Age-dependent genetic variance in a life-history trait in the mute swan

Genetic variance in characters under natural selection in natural populations determines the way those populations respond to that selection. Whether populations show temporal and/or spatial constancy in patterns of genetic variance and covariance is regularly considered, as this will determine whether selection responses are constant over space and time. Much less often considered is whether characters show differing amounts of genetic variance over the life-history of individuals. Such age-specific variation, if present, has important potential consequences for the force of natural selection and for understanding the causes of variation in quantitative characters. Using data from a long-term study of the mute swan Cygnus olor, we report the partitioning of phenotypic variance in timing of breeding (subject to strong natural selection) into component parts over 12 different age classes. We show that the additive genetic variance and heritability of this trait are strongly age-dependent, with higher additive genetic variance present in young and, particularly, old birds, but little evidence of any genetic variance for birds of intermediate ages. These results demonstrate that age can have a very important influence on the components of variation of characters in natural populations, and consequently that separate age classes cannot be assumed to be equivalent, either with respect to their evolutionary potential or response.     

Evolution of additive and nonadditive genetic variance in development time along a cline in Drosophila serrata

Abstract. Latitudinal clines provide natural systems that may allow the effect of natural selection on the genetic variance to be determined. Ten clinal populations of Drosophila serrata collected from the eastern coast of Australia were used to examine clinal patterns in the trait mean and genetic variance of the life-history trait egg-to-adult development time. Development time significantly lengthened from tropical areas to temperate areas. The additive genetic variance for development time in each population was not associated with latitude but was associated with the population mean development time. Additive genetic variance tended to be larger in populations with more extreme development times and appeared to be consistent with allele frequency change. In contrast, the nonadditive genetic variance was not associated with the population mean but was associated with latitude. Levels of nonadditive genetic variance were greatest in the region of the cline where the gradient in the change in mean was greatest, consistent with Barton's (1999) conjecture that the generation of linkage disequilibrium may become an important component of the genetic variance in systems with a spatially varying optimum.     

Estimating genetic variance contributed by a quantitative trait locus: A random model approach

Detecting quantitative trait loci (QTL) and estimating QTL variances (represented by the squared QTL effects) are two main goals of QTL mapping and genome-wide association studies (GWAS). However, there are issues associated with estimated QTL variances and such issues have not attracted much attention from the QTL mapping community. Estimated QTL variances are usually biased upwards due to estimation being associated with significance tests. The phenomenon is called the Beavis effect. However, estimated variances of QTL without significance tests can also be biased upwards, which cannot be explained by the Beavis effect; rather, this bias is due to the fact that QTL variances are often estimated as the squares of the estimated QTL effects. The parameters are the QTL effects and the estimated QTL variances are obtained by squaring the estimated QTL effects. This square transformation failed to incorporate the errors of estimated QTL effects into the transformation. The consequence is biases in estimated QTL variances. To correct the biases, we can either reformulate the QTL model by treating the QTL effect as random and directly estimate the QTL variance (as a variance component) or adjust the bias by taking into account the error of the estimated QTL effect. A moment method of estimation has been proposed to correct the bias. The method has been validated via Monte Carlo simulation studies. The method has been applied to QTL mapping for the 10-week-body-weight trait from an F₂ mouse population.     

Argentine population genetic structure: large variance in Amerindian contribution

Argentine population genetic structure was examined using a set of 78 ancestry informative markers (AIMs) to assess the contributions of European, Amerindian, and African ancestry in 94 individuals members of this population. Using the Bayesian clustering algorithm STRUCTURE, the mean European contribution was 78%, the Amerindian contribution was 19.4%, and the African contribution was 2.5%. Similar results were found using weighted least mean square method: European, 80.2%; Amerindian, 18.1%; and African, 1.7%. Consistent with previous studies the current results showed very few individuals (four of 94) with greater than 10% African admixture. Notably, when individual admixture was examined, the Amerindian and European admixture showed a very large variance and individual Amerindian contribution ranged from 1.5 to 84.5% in the 94 individual Argentine subjects. These results indicate that admixture must be considered when clinical epidemiology or case control genetic analyses are studied in this population. Moreover, the current study provides a set of informative SNPs that can be used to ascertain or control for this potentially hidden stratification. In addition, the large variance in admixture proportions in individual Argentine subjects shown by this study suggests that this population is appropriate for future admixture mapping studies.     

Sexually antagonistic genetic variance for fitness in an ancestral and a novel environment

The intersex genetic correlation for fitness (rwfm), a standardized measure of the degree to which male and female fitness covary genetically, has consequences for important evolutionary processes, but few estimates are available and none have explored how it changes with environment. Using a half-sibling breeding design, we estimated the genetic (co)variance matrix (G) for male and female fitness, and the resulting rwfm, in Drosophila serrata. Our estimates were performed in two environments: the laboratory yeast food to which the population was well adapted and a novel corn food. The major axis of genetic variation for fitness in the two environments, accounting for 51.3 per cent of the total genetic variation, was significant and revealed a strong signal of sexual antagonism, loading negatively in both environments on males but positively on females. Consequently, estimates of rwfm were negative in both environments (−0.34 and −0.73, respectively), indicating that the majority of genetic variance segregating in this population has contrasting effects on male and female fitness. The possible strengthening of the negative rwfm in this novel environment may be a consequence of no history of selection for amelioration of sexual conflict. Additional studies from a diverse range of novel environments will be needed to determine the generality of this finding.     

Very low levels of direct additive genetic variance in fitness and fitness components in a red squirrel population

A trait must genetically correlate with fitness in order to evolve in response to natural selection, but theory suggests that strong directional selection should erode additive genetic variance in fitness and limit future evolutionary potential. Balancing selection has been proposed as a mechanism that could maintain genetic variance if fitness components trade off with one another and has been invoked to account for empirical observations of higher levels of additive genetic variance in fitness components than would be expected from mutation–selection balance. Here, we used a long‐term study of an individually marked population of North American red squirrels (Tamiasciurus hudsonicus) to look for evidence of (1) additive genetic variance in lifetime reproductive success and (2) fitness trade‐offs between fitness components, such as male and female fitness or fitness in high‐ and low‐resource environments. “Animal model” analyses of a multigenerational pedigree revealed modest maternal effects on fitness, but very low levels of additive genetic variance in lifetime reproductive success overall as well as fitness measures within each sex and environment. It therefore appears that there are very low levels of direct genetic variance in fitness and fitness components in red squirrels to facilitate contemporary adaptation in this population.     

A factor analysis of associations among self-reported immune related symptoms in a large twin sample.

We examined the cumulative prevalences of 22 symptoms thought to reflect immune system function reported in a questionnaire mailed to 7616 Australian twins. The associations between symptoms and demographic variables were expressed in terms of polychoric or polyserial correlations, and a principal components analysis performed. Factors representing underlying propensities respectively to allergic disease, various minor infections, diseases associated with aging such as arthritis, skin disease, and respiratory tract infection were extracted. Possible processes underlying these symptom clusters and the relative strengths and weaknesses of this type of analysis are discussed.     

Age at menarche in urban Argentinian girls: association with biological and socioeconomic factors

Age at menarche is regarded as a sensitive indicator of physical, biological, and psychosocial environment. The aim of this study was to determine the age at menarche and its association with biological and socioeconomic factors in girls from Santa Rosa (La Pampa, Argentina). An observational cross-sectional study was carried out on 1,221 schoolgirls aged 9-15 years. Menarche data were obtained by the status-quo method. Height, sitting height, weight, arm circumference, tricipital and subscapular skinfolds were measured. We also calculated body mass index, measures of body composition and proportions, and fat distribution. To assess socioeconomic factors, parents completed a self-administered questionnaire about their occupation and education, family size, household, and other family characteristics. The median age at menarche - estimated by the logit method--was 12.84 years (95% CI: 12.71, 12.97). Compared with their premenarcheal age peers, postmenarcheal girls had greater anthropometric dimensions through age 12. After this age, only height was higher in the latter group. Data were processed by fitting two logistic regressions, both including age. The first model included anthropometric variables and birth weight, while the second model included the socioeconomic variables. The significant variables derived from each model were incorporated into a new regression: height, sitting height ratio (first model), and maternal education (second model). These three variables remained significantly associated with menarche. The results suggest a relationship between linear growth and menarche and agree with those found in other populations where the advancement of menarche is associated with improved living conditions. In relatively uniform urban contexts, maternal education may be a good proxy for the standard of living.     

Estimation of genetic variance contributed by a quantitative trait locus: correcting the bias associated with significance tests

The Beavis effect in quantitative trait locus (QTL) mapping describes a phenomenon that the estimated effect size of a statistically significant QTL (measured by the QTL variance) is greater than the true effect size of the QTL if the sample size is not sufficiently large. This is a typical example of the Winners’ curse applied to molecular quantitative genetics. Theoretical evaluation and correction for the Winners’ curse have been studied for interval mapping. However, similar technologies have not been available for current models of QTL mapping and genome-wide association studies where a polygene is often included in the linear mixed models to control the genetic background effect. In this study, we developed the theory of the Beavis effect in a linear mixed model using a truncated noncentral Chi-square distribution. We equated the observed Wald test statistic of a significant QTL to the expectation of a truncated noncentral Chi-square distribution to obtain a bias-corrected estimate of the QTL variance. The results are validated from replicated Monte Carlo simulation experiments. We applied the new method to the grain width (GW) trait of a rice population consisting of 524 homozygous varieties with over 300 k single nucleotide polymorphism markers. Two loci were identified and the estimated QTL heritability were corrected for the Beavis effect. Bias correction for the larger QTL on chromosome 5 (GW5) with an estimated heritability of 12% did not change the QTL heritability due to the extremely large test score and estimated QTL effect. The smaller QTL on chromosome 9 (GW9) had an estimated QTL heritability of 9% reduced to 6% after the bias-correction.     

Tuberculosis as a complex trait: impact of genetic epidemiological study design

Several studies have suggested a role for human genetic risk factors in the susceptibility to developing tuberculosis (TB). However, results of these studies have been inconsistent, and one potential reason for these inconsistencies is variation in aspects of study design. Specifically, phenotype definitions and population genetic factors have varied dramatically. Since TB is a complex trait, there are many challenges in designing studies to assess appropriately human genetic risk factors for the development of TB as opposed to the acquisition of latent M. tuberculosis infection. In this review we summarize these important study design differences, with illustrations from the TB genetics literature. We cite specific examples of studies of the NRAMP1 (SLC11A1) gene and present Fisher??s combined p values for different stratifications of these studies to further illustrate the impact of study design differences. Finally, we provide suggestions for the design of future genetic epidemiological studies of TB.     

The genetic variance for multiple linked quantitative trait loci conditional on marker information in a crossed population

In the prediction of genetic values and quantitative trait loci (QTLs) mapping via the mixed model method incorporating marker information in animal populations, it is important to model the genetic variance for individuals with an arbitrary pedigree structure. In this study, for a crossed population originated from different genetic groups such as breeds or outbred strains, the variance of additive genetic values for multiple linked QTLs that are contained in a chromosome segment, especially the segregation variance, is investigated assuming the use of marker data. The variance for a finite number of QTLs in one chromosomal segment is first examined for the crossed population with the general pedigree. Then, applying the concept of the expectation of identity-by-descent proportion, an approximation to the mean of the conditional probabilities for the linked QTLs over all loci is obtained, and using it an expression for the variance in the case of an infinite number of linked QTLs marked by flanking markers is derived. It appears that the approach presented can be useful in the segment mapping using, and in the genetic evaluation of, crosses with general pedigrees in the population of concern. The calculation of the segregation variance through the current approach is illustrated numerically, using a small data-set.     

Colony shape as a genetic trait in the pattern-forming Bacillus mycoides

Background  

Bacillus mycoides Flügge, a Gram-positive, non-motile soil bacterium assigned to Bacillus cereus group, grows on agar as chains of cells linked end to end, forming radial filaments curving clock- or counter-clockwise (SIN or DX morphotypes). The molecular mechanism causing asymmetric curving is not known: our working hypothesis considers regulation of filamentous growth as the prerequisite for these morphotypes.     

Cancer as a complex genetic trait: tumor susceptibility in humans and mouse models

Cancer directly affects at least one-third of the human population, but the inherited genetic determinants of cancer risk remain largely unknown. Mouse models of human cancer are helping us to understand this disease as a complex genetic trait and thus to identify the multiple genetic variant alleles involved in pathways that affect individual cancer susceptibility.