Variance components models for gene-environment interaction in twin analysis.

Gene-environment interaction is likely to be a common and important source of variation for complex behavioral traits. Often conceptualized as the genetic control of sensitivity to the environment, it can be incorporated in variance components twin analyses by partitioning genetic effects into a mean part, which is independent of the environment, and a part that is a linear function of the environment. The model allows for one or more environmental moderator variables (that possibly interact with each other) that may i). be continuous or binary ii). differ between twins within a pair iii). interact with residual environmental as well as genetic effects iv) have nonlinear moderating properties v). show scalar (different magnitudes) or qualitative (different genes) interactions vi). be correlated with genetic effects acting upon the trait, to allow for a test of gene-environment interaction in the presence of gene-environment correlation. Aspects and applications of a class of models are explored by simulation, in the context of both individual differences twin analysis and, in a companion paper (Purcell & Sham, 2002) sibpair quantitative trait locus linkage analysis. As well as elucidating environmental pathways, consideration of gene-environment interaction in quantitative and molecular studies will potentially direct and enhance gene-mapping efforts.     

Varying coefficient model for gene-environment interaction: a non-linear look

MOTIVATION: The genetic basis of complex traits often involves the function of multiple genetic factors, their interactions and the interaction between the genetic and environmental factors. Gene-environment (G×E) interaction is considered pivotal in determining trait variations and susceptibility of many genetic disorders such as neurodegenerative diseases or mental disorders. Regression-based methods assuming a linear relationship between a disease response and the genetic and environmental factors as well as their interaction is the commonly used approach in detecting G×E interaction. The linearity assumption, however, could be easily violated due to non-linear genetic penetrance which induces non-linear G×E interaction. RESULTS: In this work, we propose to relax the linear G×E assumption and allow for non-linear G×E interaction under a varying coefficient model framework. We propose to estimate the varying coefficients with regression spline technique. The model allows one to assess the non-linear penetrance of a genetic variant under different environmental stimuli, therefore help us to gain novel insights into the etiology of a complex disease. Several statistical tests are proposed for a complete dissection of G×E interaction. A wild bootstrap method is adopted to assess the statistical significance. Both simulation and real data analysis demonstrate the power and utility of the proposed method. Our method provides a powerful and testable framework for assessing non-linear G×E interaction.     

"Missing" G x E Variation Controls Flowering Time in Arabidopsis thaliana

Understanding how genetic variation interacts with the environment is essential for understanding adaptation. In particular, the life cycle of plants is tightly coordinated with local environmental signals through complex interactions with the genetic variation (G x E). The mechanistic basis for G x E is almost completely unknown. We collected flowering time data for 173 natural inbred lines of Arabidopsis thaliana from Sweden under two growth temperatures (10°C and 16°C), and observed massive G x E variation. To identify the genetic polymorphisms underlying this variation, we conducted genome-wide scans using both SNPs and local variance components. The SNP-based scan identified several variants that had common effects in both environments, but found no trace of G x E effects, whereas the scan using local variance components found both. Furthermore, the G x E effects appears to be concentrated in a small fraction of the genome (0.5%). Our conclusion is that G x E effects in this study are mostly due to large numbers of allele or haplotypes at a small number of loci, many of which correspond to previously identified flowering time genes.     

Genotype by environment interactions in viability and developmental time in populations of cactophilic Drosophila

The genetic and ecological basis of viability and developmental time differences between Drosophila buzzatii and D. koepferae were analysed using the isofemale line technique. Several isofemale lines were sampled from pairs of allopatric/sympatric populations of each species. Flies were reared in media prepared with decaying tissues of two of the main natural cactus hosts of each species. This experimental design enabled us to evaluate the relative contribution of phenotypic plasticity, genetic variation and genotype by environment interaction (G x E) to total phenotypic variation for two fitness traits, viability and developmental time. Our results revealed significant G x E in both traits, suggesting that the maintenance of genetic variation can be explained, at least in part, by diversifying selection in different patches of a heterogeneous environment in both species. However, the relative importance of the factors involved in the G x E varied between traits and populations within species. For viability, the G x E can be mainly attributed to changes in the rank order of lines across cacti. However, the pattern was different for developmental time. In D. buzzatii the G x E can be mainly accounted for by changes in among line variance across cacti, whereas changes in the rank order of lines across cacti was the main component in D. koepferae. These dissimilar patterns of variation between traits and species suggest that the evolutionary forces shaping genetic variation for developmental time and viability vary between populations within species and between species.     

Inheritance of human finger and palm dermatoglyphic characteristics]

The degree of genetic determination of 25 quantitative dermatoglyphic characteristics has been studied on family: twin material: 45 pairs of MZ and 75 single-sex DZ twins; and 53 single-sex "parent-child" pairs. Approximating formulae were used to estimate main components of phenotypic variance due to additive interaction of genetic factors, to non-linear effects (intralocus dominance) and to the effect of total-familiar and random environmental factors. All the finger dermatoglyphic characteristics studied had a high degree of genetic determination (G greater than 0,80), and for most of them the contribution into the large variance of intralocus dominance effects was comparable with that of additive gene interaction, included in the determination of these characters. There are some palm dermatoglyphic characteristics ("ad" distance "cd" comb counting, "bad", "adt" and "cda" angles), which degree of genetic determination is low (G less than 0,35). At least ten quantitative finger and palm dermatogliphic characteristics with a high degree of genetic determination can be used for special studies in frames of multidimentional genetical analysis, including determination of twin zygosity type. Earlier described "indices" (using twin data) of relative role of genetic and environment factors in the determination of populational variability of quantitative characters are considered. None of them is shown to be a reliable estimate of the coefficient of genetic character determination. The use of these indices in practical studies can result in wrong conclusions on the degree and the character of genetic determination of quantitative characters.     

Genotype-by-genotype interactions modified by a third species in a plant-insect system

Community genetics examines how genotypic variation within a species influences the associated ecological community. The inclusion of additional environmental and genotypic factors is a natural extension of the current community genetics framework. However, the extent to which the presence of and genetic variation in associated species influences interspecific interactions (i.e., genotype x genotype x environment [G x G x E] interactions) has been largely ignored. We used a community genetics approach to study the interaction of barley and aphids in the absence and presence of rhizosphere bacteria. We designed a matrix of aphid genotype and barley genotype combinations and found a significant G x G x E interaction, indicating that the barley-aphid interaction is dependent on the genotypes of the interacting species as well as the biotic environment. We discuss the consequences of the strong G x G x E interaction found in our study in relation to its impact on the study of species interactions in a community context.     

Host shifts and the beginning of signal divergence

Divergence between populations adapting to different environments may be facilitated when the populations differ in their sexual traits. We tested whether colonizing a novel environment may, through phenotypic plasticity, change sexual traits in a way that could alter the dynamics of sexual selection. This hypothesis has two components: changes in mean phenotypes across environments, and changes in the genetic background of the phenotypes that are produced -- or genotype x environment interaction (G x E). We simulated colonization of a novel environment and tested its effect on the mating signals of a member of the Enchenopa binotata species complex of treehoppers (Hemiptera: Membracidae), a clade that has diverged in a process involving host plant shifts and signal diversification. We found substantial genetic variation and G x E in most signal traits measured, with little or no change in mean signal phenotypes. We suggest that the expression of extant genetic variation across old and novel environments can initiate signal divergence.     

Direct and indirect genetic effects on reproductive investment in a grasshopper

A fundamental part of the quantitative genetic theory deals with the partitioning of the phenotypic variance into additive genetic and environmental components. During interaction with conspecifics, the interaction partner becomes a part of the environment from the perspective of the focal individual. If the interaction effects have a genetic basis, they are called indirect genetic effects (IGEs) and can evolve along with direct genetic effects. Sexual reproduction is a classic context where potential conflict between males and females can arise from trade‐offs between current and future investments. We studied five female fecundity traits, egg length and number, egg pod length and number and latency to first egg pod, and estimated the direct and IGEs using a half‐sib breeding design in the grasshopper Chorthippus biguttulus. We found that the male IGEs were an order of magnitude lower than the direct genetic effects and were not significantly different from zero. However, there was some indication that IGEs were larger shortly after mating, consistent with the idea that IGEs fade with time after interaction. Female direct heritabilities were moderate to low. Simulation shows that the variance component estimates can appear larger with less data, calling for care when interpreting variance components estimated with low power. Our results illustrate that the contribution of male IGEs is overall low on the phenotypic variance of female fecundity traits. Thus, even in the relevant context of sexual conflict, the influence of male IGEs on the evolutionary trajectory of female reproductive traits is likely to be small.     

Integration of statistical and physiological analyses of adaptation of near-isogenic barley lines

Seven near-isogenic barley lines, differing for three independent mutant genes, were grown in 15 environments in Spain. Genotype x environment interaction (G x E) for grain yield was examined with the Additive Main Effects and Multiplicative interaction (AMMI) model. The results of this statistical analysis of multilocation yield-data were compared with a morpho-physiological characterization of the lines at two sites (Molina-Cano et al. 1990). The first two principal component axes from the AMMI analysis were strongly associated with the morpho-physiological characters. The independent but parallel discrimination among genotypes reflects genetic differences and highlights the power of the AMMI analysis as a tool to investigate G x E. Characters which appear to be positively associated with yield in the germplasm under study could be identified for some environments.     

Genotype x environment interaction in QTL analysis of an intervarietal almond cross by means of genetic markers

Besides QTL location and the estimation of gene effects, QTL analysis based on genetic markers could be used to comprehensively investigate quantitative trait-related phenomena such as pleiotropy, gene interactions, heterosis, and genotype-by-environment interaction (G x E). Given that the G x E interaction is of great relevance in tree improvement, the objective of the research presented here was to study the effect of years on QTL detection for 15 quantitative traits by means of isozymatic markers in a large progeny group of an intervarietal cross of almond. At least 17 putative QTLs were detected, 3 of which had alleles with opposite effects to those predicted from the parental genotypes. Only 3 QTLs behaved homogeneously over the years. Three possible causes are discussed in relation to this lack of stability: the power of the test statistic being used, the low contribution of the QTL to the genetic variation of the trait, and a differential gene expression dependent on the year (G x E). Most cases showing lack of stability involved traits whose heritability estimates change drastically from year to year and/or whose correlation coefficients between years are low, suggesting the presence of G x E as the most likely cause. A marker-assisted selection scheme to improve late flowering and short flowering duration is suggested for an early and wide screening of the progeny.     

Gene-environment interaction effects on behavioral variation and risk of complex disorders: the example of alcoholism and other psychiatric disorders.

There have been few replicated examples of genotype x environment interaction effects on behavioral variation or risk of psychiatric disorder. We review some of the factors that have made detection of genotype x environment interaction effects difficult, and show how genotype x shared environment interaction (GxSE) effects are commonly confounded with genetic parameters in data from twin pairs reared together. Historic data on twin pairs reared apart can in principle be used to estimate such GxSE effects, but have rarely been used for this purpose. We illustrate this using previously published data from the Swedish Adoption Twin Study of Aging (SATSA), which suggest that GxSE effects could account for as much as 25% of the total variance in risk of becoming a regular smoker. Since few separated twin pairs will be available for study in the future, we also consider methods for modifying variance components linkage analysis to allow for environmental interactions with linked loci.     

非等试验设计胚乳品质性状的遗传分析方法

根据朱军(1996)提出的包括基因型×环境互作的胚乳品质性状三倍体遗传模型,运用蒙特卡罗模拟证明,以混合线性模型统计分析的MINQUE法,对非等试验设计获得的实验数据进行数量遗传分析是可行的.蒙特卡罗模拟结果表明在样本群体大小基本一致的条件下,采用相等试验设计或非等试验设计所估算的遗传参数的偏差(Blas)和功效值(Power)没有明显差异,表明以非等试验设计获得的非平衡数据也可用来进行遗传分析,估算上述遗传模型中的各项遗传方差分量和协方差分量,并且可以采用朱军(1993)提出的AUP法来预测遗传模型中的各项遗传效应值.     

Heritable Variation for Sex Ratio under Environmental Sex Determination in the Common Snapping Turtle (Chelydra Serpentina)

The magnitude of quantitative genetic variation for primary sex ratio was measured in families extracted from a natural population of the common snapping turtle (Chelydra serpentina), which possesses temperature-dependent sex determination (TSD). Eggs were incubated at three temperatures that produced mixed sex ratios. This experimental design provided estimates of the heritability of sex ratio in multiple environments and a test of the hypothesis that genotype x environment (G x E) interactions may be maintaining genetic variation for sex ratio in this population of C. serpentina. Substantial quantitative genetic variation for primary sex ratio was detected in all experimental treatments. These results in conjunction with the occurrence of TSD in this species provide support for three critical assumptions of Fisher's theory for the microevolution of sex ratio. There were statistically significant effects of family and incubation temperature on sex ratio, but no significant interaction was observed. Estimates of the genetic correlations of sex ratio across environments were highly positive and essentially indistinguishable from + 1. These latter two findings suggest that G x E interaction is not the mechanism maintaining genetic variation for sex ratio in this system. Finally, although substantial heritable variation exists for primary sex ratio of C. serpentina under constant temperatures, estimates of the effective heritability of primary sex ratio in nature are approximately an order of magnitude smaller. Small effective heritability and a long generation time in C. serpentina imply that evolution of sex ratios would be slow even in response to strong selection by, among other potential agents, any rapid and/or substantial shifts in local temperatures, including those produced by changes in the global climate.     

数量性状的核质互作遗传效应分析:二倍体植株遗传模型

提出了能分析二倍体植株数量性状核质互作效应的遗传模型,该模型把控制数量性状总的遗传效应分为核效应、质效应和核质互作效应,以及它们分别与环境作用的效应。其中,核质互作效应可进一步分解为加性核质互作与显性核质互作。基于平衡与非平衡两种双列杂交试验设计,蒙特卡罗模拟结果表明:采用混合线性模型方法进行统计分析,可以有效地估计各项遗传效应值及其方差分量。此外,运用该模型对棉花的4个数量性状(单株铃数、衣分、2.5%跨长和麦克隆值)进行了遗传分析。     

Quantitative trait locus mapping using human pedigrees

In the past decade phenomenal progress has been made in molecular and statistical genetic methods for localizing quantitative trait loci. Because of these advances, we can anticipate a long period of active genetic research in which the genes influencing human quantitative variability will be mapped and their effects accurately evaluated. Here, we review the current state of the science in statistical genetic methods for quantitative trait linkage analysis. In particular, we detail a variance component-based framework for localizing quantitative trait loci and for accurately estimating their relative effect sizes. Attention is paid to the optimal design of human family studies for localizing genes of small to moderate effect. In addition, methods and strategies are described for dealing with the most important complications of quantitative variation, including the assessment of genotype x environment interaction and epistasis.     

Phenotypic plasticity of growth trajectory and ontogenic allometry in response to density for eucalyptus hybrid clones and families

BACKGROUND: and Aims Response to density is a crucial aspect of the ecology of trees in forests and plantations. Few studies have investigated the genetics of plasticity in response to density for growth traits such as height and circumference through development. METHODS: Two experiments were carried out in the field, the first with full-sib families of Eucalyptus urophylla x E. grandis hybrids, and the second with clones of E. tereticornis x E. grandis hybrids planted across a range of densities (625, 1111 and 2500 trees ha-1). Height, circumference and stem taper were measured through development in both experiments. Variance components were estimated and a repeated measure approach for plasticity and three different methods were used to compare the variance-covariance matrix across densities. KEY RESULTS: Genetic variance was significantly different from zero but the density x genotype interaction was significant only for clone experiments at the adult stage. Significant plasticity for three traits in both experiments was found. In the clone experiments, a significant clone x time x density interaction was found, suggesting that plasticity for growth and stem form is under genetic control. In both experiments, density did not affect environmental correlation, which remained high throughout tree development. The impact of density on genetic correlation was marked in the clone experiment, with a reduced value at lower density, but was not observed in the family trial. The differences between clones and family are mainly explained by the distribution of genetic variation within and among genotypes. CONCLUSIONS: The results suggest that plasticity for growth traits and form of tropical Eucalyptus species is under genetic control and that the environment changes genetic co-variation through ontogeny. The findings confirm that a tree population with a narrow genetic basis (represented by clones) is sensitive to a changing environment, whereas a population with a broader genetic basis (full-sib family here) exhibits a more stable reaction.     

Marker-based quantitative genetics in the wild?: the heritability and genetic correlation of chemical defenses in eucalyptus

Marker-based methods for estimating heritability and genetic correlation in the wild have attracted interest because traditional methods may be impractical or introduce bias via G x E effects, mating system variation, and sampling effects. However, they have not been widely used, especially in plants. A regression-based approach, which uses a continuous measure of genetic relatedness, promises to be particularly appropriate for use in plants with mixed-mating systems and overlapping generations. Using this method, we found significant narrow-sense heritability of foliar defense chemicals in a natural population of Eucalyptus melliodora. We also demonstrated a genetic basis for the phenotypic correlation underlying an ecological example of conditioned flavor aversion involving different biosynthetic pathways. Our results revealed that heritability estimates depend on the spatial scale of the analysis in a way that offers insight into the distribution of genetic and environmental variance. This study is the first to successfully use a marker-based method to measure quantitative genetic parameters in a tree. We suggest that this method will prove to be a useful tool in other studies and offer some recommendations for future applications of the method.     

Quantitative genetic study on sexual difference in emigration behavior of Drosophila melanogaster in a natural population.

A quantitative genetic analysis was conducted on emigration response behavior using 140 second chromosome lines of Drosophila melanogaster. Fourteen sets of 5 x 5 partial diallel cross experiments were made in the parental generation. The emigration activity per batch of 50 male and 50 female F1 progeny was scored with Sakai's population system. Sexual difference did not appear in the emigration activity in these experiments. A significant genotype x sex x set interaction was detected. The genetic variance components of emigration activity differed between sexes: In males, additive genetic variance of emigration activity was 0.0497 +/- 0.0092 and dominance variance, 0.0018 +/- 0.0046; in females, additive, 0.0373 +/- 0.0076 and dominance, 0.0169 +/- 0.0044. Additive genetic correlation between sexes for the emigration activity was 0.685 +/- 0.150, deviating significantly from unity. These results suggested that the genes affecting emigration activity would operate differently between sexes of D. melanogaster in natural populations.     

Naturally segregating loci exhibit epistasis for fitness

The extent to which gene interaction or epistasis contributes to fitness variation within populations remains poorly understood, despite its importance to a myriad of evolutionary questions. Here, we report a multi-year field study estimating fitness of Mimulus guttatus genetic lines in which pairs of naturally segregating loci exist in an otherwise uniform background. An allele at QTL x5b—a locus originally mapped for its effect on flower size—positively affects survival if combined with one genotype at quantitative trait locus x10a (aa) but has negative effects when combined with the other genotypes (Aa and AA). The viability differences between genotypes parallel phenotypic differences for the time and node at which a plant flowers. Viability is negatively correlated with fecundity across genotypes, indicating antagonistic pleiotropy for fitness components. This trade-off reduces the genetic variance for total fitness relative to the individual fitness components and thus may serve to maintain variation. Additionally, we find that the effects of each locus and their interaction often vary with the environment.     

Analysis of genetic effects of nuclear–cytoplasmic interaction on quantitative traits: Genetic models for seed traits of plants

Two Genetic models (an embryo model and an endosperm model) were proposed for analyzing genetic effects of nuclear genes, cytoplasmic genes, maternal genes, and nuclear–cytoplasmic interaction (NCI) as well as their genotype by environment interaction for quantitative traits of plant seed. In these models, the NCI effects were partitioned into direct additive and dominance NCI components. Mixed linear model approaches were employed for statistical analysis. For both balanced and unbalanced diallel cross designs, Monte Carlo simulations were conducted to evaluate unbiasedness and precision of estimated variance components of these models. The results showed that the proposed methods work well. Random genetic effects were predicted with an adjusted unbiased prediction method. Seed traits (protein content and oil content) of Upland cotton (Gossypium hirsutum L.) were analyzed as worked examples to demonstrate the use of the models.