpression might be a useful strategy in the analysis of developmental pathways.

Repeated efforts to estimate the genomic deleterious mutation rate per generation (U) in Drosophila melanogaster have yielded inconsistent estimates ranging from 0·01 to nearly 1. We carried out a mutation-accumulation experiment with a cryopreserved control population in hopes of resolving some of the uncertainties raised by these estimates. Mutation accumulation (MA) was carried out by brother–sister mating of 150 sublines derived from two inbred lines. Fitness was measured under conditions chosen to mimic the ancestral laboratory environment of these genotypes. We monitored the insertions of a transposable element, copia, that proved to accumulate at the unusually high rate of 0·24 per genome per generation in one of our MA lines. Mutational variance in fitness increased at a rate consistent with previous studies, yielding a mutational coefficient of variation greater than 3%. The performance of the cryopreserved control relative to the MA lines was inconsistent, so estimates of mutation rate by the Bateman–Mukai method are suspect. Taken at face value, these data suggest a modest decline in fitness of about 0·3% per generation. The element number of copia was a significant predictor of fitness within generations; on average, insertions caused a 0·76% loss in fitness, although the confidence limits on this estimate are wide.

Genes involved in major biological functions, such as reproductive or cognitive functions, are choice targets for natural selection. However, the extent to which these genes are affected by selective pressures remains undefined. The apparent clustering of these genes on sex chromosomes makes this genomic region an attractive model system to study the effects of evolutionary forces. In the present study, we analysed the genetic diversity of a X-linked microsatellite in 1410 X-chromosomes from 10 different human populations. Allelic frequency distributions revealed an unexpected discrepancy between the sexes. By evaluating the different scenarios that could have led to this pattern, we show that sex-specific selection on the tightly linked VCX gene could be the most likely cause of such a distortion.

Parthenogenetic strains of several species have been found in the genus Drosophila. The mode of diploidization in the eggs of females has been found to be post-meiotic nuclear fusion. The genetic basis for this parthenogenesis is not understood but is believed to be under the control of a complex polygenic system. We found parthenogenetic females in an isofemale strain (LAE345) of D. pallidosa-like collected in 1981 at Lae, Papua New Guinea, and established a parthenogenetically reproducing strain. Parthenogenetic strains of D. ananassae and D. pallidosa collected at Taputimu, American Samoa had also been established by Futch (1972). D. ananassae, D. pallidosa and D. pallidosa-like are very closely related species belonging to the ananassae complex of the ananassae species subgroup of the melanogaster species group. Using these three species, we found that more than 80% of females from parthenogenetic strains produced progeny parthenogenetically and that inter-specific hybrid females also produced impaternate progeny. In the present report, we demonstrate that the mode of parthenogenesis of D. ananassae appears to be the post-meiotic nuclear doubling of a single meiotic product, and that a major gene responsible for the parthenogenesis maps to the left arm of the second chromosome of D. ananassae. We also suggest that the genetic basis for parthenogenesis capacity may be identical among the three closely related species. We discuss the function of the gene required for parthenogenesis and its significance for the evolutionary process.

In regions of suppressed recombination, where selection is expected to be less efficient in removing slightly deleterious mutations, transposable element (TE) insertions should be more likely to drift to higher frequencies, and even to reach fixation. In the absence of excision events, once a TE is fixed it cannot be eliminated from the population, and accumulation of elements thus should become an irreversible process. In the long term, this can drive the degeneration of large non-recombining fractions of the genomes. Chromosome 4 of Drosophila melanogaster has very low levels of recombination, if any, and this could be causing its degeneration. Here we report the results of a PCR-based analysis of the population frequencies of TE insertions in a sample from three African natural populations. We investigated 27 insertions from 12 TE families, located in regions of either suppressed or free recombination. Our results suggest that TE insertions tend to be fixed in the non-recombining regions, particularly on the fourth chromosome. We have also found that this involves all types of elements, and that fixed insertions are significantly shorter and more divergent from the canonical sequence than those segregating in the sample (28·1% vs. 86·3% of the canonical length, and average nucleotide divergence (DXY)=0·082 vs. 0·008, respectively). Finally, DNA-based elements seem to show a greater tendency to reach fixation than retrotransposons. Implications of these findings for the population dynamics of TEs, and the evolutionary forces that shape the patterns of genetic variation in regions of reduced recombination, are discussed.

Identification of cis-regulatory motifs has been difficult due to the short and variable length of the sequences that bind transcription factors. Using both sequence and microarray expression data, we present a method for identifying cis-regulatory motifs that uses regression trees to refine results from simple linear regression of expression levels on motif counts. Analysis of expression patterns from two separate datasets for genes showing significant differences in expression between the sexes in Drosophila melanogaster resulted in a model that identified known binding sites upstream of genes that are differentially expressed in the germline. We obtained a strong result for motif TCGATA, part of the larger, characterized binding site of dGATAb protein. We also identified an uncharacterized motif that is positively associated with sex-biased expression and was assembled from smaller motifs grouped by our model. A regression tree model provides a grouping of independent variables into multiple linear models, an advantage over a single multivariate model. In our case, this grouping of motifs suggests binding sites for cooperating factors in sex-specific expression, as well as a way of combining smaller motifs into larger binding sites.

Drosophila ananassae is a cosmopolitan species with a geographic range throughout most of the tropical and subtropical regions of the world. Previous studies of DNA sequence polymorphism in three genes has shown evidence of selection affecting broad expanses of the genome in regions with low rates of recombination in geographically local populations in and around India. The studies suggest that extensive physical and genetic maps based on molecular markers, and detailed studies of population structure may provide insight into the degree to which natural selection affects DNA sequence polymorphism across broad regions of chromosomes. We have isolated 85 dinucleotide repeat microsatellite sequences and developed assay conditions for genotyping using PCR. The dinucleotide repeats we isolated are shorter, on average, than those isolated in many other Drosophila species. Levels of genetic variation are high, comparable to Drosophila melanogaster. The levels of variation indicate the effective population size of an Indonesian population of D. ananassae is 58692 (infinite allele model) and 217284 (stepwise mutation model), similar to estimates of effective population size for D. melanogaster calculated using dinucleotide repeat microsatellites. The data also show that the Indonesian population is in a rapid expansion phase. Cross-species amplification of the microsatellites in 11 species from the Ananassae, Elegans, Eugracilis and Ficusphila subgroups indicates that the loci may be useful for studies of the sister species, D. pallidosa, but will have limited use for more distantly related species.

An understanding of genetic variation and structure of pest populations has the potential to improve the efficiency of measures to control them. Genetic analysis was undertaken at five microsatellite loci in four native Australian and 14 introduced New Zealand populations of the common brushtail possum Trichosurus vulpecula in order to document these parameters. Genetic variation in New Zealand populations, and phylogenetic relationships among Australian and New Zealand populations, were largely predicted by the recorded introduction history. Populations on the two main islands of New Zealand had only slightly lower genetic diversity than did Australian populations, except that allelic richness on the South Is. was significantly lower. Diversity was higher in North Is. than in South Is. populations (although not significantly so) and mainland New Zealand populations as a group were significantly more diverse than offshore islands that represented secondary population size bottlenecks. In phylogenetic analyses South Is. and offshore island populations grouped with Tasmania, while North Is. populations grouped either with mainland Australia or were intermediate between the two Australian sources. This scheme was supported by admixture coefficients showing that North and South Is./offshore island populations were largely mainland Australian and Tasmanian in origin, respectively. Population structure differed markedly between the North and South Islands: populations were typically more genetically differentiated on the former than the latter, which also showed significant isolation-by-distance. Substantial linkage disequilibrium in most sampled New Zealand but no Australian population between microsatellite loci Tv16 and Tv27 suggests they may be physically linked.

The Hudson–Kreitman–Aguade (HKA) test is based on the prediction from the neutral theory that levels of polymorphism within a species and the divergence between two closely related species should be correlated. Population subdivision has been shown to alter both the amounts of polymorphism segregating within species and the rate of divergence between species, meaning that genomic regions with different population structures also differ in their divergence to polymorphism ratios. Population subdivision may hence hamper the utility of the HKA test for detecting deviations from the standard neutral model, especially for organelle genomes that often have different patterns of population structure compared with nuclear genes. In this paper, I show that population subdivision inflates the number of instances where the HKA test detects deviations from the neutral model. Using coalescent simulations I show that this bias is most apparent when population subdivision is strong and differs substantially between the loci included. However, if divergence time is large and population structure substantial even changes in the levels of polymorphism and divergence associated with differences in the effective population size between two loci is enough to substantially alter the number of significant outcomes of the HKA test. A dataset on cytoplasmic diversity in Silene vulgaris and S. latifolia (Ingvarsson & Taylor, 2002) is also reanalysed. The previous study had shown a marked excess of intraspecific polymorphism in both species. However, when effects of population subdivision were removed, ad hoc, levels of intraspecific polymorphism were no longer significantly different from neutral expectations, suggesting that population subdivision contributed to the observed excess of intraspecific polymorphism seen in both species of Silene.

Newly occurring adaptive genes, such as those providing insecticide resistance, display a fitness cost which is poorly understood. In order to detect subtle behavioural changes induced by the presence of resistance genes, we used natural predators and compared their differential predation on susceptible and resistant Culex pipiens mosquitoes, using strains with a similar genetic background. Resistance genes were either coding an overproduced detoxifying esterase (locus Ester), or an insensitive target (locus ace-1). Differential predation was measured between susceptible and resistant individuals, as well as among resistant mosquitoes. A backswimmer, a water measurer, a water boatman and a predaceous diving beetle were used as larval predators, and a pholcid spider as adult predator. Overall, the presence of a resistance gene increased the probability of predation: all resistance genes displayed predation costs relative to susceptible ones, at either the larval or adult stage, or both. Interestingly, predation preferences among the susceptible and the resistance genes were not ranked uniformly. Possible explanations for these results are given, and we suggest that predators, which are designed by natural selection to detect specific behavioural phenotypes, are useful tools to explore non-obvious differences between two classes of individuals, for example when they differ by the presence or absence of one recent gene, such as insecticide resistance genes.

We present a maximum likelihood method for mapping quantitative trait loci that uses linkage disequilibrium information from single and multiple markers. We made paired comparisons between analyses using a single marker, two markers and six markers. We also compared the method to single marker regression analysis under several scenarios using simulated data. In general, our method outperformed regression (smaller mean square error and confidence intervals of location estimate) for quantitative trait loci with dominance effects. In addition, the method provides estimates of the frequency and additive and dominance effects of the quantitative trait locus.

We used simultaneous mapping of interacting quantitative trait locus (QTL) pairs to study various growth traits in a chicken F2 intercross. The method was shown to increase the number of detected QTLs by 30% compared with a traditional method detecting QTLs by their marginal genetic effects. Epistasis was shown to be an important contributor to the genetic variance of growth, with the largest impact on early growth (before 6 weeks of age). There is also evidence for a discrete set of interacting loci involved in early growth, supporting the previous findings of different genetic regulation of early and late growth in chicken. The genotype–phenotype relationship was evaluated for all interacting QTL pairs and 17 of the 21 evaluated QTL pairs could be assigned to one of four clusters in which the pairs in a cluster have very similar genetic effects on growth. The genetic effects of the pairs indicate commonly occurring dominance-by-dominance, heterosis and multiplicative interactions. The results from this study clearly illustrate the increase in power obtained by using this novel method for simultaneous detection of epistatic QTL, and also how visualization of genotype–phenotype relationships for epistatic QTL pairs provides new insights to biological mechanisms underlying complex traits.

A new deterministic method for predicting simultaneous inbreeding coefficients at three and four loci is presented. The method involves calculating the conditional probability of IBD (identical by descent) at one locus given IBD at other loci, and multiplying this probability by the prior probability of the latter loci being simultaneously IBD. The conditional probability is obtained applying a novel regression model, and the prior probability from the theory of digenic measures of Weir and Cockerham. The model was validated for a finite monoecious population mating at random, with a constant effective population size, and with or without selfing, and also for an infinite population with a constant intermediate proportion of selfing. We assumed discrete generations. Deterministic predictions were very accurate when compared with simulation results, and robust to alternative forms of implementation. These simultaneous inbreeding coefficients were more sensitive to changes in effective population size than in marker spacing. Extensions to predict simultaneous inbreeding coefficients at more than four loci are now possible.

In standard models of quantitative traits, genotypes are assumed to differ in mean but not variance of the trait. Here we consider directional selection for a quantitative trait for which genotypes also confer differences in variability, viewed either as differences in residual phenotypic variance when individual loci are concerned or as differences in environmental variability when the whole genome is considered. At an individual locus with additive effects, the selective value of the increasing allele is given by ia/σ+½ixb/σ2, where i is the selection intensity, x is the standardized truncation point, σ2 is the phenotypic variance, and a/σ and b/σ2 are the standardized differences in mean and variance respectively between genotypes at the locus. Assuming additive effects on mean and variance across loci, the response to selection on phenotype in mean is iσAm2/σ+½ixcovAmv/σ2 and in variance is icovAmv/σ+½ixσ2Av/σ2, where σAm2 is the (usual) additive genetic variance of effects of genes on the mean, σ2Av is the corresponding additive genetic variance of their effects on the variance, and covAmv is the additive genetic covariance of their effects. Changes in variance also have to be corrected for any changes due to gene frequency change and for the Bulmer effect, and relevant formulae are given. It is shown that effects on variance are likely to be greatest when selection is intense and when selection is on individual phenotype or within family deviation rather than on family mean performance. The evidence for and implications of such variability in variance are discussed.

This study investigated whether quantitative trait loci (QTL) identified in experimental crosses of chickens provide a short cut to the identification of QTL in commercial populations. A commercial population of broilers was targeted for chromosomal regions in which QTL for traits associated with meat production have previously been detected in extreme crosses. A three-generation design, consisting of 15 grandsires, 608 half-sib hens and over 15000 third-generation offspring, was implemented within the existing breeding scheme of a broiler breeding company. The first two generations were typed for 52 microsatellite markers spanning regions of nine chicken chromosomes and covering a total of 730 cM, approximately one-fifth of the chicken genome. Using half-sib analyses with a multiple QTL model, linkage was studied between these regions and 17 growth and carcass traits. Out of 153 trait×region comparisons, 53 QTL exceeded the threshold for genome-wide significance while an additional 23 QTL were significant at the nominal 1% level. Many of the QTL affect the carcass proportions and feed intake, for which there are few published studies. Given intensive selection for efficient growth in broilers for more than 50 generations it is surprising that many QTL affecting these traits are still segregating. Future fine-mapping efforts could elucidate whether ancestral mutations are still segregating as a result of pleiotropic effects on fitness traits or whether this variation is due to new mutations.

This report presents a theoretical formulation for predicting heterozygosity of a putative marker locus linked to two quantitative trait loci (QTL) in a recurrent selection and backcross (RSB) scheme. Since the heterozygosity at any given marker locus maintained in such a breeding programme reflects its map location relative to QTL, the present study develops the theoretical analysis of the QTL mapping method that recently appeared in the literature. The formulae take into account selection, recombination and finite population size during the multiple-generation breeding scheme. The single-marker and two-QTL model was compared numerically with the model involving two linked marker loci and two QTL. Without recombination interference, the two models predict the same expected heterozygosity at the linked marker loci, indicating that the model is valid for predicting marker heterozygosity maintained at any loci in an RSB breeding scheme. The formulation is demonstrated numerically for several RSB schemes and its implications in developing a likelihood-based statistical framework for modeling the RSB experiments are discussed.

Quadratic indices are a general approach for the joint management of genetic gain and inbreeding in artificial selection programmes. They provide the optimal contributions that selection candidates should have to obtain the maximum gain when the rate of inbreeding is constrained to a predefined value. This study shows that, when using quadratic indices, the selective advantage is a function of the Mendelian sampling terms. That is, at all times, contributions of selected candidates are allocated according to the best available information about their Mendelian sampling terms (i.e. about their superiority over their parental average) and not on their breeding values. By contrast, under standard truncation selection, both estimated breeding values and Mendelian sampling terms play a major role in determining contributions. A measure of the effectiveness of using genetic variation to achieve genetic gain is presented and benchmark values of 0·92 for quadratic optimisation and 0·5 for truncation selection are found for a rate of inbreeding of 0·01 and a heritability of 0·25.

The transmission/disequilibrium test (TDT) and the affected sib pair test (ASP) both test for the association of a marker allele with some conditions. Here, we present methods for calculating the probability of detecting the association (power) for a study examining a fixed number of families for suitability for the study and for calculating the number of such families to be examined. Both calculations use a genetic model for the association. The model considered posits a bi-allelic marker locus that is linked to a bi-allelic disease locus with a possibly nonzero recombination fraction between the loci. The penetrance of the disease is an increasing function of the number of disease alleles. The TDT tests whether the transmission by a heterozygous parent of a particular allele at a marker locus to an affected offspring occurs with probability greater than 0·5. The ASP tests whether transmission of the same allele to two affected sibs occurs with probability greater than 0·5. In either case, evidence that the probability is greater than 0·5 is evidence for association between the marker and the disease. Study inclusion criteria (IC) can greatly affect the necessary sample size of a TDT or ASP study. IC considered by us include a randomly selected parent at least one parent or both parents required to be heterozygous. It also allows a specified minimum number of affected offspring to be required (TDT only). We use elementary probability calculations rather than complex mathematical manipulations or asymptotic methods (large sample size approximations) to compute power and requisite sample size for a proposed study. The advantages of these methods are simplicity and generality.