Food shortage is a stress factor that commonly affects organisms in nature. Resistance to food shortage or starvation resistance (SR) is a complex quantitative trait with direct implications on fitness. However, surveys of natural genetic variation in SR at different geographic scales are scarce. Here, we have measured variation in SR in sets of lines derived from nine natural populations of Drosophila melanogaster collected in western Argentina. Our study shows that within population variation explained a larger proportion of overall phenotypic variance (80%) than among populations (7·2%). We also noticed that an important fraction of variation was sex-specific. Overall females were more resistant to starvation than males; however, the magnitude of the sexual dimorphism (SD) in SR varied among lines and explained a significant fraction of phenotypic variance in all populations. Estimates of cross-sex genetic correlations suggest that the genetic architecture of SR is only partially shared between sexes in the populations examined, thus, facilitating further evolution of the SD.

Drosophila melanogaster, like other organisms, move and orient themselves in response to the earth's gravitational force. The ability to sense and respond to gravity is essential for an organism to navigate and thrive in its environment. The genes underlying this behaviour in Drosophila remain elusive. Using 88 recombinant inbred lines, we have identified four quantitative trait loci (QTLs) that contribute to adult gravitaxis (geotaxis) behaviour in Drosophila. Candidate genes of interest were selected from the QTLs of highest significance based on their function in chordotonal organ formation. Quantitative complementation tests with these candidate genes revealed a role for skittles in adult gravitaxis behaviour in D. melanogaster.

Survival from birth to a reproductive adult is a challenge that only robust individuals resistant to a variety of mortality factors will overcome. To assess whether survival traits share genetic architecture throughout the life cycle, we estimated genetic correlations for survival within fingerling stage, and across egg, fingerling and grow-out stages in farmed rainbow trout. Genetic parameters of survival at three life cycle stages were estimated for 249 166 individuals originating from ten year classes of a pedigreed population. Despite being an important fitness component, survival traits harboured significant but modest amount of genetic variation (h2=0·07–0·27). Weak associations between survival during egg-fry and fingerling periods, between early and late fingerling periods (rG=0·30) and generally low genetic correlations between fingerling and grow-out survival (mean rG=0·06) suggested that life-stage specific survival traits are best regarded as separate traits. However, in the sub-set of data with detailed time of death records, positive genetic correlations between early and late fingerling survival (rG=0·89) showed that during certain years the best genotypes in the early period were also among the best in the late period. That survival across fingerling period can be genetically the same, trait was indicated also by only slightly higher heritability (h2=0·15) estimated with the survival analysis of time to death during fingerling period compared to the analysis treating fingerling survival as a binary character (h2=0·11). The results imply that (1) inherited resistance against unknown mortality factors exists, but (2) ranking of genotypes changes across life stages.

The mode of reproduction of the soil ascomycetous fungus Emericella nidulans of Israeli populations was studied using 15 microsatellite (simple sequence repeats or SSR) trinucleotide markers. The study was performed in three canyons: two located in the northern part of Israel (Mount Carmel and western Upper Galilee) and one in the southern Negev desert. In each canyon, E. nidulans strains were isolated from the opposite slopes and (in the desert canyon) the valley bottom. Testing the reproductive structure of the populations indicated the presence of sexuality in the northern population and predominant clonality in the desert population. The predominantly clonal character of the desert population of E. nidulans was explained by the assumption that for relevant multilocus systems of a fungus, only several haplotypes can survive in the rather constant, extremely stressful desert conditions. Additionally, the very low density of E. nidulans populations in the soil of the desert canyon, which reduces the probability of finding a sexual partner, might favour predominant clonality via selfing. Increasing sexuality in E. nidulans populations on the north-facing slopes of the northern canyons may be a result of biotic stress (pressure of competitive fungal species), due to the more mild ecological conditions in these canyons.

Over the past 30 years, the characteristics that have made the nematode Caenorhabditis elegans one of the premier animal model systems have also allowed it to emerge as a powerful model system for determining the genetic basis of quantitative traits, particularly for the identification of naturally segregating and/or lab-adapted alleles with large phenotypic effects. To better understand the genetic underpinnings of natural variation in other complex phenotypes, C. elegans is uniquely poised in the emerging field of quantitative systems biology because of the extensive knowledge of cellular and neural bases to such traits. However, perturbations in standing genetic variation and patterns of linkage disequilibrium among loci are likely to limit our ability to tie understanding of molecular function to a broader evolutionary context. Coupling the experimental strengths of the C. elegans system with the ecological advantages of closely related nematodes should provide a powerful means of understanding both the molecular and evolutionary genetics of quantitative traits.

TP5, a P element inserted in the telomere-associated sequences of the X chromosome, represses the excision of other P elements in the germ line through a combination of maternal and zygotic effects. The maternal component of this repression is impaired by heterozygous mutations in the aubergine and Suppressor of variegation 205 genes; one mutation in the piwi gene also appears to impair repression. In the female germ line, the level of TP5 mRNA is increased by these impairing mutations. The impairing aubergine and piwi mutations also increase the level of germ-line mRNA from CP, a transgene that encodes the P-element transposase; however, the Suppressor of variegation 205 mutation does not. These findings are discussed in terms of a model of P-element regulation that involves post-transcriptional and chromatin re-organizing events mediated by maternally transmitted small RNAs derived from the telomeric P element.

In the C1 population of Drosophila melanogaster of moderate effective size (≈500), which was genetically invariant in its origin, we studied the regeneration by spontaneous mutation of the genetic variance for two metric traits [abdominal (AB) and sternopleural (ST) bristle number] and that of the concealed mutation load for viability, together with their temporal stability, using alternative selection models based on mutational parameters estimated in the C1 genetic background. During generations 381–485 of mutation accumulation (MA), the additive variances of AB and ST approached the levels observed in standing laboratory populations, fluctuating around their expected equilibrium values under neutrality or under relatively weak causal stabilizing selection. This type of selection was required to simultaneously account for the observed additive variance in our population and for those previously reported in natural and laboratory populations, indicating that most mutations affecting bristle traits would only be subjected to weak selective constraints. Although gene action for bristles was essentially additive, transient situations occurred where inbreeding resulted in a depression of the mean and an increase of the additive variance. This was ascribed to the occasional segregation of mutations of large recessive effects. On the other hand, the observed non-lethal inbreeding depression for viability must be explained by the segregation of alleles of considerable and largely recessive deleterious effects, and the corresponding load concealed in the heterozygous condition was found to be temporally stable, as expected from tighter constraints imposed by natural selection.

In order to document further the phenomena of variance in reproductive success in natural populations of the European flat oyster Ostrea edulis, two complementary studies based on natural and experimental populations were conducted. The first part of this work was focused on paternity analyses using a set of four microsatellite markers for larvae collected from 13 brooding females sampled in Quiberon Bay (Brittany, France). The number of individuals contributing as the male parent to each progeny assay was highly variable, ranging from 2 to more than 40. Moreover, paternal contributions showed a much skewed distribution, with some males contributing to 50–100% of the progeny assay. The second part of this work consisted of the analysis of six successive cohorts experimentally produced from an acclimated broodstock (62 wild oysters sampled in the Quiberon Bay). Allelic richness was significantly higher in the adult population than in the temporal cohorts collected. Genetic differentiation (Fst estimates) was computed for each pair of samples and all significant values ranged from 0·7 to 11·9%. A limited effective number of breeders (generally below 25) was estimated in the six temporal cohorts. The study gives first indications of the high variance in reproductive success as well as a reduced effective size, not only under experimental conditions but also in the wild. Surprisingly, the pool of the successive cohorts, based on the low number of loci used, appeared to depict a random and representative set of alleles of the progenitor population, indicating that the detection of patterns of temporal genetic differentiation at a local scale most likely depends on the sampling window.

We proposed hierarchical Poisson and binomial models for mapping multiple interacting quantitative trait loci (QTLs) for count traits in experimental crosses. We applied our methods to two counted reproductive traits, live fetuses (LF) and dead fetuses (DF) at 17 days gestation, in an F2 female mouse population. We treated observed number of corpora lutea (ovulation rate) as the baseline and the total trials in our Poisson and binomial models, respectively. We detected more than 10 QTLs for LF and DF, most having epistatic and pleiotropic effects. The epistatic effects were larger, involved more QTLs, and explained a larger proportion of phenotypic variance than the main effects. Our analyses revealed a complex network of multiple interacting QTLs for the reproductive traits, and increase our understanding of the genetic architecture of reproductive characters. The proposed statistical models and methods provide valuable tools for detecting multiple interacting QTLs for complex count phenotypes.

We analysed the family linkage data obtained from short tandem repeat (STR) genotyping of 212 unrelated Indian families having a single Down syndrome (DS) baby each, in order to explore the incidence and aetiology of this human aneuploidy in our cohort. The estimated values of maternal meiotic I and meiotic II non-disjunction (NDJ) errors of chromosome 21 (Ch 21) were ~78 and ~22%, respectively. Within the paternal outcome group, about 47 and 53% were accounted for NDJ at meiosis I and meiosis II, respectively. We estimated only ~2% post-zygotic mitotic errors. The comparison of average age of conception between controls and DS-bearing mothers revealed a significant difference (P<0·001) with DS-bearing women were on an average older than controls and meiotic II non-disjoined mothers were oldest among meiotic outcome groups. Our linkage analysis suggested an overall reduction in recombination by more than 50% on meiotic I non-disjoined maternal Ch 21 with error prone to susceptible chiasma formation within the ~5·1 kbp segment near the telomeric end. We stratified meiotic I non-disjoined women in three age groups, viz. young (⩽28 years), middle (29–34 years) and old (⩾35 years) and found linear decrease in the frequency of achiasmate meiosis from the young to the old group. In contrary, a linear increase in the multiple chiasma frequency from the young to the old group was observed. Considering these results together, we propose that the risk factors for Ch 21 NDJ are of two types, one being ‘maternal age-independent’ and the other being ‘maternal age-dependent’. Moreover, a comparison of our present Indian dataset with that of other published data of ethnically different populations suggested that the genetics that underlies the NDJ of Ch 21 is probably universal irrespective of racial difference across human populations. The present study is the first population-based report on any DS cohort from the Indian subcontinent and our work will help future workers in understanding better the aetiology of this birth defect.

The genus Drosophila is diverse and heterogeneous and contains a large number of easy-to-rear species, so it is an attractive subject for comparative studies. The ability to perform such studies is currently compromised by the lack of a comprehensive phylogeny for Drosophila and related genera. The genus Drosophila as currently defined is known to be paraphyletic with respect to several other genera, but considerable uncertainty remains about other aspects of the phylogeny. Here, we estimate a phylogeny for 176 drosophilid (12 genera) and four non-drosophilid species, using gene sequences for up to 13 different genes per species (average: 4333 bp, five genes per species). This is the most extensive set of molecular data on drosophilids yet analysed. Phylogenetic analyses were conducted with maximum-likelihood (ML) and Bayesian approaches. Our analysis confirms that the genus Drosophila is paraphyletic with 100% support in the Bayesian analysis and 90% bootstrap support in the ML analysis. The subgenus Sophophora, which includes Drosophila melanogaster, is the sister clade of all the other subgenera as well as of most species of six other genera. This sister clade contains two large, well-supported subclades. The first subclade contains the Hawaiian Drosophila, the genus Scaptomyza, and the virilis-repleta radiation. The second contains the immigrans-tripunctata radiation as well as the genera Hirtodrosophila (except Hirtodrosophila duncani), Mycodrosophila, Zaprionus and Liodrosophila. We argue that these results support a taxonomic revision of the genus Drosophila.

A two-step procedure is presented for analysis of θ (FST) statistics obtained for a battery of loci, which eventually leads to a clustered structure of values. The first step uses a simple Bayesian model for drawing samples from posterior distributions of θ-parameters, but without constructing Markov chains. This step assigns a weakly informative prior to allelic frequencies and does not make any assumptions about evolutionary models. The second step regards samples from these posterior distributions as ‘data’ and fits a sequence of finite mixture models, with the aim of identifying clusters of θ-statistics. Hopefully, these would reflect different types of processes and would assist in interpreting results. Procedures are illustrated with hypothetical data, and with published allelic frequency data for type II diabetes in three human populations, and for 12 isozyme loci in 12 populations of the argan tree in Morocco.

The expression of behaviours is influenced by many segregating genes. Behaviours are, therefore, complex traits. They have, however, unique characteristics that set them apart from physiological and morphological quantitative traits. First, behaviours are the ultimate expression of the nervous system. This means that understanding the genetic underpinnings of behaviours requires a neurobiological context, i.e. an understanding of the genes–brain–behaviour axis. In other words, how do ensembles of genes empower specific neural circuits to drive behaviours? Second, behaviours represent the interface between an organism and its environment. Thus, environmental effects are likely to make substantial contributions to determining behavioural outputs and genotype-by-environment interactions are expected to be prominent. It is important to differentiate between genes that contribute to the manifestation of the behavioural phenotype and genes that contribute to phenotypic variation in behaviour. The former are identified by classical mutagenesis experiments, whereas the latter can be detected through quantitative genetic approaches. Genes that contribute to phenotypic variation in behaviour harbour polymorphisms that provide the substrates for evolution. This review focuses on olfactory behaviour in Drosophila with the goal to illustrate how fundamental insights derived from studies on chemosensation can be applied to a wide range of behavioural phenotypes.

Historical information can be used, in addition to pedigree, traits and genotypes, to map quantitative trait locus (QTL) in general populations via maximum likelihood estimation of variance components. This analysis is known as linkage disequilibrium (LD) and linkage mapping, because it exploits both linkage in families and LD at the population level. The search for QTL in the wild population of Soay sheep on St. Kilda is a proof of principle. We analysed the data from a previous study and confirmed some of the QTLs reported. The most striking result was the confirmation of a QTL affecting birth weight that had been reported using association tests but not when using linkage-based analyses.

Isolated founder populations which exhibit great genetic and environmental homogeneity provide an attractive setting for the study of quantitative traits (QTs). Geneticists have repeatedly turned to population isolates and the past successes have prompted increased interest among medical researchers. We studied nine small isolated villages of a secluded area of Sardinia (Ogliastra), all of them characterized by a few founders, high endogamy rates, slow population expansion and a distinct genetic makeup. Anthropometric and blood parameters, 43 QTs in all, were analysed in about 9000 voluntary subjects for whom extended genealogical information was available. We explored the distribution and examined mean differences of each trait among villages by analysis of variance (ANOVA). A heritability analysis with the variance component (VC) method was performed. Results show significant differences in the distribution of most traits between groups of villages located in two distinct geographical areas already identified by a previous population structure analysis, thus supporting the existence of differentiation among sub-populations in the same region. Heritability estimates range between 30 and 89%, demonstrating that genetic effects substantially contribute to phenotypic variation of all investigated traits and that this population provides excellent research conditions for gene-mapping projects. Results suggest that history, geographic location and population structure may have influenced the genetic and phenotypic features of these isolates. Our findings may be useful for the ongoing linkage and association studies in these isolates and suggest that a thorough characterization of population is valuable to better identify genes or variants that may be rare in the population at large and peculiar to single villages.

Human gene expression profiles have emerged as an effective model system for the dissection of quantitative genetic traits. Peripheral blood and transformed lymphoblasts are particularly attractive for their ready availability and repeatability, respectively, and the advent of relatively inexpensive genotyping and microarray analysis technologies has facilitated genome-wide association for transcript abundance in numerous settings. Thousands of genes have been shown to harbour regulatory polymorphisms that have large local effects on transcription, explaining 20% or more of the variance in many cases, but the focus on such results obscures the reality that the vast majority of the genetic component of transcriptional variance remains to be ascertained. This mini-review surveys the inferences derived from genome-wide association studies (GWAS) for gene expression to date, and discusses some of the issues we face in finding the remainder of the heritability and understanding how environmental and genetic regulatory factors orchestrate the highly structured architecture of transcriptional variation.

Inbreeding depression has important implications for a wide range of biological phenomena, such as inbreeding avoidance, the evolution and maintenance of sexual systems and extinction rates of small populations. Previous investigations have asked how inbreeding depression evolves in single and subdivided populations through the fixation of deleterious mutations as a result of drift, as well as through the expression of deleterious mutations segregating in a population. These studies have focused on the effects of mutation and selection at single loci, or at unlinked loci. Here, we used simulations to investigate the evolution of genetic load and inbreeding depression due to multiple partially linked loci in metapopulations. Our results indicate that the effect of linkage depends largely on the kinds of deleterious alleles involved. For weakly deleterious and partially recessive mutations, the speed of mutation accumulation at segregating loci in a random-mating subdivided population of a given structure tends to be retarded by increased recombination between adjacent loci – although the highest numbers of fixation of slightly recessive mutant alleles were for low but finite recombination rates. Although linkage had a relatively minor effect on the evolution of metapopulations unless very low values of recombination were assumed, close linkage between adjacent loci tended to enhance population structure and population turnover. Finally, within-deme inbreeding depression, between-deme inbreeding depression and heterosis generally increased with decreased recombination rates. Moreover, increased selfing reduced the effective amount of recombination, and hence the effects of tight linkage on metapopulation genetic structure were decreased with increasing selfing. In contrast, linkage had little effect on the fate of lethal and highly recessive alleles. We compare our simulation results with predictions made by models that ignore the complexities of recombination.

Hu & Xu (2008) developed a statistical method for computing the statistical power for detecting a quantitative trait locus (QTL) located in a marker interval. Their method is based on the regression interval mapping method and allows experimenters to effectively investigate the power for detecting a QTL in a population. This paper continues to work on the power analysis of separating multiple-linked QTLs. We propose simple formulae to calculate the power of separating closely linked QTLs located in marker intervals. The proposed formulae are simple functions of information numbers, variance inflation factors and genetic parameters of a statistical model in a population. Both regression and maximum likelihood interval mappings suitable for detecting QTL in the marker intervals are considered. In addition, the issue of separating linked QTLs in the progeny populations from an F2 subject to further self and/or random mating is also touched upon. One of the primary keys to our approach is to derive the genotypic distributions of three and four loci for evaluating the correlation structures between pairwise unobservable QTLs in the model across populations. The proposed formulae allow us to predict the power of separation when several factors, such as sample sizes, sizes and directions of QTL effects, distances between QTLs, interval sizes and relative QTL positions in the intervals, are considered together at a time in different experimental populations. Numerical justifications and Monte Carlo simulations were provided for confirmation and illustration.

Increasingly researchers are conducting quantitative trait locus (QTL) mapping in metabolomics and proteomics studies. These data often are distributed as a point-mass mixture, consisting of a spike at zero in combination with continuous non-negative measurements. Composite interval mapping (CIM) is a common method used to map QTL that has been developed only for normally distributed or binary data. Here we propose a two-part CIM method for identifying QTLs when the phenotype is distributed as a point-mass mixture. We compare our new method with existing normal and binary CIM methods through an analysis of metabolomics data from Arabidopsis thaliana. We then conduct a simulation study to further understand the power and error rate of our two-part CIM method relative to normal and binary CIM methods. Our results show that the two-part CIM has greater power and a lower false positive rate than the other methods when a continuous phenotype is measured with many zero observations.